Journal articles on the topic 'Mutual funds Classification Statistical methods'
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1
Homocianu, Daniel. "A Methodology of Discovering Comparable Models. The Case of Investing in Retirement Accounts when Considering Age, Main Residence and Education before 1989 vs. Globalization." Scientific Annals of Economics and Business 67, SI (2020): 19–31. http://dx.doi.org/10.47743/saeb-2020-0026.
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This paper provides a way to discover strong individual influences on investments in retirement accounts. Data are from SHARE-ERIC (Wave7). Principal residences in ex-communist countries or not and full-time education before 1989 served as filters. Two particular models with good classification accuracy resulted based on data mining, variable selection methods, and logistic regressions. A statistical script generated tables with comparable coefficients (average marginal effects). Common influences from the same financial category as the outcome emerged (having life insurance or ever investing in mutual funds or stocks). The younger respondents, those with computer skills or exposed to high stress, are more likely to invest in retirement accounts regardless of the presence of the communist heritage. Specific influences (personality traits and life experiences) also resulted despite the increasing globalization, which, in the case of people over a certain age, was not able to erase some behavioral differences reflected until today.
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Amin, Moch. "Performance Comparison of Islamic Mutual Funds with Conventional Mutual Funds." Jihbiz : jurnal ekonomi, keuangan dan perbankan syariah 3, no. 1 (January 22, 2019): 38–54. http://dx.doi.org/10.33379/jihbiz.v3i1.787.
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The purpose of this study is to determine whether or not there is a difference in mutual fund performance between sharia mutual funds and conventional mutual funds from 2016 to 2018. The data used is secondary data in the form of NVA report data of 34 mutual funds consisting of 16 sharia mutual funds and 18 conventional mutual funds. The data analysis method used is the Jensen Index, Sharpe index, Treynor Index, MM Index, and TT Index methods and uses the t-test to see whether there are differences in mutual fund performance. The results of this study conclude that quantitatively there is no difference in mutual fund performance between sharia mutual funds and conventional mutual funds. Likewise, the statistical test with the t-test shows that there is no difference in performance in terms of the Jensen Index, Sharpe index, Treynor Index, MM Index, and TT Index.
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Čomić, Dragan Ratko. "Forest Estates/Organisational Units Ranking Model - The MRG Model." South-east European forestry 10, no. 1 (March 22, 2019): 39–51. http://dx.doi.org/10.15177/seefor.19-03.
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Background and Purpose: The fact that new organizational concepts require comparison and ranking of some business entities, implies the analogy that, in forestry, ranking should create the basis for differentiation of Forest Estates (FE) (seen as profit centers) according to their capability to allocate funds from rent for the utilization of forests and forest land. In this sense, it was necessary to determine the basic criteria and variables, and then to create the model for FE ranking on the basis of ecological and production potentials, and business results (economic indicators). The main idea was to create a model that can be used primarily by forest owners (which are, in certain countries such as Bosnia and Herzegovina, Croatia, Serbia, and Montenegro, mainly governments) and by public forest enterprises. The proposed models may serve to all other scientific, professional, research and other institutions, as the starting point for further research and as suggestions for possible improvements of the proposed solutions. Materials and Methods: The research was carried out within the project "Differential rent in the Republic of Srpska forestry". Total sample for the survey was 44 interviewed parties, with 118 questionnaires filled in. The methods of classification, content analysis, desk research, analysis, synthesis and comparison were used. In the concrete application of the Forest Estates/Organisational Units Ranking Model (hereinafter MRG Model; Model rangiranja šumskih gazdinstava, in Bosnian), the following methods were used: brainstorming, focus groups, survey, desk research method, Pareto analysis, modelling and induction. The statistical methods used were descriptive statistics and rank correlation. By using these methods and by combining them, a new model for forest estates ranking was created. Different input data and variables that refer to economic and natural indicators were used for ranking, all in accordance with the values for areas for which the ranking was carried out. Results: The main results are used for defining and proposal of the new model for forests estates ranking, i.e. the MRG Model. This model includes the following steps: (1) Survey, (2) Selection and scoring of specific variables, (3) Determining the intervals for specific variables, (4) Ranking of forest estates, and (5) Validation and rank correlation. This paper presented the algorithm of implementation of specific steps within the MRG Model, together with all activities that need to be implemented in order to perform forest estates ranking. It is necessary to emphasize that forest estates ranking was performed in accordance with the following three ranks: (1) for all analyzed variables, (2) for economic variables, and (3) for natural variables. Additionally, three modules for the calculation of scores for individual forest estates are the result of this research. Conclusions: The MRG Model is based on FE ranking according to deviation from the average value of the selected variables. The quality of the model lies in the fact that it is relatively simple (there are no complex statistical or other methods, necessary data can be collected easily), and that it can be applied again for similar surveys. Implementation of the MRG Model involves 5 basic steps with 7 phases to be performed in the order specified in this paper. The selection of variables which will be part of the MRG Model is crucial. The survey sample must include representatives that are directly or indirectly involved in the forestry sector. Although it might seem that all selected variables are significant, it is always necessary to give each variable the importance in accordance with the survey results. It is necessary to validate the defined model, data and final ranks on a pilot sample. Since there are three ranks, it is necessary to consider their mutual correlation, by performing statistical analysis rank correlation.
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Andriani, Fitria. "INVESTASI REKSADANA SYARIAH DI INDONESIA." AT-TIJARAH: Jurnal Penelitian Keuangan dan Perbankan Syariah 2, no. 1 (October 16, 2020): 44–65. http://dx.doi.org/10.52490/at-tijarah.v2i1.816.
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The development of Islamic investment in Indonesia is progressing very rapidly. The principle of every investment made by each individual must be based on sharia principles. This study aims to explain the principles of sharia mutual funds investing which are currently growing rapidly as well as the development and procedures for investing in Islamic mutual funds. The results of this study indicate that the statistical development of Islamic mutual funds tends to increase significantly, the NAV of Islamic mutual funds in August 2020 reached 67.71 trillion. Players in sharia mutual fund investments include investors and investment managers who are trusted by investors in managing their mutual funds. The procedure for investing in Islamic mutual funds includes two ways, namely the method of buying or referred to as subcription and redemption or the method of selling Islamic mutual funds, a good understanding of these two methods will determine the risks and benefits that investors and investment managers get.
Keyword: Mutual Fund Investment, Investment Procedures.
Abstrak
Perkembangan investasi syariah di Indonesia melaju dengan sangat pesat, Prinsip dari setiap investasi yang dilakukan oleh setiap individu harus berlandaskan dengan prinsip syariah. Penelitian ini bertujuan untuk menjelaskan prinsip dari investasi reksadana syariah yang saat ini sedang berkembang pesat serta perkembangannya dan tata cara melakukan investasi pada reksadana syariah. hasil penelitian ini menunjukkan perkembangan statistik reksadana syariah cenderung naik signifikan, NAB reksadana syariah agustus 2020 mencapai 67,71 Triliun. Pelaku dalam investasi reksadana syariah meliputi investor dan manajer inverstasi yang dipercayai oleh investor dalam mengelola reksadana miliknya. Tata cara investasi pada reksadana syariah meliputi dengan dua cara yaitu cara pembelian atau disebut dengan subcription dan redemtion atau cara penjualan pada reksadana syariah, pemahaman yang baik akan kedua cara ini akan menentuan resiko dan keuntungan yang di dapatkan oleh investor dan manajer investasi.
Kata kunci: Investasi Reksadana, Tata Cara Invetasi Reksadana.
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Danilov, Igor Sergeevich, and Galina Viktorovna Tretyakova. "Theoretical aspects of collective investment in the international financial market." Mezhdunarodnaja jekonomika (The World Economics), no. 12 (December 1, 2020): 31–41. http://dx.doi.org/10.33920/vne-04-2012-04.
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The global fi nancial crisis of 2008–2009 and the crisis of the end of 2014–2015 had a negative impact on the state of the collective investment market, which became a constraining factor for its development. These problems of the formation and development of the market for collective investments in Russia, including mutual funds, dictate the need for theoretical research on these issues and their practical implementation. This determined the relevance and signifi cance of the chosen research topic. The concept of «collective investment» has not been suffi ciently researched in the works of Russian and foreign economists, it is not contained in the regulatory documents of the Russian Federation. That is why this topic is relevant: there are a large number of unexplored issues that need to be considered. The purpose of this research is to study and generalize the theoretical and practical aspects of the formation and development of mutual funds and ETFs as one of the most promising forms of collective investment. The main research methods used a systematic approach, statistical and economic analysis, and other general scientifi c methods. The article examines the aspects of collective investment in the international fi nancial market, as well as the mechanism of the collective investment market functioning. Moreover, a comparative description of mutual funds and ETFs are presented. In the course of research activities, directions for the development of mutual funds and ETFs were proposed as important elements of the collective investment system. The implementation of these proposals will increase the role of mutual funds and ETFs in the collective investment market in Russia and abroad, stabilize their reliability and attractiveness for investors.
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Kurniawan, Elan. "PENGARUH INFLASI, JAKARTA ISLAMIC INDEX, BAGI HASIL BANK SYARIAH TERHADAP INVESTASI REKSA DANA SYARIAH." Kinerja 2, no. 01 (April 18, 2020): 113–21. http://dx.doi.org/10.34005/kinerja.v2i02.799.
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The purpose of this study is to obtain empirical evidence about the problems discussed, namely "Influence of Inflation, Jakarta Islamic Index, and Profit-Sharing of Islamic Banks on Sharia Mutual Investment". Investment is proxied by the Net Asset Value of Sharia Funds.
Presentation and analysis of research data in 2013-2017, using descriptive statistical analysis, panel data regression models, data estimation methods namely Chow Test, classical assumption analysis using normality test, multicollinearity test, and hypothesis testing.
Based on the results of the analysis of this research data, positive inflation has a significant positive effect on Sharia Mutual Fund Investment, the Jakarta Islamic Index has a significant positive effect on Sharia Mutual Fund Investment, while Sharia Bank Profit Sharing is also significantly negative on Sharia Mutual Fund Investment.
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Darmayanti, Ni Putu Ayu, Ni Putu Santi Suryantini, Henny Rahyuda, and Sayu Ketut Sutrisna Dewi. "PERBANDINGAN KINERJA REKSA DANA SAHAM DENGAN METODE SHARPE, TREYNOR, DAN JENSEN." Jurnal Riset Ekonomi dan Bisnis 11, no. 2 (August 28, 2018): 93. http://dx.doi.org/10.26623/jreb.v11i2.1079.
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<p>Reksa dana saham merupakan reksa dana yang menawarkan keuntungan yang tinggi namun juga memiliki risiko yang tinggi karena dipengaruhi oleh fluktuasi yakni penurunan harga saham yang dipengaruhi mekanisme pasar di bursa efek. Oleh karena itu para calon investor harus memiliki pengetahuan dalam memilih reksa dana mana yang akan dipilih. Dalam penelitian ini ingin membandingkan antara metode pengukuran kinerja Treynor, Sharpe, dan Jensen. Tujuan dari penelitian ini adalah untuk mengetahui ranking kinerja reksa dana saham yang dihasilkan menggunakan ketiga metode tersebut, membandingkan kinerja reksa dana saham dengan suatu standar pengukuran (<em>benchmark</em>) yaitu kinerja IHSG, dan kemudian untuk mengetahui ada atau tidaknya perbedaan ranking yang dihasilkan oleh ketiga metode tersebut. Berdasarkan hasil penilaian kinerja dengan metode Sharpe, jika dibandingkan dengan IHSG sebagai <em>benchmark</em>, sebanyak 17 (18,5 persen) reksa dana memiliki kinerja yang <em>outperform</em> atau kinerjanya di atas kinerja portofolio pasar. Sisanya sebanyak 75 reksa dana ditemukan <em>underperform</em> atau kinerjanya di bawah portofolio pasar. Hasil penilaian kinerja dengan metode Treynor dan Jensen, sebanyak 33 (35,87 persen) reksa dana memiliki kinerja yang <em>outperform</em> atau kinerjanya di atas kinerja portofolio pasar. Sisanya sebanyak 59 reksa dana ditemukan <em>underperform. </em>Reksa dana yang <em>outperform</em> dapat dipertimbangkan oleh investor sebagai alternatif investasi. Dari hasil pengujian statistik mengenai perbedaan ranking kinerja reksa dana dengan menggunakan metode Sharpe, Treynor, dan Jensen, dapat disimpulkan bahwa ketiga metode penilaian kinerja tidak menghasilkan ranking kinerja yang berbeda-beda secara signifikan</p><p> </p><p><em>Equity funds are mutual funds that offer high profits but also have a high risk because they are influenced by fluctuations in the decline in stock prices which are influenced by market mechanisms on the stock exchange. Therefore, potential investors must have knowledge in choosing which mutual fund to choose. In this study wanted to compare the performance measurement methods of Treynor, Sharpe, and Jensen. The purpose of this study was to determine the ranking performance of equity funds generated using these three methods, compare the performance of equity funds with a benchmark standard, namely the JCI performance, and then to find out whether or not there are ranking differences generated by these three methods. . Based on the results of the performance evaluation with the Sharpe method, when compared with the JCI as a benchmark, as many as 17 (18.5 percent) mutual funds have outperformed performance or performance above the market portfolio performance. The results of the performance appraisal with the Treynor and Jensen methods, as many as 33 (35.87 percent) mutual funds have outperformed performance or performance above the market portfolio performance. Mutual funds that are outperformed can be considered by investors as an alternative investment. From the results of statistical tests regarding differences in the ranking of mutual fund performance using the Sharpe, Treynor, and Jensen methods, it can be concluded that the three methods of performance appraisal do not produce performance ratings that differ significantly.</em><em></em></p>
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Jain, Nidhi, and Bikrant Kesari. "Impact of Behavioral Biases in Financial Risk Tolerance Ability of Mutual Fund Investors." Tobacco Regulatory Science 7, no. 5 (September 30, 2021): 2748–65. http://dx.doi.org/10.18001/trs.7.5.1.45.
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Objective: The Behavioral bias is the term that deals with the investors’ psychology about their investment decision with their investment expertise. Every individual is biased, according to standard economic theory by his behavior and experiences which are rational. Methods: This research seeks to segregate mutual fund holders into various groups (persons and professionals) based on Behavioral biases and then investigates whether these Behavioral biases are influencing the level of knowledge of investors and the financial risk tolerance of certain mutual funds. Statistical tools compare investors characteristics and analyse how Behavioral biases are associated. Results: The factors analysed are financial circumstance, Type of Investors, Asset class preference, Time Horizon and Purpose of Investment. The primary information was gathered from 250 Central India mutual fund investors dependent on Judgment sampling. CFA, Correlation, MANOVA and Regression. Conclusions: Findings shows the effect of the behavior bias has positive impact on mutual fund investor awareness and financial risk tolerance.
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Meng, Ming, Luyang Dai, Qingshan She, Yuliang Ma, and Wanzeng Kong. "Crossing time windows optimization based on mutual information for hybrid BCI." Mathematical Biosciences and Engineering 18, no. 6 (2021): 7919–35. http://dx.doi.org/10.3934/mbe.2021392.
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<abstract> <p>Hybrid EEG-fNIRS brain-computer interface (HBCI) is widely employed to enhance BCI performance. EEG and fNIRS signals are combined to increase the dimensionality of the information. Time windows are used to select EEG and fNIRS singles synchronously. However, it ignores that specific modal signals have their own characteristics, when the task is stimulated, the information between the modalities will mismatch at the moment, which has a significant impact on the classification performance. Here we propose a novel crossing time windows optimization for mental arithmetic (MA) based BCI. The EEG and fNIRS signals were segmented separately by sliding time windows. Then crossing time windows (CTW) were combined with each one segment from EEG and fNIRS selected independently. Furthermore, EEG and fNIRS features were extracted using Filter Bank Common Spatial Pattern (FBCSP) and statistical methods from each sample. Mutual information was calculated for FBCSP and statistical features to characterize the discrimination of crossing time windows, and the optimal window would be selected based on the largest mutual information. Finally, a sparse structured framework of Fisher Lasso feature selection (FLFS) was designed to select the joint features, and conventional Linear Discriminant Analysis (LDA) was employed to perform classification. We used proposed method for a MA dataset. The classification accuracy of the proposed method is 92.52 ± 5.38% and higher than other methods, which shows the rationality and superiority of the proposed method.</p> </abstract>
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Ziyadinov, Vadim V., and Maxim V. Tereshonok. "MATHEMATICAL MODELS AND RECOGNITION METHODS FOR MOBILE SUBSCRIBERS MUTUAL PLACEMENT." T-Comm 15, no. 4 (2021): 49–56. http://dx.doi.org/10.36724/2072-8735-2021-15-4-49-56.
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The challenge of mobile subscribers’ groups and crowd’s behavior prediction during the mass events is now increasingly important. Operative methods application of this task solution is difficult; accordingly, development and application of technical methods is necessary. The method of this problem solution consists of subscribers’ telephone conversations recording in a zone of mass action, and the following speech recognition, the semantic analysis and statistical processing application. However, there is a tendency demand decrease for mobile systems voice services with simultaneous demand growth for data traffic nowadays. The purpose of this paper is to create a mathematical model of mobile networks subscribers’ mutual placement types, applicable for automatization of the subscribers’ activities nature prediction systems. The research method consists of mathematical simulation model development for pseudo-random examples generation of subscribers’ mutual placement types set, creation of training dataset, convolution neural network training and usage of training results to recognize the new examples. The results obtained. A mathematical model is proposed allowing to create a representative training and validation dataset of mobile networks subscribers’ mutual placement types for neural network training and testing. The convolution neural network trained using these samples has shown high classification accuracy results with a wide class of subscribers’ mutual placement types.
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Maria, Merzouqi, Sarhrouni El Kebir, and Hammouch Ahmed. "Reduction dimensionality of hyperspectral imagery using genetic algorithm and mutual information and normalized mutual information as a fitness function." International Review of Applied Sciences and Engineering 12, no. 1 (March 20, 2021): 64–75. http://dx.doi.org/10.1556/1848.2020.00149.
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AbstractHyperspectral images (HSI) present a wealth of information. It is distinguished by its high dimensionality. It served humanity in many fields. The quantity of HSI information represents a double-edged sword. As a consequence, their dimensionality must be reduced. Nowadays, several methods are proposed to overcome their duress. The most useful and essential solution is selection approaches of hyperspectral bands to analyze it quickly. Our work suggests a novel method to achieve this selection: we introduce a Genetic Algorithm (GA) based on mutual information (MI) and Normalized Mutual Information (NMI) as fitness functions. It selects the relevant bands from noisiest and redundant ones that don’t contain any additional information. .The proposed method is applied to three different HSI: INDIAN PINE, PAVIA, and SALINAS. The introduced algorithm provides a remarkable efficiency on the accuracy of the classification, in front of other statistical methods: the Bhattacharyya coefficient as well as the inter-bands correlation (Pearson correlation). We conclude that the measure of information (MI, NMI) provides more efficiency as a fitness function for GA selection applied to HSI; it must be more investigated.
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Jebadurai, Immanuel, Getzi Paulraj, Jebaveerasingh Jebadurai, and Salaja Silas. "Experimental analysis of filtering-based feature selection techniques for fetal health classification." Serbian Journal of Electrical Engineering 19, no. 2 (2022): 207–24. http://dx.doi.org/10.2298/sjee2202207j.
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Machine learning techniques enable computers to acquire intelligence through learning. Trained machines can carry out various tasks, such as prediction, classification, clustering, and recommendation, within a wide variety of applications. Classification is a supervised learning technique that can be improved using feature selection techniques such as filtering, wrapping, and embedding. This paper explores the impact of filtering-based feature selection techniques on classification methods, and focuses on an analysis of correlationbased filtering techniques based on Pearson, Spearman, and Kendall rank correlation. Similarly, we explore the impacts of using statistical filtering techniques such as mutual information, chi-squared score, the ANOVA univariate test, and the univariate ROC-AUC. These filtering techniques are evaluated by implementing them with the k-nearest neighbor, support vector machine, decision tree, and Gaussian na?ve Bayes classification methods. Our experiments were carried out using a fetal heart rate dataset, and the performance of each combination of methods was measured based on precision, recall, F1-score, and accuracy. An analysis of the experimental results showed that the performance metrics for the Gaussian na?ve Bayes and k-nearest neighbor methods were improved by 3% through the use of the statistical feature selection technique, and a 4% improvement was observed for the decision tree and support vector machine methods using a correlation-based filtering technique. Of the statistical feature selection techniques, ANOVA and ROC-AUC were the best as they improved the accuracy by 92%; compared to the other correlation techniques, the Spearman correlation coefficient gave the best results, as it also improved the accuracy by 92%.
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Zuo, Jingping, Hangxin Gan, and Huixin Li. "A study of ancient glass classification problem based on multiple logistic regression." Highlights in Science, Engineering and Technology 22 (December 7, 2022): 265–69. http://dx.doi.org/10.54097/hset.v22i.3386.
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The Silk Road was a commercial route linking China and the West in ancient times, and was an important window for China to open up to the outside world during the Han Dynasty, strongly promoting cultural exchange between China and the West. Ancient glass is susceptible to weathering by the burial environment, and in the process the proportions of its various chemical components change. This paper studies the chemical composition content of ancient glass objects, establishes a classification model, analyses the correlation between various parameters of different types of glass objects, gives statistical laws and specific classification methods, and uses glass objects to help the exchange and mutual appreciation between Eastern and Western civilizations and the longevity of Chinese civilization.
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Ahmad, Muhammad, Manuel Mazzara, Rana Aamir Raza, Salvatore Distefano, Muhammad Asif, Muhammad Shahzad Sarfraz, Adil Mehmood Khan, and Ahmed Sohaib. "Multiclass Non-Randomized Spectral–Spatial Active Learning for Hyperspectral Image Classification." Applied Sciences 10, no. 14 (July 9, 2020): 4739. http://dx.doi.org/10.3390/app10144739.
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Active Learning (AL) for Hyperspectral Image Classification (HSIC) has been extensively studied. However, the traditional AL methods do not consider randomness among the existing and new samples. Secondly, very limited AL research has been carried out on joint spectral–spatial information. Thirdly, a minor but still worth mentioning factor is the stopping criteria. Therefore, this study caters to all these issues using a spatial prior Fuzziness concept coupled with Multinomial Logistic Regression via a Splitting and Augmented Lagrangian (MLR-LORSAL) classifier with dual stopping criteria. This work further compares several sample selection methods with the diverse nature of classifiers i.e., probabilistic and non-probabilistic. The sample selection methods include Breaking Ties (BT), Mutual Information (MI) and Modified Breaking Ties (MBT). The comparative classifiers include Support Vector Machine (SVM), Extreme Learning Machine (ELM), K-Nearest Neighbour (KNN) and Ensemble Learning (EL). The experimental results on three benchmark hyperspectral datasets reveal that the proposed pipeline significantly increases the classification accuracy and generalization performance. To further validate the performance, several statistical tests are also considered such as Precision, Recall and F1-Score.
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Ganbat, Khaliun, Inessa Popova, and Ivan Potravnyy. "Impact Investment of Project Financing: Opportunity for Banks to Participate in Supporting Green Economy." Baltic Journal of Real Estate Economics and Construction Management 4, no. 1 (November 1, 2016): 69–83. http://dx.doi.org/10.1515/bjreecm-2016-0006.
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Abstract The article analyses impact investment of project financing. Companies’ own funds, own funds of the consortium members, the company’s own resources and budget funding, own funds of the company on the basis of a production sharing agreement, borrowed funds; the funds raised by the bond issue are all considered as the project financing sources in the natural resource field. The purpose of this article is to consider various opportunities to support environmentally oriented projects in the framework of project financing, including through attracting funds of banks for the development of “green” economy. The role of banks and the banking sector in supporting environmentally and socially oriented projects is analysed. The experience of banks in Asia, Europe and the United States in terms of “green” economy projects is shown. Moreover, environmental and social risks, and impact of a project, the project compliance with the norms and standards of responsible finance are all considered in this article. Classification of environmental projects with the purpose of project financing is proposed, and also the scheme of interaction between stakeholders is shown, including banks, in the implementation of projects reducing greenhouse gas emissions. Furthermore, impact investment in financing projects with the participation of banking sector is analysed and justified on the example of such countries as Mongolia, Russia, Japan, the United States and others. Evaluation procedures and the selection of projects for social investment purposes are shown in the article, including the measures of supporting banks for the project implementation in the field of “green” economy. The following research methods are considered: systematic analysis, environmental economic analysis environmental auditing, statistical methods for evaluating the costs and benefits from implementing environmentally oriented projects, methods of assessment of damage from environmental pollution, etc.
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Mehea, Marek, Slavomíra Staaková, Adela Feranecová, and Veronika Ragániová. "Selecting the savings account in the Slovak Republic." Problems and Perspectives in Management 14, no. 4 (December 14, 2016): 8–16. http://dx.doi.org/10.21511/ppm.14(4).2016.01.
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There are currently many investment and financial products that can be used for capitalizing of savings. Although investments in various commodities, shares, securities, or funds can be with high yields, it requires some knowledge and experience. Unattempted investor may experience unpleasant surprise of possible losses of greater amount of money, as such investments are generally associated with a higher risk. For these reasons, the majority of the population remains in the Slovak Republic faithful to traditional forms of capitalizing of funds. One of these forms are savings accounts in banks. The main purpose of this paper is to find possibly the best savings account in the Slovak Republic. In cooperation with experts from the field of banking, the authors have defined the selection criteria of savings accounts, assessed their importance and, then, they have arranged savings accounts offered in the Slovak Republic according to achieved score. For this purpose, methods of multicriteria decision making were used. These methods are based on the evaluation of several alternative solutions based on multiple criteria. These criteria must be assigned by weights which represent their importance in decision making process. These weights were calculated using the Saaty’s method, which is a method based on mutual comparison of all the criteria. For final ranking of term deposits, taking into account the weights of the criteria, the method TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) was used. Keywords: savings, banking products, savings accounts, multicriteria decision making. JEL Classification: E21, G21
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Wang, Yifeng, Ping Wang, Qihang Wang, Zhengxing Chen, and Qing He. "Using Vehicle Interior Noise Classification for Monitoring Urban Rail Transit Infrastructure." Sensors 20, no. 4 (February 18, 2020): 1112. http://dx.doi.org/10.3390/s20041112.
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This study developed a multi-classification model for vehicle interior noise from the subway system, collected on smartphones. The proposed model has the potential to be used to analyze the causes of abnormal noise using statistical methods and evaluate the effect of rail maintenance work. To this end, first, we developed a multi-source data (audio, acceleration, and angle rate) collection framework via smartphone built-in sensors. Then, considering the Shannon entropy, a 1-second window was selected to segment the time-series signals. This study extracted 45 features from the time- and frequency-domains to establish the classifier. Next, we investigated the effects of balancing the training dataset with the Synthetic Minority Oversampling Technique (SMOTE). By comparing and analyzing the classification results of importance-based and mutual information-based feature selection methods, the study employed a feature set consisting of the top 10 features by importance score. Comparisons with other classifiers indicated that the proposed XGBoost-based classifier runs fast while maintaining good accuracy. Finally, case studies were provided to extend the applications of this classifier to the analysis of abnormal vehicle interior noise events and evaluate the effects of rail grinding.
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Li, Tengyue, and Simon Fong. "Similarity Measure of Breast Cancer Datasets Using Fuzzy Rule-Based Classification by Attribute." International Journal of Extreme Automation and Connectivity in Healthcare 1, no. 1 (January 2019): 12–28. http://dx.doi.org/10.4018/ijeach.2019010103.
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To compare with two datasets based on attributes by using classification algorithms, for the attributes, the authors need to select them by rules and the system is known as rule-based reasoning system which classifies a given test instance into a particular outcome from the learned rules. The test instance carries multiple attributes, which are usually the values of diagnostic tests. In this article, the authors propose a classifier ensemble-based method for comparison of two breast cancer datasets. The ensemble data mining learning methods are applied to rule generation, and a multi-criterion evaluation approach is used for selecting reliable rules over the results of the ensemble methods. The efficacy of the proposed methodology is illustrated via an example of two breast cancer datasets. This article introduces a novel fuzzy rule-based classification method called FURIA, to obtain a relationship between two breast cancer datasets. Hence, it can find the similarity between these two datasets. The new method is compared vis-à-vis with other classical statistical approaches such as correlation and mutual information gain.
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Hruzky, Yuriy. "Comparative analysis of classifications of public procurement." University Economic Bulletin, no. 50 (August 31, 2021): 24–32. http://dx.doi.org/10.31470/2306-546x-2021-50-24-32.
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Relevance of the research topic. The article is devoted to theoretical and practical aspects of classification of public procurement in Ukraine. Formulation of the problem. The development of a scientifically sound classification of procurement, which would provide a combination of theory and practice of public procurement, allowed for a more accurate assessment of the effectiveness of the use of budget funds. Analysis of recent research and publications. The article provides an overview of current publications on public procurement management, as well as scientific approaches to the classification of public procurement. Selection of unexplored parts of the general problem. The author emphasizes the insufficiency of domestic works on the classification of public procurement, taking into account the latest changes in the legislation of our state. The purpose of the article is to analyze the classification criteria of public procurement, as well as to find ways to improve the classification of public procurement. Research methods: dialectical, analysis and synthesis, empirical, statistical. Work results and conclusions. The article considers the theoretical and practical principles of classification of public procurement, analyzes scientific approaches to the classification of public procurement, identifies the main criteria for the classification of procurement, improved the classification of public procurement. Field of application of results. The obtained results can be used primarily in procurement procedures, as well as in improving the economic policy of the state. Novelty: The proposed classification of public procurement, which corresponds to the modern stage of the formation of the sphere of public procurement, reproduces the structure and organization of procurement activities in Ukraine.
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Murthi, M. V. Narayana. "Comparing Two ARIMA Models for Daily Stock Price Data." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 1606–10. http://dx.doi.org/10.22214/ijraset.2021.38943.
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Abstract: Analyzing the past data and planning for future is very important for every public and private organizational decisions. Now a days individuals also using forecasting methods to invest in Stock market. Investments in mutual funds and in registered companies in companies in stock market is the order of the day. In this paper, advanced forecasting methods are fitted to the time related stock price data to study its effectiveness in forecasting future events. Auto correlation and standard models have been analyzed before fitting this model to the above data. The forecasting can be done by using the ARIMA time series(using auto. arima) model. A particular reference have been made to Box and Jenkins approach for day to day stock price data values of Exxon Mobile Corporation from '1995-01-01 to 2020-03-01. With usual statistical software R. Here, ARIMA(1,1,1,) is fitted to this data, These results are compared with the model ARIMA(1,1,1,) by using accuracy measures. Keywords: ARIMA: Auto Regressive Integrated Moving Average ACF: Auto Correlation Function PACF: Partial Auto Correlation Function AIC: Akaikae Information Criterion RMSE: Root mean square error XOM: Exxon Mobil Corporation
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Cherniavskyi, Sergii, Andriy Zapototskyi, and Anton Syzonenko. "MODERN TECHNOLOGIES OF ACQUISITION OF FUNDS OF CITIZENS BY THE FINANCIAL PYRAMID." Baltic Journal of Economic Studies 4, no. 4 (September 2018): 356–60. http://dx.doi.org/10.30525/2256-0742/2018-4-4-356-360.
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The purpose of the article is to study the criminalistics of the use of the most common technologies of acquisition of funds of citizens, done by the way of the financial pyramid. The subject of the study is the content of criminal technology of fraudulent way of the financial pyramid. Methodology. The research is based on the use of general scientific and special-scientific methods and methods of scientific knowledge. The historical-legal method allowed determining the genesis of the concepts of “technology of criminal activity” and “financial pyramid”, as well as the formation of scientific and theoretical views on problems and methods of combating them. The comparative legal method was used to compare the doctrinal approaches of legislative regulation to counteract fraud committed by the method of the financial pyramid. The system-structural method contributed to the awareness of the technologies of preparing, committing, and concealing the fraud. The methods of grouping and classification were the basis for the author’s approach to the differentiation of technologies for the acquisition of funds of citizens, depending on the organizational and legal form, under the cover of which a financial pyramid was created. The statistical method is used in the analysis of investigative and judicial practice for ten years. The results of the study showed that the method of financial pyramid used for committing fraud is fully structured and includes criminal technologies for preparing, committing, and concealing the fraud. The combination of separate technologies in the mechanism of the crime is aimed at masking the active phase of criminal activity under civil-law relations, which complicates the timely detection of the signs of the crime both by the victim and by law enforcement agencies. Practical implications. The research carried out the typing of fraudulent techniques using the financial pyramid method, which is the basis for developing and improving methods of disclosure and investigation of crimes. Value/ originality. On the basis of the proposed author’s approach to the differentiation of technologies of criminal activity, it is possible to predict the emergence of the new ways of committing fraud in the financial sector.
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Momin, Shadab, Yang Lei, Zhen Tian, Justin Roper, Jolinta Lin, Shannon Kahn, Hui-Kuo Shu, Jeffrey Bradley, Tian Liu, and Xiaofeng Yang. "Cascaded mutual enhancing networks for brain tumor subregion segmentation in multiparametric MRI." Physics in Medicine & Biology 67, no. 8 (April 11, 2022): 085015. http://dx.doi.org/10.1088/1361-6560/ac5ed8.
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Abstract Accurate segmentation of glioma and its subregions plays an important role in radiotherapy treatment planning. Due to a very populated multiparameter magnetic resonance imaging image, manual segmentation tasks can be very time-consuming, meticulous, and prone to subjective errors. Here, we propose a novel deep learning framework based on mutual enhancing networks to automatically segment brain tumor subregions. The proposed framework is suitable for the segmentation of brain tumor subregions owing to the contribution of Retina U-Net followed by the implementation of a mutual enhancing strategy between the classification localization map (CLM) module and segmentation module. Retina U-Net is trained to accurately identify view-of-interest and feature maps of the whole tumor (WT), which are then transferred to the CLM module and segmentation module. Subsequently, CLM generated by the CLM module is integrated with the segmentation module to bring forth a mutual enhancing strategy. In this way, our proposed framework first focuses on WT through Retina U-Net, and since WT consists of subregions, a mutual enhancing strategy then further aims to classify and segment subregions embedded within WT. We implemented and evaluated our proposed framework on the BraTS 2020 dataset consisting of 369 cases. We performed a 5-fold cross-validation on 200 datasets and a hold-out test on the remaining 169 cases. To demonstrate the effectiveness of our network design, we compared our method against the networks without Retina U-Net, mutual enhancing strategy, and a recently published Cascaded U-Net architecture. Results of all four methods were compared to the ground truth for segmentation and localization accuracies. Our method yielded significantly (P < 0.01) better values of dice-similarity-coefficient, center-of-mass-distance, and volume difference compared to all three competing methods across all tumor labels (necrosis and non-enhancing, edema, enhancing tumor, WT, tumor core) on both validation and hold-out dataset. Overall quantitative and statistical results of this work demonstrate the ability of our method to both accurately and automatically segment brain tumor subregions.
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Baudot, Pierre, Monica Tapia, Daniel Bennequin, and Jean-Marc Goaillard. "Topological Information Data Analysis." Entropy 21, no. 9 (September 6, 2019): 869. http://dx.doi.org/10.3390/e21090869.
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This paper presents methods that quantify the structure of statistical interactions within a given data set, and were applied in a previous article. It establishes new results on the k-multivariate mutual-information ( I k ) inspired by the topological formulation of Information introduced in a serie of studies. In particular, we show that the vanishing of all I k for 2 ≤ k ≤ n of n random variables is equivalent to their statistical independence. Pursuing the work of Hu Kuo Ting and Te Sun Han, we show that information functions provide co-ordinates for binary variables, and that they are analytically independent from the probability simplex for any set of finite variables. The maximal positive I k identifies the variables that co-vary the most in the population, whereas the minimal negative I k identifies synergistic clusters and the variables that differentiate–segregate the most in the population. Finite data size effects and estimation biases severely constrain the effective computation of the information topology on data, and we provide simple statistical tests for the undersampling bias and the k-dependences. We give an example of application of these methods to genetic expression and unsupervised cell-type classification. The methods unravel biologically relevant subtypes, with a sample size of 41 genes and with few errors. It establishes generic basic methods to quantify the epigenetic information storage and a unified epigenetic unsupervised learning formalism. We propose that higher-order statistical interactions and non-identically distributed variables are constitutive characteristics of biological systems that should be estimated in order to unravel their significant statistical structure and diversity. The topological information data analysis presented here allows for precisely estimating this higher-order structure characteristic of biological systems.
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Senkevich, Oleksandr F. "Investment component in promoting the development of the digital economy and society." Economies' Horizons, no. 4(11) (November 10, 2019): 55–64. http://dx.doi.org/10.31499/2616-5236.4(11).2019.209520.
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The purpose of the article is to substantiate the investment component in promoting the development of the digital economy and society. Methodology. General scientific methods are used in the research, in particular system economic analysis – to substantiate the strategic dominants of the digital transformation of the economy; statistical analysis – to study the current state and trends in foreign direct investment in digitalization; methods of positive and normative analysis – to develop recommendations for improving the investment component in promoting the development of the digital economy and society. Results. The analysis of the capital investment dynamics by section of information and telecommunications for 2010–2018 shows an increase in the share of telecommunications in its total capital investment by 0.38 percentage points. This increase was due to a slight increase in telecommunications investment in 2018 and an overall increase in capital investment. In general, capital investment increased 3.2 times in eight years, and investment in information and telecommunications – 3.5 times. It is proved that significant innovative changes in telecommunications, the transition to 3G and 4G in 2015 and 2018 increased the amount of investment in these periods by 14,799.9 million UAH and 11,489.7 million UAH, respectively. According to the growth rate, it is necessary to note the receipts in the area of computer programming and the provision of other information services, which increased 11 times (telecommunications – 3.4 times, publishing, radio, television – 2.5 times). It is noted that foreign direct investment in the economic activity of information and telecommunications has a positive trend to increase from 1,734.9 million USD in 2010 to 2,201.1 million USD in 2018. These investments also characterize a favorable investment climate for foreign investors when investing in digitalization. It is proved that today in Ukraine the most attention is paid to the creation of high-tech and engineering clusters. In addition, the development of intersectoral alliances, RD centers, laboratories, incubators, accelerators, venture funds and innovation teams is promising. The strategic dominants of the economy digital transformation are determined. Practical meaning. The main priority projects for investing in transformation infrastructure in 2020–2030 are presented. Prospects for further research. It is substantiated that the model of financing through venture capital, business angels, grants, business incubators, accelerators, crowdfunding platforms, innovation teams is expedient for innovative projects. It can be through raising funds in the stock market, through IPOs, SPOs, ISOs, direct investment funds, mutual investment institutions, state and non-state pension funds.
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Aydin, Serap, Nafiz Arica, Emrah Ergul, and Oğuz Tan. "Classification of Obsessive Compulsive Disorder by EEG Complexity and Hemispheric Dependency Measurements." International Journal of Neural Systems 25, no. 03 (April 8, 2015): 1550010. http://dx.doi.org/10.1142/s0129065715500100.
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In the present study, both single channel electroencephalography (EEG) complexity and two channel interhemispheric dependency measurements have newly been examined for classification of patients with obsessive–compulsive disorder (OCD) and controls by using support vector machine classifiers. Three embedding entropy measurements (approximate entropy, sample entropy, permutation entropy (PermEn)) are used to estimate single channel EEG complexity for 19-channel eyes closed cortical measurements. Mean coherence and mutual information are examined to measure the level of interhemispheric dependency in frequency and statistical domain, respectively for eight distinct electrode pairs placed on the scalp with respect to the international 10–20 electrode placement system. All methods are applied to short EEG segments of 2 s. The classification performance is measured 20 times with different 2-fold cross-validation data for both single channel complexity features (19 features) and interhemispheric dependency features (eight features). The highest classification accuracy of 85 ±5.2% is provided by PermEn at prefrontal regions of the brain. Even if the classification success do not provided by other methods as high as PermEn, the clear differences between patients and controls at prefrontal regions can also be obtained by using other methods except coherence. In conclusion, OCD, defined as illness of orbitofronto-striatal structures [Beucke et al., JAMA Psychiatry 70 (2013) 619–629; Cavedini et al., Psychiatry Res. 78 (1998) 21–28; Menzies et al., Neurosci. Biobehav. Rev. 32(3) (2008) 525–549], is caused by functional abnormalities in the pre-frontal regions. Particularly, patients are characterized by lower EEG complexity at both pre-frontal regions and right fronto-temporal locations. Our results are compatible with imaging studies that define OCD as a sub group of anxiety disorders exhibited a decreased complexity (such as anorexia nervosa [Toth et al., Int. J. Psychophysiol. 51(3) (2004) 253–260] and panic disorder [Bob et al., Physiol. Res. 55 (2006) S113–S119]).
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Zuo, Wei, Xingguo Zeng, Xingye Gao, Zhoubin Zhang, Dawei Liu, and Chunlai Li. "Machine Learning Fusion Multi-Source Data Features for Classification Prediction of Lunar Surface Geological Units." Remote Sensing 14, no. 20 (October 11, 2022): 5075. http://dx.doi.org/10.3390/rs14205075.
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Taking the Chang’e-4 and Chang’e-5 landing areas as the study areas, this study extracts the geological unit information from the regional USGS geological map, as well as the feature information such as topography and geomorphology, material composition and mineral abundance from Chang’e-2 DOM and DEM, wide angle camera (WAC) and Kaguya multi-band imager data. By applying methods including the statistical-based estimation of mutual information of data and the integrated-algorithmic-model-based evaluation of feature importance to this extracted information, we screen the significant features and construct a high-precision classification model by combining machine learning algorithm with important features of sample data. The practical application of the multi-classification prediction on the complex geological units in the two study areas achieves 97.9% and 95.1% accuracy. At the same time, the significant characteristics of the study area are mined, and the rules and knowledge associated with the geological evolution of the study area are obtained. In this study, we carry out research on quantitative prediction and identification of lunar surface geological units based on large samples and construct a high-precision multi-classification model to achieve automatic classification and prediction on large sample geological units with high accuracy. This method provides a new idea for the predicted mapping of geological units of lunar global digital mapping. In addition, it helps to fully exploit the useful information in the data and enrich the knowledge regarding the formation and evolution of the Moon.
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UMAROV, Husan S. "The role of crowdfunding as an instrument of innovative transformation of capital markets." Finance and Credit 27, no. 12 (December 27, 2021): 2872–96. http://dx.doi.org/10.24891/fc.27.12.2872.
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Subject. The article investigates crowdfunding as a new element of the capital market. Objectives. The purpose is to identify the role of crowdfunding in the modern capital market and in the financial market in general, systematize the ideas of what crowdfunding is and classify them, suggest possible future areas for its development. Methods. The study employs methods of logical and statistical analysis, systematization, and deduction. Results. The paper offers a classification of crowdfunding based on three main characteristics, i.e. purposes, geographic model, and financial nature. The performed statistical analysis proved that the main recipients of funds on the crowdfunding platforms are enterprises involved in creative activities, since they either do not have any access to traditional financing instruments or the financing is expensive. I identify a number of directions for the development of crowdfunding, like auction, innovation, and social. Conclusions. The research has practical and theoretical significance. It can be used for further investigation of crowdfunding and its social role. Government agencies may apply the main findings of this study when developing programs for the introduction of crowdfunding as a financial instrument in Russia. Furthermore, the paper may be interesting for crowdfunding platforms both in the new markets, as it enables to identify their target audience, and in developed markets, as the result of the study is to reveal new directions for crowdfunding development.
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CHANG, YUNFENG, and YUAN PING. "EMERGING CLUSTER ANALYSIS OF SCI JOURNALS AND ITS EFFICIENCY." International Journal of Modern Physics C 22, no. 11 (November 2011): 1247–56. http://dx.doi.org/10.1142/s0129183111016865.
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Cluster analysis is an important way to ascertain whether or not a complex system consists of sub-clusters with different properties. On the basis of journal citation pattern, we clustered 1896 SCI journals in an emerging way (emerging clustering) in this paper. By this emerging clustering, the data to be checked for clustering is reduced from [Formula: see text] to O(NJ) (NJ is the total number of journals), this reduction could reduce the time complexity of clustering to a certain extent. During the clustering process, characteristic numbers of clusters are obtained, which correspond to various resolution scales for viewing the journals and might be helpful in understanding the mutual interactions among various knowledge domains. Its efficiency is further checked by comparisons between emerging clustering and hierarchical clustering with different inter-cluster linkage techniques. Statistical properties and comparisons of the clustering results show that this is an efficient clustering method for journal system. It could be a helpful improvement for traditional classification methods based on subjective analysis.
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Shevchenko, Olga V., and Nataliia V. Kuzmynchuk. "The Methodical Approaches to the Classification of Ukraine’s Territories for the Recovery and the Regional Economy Administration." PROBLEMS OF ECONOMY 3, no. 53 (2022): 104–11. http://dx.doi.org/10.32983/2222-0712-2022-3-104-111.
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The study is aimed at forming the methodological approaches to combining different classifications of territories of Ukraine in order to develop an instrumentarium for their recovery and long-term development. This involves the implementation of the latest approaches to the short-term management of territories and their strategizing. A consideration of the works of scholars demonstrated the lack of a coordinated system of separation of territories (in the presence of several classifications of territories in accordance with the levels of their development) for the needs of socioeconomic recovery and stimulation of development. The paper analyzes various classifications of territories according to the administrative-territorial division, allocated functional types, levels of economic security and distinguishes common features of different classifications of territories (regions and communities) of Ukraine. The goals of further development of territories such as compliance with certain standards of living in the regions are determined, the foundations of economic growth are outlined, the methods of accumulating additional funds in the territories are indicated, the influence of the levels of economic security of the regional economy on the possibilities of stimulating its development is demonstrated. A methodical approach to the grouping of territories by levels of development, needs for recovery, threats to economic security in different regions is formed, on the basis of which a coordinated system of typification of the territories of Ukraine for their socioeconomic recovery and stimulation of development is proposed. It is proved that different territories can belong to different types, which makes the classification flexible, and the goals of stimulating the development of territories remain variable. This underlines the need to use various instruments to enhance the development of territories in different periods. The originality of the publication lies in the mutual combination of different types of classifications of the territories of Ukraine and the development of their grouped classification. This will allow to develop a logical system of measures to manage the regional and local economy on the basis of new principles of their short-term and strategic development, needs for recovery and growth.
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Buś, Szymon, Konrad Jędrzejewski, and Przemysław Guzik. "Statistical and Diagnostic Properties of pRRx Parameters in Atrial Fibrillation Detection." Journal of Clinical Medicine 11, no. 19 (September 27, 2022): 5702. http://dx.doi.org/10.3390/jcm11195702.
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Background: We studied the diagnostic properties of the percentage of successive RR intervals differing by at least x ms (pRRx) as functions of the threshold value x in a range of 7 to 195 ms for the differentiation of atrial fibrillation (AF) from sinus rhythm (SR). Methods: RR intervals were measured in 60-s electrocardiogram (ECG) segments with either AF (32,141 segments) or SR (32,769 segments) from the publicly available Physionet Long-Term Atrial Fibrillation Database (LTAFDB). For validation, we have used ECGs from the Massachusetts Institute of Technology–Beth Israel Hospital (MIT–BIH) Atrial Fibrillation Database. The pRRx distributions in AF and SR in relation to x were studied by histograms, along with the mutual association by the nonparametric Spearman correlations for all pairs of pRRx, and separately for AF or SR. The optimal cutoff values for all pRRx were determined using the receiver operator curve characteristic. A nonparametric bootstrap with 5000 samples was used to calculate a 95% confidence interval for several classification metrics. Results: The distributions of pRRx for x in the 7–195 ms range are significantly different in AF than in SR. The sensitivity, specificity, accuracy, and diagnostic odds ratios differ for pRRx, with the highest values for x = 31 ms (pRR31) rather than x = 50 (pRR50), which is most commonly applied in studies on heart rate variability. For the optimal cutoff of pRR31 (68.79%), the sensitivity is 90.42%, specificity 95.37%, and the diagnostic odds ratio is 194.11. Validation with the ECGs from the MIT–BIH Atrial Fibrillation Database confirmed our findings. Conclusions: We demonstrate that the diagnostic properties of pRRx depend on x, and pRR31 outperforms pRR50, at least for ECGs of 60-s duration.
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Melnyk, Tetiana, Svitlana Melnychenko, and Natalya Reznikova. "THE CONCEPTUAL FRAMEWORK FOR THE OPERATION OF FINANCIAL SYSTEMS IN THE CONTEXT OF GLOBAL STRUCTURAL TRANSFORMATIONS OF BUSINESS MODELS OF BANKING." Baltic Journal of Economic Studies 5, no. 4 (October 29, 2019): 148. http://dx.doi.org/10.30525/2256-0742/2019-5-4-148-154.
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The authors reveal fundamental tendencies of banks financial intermediation especially in the sphere of shadow banking and off-balance writes-off. Substantial transformations of financial system structure caused by liberalization of financial legislation, invention of brand new financial instruments and special risk-transferring schemes (special purpose entities via special investment vehicles) and the gradual process of banking universalization specifically the approximation of business models conducted by traditional commercial and investment banks created grounds for the review of current approaches to financial systems classification. The objective of the study is to identify operative patterns and specifics of financial systems in the context of global structural transformations of business models in the bank sector. Methodology. The methodological basis of the study is formed by theoretical works of foreign and domestic experts on issues related with financial systems worldwide, and the statistical data on the operation of banks in various countries, normative documents of prominent international economic institutions. The general scientific methods of analysis and synthesis, abstraction, quantitative and qualitative comparisons, descriptive analysis, analysis of the current performance of the financial system are used in elaborating theoretical and methodological framework for the typology of national financial systems by position and role played by banks in the financial system. Results. The central objective of the financial system is to transfer temporarily free financial resources from its actors that have their surplus to the ones that feel the deficit of funds. National financial systems can, therefore, be classified by the way domestic companies raise funds they need.
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Siximbayeva, G. Т., N. Juraj, M. M. Khalitova, and Zh G. Imangali. "Managing Corruption Risk in the Agricultural Sector of Kazakhstan and Its Assessment." Economics: the strategy and practice 17, no. 1 (April 5, 2022): 199–211. http://dx.doi.org/10.51176/1997-9967-2022-1-199-211.
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Kazakhstan has a remarkable ability to become the core of food security in the Eurasian region. Obviously, the advantages of Kazakhstan in natural and climatic conditions help strengthen the agricultural sector’s position in its economy. In particular, the positive factors of agricultural sector production are enormous land resources, inland geographical location, and historical background (nomadic cattle breeding, crop production). The agricultural sector is one of the riskiest sectors and manifests itself in climatic, political, technological, financial, corruption, and other issues. It is noted that investments in the industry are mainly represented by state funds (budget, extra-budgetary). Such massive public and private financial investments generate a corruption component effect. The opinion of importance to manage the corruption risk in agriculture is shown. The authors also give the corruption risk concept to analyze the corruption risk features in agriculture. Within the framework of the agricultural specifics, the classification of corruption risks is given. The authors also investigate this risk category’s prerequisites, features, and types. The article presents the internal and external analysis of Kazakhstan’s agriculture corruption risk. Modeling the corruption risk in agriculture as a matrix is proposed as one of the methods of its managing. Forming a standard matrix template with examples of its application shows the significance of preventing measures. In conclusion, there is the need for mutual goals to combat corruption risks both for the state and for agribusiness entities.
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Ewadh, Hussein Ali, Raid Almuhanna, and Saja Alasadi. "Developing optimized prioritizing road maintenance." MATEC Web of Conferences 162 (2018): 01044. http://dx.doi.org/10.1051/matecconf/201816201044.
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Increased demand for efficient maintenance of the existing roadway system needs optimal usage of the allocated funds. The paper demonstrates optimized methods for prioritizing maintenance implementation projects. A selected zone of roadway system in Kerbala city represents the study area to demonstrate the application of the developed prioritization process. Paver system PAVER integrated with GIS is used to estimate and display the pavement condition index PCI, thereby to establish a priority of maintenance. In addition to simple ranking method by PCI produced by the output of PAVER, the paper introduces PCI measure for each section of roadway. The paper introduces ranking by multiple measures investigated through expert knowledge about measures that affect prioritization and their irrespective weights due to a predesigned questionnaire. The maintenance priority index (MPI) is related to cost of suitable proposed maintenance, easiness of proposed maintenance, average daily traffic and functional classification of the roadway in addition to PCI. Further, incremental benefit-cost analysis ranking provide an optimized process due to benefit and cost of maintenance. The paper introduces efficient display of layout and ranking for the selected zone of roadway system based on MPI index and incremental BCR method. Although the two developed methods introduce different layout display for priority, statistical test shows that no significant difference between ranking of all methods of prioritization.
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TRIPAK, Marian. "MODELING OF EXPENDITURE OF THE INCLUSIVE HIGHER EDUCATION INSTITUTION." WORLD OF FINANCE, no. 2(55) (2018): 78–88. http://dx.doi.org/10.35774/sf2018.02.078.
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Purpose. The logic chains of primary importance in planning of the relevant expenses, which had been called to influence positively to the social development of the college are processed. The directions of budget savings in the college are determined. Methodology of research. The article uses modern general scientific and special methods of economic research, in particular: a systematic approach – when studying the connections between phenomena and processes of analysis of the financial state of the inclusive institution; statistical analysis – in determining the dynamics, structure of financial resources of the inclusive institution of higher education in the context of general and special funds; dialectical and abstract-logical – when conducting theoretical generalizations and forming conclusions. Results. The author’s own methodological aspects are developed with the help of mathematical modeling in relation to optimization of the structure of the college general fund budget expenditures in conditions of their effective implementation, taking into account the features of socio-cultural, health and rehabilitation society. Therefore, for the effective redistribution of the funds of the general fund of the college, we use a mathematical model, which defines the main factors of the activity of the higher education institution in conditions of socio-cultural and recreational rehabilitation. As outcome indicators, the frequency of "desirable and undesirable" factors that characterize the state of functional classification of cost estimates, as well as their correlation to the amount involved in expenditure estimates, that is, intensity indicators are offered. Thus, the logic chains of the general fund structure are determined, which should positively influence on the state of social development of the inclusive higher education institution. Conclusions. Taking into account the above-mentioned methodology, about 7 thousand UAH of funds of the general fund of the college budget are saved. The same marginal cost savings can be achieved through the support of funding for educational, club activities work and physical education rehabilitation, which should actively generate a program of the development of social activities of college students.
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Heydarian, Golnaz. "Designing Organizational Entrepreneurship Structural Equation Modeling with Emphasis on Knowledge Management and Empowerment of Employees." Journal of Management and Accounting Studies 6, no. 04 (September 29, 2020): 44–58. http://dx.doi.org/10.24200/jmas.vol6iss04pp44-58.
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Objective: The purpose of this research was to design an Organizational Entrepreneurship Structural Equation Modeling with emphasis on knowledge management and empowerment of employees. The statistical population consisted of the personnel of IranKhodro Company, totaling 1000 people. Methodology: Using the Cochran equation, the sample size was 278 people. Data were collected by Thomson Enterprise Standard Entrepreneurship Questionnaire (2002), Knowledge Management, Proust et al. (2000), and Empowerment of Speakers (1995), whose face and content validity was confirmed by 10 experts and its reliability was in a preliminary test. With 30 subjects, all of the variables evaluated were above 0.7, which has acceptable limit. Results: Descriptive and inferential statistical methods of structural equation analysis using Smart PLS software and regression test in SPSS software were used to analyze the data. Findings showed that knowledge management and its components affect organizational entrepreneurship. On the other hand, employee empowerment and its components also have a mutual positive and significant effect on organizational entrepreneurship. Conclusion: Therefore, according to the results of this study, it can be said that designing a knowledge-based structure at all levels of the country's organizations will be effective in improving the entrepreneurial status of these organizations, and in this regard, managers will play an important role as producers and national knowledge funds. Therefore, it is necessary that the top managers of IranKhodro Company be more concerned with the training and empowerment of their employees and one of the first activities to be considered by the managers of this organization and emphasized in different sections. Educational needs based on the acquisition of knowledge as one of the components of knowledge management and the establishment of continuing education programs for empowerment in different parts of IranKhodro Company, in order to empower the employee, will develop organizational entrepreneurship in this organization.
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Penmetsa, G., S. Pei, B. Sauer, J. A. Walsh, B. Feng, J. Walker, K. Douglas, and J. Clewell. "POS0262 IDENTIFYING EROSIVE DISEASE FROM RADIOLOGY REPORTS OF VETERANS WITH INFLAMMATORY ARTHRITIS USING NATURAL LANGUAGE PROCESSING." Annals of the Rheumatic Diseases 80, Suppl 1 (May 19, 2021): 353.2–354. http://dx.doi.org/10.1136/annrheumdis-2021-eular.1794.
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Background:The presence of erosive disease influences diagnosis, management, and prognosis in inflammatory arthritis (IA).Research of IA in large datasets is limited by a lack of methods for identifying erosions.Objectives:To develop methods for identifying articular erosions in radiology reports from veterans with IA.Methods:Included veterans had ≥2 ICD codes for ankylosing spondylitis (AS), psoriatic arthritis (PsA), or rheumatoid arthritis (RA) between 2005- 2019, in Veterans Affairs Corporate Data Warehouse. Chart review & annotation of radiology notes produced the reference standard, & identified erosion terms that informed classification rule development. A rule-based natural language processing (NLP) model was created & revised in training snippets. The NLP method was validated in an independent reference sample of IA patients at the snippet & patient levelsStepDescriptionNumber & example1 Radiology notesa.Select note titles potentially relevant to IAa. 35,141 notes titlesb.Extract notes with titles potentially related to IAb. 2,926,113 radiology notes2 Possible meaningful termsa.Compile list of root terms that may indicate erosiona. 11 root terms (i.e. ero*, pencil*cup, irreg*)b.Query radiology notes for root term variationsb. 1178 variations (i.e. erosion, erotic, erode)c.Select possible meaningful termsc. 179 possible terms (i.e. erosion, erode)3 Annotationa.Extract snippets^ containing possible meaningful termsa.5000 snippets from radiology notesb.Classify snippets according to: 1) Meaningful term, 2) Relevance to joint, 3) Attribution to IA, 4) Affirmationb.4068 classifications with 1017 snippets (in rounds of 50-417 snippets for NLP training & testing)4 Rule developmenta.Identify meaningful terms representing erosiona. 6 terms (pencil * cup, erosion, erosive, etc.)b.Exclude erosive processes irrelevant to joint(s)b. 28 irrelevant processes (i.e. gastric erosion)c. Exclude articular erosive processes not attributed to IAc. 5 non-IA processes IA (i.e. infection)d. Classify as affirmed/negated (erosion present/absent)d. 83 affirmation/negation rules5 NLP trainingDesign & revise NLP model until accuracy ≥90%6 rounds, 817 snippets (AS 417, RA 200, PsA 200)6 NLP testingTest NLP model200 snippets (AS 100, RA 50, PsA 50)7 Pt classificationa. Develop rules for classifying pts with discordant snippetsa. 5 rules developed in 368 ptsb. Build reference sample (pts classified as erosive or non-erosive via chart review)b. 30 IA pts (10 AS, 10 RA, 10 PsA)8 NLP validationValidate NLP model in reference sample at snippet level149 snippets (29 AS, 76 RA, 44 PsA)9 Method validationValidate methods (NLP+pt classification) at pt level30 IA pts (reference sample)pt= patient. ^Snippets include text containing 30 words before & after meaningful termsResults:In 168,667 veterans with IA, the mean age was 63.1 & 90.3% were male. Method development involved radiology note & erosion term selection, rule development, NLP model building, & method validation. The NLP model accuracy was 94.6% at the snippet level & 90.0% at the patient level, for all IA patients.Accuracy of methods.Conclusion:The methods accurately identify erosions from radiology reports of veterans with IA. They may facilitate a broad range of research involving cohort identification & disease severity stratificationReferences:[1]Walsh JA, et al. J Rheumatol. 2020;47(1):42-49Disclosure of Interests:Gopi Penmetsa: None declared, Shaobo Pei: None declared, Brian Sauer Grant/research support from: I have been an investigator on research contracts supported by Abbvie., Jessica A. Walsh Consultant of: AbbVie, Amgen, Janssen, Lilly, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Merck, Pfizer, Bingjian Feng Grant/research support from: Bing-Jian Feng reports funding and sponsorship to his institution on his behalf from Pfizer Inc., Regeneron Genetics Center LLC, and Astra Zeneca (UK). The PERCH software, for which Bing-Jian Feng is the inventor, has been non-exclusively licensed to Ambry Genetics for clinical genetic testing services and research., Jodi Walker Shareholder of: Abbvie and mutual funds containing various pharmaceutical companies, Employee of: Abbvie, Kevin Douglas Shareholder of: employed by Abbvie, Employee of: employed by Abbvie, Jerry Clewell Shareholder of: Own Abbvie Shares and mutual funds that hold pharmaceutical and other health care stocks, Employee of: I am current Abbvie Inc employee and past employee of Eli Lilly co
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Hontar, Daria, Nataliya Opeshko, and Svitlana Kolodizieva. "Forecasting the development of leasing market (on the example of Ukraine)." Problems and Perspectives in Management 14, no. 4 (December 23, 2016): 264–72. http://dx.doi.org/10.21511/ppm.14(4-1).2016.16.
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The purpose of the study consists in the investigation of the leasing market and determining the prospects of its development in Ukraine, which will make possible for lessors to justify the choice of their strategies. There were forecasted values of the analyzed indicators of leasing market for the following three periods: the third quarter of 2016, fourth quarter of 2016, first quarter of 2017. It was proposed to calculate the integral development index of leasing services in Ukraine based on the amount of leasing companies in Ukraine, the amount of financial leasing contracts, the share of long-term lease agreements, the value of financial leasing contracts, the proportion of borrowed funds in the structure of leasing transactions financing, the share reward the lessor for the leased property in the structure of the lease payments, in the amount of leasing companies in Ukraine, the amount of financial leasing contracts, the share of long-term lease agreements, the value of financial leasing contracts, the proportion of borrowed funds in the structure of leasing transactions financing, the share reward the lessor for the leased property in the structure of the lease payments. The authors defined the growth of Ukrainian leasing market in the first quarter of 2017. The proposed integral development index is applicable both on regional and international level. The results of study can be used for substantiation of the choice of lessors’ strategies by developing alternative strategic decisions, the optimal use of which should lead to a further growth of the leasing market. Keywords: leasing, leasing companies, methods of multivariate statistical analysis, forecasting, market of leasing services. JEL Classification: C53, G17, G21
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Podlewska, Sabina, and Rafał Kurczab. "Mutual Support of Ligand- and Structure-Based Approaches—To What Extent We Can Optimize the Power of Predictive Model? Case Study of Opioid Receptors." Molecules 26, no. 6 (March 14, 2021): 1607. http://dx.doi.org/10.3390/molecules26061607.
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The process of modern drug design would not exist in the current form without computational methods. They are part of every stage of the drug design pipeline, supporting the search and optimization of new bioactive substances. Nevertheless, despite the great help that is offered by in silico strategies, the power of computational methods strongly depends on the input data supplied at the stage of the predictive model construction. The studies on the efficiency of the computational protocols most often focus on global efficiency. They use general parameters that refer to the whole dataset, such as accuracy, precision, mean squared error, etc. In the study, we examined machine learning predictions obtained for opioid receptors (mu, kappa, delta) and focused on cases for which the predictions were the most accurate and the least accurate. Moreover, by using docking, we tried to explain prediction errors. We attempted to develop a rule of thumb, which can help in the prediction of compound activity towards opioid receptors via docking, especially those that have been incorrectly predicted by machine learning. We found out that although the combination of ligand- and structure-based path can be beneficial for the prediction accuracy, there still remain cases that cannot be reliably predicted by any available modeling method. In addition to challenging ligand- and structure-based predictions, we also examined the role of the application of machine-learning methods in comparison to simple statistical methods for both standard ligand-based representations (molecular fingerprints) and interaction fingerprints. All approaches were confronted in both classification (where compounds were assigned to the group of active and inactive group constructed on the basis of Ki values) and regression (where exact Ki value was predicted) experiments.
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Matantseva, O. Yu, I. S. Kazantsev, M. A. Nizov, and I. V. Spirin. "Methodological Foundations of Renewal and Expansion of Car Fleet." World of Transport and Transportation 19, no. 4 (January 12, 2022): 48–61. http://dx.doi.org/10.30932/1992-3252-2021-19-4-6.
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Currently, Russian international road transport carriers do not have sufficient potential to successfully compete with their foreign partners. The main reasons for this are significant deterioration of the car fleet and its non-compliance to modern environmental requirements, lack of own funds for timely renovation and development of the motor transport fleet, as well as systemic lag in development of transportation technologies and their logistics support.The objective of the article is to substantiate the choice of rational measures to solve the problem of expanded reproduction of car fleet used in international road haulage. The methodology used in preparation of the article is based on the use of general scientific methods in combination with special methods, including the analysis of statistical data on international road haulage, a comparative analysis of the state of the car fleet of Russian carriers, considering the basic conditions and operational characteristics, classification of the fleet of trucks based on typification of their operational characteristics with subsequent subdivision of this fleet into three main groups, an overview analysis and benchmarking of foreign operating experience and future development of car fleet, an analysis of the economic and legal possibilities of raising funds for renewal of car fleet.The article examines and studies: a) urgency of solving the problem of renewal and expansion of the car fleet used by Russian carriers in international road transportation; b) foreign experience and trends in development of fleet used for international haulage; c) the main directions of providing economic opportunities for transition to expanded renewal of vehicles; d) analysis of the legal possibilities of providing public support for expanded reproduction of the motor transport fleet of Russian international road carriers including through the use of public-private partnerships.Based on the results of the study, proposals have been developed aimed at ensuring renewal and expansion of car fleet and increasing the efficiency of international road haulage operations.
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Anđelković, Goran, Ivan Samardžić, and Duško Đukić. "Research possibilities of extreme hydrological phenomena in Serbia in the function of climate change adaptation." Zbornik radova - Geografski fakultet Univerziteta u Beogradu, no. 68 (2020): 5–21. http://dx.doi.org/10.5937/zrgfub2068005a.
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Many natural disasters are nowadays interpreted as consequences of climate changes. They represent a form of extreme occurrences, i.e. deviation of normal conditions. They are recognized as deviation in the intensity, frequency or spatial distribution of a phenomenon from normal conditions. Thus, they represent a threat to ecosystems, economic stability and can lead to social and political problems. So far, there is no generally accepted classification of the disasters. This paper starts from the fact that a special grouping represents disasters that are happening as result of interaction of atmosphere and hydrosphere, due to the mutual interconnections. It is considered that the genetic grouping of climatehydrological extremes represents the majority of natural disasters. In the near past, the Southeast Europe countries were exposed to hydrological extremes whose causes were atmospheric occurrences. Due to the region's compactness and similar geographical conditions, these countries were sensitive to similar phenomena. The paper discusses about the hydrological extremes in Serbia that represents the result of extreme climatic conditions in relation to the consequences they have in the geographical surrounding. A total of 19 extreme hydrological phenomena have been outlined in this paper. Based on the level of destructiveness, they are classified into five categories: exceptional, significant, dangerous, strong and catastrophic. Each of them can be identified using statistical thresholds as physical parameters. The type of distribution basically determines the way in which thresholds are calculated. Four methods for their detection are outlined: the normal distribution method, the peaks method, the deciles method and the recurrence interval method. Defining each unfavorable phenomenon, their classification and determination of methods for detection are conditions for recognition and announcement. This allows an adequate reaction from the social community and the risks of disasters are reduced.
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Tang, Wenzhe, and Fang Zhang. "Research on Semisupervised Affective Interaction Technology in Immersive Virtual Teaching Environment." Wireless Communications and Mobile Computing 2022 (May 28, 2022): 1–7. http://dx.doi.org/10.1155/2022/2216638.
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The separation of time and space in immersive virtual teaching makes students unable to realize emotional communication, which may affect students’ mental health. In recent years, the use of affective computing technology to solve the problem of affective loss in distance education has become a key research topic. In order to realize the problem of emotion interaction in immersive virtual teaching, a semisupervised support vector machine- (SVM-) based affective interaction model was proposed. First, the natural language sequences of students in the virtual teaching environment are preprocessed using a statistical-based framing method, and mutual information and expected cross-entropy are used as feature selection methods. Then, a vector space model based on TF/IDF feature term weights is proposed to implement the feature vector representation of natural language sequences. Finally, after the constructed sentiment space, a semisupervised SVM is employed as the classifier to complete the affective interaction computation. The experimental results of emotion classification show that the proposed model is able to determine and understand the emotional state more accurately than other traditional models and significantly improves the training speed. In addition, the proposed model can provide emotional encouragement or emotional compensation according to the specific emotional state of the learner.
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Smirnov, V. V. "Analyzing trade and financial relations in Russia today." Finance and Credit 26, no. 8 (August 28, 2020): 1703–30. http://dx.doi.org/10.24891/fc.26.8.1703.
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Subject. The article discusses trading and financial relations of today’s Russia. Objectives. The article is to determine requirements for trading and financial relations to progress in Russia today and evaluate how they influence the economic growth. Methods. The study is based on the systems approach and the statistical analysis. Results. Having analyzed trading and financial relations, I found what can give an impetus to the contemporary economy in Russia, i.e. oil prices, related risks. The article demonstrates that government bonds (federal loan bonds) cushion and set off an increase in the foreign exchange rate. The dynamics of the oil price and the issue of federal loan bonds shape the environment where trading and financial relations evolve in Russia today, i.e. export prices for natural resources outgrowing prices for some commodities; a stalling growth in the acquisition of financial assets, debt instruments and a growth in liabilities, equity and shares of mutual funds; a growing pace of long positions of forward, futures, options contracts due to a slow down in short positions; rising pace of official reserve assets. As long as the international trade slows down and the global recession begins, the existing trading and financial relations resulted in a palpable economic growth. Conclusions and Relevance. Opportunities for the development of trade and financial relations in contemporary Russia are conditioned by the changing world order, which determines the dynamics of economic growth. The findings expand the knowledge and create new competencies of governmental authorities when making managerial decisions to ensure the effective design of the Russian economy in terms of the current trading and financial policy.
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Sukach, Olena. "Risk Minimization as a Tool to Ensure the Banks Security." Modern Economics 22, no. 1 (August 27, 2020): 90–94. http://dx.doi.org/10.31521/modecon.v22(2020)-14.
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Introduction. The banking system of Ukraine, in the conditions of the current crisis, turned out to be untenable to quickly adapt to structural changes in the economy, which manifested itself in the absence of an effective system for managing banking risks. Further instability in the financial market will increase the negative impact on the level of financial security of the banking sector. Today there is a need for the formation of preventive measures for risk management, prevention of their occurrence and minimization, which will contribute to the safe position of the bank. Purpose. The main purpose of the study is to identify modern methods and approaches regarding the classification of banking risks and substantiation of proposals for their minimization, as well as ensuring the financial security of the banking sector in Ukraine. The main research methods are methods of quantitative, qualitative analysis and statistical analysis, as well as methods of expert assessments. Results. Summarizing the results of research by scientists, it was stated that banking risk is the likelihood of losses in the form of loss of assets, shortfall in planned income, or the appearance of additional costs as a result of the bank’s financial transactions. The main results of the banking system of Ukraine in 2019 and the dynamics for 7 months of 2020 are determined. Despite the positive trends of 2019, there is a risk of new problem loans due to non-conservative policy of banks in the growing segment of consumer lending. Modern practice shows that any credit product of a bank leads to the formation of a certain credit risk, and until the client returns the received resources, the bank is forced to form reserves for possible losses from non-repayment of funds. Conclusions. Сonclusions are drawn regarding the credit risk management tools. Based on the results of the study, the author’s approach to the classification of risks and reasonable approaches to their management are presented. In particular, it has been proved that during the formation of risk management tools, namely credit risk, and ensuring the bank’s security, it is necessary to take into account that risk assessment indicators should consider not only the ratio between assets and liabilities, but also their maturity dates.
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Ermilina, D. A., and A. V. Borschevа. "Life and survival: sources of working capital of the Soviet and Russian economies." Russian Journal of Industrial Economics 11, no. 4 (December 25, 2018): 368–76. http://dx.doi.org/10.17073/2072-1633-2018-4-368-376.
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Working capital plays an important role in the economic life of the enterprise in particular and the prosperous development of the state as a whole. At the same time, they themselves have a heterogeneous structure: the ratio of own and borrowed funds in their composition can seriously affect the financial sustainability of economic entities and industries, the possibilities of their modernization and innovative development. The presence of a sufficient number of working capital allows the company to pursue an independent economic policy, while the loss of its own and borrowed working capital is fraught with the most serious consequences.In modern conditions, the slowdown in economic growth, problems in the banking system, inflation, currency fluctuations lead to the fact that most enterprises, especially the manufacturing sector of the economy, have difficulty attracting working capital and managing it.The purpose of this study is to analyze the structure of the sources of the working capital of the economy of the Soviet and post-Soviet periods. Within the framework of the goal, the article suggests a method for classifying all sources of working capital of the Russian economy into own and borrowed funds in order to conduct a comparative analysis of the structure of sources of circulating assets of the Soviet and Russian economies. When performing the study, the methods of system analysis, classification and generalization, logical and statistical analysis were used.The article convincingly proved that the enterprises of the Russian economy are characterized by massive lack of working capital and a deep deformation of the structure of the sources of their formation. On the contrary, the structure of sources for the formation of working capital of the economy of the Soviet period is more balanced, as evidenced by the financial performance of that period. The absence in the foreseeable future of a comprehensive working capital management program will lead the Russian economy to even deeper degradation.
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Holguín-Londoño, Mauricio, Oscar Cardona-Morales, Edgar F. Sierra-Alonso, Juan D. Mejia-Henao, Álvaro Orozco-Gutiérrez, and German Castellanos-Dominguez. "Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis." Mathematical Problems in Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/7906834.
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Vibration and acoustic analysis actively support the nondestructive and noninvasive fault diagnostics of rotating machines at early stages. Nonetheless, the acoustic signal is less used because of its vulnerability to external interferences, hindering an efficient and robust analysis for condition monitoring (CM). This paper presents a novel methodology to characterize different failure signatures from rotating machines using either acoustic or vibration signals. Firstly, the signal is decomposed into several narrow-band spectral components applying different filter bank methods such as empirical mode decomposition, wavelet packet transform, and Fourier-based filtering. Secondly, a feature set is built using a proposed similarity measure termed cumulative spectral density index and used to estimate the mutual statistical dependence between each bandwidth-limited component and the raw signal. Finally, a classification scheme is carried out to distinguish the different types of faults. The methodology is tested in two laboratory experiments, including turbine blade degradation and rolling element bearing faults. The robustness of our approach is validated contaminating the signal with several levels of additive white Gaussian noise, obtaining high-performance outcomes that make the usage of vibration, acoustic, and vibroacoustic measurements in different applications comparable. As a result, the proposed fault detection based on filter bank similarity features is a promising methodology to implement in CM of rotating machinery, even using measurements with low signal-to-noise ratio.
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Khimich, S. D., I. V. Stoianovskyi, and O. M. Chemerys. "Problems of terminology and clinical coding of necrotizing fasciitis." Paediatric Surgery. Ukraine, no. 1(74) (March 30, 2022): 14–19. http://dx.doi.org/10.15574/ps.2022.74.14.
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Purpose - to analyze the typical defects of the formulation of the diagnosis of necrotizing fasciitis (NF), to verify the lexically correct term NF, to develop proposals for the correct coding of NF according to ICD-10-AM. Materials and methods. The medical records of 150 patients who during 1999-2021 were treated in two hospitals of Lviv City (Ukraine) for necrotizing fasciitis was analyzed. Compared diagnoses when referred to the hospital, preliminary and final clinical diagnoses, preoperative and postoperative diagnoses, recorded their statistical codes for ICD-10. An analysis of Ukrainian and Russian-language surgical publications available in Ukraine for the period from 1985 to 2021 on the keywords «surgical soft tissue infection», «necrotizing fasciitis», «soft tissue necrosis». Results. In 142 (95.0%) of the 150 patients operated on for NF, the diagnosis was not correctly formulated during referral. Most often NF was directed and in the initial stages was treated under the guise of other diagnoses: «phlegmon», «erysipelas», «thrombophlebitis», «gangrene», «perianal abscess». NF was suspected by the surgeon prior to the first surgery only in 53 (35.33%) patients. In other cases, it was diagnosed intraoperatively or during repeated interventions. Codes corresponding to other forms of surgical infection were often used for statistical coding of NF. We also worked on lexical variants of the term «necrotizing fasciitis» in Ukrainian language. Conclusions. It was worked out the most correct terminologically Ukrainian equivalent of the diagnosis «necrotizing fasciitis». For statistical coding of NF, it should be designated as the main active disease by code M72.6. The use of a unified term and statistical coding will allow in the future to form a single within the state diagnostic-related group for fair reimbursement of funds to health care providers for treated cases of NF. The research was carried out in accordance with the principles of the Helsinki declaration. The study protocol was approved by the Local ethics committee of all participating institutions. The informed consent of the patient was obtained for conducting the studies. No conflict of interests was declared by the authors. Key words: necrotizing fasciitis, terminology, international classification of diseases.
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Laponoh, Danyil V. "FEATURES OF THE USE OF PUBLIC-PRIVATE PARTNERSHIPS IN THE PRACTICE OF ROAD TRANSPORT SERVICES." Management 32, no. 2 (April 16, 2021): 84–92. http://dx.doi.org/10.30857/2415-3206.2020.2.6.
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Background and objectives. Public-private partnership (PPP) is one of the most popular forms of cooperation between the state and business in the world. For Ukraine, PPP is one of the most promising ways to attract investment in the existing state and municipal infrastructure. The Law of Ukraine "On Public-Private Partnership" (2010) allows the implementation of projects in the format of the classic PPP. Most projects involved the development of infrastructure facilities and mining, which is typical for this kind of cooperation between the state and businessMethods. The study used: expert, statistical, comparative, scenario analysis; analysis of empirical data using methods of grouping, generalization, classification methods.Findings. The components of PPP relations are defined, the criteria for the classification of its forms, the essence and economic content of the category "public-private partnership", the features of public-private partnership in the market of road transport services in Ukraine are substantiated. The qualitative analysis of 111 concession projects has allowed to reveal the regularity and to present the variant of possible combination of experts' indications at certain parameters. Mean values and standard deviations of the expert testimonies were determined and distributions of the obtained data array of 111 concession PPP projects were constructed. The definition of the "quality" of expert assessments and evaluation of the effectiveness of 111 PPP projects for the provision of road transport services is formed.Conclusion. The components for public-private partnership in the market of road transport services have been defined: PPP implies a contractual form (agreements, contracts, etc.), in which the rights and obligations of each party are clearly defined; implementation of projects in the market of road transport services implies mutual economic benefit for all project participants through the best interaction, focused on better results for lower cost; public-private partnership is characterized by increased.
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Sutrisno, Paulina, and Kashan Pirzada. "Are CEO Overconfidence and Audit Firm Size Related To Tax Avoidance?" GATR Accounting and Finance Review 5, no. 2 (September 30, 2020): 56–65. http://dx.doi.org/10.35609/afr.2020.5.2(3).
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Objective – This study aims to examine whether audit firm size mitigates the relationship between CEO overconfidence and tax avoidance. CEO overconfidence has the characteristics of a very high level of self-confidence which influences the pattern of thought and the way they make strategic decisions. CEO overconfidence has a tendency to avoid taxes. It aims to show competence in tax management and raise funds for investment. External party oversight, such as by audit firms, will mitigate the relationship between CEO overconfidence and tax avoidance through an attitude of independence, as well as competence and function as examiners of the company's financial reporting. Methodology/Technique – This study uses a sample of Indonesian non-financial companies in the period 2013-2017. This study analyses the data with statistical methods using linear multiple regression. Findings – The results of this study indicate that CEO overconfidence is positively related to tax avoidance, while audit firm size is negatively related to tax avoidance. However, this study has not been able to prove the influence of audit firm size on the relationship between CEO overconfidence and tax avoidance. Type of Paper: Empirical Keywords: CEO overconfidence; Tax Avoidance; Audit Firm Size; Big 4; Book Tax Difference. Reference to this paper should be made as follows: Sutrisno, P; Pirzada, K. 2020. Are CEO Overconfidence and Audit Firm Size Related To Tax Avoidance?, Acc. Fin. Review 5(2): 72 – 81. https://doi.org/10.35609/afr.2020.5.2(3) JEL Classification: M41, M49.
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Vrabková, Iveta, and Václav Friedrich. "Gaps in performance: benchmarking of the Czech and Slovak city libraries." Library Management 38, no. 4/5 (June 13, 2017): 263–75. http://dx.doi.org/10.1108/lm-11-2016-0085.
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Purpose The purpose of this paper is to identify gaps in performance of city libraries from the Czech and from the Slovak Republic engaged in the project Benchmarking of Libraries. The subject of research consists of input and output performance variables of selected 51 city libraries for the period of 2011-2015 and their mutual dependence and influence. Design/methodology/approach To analyse relationships among ten input and four output variables, the correlation and regression analyses were used. Regression analysis was focussed on four output variables – numbers of physical visitors of libraries, numbers of loans, numbers of visitors using the internet in the library, and numbers of registered readers. Interpretation of results was supplemented with classification multidimensional analysis Chi-square automatic interaction detection. Findings Findings reveal that besides others the significant gap in performance was represented by library additions, which means the renewal of library collections. Performance differences were also found between city libraries in the Czech Republic and those in the Slovak Republic. Research limitations/implications This paper evaluates gaps in the performance on representative sample of city libraries. The number of population served among individual selected 51 libraries ranges between 15 and 35 thousand inhabitants. Analysed data are from years 2011-2015. Originality/value The paper analyses, by using statistical methods, data that are generated within the benchmarking project. This methodology proves and reveals causalities among performance indicators of city libraries in an unconventional way.
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Kutsyk, Petro. "STATISTICAL ANALYSIS OF THE RECEIVABLES OF ENTERPRISES OF HOUSING AND COMMUNAL SERVICES: ACCOUNTING SUPPORT." Three Seas Economic Journal 1, no. 3 (December 18, 2020): 53–58. http://dx.doi.org/10.30525/2661-5150/2020-3-9.
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The branch characteristics of activity of the enterprises of housing and communal services are defined with features of management of receivables: its absence of alternative concerning partially rendered services to consumers that would directly influence reduction of incomes of the enterprise of housing and communal services; its impossibility of resale of services, lack of clear control over the quality of services provided and its price, which leads to dissatisfaction with the social needs of the population; its lack of flexible discounts for honest payers of housing and communal services. The analysis of the structure of receivables of the population for the consumed housing and communal services of the enterprises of the Lviv region during April-August 2020 is carried out. It is established that the use of inefficient methods of housing management leads to low payment discipline of buyers, which contributes to the deterioration of the financial condition of the industry as a whole. Therefore, methods of accelerating the payment of receivables with appropriate reporting on the quality of services provided should be actively used. The dynamics of the amount of funds for which agreements on debt restructuring for housing and communal services have been concluded, and the amount repaid by consumers-debtors indicates increased activities on concluding contracts and gradual repayment of debts by consumers. In case of overdue receivables for housing and communal services, the consumer should be reminded of the need to pay the debt in different ways. These are in the form of a re-receipt, correspondent (send by registered mail on demand), SMS, or call, or direct visit of the housing and communal services department representative to the service object, and finding out the cause of existing receivables, the order of criteria for their classification into doubtful and bad types of receivables. The purpose of the research is to identify sectorial characteristics of housing and communal services, which determine the features of receivables management and improve the methodology of statistical analysis of receivables to identify causes of late payment of housing and communal services and ways to motivate consumers to repay debts. Methodology. The method of statistical analysis of receivables is developed to be carried out in three stages: analysis of the structure of receivables; analysis of the dynamics of receivables for communal services; analysis of the effectiveness of receivables restructuring. Results. The following stages of statistical analysis of receivables for housing and communal services are offered. Analysis of the structure of receivables to determine the types of housing and communal services for which we observe the largest and smallest share in total is proposed. Analysis of the dynamics of receivables for communal services to determine trends in indicators in the regional aspect is suggested. Analysis of the effectiveness of the restructuring receivables (provides for the calculation of the increase in the number of agreements on debt restructuring and assessment in the dynamics of repayment of these receivables) is proffered. Practical implications. We identified effective management methods of receivables of housing and communal services that improves the financial condition of the industry as a whole. Value/originality. The statistical analysis of the receivables of enterprise of housing and communal services has been further developed.