Journal articles: 'One stage selection'

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Carter, Nancy J., and G. David Faulkenberry. "A model-based sample selection procedure for one-stage sampling." Communications in Statistics - Theory and Methods 18, no. 8 (1989): 3135–47. http://dx.doi.org/10.1080/03610928908830082.

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Settembrini, Fernanda, Stefano Bonomi, and Chiara Gregorelli. "Patient Selection and Aesthetic Outcomes in One-Stage versus Two-Stage Implant Breast Reconstruction." Plastic and Reconstructive Surgery 129, no. 2 (February 2012): 364e—366e. http://dx.doi.org/10.1097/prs.0b013e318230be38.

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Dehal, Ahmed, Amanda N. Graff-Baker, Brooke Vuong, Daniel Nelson, Shu-Ching Chang, Melanie Goldfarb, and Anton J. Bilchik. "Current Imaging Modalities Understage One-Third of Patients with Stage I Rectal Cancer: Implications for Treatment Selection." American Surgeon 84, no. 10 (October 2018): 1589–94. http://dx.doi.org/10.1177/000313481808401010.

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Accurate preoperative clinical staging is essential to optimize the treatment of rectal cancer. Primary surgical resection is typically indicated for stage I disease, whereas neoadjuvant therapy is recommended for stages II and III. The objective of this study is to examine the accuracy of clinical staging using current imaging modalities in predicting pathologic stage and, thus, selecting appropriate treatment. Adult patients with nonmetastatic rectal cancer who underwent primary surgical resection were identified from the National Cancer Database between 2006 and 2014. Data on clinical and pathologic staging was obtained. Kappa index was used to determine the correlation between clinical and pathologic staging. A total of 13,175 patients were identified. The correlation between clinical and pathologic staging was 69 per cent for stage I (31% upstaged) (Kappa 0.54, P < 0.001). One-third of patients who were clinically staged as stage I, and were therefore treated with primary surgical resection, had pathologic stage II or III disease. Based on their clinical staging, those patients did not receive the neoadjuvant therapy recommended by present guidelines. Where accurate clinical staging is in doubt, oncologists should carefully examine the quality of staging modality and perhaps consider multimodal imaging using both endorectal ultrasound and MRI.

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Izdebski, Mariusz, Ilona Jacyna-Gołda, Marcin Nivette, and Emilian Szczepański. "Selection of a fleet of vehicles for tasks based on the statistical characteristics of their operational parameters." Eksploatacja i Niezawodnosc - Maintenance and Reliability 24, no. 3 (May 20, 2022): 407–18. http://dx.doi.org/10.17531/ein.2022.3.2.

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The article presents a method of selecting a fleet of vehicles with a homogeneous structure for tasks based on the statistical characteristics of their operational parameters. The selection of a vehicle fleet for tasks is one of the stages of vehicle fleet management in transport companies. The selection of a vehicle fleet for tasks has been defined as the allocation of a vehicle model to a given company, which is associated with the unification of the vehicle fleet to one specific type. The problem of selecting a fleet of vehicles has been presented in a multi-criteria approach. The operational parameters assessing the selection of vehicles for the tasks are mileage and the number of days to the first and subsequent failure, and vehicle maintenance costs. The developed method of selecting a fleet of vehicles for the tasks consists of two stages. In the first stage, the average operating parameter values are determined using statistical inference. In the second stage, using the MAJA method, a unified model of the fleet of vehicles operating in the enterprise is established.

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Longin, C. Friedrich H., H. Friedrich Utz, Jochen C. Reif, Wolfgang Schipprack, and Albrecht E. Melchinger. "Hybrid maize breeding with doubled haploids: I. One-stage versus two-stage selection for testcross performance." Theoretical and Applied Genetics 112, no. 5 (January 25, 2006): 903–12. http://dx.doi.org/10.1007/s00122-005-0192-z.

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Roper, Jack, and Tom Stone. "Natural Selection." Industrial Vehicle Technology International 27, no. 2 (June 2019): 16–22. http://dx.doi.org/10.12968/s1471-115x(23)70532-1.

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ONE OF THE MOST STRIKING CONCEPTS UNVEILED AT BAUMA MUNICH IN APRIL WAS THE WORLD'S FIRST NATURAL-GAS POWERED CONSTRUCTION VEHICLE. CASE'S PROJECT TETRA WAS SOMETHING OF A SHOW STOPPER, BUT – AS DESIGN DIRECTOR DAVID WILKIE TELLS iVT IN THIS EXCLUSIVE INTERVIEW – IT'S PART OF A NEW STAGE OF EVOLUTION AT CNH INDUSTRIAL THAT IS ONLY JUST BEGINNING

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Natarajan, Sijesh, Jayampathi Basnayake, Xianming Wei, and Prakash Lakshmanan. "High-Throughput Phenotyping of Indirect Traits for Early-Stage Selection in Sugarcane Breeding." Remote Sensing 11, no. 24 (December 10, 2019): 2952. http://dx.doi.org/10.3390/rs11242952.

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One of the major limitations for sugarcane genetic improvement is the low heritability of yield in the early stages of breeding, mainly due to confounding inter-plot competition effects. In this study, we investigate an indirect selection index (Si), developed based on traits correlated to yield (indirect traits) that were measured using an unmanned aerial vehicle (UAV), to improve clonal assessment in early stages of sugarcane breeding. A single-row early-stage clonal assessment trial, involving 2134 progenies derived from 245 crosses, and a multi-row experiment representative of pure-stand conditions, with an unrelated population of 40 genotypes, were used in this study. Both experiments were screened at several stages using visual, multispectral, and thermal sensors mounted on a UAV for indirect traits, including canopy cover, canopy height, canopy temperature, and normalised difference vegetation index (NDVI). To construct the indirect selection index, phenotypic and genotypic variance-covariances were estimated in the single-row and multi-row experiment, respectively. Clonal selection from the indirect selection index was compared to single-row yield-based selection. Ground observations of stalk number and plant height at six months after planting made from a subset of 75 clones within the single-row experiment were highly correlated to canopy cover (rg = 0.72) and canopy height (rg = 0.69), respectively. The indirect traits had high heritability and strong genetic correlation with cane yield in both the single-row and multi-row experiments. Only 45% of the clones were common between the indirect selection index and single-row yield based selection, and the expected efficiency of correlated response to selection for pure-stand yield based on indirect traits (44%–73%) was higher than that based on single-row yield (45%). These results highlight the potential of high-throughput phenotyping of indirect traits combined in an indirect selection index for improving early-stage clonal selections in sugarcane breeding.

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Liogienė, Tatjana, and Gintautas Tamulevičius. "Multi-Stage Recognition of Speech Emotion Using Sequential Forward Feature Selection." Electrical, Control and Communication Engineering 10, no. 1 (July 1, 2016): 35–41. http://dx.doi.org/10.1515/ecce-2016-0005.

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Abstract The intensive research of speech emotion recognition introduced a huge collection of speech emotion features. Large feature sets complicate the speech emotion recognition task. Among various feature selection and transformation techniques for one-stage classification, multiple classifier systems were proposed. The main idea of multiple classifiers is to arrange the emotion classification process in stages. Besides parallel and serial cases, the hierarchical arrangement of multi-stage classification is most widely used for speech emotion recognition. In this paper, we present a sequential-forward-feature-selection-based multi-stage classification scheme. The Sequential Forward Selection (SFS) and Sequential Floating Forward Selection (SFFS) techniques were employed for every stage of the multi-stage classification scheme. Experimental testing of the proposed scheme was performed using the German and Lithuanian emotional speech datasets. Sequential-feature-selection-based multi-stage classification outperformed the single-stage scheme by 12–42 % for different emotion sets. The multi-stage scheme has shown higher robustness to the growth of emotion set. The decrease in recognition rate with the increase in emotion set for multi-stage scheme was lower by 10–20 % in comparison with the single-stage case. Differences in SFS and SFFS employment for feature selection were negligible.

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Gupta, Shanti S., and Klaus J. Miescke. "Bayesian look ahead one-stage sampling allocations for selection of the best population." Journal of Statistical Planning and Inference 54, no. 2 (September 1996): 229–44. http://dx.doi.org/10.1016/0378-3758(95)00169-7.

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Khan, Ayesha, George Hicks, Caroline Pogson, and Wail Al-Sarakbi. "Patient selection and outcome in one stage dermal sling assisted immediate breast reconstruction." European Journal of Surgical Oncology (EJSO) 43, no. 5 (May 2017): S47. http://dx.doi.org/10.1016/j.ejso.2017.01.182.

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Jamshidy, Ladan, Hamid Reza Mozaffari, Payam Faraji, and Roohollah Sharifi. "Accuracy of the One-Stage and Two-Stage Impression Techniques: A Comparative Analysis." International Journal of Dentistry 2016 (2016): 1–5. http://dx.doi.org/10.1155/2016/7256496.

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Introduction. One of the main steps of impression is the selection and preparation of an appropriate tray. Hence, the present study aimed to analyze and compare the accuracy of one- and two-stage impression techniques. Materials and Methods. A resin laboratory-made model, as the first molar, was prepared by standard method for full crowns with processed preparation finish line of 1 mm depth and convergence angle of 3-4°. Impression was made 20 times with one-stage technique and 20 times with two-stage technique using an appropriate tray. To measure the marginal gap, the distance between the restoration margin and preparation finish line of plaster dies was vertically determined in mid mesial, distal, buccal, and lingual (MDBL) regions by a stereomicroscope using a standard method. Results. The results of independent test showed that the mean value of the marginal gap obtained by one-stage impression technique was higher than that of two-stage impression technique. Further, there was no significant difference between one- and two-stage impression techniques in mid buccal region, but a significant difference was reported between the two impression techniques in MDL regions and in general. Conclusion. The findings of the present study indicated higher accuracy for two-stage impression technique than for the one-stage impression technique.

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Djellali, Hayet, Nacira Ghoualmi-Zine, and Souad Guessoum. "Hybrid adapted fast correlation FCBF-support vector machine recursive feature elimination for feature selection." Intelligent Decision Technologies 14, no. 3 (September 29, 2020): 269–79. http://dx.doi.org/10.3233/idt-190014.

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This paper investigates feature selection methods based on hybrid architecture using feature selection algorithm called Adapted Fast Correlation Based Feature selection and Support Vector Machine Recursive Feature Elimination (AFCBF-SVMRFE). The AFCBF-SVMRFE has three stages and composed of SVMRFE embedded method with Correlation based Features Selection. The first stage is the relevance analysis, the second one is a redundancy analysis, and the third stage is a performance evaluation and features restoration stage. Experiments show that the proposed method tested on different classifiers: Support Vector Machine SVM and K nearest neighbors KNN provide a best accuracy on various dataset. The SVM classifier outperforms KNN classifier on these data. The AFCBF-SVMRFE outperforms FCBF multivariate filter, SVMRFE, Particle swarm optimization PSO and Artificial bees colony ABC.

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Bertozzi, Nicolò, Marianna Pesce, Pierluigi Santi, and Edoardo Raposio. "One-Stage Immediate Breast Reconstruction: A Concise Review." BioMed Research International 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/6486859.

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Background. One-stage direct-to-implant immediate breast reconstruction (IBR) is performed simultaneously with breast cancer resection. We explored indications, techniques, and outcomes of IBR to determine its feasibility, safety, and effectiveness.Material and Methods. We reviewed the available literature on one-stage direct-to-implant IBR, with or without acellular dermal matrix (ADM), synthetic mesh, or autologous fat grafting. We analyzed the indications, preoperative work-up, surgical technique, postoperative care, outcomes, and complications.Results. IBR is indicated for small-to-medium nonptotic breasts and contraindicated in patients who require or have undergone radiotherapy, due to unacceptably high complications rates. Only patients with thick, well-vascularized mastectomy flaps are IBR candidates. Expandable implants should be used for ptotic breasts, while anatomical shaped implants should be used to reconstruct small-to-medium nonptotic breasts. ADMs can be used to cover the implant during IBR and avoid muscle elevation, thereby minimizing postoperative pain. Flap necrosis, reoperation, and implant loss are more common with IBR than conventional two-staged reconstruction, but IBR has advantages such as lack of secondary surgery, faster recovery, and better quality of life.Conclusions. IBR has good outcomes and patient-satisfaction rates. With ADM use, a shift from conventional reconstruction to IBR has occurred. Drawbacks of IBR can be overcome by careful patient selection.

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Zubanov, A. M., N. I. Kokonkov, and P. D. Shirkov. "One-stage Rosenbrock method with complex coefficients and automatic selection of the time step." Mathematical Models and Computer Simulations 3, no. 5 (September 17, 2011): 596–603. http://dx.doi.org/10.1134/s2070048211050139.

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Jenny, Jean-Yves, Bruno Barbe, Alain Cazenave, Olivier Roche, and Philippe Massin. "Patient selection does not improve the success rate of infected TKA one stage exchange." Knee 23, no. 6 (December 2016): 1012–15. http://dx.doi.org/10.1016/j.knee.2016.09.002.

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Chen, Hongjie, Jiahua Zhu, and Wei Lu. "Optimized selection of one- and two-stage ejectors under design and off-design conditions." Energy Conversion and Management 173 (October 2018): 743–52. http://dx.doi.org/10.1016/j.enconman.2018.06.113.

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Susetyoko, Ronny. "Pemodelan Regresi Logistik Biner dan Ordinal Pada Proses Seleksi Mahasiswa Baru Program D3KPLN PENS." AITI 15, no. 1 (February 15, 2018): 56–66. http://dx.doi.org/10.24246/aiti.v15i1.56-66.

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Starting in 2016, Politeknik Elektronika Negeri Surabaya (PENS) accept new students D3KPLN. D3KPLN scheme is a joint program between PENS with PT. PLN(Persero) as a form of link and match between higher education and industry needs. In the program, student candidates must go through five stages of selection, namely: academic potential test (stage-1), psychotest (stage-2), physical test (stage-3), medical tests (stage 4), and interview ( stage-5). To know the probability characteristics of the selection process generally used ordinal logistic regression model. As for knowing the accepted probability characteristics at each stage of selection used binary logistic regression model. Based on testing at each stage, the academic potential test scores are not the only determinants of acceptance as a student D3KPLN. However, other factors such as physical condition, medical test results, and interviews were also decisive. In general, theacademic potential test scores significantly affect the results of the selection phase by phase (phase-1 until phase-5). Binary logistic regression model of the final stage is = exp (-4.788 + 0.02127 Score) / (1 + (exp (-4.788 + 0.02127 Score)). This indicates that an increase of one score of the academic potential test increases probability of the applicants be accepted as student to 1.0215 times. The results of this modeling can be used as a reference to determine the passing grade in selection process next year.

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EPURE, M., and D. BĂDĂU. "THE IMPORTANCE OF THE SELECTION PROCESS IN BASKETBALL. THE ANALYSIS OF THE SPECIALISTS’ OPINION." Bulletin of the Transilvania University of Braşov Series IX Sciences of Human Kinetics 14(63), no. 2 (2021): 55–62. http://dx.doi.org/10.31926/but.shk.2021.14.63.2.6.

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"objective: The purpose of this study was to identify the specialists’ in the field opinion on the selection process in the basketball game.Method: Data were collected through a questionnaire survey consisting of 27 items, divided into two sections. In this study, 25 specialists participated, out of whom 22 were basketball coaches and 3 were Physical Education and Sports teachers, specializing in basketball.Results: The questionnaire had an Alpha Cronbach fidelity index value of .766. Conclusions: The analysis of the answers received based on the questionnaire highlights the need to improve the secondary selection process in basketball.Key words: basketball, sports selection, questionnaire. 1 Transilvania University of Braşov 1. Introduction The selection or ""identification of talents"" is an organized activity, with a repetitive character, of early detection of children with special skills for practicing certain branches or sports, based on medical, biological, socio-psychological and motor criteria [1], [15], [16]. The selection process and the analysis of the young players’ potential skills has as ultimate goal their preparation for the requirements of the higher leagues and the access into these higher leagues as well as the capitalization on the basketball players’ full potential [11], [18], [19]. This process of identifying talents is a complex one because it requires defining efficient selection criteria and involving several professionals, as follows: coaches, physical trainers, doctors, kinesiologists, psychologists, etc. [13]. In general, the selection process [2] is developed in three stages: STAGE I - the initial or primary selection, which involves attracting, discovering and selecting talented children, with skills for playing basketball. STAGE II – the intermediate or secondary selection, which is considered the most important stage of the selection process because it takes place around the pre-pubertal period when the mental and biological stabilization takes place. The "

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Xie, Qi, Gengguo Cheng, Xiao Zhang, and Lei Peng. "Feature Selection Using Improved Forest Optimization Algorithm." Information Technology And Control 49, no. 2 (June 16, 2020): 289–301. http://dx.doi.org/10.5755/j01.itc.49.2.24858.

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Feature selection is one of the hottest topics in the field of machine learning and data mining. In 2016, the feature selection using forest optimization algorithm (FSFOA) was proposed, which had a better classification performance and dimensionality reduction ability. However, there are some shortcomings in FSFOA. Feature Selection using Improved Forest Optimization Algorithm (FSIFOA) is proposed in this article, which aims at solving the problems of FSFOA during the stages of random initialization, forming the candidate population and updating the best tree. FSIFOA uses the Pearson correlation coefficient and the L1 regularization method to replace the random initialization strategy in the initialization stage, uses the method of separating good and bad trees and filling the quantity gap between them to solve the problem of category imbalance in the candidate population generation stage, adds trees of the same precision but different dimension compared with the best tree to the forest in the update stage. In experiment, the new algorithm uses the same data and parameters as the traditional algorithm to test the small, medium and large dimensional data respectively. The results of the experiments show that the new algorithm can improve the classification accuracy of classifiers and increase the dimension reduction ratio compared with the traditional algorithms in the medium and large dimension data set.

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Doherty, P., M. Kingsford, D. Booth, and J. Carleton. "Habitat Selection before Settlement by Pomacentrus coelestis." Marine and Freshwater Research 47, no. 2 (1996): 391. http://dx.doi.org/10.1071/mf9960391.

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The neon damsel, Pomacentrus coelestis, is characteristic of surge zones on Australian coral reefs and is most abundant on outer slopes of reefs in the southern Great Barrier Reef. When settling, it appears to 'avoid' lagoonal habitats. Recruitment records confirm that this is a general pattern regardless of whether lagoons have permanent or temporary connections to the ocean. This study included direct sampling, around One Tree Reef from the southern Great Barrier Reef, of all presettlement stages of P. coelestis with the aid of light-traps, channel nets and a plankton purse seine. Pelagic juveniles were abundant in catches from light-traps moored outside of the reef crest. In contrast, this developmental stage was rare in catches from all gear types used within the lagoon. The channel nets collected newly hatched larvae that entered the lagoon at night, but either they did not remain in the lagoon or they did not survive because they were not taken from the lagoon by diurnal purse seines. This direct evidence shows that broad-scale habitat selection can begin in the planktonic stage. It implies that pelagic juveniles have excellent sensory and motor capabilities, which disqualify them from being classified and modelled as plankton. Temperature records from inside and outside of the lagoon indicated that warm plumes (up to 3�C above ambient) influence reef waters near One Tree Reef, and temperature may be one of the cues that presettlement fish use to identify lagoonal habitats.

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Huaping, Jia, Zhao Junlong, and A. M. Norouzzadeh Gil Molk. "Skin Cancer Detection Using Kernel Fuzzy C-Means and Improved Neural Network Optimization Algorithm." Computational Intelligence and Neuroscience 2021 (July 17, 2021): 1–12. http://dx.doi.org/10.1155/2021/9651957.

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Early diagnosis of malignant skin cancer from images is a significant part of the cancer treatment process. One of the principal purposes of this research is to propose a pipeline methodology for an optimum computer-aided diagnosis of skin cancers. The method contains four main stages. The first stage is to perform a preprocessing based on noise reduction and contrast enhancement. The second stage is to segment the region of interest (ROI). This study uses kernel fuzzy C-means for ROI segmentation. Then, some features from the ROI are extracted, and then, a feature selection is used for selecting the best ones. The selected features are then injected into a support vector machine (SVM) for final identification. One important part of the contribution in this study is to propose a developed version of a new metaheuristic, named neural network optimization algorithm, to optimize both parts of feature selection and SVM classifier. Comparison results of the method with 5 state-of-the-art methods showed the approach’s higher superiority toward the others.

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MAMET, L. D., and R. DOMAINGUE. "Shortening the selection process for sugarcane." Experimental Agriculture 35, no. 4 (October 1999): 391–405. http://dx.doi.org/10.1017/s0014479799354028.

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There is a need to shorten the selection process for sugarcane (Saccharum hybrids) in Mauritius in order to improve the efficiency of the varietal improvement programme. On average six to seven ratoon crops are grown in Mauritius and selection for ratooning ability is of major importance. The current selection cycle lasts around 15 years and ratooning ability is tested on five occasions. Data (estimates of sucrose content, cane and sugar yields) from the Mauritius Sugar Industry Research Institute's selection trials planted in 1986–90, representing 85 trials (9680 genotypes) in Stage 3 (one-line stage) and 141 trials (2620 genotypes) in Stage 4 (two-line stage) were analysed. It was hypothesized that 1st ratoon (1R) data in Stage 3 and 2nd ratoon (2R) in Stage 4 were effectively redundant and that the cycle could be shortened by two years without loss of precision. Repeatability estimates, between plant cane (P) and the mean of P and 1R (P + 1R) in Stage 3, and between (P + 1R) and the mean of plant cane, 1st and 2nd ratoon (P + 1R + 2R) in Stage 4, were found to be positive and highly significant for all characters indicating that the extra ratoon data were unnecessary.Present and proposed selection scenarios were studied further using differential-selection methodology. The coincidence indices (CI) obtained with the two scenarios were extremely high (63–82% in Stage 3 and 91–96% in Stage 4) again indicating that the additional ratoon data were not cost effective. Realized gains from selection in Stage 4 based on (P + 1R + 2R) as opposed to (P + 1R) were shown to be small or even negative. The results concur extremely well with published data from Australia and the USA. It was therefore recommended that the cycle be reduced by two years and that the resources be more usefully allocated to test genotypes over more sites and more replicates.

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Darusman, Farhan Setiyo, Amalia Anjani Arifiyanti, and Seftin Fitri Ana Wati. "Sentiment Analysis Pedulilindungi Tweet Using Support Vector Machine Method." Applied Technology and Computing Science Journal 4, no. 2 (May 30, 2022): 113–18. http://dx.doi.org/10.33086/atcsj.v4i2.2836.

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Pedulilindungi application has many benefits but many controversies arise in the community. Various opinions in the form of tweets were expressed by the public, both positive and negative opinions. In this study, the objective is to make a classification model to classify tweets into two types of sentiment, namely positive and negative. The model is made in several stages, namely data retrieval, data filtering, data labeling, data preprocessing, splitting data train and data test, feature selection using Information Gain and Genetic Algorithm, and then classification using the SVM method. The model using two-stage feature selection and SVM method, obtained an accuracy value of 64.08% with 841 features and processing time of 0.033 seconds with 9.6% CPU usage. The model with two-stage feature selection is more efficient and effective than the one-stage feature selection model whose accuracy value is only 60.56% with 1800 features and a processing time of 0.044 seconds with 15.4% CPU usage.

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Lee, Dongkon, Kyung-Ho Lee, and Soon-Hung Han. "Intelligent Selection of Main Engine at the Preliminary Design Stage of Ships." Journal of Ship Production 11, no. 04 (November 1, 1995): 245–51. http://dx.doi.org/10.5957/jsp.1995.11.4.245.

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The propulsion system is one of the most complicated systems in a ship and its performance greatly depends on the selection of the main engine. Also, the propulsion system occupies a large portion of the total shipbuilding cost, as well as a large portion of the annual operating cost in fuel consumption. Selecting the right propulsion system is an important factor consideration for shipowners and designers. In the preliminary stage of ship design, the main engine is selected by a design expert and this usually is a difficult task for a novice designer. With the help of a design support system, efficiency in selecting the right engine can be increased. In this study, a knowledge-based system for engine selection which can be used in the preliminary design stage for a merchant ship has been developed. The knowledge base is constructed using heuristic knowledge acquired from design experts. Two databases of engine catalogs and of existing ships are also constructed. Various performance prediction modules of the domain of naval architecture are integrated with the knowledge bases and databases. To enhance the user interface, a graphical user interface (GUI) built upon the Motif widgets is adapted.

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Zhang, Zhengkun, Jun Wang, Adam Jatowt, Zhe Sun, Shao-Ping Lu, and Zhenglu Yang. "News Content Completion with Location-Aware Image Selection." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 16 (May 18, 2021): 14498–505. http://dx.doi.org/10.1609/aaai.v35i16.17704.

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News, as one of the fundamental social media types, typically contains both texts and images. Image selection, which involves choosing appropriate images according to some specified contexts, is crucial for formulating good news. However, it presents two challenges: where to place images and which images to use. The difficulties associated with this where-which problem lie in the fact that news typically contains linguistically rich text that delivers complex information and more than one image. In this paper, we propose a novel end-to-end two-stage framework to address these issues comprehensively. In the first stage, we identify key information in news by using location embeddings, which represent the local contextual information of each candidate location for image insertion. Then, in the second stage, we thoroughly examine the candidate images and select the most context-related ones to insert into each location identified in the first stage. We also introduce three insertion strategies to formulate different scenarios influencing the image selection procedure. Extensive experiments demonstrate the consistent superiority of the proposed framework in image selection.

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Malik, Kainat, Faisal Rehman, Tahir Maqsood, Saad Mustafa, Osman Khalid, and Adnan Akhunzada. "Lightweight Internet of Things Botnet Detection Using One-Class Classification." Sensors 22, no. 10 (May 10, 2022): 3646. http://dx.doi.org/10.3390/s22103646.

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Like smart phones, the recent years have seen an increased usage of internet of things (IoT) technology. IoT devices, being resource constrained due to smaller size, are vulnerable to various security threats. Recently, many distributed denial of service (DDoS) attacks generated with the help of IoT botnets affected the services of many websites. The destructive botnets need to be detected at the early stage of infection. Machine-learning models can be utilized for early detection of botnets. This paper proposes one-class classifier-based machine-learning solution for the detection of IoT botnets in a heterogeneous environment. The proposed one-class classifier, which is based on one-class KNN, can detect the IoT botnets at the early stage with high accuracy. The proposed machine-learning-based model is a lightweight solution that works by selecting the best features leveraging well-known filter and wrapper methods for feature selection. The proposed strategy is evaluated over different datasets collected from varying network scenarios. The experimental results reveal that the proposed technique shows improved performance, consistent across three different datasets used for evaluation.

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Wang, Binhuan. "Variable Selection in ROC Regression." Computational and Mathematical Methods in Medicine 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/436493.

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Regression models are introduced into thereceiver operating characteristic(ROC) analysis to accommodate effects of covariates, such as genes. If many covariates are available, the variable selection issue arises. The traditional induced methodology separately models outcomes of diseased and nondiseased groups; thus, separate application of variable selections to two models will bring barriers in interpretation, due to differences in selected models. Furthermore, in the ROC regression, the accuracy of area under the curve (AUC) should be the focus instead of aiming at the consistency of model selection or the good prediction performance. In this paper, we obtain one single objective function with the group SCAD to select grouped variables, which adapts to popular criteria of model selection, and propose a two-stage framework to apply the focused information criterion (FIC). Some asymptotic properties of the proposed methods are derived. Simulation studies show that the grouped variable selection is superior to separate model selections. Furthermore, the FIC improves the accuracy of the estimated AUC compared with other criteria.

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Sharma, Neha. "TRANSITION OF STAGE TECHNIQUES FROM SHAKESPEAREAN TO MODERN AGE." International Journal of Research -GRANTHAALAYAH 3, no. 1SE (January 31, 2015): 1–2. http://dx.doi.org/10.29121/granthaalayah.v3.i1se.2015.3503.

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There are several techniques employed in presenting any art form. Stage is one of the most important element among these technique. It is the medium where one can show the talent and skills in front of audience. A place where selection, designing, adaptation and modification of any performance takes place is called stage. The stages used from ancient to modern age are the symbols of inheriting art and tradition of a generation to another generations. It can also be said that the visual detailing of any play, drama or art form can be technically performed on stage.

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Martínez de Toda, Fernando, Pedro Balda, and Juan Carlos Sancha. "Preservation of intravarietal diversity in clonal and sanitary pre-selection for a minority variety in danger of extinction: Maturana Blanca." OENO One 46, no. 2 (June 30, 2012): 123. http://dx.doi.org/10.20870/oeno-one.2012.46.2.1511.

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Aim: An objective methodology to preserve intravarietal diversity during the stage of clonal and sanitary pre-selection is exposed. The case of the minority variety in danger of extinction called Maturana Blanca is analyzed.Methods and results: The cluster analysis of the initial population’s data (OIV descriptors) allows leading the pre-selection with the objective of preserving the intravarietal diversity. The pre-selection process, where one accession from each cluster is selected and its sanitary status evaluated, is carried out for three consecutive years. It is verified that the intravarietal diversity is kept after the pre-selection by comparing the distribution of the selected vines to the ones of the initial population for each variable and the principal component analysis of both populations.Significance and impact of the study: The advantage of this method consists of grouping the individuals by a statistical procedure of cluster analysis, enabling a randomized selection.Conclusion: The methodology that has been established to carry out the clonal and sanitary pre-selection of the variety Maturana Blanca allows the preservation of the existing intravarietal diversity.

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Mawardi, Irvan. "PENYELESAIAN SENGKETA ADMINISTRASI TERHADAP HASIL SELEKSI CALON ANGGOTA KPU/BAWASLU DI PROVINSI DAN KABUPATEN/KOTA." Jurnal Keadilan Pemilu 2, no. 2 (July 18, 2022): 21–34. http://dx.doi.org/10.55108/jkp.v2i2.135.

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The General Election Commission (KPU) and the Election Supervisory Agency (Bawaslu) will select election organizers gradually in advance of the 2024 General Election and Regional Election. The time period will end in 2022 or 2023. Such circumstances will have an impact on election preparations and regional head elections. Disputes over the selection stages and results at the State Administrative Court are one of the potentials that can disrupt the selection process for organizers and affect the stages of the general election and local elections. A lawsuit that appears in the middle of the selection stage has the potential to create uncertainty about the schedule for the next selection stage. This is because the Defendant in the Administrative Court is the Selection Team, not the Chairperson of the General Election Comission (KPU)/the General Supervisory Agency (Bawaslu). Furthermore, the dispute resolution process in the Administrative Court takes a long time. The purpose of this study is to examine the administrative dispute resolution arrangement in the selection of election organizers by looking at two things: (1) the legal position of the provincial/district election organizers selection team in dispute in the Administrative Court, and (2) the effectiveness and efficiency of the State Administrative Court's adjudication of the selection results.

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Marulanda, Jose J., Xuefei Mi, H. Friedrich Utz, Albrecht E. Melchinger, Tobias Würschum, and C. Friedrich H. Longin. "Optimum breeding strategies using genomic and phenotypic selection for the simultaneous improvement of two traits." Theoretical and Applied Genetics 134, no. 12 (October 7, 2021): 4025–42. http://dx.doi.org/10.1007/s00122-021-03945-5.

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Abstract Key message A breeding strategy combining genomic with one-stage phenotypic selection maximizes annual selection gain for net merit. Choice of the selection index strongly affects the selection gain expected in individual traits. Abstract Selection indices using genomic information have been proposed in crop-specific scenarios. Routine use of genomic selection (GS) for simultaneous improvement of multiple traits requires information about the impact of the available economic and logistic resources and genetic properties (variances, trait correlations, and prediction accuracies) of the breeding population on the expected selection gain. We extended the R package “selectiongain” from single trait to index selection to optimize and compare breeding strategies for simultaneous improvement of two traits. We focused on the expected annual selection gain (ΔGa) for traits differing in their genetic correlation, economic weights, variance components, and prediction accuracies of GS. For all scenarios considered, breeding strategy GSrapid (one-stage GS followed by one-stage phenotypic selection) achieved higher ΔGa than classical two-stage phenotypic selection, regardless of the index chosen to combine the two traits and the prediction accuracy of GS. The Smith–Hazel or base index delivered higher ΔGa for net merit and individual traits compared to selection by independent culling levels, whereas the restricted index led to lower ΔGa in net merit and divergent results for selection gain of individual traits. The differences among the indices depended strongly on the correlation of traits, their variance components, and economic weights, underpinning the importance of choosing the selection indices according to the goal of the breeding program. We demonstrate our theoretical derivations and extensions of the R package “selectiongain” with an example from hybrid wheat by designing indices to simultaneously improve grain yield and grain protein content or sedimentation volume.

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Ach. Supyanto, Suhartono, and Achmad Amzeri. "Increased productivity of maize (Zea mays L.) through ear-to-row selection." Open Access Research Journal of Life Sciences 6, no. 1 (July 30, 2023): 027–33. http://dx.doi.org/10.53022/oarjls.2023.6.1.0049.

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Assembling superior maize varieties is one of the strategies to increase maize productivity on suboptimal land on Madura Island, Indonesia. One method of assembling high-yielding maize varieties is ear-to-row selection. The research aimed to determine the genetic advances due to ear-to-row selection on the Tambin, Sukmaraga, and Srikandi Kuning varieties. The research was carried out in two stages of activity. Stage 1, carrying out ear-to-row selection for one cycle from the C0 population to form a C1 population. Ear-to-row selection was done on three varieties: the Tambin, Sukmaraga, and Srikandi Kuning. Stage II, carried out an evaluation of the C0 and C1 populations on the three varieties so that six populations were produced. Population evaluation used a completely randomized block design with three replications, resulting in 18 experimental units. Observational variables include ear length, ear diameter, seeds number per row, weight of 100 seeds, seed weight per ear, and production per hectare. The results showed that ear-to-row selection on maize varieties Tambin, Sukmaraga, and Srikandi Kuning showed significantly different selection progress based on the t-test at 5% on maize production per hectare. Heritability values in a broad sense for all characters observed in the moderate to high categories of the three varieties (Tambin, Sukmaraga, and Srikandi Kuning).

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Grégoire, Philippe, and Arthur Robson. "Imitation, Group Selection and Cooperation." International Game Theory Review 05, no. 03 (September 2003): 229–47. http://dx.doi.org/10.1142/s0219198903001033.

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A prior signalling stage is added to the Prisoner's Dilemma and the overall population involved is divided into a number of subpopulations. Evolution involves both local and global imitation — so that the process is formally one of "group selection". A subpopulation that is not signalling and defecting against one and all can be invaded by two "secret handshake" mutants. A subpopulation that is composed entirely of the secret handshake strategy can be invaded by a single "sucker punch" mutant. Nevertheless, if there are at least three subpopulations, the population cooperates always, in the limit as the mutation rate tends to zero.

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Allel, Dorsaf, Anis BenAmar, Mounawer Badri, and Chedly Abdelly. "Evaluation of salinity tolerance indices in North African barley accessions at reproductive stage." Czech Journal of Genetics and Plant Breeding 55, No. 2 (May 22, 2019): 61–69. http://dx.doi.org/10.17221/50/2017-cjgpb.

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Soil salinity is one of the main factors limiting cereal productivity in worldwide agriculture. Exploitation of natural variation in local barley germplasm is an effective approach to overcome yield losses. Three gene pools of North African Hordeum vulgare L. grown in Tunisia, Algeria and Egypt were evaluated at the reproductive stage under control and saline conditions. Assessment of stress tolerance was monitored using morphological, yield-related traits and phenological parameters of reproductive organs showing significant genetic variation. High heritability and positive relationships were found suggesting that some traits associated with salt tolerance could be used as selection criteria. The phenotypic correlations revealed that vegetative traits including shoot biomass, tiller number and leaf number along with yield-related traits such as spike number, one spike dry weight, grain number/plant and grain number/spike were highly positively correlated with grain yield under saline conditions. Hence, these traits can be used as reliable selection criteria to improve barley grain yield. Keeping a higher shoot biomass and longer heading and maturity periods as well as privileged filling ability might contribute to higher grain production in barley and thus could be potential target traits in barley crop breeding toward improvement of salinity tolerance. Multiple selection indices revealed that salt tolerance trait index provided a better discrimination of barley landraces allowing selection of highly salt-tolerant and highly productive genotypes under severe salinity level. Effective evaluation of salt tolerance requires an integration of selection indices to successfully identify and characterize salt tolerant lines required for valuable exploitation in the management of salt-affected areas.

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Vijay, P., Dr A. Srinath, P. Sri Naga Venkat, L. Ranganath, and P. Appalaraju. "Design, Analysis and Selection of Planar Parallel Mechanisms." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 44. http://dx.doi.org/10.14419/ijet.v7i2.32.13522.

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This paper presents the application of methodology for ten bar single degree mechanisms and selecting the best among them at the conceptual design stage itself. This saves lot of time for one wants to carry away analysis for getting desired output of the mechanism at the design stage. The methodology has been applied to Tiscler robot hands successfully and has obtained the best mechanism in motion distribution among the links of the chain.

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Wang, Hong Fei. "Research on a Model of Order Allocation for Virtual Enterprises." Advanced Materials Research 215 (March 2011): 282–85. http://dx.doi.org/10.4028/www.scientific.net/amr.215.282.

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Industrial clusters can be found very often in the world, particularly in many developing countries. To build virtual enterprise based on an industrial cluster is one of the most important ways to improve the agility and competitiveness of manufacturing enterprises in the cluster. One of the key factors towards the success of virtual enterprises is the correct selection of cooperative partners in the virtual enterprise. An approach of order allocation and partner selection in the environment of industrial clusters is proposed. This approach is composed of two stages: task-resource matching and quantitative evaluation. In the first stage the potential candidates are identified and in the second stage evolutionary programming is applied to deal with partner selection and order allocation problem. The target function, in which the load rate of candidate enterprise is taken as the main variable, is developed, and a simplified example is used to verify the feasibility of the proposed approach. The result suggests that the proposed model and the algorithm obtain satisfactory solutions.

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Nenggelis, Siti Aisyah, Rehia K. I. Barus, and Bahrum Jamil. "Penetrasi Sosial Hubungan Pacaran Pada Perempuan Yang Hamil Di Luar Pernikahan (Studi Deskriptif Kualitatif pada Perempuan di Desa Bandar Setia)." Jurnal Ilmu Pemerintahan, Administrasi Publik, dan Ilmu Komunikasi (JIPIKOM) 1, no. 2 (April 26, 2019): 94–104. http://dx.doi.org/10.31289/jipikom.v1i2.157.

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The purpose of this research was to find out and understand how the penetration stages are applied on their dating relationship. There are four of social penetration stages. First, is introduction stage. Second, is open up stage. Third, ares commitment and comfort stage. Fourth, are formality, honesty, and intimacy stage. This research’s type is qualitative descriptive is data from interview, observation and documentation that have been done, then clearly described. The informant selection technique used in this research was “snowball technique”. The snowball technique are often used to find and recruit hidden informants, namely individuals who aren’t easily accessible to researchers through other informant selection techniques. The conclusion of this research was the three informants applied the all social penetration stages on their dating relationship with their babies’ father however, each stage should have a long time to process, it is applied too quickly by the three informants. Initially, the three informants only wanted to undergo dating relationship as in general without any sexual elements. But, one, two, three informants were forced to have intercourse with their babies’ father. The consequence, the three informants were very sorry for having premarital sex.

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Surnis, Prathmesh. "Design and Analysis of 2-Stage Gearbox for ATV Applications." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (September 30, 2021): 2193–210. http://dx.doi.org/10.22214/ijraset.2021.38326.

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Abstract: The main objective of this project is to design and develop a 2-Stage- Reduction gearbox for all terrain vehicles application. Gearbox is a mechanical unit consisting of series of gears within a housing (casing) or a simple gear train. It is the main component of the powertrain system as it provides speed and torque conversions from the Engine or CVT to the wheels. The gears inside of gearbox can be any one of a number of different types of the gear that are available in the market i.e., from spur gears to worm gears and planetary gears as well. In this report the gearbox is made from a helical gear train. This report focuses on selection of overall reduction ratio of the gearbox, material selection, selection of gear dimensions, selection of shaft dimension, design of key and bearing selection from SKF bearing catalogue. The bending and wear strengths are calculated to determine factor of safety and later, Finite element analysis is performed to validate the results. Keywords: Geartrain, Shaft Design, SKF Bearings, Solidworks, FEA

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Ma, Xin. "Supplier Selection Model Based on Two Stage Signal Game and Reputation Mechanism." Advanced Materials Research 214 (February 2011): 50–54. http://dx.doi.org/10.4028/www.scientific.net/amr.214.50.

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Asymmetric information will lead to adverse selection in the supplier selection in the supply. One the basis of game theory and information economics theories, a two stage supplier selection signal game reputation model is presented. The optimal price signal and utility of supplier are derived under symmetric and asymmetric information. The optimal signal of supplier will be strengthen and the utility at the second stage will also be increased if the supplier sets up reputation at the first stage, and it also shown that more utilities can be achieved when a supplier uses reputation.

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Reis, Ângelo V. dos, Antônio L. T. Machado, Mário C. Gomes, Norberto L. M. Andersson, and Roberto L. T. Machado. "A multicriteria model to assess tractors used in family agriculture." Engenharia Agrícola 34, no. 4 (August 2014): 727–37. http://dx.doi.org/10.1590/s0100-69162014000400012.

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In recent years, public policy has been offering subsidized credit for machine purchase to family farmers. However, there is no methodological procedure to select a suitable tractor for these farmers' situation. In this way, we aimed to develop a selection model for smallholder farmers from Pelotas city region in the state of Rio Grande do Sul. Building a multicriteria model to aid decisions is divided into three main stages: structuring stage (identifying stakeholders, decisional context and model creation), evaluation stage (stakeholder preference quantification) and recommendation stage (choice selection). The Multicriteria method is able to identify and value the criteria used in tractor selection by regional family farmers. Six main evaluation areas were identified: operational cost (weight 0.20), purchase cost (weight 0.22), maintainability (weight 0.10), tractor capacity (weight 0.26), ergonomics (weight 0.14) and safety (weight 0.08). The best-rated tractor model (14.7 kW rated power) also was the one purchased by 53.3% of local families.

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Yang, Ming Shun, Yan Li, Yong Liu, and Xin Qin Gao. "A Method for Problem Selection in the 6σ Definition Stage." Advanced Materials Research 139-141 (October 2010): 1485–89. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1485.

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6σ has proved numerous times that it can help any business to deliver products to meet or even exceed customer expectations. DMAIC (Define – Measure – Analyze – Improve - Control) is one of the Six Sigma methodologies used for a 6σ project that aims to improve and control quality of exiting products. Aiming at the drawbacks existed in the problem selection in definition stage, considering the fuzziness and uncertainty of problem analyzing, a method integrating fuzzy QFD (Quality Function Deployment), frequency-cost FMEA (Failure Mode Effect Analysis) and gray relation analysis is presented, in which the customer requirements, occurring frequencies and the relative costs of the problems are taken into account comprehensively. Thus the key quality characteristics or process features to be improved are determined, which can provide decision support for key problem selection. An example is given to illustrate the effectiveness of the proposed method.

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Janardhan, Naulegari, and Nandhini Kumaresh. "Improving Depression Prediction Accuracy Using Fisher Score-Based Feature Selection and Dynamic Ensemble Selection Approach Based on Acoustic Features of Speech." Traitement du Signal 39, no. 1 (February 28, 2022): 87–107. http://dx.doi.org/10.18280/ts.390109.

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Depression affects over 322 million people, and it is the most common source of disability worldwide. Literature in speech processing revealed that speech could be used for detecting depression. Depressed individuals exhibit varied acoustic characteristics compared to non-depressed. A four-staged machine learning classification system is developed to investigate the acoustic parameters to detect depression. Stage one uses speech recordings from a publicly available and clinically validated dataset DAIC-WOZ. The baseline acoustic feature vector, eGeMAPS, is extracted from the dataset in stage two. Adaptive synthetic (ADASYN) is performed along with data preprocessing to overcome the class imbalance. In stage three, we conducted feature selection (FS) using three techniques; Boruta FS, recursive feature elimination using support vector machine (SVM-RFE), and the fisher score-based FS. Experimentation with various machine learning base classifiers like gaussian naïve bayes (GNB), support vector machine (SVM), k-nearest neighbors (KNN), logistic regression (LR), and random forest classifier (RF) is performed in stage four. The hyperparameters of the classifiers are tuned using the GridSearchCV technique throughout the 10-fold stratified cross-validation (CV). Then we employed multiple dynamic ensemble selection of classifier algorithms (DES) with k=3 and k=5 utilizing the pool of aforementioned four base classifiers to improve the accuracy. We present a comparative study using eGeMAPS features against the base classifiers and the experimented DES classifiers. Our results on the DAIC-WOZ benchmark dataset suggested that K-Nearest Oracles Union (KNORA-U) DES with k=3 has superior accuracy using a subset of 15 features selected by fisher score-based FS than the individual base classifiers.

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Adam Huda Nugraha. "DEVELOPMENT OF RW CHAIRMAN SELECTION APPLICATION WEB USING CODEIGNITER, PHP AND MYSQL FRAMEWORK." Journal of Engineering, Electrical and Informatics 1, no. 3 (October 1, 2021): 1–10. http://dx.doi.org/10.55606/jeei.v1i3.201.

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E-Voting is the use of computer technology for the implementation of voting. One choice of computer technology used for the implementation of e-voting is to use a client-server architecture. So the use of an all-computer-based-system is expected to replace the manual voting process. The goal to be achieved from making this e-voting application is to be able to assist committee officers in calculating the number of voters and calculating election results quickly and accurately. This application is made using the PHP programming language which is expected to overcome problems related to selection. In making this website, the stages carried out are, preparing the required data, designing the website, designing input and output, followed by the implementation stage of making program coding, the last stage is the trial stage on localhost. Planned trials that set up the application to run properly.

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Campo, J. L., and M. B. Fuente. "Comparison of one- and two-stage selection on adult weight and egg number in Tribolium castaneum." Journal of Animal Breeding and Genetics 108, no. 1-6 (January 12, 1991): 17–22. http://dx.doi.org/10.1111/j.1439-0388.1991.tb00151.x.

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Rincon, M., and R. A. Flavell. "Regulation of AP-1 and NFAT transcription factors during thymic selection of T cells." Molecular and Cellular Biology 16, no. 3 (March 1996): 1074–84. http://dx.doi.org/10.1128/mcb.16.3.1074.

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The ability of thymocytes to express cytokine genes changes during the different stages of thymic development. Although CD4- CD8- thymocytes are able to produce a wide spectrum of cytokines in response to a T-cell receptor (TcR)-independent stimulus, as they approach the double-positive (DP) CD4+ CD8+ stage, they lose the ability to produce cytokine. After the DP stage, thymocytes become single-positive CD4+ or CD8+ thymocytes which reacquire the ability to secrete cytokines. In an attempt to understand the molecular basis of this specific regulatin, we use AP-1-luciferase and newly generated NFAT-luciferase transgenic mice to analyze the transcriptional and DNA-binding activities of these two transcription factors that are involved in the regulation of cytokine gene expression. Here, we show that both AP-1 and NFAT transcriptional activities are not inducible in the majority of DP cells but that during the differentiation of DP cells to the mature single-positive stage, thymocytes regain this inducibility. Subpopulation analysis demonstrates that this inducibility is reacquired at the DP stage before the down-modulation of one of the coreceptors. Indeed AP-1 inducibility, just like the ability to express the interleukin-2 gene, is reacquired during the differentiation of DP TcRlow CD69low heat-stable antigen (HSA)high thymocytes to DP TcRhigh CD69high HSAhigh cells, which is considered to be the consequence of the first signal that initiates positive selection. We therefore propose that the inability of DP thymocytes to induce AP-1 and NFAT activities is one of the causes for the lack of cytokine gene expression at this stage and that this inducibility is reacquired at the latest stage of DP differentiation as a consequence of positive selection. This could be a mechanism to prevent the activation of DP thymocytes before selection has taken place.

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ZHUANG, HAN, XUELING LIU, HUI WANG, CHUNLI QIN, YUXIN LI, WENSHENG LI, and YONGHONG SHI. "DIAGNOSIS OF EARLY STAGE PARKINSON’S DISEASE ON QUANTITATIVE SUSCEPTIBILITY MAPPING USING COMPLEX NETWORK WITH ONE-WAY ANOVA F-TEST FEATURE SELECTION." Journal of Mechanics in Medicine and Biology 21, no. 05 (April 17, 2021): 2140026. http://dx.doi.org/10.1142/s0219519421400261.

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This paper presented a novel complex network with one-way ANOVA F-test feature selection to diagnose early-stage Parkinson’s disease (PD) on quantitative susceptibility mapping (QSM). Experimental results on QSM images of 30 early-stage PD patients and 27 healthy controls (HC) proved that the F-test feature selection scheme was effective and achieved good classification results. The accuracy, AUC, sensitivity and specificity of our method were 0.96, 0.97, 0.99 and 0.95, respectively, which were improved by 15%, 4%, 29% and 2%, respectively by comparison with the commonly used region of interest (ROI) based method. Meanwhile, according to the feature importance, the potential brain regions affected by PD were arranged orderly. The affected regions were distributed as follows: 61% of them are located in right hemisphere and 39% in the left hemisphere. Particularly, frontal lobe, parietal lobe, temporal lobe and occipital lobe accounted for 24%, 20%, 5% and 14%, respectively, and striatum and the dorsal thalamus accounted for 16%. It concludes that the complex network with one-way ANOVA F-test feature selection can greatly improve the diagnostic performance of early-stage PD based on QSM, as well as provide a new way to study the effect of PD on brain in the future.

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Kabanov, A. V. "Introduction and selection of the genus of Astilbe in the Main Botanical Garden named after N. V. Tsitsin of the RAS." Plant Biology and Horticulture: theory, innovation, no. 155 (November 16, 2020): 52–58. http://dx.doi.org/10.36305/2712-7788-2020-2-155-52-58.

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The Laboratory of Ornamental Plants of theof the Main Botanical Garden named after N. V. Tsitsin of RAS has collected a very representative collection of representatives of the genus Astilbe , which includes 132 varieties and 8 natural species.The collection contains all geographical groups of this genus that grow in temperate climates. At the first stage of collection, the main task was to include historical varieties that reflect the various stages of selection. We managed to collect a unique variety of varieties that reflects the breeding achievements of the vast majority of breeders of this crop and all known breeding centers. Special attention was paid to the creation of separate complexes of varieties belonging to both individual breeders and breeding centers. The result of the first stage of work was the creation of a collection of varieties that reflects the history of breeding culture over a 120-year period. Currently, selection work has begun on the basis of the collection. One of the directions of selection is to obtain high and early flowering forms of Astilbe . Currently, two hybrid samples have been selected, which are promising for use as a variety due to their decorative characteristics. Crosses are also carried out within the natural species Astilbemicrophylla and Astilbebiternata , which were previously little used in breeding and have valuable decorative features. Since the beginning of selection, the principle of selecting varieties for inclusion in the collection Fund has changed. Now the main principle of selection is to include varieties with valuable characteristics that can be used in breeding work.

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Huang, Chao-Ming, Shin-Ju Chen, Sung-Pei Yang, and Hsin-Jen Chen. "One-Day-Ahead Hourly Wind Power Forecasting Using Optimized Ensemble Prediction Methods." Energies 16, no. 6 (March 13, 2023): 2688. http://dx.doi.org/10.3390/en16062688.

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This paper proposes an optimal ensemble method for one-day-ahead hourly wind power forecasting. The ensemble forecasting method is the most common method of meteorological forecasting. Several different forecasting models are combined to increase forecasting accuracy. The proposed optimal ensemble method has three stages. The first stage uses the k-means method to classify wind power generation data into five distinct categories. In the second stage, five single prediction models, including a K-nearest neighbors (KNN) model, a recurrent neural network (RNN) model, a long short-term memory (LSTM) model, a support vector regression (SVR) model, and a random forest regression (RFR) model, are used to determine five categories of wind power data to generate a preliminary forecast. The final stage uses an optimal ensemble forecasting method for one-day-ahead hourly forecasting. This stage uses swarm-based intelligence (SBI) algorithms, including the particle swarm optimization (PSO), the salp swarm algorithm (SSA) and the whale optimization algorithm (WOA) to optimize the weight distribution for each single model. The final predicted value is the weighted sum of the integral for each individual model. The proposed method is applied to a 3.6 MW wind power generation system that is located in Changhua, Taiwan. The results show that the proposed optimal ensemble model gives more accurate forecasts than the single prediction models. When comparing to the other ensemble methods such as the least absolute shrinkage and selection operator (LASSO) and ridge regression methods, the proposed SBI algorithm also allows more accurate prediction.

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Kadhim, Saraa Naseer, and Kadhim Raheim Erzaij. "Examining sensitivity of financial performance at construction projects prequalification stage." Journal of Engineering 26, no. 7 (July 1, 2020): 175–89. http://dx.doi.org/10.31026/j.eng.2020.07.12.

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Construction projects are complicated in nature and require many considerations in contractor selection. One of the complicated interactions is that between performance with the project size, and contractor financial status, and size of projects contracted. At the prequalification stage, the financial ‎requirements restrict the ‎contractors to meet minimum limits in financial criteria such as net worth, working capital and ‎annual turnover, etc. In construction projects, however, there are cases when contractors meet these requirements but show low performance in practice. The model used in the study predicts the performance by training of a neural network. The data used in the study are 72 of the most recent roadwork projects‎ in Bahrain. The results are shown in terms of the sensitivity of changing one variable on the performance of all the 72 projects. These results can reflect on the methods currently used on contractors’ assessments in the tendering stage and support decision-makers in assessing contractors and selecting the best bidders.

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Sivarao, Mohd Fairuz Dimin, N. M. F. Faris, A. Hambali, Sivakumar Dhar Malingam, and S. M. Sapuan. "Analytical Hierarchy Process for Design Selection of Micro Hot-Marking Tool." Applied Mechanics and Materials 699 (November 2014): 897–902. http://dx.doi.org/10.4028/www.scientific.net/amm.699.897.

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Veracious concept selection process is crucial in design engineering where, a concept with concise description will fulfill customers’ requirements. Failure in concept selection can lead to inaccurate design which will result in unnecessary process repetition of the initial stage. One of the best tools that can be used in determining the best design concept is Analytical Hierarchy Process (AHP). Micro Hot-Marking Tool (HMT) is a super-finished tool with micro tip which is to be used for alphabetical marking process using CNC milling machine. In this research, AHP was successfully employed in selecting design concept for HMT. Four significant and robust concepts were analyzed, namely C1, C2, C3 & C4. Concept 2 (C2) has been chosen as the best concept with the highest score of 27% among all the evaluated concepts which will be taken into next design stage.

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Journal articles on the topic 'One stage selection'

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