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Chase, Jo-Ana, Chelsea Howland, Malaika Gallimore, and Blaine Reeder. "Usability and Feature Evaluation of the Amazfit Bips Smart Watch in the Precision START Lab." Innovation in Aging 4, Supplement_1 (December 1, 2020): 196. http://dx.doi.org/10.1093/geroni/igaa057.634.
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Abstract Interventions utilizing consumer-grade wearable and mobile devices may support older adult health and wellness. However, rapid technology change and short industry product release cycles limit timely incorporation of these devices. We developed a novel, multi-stage process to rapidly move from within-team evaluations to lab- and field-based participants studies based on small-sample technology testing methods from Human-Computer Interaction. We present findings from a first-stage evaluation of the Amazfit Bips smart watch for potential use in studies with older adults as part of the methodology validation. A four-person research team conducted evaluations using: 1) a wearables framework for user experience and feature availability; and 2) the System Usability Scale (SUS). Evaluators wore the watch seven days straight from the box. User experience checklists indicated high usability. However, corresponding comments identified challenges with downloading the mobile app, pairing the watch and phone, navigating watch and mobile interfaces, and privacy controls. Average SUS score was 65.6 indicating marginal usability (C grade). While meeting study goals, divergence in usability perceptions suggest the process could be improved by completing each set of instruments separately for the watch and mobile app rather than all at once. Given failures in pairing, app navigation challenges, and small screen size, the Amazfit Bips may be best suited for studies among older adults with a high degree of technical proficiency. For those with little technical experience or high disease burden, training materials and dedicated training with support may be required. Future steps are lab- and field-based tests with older adult participants.
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Düking, Peter, Marie Tafler, Birgit Wallmann-Sperlich, Billy Sperlich, and Sonja Kleih. "Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis." JMIR mHealth and uHealth 8, no. 11 (November 19, 2020): e20820. http://dx.doi.org/10.2196/20820.
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Background Decreasing levels of physical activity (PA) increase the incidences of noncommunicable diseases, obesity, and mortality. To counteract these developments, interventions aiming to increase PA are urgently needed. Mobile health (mHealth) solutions such as wearable sensors (wearables) may assist with an improvement in PA. Objective The aim of this study is to examine which behavior change techniques (BCTs) are incorporated in currently available commercial high-end wearables that target users’ PA behavior. Methods The BCTs incorporated in 5 different high-end wearables (Apple Watch Series 3, Garmin Vívoactive 3, Fitbit Versa, Xiaomi Amazfit Stratos 2, and Polar M600) were assessed by 2 researchers using the BCT Taxonomy version 1 (BCTTv1). Effectiveness of the incorporated BCTs in promoting PA behavior was assessed by a content analysis of the existing literature. Results The most common BCTs were goal setting (behavior), action planning, review behavior goal(s), discrepancy between current behavior and goal, feedback on behavior, self-monitoring of behavior, and biofeedback. Fitbit Versa, Garmin Vívoactive 3, Apple Watch Series 3, Polar M600, and Xiaomi Amazfit Stratos 2 incorporated 17, 16, 12, 11, and 11 BCTs, respectively, which are proven to effectively promote PA. Conclusions Wearables employ different numbers and combinations of BCTs, which might impact their effectiveness in improving PA. To promote PA by employing wearables, we encourage researchers to develop a taxonomy specifically designed to assess BCTs incorporated in wearables. We also encourage manufacturers to customize BCTs based on the targeted populations.
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Song, Jinzhong, Tianshu Zhou, Zhonggang Liang, Ruoxi Liu, Jianping Guo, Xinming Yu, Zhongping Cao, Chuang Yu, Qingjun Liu, and Jingsong Li. "Electrochemical Characteristics Based on Skin-Electrode Contact Pressure for Dry Biomedical Electrodes and the Application to Wearable ECG Signal Acquisition." Journal of Sensors 2021 (September 15, 2021): 1–9. http://dx.doi.org/10.1155/2021/7741881.
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Based on one simulated skin-electrode electrochemical interface, some electrochemical characteristics based on skin-electrode contact pressure (SECP) for dry biomedical electrodes were analysed and applied in this research. First, 14 electrochemical characteristics including 2 static impedance (SI) characteristics, 11 alternating current impedance (ACI) characteristics and one polarization voltage (PV), and 4 SECP characteristics were extracted in one electrochemical evaluation platform, and their correlation trends were statistically analysed. Second, dry biomedical electrode samples developed by the company and the laboratory, including textile electrodes, Apple watch, AMAZFIT rice health bracelet 1S, and stainless steel electrodes, were placed horizontally and vertically on the “skin” surface of the electrochemical evaluation platform, whose polarization voltages were quantitatively analysed. Third, electrocardiogram (ECG) collection circuits based on an impedance transformation (IT) circuit for textile electrodes were designed, and a wearable ECG acquisition device was designed, which could obtain complete ECG signals. Experimental results showed SECP characteristics for dry electrodes had good correlations with static impedance and ACI characteristics and the better correlation values among 2-10 Hz. In addition, polarization voltages in vertical state were smaller in horizontal state for dry biomedical electrodes, and polarization voltage of electrode pair (PVEP) values for Apple watch bottom was always smaller than ones for Apple watch crown and LMF-2 textile electrode. And the skin-electrode contact impedance of IT textile electrodes was less than the traditional textile electrodes.
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Andi Suhendi, Acep. "IMPLEMENTATION OF BLUE OCEAN STRATEGY (BOS) AT PT. ANEKA DIGITAL SUKSESINDO IN THE EFFORT TO INCREASE THE COMPETITIVE ADVANTAGE AGAINST THE COMPETITORS." Dinasti International Journal of Economics, Finance & Accounting 1, no. 3 (July 29, 2020): 413–20. http://dx.doi.org/10.38035/dijefa.v1i3.420.
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The increasing competition in the business world requires a company to always make transformation not only to meet the company's targets but also for business sustainability or survival. The similar thing happened with PT.Aneka Digital Suksesindo which is one of the PMA (Foreign Investment Company) from China which is engaged in the distribution of electronic products made in China which is always innovating in order to maintain its existence in Indonesia. Some of its superior products are 1. Black Shark which is mobile gaming that offers maximum performance. It is a smart phone which is able to hold on for hours to play games and fast charging, 2. Amazfit Smartwatch is a smart watch from Xiaomi that can be used to monitor heart rate, real GPS time to record running track, speed and distance. This study aims to explain the implementation of the Blue Ocean Strategy in an effort to improve competitive advantage and also to determine the conditions of the internal and external environment through SWOT Analysis, namely Strength, Weakness, Opportunity, Threat (Threat) at PT. Aneka Digital Suksesindo. Based on the type of research that is descriptive research using a qualitative approach
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Dalimunthe, Dzakiyyatul Kirom, and Raden Bagus Fajriya Hakim. "APPLICATION OF RANDOM FOREST ALGORITHM ON WATCH PRICE PREDICTION SYSTEM USING FRAMEWORK FLASK." BAREKENG: Jurnal Ilmu Matematika dan Terapan 17, no. 1 (April 16, 2023): 0171–84. http://dx.doi.org/10.30598/barekengvol17iss1pp0171-0184.
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In the modern era like today, watches not only function as timepieces, but have become a fashion trend for the community, especially teenagers. The increasing market demand for watches opens up opportunities for counterfeit watch sellers to sell their products by claiming that the watches they sell are genuine watches by offering relatively cheaper prices compared to genuine watches. This is very detrimental to consumers and also the watch industry. To minimize fraud committed by fake watch sellers, it is necessary to know the price of the original watch in advance, before buying the desired watch. Therefore, the purpose of this study is to predict the price of watches using the Random Forest method and will be developed into a web system using the Framework Flask. The results of the study using 3337 trees obtained an accuracy rate of 84,98% with a MAPE of 15,02%. The most influential variable on the price of watches is the material variable with the level of importance obtained at 0,359. After getting the best model, the model is then developed into a web system using the help of the Framework Flask and Heroku which can later be accessed online.
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Anang Furkon RIfai and Erwin Budi Setiawan. "Memory-based Collaborative Filtering on Twitter Using Support Vector Machine Classification." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 4 (August 22, 2022): 624–31. http://dx.doi.org/10.29207/resti.v6i4.4270.
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Nowadays, watching films at home is one of people's entertainment. Netflix is a service provider for watching films and provides many types of film genres. However, of the many films available, it makes users confused to choose which film to watch first. The solution to the problem is a system that provides recommendations for the best films to watch based on user ratings. Twitter is still people's favorite social media to express their feelings, thoughts, and criticisms. In this system, tweets serve as input data that will be processed into data with rating values. This research implemented a recommendation system based on user ratings from tweets using collaborative filtering combined with Support Vector Machine (SVM) classification and implemented it on user-based and item-based. The test results in this study show that Collaborative Filtering gets the best RMSE value results on item-based 0.5911 and 0.8162 on user-based. The Support Vector Machine (SVM) classification algorithm using hyperparameter tuning produces item-based values with a precision of 85.03% and recall of 90.71%, while user-based values with a precision of 87.75% and recall of 88.95%.
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Anang Furkon RIfai and Erwin Budi Setiawan. "Memory-based Collaborative Filtering on Twitter Using Support Vector Machine Classification." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 5 (October 1, 2022): 702–9. http://dx.doi.org/10.29207/resti.v6i5.4270.
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Nowadays, watching films at home is one of people's entertainment. Netflix is a service provider for watching films and provides many types of film genres. However, of the many films available, it makes users confused to choose which film to watch first. The solution to the problem is a system that provides recommendations for the best films to watch based on user ratings. Twitter is still people's favorite social media to express their feelings, thoughts, and criticisms. In this system, tweets serve as input data that will be processed into data with rating values. This research implemented a recommendation system based on user ratings from tweets using collaborative filtering combined with Support Vector Machine (SVM) classification and implemented it on user-based and item-based. The test results in this study show that Collaborative Filtering gets the best RMSE value results on item-based 0.5911 and 0.8162 on user-based. The Support Vector Machine (SVM) classification algorithm using hyperparameter tuning produces item-based values with a precision of 85.03% and recall of 90.71%, while user-based values with a precision of 87.75% and recall of 88.95%.
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Paul, Chiranjib, and P. K. Das. "A Machine Learning-Driven Movie Performance Prediction System to Improve Decision-Making Capability of Movie Investors." Journal of Management and Humanity Research 08 (2022): 57–75. http://dx.doi.org/10.22457/jmhr.v08a062254.
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Moviegoers refer to online audience movie ratings before deciding to watch a movie. They are more inclined to watch a movie with a high average rating. We develop a system to predict average audience movie ratings based on the lead cast and crew at an early stage of movie production. After valuing multiple scenarios, investors can use our study to select the lead cast and crew objectively. Judicious selection of the key cast and crew is extremely important as investors commit to large sums of money as professional fees while signing contracts with them. Our study uses a relatively large sample of 1687 Indian movies spread across 10+ languages released in India between 2010 and 2019 to identify the important predictors influencing average audience movie rating. Identification of important predictors improves the explainability of the prediction model, which increases the investors’ trust in the predicted values. The best model, random forest, reduces the baseline prediction error of the average rating by 10.21%.
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Mali, Mahesh, Dhirendra Mishra, and M. Vijayalaxmi. "Bi-clustering based recommendation system." Journal of Information and Optimization Sciences 45, no. 4 (2024): 1029–39. http://dx.doi.org/10.47974/jios-1625.
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Users in the new age have countless choices of movies to watch, which creates the need for recommendation algorithms that will suggest a list of the best movies. The Recommendation algorithms will help users select the best movie to watch based on their personal choices and movie features. The first challenge among researchers is to find the most suitable dataset for the evaluation of recommendation algorithm performance. The work in the paper introduced a new MFRISE dataset to fulfil this challenge partially. The dataset is constructed using social data like Wikipedia, YouTube and other web sources with the help of web scraping data. The proposed algorithm uses Collaborative as well as Content-Based Filtering to produce more accurate results. This architecture is based on the biclustering technique to improve the accuracy of the predicted ratings for better recommendations. The biclustering method involves simultaneous clustering of the user, as well as movie dimensions. The biclustering method will uncover the hidden insights from the intersection of two clusters. The method has produced more relevant recommendations by reducing error values in the prediction of user ratings. The RMSE for the new algorithm is observed as 0.83, which is better than that of many popular algorithms. The paper presents several experiments for analysing the proposed bi-clustering method using meta-features of the new proposed dataset. The future development of the biclustering method is suggested at the end of our paper.
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Gupta, Gaurav, and Atul Dattatrya Newase. "HYBRID RECOMMENDATION SYSTEM FOR BETTER MINING RULES GENERATION OF USER AND CONSUMER DATA." BSSS journal of computer 12, no. 1 (June 30, 2021): 49–57. http://dx.doi.org/10.51767/jc1206.
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In today’s world Data and information playing an important role in each field including online and software data. However, it is very difficult task to abstract & sorted consumer data for use. To solve this data overloading and sorting of useful data a Hybrid Recommendation System (HRS) comes into existence. The focus of HRS is to suggest the best applicable and useful items to the related customers or user. The recommendations can be applied to decision-making processes, like which types of things to get, which new videos to watch to, which online latest games and software to search, or which is the best product among all. The benefits of Hybrid Recommendation System persist on quality efficiency of the system. The efficient things can be calculated in the forms of easy to use, reliable accurate and expandable. The main goal of this proposed HRS is to better mining rules based on user and consumer data to improve the accuracy of Hybrid Recommendation System.
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Muhadzdzib Ramadhan, Muhammad Tsaqif, and Erwin Budi Setiawan. "Netflix Movie Recommendation System Using Collaborative Filtering With K-Means Clustering Method on Twitter." JURNAL MEDIA INFORMATIKA BUDIDARMA 6, no. 4 (October 25, 2022): 2056. http://dx.doi.org/10.30865/mib.v6i4.4571.
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Nowadays, the development of technology is very rapid, so watching movies at home has become a means of entertainment. Netflix is one of the platforms for watching movies and provides various movie titles. However, because of the many movie titles, it makes it difficult for users to determine the movie they want to watch. The solution to this problem is to provide a recommendation system that can provide movie recommendations to watch. Collaborative filtering is a method that exists in the recommendation system by providing recommendations based on the ratings given by other users. Collaborative filtering is divided into two, namely based on items (item-based) and based on users (user-based). Twitter is a social media used to write posts called tweets. For this system, tweets serve as data that will be processed into ratings. This research was conducted using k-means clustering with collaborative filtering and collaborative filtering only. By using a dataset obtained from Twitter by crawling data and added with ratings from IMDb, Rotten Tomatoes, and Metacritic. Which resulted in a dataset with 35 users, 785 movie titles, and 6184 reviews. Then preprocessing the data with text processing, polarity, and labeling. And get the dataset that will be used for this experiment. The results of this research test show that k-means clustering with collaborative filtering gets the best results with the best prediction of 2.8466, getting an MAE value of 0.5029, and an RMSE value of 0.6354
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Bagane, Pooja, Sudhanshu Gonge, Rahul Joshi, and Obsa Amenu Jebessa. "Automotive Movie Recommendation System based on Natural Language Processing." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 5 (May 17, 2023): 300–303. http://dx.doi.org/10.17762/ijritcc.v11i5.6617.
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People are puzzled about which movie to watch these days because there are so many movies available on various OTT platforms. A recommender system would solve this problem by recommending the best movie to the user based on his genre, actor, director, and rating preferences. The cosine similarity principle would be used to guide the recommendation system. Apart from that, we will use the Tfidftransformer and count vectorizer from the sci-kit-learn library in Python in this work. In this study work, all of the approaches' constraints have been described. All of this work was done using datasets from several OTT platforms that were available on Kaggle.
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Nawaz, Shoaib, Muhammad Rizwan, Samina Yasin, Mehtab Ahmed, and Umar Farooq. "Multi-Class Classification of the YouTube Comments using Machine Learning." Pakistan Journal of Engineering and Technology 3, no. 2 (April 21, 2022): 183–88. http://dx.doi.org/10.51846/vol3iss2pp183-188.
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Due to huge data on Social media the people face difficulty to finding in qualitative content of the video if they find the qualitative content as per their judgment and knowledge, they do not confirm the actual content quality. People put their idea and subscriber watch the videos and put their feedback in the comments. Our purposed study help the subscribers to find the best-experienced idea based on the people personal experience here we classify the collection of comments collected using Google API’s(“Google API YouTube” n.d.) and annotate them in different classes which are Experience-positive, Experience-negative, Warning, Suggestions, Questions, Praise, these classes helps us to find the qualitative analysis of the comments but based on the these required classes. Our proposed model shows experiments that the best classifier for us is the SVM have accuracy is 89.18% and F1 score is 0.89 this shows that our model is productive and efficient for classification to help out the user as well as the author to find the best qualitative video content which is experienced and confirmed by the user’s experience(Abbas 2017).
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Sato, Kohei, Masaru Sugano, Hitomi Murakami, and Atsushi Koike. "Key Frame Detection Method from News Program using Common Features to News Topics." ECTI Transactions on Electrical Engineering, Electronics, and Communications 9, no. 2 (February 28, 2011): 308–14. http://dx.doi.org/10.37936/ecti-eec.201192.172512.
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A hard disk drive and a flash memory have become high capacity, so that we are now in the situation where a lot of TV programs can be recorded. However, while convenient, it is not easy to watch all the recorded programs in a limited time. Therefore, an efficient TV browsing application is needed. In this paper, we propose a key frame detection method for TV news program to allow a viewer to efficiently browse TV news programs and/or particular TV news topics. Instead of using features specific to certain news topics, our proposal is to extract important features which are common to news topics, and to generally detect the unique key frame which best represents each news topic. We show the validity of our proposed method by a simulation experiment.
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Singh, Abhay Pratap, Mukul Sharma, Ashish Chauhan, and Kamal Soni. "Build a Recommendation System for Movies or Books." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 1379–82. http://dx.doi.org/10.22214/ijraset.2023.50303.
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Abstract: These days everyone will change their life style to search the movies on the internet. They will provide the information of their preferences which the y like to watch. There are many recommended and popular system is applied to search their favorite things like books, articles music videos, movies etc. these paper we are proposed a movie recommendation system. It will be working on the various filter or collaborate filter method that will collect and gave the information to the user and it will also analyzes the user and gave them the best movies to there users at that time. We sorted the movies according to the user recommendation of the previous users preferences so for these purpose we use k-means algorithm. Movie recommendation system can also help the user to find the choices of there movies are based on there previous experiences and manners without wasting its useless time on the browser to search their best movies. It will give us various type of previous recommendation using customized the database. then the user can browse it easily and choice his best movie
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Ashar, Muhammad Adam, Fuad Muhajirin Farid, and Selvi Annisa. "PENGARUH PERFORMA VIDEO TERHADAP JUMLAH VIEWS VIDEO REGULER DI YOUTUBE MENGGUNAKAN ANALISIS JALUR." RAGAM: Journal of Statistics & Its Application 2, no. 1 (August 31, 2023): 82. http://dx.doi.org/10.20527/ragam.v2i1.10042.
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YouTube is a video-sharing website which is one of the media for deployment information that is of great interest to the public in Indonesia. Being the most visited website in the world, YouTube has had a significant impact on modern society. Many people in Indonesia have utilized YouTube as a platform to share their thoughts and creativity through the video they create, as well as to make income. Creative content will usually get more responses from the audience. Creating a regression model for use in path analysis enables the investigation of causal links between various variables. The intention of this study is to specify the path's structure and analyze what variables effect YouTube video views. The exogenous variables used to observe the influence of views are impressions, CTR and watch time. This study uses path analysis to examine how video performance impacts views both directly and indirectly using path diagrams. Considering the outcomes of this study, the variables that affect views are impressions and CTR. Impressions have an indirect effect on Watch Time and Views but smaller than the direct effect, so the best path to increase views is the direct effect path of impressions. Impressions have a direct effect of 1,214 while CTR has a direct effect on views of 1,077. Keywords: YouTube, Views, Path Analysis, Direct Effect
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Roberts, Bill. "‘Teaching’ Practicing." Practicing Anthropology 28, no. 1 (January 1, 2006): 44. http://dx.doi.org/10.17730/praa.28.1.t0600510452t8470.
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The introduction to this issue states that this is a different style PA issue, and so this iteration of Teaching Practicing follows in the same spirit. Learning to practice anthropology is based on experience. If experience is the best teacher, then our over-riding question should be, "how can we best help our students learn lessons about the world of practice, and the conditions under which many of our colleagues practice, as illustrated so well by the preceding articles?" How can we help our students think about identifying the ethical issues that require careful consideration before action is taken? What are the logistics, liabilities and precautions required to work in areas of the world where cultures of violence exist, yet efforts are underway to provide relief, assistance or even attempts to promote understanding and peace? How can we comfortably stand by and watch or study extreme situations from afar, when we have an opportunity to make a difference? For us, part of the passion one derives from teaching is this opportunity.
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Gala, Leticya, Willem J. F. A. Tumbuan, and Shinta Wangke. "ANALYZING MANADO YOUTH PREFERENCES ON ONLINE MOVIE STREAMING." Jurnal EMBA : Jurnal Riset Ekonomi, Manajemen, Bisnis dan Akuntansi 11, no. 1 (March 29, 2023): 1393–99. http://dx.doi.org/10.35794/emba.v11i1.47501.
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Nowadays, young people dominate the use of the internet. One thing that we can do with the internet is watch a movie. Currently, there are many online movie streaming platforms available, including Viu, Disney+ Hotstar, and Netflix. Based on the problem's background, this research aims to determine which movie streaming platforms are most demanded by young people in Manado. This research uses quantitative methods to measure data. The method used is the Analytical Hierarchy Process (AHP) method. The AHP method is for rating alternatives to decisions and selecting the best multiple criteria, allowing users to assess the relative weights of some criteria given intuitively. The study shows that young people in Manado prefer the Disney+ Hotstar streaming application over other alternatives. Ease of Use is the essential criterion for young people in Manado in deciding which movie streaming application they choose. Keywords: customer preferences, analytical hierarchy process
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Soeharli, Kevin Ardhana, and Satya Aditya Wibowo. "How to maintain and expand the star wars film franchise in Indonesia." Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan 4, no. 10 (May 25, 2022): 4347–69. http://dx.doi.org/10.32670/fairvalue.v4i10.1657.
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The objectives of this research are to find out the primary reasons Indonesian customers watch the movies. To advise a proper marketing strategy for future Star Wars films so the revenue of the film franchise will grow optimally. In other words, to increase the number of Star Wars films audience. To find out the optimal promotional channel for the Star Wars film franchise to expand its customer base in Indonesia. To develop an implementation plan for the proposed marketing strategy. This research used primary and secondary data. The primary data are from quantitative and qualitative research, whereas the secondary data are from various internet sources. The conclusion shows that the future of the Star Wars film franchise is deeply connected and dependent on its fanbase due to the nature of the Star Wars brand embedding nostalgia within its fans, young and old. Time and time again, the fans have been responsible for some of the best marketing ploys in the industry, like Star Wars Day, “May the fourth be with you,” which was organically created by the fans to appreciate and celebrate the Star Wars films. Star Wars fans continue to create demands for Star Wars films and merchandise. They also organically create new fans by spreading their joy and hobby in Star Wars. Indonesian customers watch movies to be entertained but a major reason is so that they are up to date with the current trend.
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Bianco, Giuliana, Luca Foti, Raffaella Pascale, Filomena Lelario, Donatella Coviello, Monica Brienza, Sabino Bufo, and Laura Scrano. "Phosphodiesterase-5 (PDE-5) Inhibitors as Emergent Environmental Contaminants: Advanced Remediation and Analytical Methods." Water 13, no. 20 (October 13, 2021): 2859. http://dx.doi.org/10.3390/w13202859.
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Pharmaceuticals, fundamental in therapy and the prevention of known pathologies, are responsible for environmental pollution. These substances, called “emerging contaminants,” are harmful to human health because they enter the environment in quantities exceeding the natural self-capacity purification of the ecosystems. Furthermore, wastewater treatment plants (WWTPs) cannot remove these substances, which can undergo chemical/biological transformations in the environment, thus forming by-products, sometimes more toxic than the parent molecules; successively, they move into rivers and could reach the drinking water supplies. All these phenomena represent a severe public health problem. Therefore, the Water Framework Directive by European Union imposed the monitoring of drugs’ levels in aqueous matrices. Every two years, the EU carefully updates the list of potential water pollutants, called the Watch List, including pharmaceuticals, to evaluate their risk on the aquatic environment. The last Commission Implementing Decision (EU 2018/840) comprises several substances of primary concern. In addition, the scientific community is giving particular attention to other pharmaceuticals not yet on the Watch list, whose markets are in growth; particularly, the Phosphodiesterase 5 (PDE-5) inhibitors used for the pharmaceutical treatment of erectile dysfunction (ED) in men. This review discusses the presence of PDE-5 inhibitors in environmental systems, their toxic effects, the different kinds of removal, and the analytical methods normally adopted for their detection. In addition, the study helps figure out the best possible strategy to tackle pharmaceutical pollution by using analytical and advanced diagnostic methods.
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Emile, Sameh Hany, and Anjelli Wignakumar. "Non-operative management of rectal cancer: Highlighting the controversies." World Journal of Gastrointestinal Surgery 16, no. 6 (June 27, 2024): 1501–6. http://dx.doi.org/10.4240/wjgs.v16.i6.1501.
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There remains much ambiguity on what non-operative management (NOM) of rectal cancer truly entails in terms of the methods to be adopted and the best algorithm to follow. This is clearly shown by the discordance between various national and international guidelines on NOM of rectal cancer. The main aim of the NOM strategy is organ preservation and avoiding unnecessary surgical intervention, which carries its own risk of morbidity. A highly specific and sensitive surveillance program must be devised to avoid patients undergoing unnecessary surgical interventions. In many studies, NOM, often interchangeably called the Watch and Wait strategy, has been shown as a promising treatment option when undertaken in the appropriate patient population, where a clinical complete response is achieved. However, there are no clear guidelines on patient selection for NOM along with the optimal method of surveillance.
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Holttum, Sue. "Research watch: Coronavirus (COVID-19), mental health and social inclusion in the UK and Ireland." Mental Health and Social Inclusion 24, no. 3 (June 30, 2020): 117–23. http://dx.doi.org/10.1108/mhsi-05-2020-0032.
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Purpose This paper aims to examine recent papers on the effects of the COVID-19 pandemic on mental health, including implications for some of the groups of people already less included in society. Design/methodology/approach A search was carried out for recent papers on mental health and the COVID-19 pandemic. Findings Two papers describe surveys of adults in the UK and Irish Republic in the first days of lockdown. Low income and loss of income were associated with anxiety and depression. These surveys could not examine distress in Black and minority ethnicities, who have higher death rates from COVID-19. Two surveys of children and young people report distress and what can help. One paper summarises a host of ways in which the pandemic may affect mental well-being in different groups, and what might help. Another calls for research to understand how to protect mental well-being in various groups. Originality/value These five papers give a sense of the early days of the pandemic, especially in the UK. They also highlight the needs of some specific groups of people, or the need to find out more about how these groups experience the pandemic. They suggest some ways of trying to ensure that everyone has the best chance to thrive in the aftermath of the pandemic.
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LIAO, Chin-Nung, Chih-Hsiang LIN, and Yan-Kai FU. "INTEGRATIVE MODEL FOR THE SELECTION OF A NEW PRODUCT LAUNCH STRATEGY, BASED ON ANP, TOPSIS AND MCGP: A CASE STUDY." Technological and Economic Development of Economy 22, no. 5 (November 3, 2015): 715–37. http://dx.doi.org/10.3846/20294913.2015.1074951.
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New product launch strategy is a key competitive advantage for a new product development. A new product launch is a multiple criteria decision-making problem, which involves evaluating different criteria or attributes in a strategy selection process. The purpose of this paper is to develop a qualitative and quantitative approach for the selection of a new product launch strategy. The current study proposes an integrated approach, integrating analytic network process, the technique for order preference by similarity to an ideal solution and multi-choice goal programming, which can be used to determine the best launch strategy for marketing problems. The advantage of this integrated method is that it enables the consideration of both tangible (qualitative) and intangible (quantitative) criteria as well as both “more/higher is better” (e.g., benefit criteria) and “less/lower is better” (e.g., cost criteria) in the launch strategy of a new product selection problem. To show the practicality and usefulness of this method, an empirical example of a watch company is demonstrated.
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Kidenda, Dr Mary Claire Akinyi. "THE NECESSITY FOR PARENTS TO WATCH ANIMATED CARTOONS WITH CHILDREN AGED SEVEN TO ELEVEN YEARS." Journal of Education and Practice 2, no. 1 (November 16, 2018): 42. http://dx.doi.org/10.47941/jep.261.
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Purpose: The purpose of this study was to establish the necessity for parents to watch televised animated cartoons with children aged seven to eleven years.Methodology: The study used a descriptive survey method to collect information through casual interviews and self-administered questionnaires.Results: The study found out that the amount of time children spend watching animated cartoons on television can make them retract from social interactions with visitors, parents or other siblings when the television is on. Animated cartoons have an impact on children in respect to acquired or "borrowed" language and dressing styles and attitudes towards role types. These relations may be imperceptible to the casual observer but data show that the best (Kim Possible, Ben 10 and American Dragon) cartoon characters are idols, image ideals and role models to children in Nairobi, yet both the two cartoon characters are not representative of children they interact with every day. This study found that it is prudent animated cartoons affect the perceptions and attitudes that are being reinforced in children and the implication of this on how they construct their worldview and self-worth.Unique contribution to theory, practice and policy: Parents should be concerned and watch animated cartoons with children because animated cartoons have become an institution through which society is using to bring up children and use to teach values. Media practitioners should air animated cartoons that have no violence or bad morals but are still popular with children. The government should set policies governing the content in animated cartoons aired by the media houses
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Fadhia raihan, Aqilla, Ika Mustika, and Dida Firmansyah. "BEDAH ALUR EKRANISASI NOVEL BUMI MANUSIA KARYA PRAMOEDYA ANANTA TOER KE DALAM FILM KARYA HANUNG BRAMANTYO." Parole : Jurnal Pendidikan Bahasa dan Sastra Indonesia 6, no. 5 (November 27, 2023): 509–18. http://dx.doi.org/10.22460/parole.v6i5.21496.
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Currently, literart works become a trend among all ages because of changes in form that add to the aesthetics of a literary work. Not infrequently a literary work becomes a film that is widely carried out by filmmakers. Most people choose to watch movies in the midst of their busy lives to calm their minds from various activites. This is further strengthened by the number of best-selling novels in the market which are converted into films. Whether youth novels, horror, even history, a novel can be turned into an interesting and worthy film to watch. In this study, researchers chose the novel Bumi Manusia by Pramoedya Ananta Toer and the film Bumi Manusia by director Hanung Bramantyo as research materials. The purpose of this study is to describe the process of ecranization of the plot, setting, character, both in terms of categories of shrinking, adding, and varying aspects in the transfer of the novel to the film form. Data is done by reading, then watching, then taking notes. The results show that the ecranization process occurs in the elements of the plot, setting, character, namely the existence of various shrinkage, additions and changes. As for the various changes that occur at the end of the scenes that seem to be accelerated by the omission of scenes in the novel. When the screening of the film does not deviate from the plot of the novel and these changes add to the content of the meaning of the film Bumi Manusia.
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Watkins, John. "How I Almost Solved the Problem of Induction." Philosophy 70, no. 273 (July 1995): 429–35. http://dx.doi.org/10.1017/s0031819100065608.
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At the seventh international congress of Logic, Methodology, and Philosophy of Science, held at Salzburg in 1983, I was talking with John Searle when I glanced at my watch and exclaimed, I must run. I'm due to solve the problem of induction at 2.15. ‘Yes,’ he replied, I must go too; I'm due to solve the mind-body problem. I don't know how seriously he meant his remark, but I did actually believe that I had cracked this old problem in the Epilogue of my Science and Scepticism,1 the manuscript of which was then with the publisher. In that book I drew a sharp distinction between the problem which faces a theoretical scientist trying to select, out of several competing theories, the one that best fulfils the aim of science, and the pragmatic problem which faces an applied scientist or practical decision-maker trying to select, out of several competing hypotheses, the one that offers the best guidance. I had what I still regard as a viable solution to the theoreticians problem. It aid that theoreticians should prefer that theory, if there is one, that is the best corroborated; for on a certain non-trivial but uncontroversial assumption about what kinds of test have been made, the best corroborated theory will best satisfy what I claimed to be the optimum aim for science: it will be deeper and wider than its rivals and, moreover, possibly true, given all the reported outcomes of tests in its field. For present purposes we can forget the explications I offered for ‘deeper’ and ‘wider’. As to ‘possibly true’: this reflects the abandonment of hopes (still nursed as recently as 1918 by Moritz Schlick, for example) that science can arrive at theories that are certainly true, or at least have a high probability of being true, or at the very least have had their probability raised by the experimental evidence.
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Santos, Ana Luisa, Filipa Barros, and António Azevedo. "Matching-up celebrities’ brands with products and social causes." Journal of Product & Brand Management 28, no. 2 (March 11, 2019): 242–55. http://dx.doi.org/10.1108/jpbm-03-2017-1439.
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PurposeBeyond traditional brand endorsement, many celebrities have in recent years decided to launch their own product lines, which may be used to promote their own celebrity brand. Which product categories or social causes match a celebrity’s brand personality? This study aims to investigate the antecedents of celebrity–product degree of fit and willingness to pay (WTP)/make a donation in different scenarios. The manipulation of the scenarios aims to capture the role of celebrity attributes, perceived personality profiles, product involvement and acceptance of social causes.Design/methodology/approachIn total, 335 respondents answered an online questionnaire with a factorial plan corresponding to 20 different matching scenarios: five celebrities/perceived personalities (Emma Watson, Jennifer Lawrence, Kim Kardashian, Natalie Portman and Scarlet Johansson) × four types of branding scenarios (a lipstick for low involvement; a watch for high involvement; an eco-foundation for “high social acceptance” and vodka for “low social acceptance/controversial”).FindingsScarlett Johansson obtained the highest degree of fit, both for launching her own brand of lipstick or a watch. Kim Kardashian had the best degree of fit for launching her own vodka brand, while Emma Watson’s attributes confirmed that she would be seen as the ideal founder of an eco-foundation. Significant predictors of WTP/make a donation were assessed by multiple linear regression for each type of product.Practical implicationsThe paper provides recommendations that may help guide celebrity brand managers through the celebrity–product matching process.Social implicationsCelebrity branding in relation to social causes is also discussed in this paper.Originality/valueThis study explores a gap found in the literature as it explores the product match-up hypotheses within a celebrity branding context and moreover extends this investigation to social causes and products with different degrees of involvement and social acceptance.
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Avdić, Dino, and Marina Bagić Babac. "APPLICATION OF AFFECTIVE LEXICONS IN SPORTS TEXT MINING: A CASE STUDY OF FIFA WORLD CUP 2018." South Eastern European Journal of Communication 3, no. 2 (December 30, 2021): 23–33. http://dx.doi.org/10.47960/2712-0457.2021.2.3.23.
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World Cup is a major football event that is globally popular and has its very best influence on human emotions. As such, it affects how people verbally discuss football topics on the Internet. In addition, it shows great significance when viewers who usually do not watch other football competitions start paying close attention when their nation plays a World Cup football match. In this paper, fans’ online behaviour during World Cup 2018 was analysed using text mining methods. With the use of emotion analysis, it is noticed that there are different emotional states through which people go while sharing their thoughts with other people about football. Reddit, a discussion Internet website, was used as a generator of user data. Five supervised machine learning algorithms were used to test and revise an existing model. It is affirmed that the model successfully predicts the emotions within the text with an average accuracy of 78%.
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Wang, Eunice S., and Jeffrey Baron. "Management of toxicities associated with targeted therapies for acute myeloid leukemia: when to push through and when to stop." Hematology 2020, no. 1 (December 4, 2020): 57–66. http://dx.doi.org/10.1182/hematology.2020000089.
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Abstract The recent advent of myriad targeted therapies for acute myeloid leukemia (AML) has led to new hope for our patients but has also introduced new challenges in managing the disease. For clinicians, the ability to treat AML in the outpatient setting with novel agents of equal or greater efficacy than 7+3 has been transformative. Despite the enthusiasm, however, the reality is that many patients are still frail and remain at risk for treatment-related complications. Translating the results of clinical trials into improved outcomes for these individuals requires an understanding of how best to manage the adverse effects of these agents. Which patients benefit most and what to watch for? When to stop therapy? Using illustrative case presentations, this review details the unique toxicities associated with each of the approved mutation-specific and nonspecific targeted drugs for AML. The goal of this review is to help clinicians determine the risk:benefit ratio in decision making for individual patients with AML.
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Karo Karo, Ichwanul Muslim, Sri Dewi, Mardiana Mardiana, Fanny Ramadhani, and Putri Harliana. "K-Means and K-Medoids Algorithm Comparison for Clustering Forest Fire Location in Indonesia." Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) 10, no. 1 (April 19, 2023): 86–94. http://dx.doi.org/10.33019/jurnalecotipe.v10i1.3896.
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Forest fires are the most common cause of deforestation in Indonesia. This condition has a negative impact on the survival of living things. Of course, this has received special attention from various parties. One effort that can be made for prevention is to group these points into areas with the potential for fire using the clustering method. In this research, a comparative study of the clustering algorithm between K-Means and K-Medoids was conducted on hotspot location data obtained from Global Forest Watch (GFW). Besides that, important variables that affect the clustering process are also analyzed in terms of feature importance. There are nine important variables used in the clustering process, of which the Acq_time variable is the most important. The cluster quality of both algorithms is evaluated using the silhouette coefficient (SC). Both algorithms are capable of producing strong clusters. The best number of clusters is six clusters. The K-medoids algorithm is better at grouping data than K-means.
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Lee, Hyoung-kon. "The Actuality on Tea Tao as a way of cultivation: as to its philosophical basis." Association for International Tea Culture 57 (September 30, 2022): 83–114. http://dx.doi.org/10.21483/qwoaud.57..202209.83.
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This study is about presenting a practical way to cultivate mind based on the tea as a spiritual concept of the Tea Tao (茶道) and a ceremonial concept of the Confucian thought. Specifically, this study analyzed Tea Tao as a way of cultivation (修養) in three different cultural aspects, which are respect, sincerity, and courtesy. The characteristics of Confucianism are that the human nature is the principle of the sky and the duty of human being, we have to preserve the mind and train the nature. To do so, we need to watch ourselves, which is referred to as the inner reflection. Also, we need to watch out our actions based on respect, sincerity, and courtesy.
In the tea drinking culture of the mind cultivation theory, making tea with energy from heaven with all your heart. By doing so, tea and oneself become one, not two. reaching the state of introspection while drinking alone with nature as a friend. According to the yin-da culture of cultivation theory, greedy comes from the abundance of material leading to worries, defilements, wrongdoings, and extravagant thoughts. The practice of tea ceremony is to rectify the body and mind, and to keep the mind from being greedy. Also, 'Ki control (气統制) and Temperance (心節制)' is to change the temperament and make it good. Tea with Ki, which is the mechanism for cultivation, is highly effective in cultivating. In addition, renunciation of greed and the good attitude of the heart (制心) is required to cultivate the mind even thought the mind is originally bright, Finally, by letting go of selfish mind and obsession and meditating in a sitting position to find the nature, the mind will settle down and cultivation will lead to enlightenment through tea. It will become the best state of tea life, and it will reach the state of Confucianism that preserves the principles of heaven and removes greed.
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A.M. Ahmadova. "THE COMPARISON OF TRADITIONAL MEDIA AND SOCIAL MEDIA IN SPORT NEWS." Scientific News of Academy of Physical Education and Sport 4, no. 1 (June 6, 2022): 175–79. http://dx.doi.org/10.28942/ssj.v4i1.498.
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The purpose of this article is both to create a very contemporary understanding of traditional media and social media regarding sport news and to provide readers with a broader context. All over the world for years people used traditional media which represents a form of communication employing vocal, verbal, musical and visual folk art forms, transmitted to a society or group of societies from one generation to another. Nowadays we can find thousands of resources about social media that are spread live news all over the world. Especially the sport news in social media make easier to get the results immediately after the game or to watch from home all the results. With this article, we will touch on the role of both, traditional media and social media and comparing them in sports news. For the best presentation of the credible news each sport journalist needs to get the exact facts, videos and photos. Some sports needed to promotion and presentation depending on the media outlets which is interested in it. The sport fans, especially the huge games audience are the customers of both media which also try to save its ranking all over the world.
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Yi, Yang, Yang Sun, Saimei Yuan, Yiji Zhu, Mengyi Zhang, and Wenjun Zhu. "COWO: towards real-time spatiotemporal action localization in videos." Assembly Automation 42, no. 2 (January 18, 2022): 202–8. http://dx.doi.org/10.1108/aa-07-2021-0098.
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Purpose The purpose of this paper is to provide a fast and accurate network for spatiotemporal action localization in videos. It detects human actions both in time and space simultaneously in real-time, which is applicable in real-world scenarios such as safety monitoring and collaborative assembly. Design/methodology/approach This paper design an end-to-end deep learning network called collaborator only watch once (COWO). COWO recognizes the ongoing human activities in real-time with enhanced accuracy. COWO inherits from the architecture of you only watch once (YOWO), known to be the best performing network for online action localization to date, but with three major structural modifications: COWO enhances the intraclass compactness and enlarges the interclass separability in the feature level. A new correlation channel fusion and attention mechanism are designed based on the Pearson correlation coefficient. Accordingly, a correction loss function is designed. This function minimizes the same class distance and enhances the intraclass compactness. Use a probabilistic K-means clustering technique for selecting the initial seed points. The idea behind this is that the initial distance between cluster centers should be as considerable as possible. CIOU regression loss function is applied instead of the Smooth L1 loss function to help the model converge stably. Findings COWO outperforms the original YOWO with improvements of frame mAP 3% and 2.1% at a speed of 35.12 fps. Compared with the two-stream, T-CNN, C3D, the improvement is about 5% and 14.5% when applied to J-HMDB-21, UCF101-24 and AGOT data sets. Originality/value COWO extends more flexibility for assembly scenarios as it perceives spatiotemporal human actions in real-time. It contributes to many real-world scenarios such as safety monitoring and collaborative assembly.
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Wibawa, Aji Prasetya, Adjie Rosyidin, Fitriana Kurniawati, Gwinny Tirza Rarastri, Ilham Ari Elbaith Zaeni, Suyono Suyono, Agung Bella Putra Utama, and Felix Andika Dwiyanto. "Mining the public sentiment for wayang climen preservation and promotion." International Journal of Visual and Performing Arts 5, no. 2 (November 10, 2023): 84–95. http://dx.doi.org/10.31763/viperarts.v5i2.1163.
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Indonesia is a country that has a variety of cultural arts, one of which is shadow puppetry (Wayang). Wayang, in a staged, simple, and minimalist manner, is called Wayang Climen. Wayang Climen has been performed since the COVID-19 pandemic as a solution to keep working while still complying with health protocols. Utilization through YouTube social media attracts people to watch and provide opinions through comments. This opinion is beneficial and can be used as a feasibility study through sentiment analysis information classified as positive, negative, and neutral opinions. Sentiment analysis determines a person's opinion and tendency to opinionated sentences. The methods used are Random Forest (RF), Support Vector Machine (SVM), and Naïve Bayes (NB). The dataset comes from YouTube comments of Dalang Seno and Ki Seno Nugroho. The best accuracy is generated by SVM (70.29%). The positive sentiment shows the public's appreciation for the Wayang Climen performance, which ultimately represents the performance even though it is staged densely. This research contributes to effectively utilizing digital platforms for cultural preservation and audience engagement during challenging times, demonstrating the potential for innovative solutions in traditional arts and entertainment.
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Tapinaki, S., M. Skamantzari, R. Chliverou, V. Evgenikou, A. M. Konidi, E. Ioannatou, A. Mylonas, and A. Georgopoulos. "3D IMAGE BASED GEOMETRIC DOCUMENTATION OF A MEDIEVAL FORTRESS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W9 (January 31, 2019): 699–705. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w9-699-2019.
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<p><strong>Abstract.</strong> The detailed and thorough documentation of monuments is a rather complex process that requires the application of the best available state of the art techniques in order to preserve, restore, promote and make cultural heritage accessible to the public. This paper presents the 3D Geometric Documentation of a part of the medieval fortress of Chios, focussing in particular on the practical challenges which the object presented. The case study is a part of the fortified construction, consisting of a bastion, a watch tower on top of this bastion and a significant part of its walls with a surface of about 1053<span class="thinspace"></span>m<sup>2</sup> in total. The goal of the survey was to produce an accurate 3D detailed textured model and a series of coloured orthophotos and 2D vector drawings. The documentation methods employed included close-range automated photogrammetry and image-based modelling, terrestrial laser scanning and topographic surveys, an ideal combination of methods.</p>
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Kay, Shayna, Chimaobi Oyiliagu, and Amena Ali. "388 Prototyping a mobile phone application for Chimeric Antigen Receptor (CAR) T-cell therapy patient monitoring and data collection post-discharge." Journal of Clinical and Translational Science 8, s1 (April 2024): 115–16. http://dx.doi.org/10.1017/cts.2024.339.
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OBJECTIVES/GOALS: Research objectives include prototyping a mobile phone application that allows physicians to monitor CD19-directed CAR T-cell therapy patients remotely after discharge. This app will also enable standardized data collection across different centers that provide CAR-T cell therapy and allow for the harmonization of follow-up protocols. METHODS/STUDY POPULATION: Literature review and semi-structured interviews with patients, clinical coordinators, and other experts in the field will be used to determine what parameters must be included in the mobile application prototype to effectively monitor the side effects of CD19-directed CAR T-cell therapy. The mobile phone application will be designed using process mapping to integrate data from self-reporting and wearable technologies, including the Garmin smart watch. Figma will then be used to develop new screens based on an existing patient monitoring app for Allogeneic Stem Cell Transplant follow-up. Finally, a preliminary feasibility study will be conducted to collect feedback on the app prototype from CAR T-cell therapy patients, providers, and stakeholders. RESULTS/ANTICIPATED RESULTS: The anticipated results of this study include an app prototype that will include the functionalities required to monitor patients for adverse effects of CD19-directed CAR T-cell therapy. This will include the parameters that will be recorded or measured using a combination of self-reporting, a reliable body temperature sensor, and the Garmin watch which monitors basic vitals, activity, and sleep. Additional parameters may be added during the stakeholder co-design process. The app prototype will include a physician interface where doctors can monitor their patients and will be alerted if they require further physician assessment. It is expected that the app will provide standardized monitoring of patients when they are discharged from the hospital after receiving CAR T-cell therapy. DISCUSSION/SIGNIFICANCE: This app will allow physicians to monitor patients for general follow-up and adverse effects, including cytokine release syndrome and neurotoxicity. Future studies may utilize this app to develop best practices for harmonizing CAR-T follow-up protocols across Canada.
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Damanhuri, Ahmad Mafazi, and Zhang Huaping. "DESIGN OF PEOPLE PROFILING AND MODELING REPUTATION COMPUTATION BASED ON SENTIMENT ANALYSIS." SINERGI 23, no. 1 (February 28, 2019): 1. http://dx.doi.org/10.22441/sinergi.2019.1.001.
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The number of popular people is still growing because of the easiness to access information technology. Every time people upload things and let people watch it and give it a like or comment. People who can impress other people will grow their popularity and fame. Some famous people make influences, help poor people with powers, and others are causing troubles. Community these days drives people perspective by share their thoughts on social media. They spread information and makes others want to see things they are talked about. Troublesome popular people defended by their fan base and attacked by other communities. By these cases, the research tried to gather information on social media and used it for calculation and profiling. The method that proposed to rely on this information is based on sentiment analysis to look up someone’s record and listing them into top 10 best got from DBpedia. This system shows the list of people and contains all important record about that person which can be used for decision support for a policy or rewarding people. The results have successfully visualized the output in the list of people with any further details following by clicking their names.
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REDONDO-GARCÍA, JOSÉ LUIS, and ADOLFO LOZANO-TELLO. "ONTOTV: AN ONTOLOGY-BASED SYSTEM FOR THE MANAGEMENT OF INFORMATION ABOUT TELEVISION CONTENTS." International Journal of Semantic Computing 06, no. 01 (March 2012): 111–30. http://dx.doi.org/10.1142/s1793351x1250002x.
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Nowadays, there are a huge number of digital television platforms and channels, so it is not easy for the viewer to decide what they want to watch. Some television providers offer information about the programs they broadcast, but this information is usually scarce and there is no possibility to perform advanced operations like recommendation ones. For this reason, viewers could benefit from a system that integrates all the available information about contents, and applies semantics methodologies in order to provide a better television watching experience. The main objective of this research is the design of a television content management system, called OntoTV, which retrieves television content information from various existing sources and represents all these data in the best way possible by using knowledge engineering and ontologies. These semantic computing techniques make it possible to offer the viewers more useful operations on the stored data than traditional systems do, and with a high degree of personalization. Additionally, OntoTV accomplishes all of this regardless of the TV platform installed and the client device used. The viewers' satisfaction when using this system has been also studied to prove its functionality.
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Saeed, Muhammad Zubair, Sobia Sultana, Zujaj Ahmed, Muhammad Talha Aziz, and Kainat Fatima. "Macroeconomic Factors Influencing Market Capitalization of Pakistan Stock Exchange (PSX)." Research Journal for Societal Issues 5, no. 2 (June 30, 2023): 303–17. http://dx.doi.org/10.56976/rjsi.v5i2.102.
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Stock exchanges worldwide are discovering the best possible outcomes that can increase trading options in financial assets for potential investors. The principal purpose of the study is to provide an efficient and stable picture of market capitalization of Pakistan Stock Exchange (PSX) with various macroeconomic variables, which can be helpful to local and foreign investors. The study analyzed the secondary data from 1992 to 2021. Based on the theoretical background, various diagnostics were applied, precisely (ARDL) Autoregressive Distributed Lag methodology. Empirical outcomes confirmed that hypotheses regarding (FPE) Foreign Portfolio Equity, Inflation, (FDI) Foreign Direct Investment, and (GFCF) Gross Fixed Capital Formation affect market capitalization of PSX with significant positive behavior. Only Exchange Rate has significant negative relationship with PSX market capitalization. This study suggests that PSX-listed companies and policymakers require significant attention to improve their operations and increase the market capitalization of firms to catch the capital from potential investors. The government should watch the exchange rate and inflation-controlling factors for the sustainable development of Pakistan in the long run. However, this study has various limitations, such as limited time, resources, and specific data.
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Jebamalar, A., and Anbuselvi Anbuselvi. "Survey on Nearest Keyword Set Search in Multi-dimensional Datasets." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 8 (August 30, 2017): 64. http://dx.doi.org/10.23956/ijarcsse.v7i8.23.
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Keyword query in multi-dimensional datasets is a noteworthy application in information mining. It is normal that the articles in a spatial database (e.g. eateries/inns) are connected with keyword(s) to demonstrate their organizations/administrations/highlights. An interesting issue known as neighboring Keywords inquiry is to question objects, called catchphrase cover, which together cover an agreement of question watchwords and have the base among items remove. As of late, we watch the increasing accessibility and significance of catchword rating in protest assessment for the better basic leadership. This propels us to study a non-particular version of Closest Keywords search called Best Keyword Cover which considers among items remove and also the watchword evaluation of articles. The baseline algorithm is enlivened by the strategies for Closest Keywords search which depends on comprehensively joining objects from various query keywords to produce contestant catchphrase covers. At the point when the quantity of query keywords builds, the execution of the baseline algorithm drops extensively as a consequence of enormous competitor catchphrase covers produced. To assault this downside, this work proposes an a great deal more adaptable algorithm called catchphrase nearest neighbor expansion (watchword NNE). Contrasted with the baseline algorithm, watchword NNE algorithm fundamentally decreases the amount of applicant catchphrase covers formed. The surrounded by and out investigation and broad examinations on genuine information sets have legitimized the prevalence of our watchword NNE algorithm.
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Charalampos, Basdekis, Katsampoxakis Ioannis, and Gkolfinopoulos Alexandros. "VaR as a mitigating risk tool in the maritime sector: An empirical approach on freight rates." Quantitative Finance and Economics 6, no. 2 (2022): 158–76. http://dx.doi.org/10.3934/qfe.2022007.
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<abstract> <p>Shipping freight rates fluctuation is considered as one of the most important risk factors that participants face in the tanker shipping market (ship-owners, charterers, traders, hedge funds, banks and other financial institutions) in order to watch its evolution. This study examines freight rates for two of the most popular clean and dirty tanker routes; TC2 and TD3 from 22 May 2007 to 21 September 2015, using daily spot and future prices. The full data sample is divided into two sub periods, from 22 May 2007 to 13 August 2013 (in sample period) on which the model estimation section is based and from 14 August 2013 to 21 September 2015 (out of sample period) over which the Value at Risk is measured and backtesting process was performed. In all cases tested, there are observed high peaks and fat tails in all distributions. We apply a range of VaR models (parametric and non-parametric) in order to estimate the risk of the returns of TC2 route and TD3 route for spot, one month and three months future market. Backtesting tools are implemented in order to find the best fit model in terms of economic and statistical accuracy. Our empirical analysis concludes that the best fit models used for mitigating risk are simple GARCH model and non-parametric model. The above outcome seems to be valid a) for spot returns as well as for future returns and b) for short and long positions. In addition to the aforementioned conclusions, it is observed high freight rate risk at all routes. Our results are useful for risk management purposes for all the tanker shipping market participants and derivatives' counterparties.</p> </abstract>
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Zhai, Bing, Yu Guan, Michael Catt, and Thomas Plötz. "Ubi-SleepNet." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 4 (December 27, 2021): 1–33. http://dx.doi.org/10.1145/3494961.
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Sleep is a fundamental physiological process that is essential for sustaining a healthy body and mind. The gold standard for clinical sleep monitoring is polysomnography(PSG), based on which sleep can be categorized into five stages, including wake/rapid eye movement sleep (REM sleep)/Non-REM sleep 1 (N1)/Non-REM sleep 2 (N2)/Non-REM sleep 3 (N3). However, PSG is expensive, burdensome and not suitable for daily use. For long-term sleep monitoring, ubiquitous sensing may be a solution. Most recently, cardiac and movement sensing has become popular in classifying three-stage sleep, since both modalities can be easily acquired from research-grade or consumer-grade devices (e.g., Apple Watch). However, how best to fuse the data for greatest accuracy remains an open question. In this work, we comprehensively studied deep learning (DL)-based advanced fusion techniques consisting of three fusion strategies alongside three fusion methods for three-stage sleep classification based on two publicly available datasets. Experimental results demonstrate important evidences that three-stage sleep can be reliably classified by fusing cardiac/movement sensing modalities, which may potentially become a practical tool to conduct large-scale sleep stage assessment studies or long-term self-tracking on sleep. To accelerate the progression of sleep research in the ubiquitous/wearable computing community, we made this project open source, and the code can be found at: https://github.com/bzhai/Ubi-SleepNet.
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Shaddick, Gavin, James M. Salter, Vincent-Henri Peuch, Guilia Ruggeri, Matthew L. Thomas, Pierpaulo Mudu, Oksana Tarasova, Alexander Baklanov, and Sophie Gumy. "Global Air Quality: An Inter-Disciplinary Approach to Exposure Assessment for Burden of Disease Analyses." Atmosphere 12, no. 1 (December 31, 2020): 48. http://dx.doi.org/10.3390/atmos12010048.
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Global assessments of air quality and health require comprehensive estimates of the exposures to air pollution that are experienced by populations in every country. However, there are many countries in which measurements from ground-based monitoring are sparse or non-existent, with quality-control and representativeness providing additional challenges. While ground-based monitoring provides a far from complete picture of global air quality, there are other sources of information that provide comprehensive coverage across the globe. The World Health Organization developed the Data Integration Model for Air Quality (DIMAQ) to combine information from ground measurements with that from other sources, such as atmospheric chemical transport models and estimates from remote sensing satellites in order to produce the information that is required for health burden assessment and the calculation of air pollution-related Sustainable Development Goals indicators. Here, we show an example of the use of DIMAQ with the Copernicus Atmosphere Monitoring Service Re-Analysis (CAMSRA) of atmospheric composition, which represents the best practices in meteorology and climate monitoring that were developed under the World Meteorological Organization’s Global Atmosphere Watch programme. Estimates of PM2.5 from CAMSRA are integrated within the DIMAQ framework in order to produce high-resolution estimates of air pollution exposure that can be aggregated in a coherent fashion to produce country-level assessments of exposures.
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Buheji, Mohamed. "Book Review: The Rise to Market Leadership." International Journal of Business Administration 9, no. 2 (February 8, 2018): 44. http://dx.doi.org/10.5430/ijba.v9n2p44.
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Development has been happening the last two decades and specially the beginning of the 21st century shows that the emerging economies are going to change the formula of the current market dominated leadership. Certainly, many emerging economies as the BRICS countries is a must watch and explore markets from the perspective of being economies that having the strong diversified mix to make more sustainable as the developed countries markets and even more. The work of Malerba et al. (2017) team is highly important since it reflects not only the literature review but also the actual observations of the history of development of the BRICS countries, which resembled by China, India and Brazil. In fact, the book also shows the best practices in how did these new market leaders emerge and become key players in their respective industries. This review is considered of importance since it shows a model for other countries and how to manage the high industries risk and still manage to create market development. The review shows that there are similar industries as automotive, pharmaceutical and ICT industries which can contribute to the success of the developing countries and enable them to become market leaders too. The researchers were very focused on defining market leadership from the following three angles mainly: domination of local market, global reach and the innovative capabilities and capacity of the production or the processes.
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Yadav, Sanchit, and Kamlesh Kumar Singh. "Smart Environmental Health Monitoring System." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 2, no. 1 (April 5, 2021): 1–5. http://dx.doi.org/10.54060/jieee/002.01.003.
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Pollution is a growing issue these days. It is necessary to analyze environment & keep it in check for a for best future as well as healthy living for all. Here we propose an Envi-ronment Monitoring System that permit us to watch & check live environment in espe-cially areas through Internet of Things (IOT). IoT supported a real time environmental monitoring system. It plays a crucial role in today’s world through a huge and pro-tract-ed system of sensor networks concerned to the environment & its parameters. This technique deals with monitoring important environmental conditions like temperature, humidity & CO level using the sensor & then this data is shipped to the web page. This information is often access from anyplace over the internet & then the sensor in-formation is presented as graphical statistics during mobile application. This paper explains & present the implementation & outcome of this environmental system uses the sensors for temperature, humidity, air quality & different environmental parameters of the surrounding space. This data is often used to take remote actions to regulate the conditions. Information is pushed to the distributed storage & android app get to the cloud & present the effect to the end users. The system employs a Node MCU, DHT-11 sensor, MQl35 sensor, which transmits data to WEBPAGE. An Android application is made which accesses the cloud data and displays results to the end users. The sensors interact with microcontroller which processes this information & transmit it over internet. This system is best method for any use in monitoring the environment and handling it because everything is controlled automatically through all the time of the process. The results say everything about the application of this system across different field where it was controlled precisely and effectively which further explains that this system easily makes our work easier because of this automatic monitoring system worries about other unexpected climate issues for world.
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Lavanya, R., and B. Bharathi. "Movie Recommendation System to Solve Data Sparsity Using Collaborative Filtering Approach." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 5 (July 24, 2021): 1–14. http://dx.doi.org/10.1145/3459091.
Full textAbstract:
With the increase in numbers of multimedia technologies around us, movies and videos on social media and OTT platforms are growing, making it confusing for users to decide which one to watch for. For this, movie recommendation systems are widely used. It has been observed that two-thirds of the films watched on Netflix are the recommended ones to its users. The target of this work is to use implicit feedback given by other users to recommend movies, i.e., ratings given by them. Implicit feedback will help to enhance Data Sparsity as for a replacement logged-in user, the system won't have details of their past liked movies. So, matching the similarity with other users is often a plus point to recommend movies that they would like. The anticipated result will depend upon the positive attitude; i.e., if the predicted rating is high, then it'll be recommended; otherwise it'll not be recommended. The performance of the methodology is measured with accuracy and precision values for different strategies. It gives the best accuracy and highest precision values using Logistic Regression (LR) and lowest recall value as compared to other algorithms. This technique gives an accuracy, precision, and recall value of 81.9%, 69.82%, and 32.5%, respectively, using LR.
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Alaraj, Dr Mamoon. "The Role of Audio and Visual Media in Improving English-Speaking Proficiency from Saudi College Students’ Perspective." International Journal of Social Sciences and Humanities Invention 7, no. 12 (December 22, 2020): 6630. http://dx.doi.org/10.18535/ijsshi/v7i012.02.
Full textAbstract:
This study aims to deeply explore the Saudi college students’ perspective about the role of audio and visual English media in developing their English-speaking proficiency. To arrive to the best results possible a survey was used as a data collection tool. A focus group of five college students who were interested in improving their English proficiency was formed. Following the brainstorming technique, they created a questionnaire of six multiple choice, checkbox, rating, and scale questions which was reviewed by three experts and then piloted on 30 students, improved accordingly, created by Google Forms, and finally distributed online via WhatsApp groups. College students who were interested in improving their English-speaking proficiency and used to listen to and/or watch English media were requested to respond to the questionnaire. A sample of 65 college students’ responses were received and the data was analyzed by Google Forms. The major results revealed that: -the immense majority of students believed the English media could affect their speaking proficiency, -YouTube, social media, songs, and movies were the most repetitively and continuously used by students. -YouTube and movies were the types of media that affected the speaking proficiency the most. -Pronunciation was the most affected area by the media. Related educational recommendations and deeper further studies were suggested.
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Padayachee, Ashlyn L., Şerban Procheş, and John R. U. Wilson. "Prioritising potential incursions for contingency planning: pathways, species, and sites in Durban (eThekwini), South Africa as an example." NeoBiota 47 (June 19, 2019): 1–21. http://dx.doi.org/10.3897/neobiota.47.31959.
Full textAbstract:
Increased trade and travel have resulted in an increasing rate of introduction of biological organisms to new regions. Urban environments, such as cities, are hubs for human activities facilitating the introduction of alien species. Additionally, cities are susceptible to invading organisms as a result of the highly altered and transformed nature of these environments. Despite best efforts at prevention, new incursions of alien species will occur; therefore, prioritising incursion response efforts is essential. This study explores these ideas to identify priorities for strategic prevention planning in a South African city, Durban (eThekwini), by combining data from alien species watch lists, environmental criteria, and the pathways which facilitate the introduction of alien species in the city. Three species (with known adverse impacts elsewhere in the world) were identified as highly likely to be introduced and established in Durban (Alternantheraphiloxeroides,LithobatescatesbeianusandSolenopsisinvicta). These species are most likely to enter at either the Durban Harbour; pet and aquarium stores; or plant nurseries and garden centres – therefore active surveillance should target these sites as well as adjacent major river systems and infrastructure. We suggest that the integrated approach (species, pathways, and sites) demonstrated in this study will help prioritise resources to detect the most likely and damaging future incursions of alien species.
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Jaramillo, Julio J., Carlos A. Rivas, José Oteros, and Rafael M. Navarro-Cerrillo. "Forest Fragmentation and Landscape Connectivity Changes in Ecuadorian Mangroves: Some Hope for the Future?" Applied Sciences 13, no. 8 (April 16, 2023): 5001. http://dx.doi.org/10.3390/app13085001.
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This study investigates the impact of fragmentation on Ecuador’s coastal mangrove forests. Fragmentation is identified as a primary cause of aquatic ecosystem degradation. We analyzed the relationship between habitat loss, fragmentation, and mangrove connectivity through a multitemporal approach using Global Mangrove Watch and fragmentation and connectivity metrics. The terrain was divided into 10 km2 hexagons, and six fragmentation metrics were calculated. A Getis–Ord Gi* statistical analysis was used to identified areas with the best and worst conservation status, while connectivity analyses were performed for a generic species with a 5 km dispersion. Findings revealed widespread mangrove fragmentation in Ecuador, with geographical differences between the insular region (Galapagos) and the mainland coast. Minimal loss or even expansion of mangrove forests in areas like the Galapagos Islands contrasted with severe fragmentation along the mainland coast. Transformation of forests into fisheries, mainly prawn factories, was the primary driver of change, while only a weak correlation was observed between mangrove fragmentation and conversion to agriculture, which accounts for less than 15% of all deforestation in Ecuador. Fragmentation may increase or decrease depending on the management of different deforestation drivers and should be considered in large-scale mangrove monitoring. Focusing only on mangrove deforestation rates in defining regional conservation priorities may overlook the loss of ecosystem functions and fragmentation.
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Markovic Vasiljkovic, Biljana, Aleksa Janovic, Svetlana Antic, Branko Dozic, Milos Bracanovic, and Djurdja Bracanovic. "Chondrosarcoma of the Alveolar Process of the Mandible Initially Suspected to Be a Periodontal Lesion." Diagnostics 14, no. 4 (February 6, 2024): 348. http://dx.doi.org/10.3390/diagnostics14040348.
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Chondrosarcoma (CS) initially suspected to be a periodontal lesion is atypical and rare. To the best of our knowledge, only six similar cases have been reported so far. A 47-year-old woman presented with a discreet swelling of the alveolar process of the mandible, while adjacent mucosa appeared normal. Upon initial intraoral radiography, a periodontal lesion was suspected by the ordinating dentist. Further radiological evaluations included CBCT, CT, and MRI, which showed a thickening of the supporting bone with ground-glass foci but without visible calcifications. The periodontal space of the affected teeth appeared to be uniformly widened. The destruction of the vestibular and lingual cortex was observed, as well as a discreet periosteal reaction, implying the secondary involvement of these teeth and not the odontogenic nature of the lesion. The lesion was restricted to the alveolar process of the mandible, and the bone marrow was not affected. Upon biopsy, a preliminary histopathology report suggested chondrosarcoma, and the patient underwent surgery. It is important to emphasize the possible malignant nature of atypical lesions in the alveolar bone, especially in cases with the expansion of vestibular and lingual cortical plates. Additionally, postoperative “watch and see” follow-ups may be considered in cases of CS in the jaws.