Reviewerly/exHarmony huggingface dataset:
Utilization of Modified NDVIred and red edge algorithm for analysis of Mangrove ecosystem conditions in Lembar bay area of West Lombok Indonesia

Efforts to collect data and information about the profile of coastal resources, especially mangrove ecosystems are very necessary.This can be done through in ventory activities that aim to obtain a clear and real picture of the condition and potential of mangrove vegetation on an ongoing basis.Therefore, thepurpose of this study is to utilize the modified NDVI red and red edge algorithm to determine the condition of the mangrove ecosystem in the mangrove ecosystem area of LembarBay, West Lombok Regency.The research method used is a survey method approach with either direct or indirect surveys.The algorithm analysis of the vegetation index used in this study is NDVI red and red edge .The results showed that the mangrove ecosystem area in the Lembar bay area, West Lombok, was mostly categorized in good condition, which was about 45.27% of the total area of the mangrove ecosystem.Most of the mangrove ecosystem areas with dense conditions are areas that are far from settlements and fishponds, dominated by natural mangroves which are very rarely visited by both local communities and outside communities so that the utilization rate is relatively low.
Sign Language Detection Using Hand Gestures

Abstract- Some of the major problems faced by a person who are unable to speak are, they cannot express their emotion and they are unable to use (Artificial Intelligence) like google assistance, or Apple's SIRI etc because all those apps are based on voice controlling. Hand gestures are one of the nonverbal communication strategies used in sign language. People who are deaf or hard of hearing are the ones who use it the most to communicate with one another and with others. Various sign language systems have been developed by several firms across the world, however they are neither customizable nor costeffective for end users. We developed an app that recognises pre-defined American signed language using hand gestures (ASL).Our application will have two main featuresThe motion has been recognised, and the corresponding letter has been shown. The second feature is to display a meaningful word. In sign language each gesture has a specific meaning. So therefore complex meanings can be explain by the help of combination of various basic elements. Sign language contains special rules and grammar’s for expressing effectively. In a range of applications, such as human-computer interfaces, multimedia, and security
Presentasi Materi Value Proposition Design, Chapter IV: Evolve

Merupakan presentasi materi dari buku Osterwalder, A. et al. (2014) Value proposition design: How to create products and services customers want. New Jersey: John Wiley and Sons.
Formulation of Framework for Evacuation of Tsunami Disaster after COVID-19 Pandemic on The South Coast of Watulimo, Trenggalek

The research aims to identify and design the latest theory-based tsunami disaster evacuation after the COVID-19 pandemic. Analysis of temporary shelters and analysis of evacuation routes were used in research with scoring techniques and network analysis techniques. The conceptual framework related to tsunami disaster evacuation after the COVID-19 pandemic has been compiled in research and can be used as material for consideration to formulate government policies and determine contingency plans and operational plans that will be carried out in the event of a tsunami disaster following the COVID-19 pandemic. Parameters of temporary shelter variables that must be considered are building function, the number of floors, building capacity, road location, building area, distance from the beach, and building construction. The capacity of the temporary shelter before the COVID-19 pandemic was obtained from the building area divided by the minimum space requirement per person of 1.64 m2. After the COVID-19 pandemic, the minimum space requirement per person combined with a physical distance of 2 m, the total area required will be 6 m2/person. Meanwhile, the parameters of the evacuation route variables that must be considered are road width, travel time, road pavement conditions, and road class.
Development of Augmented Reality-Based Interactive “Element Card” Media on Electron Configuration Submaterial According to Niels Bohr

This study aims to obtain the feasibility of Augmented Reality-based Element Card interactive media on the electron configuration submaterial according to Bohr's theory. This research uses a 4D model which is only carried out until the development stage. This research was conducted at SMAN 1 Gedangan Sidoarjo on 30 students X IPA. This study used a validation sheet instrument, pretest and posttest questions, student response questionnaires, and student observation questionnaires. If the value of the validation result is ≥ 61% then it is considered valid, the practicality value is ≥ 61% then it is considered practical, and the effectiveness value if it is classified above 0.3 which includes medium or high then it is considered effective. The results of content and construct validation are 88% and 84% are included in the very valid category. Practicality was obtained from 94.86% and 97% of student responses and observations included in the very practical. The effectiveness is obtained from learning outcomes by calculating the N-Gain and Wilcoxon Signed Ranks Test, the value of Asymp. Sig (2 tailed) is 0.000 which is smaller than 0.05 so there is a difference in the students' pretest and posttest scores. This proves that the interactive media based on the Augmented Reality Element Card can be used for chemistry learning media.
The Profile of Efl Learners As Measured By An English Proficiency Test

This study aims at profiling the students’ English proficiency in the Department of English, Universitas Negeri Malang (UM). The English proficiency of 277 students across admission Classes in 2016, 2015, 2014, and 2013 who are involved in the study is measured by using a proficiency test. The subtests reliability was assured and the data was analyzed by using descriptive and inferential statistical analyses. The results show no respondent reached the advanced level; the majority was in the low intermediate level. It indicates that the respondents’ score was not linear with their year of admission classes. However, a linearly increasing average score was respectively observed from the scores of Classes of 2015, 2014, and 2013. Statistical differences in the mean scores of the students across admission classes were observed. Next, no evidence of statistical differences was observed in the mean score of the students across different study programs in their seventh semester. Finally, none of Class of 2013 exactly met the graduate profile. However, those beyond the profile and those below the profile were marginally comparable. These findings were further discussed.
Building a Strong Partnership with International Partner Institutions

The three stages for building a solid partnership between international partner universities are collaboration management, development program, and strengthening. Collaboration management is needed to tie the partnership between universities. Since the partner universities may have different time zones and cultures, good collaboration is needed. The partnership can be secured by developing programs for its effective implementation. The program can be academic such as student exchange, joint degree, faculty exchange, joint research and publication, international conference, and visiting scholars programs. To have a solid partnership, each university must run the program together. Programs with three or more partners can form a consortium. The consortium in turn can help each university strengthen its collaboration, increase the university ranking, and develop more benefit programs.&#x0D; Keywords: collaboration management, development program, solid partnerships
Utilizing WhatsApp Group as a Medium of Lecturer-Students Interaction in EFL Classes during COVID-19 Pandemic

Abstract: This study aims to investigate learners' perceptions and attitudes towards the interaction between lecturer and learners in WhatsApp groups regarding university's closure caused by the COVID-19 pandemic. This research employed a survey design, involving 60 university students who were required to complete a set of close-ended and open-ended questionnaires. The findings showed that the use of WhatsApp group discussion has benefited the students greatly to engage with their lecturer and their classmates. Around 55.17 percent of the respondents perceived the WhatsApp group discussion positively, 27.55 percent perceived mixed and 17.24 percent negatively. Generally, the respondents perceive WhatsApp group discussion as a tool for convenience, accessibility, speed and even self-confidence for classroom interaction. However, some of the respondents also reported the drawbacks of WhatsApp Group discussion, namely, the distraction during the discussion, overwhelmed by the volume of the message, and lack of speaking activities in the WhatsApp-mediated classroom. Future research which includes lecturers’ perspective is needed to further explore the phenomenon of WhatsApp Group used in EFL classrooms. Keywords: perceptions, interaction, learners, lecturers, pandemic Abstrak: Penelitian ini dikembangkan untuk menginvestigasi persepsi dan sikap mahasiswa tentang interaksi antara dosen dan mahasiswa melalui WhatsApp grup sehubungan dengan ditutupnya universitas karena pandemic COVID-19. Penelitian ini menggunakan desain survey yang melibatkan 60 pelajar dari universitas untuk menyelesaikan satu set kuisioner dengan pertanyaan terbuka dan tertutup. Hasil dari penelitian ini memperlihatkan bahwa pengunaan diskusi pada WhatsApp grup menguntungkan mahasiswa untuk sangat terikat kepada dosen dan rekan sekelas. Sekitar 55,17 persen peserta beranggapan pengunaan WhatsApp grup positif, 27,55 persen merasa bimbang dan 17,24 persen negatif. Pada umumnya, para responden beranggapan bahwa diskusi WhatsApp grup merupakan alat untuk aspek kenyamanaan, aksebilitas, kecepatan, dan bahkan kepercayaan diri untuk berinteraksi dalam kelas. Namun, beberapa responden juga menyebutkan tentang kekurangan dari diskusi dalam WhatsApp grup, yaitu gangguan selama diskusi, kewalahan dengan jumlah pesan, dan kurangnya kegiatan speaking di kelas yang dimediasi menggunakan WhatsApp. Penelitian selanjutnya yang mencakup perspektif dosen diperlukan untuk lebih mengeksplorasi fenomena WhatsApp grup yang digunakan di kelas Bahasa Inggris. Kata kunci: persepsi, interaksi, mahasiswa, dosen, pandemi
Playing Tetris with Reinforcement Learning

Abstract: The essential inspiration for this uAndertaking was a pleasant utilization of AI. Tetris is a notable game that is cherished and loathed by a lot of people. Tetris game has a few qualitiesmaking it an intriguing issue for the field of ML. A total portrayal of the tetris issue incorporates tremendous number of states making a meaning of a non-learning procedure for all intents and purposes unthinkable. Late outcomes from the group at Google DeepMind have shown that support learning can have noteworthy execution at game playing, utilizing a negligible measure of earlier data about the game. We use support figuring out how to prepare an AI specialist to play tetris. Support learning permits the machine or programming specialist to gain proficiency with its conduct in light of the criticism that is gotten from the climate. The machine might adjust after some time or may advance once and proceed with that behavior. Tetris is played on a rectangular lattice divided into more modest square regions, regularly ten units wide by twenty units tall. The player controls the direction and even area of pieces that tumble from the highest point of the board to the base and procures focuses by framing total level lines, which are then eliminated from play, causing pieces put higher to move descending. The key speculation of this undertaking is that assuming that the focuses procured in Tetris are utilized as the prize capacity for an AI specialist, then that specialist ought to have the option to figure out how to play Tetris without other oversight.
Non-destructive Inspection of Subsurface Cracks in Carbon-fiber and Glass-fiber Reinforced Polymeric Materials Using Digital Shearography Method

Non-destructive Inspection of Subsurface Cracks in Carbon-fiber and Glass-fiber Reinforced Polymeric Materials Using Digital Shearography Method
Secured Lottery System Using Smart Contract and Blockchain Technology

Abstract: To create a lottery based smart contract on ethereum blockchain for increasing transparency and reduce frauds in the lottery industry. Once the contract has been deployed by the administrator, there will be a minimum contribution amount for players to register in the game and a price pool will be maintained by the smart contract. The winning process will be structured in a way such that only the administrator's wallet will be authorized to initiate the process to randomly pick an address and the smart contract will by definition transfer the prize to the winner. The contract once deployed on blockchain cannot be changed by the administrator to maintain transparency and fairness. Keywords: Smart contract, lottery system, application of ethereum, blockchain technology.
Gender Voice Recognition Using Machine Learning Algorithms

Abstract: Gender identification is one of the major problems in the area of signal processing. The system deals with finding the gender of a person using oral features. One of the most persnickety problems faced is feature selection from wide range of features, which is distinguishing factor in classifying the gender of aperson. The ideal of this design is to design a system that determines the speaker gender using the pitch of the speaker's voice. relating the gender from the plots of voice data set i.e., pitch, median, frequency etc. can be possible by using machine learning. In this design, we're trying to classify gender into male or female based on the data set containing varied attributes related to voice like pitch, frequency etc. The data set have features with explanation data points recorded samples of male and female voices. The data set can be trained with different machine learning algorithms. The proposed system can determine the gender of the speaker with real time test data a new result to discover the gender of the speaker using Fast Fourier Transform with Logistic Regression
An evolution of virtual training: implications for talent development in the post-pandemic period

Purpose This study examines the effectiveness of virtual training programs in times of crisis at a public institution in South Africa for an enhancement of talent development via virtual training in the post-pandemic period. Design/methodology/approach This study adopted a survey research design following a quantitative approach for data collection and analysis procedure. The respondents (employees receiving virtual training and the facilitators providing the training in times of crisis) were selected using a stratified random sampling technique. A structured questionnaire was designed and administered to 119 respondents in the participating public institution in South Africa. The data were analyzed using a variance-based structural equation modeling via SmartPLS, version 3.3.3. Findings The results showcased the impact of information technology and virtual training platform on the effectiveness of virtual training programs during the pandemic in South Africa. Originality There is a dearth of literature on the evolution and effectiveness of virtual training in times of crisis in South Africa. The outcomes of this study contribute to the extant literature on talent development, virtual training, and HR effectiveness in the digital age.
Fifty years of SPIE Medical Imaging proceedings papers

Purpose: To commemorate the 50th anniversary of the first SPIE Medical Imaging meeting, we highlight some of the important publications published in the conference proceedings. Approach: We determined the top cited and downloaded papers. We also asked members of the editorial board of the Journal of Medical Imaging to select their favorite papers. Results: There was very little overlap between the three methods of highlighting papers. The downloads were mostly recent papers, whereas the favorite papers were mostly older papers. Conclusions: The three different methods combined provide an overview of the highlights of the papers published in the SPIE Medical Imaging conference proceedings over the last 50 years.
Multi-Class Object Detection Using Adaptive Non-Maximum Suppression in Dense Images

Deep learning-based object detection technology is actively studied, and non-maximum suppression (NMS) is an algorithm used to remove redundant object detection. NMS creates a bounding box for objects detected using a fixed ratio to determine the probability of an object being present. However, this constraint does not solve the difficulty in detecting objects that significantly overlap or are too small. Soft-NMS is an improvement. Nevertheless, free parameter values are manually chosen to provide non-optimal results. Our proposed Adaptive-NMS algorithm (1) calculates the optimal free parameters in real-time and (2) provides for multi-class object detection in highly dense images, improving results over Soft-NMS up to 12.2%.
An improved teaching-learning-based optimization with multi-learning strategy and ranking-based selection for multitask optimization problems

Abstract In recent years, evolutionary multitask optimization (EMTO) has gained enough attention in the research community. Multitask optimization (MTO) makes full use of the potential parallelism of population search-based efforts to achieve cross-domain optimization of multiple optimization problems and make knowledge migration between different optimization problems possible. Whether from the angle of convergence speed or quality, it shows better ability than single task optimization. However, we note that the current EMTO algorithm uses only a single crossover for knowledge transfer, which can’t reduce the impact of negative information in the process of knowledge transfer. There are some limitations in solving available tasks. This paper presents a new multitask teaching-learning-based optimization with multi-learning strategies and ranking-based selection strategy (MTTLBO-MR). In the teaching stage, there are three learning strategies for students to choose. In the learning stage, each student chooses the learning strategy from two strategies according to their own situation. Different from the greedy selection strategy of the original TLBO, the new offspring is selected on the basis of the rank based on the factorial rank and diversity rank of each individual. The test result states clearly that MTTLBO-MR updates knowledge through suitable learning strategies at different optimization stages and has outstanding performance on dealing with multitask optimization tasks.
An Empirical Study On Correlation between Readme Content and Project Popularity

Readme in GitHub repositories serves as a preliminary source of information, and thus helps developers in understanding about the projects, for reuse or extension. Different types of contextual and structural content, which we refer to as categories of the content and features in the content respectively, are present in readme files, and could determine the extent of comprehension about project. Consequently, the structural and contextual aspects of the content could impact the project popularity. Studying the correlation between the content and project popularity could help in focusing on the aspects that could improve popularity, while designing the readme files. However, existing studies explore the categories of content and types of features in readme files, and do not explore their usefulness towards project popularity. Hence, we present an empirical study to understand correlation between readme file content and project popularity. We perform the study on 1950 readme files of public GitHub projects, spanning across ten programming languages, and observe that readme files in majority of the popular projects are well organised using lists and images, and comprise links to external sources. Also, repositories with readme files containing contribution guidelines and references were observed to be associated with higher popularity.
A Multi-Scenario Crowd Data Synthesis Based On Building Information Modeling

Deep learning methods have proven to be effective in the field of crowd analysis recently. Nonetheless, the performance of deep learning models is affected by the inadequacy of training datasets. Because of policy implications and privacy restrictions, crowd data is commonly difficult to access. In order to overcome the difficulty of insufficient dataset, the previous work used to synthesize labelled crowd data in outdoor scenes and virtual games. However, these methods perform data synthesis with limited environmental information and inflexible crowd rules, usually in unauthentic environment. In this paper, a tool for synthesizing crowd data in BIM models with multiple scenes is proposed. This tool can make full use of the comprehensive information of real-world buildings, and conduct crowd simulations by setting behavior rules. The synthesized dataset is used for data augmentation for crowd analysis problems and the experimental results clearly confirm the effectiveness of the tool.