Reviewerly/exHarmony huggingface dataset:
PENERAPAN PEMBELAJARAN PARTISIPATIF DALAM UPAYA MENINGKATKAN PRESTASI BELAJAR SISWA KELAS IV MATERI MENGIDENTIFIKASI GAGASAN POKOK PARAGRAF DI SDN 1 KUMPAI BATU BAWAH TAHUN PELAJARAN 2020/2021

This study aims to improve student achievement in Indonesian subjects through a participatory method with the material to identify the main idea of a paragraph at SDN 01 Kumpai Batu Atas, West Kotawaringin Regency, for the 2020/2021 academic year. The method used is classroom action research. The results of this study indicate that the implementation of participatory learning in Indonesian language classes is very effective in increasing student scores. This can be seen from the increase in research results from pre-cycle activities, cycle I and cycle II.
Stochastic-Depth Ambient Occlusion

Ambient occlusion (AO) is a popular rendering technique that enhances depth perception and realism by darkening locations that are less exposed to ambient light (e.g., corners and creases). In real-time applications, screen-space variants, relying on the depth buffer, are used due to their high performance and good visual quality. However, these only take visible surfaces into account, resulting in inconsistencies, especially during motion. Stochastic-Depth Ambient Occlusion is a novel AO algorithm that accounts for occluded geometry by relying on a stochastic depth map, capturing multiple scene layers per pixel at random. Hereby, we efficiently gather missing information in order to improve upon the accuracy and spatial stability of conventional screen-space approximations, while maintaining real-time performance. Our approach integrates well into existing rendering pipelines and improves the robustness of many different AO techniques, including multi-view solutions.
Victim in electronic commercial fraud

The article presents a criminological victimological and psychological analysis of the interaction between a fraudster and a victim in electronic commercial fraud. It is noted that the scientific plane of research of modern fraud needs constant empirical updating and theoretical understanding in the field of criminology and victimology, in particular, in the study of fraud in the field of e-commerce and trade.The basis of scientific criminological analysis was a complex combination of philosophical (in particular, dialectical), general scientific (synthesis, analysis, induction, deduction and generalization) and special scientific methods.For the purpose of this work, in particular, the features of electronic commercial fraud are substantiated, namely: 1) contact between the fraudster and the victim is established remotely; 2) the fraudster is deprived of an audiovisual portrait of the victim; 3) the target audience of the fraudster, given the use of digital technology, has expanded significantly.The author’s statements and conclusions are based on a study that statistically substantiates that the likelihood of becoming a victim of fraud in e-commerce and trade is significantly increased in greedy and overconfident citizens. &#x0D; Usually, victims are characterized by a lack or underdeveloped critical thinking and are unaware of modern methods of fraud. There is a separate category of gamblers and self-confident citizens who are characterized by risk, believe in luck, have a good education, lead an active lifestyle, learn new activities, however, are also characterized by a high degree of victimhood against e-commerce fraud.The conclusions outline the specific group victim traits of victims in electronic commercial fraud, methods and techniques used by fraudsters to build interaction with the victim during the crime.
The economic and organizational model of the international admission campaign during the COVID-19 pandemic (the case of the Moscow Institute of Physics and Technology)

Relevance. In the face of the COVID-19 pandemic, universities all over the world had to deal with a major challenge – transition from face-to-face to online learning. It was necessary to make this transition without damaging the quality of education and the transparency of examinations, especially entrance examinations taken by international students. The number of the latter fell significantly because of the pandemic and the competition for overseas students became especially fierce. One of the optimal solutions to the problem of conducting entrance exams during the pandemic was the online proctoring system. Research objective. This research aims to assess the economic efficiency of the online proctoring system by looking at the case of the Moscow Institute of Physics and Technology (MIPT). Data and methods. The article compares the most popular online proctoring systems on the market and used by universities in Russia and other country. Furthermore, it analyzes the results of the international admission campaign in 2020 and the economic effect of the in-house proctoring system in comparison with other readymade solutions. Results. The research results showed that the MIPT’s in-house proctoring system is no less efficient than the most popular readymade systems used by the majority of universities in Russia and worldwide, yet the costs of developing and operating the university’s own system are significantly lower. Conclusion. The development of an in-house online proctoring system can increase the economic efficiency of universities in terms of international admission in the forthcoming years.
ISO 경영시스템의 심사보고서 분석을 통한 지속가능경영 개선 포인트에 관한 연구

Purpose The purpose of this study is to analyze the PDCA cycle aspect through empirical analysis of the ISO certification audit report that evaluates the organization''s process and overall system management based on ISO 9001, ISO 14001, and ISO 45001, and to find improvement points for the company''s sustainability management.Method An empirical analysis was conducted focusing on the ‘observation’ presented in 424 audit reports prepared during the ISO management system certification audit and follow-up management audit conducted by Certification Body A from 2018 to 2020.Results The requirements for improvement in each ISO management system include resources(7.1), production and service provision(8.5) in ISO 9001, actions to address risks and opportunities(6.1) and emergency preparedness and response(8.2) in ISO 14001, ISO 45001 identified competence(7.2), operation planning and control(8.1), and emergency preparedness and response(8.2).Conclusion It is very meaningful to explore the points and directions for building a foundation for sustainable management and improving it based on the audit findings presented in the existing ISO management system audit report. Based on this point, it is judged that it will be possible to clearly recognize the core goals pursued by each ISO management system and to develop efficient management activities that can increase the value of the management system.
The Implementation Of Target Recognation to Determine Enemy Coordinates Using Unmanned Aerial Vehicle (UAV) GALAK-24 Aircraft Cameras With Object Detection Method

Abstract – In this era of increasingly advance, camera technology to make it easier for the military to carry out attacks and defenses to destroy embattled opponents, for that is requires camera technology that can detect objects at once with the coordinates or position of the object cleary, so as to help troops to maximize attacks and maneuvers in war. This research is expected to develop GALAK-24 aitcraft equipped with enemy detection cameras and at the same time determine the position of enemy coorninates in real time in helping intelligence on the bettlefield, thus facilitating decision-making in warfare. The detection system uses object Detection methods to detect objects that are on the surface of the land crossed by the aircraft. The workings of this detection camera is to use the phython programming language thats is connected to the PC and connected also to the camera, when the aircraft makes a flight across enemy territory then the camera will capture the entire enemy territory so that there are vehicle object recorded as well, the target will be reported to calculate the enemy’s strength and enemy position. For security prosedures the aircraft will be flown at on altitude of 500 (m) to avoid enemy personnel fire and also reduce noise so as not to be heard by the enemy reporting the condition of enemy territory, enemy forces at the same time and sent to the operator.
Enhancing Management Efficiency through Analysis of Efficiency Trends and Stability of IT-Service Companies

AbstractThis study was conducted to improve the management efficiency of IT-Service companies. We collecteddata over the last nine years and evaluated the relative efficiency of six companies and analyzed thevariability and stability of efficiency. For this, it was modeled using the DEA/Window method and theresults were derived. Through this study, it provided an opportunity to continuously improve the company'smanagement efficiency by utilizing the relative efficiency and change trends of IT-Service companies.
Fundamentals of voice biometrics: classical and machine learning approaches learning approaches

Chapter Contents: 2.1 Introduction to speaker recognition systems 2.2 Metrics for system performance evaluation 2.2.1 ROC, DET and EER 2.2.2 Detection cost function 2.3 Text-independent speaker recognition 2.3.1 Classical acoustic approaches: GMM-UBM, i-vector and PLDA 2.3.2 DNN approaches 2.3.2.1 Basic concepts of neural networks 2.3.2.2 Some applications of DNNs to speech processing 2.3.3 DNNs for speaker recognition 2.4 Text-dependent speaker recognition 2.4.1 Classification of systems and techniques 2.4.2 Databases and benchmarks 2.5 Calibration of speaker recognition scores 2.5.1 Motivation: why to calibrate? 2.5.2 What is calibration? 2.5.3 Score-to-LR computation methods 2.5.3.1 Generative calibration models: fitting distributions to scores 2.5.3.2 Discriminative calibration models: transforming scores into LR values to optimize a cost function 2.5.4 Performance measurement of score-to-LR methods References
The Effects of Online Home Learning in Connection with Extracurricular Activities for Lifelong Education for the Disabled at University on Cafeterias Cooking Assistance Skills of Job Search Persons with Developmental Disabilities

The purpose of this study is to analyze the effects of online home learning in connection with extracurricular activities for lifelong education for the disabled in university on the cooking aids skills of cafeterias for the job search persons with developmental disabilities. Three people with job search developmental disabilities who have been in a state of unemployment for three years after graduating from a special high school course participated in the experiment. In order to verify the meaningful functional relationship between independent variables and dependent variables, multiple probe design across subjects, one of the main techniques of a single object study, was used. The experimental conditions according to the research design consisted of the steps of baseline, intervention, maintenance, and generalization. The dependent variable of this study is the restaurant cooking aid skills in the cafeteria, and three subskills such as side dish arrangement, sink arrangement, and dish washing were combined by task analysis. And the independent variable of this study was composed of procedures and methods to teach the environment, tools and materials related to the performance of dependent variables to the developmental disabled people at home by using real-time image technique through zoom service, and the contents of the performance by stages of task analysis. In addition, independent variables were applied to the subjects in the course of the extracurricular activities with the theme and contents of lifelong education for the disabled at university. Students who completed the above extracurricular activities practiced the intervention scene of the researcher through the screen sharing of zoom service. As a result, the subjects with developmental disabilities effectively acquired and maintained the positive response performance of dependent variables through independent variables. The subjects also showed high positive responses to generalization tests conducted in kitchens in cafeterias located elsewhere in the same university.
Back to (for) the Future: AI and The Dualism of Persona and Res in Roman Law.

The development of AI brings many contemporary challenges which force law to face its roots. Legal relationships are materializing that take us to Roman law – to when these relationships were not about machines and their masters, but about masters and slaves. Today’s search for accountability of the AI remains within the confines of the duality of persona and res, with its modern conception limited in comparison to the Roman law of slavery and its relation to dominica potestas, a key concept for the organization of Roman society. Our objective is not to identify what historical remedies might help us “solve” AI’s problems, but to examine how new developments impose the need to become reacquainted with the classical origins of law. Law and technology were already intertwined since antiquity and its concerns resurface as the core of our answers to contemporary philosophico-legal questions.
3D Fluid Flow Reconstruction Using A Compact Light Field Camera

We present a flexible and low-cost 3D PIV solution that uses a compact light field camera as acquisition device. Real experiments demonstrate that our method can volumetric 3D fluid flows of various types.
LibGuides: ENGL 205 Stranger Than Fiction: Websites

This guide provides resources for the final project in ENGL 205 with Rita Rozzi, spring 2019.
THE ANALYSIS OF CADETS’ SPEAKING ANXIETY IN MORNING SPEECH PERFORMANCE

This study aims to determine how the level of anxiety of Cadets in speaking English during Morning Speech, what are the obstacles faced by Cadets in speaking English during Morning Speech, How the cadets solve the obstacles in speaking English during Morning Speech. This research was conducted at the Malahayati Merchant Marine Polytechnic. The participants of the study were 40 cadets from various majors, nautical, technical, and ETO. Data collection in this study was descriptive quantitative by distributing questionnaires and interviews with cadets who had carried out Morning Speech. The results showed that from 40 respondents in this study the highest is in moderate level with 35%. At the second level of anxiety is moderately high level with 25%. The low and high levels have an equal score with 17.5%. This is evidenced by a modified questionnaire assessment from McCroskey, J.C. In addition, the obstacles faced by Cadets in speaking English during the Morning Speech were anxiety, pounding, irregular breathing, nervousness when saying morning speech in front of friends, not often speaking in public, stage fright, fear of friends' opinions or lecturers, do not master the material, and the last result was how the cadets solve the obstacles faced in speaking English during the Morning Speech. There was convincing themselves confidently, trying to calm down and control themselves, by repeating before presenting a morning speech with friends at the dormitory, looking for materials and understanding the material that will be delivered during the morning speech, not showing friends that they are nervous, staring at the viewers' eyes by convincing myself psychologically that I can beat them, that I am better than them, asking for help to Miss / Mam in English to practice correct pronunciation, repeating the material until I can remember, and thinking positively.
Task scheduling characterisation in enterprise application integration

Cloud computing allows enterprises to incorporate applications and computational resources as services, and thus, enterprises can concentrate on their business processes, without concerning the development, configuration and maintenance of these applications and resources. Integration platforms are one of these services that allow enterprises to integrate applications in order to reduce the maintenance costs and operations of the integration of on-premises platforms. However, high performance on resources offered by the cloud, demands improvement in task scheduling of integration platforms. Our literature review has identified a lack of studies in the field of enterprise application integration, focusing on specificities and vulnerabilities of the task scheduling of integration processes. This is a pioneer work regarding the characterisation of the scheduling of tasks of integration processes. We propose a ranking according to their conceptual models and apply this ranking to five integration processes. Then, we have statistically analysed the influence of each component of their conceptual models on the performance of the execution of these integration processes. We characterise the task scheduling of integration processes and presented a mathematical equation for the makespan as a function of the components of this characterisation. This study can guide software engineers in the optimal task scheduling for integration processes, which can improve the performance runtime systems regarding using the computational resources and result in minimisation of costs of companies.
Exemplar 3D Faces and N95 Pleated Mask Measurement by Sex and Race

The National Institute for Occupational Safety and Health (NIOSH) requires N95 masks to provide adequate fit to at least 95% of the US population through a fit test panel, with defined face dimensions.However, researchers for many years have reported discrepancies with N95 mask fit for women and minorities.More recently with the COVID-19 pandemic, these issues were critically raised again locally when a hospital mask fitter explained to the PI issues of mask fit with women and minorities, and the challenges of finding available masks on the market that protect appropriately.A pilot study was conducted with 3D face scans from the Civilian American and European Surface Anthropometry Resource (CAESAR) dataset to uncover how exemplar faces identified through an unsupervised machine learning algorithm measured and compared to an existing N95 pleated mask (Crosstex Isolator Plus).The algorithm was based on a Variational Autoencoder (VAE) with a Point-Net inspired encoder and decoder architecture trained on Human point-cloud data obtained from the CEASAR dataset.The pilot demonstrated that the algorithm worked well to identify exemplars for sizing buckets based on sex and race and proved that ML could help replace tedious anthropometric measuring practices to develop sizing systems.From the anthropometric measures collected from the exemplars, 37.5% fitted lengthwise and widthwise into the mask, where 16.7% of the exemplars fitted in the length only, and 20.8% in the width only.Twenty-five percent did not fit at all into the mask.The results of this work highlight how critical it is for N95 mask manufacturers to look at the sizing and fit of masks differently.Multiple sizes are needed within a mask style and sex/race must be considered through relevant 3D anthropometric face/head data that represents users appropriately when developing equitable sizing systems for Personal Protective Equipment (PPE).
Analisis dan Perancangan E-Learning Adaptif di Sekolah Menengah Kejuruan

Schools have not taken advantage in using technology to carry out online-based learning 4.0, though schools have computer laboratories and Internet networks. Teachers and students need e-learning media (ELM) that can be used in learning outside the classroom. The aim of this study is to analyze and design adaptive of ELM according to the needs of teachers and students at SMK Mandiri. The purpose of this study is to study to examine and to design of ELM in accordance with what is needed by teachers and students at SMK Mandiri. The method used in this research is R &amp; D method apply ADDIE model by analyzing and designing stages only. The subjects of this development research were media expert and e-learning system expert. Data collection used is direct and indirect communication techniques, which is done virtually to determine the needs of teachers and students and questionnaire to determine the level of product feasibility. The results of this study indicate that there is a need for ELM-adaptive and designs at SMK Mandiri. The conclusion from this research is to analyze the ELM-adaptive, which can display three styles of student learning styles, namely, visual, auditory and kinesthetic, then designing and create a flow cart to describe ELM.
A Framework For Enhancing The Accuracy Of K-Means Clustering Algorithm With Linear Data Structures By Removing The Outliers

Clustering is a common technique for statistical data analysis, which can be used in various fields, like data mining, machine learning,pattern recognition, bioinformatics and image analysis.It is the method of grouping associateddata objects fromdissimilarsets, and it partitionsdatasetsas subsets.So that the data object of each subset rendering to the defined distance degree. K-means is a very well-known clustering algorithm for its nature of simplicity and the power of computational efficiency. Similarity of data objects in K-means algorithm is identified using the measure of distance which leads to implement robust algorithms in both the functionalities of classification and clustering.The measures of distance play a vital role in the overwhelming performance of K-means algorithm. The crucial functionality of distance metrics is to measure the distance between data objects in a dataset.The K-means algorithm calculates the distance between the centroids and data objects. The clusters are formed by grouping the data objects to centroids with minimum distance based on the resultant values [Nasooti et al. 2015]. Therefore, the calculation of distance plays a major role in the process of clustering. Choosing a proper technique for distance calculation is totally dependent on the type of the data.
SCMGR

Social summarization aims to produce a concise summary that describes the core content of a collection of posts on a specific topic. Existing methods tend to produce sparse or ambiguous representations of posts due to only using short and informal text content. Latest researches use social relations to improve diversity of summaries, yet they model social relations as a regularization item, which has poor flexibility and generalization. Those methods could not embody the deep semantic and social interactions among posts, making summaries still suffer from redundancy. We propose to use Social Context and Multi-Granularity Relations (SCMGR) to improve unsupervised social summarization. It learns more informative representations of posts considering both text semantics and social structure information without any annotated data. First, we design two sociologically motivated meta-paths to construct a social context graph among posts, and adopt a graph convolutional network to aggregate social context information from neighbors. Second, we design a multi-granularity relation decoder to capture the deeper semantic and social interactions from post-word and post-post aspects respectively, which can provide guidance for summary selection from semantic and social structure perspectives. Finally, a sparse reconstruction-based extractor is used to select posts that can best reconstruct original content and social network structure as summaries. Our approach improves the coverage and diversity of summaries. Experimental results on both English and Chinese corpora prove the effectiveness of our model.