Reviewerly/exHarmony huggingface dataset:
Multi-Sensor Management for Multi-Target Tracking Using Mutual Information

When multi-sensor systems are used for tracking multiple targets, adaptive sensor management is critical to ensure high precision and efficiency of data processing. This paper presents a novel sensor management method for automatically selecting informative sensors from the multi-sensor system so as to improve tracking performance. Our proposed solution, uses a Partially Observed Markov Decision Process (POMDP) formulation with the labeled multi-Bernoulli filter for tracking. The sensor management problem is posed as a as a constrained POMDP with an information-driven objective function. For numerical tractability, the heuristic greedy algorithm is used to search for the suboptimal solution to the POMDP. Simulation results validate that the proposed method provides satisfactory tracking accuracy while reduces the number of selected sensors.
DZHEGONAS MOUNTAIN JEWS HISTORY AND CULTURE IN THE MODERN DIGITAL ARCHIVES / DATEBASES (SOURCE STUDY ASPECT)

During two decades, the Databases of digitized historical documents had come into sight, specifi-cally WWI and WWII periods (www.gwar.mil.ru; www.obd-memorial.ru; www.podvignaroda.ru; www.pamyat-naroda.ru). It’s bringing a new momentum in the historical and ethnological studies by updating the focus on individual biographies, family stories and their network, genealogies and onomastics. The author is showcasing the potential of Databases for heuristic search on the local Mountain Jews group in Dzhegonas village, Kuban region. It is noted that there is an interaction process between the researcher and the platform, in which the platform, after providing options for the required data, can change the vector and focus of scientific search, thereby changing the object and subject of research, among other things. It is concluded that the advent of such Internet platforms of digitized documents and Databases affects the complex of sources in history and eth-nology on the one hand, and influences research processes on the other.
Quantifying Depth Uncertainties below Complex Overburden of Low Velocity Channels

Summary Complex overburdens of low velocity channels can obscure depth imaging due to their heterogeneous nature and lateral velocity variation. Such overburden may cause undesired effects in the form of travel-time pull-down (sag) and possible energy absorption. In depth imaging, the velocity model pertaining to such overburden is of vital importance to bring the objective level(s) to the appropriate image and the depth of reflectors. The aim of this work is to quantify the depth uncertainty using stochastic time to depth conversion method that would span the range of uncertainties of the depth maps underneath such complex overburden which shall enable full range of depth realizations to be generated, gross bulk volume (GBV) ranking that better quantifies the range of uncertainties and subsequently impacts hydrocarbon volumetric estimations.
Interaction Design of Academic Analysis Module Mobile App to Enhance Student Academic Performance Monitoring

The Faculty of Computer Science (FILKOM), Universitas Brawijaya, used technology to control students’ academics by academic supervisors by launching a mobile application called Bimo (Bimbingan Mahasiswa Online). Bimo is still relatively new and does not yet have a module to assist in analyzing students’ academic progress. This module is needed in the Bimo application because it is supported by the current condition where students are not paying enough attention to evaluate their academic progress while studying in the Faculty of Computer Science. It is expected to provide a solution that can shorten the academic consultation with academic supervisors. This has been validated with several students from the Faculty of Computer Science. Therefore, the design of a student academic analysis module becomes a solution to address this issue. The design of this user experience uses the design thinking method, allowing for an iterative process. In the testing phase with usability testing, the results showed an effectiveness rate of 93.75%, a time-based efficiency rate of 0.126 goals/second, and a satisfaction score of 88.25 based on the System Usability Scale (SUS) questionnaire, which falls under the "excellent" category. The grading scale is categorized as B and is considered acceptable. Finally, qualitative testing was conducted using four questions based on the feedback capture matrix method, which yielded several answers that served as recommendations for improvement.
AI-Based Analytics for Hawkers Identification in Video Surveillance for Smart Community

Street hawking is a widespread phenomenon in urban areas globally, presenting challenges for local authorities such as traffic congestion, waste management, and negative impacts on the city's image. This research addresses key issues faced by authorities in managing hawkers, including the resistance to formalization, maintaining urban aesthetics, waste disposal, and understanding user preferences. The study investigates the performance of the You Only Look Once (YOLO) algorithm, utilizing Convolutional Neural Networks (CNN) for real-time object detection. To achieve thisobjective, the YOLOv5 algorithm is trained with a custom image dataset collected from the same camera along the street in the city area to detect five classes of objects, namely umbrella, table, stool, car, and people. Real images that were captured via camera and video surveillance were compiled as datasets which are then used to train and test the algorithm. The study aims to provide insights into the data collection process of hawkers along the street around the areas and the development of real-time hawker detection for the smart city application.
Critical Factors Influencing Cloud Security Posture of Enterprises: An Empirical Analysis

This study examines the aspects that can impact an organization's cloud security posture and the consequences for their cloud adoption strategies. Based on a thorough examination of existing literature, a conceptual framework is developed that includes several aspects such as organisational, technical, regulatory, operational, and human elements. The cloud security readiness is influenced by these five types of characteristics. A research instrument is utilised to evaluate the hypotheses pertaining to those aspects. The pilot survey showcases the research tool within the framework of a representative sample of organisations. In addition to conducting instrument testing, the initial responses also validate the importance of several elements that impact cloud security. The prominence of technical capabilities as a key factor underscores their vital contribution to bolstering cybersecurity readiness. Regulatory factors have a significant role in emphasising the necessity of compliance in cloud security. Organisational elements, such as managerial support, training, budget allocation, policy adherence, and governance, have a moderate impact. The presence of human elements also appears to contribute to and emphasise the necessity of promoting security awareness and alertness. This study enhances the existing body of knowledge on cloud security by offering insights into the various complex issues involved. The results can provide guidance to professionals seeking to enhance the cloud security of enterprises and scholars studying the changing cloud environment.
Reimagining medical workspaces through on-site observations and bodystorming

Clinicians in acute care hospitals experience highly stressful situations daily. They work long, variable hours, complete complex technical tasks, and must also be emotionally engaged with patients and families to meet the caring demands of this profession, which can lead to burnout. In response to these challenges, a multi-disciplinary team from Virginia Tech collaborated with Steelcase to study the impact of medical workspaces on the clinician experience and how those workspaces could be improved to reduce some of the sources of burnout. The team sought to identify conditions that could either aid or hinder clinician workflow and affect burnout rate, then based on interviews and in-situ ethnographic studies, generated design concepts for nurse stations, both centralized and mobile. Using digital and physical full-scale prototypes, we enacted clinical care scenarios to seek feedback and reflect on the design.
Perilaku Pencarian Informasi Layanan Koleksi Perpustakaan FMIPA Universitas Padjadjaran di Era Digital

The college library is one of the collection services provided by the college to obtain information. In conducting information search, there are several information search behaviors. This study examines student information seeking behavior in the collection service of the Padjadjaran University FMIPA Library in the digital era. Information seeking behavior has a very close relationship with information seeking, because then information can be obtained. The purpose of this study was to determine the information seeking behavior of the Unpad FMIPA library collection service through six stages and to determine the relationship between information seeking and information seeking behavior. The research method is qualitative with observation and interviews. This research method was conducted on three Unpad FMIPA students and one Unpad FMIPA librarian. The model used in this study consists of six stages, namely start- ing, chaining, browsing, differentiating, monitoring, and extracting. The result of the research is that students who need information have carried out the six stages well, namely students understand the information needed before starting a search, and are able to identify reference sources in searching for information, students use search information tools and their support- ers. the device with the help of lib.unpad.ac.id, can determine the forms and sources of relevant information that can be used, as well as identify search keywords, and make observations on information relating to their needs. And the last stage students choose information according to their needs and which are considered important. After going through the stages of searching for student information effectively, quickly, and precisely in finding the sources of information needed, especially gathering information at FMIPA Unpad.
A aplicação da metodologia de diagnóstico de situações (MDS) para uma situação-problema em uma rede de bibliotecas especializadas na área da saúde

This study is the result of a research carried out in a Network of Specialized Libraries in the Health Area in the Federal District, constituted by a complex information system in the health area. This network is responsible for managing the information necessary to carry out teaching, research and extension activities, in addition to providing collection, research and information services in Public Health, Medical Sciences and similar areas. The research found that one of the greatest weaknesses for the development of the network is that librarians have been working in isolation, which contributes to the weakening of the Network. With this, the Situation Diagnosis Methodology (SDM) was used, aiming at facing this problem. This tool helped to identify the "critical nodes" of the problem and to formulate an action plan that identified the actions that can contribute to the strengthening and cooperation among the librarians that are part of the network.
Analisis Kinerja Pustakawan dalam Memberikan Jasa Layanan Informasi di Perpustakaan UIN Mahmud Yunus Batusangkar

Librarians have a role as an element of driving and organizing library services. Librarian's performance is a determining factor for the continuity of library life. Whether the library is good or not is closely related to how the services are provided to users. Therefore, the authors are going to analyze the extent to the performance of librarians. Providing services to users is described from the aspect of knowledge and abilities of librarians. The results showed that the librarian's performance was good and the user gave a positive impression in the attitude of the librarian, to provide service in a polite and friendly manner, showing the concern of a responsive and attitude in directing to the collection. It shows that the librarian worked professionally and responsibly. As a recommendation, the library is able to increase the number of library officers in order to maximize performance, especially in user services.
Design of Job Placement Center Dashboard for Monitoring Alumni Performance in Job Fair Application

The use of data is crucial in many factors, especially when it comes to decision-making. Too much data, however, can be overwhelming. Mistakes in data analysis can occur if data is not presentable or incomprehensible for users to understand. This study aims to create a fitting data monitoring tool that is easily understood. In this paper, we will design a dashboard to monitor alum performance in a job fair application. This dashboard uses the Human-Centered Design method, which focuses on user requirements. The design solution is evaluated using usability testing with three aspects of the dashboard’s usability. The test results show that the success rate of the dashboard is 75%, the time-based efficiency is 0,0364 goals/second, and user satisfaction, measured using the DATUS questionnaire, gets a mean score of 86 out of 100. Furthermore, in-depth interviews with end-users are conducted to investigate user experience when operating the dashboard.
Neutral Class Handling for Customer Sentiment Analysis In Binary Classification: A Comparative Study of Supervised Machine Learning Classification Algorithm

Customer sentiment analyses improve customer experience and ultimately drive business success. Polarity classification is considered the standard research task in sentiment analysis. This study’s primary focus is conducting a comparative study with 10-fold cross-validation to discover the most effective sentiment classifier to handle neutral sentiment in order to enhance sentiment polarity categorization. This study employs binary classification utilizing supervised machine learning methods such as Naïve Bayes and Support Vector Machine to classify neutral sentiment or a 3-star rating in online customer reviews. Results show that SVM outperforms Naïve Bayes in classifying sentiment with an AUC value of 0,923 for scenarios the neutral class considered removed from the data set. The comparison result based on three scenarios to handle the neutral class indicates that the neutral class may be considered a positive class with an AUC value of 0.904 based on the supervised machine-learning approach. A review with a 3-star rating is seen as positive feedback and slightly better than average or meets expectations. The neutral sentiment was considered an acceptable score of satisfied with some positive aspects. Further investigation is required to multiclass approaches to classify the customer sentiments as positive, negative, or neutral to achieve better accuracy and prevent the risk of misclassification.
Enhancing Pedestrian Re-identification and Tracking System Using 3D Correlation Method

With the proliferation of surveillance cameras and the maturation of artificial intelligence (AI), the information security industry has witnessed rapid advancement. When multiple cameras capture non-overlapping areas, the re-identification (ReID) of pedestrians presents substantial technical hurdles. Thus, we introduced a pedestrian ReID and real-time crowd-tracking system for scenarios involving multiple camera viewpoints and the streaming of images from various angles. The system effectively detected and predicted the trajectories of monitored individuals as they traversed through different cameras. We employed YOLOX to detect the positions of pedestrians within the frames of individual cameras. Subsequently, the detection outcomes were processed with the BYTE-track algorithm for trajectory tracking. The ensuing tracking trajectories were transformed using calibrated matrices to project coordinates from screen space into spatial space. This integration amalgamated coordinate trajectories from various camera perspectives onto a global plane map. The trajectories of pedestrians detected by each camera were processed to use their temporal, spatial, and positional attributes. These 3-D features were employed for approximating distance computations. Through this process, the trajectories of the same individual captured by different cameras were integrated and displayed on a plane map. Consequently, a comprehensive tracking of the global movement paths, as captured by multiple cameras, was obtained. The results indicated that this method effectively enabled multi-camera tracking of numerous objects, outlining distinct trajectories for different tracked pedestrians on the plane map. By establishing global trajectories, notable enhancements in the performance of pedestrian ReID search tasks were observed.
“Druggies Drug Dealers Rapists and Killers”

We analyze the forty-fifth president’s public discourse to characterize the narrative he consistently articulated about unauthorized immigrants. We initially undertook this analysis on behalf of the legal defense of Deferred Action for Childhood Arrivals (DACA) grantees, to provide scientifically rigorous and replicable evidence that the president’s executive action to rescind the DACA program was a violation of the Equal Protection Clause of the US Constitution. This is a critical discourse analysis of a large sample of his public discourse about immigration, from his first day as a presidential candidate to the day that he attempted to rescind DACA. We inductively analyzed thirteen speeches and 6,963 tweets that revealed an anti-immigrant narrative. We attempt to definitively demonstrate that he articulated racist statements about immigrants and Latinos, hence expressing constitutionally impermissible racial animus. Beyond our formal statement, we offer an explanation based on cognitive science and US history as to why his discourse resonates so well with a sizeable portion of the US electorate.
DIDACTIC EVALUATION OF THE DESCRIPTION AND ELEMENTS OF THE TEXT IN SCHOOL TEXTBOOKS

The article considers the issue of their qualitative and quantitative analysis in order to assess the amount of information contained in school textbooks and its complexity. To solve it, the method of paired comparison of the complexity of concepts was used and an analysis was carried out using special computer programs. Programs for counting the number of names of scientific terms in texts contained in school textbooks allow you to compare the didactic complexity of textbooks. All this makes it possible to assess the level of complexity and information saturation of various topics of the school. A textbook on the subject "Mathematics" was offered for study.
The domino effect of artificial intelligence on students' scientific writing quality

The Indonesian government is pushing for increased publications with the argument that the benchmark for the productivity of an educational institution is seen from scientific publication data that researchers and research organizing institutions must disseminate. The educational strata level is needed to disseminate the scientific work of students through various media that interested parties can access. Educational tools related to research and publications can be used free of charge or paid to make it easier to produce work. To determine the domino effect of using Artificial Intelligence of Writing Academic (AIWA) on final semester students' scientific work quality, this study used a survey method with the research sample being Masters students who were carrying out and completing writing scientific papers as a fulfillment of graduation requirements with a total of 30 respondents. The sample respondents' criteria were that they could share their experiences in writing their scientific papers. The findings of this assessment proved that the domino effect for completing assignments and making scientific work students utilized and advised colleagues to use it with the assumption of efficiency and effectiveness so that tasks given by lecturers were assisted in their work by AI.
Advanced Surface Monitoring and Control System Based on Automatic Navigation

With the increasing speed of the development of the world aviation industry, the scale of international airports has expanded rapidly and the operational traffic increased, resulting in a complexity in the operation of various aircraft and service vehicles in the airport field. There are often sudden incidents caused by human negligence, resulting in scene conflicts, runway incursions, and even aircraft collisions, this brings great pressure to traffic control work. This paper takes solving airport scene traffic as the background, Advanced Surface Monitoring and Control System Based on Automatic Navigation (ASMC-AN) is proposed as a means to solve the problem. The aircraft and vehicles are equipped with monitoring and networking linkage equipment to realize automatic planning of the optimal route, avoid the occurrence of the conflict of scene activities, and ensure the improvement of the safe operation of the airport.
"The Influence of Education using the Teams Games Tournament (TGT) Method to Enhance Knowledge of Pre-Disaster Preparedness for Mount Kelud Eruption in Students of Penataran 03 Elementary School."

Abstract: Preparedness is an activity to anticipate pre-disaster mitigation so that each individual is always ready and prepared to face natural disasters. This study aims to determine the knowledge of school-aged children about pre-disaster preparedness for the eruption of Mount Kelud. This study used a pre-experimental method with a sample size of 31 respondents taken through purposive sampling technique. Data collection was done using a questionnaire. The results of the study showed a significant increase in knowledge. The pre-test results showed that there were no respondents in the good knowledge category, but after being given education using the Time Games Tournament method, there were 23 respondents (74%) in that category. Additionally, the category of sufficient knowledge increased from 0% to 26%, and the category of poor knowledge decreased from 100% to 0%. The Time Games Tournament method is an effective learning technique for delivering pre-disaster preparedness knowledge in a fun way. This method can also increase students' spirit, enable them to actively participate, foster a sense of togetherness and mutual respect, and improve creativity. Therefore, educators and health workers are expected to apply an educational program using the Time Games Tournament learning method in conducting health education. Keywords: preparedness, education, Team Games Tournament method, school age child