Reviewerly/exHarmony huggingface dataset:
Online Multi-Agent Path Finding: New Results

Online MAPF extends the classical Multi-Agent Path Finding problem (MAPF) by considering a more realistic problem in which new agents may appear over time. As online solvers are not aware of which agents will join in the future, the notion of snapshot-optimal was defined, where only current knowledge is considered. In this paper, we perform an extensive comparison between oracle-optimal solutions (where the solver is preinformed of future agents), snapshot-optimal solutions, and suboptimal solutions obtained by prioritised planning.
More Inclusive Collection Development: Considering the Information Needs of Researchers from Outside the Subject Area of Communication

When conducting collection development, it can be assumed that librarians consider the research needs of scholars within their respective disciplines. How systematically librarians consider the needs of scholars outside the discipline, however, has not been established. This study investigates whether resources scholars from outside a discipline use differ from the resources that scholars within a specific discipline use and offers a model for evaluating engagement with core journals outside of the discipline. Focusing on the subject area of communication, the data provided in this study demonstrate the importance of assessing the information needs of researchers from outside the discipline to build a more useful and inclusive journal collection and provide communication librarians with data to guide their collection decisions. Up to twenty years of journal citation data from the Web of Science database were collected and analyzed for thirty-nine communication journals. The author identifies the most and least cited communication journals by researchers outside the discipline to support collection development decisions that meet the needs of all researchers.
TATA KELOLA PROGRAM GERAKAN LITERASI SEKOLAH DI MADRASAH IBTIDAIYAH NEGERI 8 SRAGEN

This study aims to describe the governance of the school literacy movement program at Madrasah Ibtidaiyah. The approach of this study is descriptive qualitative. The data used in this study is the management process of the school literacy movement. The source of data in this study is the document and the process of implementing the school literacy program. The data in this study were collected using the methods of documentation, interviews, and observations. Analysis of the research data using an interactive model. The results of this study indicate that the governance of the literacy movement program in Madrasahs is as follows (1) First, the planning of the school literacy program has been carried out by setting the objectives of the school literacy movement program. However, the planning has not been based on needs analysis (2) the organization of the school literacy program has been carried out by organizing human resources and literacy reading materials. However, the organization carried out has not included every task and responsibility of each manager (3) the implementation of the school literacy movement program has been carried out in accordance with the plan. However, evaluation has not been carried out for each activity implementation and (4) the control carried out is still limited to ensuring that the Saturday reading program is carried out or not. Control to improve the quality of the program has not been carried out. The management of the school literacy movement program needs to be managed properly, starting from the strategic planning process, organizing by providing task descriptions, implementing the program in accordance with strategic planning, and continuous evaluation.
Efficient Decentralized Sharing Economy Model based on Blockchain Technology: A Case Study of Najm for Insurance Services Company

Blockchain is an emerging technology that is used to address ownership, centrality, and security issues in different fields.The blockchain technology has converted centralized applications into decentralized and distributed ones.In existing sharing economy applications, there are issues related to low efficiency and high complexity of services.However, blockchain technology can be adopted to overcome these issues by effectively opening up secure information channels of the sharing economy industry and other related parties, encouraging industry integration and improving the ability of sharing economy organizations to readily gain required information.This paper discusses blockchain technology to enhance the development of insurance services by proposing a five-layer decentralized model using Ethereum platform.The Najm for Insurance Services Company in Saudi Arabia was employed in a case study for applying the proposed model to effectively solve the issue of online underwriting, and to securely and efficiently enhance the verification and validation of transactions.The paper concludes with a review of the lessons learned and provides suggestions for blockchain application development process.
Rekonstruksi Model 3D dari Set Citra Menggunakan Metode SFM-MVS dan Algoritma Poisson

The digital creative industry is growing massively and very fast. The use of 3D technology in various industrial fields is also in demand, for example in the manufacturing, film, and animation industries. In a certain scene, generally 3D generalists will create a 3D model that resembles a real model in the real world which is usually used as a property in the 3D scene such as accessories, furniture, wardrobes, and so on. The process of modeling 3D models manually by a 3D generalist is a long process and requires a long time in the process, where the process generally includes 3d layouting, 3d modeling, and 3d texturing. Through this 3D model reconstruction process, 3D models can be obtained quickly, cheaply, and efficiently. This process can be carried out through several stages using a set of images from a model to be reconstructed. Several approaches can be used in this 3D model reconstruction process. In this paper, we will use the Structure From Motion (SFM) and Multi-View Stereo (MVS) methods to obtain information on the sparse and dense point clouds in the image, followed by The Surface Reconstruction process using the Poisson Algorithm to obtain a triangle mesh from the actual shape of the object. The refinement process on the triangle mesh results is carried out in order to get maximum results. Through a combination of these methods, we managed to get a detailed and accurate 3D model with the real object being observed.
DRONE HUNTER AND FIRE USE FIRE EXTINGUISHER BALL-BASED IMAGE PROCESSING AND MACHINE LEARNING METHODS

Burning activities are still common in Indonesia, but the handling by the government has not been able to maximize performance in extinguishing fires that are difficult to achieve with standard equipment. The drone that the author developed is named Zerologic which is designed to use a remote monitoring system with machine learning algorithms and image processing methods in finding hotspots using a webcam camera. This camera sends object data which is then processed on the Raspberry Pi 4 using the OpenCV Python software. Besides being designed to search for hotspots, this drone can also minimize the spread of smoke by using a fire extinguisher ball that functions as a fire extinguisher that will be carried directly by the drone. ZEROlogic drones are useful for making it easier for forest firefighters to handle forest fires by finding and extinguishing hotspots that are difficult to reach by humans. In addition to being able to search for and search for fire, this drone ZEROlogic goes directly to the hotspots.&#x0D; &#x0D; Keywords: Drone; Fire Extingusher Ball; Image Processing; Machine Learning
Opening the Black Box: Finding Osgood’s Semantic Factors in Word2vec Space

State-of-the-art models of artificial intelligence are developed in the black-box paradigm, in which sensitive information is limited to input-output interfaces, while internal representations are not interpretable. The resulting algorithms lack explainability and transparency, requested for responsible application. This paper addresses the problem by a method for finding Osgood’s dimensions of affective meaning in multidimensional space of a pre-trained word2vec model of natural language. Three affective dimensions are found based on eight semantic prototypes, composed of individual words. Evaluation axis is found in 300-dimensional word2vec space as a difference between positive and negative prototypes. Potency and activity axes are defined from six process-semantic prototypes (perception, analysis, planning, action, progress, and evaluation), representing phases of a generalized circular process in that plane. All dimensions are found in simple analytical form, not requiring additional training. Dimensions are nearly orthogonal, as expected for independent semantic factors. Osgood’s semantics of any word2vec object is then retrieved by a simple projection of the corresponding vector to the identified dimensions. The developed approach opens the possibility for interpreting the inside of black box-type algorithms in natural affective-semantic categories, and provides insights into foundational principles of distributive vector models of natural language. In the reverse direction, the established mapping opens machine-learning models as rich sources of data for cognitive-behavioral research and technology.
Comparison of theoretical and isotropic models of incoming solar radiation for the tilted, fixed, flat-plate solar collector southoriented

Knowing the intensity of incoming solar radiation is the starting point for any further analysis of the thermal performance of (all) solar collectors. A large number of existing theoretical models (both isotropic and anisotropic) can be justified by the complexity of determining its components, because the total solar radiation for an arbitrarily oriented surface of the solar collector consists of: direct, diffuse and reflected solar radiation. In the first part of the paper, three theoretical and isotropic models of incoming solar radiation are presented in detail, for the tilted, fixed, flat-plate solar collector oriented to the south, presented in the works of the following authors: LUKIĆ-BABIĆ, WIDÉN-MUNKHAMMAR and DESPOTOVIĆ. In the second part of the paper, using the mentioned methods, the incoming solar radiation was calculated by comparing the obtained results, all with the aim of facilitating (by pointing out the advantages and disadvantages of their use) other researchers to select the appropriate solar model in theoretical calculations of the solar collectors.
Development of Electronic Books (E-Books) for Supervision of Public Services to Increase Knowledge of PPKn Teachers

People have the right to get good public services and can also participate in the supervision of it. Community rights in public services can be included in learning materials in schools. Knowledge about public service supervision for high school Civic Education teachers has not been maximized enough. The teachers should be at the forefront of socializing these rights by integrating them into Civics subject matter in Senior High School or Vocational High School (SMK). This study aimed to develop an e-book on public service supervision to increase high school and vocational high school teachers' knowledge. The research method was R&amp;D (research and development) using Borgg and Gall theory. The study analyzed the need for enrichment book references for teachers to increase their knowledge about public service supervision. The results showed that the experts gave a good and proper assessment of this enrichment book. The effectiveness test showed that this enrichment book effectively increased the knowledge of Civic Education teachers on public services supervision. The benefit of this e-book is giving proper knowledge to Civic Education teachers in Senior High School (SMA) or Vocational High School (SMK) regarding the supervision of public services so that their knowledge can be increased.
TEKNIK SMOTE DAN GINI SCORE DALAM KLASIFIKASI KANKER PAYUDARA

Breast cancer is a malignancy in breast tissue that can originate from the epithelium of the ducts and lobules. WHO says 30% - 50% of cancer cases can be prevented. Breast cancer prevention can be done utilizing screening or early diagnosis. The purpose of the initial diagnosis is that if a lump appears, predictions can be made whether it is classified as malignant or benign. Breast cancer prediction can be done using a dataset containing cancer-related parameters. However, sometimes the dataset used also has problems such as the amount of data is not balanced and the use of irrelevant features. This study aims to improve breast cancer prediction results by balancing the number of data classes and using the rank feature. The method used is SMOTE for imbalanced data and Gini score for rank features. The classification model used is random forest and naïve Bayes. The results obtained by the random forest classification model are superior to Naïve Bayes.
Job Satisfaction Impact on Motivation: An Empirical Research of Private Health Sector Employees

Since the health sector is considered to be labor intensive, employee performance levels are intrinsically tied to how well an organization functions within its environment. This objective can only be met by offering the proper incentives, which will inevitably lead to the adoption of the desired attitude and behavior. Research on the requirements a private hospital in Hyderabad Sindh Pakistan is the subject of this article's investigation of possible dynamics influencing the behaviour of its staff. SPSS version 20.0 was used to analyze the data, and correlation and regression analysis methods were used. To assess data that were gathered from 74 hospital personnel. In accordance with the findings, relationships with coworkers and accomplishment levels are the main factors that drive employee motivation, with pay levels and work requirements backing the statement. These results show that elevating employee performance levels is necessary for the hospital administration, it is necessary to create an environment where employees feel valued and appreciated while also fostering a strong work culture.
On Metadata Privacy in Instant Messaging

Users metadata collection is a concerning issue related to Instant Messaging (IM) due to the potential of privacy violation. Even with messages' content encryption, metadata such as relationships and other communication patterns are exchanged in clear text, incurring in information leakage. In this paper, we investigate popular IM solutions to identify existing metadata, propose a broader nomenclature encompassing similar information, and assess the impact of metadata leakage on users' privacy. We also present a hierarchy of metadata based on our proposed nomenclature to allow for fair comparison among related work and easy gathering of privacy needs of users.
Smartphone Inertial Sensors Applications in Medical Care Field: A Comprehensive Review

Sensors of various types are built into the majority of current smartphones each with a distinct function that aids the device's performance. Micro-Electro-Mechanical System (MEMS) inertial sensors, such as gyroscopes (gyros) and accelerometers, are built into smartphones. These embedded inertial sensors have improved user experience and accelerated smartphone development and it can be used to detect events or collect information about human activities. Additionally, machine learning algorithms applied to smartphone sensor data could have a wide range of uses in entertainment, health care, finance and other fields. There have been massive financial gains when a smartphone is utilized to provide telemedicine and remote healthcare assistance. This paper provides a brief overview of all the recent work that have been done in the medical care field by utilizing inertial navigation sensors (gyroscopes and accelerometers) whether the inertial sensors were used together or separately. The goal of this review is to outline the most recent trends in four topics. First, we’ll go over fall detection systems released research publications. Second, we'll go over the most recent scholarly papers on human activity monitoring systems that have been published. Third, we’ll review the most recently released research publications on epilepsy detection. Last, we’ll look over the recently released papers on Parkinson’s disease. This work also includes some important applications that use external inertial sensors for comparison purposes.
A New Rapid and Detail-Preserving Image Downscaling Without Noise Amplification

Video web portals have to downscale an incredible number of videos and images to various resolutions each day. The latest image downscaling algorithms conserve edges and fine details but still suffer from noise amplification. This often makes undesirable artifacts especially with a large downscaling factor. Deep learning based methods show superior performance only for some predetermined integer factors. For a practical real-time image processing that meets the requirement of video portals, it is still challenging to scale image down as quickly as possible without emphasizing noise, preserving sharp edges and important details with an arbitrary non-integer and even a large factor. In this paper, we propose a new detail-preserving image downscaling algorithm based on inverse joint bilateral filtering using an area pixel model and moving average. The proposed method not only retains visually important details but also prevents unpleasant noise amplification and aliasing artifacts by smoothing filter coefficients with respect to the downscaling factor through two-step one-dimensional filtering. Experimental results show that the proposed algorithm is about 7.37% faster on average than the fastest existing detail-preserving image downscaler. GPU implementation of our algorithm downscales a 2K video to 128-pixel width without temporal artifacts at speed of 116 frames per second. Moreover, the PSNR and SSIM scores achieved by our method were respectively 35.9% and 16.5% higher on average than the highest values scored by the existing methods when downscaling images contaminated by 5% salt and pepper noise.
Assistência ao portador de diabetes mellitus na atenção primária: papel do enfermeiro e importância na equipe multidisciplinar

Diabetes Mellitus is a chronic disease that must be tracked and monitored by the entire primary care team, with nurses being a fundamental player in the support of this pathology. The aim was to analyze the role of nurses in assisting DM patients as a family health team. Integrative literature review with descriptive analysis and quantitative approach. The main scientific databases were consulted with keywords such as “diabetes mellitus”, “family health” and “primary care”, resulting in 16 more recent articles and 9 were selected for data analysis. The nurse is an integral part of a fundamental multidisciplinary team in the adhesion and monitoring of the DM patient, with several attributions from their reception in primary care to the continuity at home for life, with the main preventive action of complications, the encouragement of self-care.
Comparability of computer based and paper &amp; pencil test on students’ performance in educational assessment course at the Federal University Gusau, Nigeria

Introduction: Computer-Based Test (CBT) is being adopted for assessment by many institutions in Nigeria due to increase in students’ population, expansion of work demands from academic staff, and advances in Information and Communication Technology (ICT). Purpose: This study investigated the comparability of Computer Based Test (CBT) and Paper-Pencil Test (PPT) on students’ scores in Educational assessment course at Federal University Gusau, Zamfara State. Methodology: The study adopted the repeated measures design. The population for this study comprised of all undergraduate students of Federal University Gusau. The target population comprised of all the 450 registered 300 level undergraduate students from Faculty of Education, Federal University Gusau during 2021/2022 academic session. All the students were purposively selected for the study. Two instruments were used for data collection: The Multiple Choice Test in Test and Measurement (MCTTM) used for PPT and CBT had acceptable content validity coefficient of correlation of 0.69 percent and split-half reliability coefficient of 0.81, while the ICT Competence Questionnaire developed for obtaining information on students’ competence in and attitude to ICT had test re-test reliability coefficient of 0.78 and 0.81 respectively. Data collected were analyzed using descriptive and inferential statistics. The hypotheses formulated for the study were tested at 0.05 alpha level of significance. Results: The findings of the study revealed that Federal University Gusau undergraduate students have little competence in ICT. It also revealed significant difference in students’ scores in CBT and PPT in an educational assessment course. The difference is in favour of PPT with mean score of 48.72. The study also revealed no significant effect of gender on students’ scores on the two modes of testing. In addition, significant relationships also exist among students’ competence in, attitude to ICT and their performance in CBT. Recommendation: The study therefore recommended that educators should encourage the use of the adequate ICT facilities for teaching and learning. This will not only motivated the learners in learning but also prepare them for CBT.
Distributed Frobenius-Norm Finite Memory Interacting Multiple Model Estimation for Mobile Robot Localization

This paper proposes a novel state estimation algorithm, called the distributed Frobenius-norm finite memory interacting multiple model (DFFM-IMM) estimation algorithm, for mobile robot localization in wireless sensor networks (WSNs). The proposed algorithm involves finite memory estimation based on recent finite measurements; such estimation facilitates robust localization in cases of missing measurements and robot kidnapping. Furthermore, the proposed algorithm employs IMM, which facilitates accurate localization if a mobile robot abruptly changes its speed and course. Notably, average-consensus-based distributed processing renders the proposed DFFM-IMM algorithm computationally efficient, and hence, real-time processing for very short sampling times of the WSN is possible. The proposed algorithm’s performance is demonstrated by comparing it with a centralized Frobenius-norm finite memory IMM (CFFM-IMM) estimation algorithm and a localization algorithm on the basis of simulations and experiments.