Reviewerly/exHarmony huggingface dataset:
Survey On Real Time Multiple Object Detection Using MobileNet-SSD with Opencv

The field of computer vision known as real-time object detection is vast, dynamic, and difficult. Real-time object recognition and tracking are critical and difficult problems in many computer vision applications, including video surveillance, robot navigation, and vehicle navigation. Detecting an item in a video sequence is what object detection is all about. Every tracking technique necessitates an object detection mechanism, either in each frame or whenever an item appears for the first time in the video sequence. The practise of identifying one object or numerous objects using a static or dynamic camera is known as object tracking. The availability of powerful computers, high-quality, low-cost video cameras will enhance the need for automated video analysis. Image Localization is used when there is only one object to distinguish in an image, and Object Detection is used when there are multiple objects in an image. The most often used strategies for contemporary deep learning models to perform various tasks on embedded devices are mobile networks and binary neural networks. In this research, we propose a method for distinguishing an item based on the MobileNet deep learning pre- prepared model for Single Shot Multi-Box Detector (SSD). This technique is used to recognise objects in a video stream in real time and for webcam broadcasting. Following that, we use an object detection module to determine what is in the video stream. To complete the module, we combine the MobileNet and SSD frameworks to create a fast and efficient deep learning-based item detection technique.
Enhanced Parasite Egg Images with Multiregion Light Source

Worms are human intestinal parasites; worm infections are often caused by roundworms, tapeworms, whipworms, or hookworms. These pathogens are prevalent in tropical and subtropical regions, and worm infections pose a major threat to public health in developing and underdeveloped countries. Parasitic infections are typically diagnosed through optical microscope observation with the human eye. However, parasite samples are often hazardous because they contain feces or blood smears, and diagnosis requires substantial time and effort from a professional medical examiner. This study proposed a multiquadrant light source and corresponding image processing methods to enhance the optical microscope images of parasite eggs. A light source with nine independently controlled areas was installed in an optical microscope to illuminate a parasite egg sample on glass substrate. Composite images additively constructed from single-axis images had improved characteristics because of the illumination with a suitable light intensity and illumination angle. A center-subtraction method enhanced the inner contours of parasite eggs. The light source and image processing methods could be employed to construct three-dimensional profiles of parasite eggs, enabling rapid screening for parasites in clinical applications.
A Background-Aware Tracker with Multi-Features Correlation Filters

Discriminative Correlation Filter (DCF) based trackers have shown great potential in visual tracking because of their excellent accuracy and high speed. However, traditional DCF framework applies cyclic samples and ignores the importance of background samples, which can lead to serious boundary effect and unsatisfactory tracking results against complex tracking challenges such as background clutter, deformation, occlusion, etc. Besides, the blind update strategy sometimes results in model drift. In order to handle such challenges, a background-aware tracker constructed via multiple features is proposed. The correlation filter based on color histogram feature is designed to be trained with abundant background samples to improve target appearance precision while reducing serious boundary effect. Based on an odd merge function, the correlation filter is also combined with a Histogram of Oriented Gradient (HOG) correlation filter to get precise tracking results. Finally, the two correlation filters are updated adaptively by the tracking result of each frame. Experiments show that the proposed tracker can act ~50FPS in OTB2015 benchmark and achieves good tracking accuracy.
Divide (CPU Load) and Conquer: Semi-Flexible Cloud Resource Allocation

Cloud resource management is often modeled by two-dimensional bin packing with a set of items that correspond to tasks having fixed CPU and memory requirements. However, applications running in clouds are much more flexible: modern frameworks allow to (horizontally) scale a single application to dozens, even hundreds of instances; and then the load balancer can precisely divide the workload between them. We analyze a model that captures this (semi)-flexibility of cloud resource management. Each cloud application is characterized by its memory footprint and its momentary CPU load. Combining the scheduler and the load balancer, the resource manager decides how many instances of each application will be created and how the CPU load will be balanced between them. In contrast to the divisible load model, each instance of the application requires a certain amount of memory, independent of the number of instances. Thus, the resource manager effectively trades additional memory for more evenly balanced load. We study two objectives: the bin-packing-like minimization of the number of machines used; and the makespan-like minimization of the maximum load among all the machines. We prove NP-hardness of the general problems, but also propose polynomial-time exact algorithms for boundary special cases. Notably, we show that (semi)-flexibility may result in reducing the required number of machines by a tight factor of 2 - ε. For the general case, we propose heuristics that we validate by simulation on instances derived from the Azure trace.
Pengembangan Buku Saku Digital Berbasis Android Mata Pelajaran PPKn Kelas VII SMP

This study aimed to produce an Android-based digital pocketbook on the subjects of Pancasila and Citizenship Education for grade 7th Junior High School that was feasible and effective. This study followed the research and development stages of ADDIE, including analysis, design, development, implementation, and evaluation. The test subjects used in this study were students of grade 7th Bhakti Junior High School in Malang. The validity test results of material experts obtained a score of 98, media experts were 92, and linguists were 93. Based on small-group trials, the questionnaire filling data were obtained by students with a score of 96 and teachers at 97, while the large group trial obtained a score student response is 97. An Android-based digital pocketbook in the subjects of Pancasila and Citizenship Education for grade 7th Junior High School, especially on the material for the formulation and stipulation of Pancasila as the basis of the state, could be categorized as feasible effective for use as a digital learning medium.
RANCANG BANGUN SISTEM INFORMASI ABSENSI KARYAWAN BERBASIS WEBSITE

In implementing employee attendance at PT Cheetah System, they still use a manual system in attendance for each employee. So that it causes problems in the future if there is absent data that is lost or can be misused by some employees. Therefore, to ensure effective and efficient employee attendance in the company, a web-based employee attendance system is needed that can be organized and not used by some employees. With the design of this employee attendance system, the development of the model used in this information system is the development of water fall software and the use of UML (Unifed Modeling Language) diagrams, namely use case diagrams, activity diagrams, deployment diagrams, component diagrams.To make this employee attendance system design, it can make it easier for HR or companies to process employee attendance systems so that they can be organized and also effective and efficient so that they are not misused and damaged or lost data in employee attendance.
Information and Digital Competence of the Teacher in the Educational Process Online

The article considers the issue of information and digital competence of the teacher during the distance learning system as an opportunity to achieve significant results in online education. It is noted that distance learning sets not only new goals for students, but also, above all, new requirements for teachers, who must constantly improve the methods and tools of teaching and management in connection with the situation in the country. This requires a high level of information and digital competencies of all participants in the educational process. Definitions of the terms «information competence», «digital competence» are given. Modern systems of remote access to education are analyzed. Forms of organization of educational process in the conditions of educational process online are offered. It is noted that with this approach to learning, students are gradually developing information and media literacy, logical and algorithmic thinking, skills in programming and security on the Internet, as well as the concept of ethics with information (copyright, intellectual property). It is proved that today's challenges, such as the COVID-19 pandemic, military action in Ukraine, have led to a rapid transition to the use of distance and e-learning technologies, mobile learning, learning with interactive methods, training in training technology and more.
FORMATION OF AN INNOVATIVE SYSTEM OF ORGANIZATION AND MANAGEMENT OF THE SCIENTIFIC, EDUCATIONAL AND TECHNOLOGICAL COMPLEX OF RUSSIA

The original concept of the formation of an innovative system of organization and management of the scientific, educational and technological complex of Russia is presented. The set of practical recommendations for the formation of this system, presented in the article, is based on preliminary clarification of both the characteristic specifics of the labor process in science, education, design, and the chains of interrelations-interactions between the relevant types of labor activity. It is recommended to build the desired system on the basis of an institution-a mechanism of public-private and public partnership. A package of structural order formulas has been developed that reveal the nature of the functioning of the scientific, educational and technological complex of Russia and the ways of its reform.
Neural Matrix Decomposition Model Based on Scholars’ Influence

Recommending conferences for scholars in academic social networks (ASNs) not only can enhance communication between scholars, but also have a power to promote the integration and development of the Internet and other fields. This paper propose to design a neural matrix decomposition model based on scholar influence to recommend conferences in ASNs, we define the scholar influence by measuring the local influence and global influence of scholars on ASNs based on their papers, books and projects, as well as their followers, tweets. We evaluate the effectiveness of our models on the SCHOLAT data set. The promising experimental results demonstrate the effectiveness of the proposed model.
Techno-Neoliberalism’s Body: Dance(r) Labour in Computing Research and Race as Always Already Additive

This paper explores how fields within dance, computing, and engineering come to know each other, not so much through their shared research topics and goals, but by leveraging similar structures for organizing human labour and making returns on that labour through various forms of cultural, symbolic and financial neoliberal capital exchange.My theoretical discussion works through questions brought up by recent community dialogue involving robotics company Boston Dynamics, their dancing robots and white, contemporary dance choreographer Monica Thomas.I also pull from my ongoing research analysing a large corpus study of 135 research papers involving dancers.(Rajko, 2021) All papers were extracted from the Association of Computing Machinery Digital Library (ACM DL).Through this work, I begin to break down how computing and engineering research involving dance maintains white-supremacist ideology and deflects critique through the strategic use of politically progressive gestures.From here, I discuss how these practices perpetuate the exclusion and erasure of Black movement philosophies through the deracination of Black aesthetics-ensuring discussions of race are always already additive.
A Natural Human-Drone Interface For Better Spatial Presence Experiences

As many remote construction projects increase in size and complexity, being able to manage personnel schedules, delegate tasks, and check work progress can improve work efficiency and productivity.Hence, video conferencing and remote monitoring software have been attempting to pursue an immersive and intuitive experience, but with limited developments.To better achieve that, we propose a system with a natural user interface (NUI) that can offer a vivid experience, facilitating AEC personnel who is novice drone operator to interact with the Unmanned Aerial Vehicle (UAV) by voice instructions and body posture to conduct remote site surveying, monitoring, and inspections instead of physical visiting.In addition, the proposed system is capable of on-demand path planning and camera movements for various tasks and enhances the spatial experience.We integrate these techniques to develop a human-drone interface, including a VR simulator and a haptic vest system, which offer a perceivable experience of spatial presence for different purposes.Compared with other relative works, the proposed system allows users to actively control the viewing angle and movements in the remote space more intuitively.Moreover, drones can augment human vision and let users gain mobile autonomy.
The Effectiveness of Write-Pair-Square and Group Investigation to Teach Writing Descriptive Text for Students With High and Low Participation

Recently, teaching and learning English as foreign language has raised its position as a trending field in language transformation in Indonesia.This study aimed to measuring the effectiveness of Write-Pair-Square and Group investigation to teach writing descriptive text as two cooperative learning strategies. There were 50 students of the seventh grade students of MTs N Tegal. This study used an experimental method with pre-test and post-test of a 2x2 factorial design. Two classes were chosen as experimental group 1 and 2, while the third class was chosen for tryout. The data of studentsâ€™ participation level was gained from observation before the treatments and the data of studentsâ€™ writing achievement was gained from writing test. The data from the test was analyzed with T-Test and ANOVA Test. The results revealed that there was significant difference of the studentsâ€™ participation on the post-test result after being taught by using Write-Pair-Square and Group Investigation strategies. Then, the result of the significance value (p value) of teaching strategies and participation was 0.032 &lt; 0.05. Thus, it can be stated that there is effective interaction among strategies and participation to enhance studentsâ€™ writing achievement.
Inference Control in Aggregation Query Processing Based on Supervised Learning Models

Data warehouses are environments used for data analysis and efficient decision making within companies.They are tools that allow the execution of complex and multidimensional queries.One of the security vulnerabilities that can be used by malicious users is data inference, which is the deduction of private information by devious means.In the present work, we tried to show that the existence of functional dependencies in the data can help to perform an inference attack by using supervised learning algorithms to infer private information.These algorithms are Support Vector Machine (SVM), Random Forest (RF), Bayesian Regularized Neural Network (BRNN) and K-Nearest Neighbors (K-NN).The BRNN provided a better performance in our study.This paper implements an inference attack using regression learning algorithms, studies different dependency situations in the data, and uses the combination of COUNT, SUM, AVG and STDEV queries.The use of several methods in this study allows the prevention of inferences when one of these methods is used by a malicious user.We managed to achieve this attack by detecting 09.12% inferences on all methods compared to BRNN whose realized inference rate is 03.94%.
A Practical Study on English-Speaking Learning Strategies of Junior College English Majors

Oral English is an important aspect of language output in the process of second language acquisition (SLA).For many English learners, time-consuming and ineffective oral English learning is a major issue.Aside from the language environment, one of the primary causes of this difficulty is a lack of suitable strategic guidance.In recent years, scholars have conducted more and more research on English-speaking learning strategies, but few have conducted corresponding research on junior college English majors.Based on the data obtained from questionnaires and interviews, this study investigates the use of speaking memory strategy, speaking cognitive strategy, speaking compensation strategy, speaking metacognitive strategy, speaking affective strategy and speaking social strategy in oral English.This study shows that junior college English majors generally adopt medium-level speaking strategies, among which speaking metacognitive strategy and speaking affective strategy are used more frequently, which has some enlightenment for junior college English majors on how to learn oral English effectively.
Development of a FAIR Data Management Infrastructure

Journal Article Development of a FAIR Data Management Infrastructure Get access Sherjeel Shabih, Sherjeel Shabih Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany Corresponding author: sherjeel.shabih@hu-berlin.de Search for other works by this author on: Oxford Academic Google Scholar Markus Kühbach, Markus Kühbach Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany Search for other works by this author on: Oxford Academic Google Scholar Markus Scheidgen, Markus Scheidgen Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany Search for other works by this author on: Oxford Academic Google Scholar Lauri Himanen, Lauri Himanen Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany Search for other works by this author on: Oxford Academic Google Scholar Sandor Brockhauser, Sandor Brockhauser Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany Search for other works by this author on: Oxford Academic Google Scholar Benedikt Haas, Benedikt Haas Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany Search for other works by this author on: Oxford Academic Google Scholar Christoph Koch Christoph Koch Humboldt Universität zu Berlin, Institut für Physik & IRIS, Adlershof, Berlin, Germany Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 28, Issue S1, 1 August 2022, Pages 2930–2932, https://doi.org/10.1017/S1431927622010996 Published: 01 August 2022
Review of Chinese Policy Against Cryptocurrency Growth

The development of financial technology arrived at a new form, namely cryptocurrency. The development of cryptocurrency with an increasingly widespread network and its autonomous nature cannot be controlled by the state, which makes China implement policies to block all domestic cryptocurrency activities. The policy becomes unnatural when China occupies the top position in the developing global digital currency market. This anomaly is interesting to study further to find reasons that motivate China to take firm policy when in a safe position as a center of production and global crypto currency transactions. To explain this reason, national interest theory and rational choice are used as the main tools in analyzing this problem. The national interest theory and rational choice explain that the policies taken by China are motivated by economic and security interests, as well as rational calculations of the advantages and disadvantages of those policies
School Managers’ Verbal Communication Skills and Conflict Resolution Strategies: Basis for Developing an Action Plan to Enhance Managers’ Skills

The study aimed to determine and analyze the manager’s verbal communication skills and conflict resolution strategies of manager’s basis for developing an action plan to enhance the manager’s skills. It shows that one of the main gates of a management success is to convey people and to make the necessary decision to have an excellent conflict strategy resolution. There were a total of 40 respondents, 20 from elementary, and 20 from secondary used in the study. The study utilized a quantitative research design to describe the study in detail. To determine the level of school manager’s verbal communication skills as perceived by elementary and secondary school teachers, frequency, percentage, and rank distribution were used. Likewise, to determine the extent of conflict resolution strategies used by school managers, mean and standard deviation were used. To determine the significant difference in manager’s communication skills and the significant difference in the manager’s conflict resolution strategies as perceived by the two groups of respondents, z-test was used. It found out that there is no significant difference between the two groups of respondents on the extent of conflict resolution strategies utilization in terms of problem-solving, compromising, and forcing. Based on the findings, the following conclusions were drawn. The level of manager’s verbal communication skills rated by the two sets of respondents elementary and secondary rated the items differently. While on the extent of conflict resolution strategies of managers used by secondary respondents rated the items and verbally interpreted as often. The results will be a big help in developing an action plan to enhance the skills of the manager. Based on the analysis and interpretation of data gathered on the two groups of respondents from the Division of Rizal, there is no significant difference on the level of manager’s verbal communication skills, and on the extent of conflict resolution strategies of managers, therefore, the hypothesis is retained.
OPTIMAL PROTECTION COORDINATION OF RELAYS IN PRESENCE OF DISTRIBUTED GENERATION USING WHALE ALGORITHM

“This paperis proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of the humpback whales. The algorithm is inspired by the bubble-net hunting strategy”which is good comparing to others. WOA is tested with 29 mathematical optimization problems and structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state the of art meta heuristic algorithms as well as conventional methods
On Hesitant Fuzzy Primary Ideal In Γ- ring

In this paper, we introduce the notions of hesitant fuzzy primary ideal and completely primary ideal, hesitant fuzzy semiprimary ideals of a -ring, and discuss the relation between hesitant primary ideal, completely primary and semiprimary