Reviewerly/exHarmony huggingface dataset:
EFEKTIFITAS REWARD DALAM MENINGKATKAN MOTIVASI BELAJAR SISWA KELAS V SDN 06 ANDALEH BARUH BUKIK

This research method is a quantitative method using experimental types, while this research approach is a pre-experimental design type one group pretest-postest. The research sample was obtained through a saturated sample technique or total sampling where all populations were sampled, namely all class V students totaling 25 people. Data collection uses essay test questions and questionnaires with statistical data analysis techniques with t-tests. From the final test result data, it shows that the final average score of students in the pretest is 44.6 with a percentage of completeness of 20% and postest which is 86.04 with a percentage of completeness of 88%. the results of student learning motivation scores on the questionnaire test at SDN 06 Andaleh Baruh Bukik were 25 students with a total score of 2206 and an average score of 88.24. It can be concluded that students' learning motivation is in a very high category. In this study, a hypothesis test was also carried out with a posttest pretest t-test with an SPSS application of 0.000&lt;0.005, then H0 was rejected and Ha was accepted so that a decision could be made that giving rewards was effective in increasing the learning motivation of grade V students in mathematics subjects at SDN 06 Andaleh Baruh Bukik.
Experiential Learning to Promote Student Autonomy at Elementary Level

The primary objective of this research is to assess Learners' Autonomy by implementing Experiential Learning in a role-play activity among class 8 elementary students at a private-sector English Medium School. Experiential Learning, which is a learner-friendly approach, has not been extensively explored at the fundamental level. However, its importance, often referred to as "learning by doing" or "hands-on approaches," has been acknowledged in various writings and research. Over time, Experiential Learning has gained popularity among adult learners and is considered crucial in educational institutions. To conduct this study, a thorough review of the literature was conducted, leading to the development of a hypothesis. The research strategy involved the use of a survey, and the study's population comprised students from elementary private schools in Karachi. A straightforward random sampling design was adopted, resulting in a sample size of 118 students as participants. For data collection, two questionnaires were employed: the Experiential Learning Scale (ELS) by Clem and Beasley, and the Learner Autonomous Scale (LAS) by Fletcher and Averill. The data was then analyzed using SPSS, with inferential statistics, correlation, and linear regression methods. The findings revealed a strong correlation between the variables (EL) and (LA). Moreover, at a significance level of 0.05, the overall relationship between all Experiential Learning and Learner Autonomous categories was determined to be moderate. Based on the overall linear regression model, instructors and practitioners are encouraged to incorporate Experiential Learning into their teaching methodologies. Additionally, the study suggests further exploration of the concept of Autonomous Learning through this process, and proposes a comparative study to assess how this approach influences students' engagement in various curricula.
Learning Media of Animation in Elementary School: How to Improve Student's Narrative Writing Skills

Writing skill is one of the four language proficiency aspects that students need to possess. However, some previous studies have revealed that students' narrative writing ability is still low. One of the efforts that can be made to address this issue is by using animation as a learning medium. This research aims to examine the extent of the influence of using animation as a learning medium on the narrative writing skill of elementary school students. This study employs a quantitative research method with a quasi-experimental design using the non-equivalent control group design. The research was conducted at SDN Cijati 1 Majalengka. The sample of the study consists of 50 respondents from Grade V students. The research instrument used is a written test through a post-test, and the data analysis technique used is quantitative descriptive analysis. The results of this research show that the narrative writing skill of students in the class that used animation as a learning medium is better than the class that did not use animation as a learning medium. Therefore, animation as a learning medium has a significant effect on developing students' narrative writing skill.
Social and Internal Conflict in Stephenie Meyer’s Novel “Breaking Dawn”: Anthropology Study of Literature

This research is about the analysis of social class, including internal and social conflicts in the novel Breaking Dawn by Stephenie Meyer. The objectives of this research are to know the kinds of conflicts and its most dominant one in the novel. The method used in this research is qualitative method by using anthropology of literature, whereas the data resource is the novel Breaking Dawn by Stephenie Meyer which was published in 2007, also some books were used to analyze and support this research. In collecting the data, the writer used note taking as the instrument to get the data. In this research, the researchers found that there are two kinds of conflict existed, i.e. social conflict and internal conflict, and the most dominant one occurs in the first eleven chapters of novel is the internal conflict. AbstrakPenelitian ini membahas analisis kelas sosial termasuk konflik internal dan sosial dalam novel Breaking Dawn karya Stephenie Meyer. Tujuan penelitian ini adalah untuk mengetahui jenis-jenis konflik dan jenis konflik yang paling dominan terdapat dalam novel Breaking Dawn karya Stephenie Meyer. Metode yang digunakan dalam penelitian ini adalah metode kualitatif dengan pendekatan antropologi sastra. Sumber data penelitian ini adalah novel Breaking Dawn karya Stephenie Meyer yang diterbitkan pada tahun 2007 serta beberapa buku yang digunakan untuk menganalisis dan mendukung penelitian ini. Dalam mengumpulkan data, penulis menggunakan note-taking sebagai instrumen untuk mendapatkan data. Dalam penelitian ini, peneliti menemukan bahwa ada dua jenis konflik yang ada dalam novel tersebut, yaitu konflik sosial dan konflik internal, sedangkan jenis konflik yang paling dominan terjadi pada sebelas bab pertama novel ini adalah konflik internal.
Classifying internet of things (IoT) devices and non-IoT devices in data center edge network by one dimensional convolutional neural network using behavioral data

Now a days it is important to distinguish IoT and non-IoT devices from their network traffic in real-time for providing differential treatment to meet quality of service (QoS) requirements. This paper focuses on the classification of IoT and non-IoT devices based on their network traffic at edge data centers. We proposed a method using One-Dimensional Convolutional Neural Networks (1D-CNNs) which are simple, compact, and computationally less expensive for real-time processing needs. We used a dataset, which contain information from 22 IoT and 7 non-IoT devices that included both User Datagram Protocol (UDP) and Transport Control Protocol (TCP) flows. The classifier is constructed using 8 consecutive timesteps of payload exchanges carrying network payload data up to 96 bytes. Using 10-CV, the classifier achieves an accuracy of classification of about 98% on the test datasets.
Evaluating Video Telemedicine for Providing Virtual Health Care for Cats Via Mock Spay Recheck Examinations

Cat caregivers face many potential barriers when accessing veterinary care, such as cat-related challenges with carriers, travel, and the clinic environment, time away from home and/or work, distance to the veterinary clinic, and costs of veterinary care. A potential solution to overcoming some of these barriers is the use of video telemedicine: using video technology to deliver health and behavior care, education, and information remotely. This study recruited companion cat caregivers and their cats (n=30) to participate in two mock spay re-check examinations: an in-clinic appointment and a virtual video telemedicine appointment. During the mock examinations, cat behavioral and physiological responses were assessed. Order of appointment was counterbalanced, and caregivers completed a pre- and post- appointment questionnaire to assess attitudes and experience with in-clinic versus video appointments before and after participation. The study results show that cats had a higher respiratory rate (p<0.001), larger pupil dilation (p<0.001), and more negative ear positions (p=0.015) during the mock clinic appointment compared to the video appointment. Cats were also more likely to leave the handling area after the mock clinic examination compared to the video examination (p=0.001). In addition, caregiver ratings of the video appointment were very positive (62.1%) or somewhat positive (34.5%), and participants stated it was very easy to access the technology (58.6%), internet (65.5%), and video conferencing platform (75.9%) needed. Post-survey participant ratings indicated that video telemedicine was perceived to be significantly more helpful than in-clinic visits for reducing caregiver stress (p=0.029) and cat stress (p<0.0001). There was also a post-survey difference in caregiver ratings on accessibility of veterinary care between video telemedicine and clinic appointments (p<0.0001), with results indicating that video telemedicine increases caregivers’ access to cat care. Thus, from cat caregiver perspectives, video telemedicine may reduce stress and increase accessibility to cat health care compared to clinic visits. Results also suggest that video appointments reduce negative responses in cats compared to in-clinic visits, and thus may be particularly useful for cats who show higher levels of stress in a clinic environment. More research is needed to evaluate cat responses during other appointment types for further assessment and replication of the study results.
Algorithm to Automatically Generate Non-Collision Trajectory to Perform Pick-and-Place Operation with a Mobile Manipulator

In recent years, the use of mobile manipulators for performing pick-and-place operations has increased in multiple workspaces. However, mobile robots often struggle with precise positioning owing to large position estimation errors. Additionally, working with a robot arm can be inconvenient because operators must teach the robot arm each individual workspace. In this study, to address these challenges, we propose a coordinate system matching method based on marker recognition. Additionally, we present an algorithm that creates a trajectory on the basis of the environmental information obtained through sensors and the marker frame of the recognized workspace. This trajectory is then corrected to avoid collisions between the robot and the environment, thereby allowing the mobile manipulator to perform pick-and-place operations in multiple workspaces without operator instructions.
Cross-border Community-based Learning as a Strategy in Diversity and Multicultural Teacher Preparation

As students in K-12 classrooms reflect the increasing racial, ethnic, and linguistic diversity of the United States as a whole, understanding diverse worldviews and inclusion of diverse students are important skills for classroom teachers. However, the pedagogical practices for training teacher education students with the knowledge and skills to effectively teach their racially, ethnically, and linguistically diverse students range greatly. This study explores the potential of one teacher training strategy, cross-border community-based learning, and the impact of this strategy on teacher education students’ understanding of diversity and commitment to future actions in their own classrooms. The research employs a comparative case study of two sections of a diversity and multicultural education course for undergraduate education students: one section participated in community-based learning at an Indigenous school in Guatemala and one section participated in traditional-classroom learning. The mixed-methods analysis of pre/post survey data, student journals, and student presentations suggests that community-based learning which centers Indigenous Knowledges and assets holds potential to motivate teacher education students to include diverse students in their future classrooms and challenge colonial systems of education in their future teaching. This research contributes five main recommendations to inform teacher education and community-based learning curriculum, including important differences between learning for teacher education Students of Color and White students on one particular survey scale.&#x0D;
Design and Application of Adaptive Sparse Deep Echo State Network

The prediction of appliances energy consumption in building belongs to time series forecasting problem, which can be solved by echo state network (ESN). However, due to the randomly initialized inputs and reservoir, some redundant or irrelevant components are inevitably generated in original ESN. To solve this problem, the adaptive sparse deep echo state network (ASDESN) is proposed, in which the information is processed layer by layer. Firstly, the principal component analysis (PCA) layer is inserted to penalize the redundant projection transmitted between sub-reservoirs. Secondly, the coordinate descent based adaptive sparse learning method is proposed to generate the sparse output weights. Particularly, the designed adaptive threshold strategy is able to enlarge the sparsity of output weights as network depth increases. Moreover, the echo state property (ESP) of ASDESN is given to ensure its applications. The experiment results in both simulated benchmark and real appliances energy datasets illustrate that the proposed ASDESN outperforms other ESNs with higher prediction accuracy and stability.
School Library: Between Hope and Reality

Libraries, with recent innovations, should be seen not just as organizations that manage books and other publications, but also as institutions that manage information resources using information technology. The School Literacy Movement should be able to reestablish the school library's primary function as the hub of student literacy information. Not only can renewable management improve school literacy, but it can also improve the operation of the library. Educational libraries should be used to address substantive issues and incorporate them into school goals.
Shot Boundary Detection with 3D Depthwise Convolutions and Visual Attention

Shot boundary detection is the process of identifying and locating the boundaries between individual shots in a video sequence. A shot is a continuous sequence of frames that are captured by a single camera, without any cuts or edits. Recent investigations have shown the effectiveness of the use of 3D convolutional networks to solve this task due to its high capacity to extract spatiotemporal features of the video and determine in which frame a transition or shot change occurs. When this task is used as part of a scene segmentation use case with the aim of improving the experience of viewing content from streaming platforms, the speed of segmentation is very important for live and near-live use cases such as start-over. The problem with models based on 3D convolutions is the large number of parameters that they entail. Standard 3D convolutions impose much higher CPU and memory requirements than do the same 2D operations. In this paper, we rely on depthwise separable convolutions to address the problem but with a scheme that significantly reduces the number of parameters. To compensate for the slight loss of performance, we analyze and propose the use of visual self-attention as a mechanism of improvement.
Analisis Sistem Informasi Akuntansi Penjualan Kredit Motor Pada PT. Harpindo Jaya Gubug Kabupaten Grobogan “Studi Kasus Pada PT. Harpindo Jaya Gubug”

This study aims to analyze how the credit sales accounting information system at PT Harpindo Jaya Gubug. This type of research is a qualitative descriptive research. Data were obtained using interview, observation and documentation techniques. The data analysis technique used in this study was descriptive analysis with a qualitative approach.&#x0D; The results of this study state that there is a dual function in the billing section and the accounting department. The credit sales accounting information system document at PT Harpindo Jaya Gubug Grobogan Regency is in accordance with the theory. The company has utilized information technology so that credit sales processing is computerized. Accounting records at PT Harpindo Jaya Gubug need to be repaired by making warehouse cards, inventory cards, accounts receivable cards. While the procedure network that forms the credit sales accounting information system at PT Harpindo Jaya Gubug needs to be improved, namely by having the procedure for recording the cost of goods sold and the procedure for recording receivables.
Pengaruh Sistem Informasi Akuntansi Penjualan Dan Pengendalian Internal Terhadap Efektivitas Pengendalian Piutang Pada PT. Sentral Medika Indonesia Semarang

This study aims to determine the effect of sales accounting information systems and internal control on the effectiveness of controlling accounts receivable at PT.Sentral Medika Indonesia Semarang. The population in this study were all employees of PT. Sentral Medika Indonesia Semarang with a total of 60 employees, while the sample taken using purposive sampling method is a total of 53 employees who work in the accounting department, sales department, warehouse department, marketing department, manager and president director. . The data analysis tool in this study used multiple linear regression.&#x0D; The results show that the sales accounting information system has a positive and significant effect on the effectiveness of controlling accounts receivable, it can be seen from the t-count value which is greater than the t-table value of 3.016&gt; 1.679, and the significance value of 0.004 is smaller than 0.05, so the hypothesis one accepted. Internal control has a positive and significant effect on the effectiveness of receivables control, it can be seen from the t-count value which is greater than the t-table value, namely 4.242 &gt; 1.679, and the significance value of 0.000 is smaller than 0.05, so hypothesis two is accepted. This means that the higher the company's sales accounting information system and internal control applied in the company, the effectiveness of the internal control carried out by PT. Central Medika Indonesia Semarang will continue to increase.
WhatsApp Data Policy, Data Security and Users’ Vulnerability

Several regulatory agencies regulate companies that deal with users' data, but specifically in the UK, they are regulated by the European Union General Data Protection Regulation (GDPR). The techniques of handling and processing data, rights of users, sanctions for defaulters, and other regulating clauses are formulated and implemented by these agencies to minimize the exploitation of the masses. Data regulation and management are essential because companies managing users' data are expected to handle data with care, caution, and due diligence. However, WhatsApp (arguably the most powerful instant messaging application in use) has been involved repeatedly in several cases that compromised the security of its users’ data over the years. The platform has become a prime target and medium for predators (con artists, fraudsters) with intentions to access users' data (phone numbers, last seen, live location, and others) for vile purposes. These cases include leaked data that could be used for marketing purposes, phishing, impersonation, and fraud. This paper highlights recent cases of data security (data leakages) and privacy policies involving WhatsApp, examining the various issues that threaten WhatsApp users and make them vulnerable to exploiters, cybercrime, and con artists. It also considers how WhatsApp can protect its users against vulnerabilities. Also, the European Union GDPR was examined in line with WhatsApp's privacy policy to measure compliance with the regulation in light of recent data breaches. &#x0D;
An Analysis of Text Mining in Big Data

The practice of extracting hidden predictive information from a database and structuring it for later use is known as data mining. Web mining, text mining, sequence mining, graph mining, temporal data mining, spatial data mining, distributed data mining, and multimedia mining are some of the diverse domains in data mining. Financial data analysis, the retail and telecommunications sectors, science and engineering, and intrusion detection and prevention are a few fields where data mining is used. Worldwide, big data analytics is a burgeoning research field in computer science and many other fields. We covered text mining methods and their uses in this paper. Text mining is becoming a significant topic of study. Text mining is the process of automatically finding new, previously undiscovered information using a computer.
Eos and Tithonus: Metamorphoses of Corporeality

The article discusses the philosophical implications of the Greek myth of Eos and Tithonus. In relation to different versions of this myth, the opinions of various authors regarding the problem of finding and maintaining individual identity in the conditions of bodily metamorphoses, as well as the problems of aging (gradual loss of the body and memory) are considered. The question is raised about the body of the mythological hero and the means of transmitting the fabula, whether it is transmission in the oral tradition through speech-logos or transmission through the text fixed on a material carrier (which can be lost, corrupted, restored ). The question of the interrelation of the myth of Eos and Tithonus with the details of the biography of the authors who refer to it is being studied. In this respect, the following are studied: the Homeric hymn to Aphrodite, Sappho’s “Tithonus poem” (including the history of its finding and reconstruction), as well as the poem “Tithonus the Cicada” by Alexei Parshchikov, which puts the ancient story into the modern context of reasoning about the “digital body”, transhumanism and cloning.
Big data cloud-based recommendation system using NLP techniques with machine and deep learning

Recommendation systems (RS) are crucial for social networking sites. Without it, finding precise products is harder. However, existing systems lack adequate efficiency, especially with big data. This paper presents a prototype cloud-based recommendation system for processing big data. The proposed work is implemented by utilizing the matrix factorization method with three approaches. In the first approach, singular value decomposition (SVD) is used, which is an old and traditional recommendation technique. The second recommendation approach is fine-tuned using the alternating least squares (ALS) algorithm with Apache Spark. Finally, the deep neural network (DNN) algorithm is utilized with TensorFlow. This study solves the challenge of handling large-scale datasets in the collaborative filtering (CF) technique after tuning the algorithms by adjusting the parameters in the second approach, which uses machine learning, as well as in the third approach, which uses deep learning. Furthermore, the results of these two approaches outperformed conventional techniques and achieved an acceptable computational time. The dataset size is about 1.5 GB and it is collected from the Goodreads website API. Moreover, the Hadoop distributed file system (HDFS) is used as cloud storage instead of the computer’s local disk for handling larger dataset sizes in the future.
IAAS CLOUD ARCHITECTURE DISTRIBUTED CLOUD INFRA STRUCTURES AND VIRTUALIZED DATA CENTERS

IAAS CLOUD ARCHITECTURE DISTRIBUTED CLOUD INFRASTRUCTURES AND VIRTUALIZED DATA CENTERS
Deep Learning-based Image Denoising Techniques: A Survey and Comparative Study

Deep Learning-based Image Denoising Techniques: A Survey andComparative Study