Reviewerly/exHarmony huggingface dataset:
Load balancing-based Optimization Techniques in Cloud Computing: A Review

Cloud computing relies heavily on load balancing, which ensures that all of the resources, such as servers, network interfaces, hard drives (storage), and virtual machines (VMs), stored on physical servers, are working at full capacity at all times. A typical problem in the cloud is load balancing, which makes it difficult to keep the performance of the applications in line with the Quality of Service (QoS) measurement and the Service Level Agreement (SLA) contract that cloud providers are obligated to give to organizations. It's difficult for cloud providers to fairly divide the work between their servers. Multi-objective optimization (MOO) algorithms, ant colony optimization (ACO) algorithms, honey bee (HB) algorithms, and evolutionary algorithms are all examples of this type of method. The foraging activity of insects like ants and bees served as inspiration for the ACO and HB algorithms. The single-objective optimization problems can be solved by these two techniques, though. ACO and HB need revisions to work with MOPs. This paper summarizes the surveyed optimization methods and describes the modifications made to three specific algorithms.
Needs Analysis Development of Character Value-Oriented Online Learning Evaluation Instruments

The rapid development of technology, especially related to online evaluation applications, provides several alternatives in making it easier for teachers to evaluate learning to their students.Preliminary data obtained from participants related to experiences related to evaluation during online learning.The response related to online learning readiness show that the average readiness of participants in planning and implementing online learning is in the good criteria.Moreover, almost 70% of the participants doubted the results of the online learning evaluation.The doubt is related to the process of completing the evaluation, to the results of student evaluations during online learning.The teacher's challenge in instilling the character education cannot be absolute responsibility of the teacher, but must be realized as a form of shared responsibility between school, parents and the home environment as school partners.
Optimal Design of a Fuzzy Controller Based on the Imperialist Competitive Algorithm for Fourth-order Nonlinear Systems

Nowadays, control and optimization of systems are two important and noticeable topics in all fields of science and engineering. One of the control methods, widely used because of its simplicity and accuracy, is the fuzzy control, which is based on the fuzzy logic theory. In the uncertainty conditions, this theory is able to formulate many inaccurate and vague implications, variables and systems in mathematical language, and provides requirements for reasoning, inference, control and decision making. This paper studies the stabilization of a Translation Oscillations with a Rotational Actuator (TORA) nonlinear fourth-order system by using a new fuzzy control technique which utilizes the small number of membership functions and rules. Besides, to determine the proper values for the controller parameters, the Imperialist Competitive Algorithm (ICA) is employed. Unlike the other optimization algorithms, ICA is not originated from evolutionary behavior of nature, but it is inspired by a human natural phenomenon called imperialism. In the optimization procedure, the objective function is defined as the sum of integrals of the rotor angle and the cart position. Finally, the comparison between the results obtained by the proposed strategy and some other researchers’ methods is provided, which shows the superiority of this work.
Ideal Contributions of Libraries in Supporting the Implementation of Children’s Literacy Movement in Elementary Schools

The library functions as a learning center in elementary schools.The development and arrangement of libraries is an important part of the implementation of the Children's Literacy Movement in elementary schools and the management of knowledge based on reading.This study aims to describe, explain, and interpret the contribution of libraries in supporting the implementation of the Children's Literacy Movement in Saleh Children's Elementary School, Malang City.This research was conducted using a case study qualitative approach.Data collection techniques were carried out through direct observation, in-depth interviews with school principals, teachers, students, librarians, school committees, and documentation studies to support the data from observations and interviews.After checking the validity, the data were analyzed by condensing the data, presenting the data and drawing conclusions.The findings of the research on the contribution of libraries in supporting the implementation of the Children's Literary Literacy Movement at the Saleh Children's Elementary School in Malang include: (1) mandatory library visits, (2) reading awards (3) reading corners and literary magazines (4) celebration of children's literacy.
NGELMU: AUGMENTED REALITY-BASED PANJI STORY LEARNING APPLICATION IN GAME-BASED LEARNING AS AN EFFORT TO REVITALIZE CULTURE AND CHARACTER EDUCATION IN ELEMENTARY SCHOOL

The story of Panji is a form of cultural revitalization that has begun to fade and be displaced by the presence of superheroes who have been adopted from western culture. Unfortunately, the majority of these figures are contrary to the noble values of the Javanese ancestors and are more oriented towards the modernization of western culture. Therefore, this study aims to map the strengths, weaknesses, opportunities and threats of the Ngelmu application which is oriented towards growing interest in learning for elementary school-age children in getting to know Panji Stories and the moral messages it conveys. The results of the study show that Ngelmu has unique and interesting features in increasing students' interest in learning. Among them are: Mirengake, Ngagara, Nyimak, Ngromo, Mitutur. From the results of the analysis, it was concluded that Ngelmu is one of the applications designed to introduce and preserve the Panji Story so that it continues to exist even though the use of technology is classified as increasing. Through this Panji story, users will be introduced to a leader who has noble character and manners in accordance with the teachings of Javanese culture. In addition, this application aims to make the younger generation familiar with original Indonesian heroes before they admire superheroes from western countries.
E- TRACER STUDY BASED ON EXPERT SYSTEMS (A CASE STUDY AT AMIK INDONESIA)

Tracer Study is one method used by several universities, especially in Indonesia to get feedback from alumni. The feedback obtained from these alumni is needed by the university in their efforts to improve and develop the quality and education system. The aim of this study was to develop an e-tracer study that made it easier for AMIK Indonesia's campuses to monitor their graduates and develop intelligent system-based e-tracer studies. Broadly speaking, this study uses data collection methods through literature studies, interviews and observations. While research design uses experiments because it produces products that are decision support systems. The method used to support this research is the FMADM method using the SAW method calculation and the design method used is the waterfall method, which is a systematic and partial software development approach that starts at the level and progress of the system in all analyzes, designs, codes, tests, and maintenance. From the results of the study, it can be concluded that the tracker study was built with the Codeigniter and NODE framework. JS uses supporting programming languages such as HTML, CSS, Jquery, JavaScript, JSON, AJAX, Bootstrap as media in interface design. Whereas PHP as server-side and MySQL as database. while the method used for testing the application is White Box Testing and the Black Box method.
INTERACTIVE TOYS (ARTIFICIAL INTELLIGENCE)

This paper presents the potential use of interactive environments as learning and teaching tools for use in the therapy of children. It is expected that a new generation of children will increasingly use computer technology in a variety of contexts, including interactive robotic toys, digitally enhanced objects. New interactive systems and novel interfaces are also likely to impact on methods of therapy and rehabilitation. In particular, the physical shape and behaviour of socially intelligent agents, that display aspects of human-style social intelligence teach social intelligence to humans who have difficulties in understanding and displaying social behaviour. Toys are a major component in every child’s life and the need to develop toys that encourage communication is a common trend today. Toy companies in conjunction with technology giants are at the forefront of developing”intelligent” toys for the current and future generation. The purpose of the research is to understand the designs, effects, and consequences of using Artificial intelligence in the manufacturer of toys. artificially intelligence toys would be the perfect solution to monitor kids to keep them safe
Development of Digital Education in the Age of Digital Transformation: Citing China’s Practice in Smart Education as a Case Study

Digital education has been catalyzing educational transition, transforming the educational views and instructional techniques while also providing opportunities for high-quality educational development. This is a subject that all nations throughout the world are concerned about. The worldwide practice of integrating digital technologies in teaching has yielded positive results. The Global Digital Education Conference, which was held in Beijing, China, in 2023, called for global collaboration on digital education development. This paper sought to illustrate the significance of digital education for educational reform and to investigate ways for digital education development in this context, using China’s smart education practice as evidence.
Penerapan Model Make A Match pada Pembelajaran Tematik Terpadu untuk Meningkatkan Hasil Belajar Siswa

This study aims to determine the increase in learning outcomes after learning with the cooperative model make a match type. The research method uses Classroom Action Research with qualitative and quantitative approaches carried out in 2 cycles covering four stages, namely planning, implementing, observing and reflecting. The subjects of this study were teacher and 21 fourth grade students of SDN 15 Koto Tangah. The results showed that the succes in the first cycle lesson plan was 87,5% then increased in the second cycle to 94%. The success of observing theacher activity in cycle I was 68,75%, increasing in cycle ii 96,8%. While the increase in the activity of student aspects in the first cycle was 73,43% and the increase in the second cycle was 93,75%. The average learning outcomes in the knowledge aspect in the first cycle was 74,04, increasing in the second cycle to 84,29. While the average learning outcomes in the skills aspect in the first cycle was 76,96, increasing in the second cycle to 83,98.
Analysis of Factors Inhibiting the Implementation of Fire Hazard Management Policies by the Fire Department of Kupang City

The reality that occurs in Kupang City is that fire prevention often encounters many obstacles in disaster management so that the output of Regional Regulation Number 24 of 2007 concerning Fire Hazard Management in Kupang City is not implemented effectively. The research method used in this study was a descriptive research method with a qualitative approach, while the informant selection technique used by the researchers in this study was a purposive sampling technique with a total of 76 people. Sources of data in this study were obtained through primary sources and secondary sources, then the data that had been collected was analyzed using data analysis techniques from Creswell (2016: 264-268). The research results show that the dominant factors hindering the implementation of fire prevention policies by the Kupang City Fire Service are; (a) lack of human resources, (b) lack of budget allocation, (c) lack of facilities and infrastructure and (d) outreach.
Pengembangan Media Pembelajaran Penyajian Data Berbasis QR-Code Untuk Meningkatkan Hasil Belajar Siswa Kelas IV SD

This study aims at developing QR-Code-based data presentation learning media which are valid and practical to improve the learning outcomes of the fourth year elementary school students. This study used a research and development (R&amp;D) model consisting of such stages as analysis, design, development, implementation, and evaluation. The subject of this study included 2 experts, 2 teachers and 26 students at class IV-B of SDN 15 Ulu Gadut, Padang. The instrument used in this study included expert validation sheets and questionnaires distributed to the teachers and students. The results indicate that (1) the use of QR-Code-based data presentation learning media to improve the learning outcomes of the fourth year elementary school students is valid according to the material expert and very valid according to the linguistic expert and media expert with the validity average of 95,41; (2) based on the response of the teachers and students, the use of QR-Code-based data presentation learning media to improve the learning outcomes of the fourth year elementary school students is very practical with the average of 95% and 88%.
Towards Visual-Prompt Temporal Answer Grounding in Instructional Video

&lt;p&gt;The temporal answer grounding in instructional video (TAGV) is a new task naturally derived from temporal sentence grounding in general video (TSGV). Given an untrimmed instructional video and a text question, this task aims at locating the frame span from the video that can semantically answer the question. Existing methods tend to formulate the TAGV task with a visual span-based predictor by matching the video frame span queried by the text question. However, due to the weak correlations of the semantic features between the textual question and visual answer, existing methods adopting the visual span-based predictor perform poorly in the TAGV task. In this paper, we propose a visual-prompt text span localizing (VPTSL) method, which introduces the timestamped subtitles to perform the text span localization. Specifically, we design the text span-based predictor, where the input text question, video subtitles, and visual prompt features are jointly learned with the pre-trained language model for enhancing the joint semantic representations. As a result, the TAGV task is reformulated with the visual-prompt subtitle span prediction matching the visual answer. Extensive experiments on three instructional video datasets, namely MedVidQA, TutorialVQA, and VehicleVQA, show that the proposed method outperforms several state-of-the-art (SOTA) methods by a large margin in terms of mIoU score, which demonstrates the effectiveness of the proposed visual prompt and text span-based predictor. Besides, all the experimental codes and datasets are open-sourced on the website https://github.com/wengsyx/VPTSL.&lt;/p&gt;
Pengembangan Media Pembelajaran Bangun Ruang Berbasis GeoGebra untuk Meningkatkan Hasil Belajar Peserta Didik Kelas V SD

This study aims to produce GeoGebra space learning media for elementary school students. This type of research is a research development with the ADDIE model, namely Analysis (analysis), Design (design), Development (Development), Implementation (implementation), and Evaluation (evaluation). The results of this study are: 1) The author has produced GeoGebra learning media for Geometric fifth grade SD which is valid with a validity of 90% 2) The author has produced GeoGebra learning media for Geometric fifth grade SD wich is practice with 89.29% practicality from the teacher's response and 91.36% of the students' responses, 3) The author has produced GeoGebra learning media for Geometric fifth grade SD wich is effective with an increase percentage of 85,15% and completeness of 88,89%.
Improving Adversarial Robustness via Finding Flat Minimum of the Weight Loss Landscape

&lt;p&gt;Recent studies have shown that robust overfitting and robust generalization gap are a major trouble in adversarial training of deep neural networks. These interesting problems of robust overfitting and robust generalization gap motivate us to explore more solutions. Inspired by recent research on the idea of smoothness, this paper introduces the latest research work on the Adversarial Model Perturbation (AMP) method of finding the flatter minimum of the weight loss landscape into the adversarial training (AT) framework of deep neural networks to alleviate the robust overfitting and robust generalization gap troubles, called AT-AMP method. The validity of the flat minimum is explained from the perspective of statistical generalization theory. Although the idea is plain, this approach is surprisingly effective. Experiments demonstrate that by incorporating the AMP method into adversarial training framework, we can boost the robust accuracy by 1.14% ~ 5.73%, on three different benchmark datasets SVHN, CIFAR-10, CIFAR-100 and two threat models norm constraint and L2 norm constraint, across diverse types of adversarial training framework such as AT, TRADES, MART, AT with pre-training and RST and diverse white-box and black-box attack, achieving the state-of-the-art performance in adversarial training framework. In addition, we compare several classical regularization and modern deep learning data augmentation tricks for robust overfitting and robust generalization with the AMP method, and the experimental research results consistently indicate that introducing the AMP method achieves advanced adversarial robustness in the adversarial training framework.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
MFMDet: Multi-scale Face Mask Detection using Improved Cascade rcnn

Abstract COVID-19 is spreading globally, posing a great risk and challenging to the world. And wearing a mask can reduce the spread of the virus and the speed of virus transmission, which is an effective mean to combat the spread of coronavirus. To limit the spread of the virus, the requirement to wear a mask is now becoming more common in public places around the world. Nowadays mask wearing detection has become an important task for computer vision to help the global community. The mask detection task involves complex and diverse scenarios with problems of missed and false detection caused by face features being obscured, varying target scales, poor detection of small targets, and small differences in features between correctly and incorrectly worn masks. For this reason, we propose a new mask detection model, MFMDet, which uses Recursive Feature Pyramid to process the multi-scale features extracted by the backbone network, increasing the global features and the perceptual field, and enhancing the detector's ability to adjust to different scales. To ensure the accurate extraction of valid information, we introduce modulated deformable RoIpooling into the detection head to make the network better adapt to the deformation of the target and enhance the spatial and task awareness of the detection head. In addition, we use Joint Image Hybrid Augmentation to increase the number of training samples and diversity to enhance the model generalization ability. Experimental results show that our method improved by 2.5 AP over the baseline, comparing to the baseline on the PWMFD dataset and outperforms other existing target detection algorithms. We also conducted experiments on the WMD dataset to further validate the generalization ability and effectiveness of the proposed method.
Blockchain-Empowered Lifecycle Management for AI-Generated Content (AIGC) Products in Edge Networks

&lt;p&gt;The rapid development of Artificial Intelligence-Generated Content (AIGC) has brought daunting challenges regarding service latency, security, and trustworthiness. Recently, researchers presented the edge AIGC paradigm, effectively optimize the service latency by distributing AIGC services to edge devices. However, AIGC products are still unprotected and vulnerable to tampering and plagiarization. Moreover, as a kind of online non-fungible digital property, the free circulation of AIGC products is hindered by the lack of trustworthiness in open networks. In this article, for the first time, we present a blockchain-empowered framework to manage the lifecycle of edge AIGC products. Specifically, leveraging fraud proof, we first propose a protocol to protect the ownership and copyright of AIGC, called Proof-of-AIGC. Then, we design an incentive mechanism to guarantee the legitimate and timely executions of the funds-AIGC ownership exchanges among anonymous users. Furthermore, we build a multi-weight subjective logic-based reputation scheme, with which AIGC producers can determine which edge service provider is trustworthy and reliable to handle their services. Through numerical results, the superiority of the proposed approach is demonstrated. Last but not least, we discuss important open directions for further research.&lt;/p&gt;
Peningkatan Hasil Belajar Peserta Didik Pada Tematik Terpadu Dengan Menggunakan Model PBL di Kelas IV SD

This study aims to describe the increase in student learning results on thematic Integrated Learning Model using Problem Based Learning in class IV SDN 14 Gadut Tilatang Kamang. This research used a qualitative and quantitative approach. This type of research i.e. Research Action class (PTK). The subject of research is the grade IV SDN 14 Gadut Tilatang Kamang. Feed as many as 20 students. Research conducted two cycles. The design of the research include, (1) planning, (2) implementation, (3) and (4) observation of the reflection. The results showed an increase in: a) the RPP cycle I 85,93% (SB) Cycle II 93,75% (SB) b) implementation on aspect of teacher cycle I 84,71% (SB), a cycle II 96,42% (SB) c) Implementation on aspect students cycle I 85.71% (B) and Cycle II 96,42% (SB) d) student learning outcomes Cycle I 75,46 (B), cycle II 87 (A). Thus the model of Problem Based Learning can improve the learning results of integrated thematic grade IV SDN 14 Gadut Tilatang Kamang.
Body Correlation Network for Person Re-Identifications

&lt;p&gt;Visual information accounts for approximately 80 to 85 percent of the information available daily in modern cities. As such, person re-identification, an instance-level image retrieval task, has become an important research topic in computer vision, machine learning, and other fields in recent years. Traditional person re-identification methods based on convolutional neural networks only extract the global feature information of people. Thus, when external factors such as changes in occlusion and illumination disturb people, the recognition performance of these methods substantially decreases. We therefore develop body correlation network (BC-Net), which takes full advantage of images of body parts and the correlations between them. Specifically, BC-Net uses body part feature information and correlation feature information as nodes and edges, respectively, and then uses graph convolutions to learn the overall topology of people. To improve use of crucial feature information, we also design a unique method of propagation between nodes and edges. We conduct extensive comparative experiments on the Market-1501 and DukeMTMC-reID datasets, and the results demonstrate that BC-Net outperforms other state-of-the-art techniques.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Drug treatment in Zebrabox v1

How to do a standard Rihel lab behaviour tracking experiment with drug treatment.