Reviewerly/exHarmony huggingface dataset:
OWASP Framework-based Network Forensics to Analyze the SQLi Attacks on Web Servers

One of dangerous vulnerabilities that attack the web is SQLi. With this vulnerability, someone can obtain user data information, then change and delete that data. The solution to this attack problem is that the design website must improve security by paying attention to input validation and installing a firewall. This study's objective is to use network forensic tools to examine the designlink website's security against SQLi attacks, namely Whois, SSL Scan, Nmap, OWASP Zap, and SQL Map. OWASP is the framework that is employed; it is utilized for web security testing. According to the research findings, there are 14 vulnerabilities in the design website, with five medium level, seven low level, and two informational level. When using SQL commands with the SQL Map tool to get username and password information on its web server design. The OWASP framework may be used to verify the security of websites against SQLi attacks using network forensic tools, according to the study's findings. So that information about the vulnerabilities found on the website can be provided. The results of this study contribute to forensic network knowledge against SQLi attacks using the OWASP framework as well as for parties involved in website security.
High performance reservoir computing system based on VCSELs with variable polarization information injection

In this work, we have demonstrated that, by introducing gradient boost technology, the parallel information processing performance can be improved in a reservoir computing (RC) system based on vertical-cavity surface-emitting lasers (VCSELs) under variable polarization information injection (VPII). For the VPII scheme, the information is added into X-polarization component (X-PC) and Y-polarization component (Y-PC) of VCSEL simultaneously, and outputs from two PCs of VCSEL are utilized to construct the node matrix. Although such an information injection method can double the processing rate, the system performance needs to be further improved. In this work, the gradient boost technology is adopted to enhance the system performance, for which an extra VCSEL-based reservoir is added to correct the residual error of the original reservoir. Via parallel processing Santa-Fe chaotic time series prediction task (Stask) and waveform recognition task (Wtask), the effectiveness of adopting gradient boost technology to improve the performance of VCSEL-based RC is confirmed.
Microring Modulators Based Optical Matrix-matrix Multiplication Accelerators

We propose and simulate a highly parallel, scalable and compact optical neural network accelerator which is able to perform matrix-matrix multiplication based on the microring modulators. Simulation results confirm its feasibility for matrix-matrix multiplication.
Penerapan Metode Segmentasi Gabor Filter Dan Algoritma Support Vector Machine Untuk Pendeteksian Penyakit Daun Tomat

This research discusses about processing a formulation that we can give to diseased tomato leaves. Gabor Filter is a method used to detect textures using frequency and orientation parameters. The Support Vector Machine (SVM) algorithm is an algorithm that can be used classifying tomato leaf diseases. The purpose of this research is to determine the accuracy of the Gabor Filter segmentation and the Support Vector Machine Algorithm for detecting tomato leaf disease to facilitate farmers in analyzing diseases on tomato leaves. The input will go through pre-processing of RGB pixels to Greyscale ones before being processed using Gabor Filter. This Gabor Filter process segments the image to produce a magnitude value. The results of the image magnitude values here will be seen and will enter the classification process using SVM. The SVM algorithm aims to find the best hyperlane on tomato leaves that have been segmented to separate classes in the input space. The application of the SVM method with class classification of tomato leaves by calculating the energy value and entropy of the extraction results, assisted by 12 features, namely: CiriR, Feature G, FeatureB, Standard DeviationR, Standard DeviationG, Standard DeviationB, SkewnessR, SkewnessG, SkewnessB, Mean, Energy, Entropy are used to the simplity classification process with a high degree of accuracy. The process of classification of tomato leaf disease with test data of 600 images managed to get an accuracy value of 74.1667%. In order to facilitate the performance of farmers in predicting tomato leaf disease.
LEARNING PROVOCATION AS A TOOL FOR DEVELOPING CRITICAL THINKING

Digitalization and informatization of the modern world have significantly affected, among other things, the accessibility and volume of information received, its diversity and, at the same time, its contradiction. The change in the pace of life associated with these processes, inevitably affects the main cognitive functions of a person: attention, thinking, memory. It seems it is impossible to modernize the modern educational system in order to meet the new challenges, without taking into account the processes occurring both in the public sphere, and at the personal level. It is now recognized that competency-based approach allows building a productive system that meets new demands at the functional level.
(Upaya Meningkatkan Kemampuan Konsep Matematika Awal Pada Anak Usia 4-5 Tahun Menggunakan Media Papan Flannel)

. In general, students who are compiling their thesis often experience difficulties. The difficulties encountered are very diverse, ranging from a lack of understanding of the problem to be studied, limited references, lack of mastery of theory, not having the desire to start writing, being busy working, and so on. This study aims to analyze the difficulties of seventh semester students in writing scientific papers. This type of research is descriptive research with a qualitative approach. Subject This research is students of seventh semester (semester VII) or final year who are under thesis guidance. Data collection techniques in this study using a questionnaire. A difficulty questionnaire was administered to students who were writing their thesis. Data analysis techniques using percentage techniques are then described. The results of the research generally obtained information that students had difficulty in putting ideas into scientific writing, namely around 58.47%. The use of statistics in data processing is a percentage of 41.64%, and the telling of research results is a percentage of 54.17%. The results of the research are expected to be input, information and reference for all students of the Faculty of Culture, Management and Business of the Mandalika University of Education so that the difficulty factor for students in completing thesis can be overcome.
Peran Guru Dalam Pengelolaan Kelas Terhadap Hasil Belajar Siswa di SDN 1 Kayangan Kabupaten Lombok Utara

In order for educators to develop innovative learning activities, they must have the skills and strive for their development. One of the eight basic teaching skills is variety. This study aims to find out how the teacher's ability influences variations in classroom management. The author of this study conducted research using the library method, namely reading books, articles, and relevant journals as well as data sources. The results showed that increasing student interest in learning, improving student learning outcomes, increasing student achievement, and improving student learning achievement all have a significant effect on the teacher's ability to manage the class. active involvement and motivation of student learning. Consequently, teachers should concentrate on increasing their capacity to manage classroom variation.
Penggunaan Model PBL Untuk Meningkatkan Hasil Belajar IPA Materi Suhu Dan Kalor Sekolah Dasar

The classroom action research conducted by the researchers aims to improve the learning outcomes of fifth grade students at SD Negeri 2 Hajimena, especially in science lessons on temperature and heat. The research was conducted for approximately 3 months. The background of this research is the low student learning outcomes, there are still many educators delivering science learning material only with lectures so that the illustrations captured by students are also still abstract. Delivering material by educators in lectures makes the learning process dominated by educators and only a few students. The lack of students' role in the learning process will cause students to be passive, bored, and bored. This research was conducted by several stages including action, test and observation. The results showed that there was an increase in student learning outcomes influenced by the PBL Model. The increase in the value of science learning outcomes on temperature and heat by students could be seen from before the action was taken, namely in the pre-cycle only 8 students (38.9%) completed, after the action was taken on The first cycle of students who passed increased to 11 students (52.38%), and after the action was taken in the second cycle the students who passed increased to 18 students (85.71%). This research was successful because it had reached the set indicators, namely ≥80% of all students with KKM ≥75.
The Sustainable Development in Sudan, Actuality and Defiance

Achieving sustainable development requires improving the living conditions of all residents in a way that preserves natural resources and avoids them being subject to unjustified waste and depletion. To achieve this, it is necessary to focus on three main areas: achieving economic growth and justice, preserving environmental and natural resources for future generations, and achieving social development by creating job opportunities, providing food, education and health care for all. The study aimed to identify the most important indicators of sustainable development and the challenges it faces in order to achieve its goals, dimensions and principles, and to know the obstacles that prevent the achievement of its goals, and development programs implemented within the framework of the sustainable development process. The solutions that must be taken to avoid these obstacles and the possible ways to develop this new method within the framework of an effective society capable of implementing the sustainable development goals. The study concluded that the indicators of sustainable development in Sudan need further modernization and development in order to be able to keep pace with the progress of nations. In addition, there is weakness on the part of the institutions concerned with overseeing the implementation of the sustainable development goals. The study recommended the need to strengthen the means of implementation and revitalize the global partnership in order to achieve the sustainable development goals. The study also recommended the need to provide and update indicators for sustainable development goals through the competent agencies.
Satellite Optical Signal Modulation Identification Based on Multiple Features and SVM

To address the signal modulation identification problem in satellite optical communication, a signal identification scheme based on multiple features and support vector machines is proposed, and the feasibility and superiority of this scheme are demonstrated.
Multidimensional Resource and Load Collaborative Scheduling Algorithm Based on Reinforcement Learning for Cloud Data Centers

Task scheduling for multi-dimensional resources is one of the most fundamental problems in cloud data centers (DC). Among existing resolutions, the Q-learning model has been considered an excellent tool for fast task scheduling in DC environments. In this paper, we propose a load-balancing model for multi-dimensional resource scheduling in a cloud DC and a Q-learning based task scheduling algorithm (TSQL) that aims to reduce task makespan time and improve resource utilization. Simulation results show that, compared with existing algorithms, our algorithm optimizes 46.92%, 33.67% in makespan and resource utilization.
Detection of Partisan Bias in Political Social Media Posts using Naïve Bayes Algorithm

This research study investigates the detection of partisan bias in political social media posts through the application of the Naive Bayes algorithm. The CrowdFlower Political Social Media Posts dataset is utilized, comprising a collection of labelled posts from diverse political affiliations. The primary objective of this research is to develop an automated system that can effectively classify political posts based on their partisan biases. The study employs data pre-processing techniques, feature extraction methods, and the Naive Bayes algorithm to evaluate the performance of this approach. The findings of this research showcase the potential for accurate detection of partisan bias, contributing to a deeper understanding of political discourse on social media platforms. In order to achieve the research objectives, the study begins by exploring the prevalence of partisan bias in political discussions on social media and the subsequent influence on public opinion. A comprehensive review of text classification algorithms is conducted, highlighting the effectiveness and suitability of the Naive Bayes algorithm for this particular task. The research methodology encompasses multiple stages, including data pre-processing to standardize the text data, feature extraction using the bag-of-words approach, and training a classification model with the Naive Bayes algorithm. The model's performance is evaluated using various metrics such as accuracy, precision, recall, and F1 score.
Exploring Significance of SPOC: A Path to Modernization of Music Cloud Computing

INTRODUCTION: With the development of the information age and the application of cloud computing and big data technology, new changes have occurred in the field of education. Today, the form of learning is becoming more and more diversified, and cloud computing, big data and other information technologies can be more often applied in teaching and learning. The application of cloud computing to the creation and teaching of music can not only improve the interaction between teachers and students in the traditional classroom, but also cloud computing can better capture the problems of teaching in the classroom and provide adjustment suggestions through big data.&#x0D; OBJECTIVES: This study is to realize distance music teaching of SPOC through cloud computing, big data and other technologies. Further use of cloud computing technology is to improve the traditional music teaching classroom teaching and learning tools are not rich enough, the student perception is more single problem. At the same time, cloud computing technology is also utilized in order to explore the effect of distance music education.&#x0D; METHODS: Based on the management of learning theory, constructivism and communicative learning theory, this paper carries out the research on music creation and teaching through the methods of cloud computing and big data, and collects and summarizes the related literature at home and abroad, researches the development of big data and cloud computing in the field of music teaching and introduces the principle of SPOC teaching that supports students' independent learning through big data technology.&#x0D; RESULTS: Based on the training concept of MOOC and cloud computing, the teaching process encourages teachers and students to apply the pedagogical methods of cloud computing to improve the level of music nowadays teaching and learning at the same time, improve the overall quality of students.&#x0D; CONCLUSION: Music aesthetics education has diversity, SPOC learning process and cloud computing technology should be developed by developing an independent learning method. Therefore, cloud computing technology can help students learn music independently in a three-dimensional way, effectively develop the design stage of the learning process, use big data and cloud computing to better enrich the music teaching model, and implement the construction of independent knowledge. Future research can continue to develop towards empirical evidence and a large number of data experiments.
Development of Procedures in Designing Blended Learning Integrated Soft Skills in Higher Education

Blended learning is a teaching approach that combines face-to-face and online learning, requiring instructors to design instruction that considers the combination and timing of both types of learning. The integration of these approaches aims to achieve learning goals. Thus, there is a need for a guide to assist instructors in designing valid, practical, and effective blended learning experiences. This study follows an Educational Design Research (EDR) methodology, which includes preliminary research, a prototyping phase, and an assessment phase, following the Plomp model. The research instruments used in this study include validation sheets, implementation assessment sheets completed by subjects, and participant response questionnaires. The data were analyzed using techniques to assess validity, practicality, and effectiveness. The analysis results indicate that all instruments fall within the valid category. The evaluation of practicality based on participant response questionnaires yielded an overall score of 80%, indicating practicality. The evaluation of effectiveness for the assessment of the design created by the subjects showed excellent results. Participant responses were positive, and the data on the impact of the design structure on new knowledge and skills indicated that participants effectively applied the acquired knowledge and skills. Therefore, the soft skills-oriented blended learning design in higher education has met the criteria of validity, practicality, and effectiveness.
DATA VISUALIZATION USING THE RAPID MINER APPLICATION TO EVALUATE SALES PATTERNS

In today's digital era, data has become a valuable asset for many companies, including those in the retail and sales sectors. Using the right method to interpret and understand this data is the key to improving business strategy and making the right decisions. In this context, data visualization plays a crucial role as a tool for presenting complex information in an intuitive and easy-to-understand way. This study aims to utilize the RapidMiner application in visualizing data for evaluating sales patterns. Using a sales dataset from a retail company, we perform a series of analytical processes using RapidMiner. Various visualization techniques, such as bar graphs, line charts, heat maps and more, applied to extract insights from sales data and identify certain patterns. The visualization results show several interesting findings, such as the season or period with the highest sales, the best-selling products, and the relationship between sales variables. Through this visualization, we are able to provide strategic recommendations to companies to increase revenue and optimize marketing strategies. The conclusion of this study is that RapidMiner, with its capabilities in data visualization, is an effective tool to help companies understand sales patterns and make data-driven decisions. as well as the relationship between sales variables. Through this visualization, we are able to provide strategic recommendations to companies to increase revenue and optimize marketing strategies. The conclusion of this research is that RapidMiner, with its data visualization capabilities, is an effective tool to help companies understand sales patterns and make data-based decisions. as well as the relationship between sales variables. Through this visualization, we are able to provide strategic recommendations to companies to increase revenue and optimize marketing strategies. The conclusion of this study is that RapidMiner, with its capabilities in data visualization
NEP 2020 in the light of Swami Vivekananda’s Educational Philosophy: An Analysis

Swami Vivekananda envisaged that a New India will arise: ‘She is awakening! This motherland of ours, from her deep long sleep. None can resist her anymore; never is she going to sleep anymore; no outward powers can hold her back anymore’ (CW, 3.146). Swami Vivekananda was a revolutionary thinker and out-of-the-box educationist who dared to discard the education system of his times and proposed to replace it with an encompassing student-centric harmonious model towards a unifying society which is just and equitable to all. He dreamt of a scheme of education which caters to the needs of the learners at every level-be it intellectual, moral or spiritual. The program that he propounded was a fusion of age-old traditional values extracted from our timeless scriptures and the modern scientific knowledge that could lead India to become a modernized nation, in unison with the developed powers of the world. There exist many grounds for commonality between Vivekananda’s vision and NEP which reflects how we’re trying to walk down the path laid down by his vision. His scheme of education is comprehensive and complete as it intends to develop all the must-haves in the young learners to help them sail through their lives with élan and to be an asset to the nation. His phenomenal educational philosophy reverberates in the guidelines laid by National Education Policy (NEP) 2020.Thus the present paper highlights the vision /ideals of Swami Vivekananda in the light of NEP 2020
Blockchain-Enhanced Smart Contract for Cost-Effective Insurance Claims Processing

Blockchain-enabled smart contracts have revolutionized the insurance industry due to their potential to streamline backend operations, mitigate fraudulent claims, and enhance data security and transparency. Guided by the design science methodology, the authors propose two specific smart contract frameworks to enhance insurance claims processing related to vehicle damage claims and personal injury claims. These proposed frameworks can improve the overall efficiency and effectiveness of insurance claims processing by automating claims submission, review, analysis, and payment, while reducing fraud and data leakage, by merging various data sources and disintermediation. Furthermore, the authors design a smart contract template supported by eight operational algorithms to facilitate the processing of insurance claims with the help of smart contracts. This template provides practitioners with a standardized prototype for the development of secure and efficient insurance applications.
Use of public domain knowledge bases: A case study on the RDF language

The purpose of this paper is to analyze Semantic Web and Linked Data technologies, with the development of a web application that performs a knowledge modeling through the use of ontologies and RDF (Resource Description Framework) language. A public knowledge ontology/vocabulary was used and populated with data from a relational database from Brazil. The aggregated data was converted to RDF format and made available in an RDF database. The Virtuoso© universal server was used for this task, a hybrid database platform that has the functionalities of a traditional relational database management system, object-relational database, virtual database, RDF, XML, free text, web application server and file server functionality in one system. As a result, a web application capable of retrieving information using the basic principles of the Semantic Web was obtained.
Experimental Demonstration on ZUC-based Key Expansion for Quantum Noise Stream Cipher

This paper proposes a seed key expansion method based on ZUC and bit shifting in QNSC system. Experimental results verify the improved efficiency of key utilization during data encryption, while the security performance is guaranteed.