Reviewerly/exHarmony huggingface dataset:
SAACCESS (SIMPAN ARSIP DENGAN ACCESS) APPLICATION DEVELOPMENT AT 11TH STATE SENIOR HIGH SCHOOL SURABAYA

Archives are the center of memory in every activity in the office. Archives function as a memory center, proof of the existence of the institution, and for the benefit of other institutions. Therefore, there must be good management or management of archives from creation to shrinkage. The main obstacle is the decreasing physical letter storage space, but it’s not possible to build a special building for physical letter storage space. Using the type of research with R&amp;D (Research and Development) and prototype development research methods. Development of this archival application uses a Microsoft Access-based application. This research goes through a research procedure starting with information gathering, designing the product quickly, building a prototype, and the final step is that the application is ready to use with an evaluation that has been carried out by experts. The subject is 2 peoples from 11th Senior High School Surabaya administration staff. The trial was conducted in December 2023 and January 2024. The application feasibility results based on material expert validators and media expert validators get a score of 96%. While the results of application feasibility based on administrative staff get a score of 88.8%, which shows the interpretation of “Very Feasible”. The development of Microsoft Access-based digital archiving applications uses a prototype development model. The SAAccess application received a feasibility score of 96% from both the material expert validator and the software developer. SAAccess also received a score of 88.8% from the administrative staff of 11th Senior High School Surabaya. It can be concluded that SAAccess is effectively used to manage letters in 11th Senior High School Surabaya digitally.
Measuring the quality of the search activity

As Search &amp; Rescue practitioners and trainers delivering to experienced full-time and volunteer searchers, a subject discussed with those who have been responsible for the coordination, management, or command and control of lost and missing person incidents is how do we measure the quality of the search activity that has been carried out on our (and our missing person’s) behalf by the assets that have been identified, briefed, tasked and de-briefed by us?
Analysis of Pepsi Brand Advertising Implementation Using #Betterwithpepsi for Fast Food Brands

Pepsi's recent advertisement campaign, which features the tagline #BetterWithPepsi, was launched in honor of National Burger Day. The campaign has been promoted across all social media platforms and showcases portraits of fast-food packaging that incorporate Pepsi's signature colors into the branding of popular fast-food chains such as Burger King, McDonald's, and Wendy's. This advertisement has been analyzed using semiotic theory by Roland Barthes, who suggests that the use of the advertisement is akin to a collaboration or combination between fast food and drinks that complement each other, such as Pepsi. The tagline #BetterWithPepsi implies that the public will consume food and drinks that are always together, thereby creating a mindset that associates the consumption of food with the use of Pepsi. The advertisement's use of semiotics is evident in the incorporation of Pepsi's colors into the branding of other fast-food chains, which creates a visual association between the two. This association is further reinforced by the tagline, which suggests that the consumption of food is incomplete without the addition of Pepsi. The advertisement's effectiveness can be attributed to its ability to tap into the public's desire for convenience and the need for a complete dining experience. By positioning Pepsi as an essential component of the fast-food experience, the advertisement creates a sense of loyalty and brand recognition among consumers.
The Mediating Effect of Problem-based Learning on the Relationship between Technology Integration and Student Engagement in Mathematics

This research aimed to determine whether problem-based learning significantly mediates the relationship between technology integration and the engagement of first-year college students. A quantitative approach with descriptive and correlational designs was employed. The respondents of the study were 133 first-year college students in three state colleges in the Division of Davao del Norte. They were chosen through stratified random sampling. Mean, Pearson-r, regression, and mediation analysis were used to analyze the data, which were obtained through the use of three adapted questionnaires. The findings revealed that technology integration is manifested in the students’ learning. In mathematics, student engagement is observed, and problem- based learning is evident among the students. It is also found out that there is a significant relationship among technology integration, problem-based learning, and student engagement. Additionally, problem-based learning partially mediated the relationship between technology integration and student engagement. The findings suggested that CHED officials should encourage and support the integration of technology into the mathematics curriculum to foster increased student engagement. School administrators can work to maximize student engagement by focusing on the integration of technology and employing problem-based learning methods. Teachers may integrate technology into their lessons and incorporate problem-based learning, and college students may consider integrating technology into their learning environment. Future researchers should explore the effects of technology integration and problem-based learning on student engagement in mathematics.
Mobile Adaptive Routing Algorithm for Road-Aware Infrastructure-Assisted Communication in Cognitive Internet of Vehicles

The Internet of Things (IoT) is expanding the capabilities of traditional vehicular ad-hoc networks (VANET) into the Internet of Vehicles (IoV). However, there are a few challenges that need to be addressed in order to enhance the intelligence of IoV, leading to the development of a new evolving technology called Cognitive Internet of Vehicles (CIoV). In this study, we propose a road-aware infrastructure-assisted and vehicle-to-vehicle (V2V) adaptive routing system to select the most efficient route for delivering data from the source to the destination vehicle, with the aim of reducing data delivery delay. The performance is measured and evaluated based on packet delivery ratio (PDR), average end-to-end (E2E) delay, and normalised routing overhead using MATLAB. By comparing the proposed mobile adaptive routing algorithm (MARA) with existing protocols, it has been examined and found to outperform the existing ones in terms of performance.
Android-Based Mobile Learning Application Using App Inventor on Computer Operating System Material: The Development and Validity Study

Mobile learning apps are widely acknowledged for their effectiveness in enhancing learning results. This study aims to develop and validate an Android-based mobile learning app for computer operating system principles. Using the user-friendly App Inventor platform known for visual programming, it integrates interactive modules and multimedia for diverse learning styles. The study adopted a Research and Development approach following the ADDIE model (analysis, design, development, implementation, and evaluation). The research was conducted at Universitas Negeri Padang and Universitas Muhammadiyah Muara Bungo and involved 10 participants. The analysis of questionnaire-based data conducted by media and material experts categorized the Android-based learning media as "Appropriate", achieving an over-all average of 82.51% and 82.29%, respectively. Meanwhile, student evaluations rated this media as "Feasible" with a score of 82.72%. In conclusion, the development of this Android-based mobile learning application for computer operating system material demonstrates significant potential as an innovative educational tool. The validation process highlighted its potential effectiveness and offered valuable recommendations to enhance its educational value. These findings make a meaningful contribution to the ongoing discourse surrounding the integration of technology-driven learning approaches into traditional education, benefiting educators and developers seeking to create impactful mobile learning experiences.
FEATURES OF THE DEVELOPMENT OF MATHEMATICAL IDEAS OLDER PRESCHOOL CHILDREN WITH INTELLECTUAL DISABILITIES

This article is devoted to the theoretical analysis of the problem of the development of mathematical concepts of older preschoolers with intellectual disabilities. The peculiarities of thinking as a cognitive process of the individual are analyzed. The basis of the thinking process is always analysis and synthesis. Analysis is a necessary condition for the scientific interpretation of facts. It requires completeness, depth and accuracy. This is the first stage of studying any phenomenon. Synthesis, as a thinking process, can occur at different levels in human activity, starting from a simple mechanical connection of parts of a whole to the creation of a scientific theory based on the generalization of individual facts and research materials. It can be carried out both on the basis of perception and on the basis of memories and ideas. Although opposite in nature, the operations of analysis and synthesis are actually closely related.&#x0D; The psychological features of older preschool children are analyzed. During this period of development, the child’s cognitive sphere is significantly enriched and developed; perception becomes more conscious and purposeful; voluntary and involuntary attention, the ability to analyze and the ability to reproduce what was previously learned develop; there is a transition from visual-active to visual-figurative thinking; verbal and logical thinking begins to develop; generalized ways of thinking are formed: comparison, search for similarities, differences, classification, analysis, combination; the grammatical structure of the native language is mastered.&#x0D; The psychological characteristics of mathematical representations of children with intellectual disabilities are provided. Such children in older preschool age have no desire to engage in intellectual games, there is an increased interest in mobile, non-targeted games. The pace of perception is slowed down, the volume is narrow. They can hardly distinguish the main or general thing in the picture, in the text, grasping only individual parts and not understanding the internal connection between the parts, they often confuse graphically similar letters, numbers, objects. All mental operations (analysis, synthesis, comparison, generalization, abstraction) are not sufficiently formed. A distinctive feature of thinking is uncriticalness, the inability to independently evaluate one’s work.&#x0D; The methodological foundations of the empirical study of the development of mathematical concepts of older preschoolers with intellectual disabilities are substantiated. The obtained indicators of the formation of mathematical representations of older preschoolers with intellectual disabilities are experimentally analyzed; specifics of combinatorial and conceptual thinking of children with intellectual disabilities; indicators of the development of thinking operations of children of older preschool age.
A Machine Learning Guided Path for Optimal Literature Review

This paper introduces a novel machine learning framework to address the challenge of optimizing literature research by identifying the optimal path. To create dataset and ensure the versatility of the solution for different applications, we developed an online scraping tool designed to extract articles from ResearchGate based on a specific search query. The proposed machine learning model leverages contextual embeddings and graph theory, translating intricate scholarly work into informative steps for one to go wider rather than deeper in their research. By employing a Christofides approximation of the Traveling Salesman Problem algorithm, our model efficiently navigates through more than 1000 article embeddings. We prove that the resulting path not only accelerates the knowledge gaining process, but also evidently diversifies the findings. Moreover, we evaluated multiple PDF reader libraries to arrive at the most suitable one for the purpose. This adaptability allows the framework to be applied not only to scraped articles, but also to those stored as PDF files, giving an option for multiple data sources. In conclusion, this paper presents a transformative approach for literature research optimization, equipping researchers with a potent tool to efficiently explore articles.
A Micro-class Teaching Data Retrieval Method of Business English Based on Network Information Classification

In order to quickly extract the required micro-class teaching data of business English in the fragmented network information environment, a micro-class teaching data retrieval method of business English based on network information classification is offered. This way, it constructs a network information classification method on the basis of the optimised SVM model, and the parameters of the SVM model are optimised and trained by the improved artificial bee colony algorithm. After optimising the function of the SVM method, the method classifies the online teaching information of various business English micro-class teaching; In the classified network information set, the targeted retrieval method of network teaching resources according to big data technology is adopted to obtain the teaching data with the highest similarity to the user's retrieval data by clustering and complete the targeted retrieval of micro-class teaching data. The experimental results show that the retrieval delay of the proposed method for micro-class teaching data retrieval of business English is less than 1s, the number of correct retrievals is relatively high, and there are few wrong retrieval phenomena.
Implementation of Virtual Laboratory of Electronic Commerce Into University Course

Plenty of information and communication technologies are frequently employed in educational activities to improve the opportunities for students to gain knowledge and experience, including the virtual laboratory. The virtual laboratory is quite often implemented into educational process in many science, technology, and engineering courses at the university level of education. However, the use of virtual laboratory in the field of electronic commerce education is rather rare. In our educational practice, a virtual laboratory of electronic commerce was designed and implemented within the course of electronic entrepreneurship. This paper presents the design of the virtual laboratory of electronic commerce and provides an outline of its integration into the university course's teaching process. The study examines the learning progress claimed by the students who participated in the most current edition of the course delivered utilizing this virtual laboratory. The findings revealed improvement of course participants' experience and abilities in the field of electronic entrepreneurship in e-commerce.
Blocking Dangerous Content in Electronic Communications Networks: Evidence from Netherlands, United States and Singapore

In recent years, the blocking of internet sites with harmful content or those deemed to be (illegal content) has increased. The policy of blocking dangerous sites has pros and cons regarding freedom of expression. Blocking is considered to be carried out to control citizens' expression, which can impact all areas, especially freedom of opinion, which can be seen as a threat to certain parties. This research aims to compare criminalization policies for blocking dangerous content in electronic communications networks in the Netherlands, the United States, and Singapore and provide thoughts on law enforcement models for blocking dangerous content in more democratic electronic communication networks. This is normative legal research using a law and case approach and comparing several countries. The conceptual approach is directed at the concept of a democratic state and the protection of human rights to formulate relevant policy models. The results of blocking studies in the Netherlands, The USA, and Singapore already have regulations and policy directions for blocking dangerous content, or at least rules regarding law enforcement for cybercrime. The difference is in the level of sensitivity to the specifications of existing problems. The policy model for blocking dangerous content with special regulations outside the Criminal Code must be carried out in a non-repressive manner so that it does not violate the ultimum remedium principle and becomes over-criminalized. The formulation of policy model of all crime prevention plans using the criminal law system, which pays attention to the problem of formulating criminal acts (criminalization), criminal responsibility, and criminal regulations and punishment.
Crime Prediction Using Twitter Sentiments and Crime Data

The incidence of crime is now of great concern globally. The culprits change their tactics on a regular basis. These crimes affect persons, groups, and the government to the extent a whole lot of budgets are allocated to serve as preventive measure to these crimes. The aim of this research is to predict crime based on Twitter hourly sentiments and crime data records. This is because it has been observed that existing crime prediction models that used Twitter data entail some drawbacks in predicting criminal incidents as a result of the unavailability of hourly sentiment polarity and demographic factors. Additionally, SHAP framework was used for the interpretability to rank the feature based on their importance. The xgboost algorithm was utilized with tuning to have an optimal model. The accuracy of 0.81 (81%) was obtained and an Area Under the Receiver Operating Curve (ROC AUC) score of 0.7079 was obtained. The result of this study indicated that crime could be predicted in real-time in contrast to earlier studies on this subject matter. Consequently, it is advised that this work be applied to real-world situations
Lightweight single image dehazing network with residual feature attention

The quality of the images captured by the camera deteriorates in hazy weather, which affects the effectiveness of subsequent high-level vision applications. Extensive methods have been proposed to remove haze and restore clear and haze-free images. However, these methods mainly focus on the accuracy of the model, while ignoring the computational complexity and inference speed that make it difficult to deploy on resource-constrained devices. To address the aforementioned problems, we propose a simple but effective single-image dehazing network. The network is based on the classical U-Net architecture. First, the encoder uses a down-sampling operation to extract shallow hierarchical features and reduce the dimension of the features. Then, the degraded features are gradually restored through the cascaded feature recovery module. Finally, the deep and shallow features are fused through the decoder to obtain the recovered images. The proposed method leverages the stacked larger kernel convolutions to enhance the local and global feature learning capability, and better cope with the severe degradation of image quality in dense and non-homogeneous haze weather through the hybrid attention mechanism.
Improving Software Engineering Students’ Creative Thinking and Motivation Using Practical Prototyping and Innovation Techniques

Traditionally university students lack motivation in subjects that are more focused on documentation and theory. This problem only deepens with each new generation. A practical workshop approach has been implemented in the subject “Analysing system requirements and specifications”. Its place in the curriculum is explained. A technique for developing innovation and prototypes, used by Google for motivation is described. The method of its’ implementation is thoroughly documented. A brief experiment in the form of a workshop is described and the gathered data is analysed. A survey on student feedback is conducted and the results are discussed. Influence on student soft skills improvement is evaluated. An observation on using the methodology as an introductory workshop to break the ice with engineering students is made. The conclusions made based on the feedback data and discussions with students show that the methodology is successful and student motivation and attendance is increased.
A Comparative Review of AI Techniques for Automated Code Generation in Software Development: Advancements, Challenges, and Future Directions

Artificial Intelligence (AI), as one of the most important fields of computer science, plays a significant role in the software development life cycle process, especially in the implementation phase, where developers require considerable effort to convert software requirements and design into code. Automated Code Generation (ACG) using AI can help in this phase. Automating the code generation process is becoming increasingly popular as a solution to address various software development challenges and increase productivity. In this work, we provide a comprehensive review and discussion of traditional and AI techniques used for ACG, their challenges, and limitations. By analysing a selection of related studies, we will identify all AI methods and algorithms used for ACG, extracting the evaluation metrics and criteria such as Accuracy, Efficiency, Scalability, Correctness, Generalization, and more. These criteria will be used to perform a comparative result for AI methods used for ACG, exploring their applications, strengths, weaknesses, performance, and future applications.
Multi-objective Meta-heuristic Technique for Energy Efficient Virtual Machine Placement in Cloud Data Centers

Cloud computing has emerged as an efficient scalable solution for storing and processing a large amount of data. Cloud data centers provide the resources on demand to the consumers on pay-per-use model. However, the large amount of datacenters is required to support the growing demand of the cloud consumers. This should be handled in an optimized way to avoid the resource wastage so that more consumers can get the benefits of the data centers. Virtualization is the technology of creating virtual version of the computers called Virtual Machines (VM). A Virtual Machine Placement problem is a fundamental challenge in cloud computing where the goal is to determine the optimal allocation of Virtual Machines to Physical Machines (PM) within a data center. An efficient Virtual Machine Placement technique helps to properly place the VMs on the PMs which significantly optimize the number of servers, maintenance cost, CPU utilization and power consumption. We present a novel hybrid approach that combines Ant Colony Optimization (ACO) algorithm and Sine Cosine Algorithm (SCA) for an efficient VM placement. Since SCA is an emerging search algorithm using Sine and Cosine functions in Engineering field, it has been used to explore the solutions obtained by ACO algorithm ACO algorithm has been applied to exploit the solutions of the search space for efficient VM placement which helps in power management and also to minimize the resource wastage. The result has been verified with the performance against other algorithms to prove that our proposed algorithm outperforms the other algorithms