Reviewerly/exHarmony huggingface dataset:
Youth exposure to and usage of illicit drugs as an imperative in security discourse in Nigeria: Media`s role in curbing the menace of drug

Terrorism, armed robbery, ritual killings, and other sundry criminal acts have put Nigeria’s security under pressure. Insecurity is now a daily topic of discussion in all parts of the country. More disturbing is the fact that most perpetrators of criminal acts associated with insecurity are youth who abuse drugs. Yet, there seems to be a paucity of studies that probe some of the root causes of insecurity in Nigeria. This study, which relied on Social Learning Theory, measured the level of exposure youth have to illicit drugs via social media; established the relationship between illicit drugs consumption and crime/insecurity, and examined the role the media can play in curbing the consumption and/or use of illicit drugs. It used a quantitative research method. Three hundred twenty-two copies of a questionnaire were administered to students of Delta State University of Science and Technology, Ozoro, Delta State, Nigeria selected through a simple sampling technique. Results showed some youth get to know about illicit drugs through social media. A correlation was also found between illicit drug consumption and insecurity. The media can help curb drug abuse by the youth through enlightenment campaigns, among others. The study concluded that the attainment of appreciable security in Nigeria may remain a mirage without adequately addressing the issue of drug abuse. Thus, it was recommended that the media should create more awareness about the negative implications of illicit drug use by the youth by pointing out the dangers associated with drug abuse.
Analisis Optimalisasi Ketahanan Daerah Berbasis GIS, Remote Sensing dan Cloud untuk Manajemen Banjir dan Rob di Kota Semarang

Abstract. Floods and tidal floods are a topic of discussion every year in the city of Semarang because no proper solution has been created for mitigation. From January 2022-May 2023, most of the flood and rob events are located in flat and sloping areas. The disaster had an impact on human life, such as material, physical, economic, and psychological losses. Importance of innovation to create flood resilience is urgently needed to eliminate or minimize the adverse effects of floods and rob. Flood resilience analysis uses a spatial approach supported by GIS optimization, Remote Sensing, and the Cloud platform. Then the model builder is used to speed up and simplify the analysis process. The results of the analysis show that the highest level of flood sensitivity is in flat and gently sloping areas with high population density &amp; buildings. Meanwhile, high capacity levels are in areas close to health facilities, have road accessibility, and have lots of economic activity. In addition, 93.37% of the area's resistance to flooding is still classified as low and medium. This should be of particular concern for areas with dense populations and buildings, such as Pedurungan District, Ngaliyan District, North Semarang District, West Semarang District, and Genuk District. Thus, through regional resilience mapping, it can become a basis for decision-making for local governments with the support of inclusive disaster management.
Evaluating the Effect of Crowd Design, Information and Management on Crowd Safety in KL Car- in Free Morning Sporting Events

The KL Car-Free Morning event in Kuala Lumpur is a popular sporting event promoting physical activity and a healthy lifestyle. It occurs every Sunday and involves closing streets for activities like cycling, running, and walking. With the growing number of participants, safety concerns have emerged, necessitating proper planning and safety measures. Event design includes street closures, accessible route design, safety measures, varied activities, evaluation and monitoring, and community engagement. The purpose of these studies is to investigate the effect of crowd design, information, and management on crowd safety in KL Car-Free Morning Sporting Events. A quantitative method was used research as a research design and a survey method was for data collected. The population of this study are all the participants that join this event either from running, cycling, walking, rollerblading, or skateboarding activities. SPSS was used as a tool for data analysis. The findings of this study present that crowd design and management significantly affect crowd safety and crowd information does not significantly affect crowd safety. This study is important for the event organizer to understand the factors that will affect the safety of the participants.
Evaluation of Reliability in Request-segregated Clouds through Remiadiations Predicting Hardware Failure Scheme

Background: Cloud services have become a popular approach for offering efficient services for a wide range of activities. Predicting hardware failures in a cloud data center can minimize downtime and make the system more reliable and fault-tolerant. Objective: This research aims to analyze a predictive hardware failure model based on machine learning that anticipates the required remediations for undiagnosed failures in a cloud computing system serving multiclass requests. Methods: The model is tested on a carefully designed cloud data center that categorizes incoming requests as web, compute, storage, and dedicated server requests. To demonstrate improved reliability, a carefully designed test case is run on ReliaCloud-NS, which is a simulator for creating a CCS and computing its reliability. Results: The work found that using this model considerably enhanced the reliability of cloud computing systems when compared to not using the model. Conclusion: Although various estimation methods are patented to evaluate the system reliability of a cloud computing network, the emphasis of this study was mostly on improving the reliability of request-segregated clouds upon failing hardware resources like CPU, memory, bandwidth, and hard disc. Moreover, the prediction model might potentially be expanded to other system resources such as GPUs, software, and database packages.
Value Assessment of Online Educational Resources in the Context of Blended Learning

In the context of promoting informatization education and reforming blended learning, how to accurately assess the value of online educational resources has become an important research topic. However, most existing assessment methods rely on direct data statistics and experience-based judgment, lacking scientific prediction models and comprehensive consideration of learning cycles. To solve this problem, this study constructed a hit prediction model of online educational resources based on the fusion of extreme learning machine and grey Verhulst model, and a hit-based value assessment model of the resources considering the learning cycles of students. The research results showed that the proposed model not only predicted and assessed the value of online educational resources more accurately, but also provided theoretical support and decision-making reference for the implementation of blended learning reform, thereby promoting the effective utilization of online educational resources.
Learning Mathematics with Large Language Models

Artificial intelligence (AI) has permeated all human activities, bringing about significant changes and creating new scientific and ethical challenges. The field of education could not be an exception to this development. OpenAI’s unveiling of ChatGPT, their large language model (LLM), has sparked significant interest in the potential applications of this technology in education. This paper aims to contribute to the ongoing discussion on the role of AI in education and its potential implications for the future of learning by exploring how LLMs could be utilized in the teaching of mathematics in higher education and how they compare to the currently widely used computer algebra systems (CAS) and other mathematical tools. It argues that these innovative tools have the potential to provide functional and pedagogical opportunities that may influence changes in curriculum and assessment approaches.
5 Künstliche neuronale Netze

No AccessKünstliche IntelligenzOct 20235 Künstliche neuronale Netzehttps://doi.org/10.3139/9783446478824.005SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2023Pages: 197-210Print ISBN: 978-3-446-47881-7eISBN: 978-3-446-47882-4 PDF downloadLoading ...
Research and Simulation of Robot Cluster Motion Based on Flocking Algorithm

The research on robot cluster control and collaborative motion has gradually become an important issue in the research of cluster robots A clustering control and collaborative motion algorithm based on the Flocking algorithm is proposed to address the above issues, which mainly includes three parts: robot cluster path planning, cluster object avoidance, and cluster formation control Firstly, a stable cluster formation is observed through the cluster control of the Flocking algorithm, which enables it to have the ability of cluster collaborative motion Based on this, an improved A * algorithm can be used to plan a cluster movement path At the same time, in the collaborative motion of robot clusters, dynamic and static objects can be avoided through the DWA algorithm, there quickly reaching the destination Solve the problem of cluster control and collaborative motion of robots in complex environments, and finally verify the effectiveness and rationality of the algorithm through simulation experiments.
EStore: A User-Friendly Encrypted Storage Scheme for Distributed File Systems

In this paper, we propose a user-friendly encrypted storage scheme named EStore, which is based on the Hadoop distributed file system. Users can make use of cloud-based distributed file systems to collaborate with each other. However, most data are processed and stored in plaintext, which is out of the owner’s control after it has been uploaded and shared. Meanwhile, simple encryption guarantees the confidentiality of uploaded data but reduces availability. Furthermore, it is difficult to deal with complex key management as there is the problem whereby a single key encrypts different files, thus increasing the risk of leakage. In order to solve the issues above, we put forward an encrypted storage model and a threat model, designed with corresponding system architecture to cope with these requirements. Further, we designed and implemented six sets of protocols to meet users’ requirements for security and use. EStore manages users and their keys through registration and authentication, and we developed a searchable encryption module and encryption/decryption module to support ciphertext retrieval and secure data outsourcing, which will only minimally increase the calculation overhead of the client and storage redundancy. Users are invulnerable compared to the original file system. Finally, we conducted a security analysis of the protocols to demonstrate that EStore is feasible and secure.
Research on Software Fault Feature Data Extraction Method for Software Fault Prediction Technology

The correlation between software failure characteristics and software failure directly determines the predictive performance of the failure prediction model. The extraction of software fault features is crucial for building equipment software fault prediction models, and is an important process to ensure accurate prediction. However, the software fault feature data extraction method is often complicated to use and has no pertinence to the selected software fault feature data, and it takes a lot of time to complete the extraction steps. This paper summarizes software metrics and software defect types based on research at home and abroad, and selects software metrics and software defect types that are suitable for equipment software. Using regular expression technology and CSV technology research the automatic extraction way of software fault features, and finally constructs a fault data set that can be used for software fault prediction models.
Design of an Automated Handling Robot System Based on Autonomous Driving Technology

An Ackerman mobile robot based on the open-source Robot Operating System (ROS) was developed in this research, which can be controlled by the self-designed upper computer and achieve automated handling in specific situations. The robot can use the gmapping algorithm to build a map, use LIDAR and IMU sensors to obtain information about the external environment, and locate the position and attitude of itself in real-time. When the robot receives the target point sent by the upper computer, The robot will autonomously path plan and avoid surrounding obstacles according to the target point sent by the upper computer and the external environment, complete the required tasks through deep learning, and reach the known target point. And, this paper makes improvements to the pure pursuit algorithm in the path tracking method for self-driving car. For the traditional pure pursuit algorithm, the tracking accuracy is limited by the look-ahead distance and the inability to achieve a good tracking effect, this paper proposes the dynamic look-ahead distance selection and the improved pure pursuit algorithm.
Applying Story Grammar Strategy Combined with Google Classroom as a Media in Teaching Reading at SMKN 3 Parepare

Reading comprehension is such very essential to life. The readers who understand how a text is structured find greater success in identifying important information and relationships between ideas in the text. Based on the preliminary test (preobservastion) at SMK Negeri 3 Parepare, the collected data showed that students were not satisfied with their learning, in this case, the subject of reading. They were inactive students in the classroom, especially because they became lazier in reading any kind of text because the teacher used the silent reading method. The hardest part is when they cannot get the whole point of the text, likewise when they have a task or assignment from their teacher to answer. Therefore, the researchers found that the students’ had difficulty understanding the context and getting the information in the text. Story Grammar Strategy is a good way to improve students’ reading comprehension combined with google classroom as a media. By using this method, the researcher’s objectives are to help the students recognize the elements of narrative text and use these elements to improve their comprehension of the story. The data of the research are Pre Experiment of Quantitative Research. The design of this research is one group pre-test and post-test design with 34 total samples. The instrument of the research was a reading test using reading text. The reading texts were taken from the Step by Step Book. The total number of the test was 10 numbers, with 5 test items for true-false test and 5 test items for the essay test. The findings of the research showed that the story grammar strategy combined with google classroom successfully improved the students’ reading comprehension. As a fact, based on the findings, most students have a very good score on the post-test., which was 90,88. While the mean score of the pre-test was 44,55. It means that the treatment was successful in improving the student’s reading comprehension, and the students gave positive responses in the learning process.
DEVELOPMENT OF ALPHABET BLOCK MEDIA FOR BEGINNING READING LEARNING IN CLASS I ELEMENTARY SCHOOL

Study Program Teaching Faculty of Education Science Balitar Islamic University Advisor (I) Desy Anindia, M.Pd.I. Advisor (II) Sripit Widiastuti, S.Pd,. M.Pd.This research has a background in the low ability to recognize students' letters with low interest in reading as well, so additional learning media is needed besides books and worksheets that are commonly used in schools. The purpose of this study was to show the feasibility of the media and to find out the readability of teachers and students towards alphabet block media in the ability to recognize letters, so as to be able to develop early reading skills in grade 1 elementary school children.Data collection techniques by conducting questionnaire observations and interviews using the Research and development (R &amp; D) method approach with 7 research steps. Data collection was carried out on 60 grade 1 elementary school students in 3 schools, namely SDN Sidorejo 01, SDN Doko 01 and SDN Doko 02 along with their class teachers.The results of the feasibility analysis of the media through 3 validators obtained a percentage with an average value of 94.29%, material and language experts obtained a percentage with an average value of 95.00%. From the results of the media feasibility analysis by 3 media expert validators, 3 material and language expert validators on product development which were then tested by conducting field practice to analyze the readability of teachers and students towards the media as teaching materials for beginning reading learning materials. In the teacher readability test, the results obtained were 93.94% &amp; student readability was 90.44% with a very decent category. The results of the validation and readability stated that the alphabet block learning media was included in the very feasible criteria with an achievement level of 81% - 100%.
The Development of a Rental Equipment Mobile Application for UiTM Shah Alam Malay and Bumiputera Students (Rent2U)

This project is regarding the development of a mobile application for rental equipment for UiTM Shah Alam Malay and Bumiputera students. The reason for the development of this project is to help the Malay and Bumiputera students to rent items and equipment they needed. Based on the previous study, most students in UiTM Shah Alam are those who have financial problems and came from a low-income family or household, known as B40. Therefore, this mobile application for rental equipment would be able to solve problems such as the inability in buying new items and belongings (or equipment). In some cases, students are required to have specific items to attend a one-time event without overspending and are unable to explore new hobbies due to financial limitations. As such, this project aims to develop an Android-based mobile application called Rent2U that can help UiTM Shah Alam students, especially those who come from a B40 family to rent items, and equipment they needed. The objectives of this project are to identify the requirements, to design and develop the equipment rental mobile applications for UiTM Shah Alam students. The chosen methodology for the development of this mobile application is Mobile Application Development Lifecycle (MADLC) and covered up until the testing phase only. The outcome of this project is the mobile application for rental equipment, which has features like geolocation to find nearby items and equipment for rentals, a search function to find items and equipment and push notifications to alert the users about the listings that have been created by them for rental. Hence, the significance of this project is that it can help the students in need to rent and lend items and equipment by providing them a platform to lend their belongings, and at the same time be able to rent items and equipment they like or need. For future enhancements, this application may include a variety of options for the users to pay such as online banking, and credit card, among others. In addition, this application may also include goods and equipment verification to avoid renting any dangerous items.
Influence of Learning Flow and Self-Efficacy for Group Work on the Problem-Solving Ability of Nursing Students in Fundamental Nursing Class using Flipped Learning

Purpose: This study was conducted to investigate the relationship between learning flow, self-efficacy for group work, and problem-solving ability and to identify the factors influencing the problem-solving ability of nursing students in a funda-mental nursing class using flipped learning. Methods: A descriptive study design was used, and data were collected using self-reported questionnaires from 121 nursing students. Descriptive statistics, Pearson correlation, and stepwise multiple re-gression analysis were used with the SPSS Win 26.0 program to analyze the data. Result: The problem-solving ability of nursing students showed a positive correlation with learning flow (r=.75, p<.001) and self-efficacy for group work (r=.68, p<.001). The significant factors that explained the problem-solving ability included learning flow and self-efficacy for group work, and together they accounted for 63.4% of the variance. Conclusion: These findings suggest that flipped learning in a fundamental nursing class has a positive effect on the learning outcomes of nursing students. One of the benefits of adopting flipped learning was that the students were able to achieve a greater depth of learning. Students were also able to gain a more complete understanding of content because they received more frequent feedback from educators. In ad-dition, classrooms that incorporate flipped learning offered more opportunities to interact and learn from other students.
Motivating Mentally Retarded Students by Using the Quizizz Application

The purpose of this study was to investigate why students in a special needs school who are mentally retarded use the Quizizz application and how teachers utilize the program at special needs school (Sekolah Khusus) 01 Serang city. Case studies made up the research methodology. The instructor and mentally retarded students, a ninth-grade mentally disabled student at Sekolah Khusus Negeri 01 Kota Serang, were watched and interviewed by the researcher. According to the research's results, utilizing Quizizz in the special needs school (SKh) 01 in Serang city began with the instructor introducing or chatting with the ninth-graders about it in order for them to feel more at test using the online assessment technique. The teacher employed Quizizzes extremely useful features in the Quizizz implementation as well. The responses of students toward using Quizizz were based on an interview with mentally retarded students, which revealed that: (1) The majority of students agree that Quizizz is excited motivation, and fun and that Quizizz creates an engaging atmosphere; (2) Quizizz is interesting with lots of useful features; and (3) A competitive surroundings can be created because Quizizz has many difficult features, which encourages the students to be the top scorer on the Quizizz leaderboard. Mentally disabled pupils in English language instruction may benefit from the Quizizz application.
Enhancing Reading Proficiency: An Investigation into the Effectiveness of Think Pair Share and Jigsaw

The aim of this study is to find out whether the Think Pair Share (TPS) method and Jigsaw method are effective for teaching reading comprehension skills to the tenth grade students of SMAN 1 Prambon, East Java. The quasi-experimental design was applied in this study. There were 33 students of X2 as the experimental class which is using Think Pair Share Method and 31 students of X1 as the control class which is using Jigsaw Method. The instruments used are pre-test and post-test. The result of this study proved that the Think Pair Share method and Jigsaw are effective to teach reading comprehension. On the other hand, when comparing which method is more effective between the Think Pair Share Method and the Jigsaw Method for teaching reading, it can be seen from the result that Think Pair Share Method is more effective than the Jigsaw Method in teaching reading comprehension.