Reviewerly/exHarmony huggingface dataset:
Security in cloud computing: Methods for ensuring privacy and integration in modern applications

Authors:
raw_author_name: Oleksii Zarichuk
raw_affiliation_string: Computer and Information Systems Manager LLC Fides 02000, 11A E. Sverstyuk Str., Kyiv, Ukraine

Abstract: Cloud computing has become a necessary component for data storage and processing and is becoming more widespread. However, there are threats to the security and privacy of user data, which is why it is important to find out the most effective methods for ensuring data security in the cloud. The purpose of the study was to develop methods aimed at ensuring privacy and security in cloud environments and in modern applications. The method of analysis was used to review other publications on the topic, and the method of experiment was used for practical implementation. The main results of the study include the development of a security monitoring programme. It analyses event logs and determines the number of failed login attempts, which indicates the detection or absence of suspicious activity. Access to resources is checked, and the necessary information is displayed on the console. A comparison table of cloud platforms has been created, considering their advantages and disadvantages in the context of data security and privacy. It specifies the criteria for delivering services to the selected services. A block diagram of ways to provide security in cloud computing is developed, illustrating the relationship between various aspects of providing security in cloud systems. It contains parameters and strategies for encrypting data, protecting sensitive data, and countering attacks. Various aspects of security and methods of ensuring privacy in cloud computing are considered, namely authorisation, intrusion detection, regulatory requirements, integration with modern applications, monitoring and logging, user identification and authentication. The practical significance of the study lies in the creation of innovative ways to help improve security and privacy in cloud computing. They will allow cloud developers and administrators to effectively protect user data and ensure their privacy in modern applications
Motivational and semantic relations of a person in professional activity

Authors:
raw_author_name: Lyudmila Zhalalovna Karavanova

Abstract: The object of this research is the motivational and semantic relations of the individual. The subject of the research is the motivational and semantic relations of employees with different professional affiliations and specifics of performing functional duties. The purpose of the research is to study the structure of motivational and semantic relations of a person and to identify patterns of influence of professional affiliation and functional duties. The methodological basis for writing the article is the research of domestic and foreign scientists. Theoretical (comparative analysis) and empirical (interview, questionnaire) research methods were used in the study. The orientation of motivational and semantic relations of a person does not depend on the professional affiliation and the specifics of the performance of functional duties. Since the motivational and semantic relations of a person in professional activity are characterized by the presence of motivation based on the personal meaning, which motivates a person to activity and depend on the psychological state of a person who is in certain life circumstances. Motivational and semantic relations of a person are based on motivational and semantic processes that accompany and support a person throughout his or her working life. The aim of the work is to establish the regularities of the influence of professional affiliation and the specifics of functional duties on the motivational and semantic relations of employees to professional activities. In order to increase the efficiency of professional activities and improve the motivation of employees to the heads of organizations, the authors give practical recommendations for improving psychological support in organizations.
Development of Basic Geology Mobile Learning Based on Android Indonesia Geodiversity Area

Authors:
raw_author_name: Tri Kukuh Prasetiyo
raw_affiliation_string: Direktorat Pengembangan Kompetensi Badan Riset dan Inovasi Nasional

Abstract: Basic Geology is a prior knowledge that needs to be supported by a flexible learning environment through the use of mobile technology. Through the supports of mobile technology, students will gain freedom of access because they can be used anytime and anywhere. The progress and speed of technological development, the ease and practicality of using smartphone devices are the potential, opportunities and challenges for presenting mobile technology in learning. The presence of generation Z who are already familiar with technology has reinforced the need to utilize technology to accommodate them in learning better. The aim of this development research is to produce a learning product in the form of a Basic Geology mobile learning application to support learning anywhere and anytime and to determine the feasibility of the product in terms of media and materials, as well as responses from users. This research uses the Lee &amp; Owens model in developing mobile learning applications. Data was collected using a questionnaire filled out by media experts, material experts and service users in the Indonesian Geodiversity Area. The results of this research are (1) user needs for mobile learning to support Basic Geology learning by providing learning resources and building learning communities, (2) producing Basic Geology mobile learning products, (3) results of feasibility tests by media experts, material experts and Individual, small group and field trials show that mobile learning is suitable for use in learning.Keywords: geodiversity; basic geology; mobile learning
Problems of crime prevention by operational-investigative units in Kazakhstan

Authors:
raw_author_name: Kanat Lakbayev
raw_author_name: Gulnara Rysmagambetova

Abstract: Relevance. Crime prevention by operational-investigative units is an integral part of effective law enforcement, yet it is increasingly being overshadowed by a punitive approach focused on arrests rather than proactive prevention measures. This reactive approach results in significant societal costs and fails to address the root causes of criminal behavior. Purpose. This study aims to examine the challenges faced in organizing effective crime prevention efforts by operational-investigative units in Kazakhstan and propose clear criteria to evaluate and improve the efficacy of such preventive measures. Methodology. An integrated approach combining theoretical principles from related legal branches and practical insights from the activities of operational-investigative units in Kazakhstan is employed. Various research methods, including system-structural, comparative, logical, and transition from general to particular concepts, are utilized. Results. The study identifies several key issues hindering preventive efforts, such as a lack of conceptual understanding, a prevailing punitive mindset among law enforcement officers, and an absence of clear evaluation criteria. To address these challenges, the authors propose specific criteria focusing on early detection of criminal intent, timely intervention to prevent crime completion, and retrospective analysis of preventive measures' effectiveness. Conclusions. Implementing the proposed criteria consistently can reorient the operational-investigative units' approach toward a stronger emphasis on prevention. This shift is crucial for addressing the root causes of crime, reducing societal costs, and enhancing the overall effectiveness of law enforcement efforts in Kazakhstan.
Analisis Pembentukan dan Perubahan Makna Wasei Eigo pada Situs Jejaring Sosial Ameba Blog

Authors:
raw_author_name: Frida Philiyanti
raw_author_name: Dwi Astuti Retno Lestari

Abstract: This study aims to identify the formation, change of meaning, and types of wasei-eigo found in the Ameba blog. The underlying theories are Tsujimura's (2014: 150) Japanese word formation, Irwin's (2011: 143) compound word shortening theory, Chaer's (2013: 140) meaning change theory, and wasei-eigo types according to Shibasaki, et al (2007: 90). The method used is qualitative descriptive method. The data analysis technique applied is translational pairing. The base technique is the technique of sorting out the determining elements (PUP) with the advanced technique of comparative relationship to distinguish (HBB). The analysis yielded 14 wasei-eigo words in the fashion category of Ameba blog. The data consisted of 9 compounds, 3 words experienced shortening type compound truncation, 1-word experienced shortening type morpho-orthographic truncation, and 1-word experienced shortening type compound truncation and ellipsis middle truncation. In the change of meaning, 4 data experienced narrowing, 1 data experienced expansion, and 9 data experienced total change of meaning. Additionally, out of the total data, 5 data involved imizuregata, 4 data involved eigohyougenfuzaigata, and 5 data involved tanshukugata and eigohyougenfuzaigata types
Supporting the Development of Classroom Reading Corner Program at Madrasah Ibtidaiyah Muhammadiyah 01 Pekanbaru Title

Authors:
raw_author_name: Ramanda Rizky
raw_author_name: Syahdan Syahdan
raw_author_name: Suharni Suharni

Abstract: The habit of reading should be introduced to children at an early age for them to continue reading throughout their lives. A well-planned and facilitated program for habituating readers is therefore necessary. This Community Service activities aim to provide assistance for the development of the Class Reading Corner Program at Madrasah Ibtidaiyah Muhammadiyah 01 Pekanbaru. Following a review of the school's problems regarding the lack of reading corners, a limited number of children's reading books, and the lack of governance of class reading corners, these activities were carried out based on the results of an analysis of these problems. As part of this program, 48 sets of children's picture books were handed over, including mini bookshelves. The program also socialized development of reading corner program and made a simulation of making picture books involving 14 teachers, 1 administrative staff, and 1 headmaster. This program employed a direct observation and questionnaire for the evaluation. The observation showed that three classroom reading corners are present and in use at the school. A satisfaction level of 89.6% was obtained from activity participants after analyzing the questionnaire, an increase of 29.20% over that obtained prior to socialization and simulation. Furthermore, 93.75 % of the participants wanted a reading corner and 100% indicated that there was a need to enhance or improve its quality. The results from these studies suggest that this mentoring program has achieved a positive effect by raising awareness of the importance of increased reading proficiency in schools.
The Design of a C1 Document Data Extraction Application Using a Tesseract-Optical Character Recognition Engine

Authors:
raw_author_name: Bety Hayat Susanti
raw_author_name: None Mareta Wahyu Ardyani

Abstract: The 2019 election process used the Vote Counting Information System, also known as Sistem Informasi Penghitungan Suara (Situng), to provide transparency in the recapitulation process. The data displayed in Situng is from document C1 for 813,336 voting stations in Indonesia. The data collected from the C1 document is entered and uploaded into Situng by the officers of the Municipal General Election Commission (GEC). Since this process is performed by humans, it is not immune to errors. In the recapitulation process of the 2019 election results, there were 269 data entry errors, and the data entry process also did not run according to the specified target, resulting in delays. Furthermore, there were cases of C1 document modification, raising concerns about the data's authenticity. To avoid human errors and increase data entry speed, automatic data entry is a plausible option. The data entered are text data in image documents with the same template format, so that optical character recognition (OCR) can be used to read the text while improving image quality and alignment, resulting in a more accurate OCR reading area. In this study, we developed a C1 document data extraction application using the waterfall SDLC method, which has undergone a systematic and thorough process. The application was developed using Tesseract optical character recognition. Tesseract is an open-source OCR engine and command-line program that allows for the recognition of text characters within a digital image. The accuracy obtained by using this method is still not optimal as a substitute for Situng's data entry officer. To guarantee the integrity of the C1 document, we use the RSA-2048 digital signature scheme. The use of the Tesseract-OCR Engine for character recognition, combined with digital signature capabilities, provides a comprehensive solution to reduce the human error factor that can lead to miscalculations and inaccurate processes.
Development of an Early Warning System Using Social Media for Flood Disaster

Authors:
raw_author_name: Ruben Cornelius Siagian

Abstract: This research paper introduces an innovative prototype system that uses IoT technologies to monitor floodwater levels. Integration of an ultrasonic sensor, ESP8266 microcontroller, Arduino IDE, and the ThingSpeak platform aims to establish a robust flood monitoring solution. The paper provides a thorough exploration of the system's background, the problem it addresses, the methodology employed, and the obtained results, along with insights into future research directions. The study meticulously describes the design, implementation and programming code for data collection and transmission within the system. Through extensive field testing and meticulous data analysis, the paper evaluates the precision and effectiveness of the proposed flood monitoring solution. In particular, research underscores the advantages of IoT, emphasizing real-time data collection, logging, and analysis as essential components for efficient flood management. Additionally, the paper elucidates step-by-step instructions for configuring Telegram notifications through the ThingSpeak React app, enhancing the practical applicability of the developed system. The research effectively highlights the potential of IoT in flood monitoring, showcasing its superior accuracy and effectiveness compared to traditional methods. By demonstrating the feasibility and advantages of IoT in the context of flood monitoring, this study contributes valuable information, enriching existing knowledge, and paving the way for future advances in the field. Research encourages the continued exploration of advanced techniques to strengthen flood monitoring and management strategies. Ultimately, this work presents a comprehensive IoT-based prototype for floodwater monitoring, offering valuable information and fostering the promising role of IoT technologies in this critical domain.
A Novel Framework for Information Security During the SDLC Implementation Stage: A Systematic Literature Review

Authors:
raw_author_name: None Setiadi Yazid

Abstract: This research delves into the critical aspects of information security during the implementation stage of the Software Development Life Cycle (SDLC). By employing a systematic literature review, the study synthesizes findings from various digital repositories, including IEEE Xplore, ACM Digital Library, Scopus, and ScienceDirect, to outline a comprehensive framework addressing the implementation stage's unique security challenges. This research contributes to the field by proposing a novel assurance model for software development vendors that focuses on enhancing information security measures during the implementation stage. The study's findings reveal 12 key steps organizations can adopt to mitigate security risks and enhance information security measures during this critical phase. These steps provide actionable insights and strategies tailored to support security protocols effectively. The article concludes that by incorporating these steps, organizations can significantly improve their security posture, ensuring the integrity and reliability of the software development process, particularly during the implementation stage. This approach not only addresses immediate security concerns but also sets a precedent for future research and practice in secure software development, particularly in the critical implementation stage of the SDLC.
Investigating the Impact of ReLU and Sigmoid Activation Functions on Animal Classification Using CNN Models

Authors:
raw_author_name: None M Mesran
raw_author_name: None Sitti Rachmawati Yahya
raw_author_name: None Fifto Nugroho
raw_author_name: None Agus Perdana Windarto

Abstract: VGG16 is a convolutional neural network model used for image recognition. It is unique in that it only has 16 weighted layers, rather than relying on a large number of hyperparameters. It is considered as one of the best vision model architectures. This study compares the performance of ReLU (rectified linear unit) and sigmoid activation functions in CNN models for animal classification. To choose which model to use, we tested 2 state-of-the-art CNN architectures: the default VGG16 with the proposed method VGG16. A data set consisting of 2,000 images of five different animals was used. The results show that ReLU achieves higher classification accuracy than sigmoid. The model with ReLU on convolutional and fully connected layers achieved the highest accuracy of 97.56% on the test dataset. However, further experiments and considerations are needed to improve the results. Research aims to find better activation functions and identify factors that influence model performance. The data set consists of animal images collected from Kaggle, including cats, cows, elephants, horses, and sheep. It is divided into training and test sets (ratio 80:20). The CNN model has two convolution layers and two fully connected layers. ReLU and sigmoid activation functions with different learning rates are used. Evaluation metrics include precision, precision, recall, F1 score, and test cost. ReLU outperforms sigmoid in accuracy, precision, recall, and F1 score. However, other factors such as the size, complexity and parameters of the data set must be taken into account. This study emphasizes the importance of choosing the right activation function for better classification accuracy. ReLU is identified as effective in solving the vanish gradient problem. These findings can guide future research to improve CNN models in animal classification.
AUV Surfacing Control With Adversarial Attack Against DLaaS Framework

Authors:
raw_author_name: Tianze Zhang
raw_affiliation_string: Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong, China
raw_author_name: Yibin Li
raw_affiliation_string: Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong, China
raw_author_name: Lei Jia
raw_affiliation_string: Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong, China

Abstract: In this study, we consider surfacing control problems for the autonomous underwater vehicle in three-dimensional space under emergencies. Most model-based controllers cannot effectively solve these problems due to the unknown task environment model. Moreover, existing deep reinforcement learning (DRL) methods have some limitations, such as slow convergence or overestimation bias. For these purposes, we propose a model-free DRL algorithm based on the Deep Deterministic Policy Gradient within the paradigm of deep learning as a service (DLaaS). The algorithm combines existing expert episodes as demonstration and transitions from the interaction between the agent and task environment, which potentially reduce risk from adversarial attack. We propose a variable delay learning mechanism to improve the performance of the proposed algorithm. The simulation results show that our method can converge faster and has a more robust performance with adversarial attack than the existing DRL method under the premise of solving the AUV surfacing control tasks for safety.
Public and Private Clouds in Hands-on, Online Learning

Authors:
raw_author_name: Peng Li
raw_affiliation_string:  American Society for Engineering Education, 2018 2018; East Carolina University, Greenville, NC 27858; University

Abstract: Adoption of cloud computing is a clear trend in online learning.What types of cloud platforms are available?What are the pros and the cons of different cloud options?We will discuss cloud options for hands-on education, based on our experience with multiple cloud platforms.There are different ways of implementing cloud computing.A public cloud is owned and operated by an external service provider.Computing resources are allocated on a pay-per-usage basis.A private cloud is owned and managed by local institutions.Computing resources are provisioned to internal users on demand.Private clouds are highly customizable and may be adjusted to better meet the needs of local users.However, setting up a private cloud requires expertise and resources.Access to public clouds can be set up quickly but users possess less control.In a diversified online learning environment, multiple cloud platforms may be necessary.
The Design and Implementation of an Intelligent Letter Box

Authors:
raw_author_name: Sasan Haghani
raw_affiliation_string: Department of Electrical and Computer Engineering, University of the District of Columbia, Washington DC, 2008

Abstract: A major cost of transportation for the US postal services is collecting mail from blue collection boxes across the country, with their numbers steadily declining over the years, to save on fuel costs.This cost could be significantly curtailed if boxes that contain mail at collection times can be identified.This paper provides a detailed study and implementation of a smart mail detection and alerting system.The system detects if any mail is placed in the blue collection box and sends an alert to the local post office indicating whether the box should or should not be visited.
Research Experience for Secondary School Teachers on Renewable Energy: Design and Implementation of a Small Scale Solar Tracker

Authors:
raw_author_name: Rocio Alba-Flores
raw_affiliation_string: Georgia Southern University

Abstract: This paper describes the experiences gained during the first year implementation of a Research Experiences for Teachers (RET) in Renewable Energy (ENERGY) at Georgia Southern University (GSU).RET is a NSF grant program that supports the professional development for secondary school teachers with emphasis on hands-on laboratory research and experiences in STEM fields.The paper also refers to the teachers' experiences gained at the GSU Engineering Research Labs during the summer 2017.Participants in the RET program completed 280 hours (seven weeks) of training and research experience in renewable energy topics.About 50 hours were devoted to lectures and workshops, and the rest, about 230 hours, were research activities, collaborating in research teams with undergraduate and graduate students, and engineering professors.Participants also developed lessons for their courses that were delivered to their own students during the 2017-2018 school year.The lessons were directly related to the experiences that teachers gained in the summer.