Reviewerly/exHarmony huggingface dataset:
Pelatihan Internet Sebagai Media Informasi dan Komunikasi Untuk Meningkatkan Skill Keperawatan Siswa SMK

Citra Medika Sukoharjo Health Vocational School students live far from urban areas and the lack of attention from the local government in conducting outreach, guidance and internet training has made many students, especially those living in rural areas, less aware of the importance of using the internet in a positive way. Internet training as a medium of information and communication to improve nursing skills to be able to maximize the function of healthy information for good communication facilities. The development of technology, especially the internet has brought many changes. Thanks to the help of the internet, all work becomes light. Therefore training and guidance activities in the use of the internet really need to be done to remind and provide awareness for students how to use the internet in a wise way so that in the future their academic abilities and knowledge of the world of education and information will increase. This training will be explained in the form of a presentation using power point. The implementation of this training and guidance is expected that nursing students, especially at this school, are able to use the internet wisely and prudently in order to support efforts to develop civilized human resources who have the ability to compete globally, not only able to compete intellectually but also have good manners and behavior.
Calculation of Mineralogical and Chemical Weathering Indices (Xd, MIA and CIA) and their Significance in Soils at Selected Areas in Northern Iraq

This study is conducted using data analysis of minerals gained from X-ray diffraction (XRD) as well as by using the data of chemical analysis of the main elements measured by the X-ray Fluorescence (XRF) at selected areas in northern Iraq Thirty samples (twenty soil and ten rock samples) are collected distributed through five regions (Qayarah, Hamam Alil, Tel kaif, Duhok, and Zakho) with four depths and two rock samples for each section in order to calculate the index of weathering mineral (Xd) and mineralogy index of alteration (MIA) as well as chemical index of alteration (CIA). The aim is to measure the amount of decomposition relative to the resistant minerals in soils and rocks, as well as to assess the amount and capability of these soils as evidence of the degree of development, and then the possibility of classification depending on the degree of resistance to weathering processes. The results show transaction weathering in these areas varying in degree and ability of these soils in resisting weathering processes at different locations and the nature of the original material. The study shows that Zakho soil samples have a high degree of weathering; on the contrary, Qayarah soil samples have a very low degree of weathering due to different topographical and climatic conditions of these two regions. The remaining areas are intermediate in the degree of weathering, considering that these areas have received variable amounts of rain precipitation ranging between 1,000 mm / year as in Zakho and 250 mm / year in Qayarah area. The topography of these areas is different being high in Zakho and low in Qayarah area
Web Search Training and Query Formulation Behaviour of Undergraduates of Kano State University of Science and Technology (KUST) Wudil, Kano State, Nigeria

The Web is predominant source of information upon which most university students depend for accomplishing their academic tasks. This study investigated the influence of web search training program on query formulation behaviour of undergraduates of Kano State University of Science and Technology (KUST), Wudil, Kano State, Nigeria. The study was set to answer two research questions and tested a hypothesis. Quasi-experimental design of the pretest and posttest type was used for the study. All 20,679 undergraduates of KUST made up the target population. Convenience sampling technique was used to recruit only 35 students, who participated in a six-week training program and lab sessions. A structured and validated questionnaire was used for data collection at both pretest and posttest levels. Cronbach’s alpha reliability coefficient for the constructs ranged 0.78 to 0.88. Two adapted search task tests were used to assess students’ query formulation behaviour on the web before and after the training. Data were analyzed with descriptive statistics and t-test. Findings revealed that web search training had significant effect on the query formulation behaviour of participants (t(34) = 17.680; p &lt;0.05,η2= 0.857). The study concluded that web search training is essential for all undergraduate students of KUST Wudil to enable them to develop appropriate web search query formulation behaviour and also accomplish their academic search tasks. The study recommended that academic librarians should include practical web search sessions in their use of library classes for freshmen. Keywords: Boolean logic, Query formulation behavior, Undergraduate students, Web Searching, Web search training
Constructing a Precise Method to Control Non-Linear Systems Employing Special Functions and Machine Learning

This paper is about finding the best way to control certain types of equations that describe heat and diffusion using methods that are not exact but close to the best solution. A new way to control things better is suggested using patterns we've seen before and computer learning. By employing the data gathered from the EEFs are computed using the Karhunen-Loève decompose in the PDE computer. The EEFs are used to convert the PDE system into a high-order ODE system. A smaller model (ROM) that may depict the primary behavior of the PDE subsystem is created using the SP approach. This facilitates understanding of the system. In order to reduce its size, a more basic model (ROM) that demonstrates the primary motions of the PDE system is created using the SP approach. Next, the optimal controller for the ROM is designed using the HJB technique. This ensures that the high-order ODE system is stable using the SP theory. By splitting the best way to control something into two sections, we can solve a math problem to figure out the first part and come up with a new equation for the second part. Third, a method is suggested for updating and controlling based on small improvements to solve a specific equation, and it has been proven to work effectively. Moreover, we use a technique called the NN approach to estimate the cost function. Finally, the simulation results demonstrate the effectiveness of the proposed optimum control approach when applied to a diffusion-reaction process using a unique spatially component.
A Novel Chaos-Based Encryption Algorithm for Secure Communication Systems

Data transmission security is of the utmost importance in many fields and industries, including healthcare, finance, military activities, and more. By capitalizing on the intrinsic unpredictability of chaotic systems, Dynamic Chaos Cipher overcomes the shortcomings of current encryption technologies, rendering it an essential answer for safeguarding contemporary communication. Modern cyber threats are becoming increasingly sophisticated, making it difficult for conventional encryption approaches to keep ahead. In an effort to address these issues and provide resilience against ever-changing attack vectors, Dynamic Chaos Cipher introduces dynamic parameters rooted in chaos theory. The algorithm is more secure because chaotic systems are inherently complicated and unpredictable. The Dynamic Chaos Cipher-Based Encryption Algorithm (DCC-EA) described in this paper uses a novel key generation technique based on chaos that adapts in real-time over conversations. The approach improves the nonlinearity and unpredictability necessary for secure encryption by generating pseudo-random sequences using chaotic maps with carefully selected initial conditions. To prevent attacks that target static cryptographic keys, the key is dynamic. Among the many fields that can benefit from DCC-EA's adaptability is the transfer of sensitive medical data, financial transactions, and military communications. Its adaptability to changing parameters makes it a good fit for mission-critical systems in the real world and guarantees strong security for a wide range of uses. Data confidentiality and integrity are well maintained by DCC-EA, according to extensive simulation analyses. The algorithm's robustness and effectiveness in comparison to more conventional encryption approaches are shown through extensive testing against a wide range of attack scenarios. Results from the simulation show that DCC-EA can successfully secure critical data in ever-changing communication settings.
Increasing Students’ Pronunciation Mastery Through Spelling Words Strategy

This study aimed to improve students’ mastery of pronunciation through words spelling strategies in the fourth grade of SD Inpres Mappu in Mamuju. This research was a classroom action research (CAR) conducted in two cycles, namely, cycle one and cycle 2. Each cycle was carried out four times. There are four steps in this research; planning, action, observation, and reflection. The data in this study used quantitative (test) as the primary data and qualitative (field notes, recording, and documentation) as supporting data. The subjects in this study were 15 students in grade IV SD Inpres Mappu in Mamuju. The results showed that the use of the Words Spelling Strategy succeeded in improving the pronunciation master of the fourth-grade students of SD Inpres Mappu. It can be seen from the increased percentage of student learning outcomes from cycle I to cycle II, with an average value of 83.6. Therefore, it can be conducted that using the Words Spelling Strategy can improve student learning outcomes in mastering pronunciation.
MULTI-CLASSIFIERS SYSTEM FOR CREDIT CARD FRAUD DETECTION

The business of issuing credit cards is extremely important to the functioning of the economy since it facilitates the use of a straightforward method of payment in a variety of contexts, such as online banking, commercial transactions, and financial dealings. Nonetheless, using credit cards is also associated with fraudulent activity and non-payment, both of which constitute a considerable danger to customers and the business as a whole. Detecting and preventing fraudulent activity involving credit cards is complex and time-consuming because of the ever-changing nature of fraudulent and expected behavior and the unequal class label and overlapping of class instances inside the data sets. The class imbalance in credit card data sets poses a significant obstacle in detecting fraud. Biased models may result from a substantially lower number of fraudulent cases compared to non-fraudulent cases. The study underlines the influence of oversampling and under-sampling techniques on single-classifier methods and stresses the significance of selecting an appropriate classifier algorithm. The results indicate that multi-classifier methods, particularly COPOD + RFC and IForest + RFC, can substantially improve credit card fraud detection compared to single-classifier methods. These results demonstrate the potential advantages of integrating multiple unsupervised and supervised learning algorithms to improve credit card fraud detection while decreasing false positives. Overall, the study emphasizes the significance of employing a combination of machine learning techniques to resolve the difficulties of credit card fraud detection. The proposed method can assist credit card companies in accurately and efficiently identifying fraudulent activities, thereby reducing the risk of financial loss and enhancing customer confidence.
Mitigation of Rowhammer Attack on DDR4 Memory: A Novel Multi-Table Frequent Element Algorithm Based Approach

As Rowhammer attacks have become more and more of a threat to modern computer systems using DRAM as main memory, defenses against it have to improve to match. Rowhammer attacks cause unidentifiable bit flips within DRAM units by using flaws in DRAM's electrical characteristics, and the threat of Rowhammer increases as DRAM continues to scale down to have higher density. This has led to many methods of defense to be developed using many means to defend DRAM including Graphene [1], a space efficient, low cost algorithm to that identifies frequent elements from incoming data streams to prevent Rowhammer bit flips. We propose an improved version of the Graphene defense method, Multi-Table Graphene (MT-Graphene). MT-Graphene uses the same data stream frequent element identification that Graphene uses, but runs multiple of the algorithm throughout smaller sections of the DRAM unit, seeing a improvement of 74% less Rowhammer bit flips when compared to Graphene using two tables, and further increases in security when more tables are added.
Application The Quantum Learning Method Using Simulation Media with The TANDUR Strategy to Improve Student Learning Outcomes

Quantum Learning was a method that was capable of sharpening understanding and the ability to think actively and creatively of students in the learning process. In this study, we tried to implement the quantum learning method as described above, which had been shown to improve learning outcomes in various subjects across various levels, with the help of simulation media, optimized with the TANDUR strategy. This study aimed to determine whether there was a significant difference in students' learning outcomes improvement by applying the Quantum Learning method using simulation media with the TANDUR strategy and by applying conventional learning methods at SMP N 3 Bengkulu City. This research was a quasi-experimental design. The population in this study was students of class VIII SMP Negeri 3 Bengkulu City. The selection of the research sample used the Random Sampling technique, which consisted of 38 students in class VIII.2 as the experimental class and 38 students in class VIII.3 as the control class. The data collection technique used the learning achievement test instrument on the concept of light and student response questionnaires. Data analysis used two independent samples t-test. The results showed that the average post-test score of the experimental class differed significantly from the average post-test score of the control class with tcount 4.032 &gt; ttable 1.992 at a significance level of 95%. Based on the results of the study, it could be concluded that: 1) there were differences in improving student learning outcomes between classes taught by applying the Quantum Learning method and classes with conventional learning at SMP N 3 Bengkulu City; 2) there was a good response from students with an average of 82% towards the application of the Quantum Learning method using simulation media with the TANDUR strategy.
An enhanced digital image watermarking technique using DWT-HD-SVD and deep convolutional neural network

This paper proposes a novel image watermarking model, which combines discrete wavelet transform (DWT), Hessenberg decomposition (HD), singular value decomposition (SVD)-based deep convolutional neural networks (D-CNN) technique to explore the subjective and objective quality of the images. Initially, the source and cover image are preprocessed using random sampling techniques. During the process of embedding a watermark image, the cover image is decomposed into a number of sub-bands using the DWT process and the resulting coefficients are fed into the HD process. In continuation to it, the source image is operated on the SVD simultaneously and finally, the cover image is embedded into the source image by the attack-defending process. The probability of data loss during the watermarking extraction process and this issue is postulated by the D-CNN technique that explores the denoising process on the extracted watermarked images. The experimental results show that the proposed method has a good trade-off between robustness and invisibility even for the watermarks with multiple sizes.
PRECURSOR-BASED EARTHQUAKE PREDICTION: WISHFUL THINKING OR REAL POSSIBILITY?

Scientists attitude towards the delicate precursor-based earthquake prediction subject was widely oscillating during the last half century, from optimism to deep pessimism according to milestone seismic events, claims of successful predictions and published expert debate results. Despite the current official/mainstream opinion according to which the precursor-based earthquake prediction is impossible in principle, new ideas and claimed positive results emerged in the last few decades allowing potentially paradigm-shifting new research strategies to be envisaged and followed. Such a strategy is proposed here based on the principles of 1) coupled and interacting geospheres, 2) uniqueness of the seismic structures, hence of their precursory fingerprints, and 3) non-equivalence of Earth surface measuring sites from the perspective of signal-reception capability. Such a strategy aims at discovering the particular precursory fingerprint of individual seismogenic structures instead of looking for universally valid precursory signals. The precursory fingerprint of a particular seismogenic structure is the assemblage of a number of pre-seismic signals of physical, chemical and biological nature detectable in advance of impending large-magnitude earthquakes using a matrix of high-accuracy sensors emplaced at pre-selected “sensitive” locations at Earth surface and on Earth-orbiting satellites. It has a pattern component (configuration of the above-threshold values of the monitored parameters) and a time component (sequence, succession and lead time of emergence of the anomalous signal parameters). Due to its complex nature, the assemblage of detected precursory signals has to be processed and evaluated by pattern recognition algorithms of Artificial Intelligence systems and validated by human experts before final conclusions to be drawn. Due to its particular setting in Europe’s geodynamically most active area, and its long-known seismic history including recurrent high-magnitude destructive events, the Vrancea seismic nest in Romania appears as an excellent experimental target for the implementation of a novel, concept-based long-term research strategy in the field of earthquake prediction.
INNOVATIVE TECHNOLOGIES IN EDUCATION

This article discusses the priority tasks of transferring knowledge to a person in the process of innovative education, developing his skills and competencies, developing his worldview, meeting his needs, as well as discovering and developing additional abilities. The main attention is paid to such pedagogical aspects as the purpose of education (why teach and who to teach?); educational content (what to teach?); forms of educational organization (how to teach?); and educational methods and tools (on what basis of teaching?). At the same time, the meaning of such expressions as “interactive methods,” “innovative educational technologies,” “advanced pedagogical technologies,” “progressive pedagogical technology,” and “modern educational technologies,” which are widely used in the educational process, is explained, as well as the feasibility of using innovative pedagogical technologies in productive education. In addition, the importance of modern technologies in modern education, their role in students’ acquisition of knowledge, independent study of topics, analysis of situations, conclusions, and decision-making are discussed. Along with this, special attention is paid to state documents that clearly indicate the tasks for the implementation of educational goals. The opinions of famous theorists and experienced teaching practitioners about modern pedagogical technologies and teaching methods are compared and analyzed.
A Study on Students’ Difficulties in Learning Vocabulary at Grade VIII of MTs Negeri in Padangsidimpuan

This study investigated the difficulties faced by eighth-grade students at MTsN Padangsidimpuan in learning English vocabulary. The research revealed that students encountered various challenges, including Pronunciation, Meaning, Spelling, Memorization, Differentiation and Sentence integration. Additionally, the study identified several factors contributing to these difficulties: Lack of engagement and Limited exposure. To address these issues, the research explored pedagogical strategies used by teachers to help students overcome their difficulties. These strategies included Vocabulary tasks, Memorization techniques, Differentiated learning, Active practice, Engaging methods, Dictionary skills. This research highlights the importance of understanding student difficulties in vocabulary learning and implementing effective pedagogical approaches to overcome them. The identified challenges, contributing factors, and teacher strategies provide valuable insights for improving English vocabulary instruction in the context of MTsN Padangsidimpuan and beyond.
Analysing Educators’ Role in Digital Education &amp; it’s Psychological Outcomes

The roles of educators in today's digital classrooms extend far beyond the mere delivery of content to include the molding of students' mental health and worldviews as well. Educators may better equip their students to succeed in today's increasingly digital classrooms by implementing successful digital teaching approaches, fostering digital literacy, and addressing the psychological consequences of digital learning. Educators' behaviors and techniques in the digital classroom have substantial psychological effects on students. Considering the effects of digital education and teachers' roles in molding students' mental health and educational experiences is crucial as technology becomes more pervasive in the classroom. Teachers' responsibilities have radically changed with the advent of digital education, which has opened up new possibilities and presented new obstacles for how pupils acquire and apply knowledge. The complex relationship between teachers' activities and the emotional consequences their students report is the focus of this research of the digital education landscape. Educators are responsible for a wide range of activities, including lesson planning, technology implementation, student-centered instruction, the promotion of digital literacy, and the facilitation of learning. In addition, the role of teachers in digital education and its impact on students' motivation, digital literacy, and well-being are investigated. It also discusses issues such as technical gaps, technostress, and striking a healthy balance between technology and non-technological activities that teachers face. This analysis aims to shed light on the expanding field of digital education and its tremendous impact on students' psychological development and overall educational experience by focusing on the educator's role and its psychological implications.
Preserving Privacy in Distributed LASSO

In this paper, we extend the Soft-Thresholding with Exact Line search Algorithm (STELA) to solve the LASSO problem in a fully decentralized manner, where each agent solves its local minimization problem, and cooperates only with its neighbors to update the local solution. Moreover, the privacy of the local data is maintained during the communication of agents via the privacy-preserving average consensus (PPAC) approach which avoids revealing local information from other agents as well as potential eavesdroppers. We examine the proposed algorithm with synthetic data. Simulation results show that with a similar privacy level, the proposed algorithm has a faster convergence speed and better accuracy compared to the state-of-the-art privacy-preserving Primal-Dual Method of Multipliers (p-PDMM) algorithm.