Reviewerly/exHarmony huggingface dataset:
Impact of Blockchain Technology: Benefits and Security Risk and Threats

The accelerated dynamics of technological evolution has led to a reconfiguration of the security environment by addressing new vulnerabilities, risks and threats generated by the migration of risk-generating entities into cyberspace.These risks are also enhanced by the interest shown by criminal entities in technologies such as Blockchain, which are proving to be attractive in terms of existing functionalities.These changes in the security environment and, by extension, in the international economic environment, are challenges that require a proactive, sustainable and integrated approach.This article aims to analyze the impact of blockchain technology on society in terms of both the benefits and risks of exploiting this technology.
PERSEPSI MAHASISWA UNIVERSITAS TERBUKA BOGOR TERHADAP TREN TUWEB SEBAGAI LAYANAN BELAJAR DARING

This study aims to analyze the perception of UPBJJ-UT Bogor students towards the implementation of webinar tutorial learning (tuweb) as a substitute for face-to-face tutorial services (TTM) during the Covid-19 pandemic. The sample in this study was selected by random sampling technique and involved 400 student respondents. Research data were collected using an electronic questionnaire and analyzed using descriptive statistical analysis to describe students' perceptions of readiness and implementation during tuweb learning. The results showed that students had a good perception of the implementation of tuweb, including accessibility, device ownership, ability to use technology, ease of obtaining materials, ease of learning materials, interactivity, learning independence, and satisfaction with tutor abilities.
Exploring Sensor Modalities to Capture User Behaviors for Reading Detection

Accurately describing user behaviors with appropriate sensors is always important when developing computing cost-effective systems. This paper employs datasets recorded for fine-grained reading detection using the J!NS MEME, an eye-wear device with electrooculography (EOG), accelerometer, and gyroscope sensors. We generate models for all possible combinations of the three sensors and employ self-supervised learning and supervised learning in order to gain an understanding of optimal sensor settings. The results show that only the EOG sensor performs roughly as well as the best performing combination of other sensors. This gives an insight into selecting the appropriate sensors for fine-grained reading detection, enabling cost-effective computation.
Using Multi-feature Embedding towards Accurate Knowledge Tracing

Knowledge tracing is a crucial task in intelligent tutoring systems.Aiming at the shortcomings of traditional knowledge tracing technology such as low prediction accuracy, overfitting and low utilization of multi-features, this paper proposes a knowledge tracing model SRGCA-M using multi-feature embedding with stacked residual GRU network.Compared with the traditional methods that only use the historical record of answering exercises, our approach utilizes a variety of features in the learning process of students to deep characterize students' learning.We increase the layers number of GRU network to expand the capacity of sequence learning and use residual connections to solve the problems of network degradation and vanishing gradient.We use the auto-encoder to solve the problem that the cross-feature encoding will rapidly increase the dimension of the input data.Comprehensive experimental results demonstrate that compared with various advanced techniques, our approach can not only achieve better performance of tracking knowledge changes of students but also fully utilize multi-feature information of students in the learning process.
Identifying Risks for Collaborative Systems during Requirements Engineering: An Ontology-Based Approach

A risk is an undesirable event that can result in mishaps if not identified early on during requirements engineering adequately.However, identifying risks can be challenging, and requirements engineers may not always be aware if risks are ignored.In this paper, we present Murphy -a framework for performing risk analysis.Murphy adopts the Reference Model, in which requirements are supposed to be met not by the projected software system behavior alone but through collaboration between the system and events occurring in its environment, hence the term Collaborative System.Murphy provides risk analysis facilities that include an activity-oriented ontology for carrying out risk analysis by systematically identifying risky activities in the system and in the environment, thereby obtaining a Risk Analysis Graph (RAG) and towards devising risk mitigation strategies later.In order to see both the strengths and weaknesses of Murphy, we experimented on developing a smartphone app involving a group of Ph.D. and senior-level graduate students -one group using Murphy and the other not using Murphy.Our observation, we feel, shows that the risks identified by the group using Murphy were able to identify more critical risks and those risks were comprehensive and relevant as.well.The results also showed that incorporating risk mitigation strategies for the risks identified can indeed help avoid them to some extent.
Development of Algorithm for Non-Linear Optimization Using Sequential Quadratic Programming (SQP) Method

This paper describes a development of an algorithm for nonlinear optimization using sequential quadratic programming (SQP) method. The computation is performed through a number of steps. The improvement of the performance is achieved and compared to a version with line search.&#x0D; هدفت هذه الورقة لتوضيح خطوات تطور خوارزمية إستناداً على الطريقة التقريبة للمعادلات التربيعية (SQP)حيت تم إنشاء خوارزمية لحساب القيم التفريبية لدالة الهدف وفق قيود محددة. ثم تم تنفيذ هذا البرامج لحل نماذج مختلفة من المعادلات الخطية والغير خطية.
دافعية التعلم وعلاقتها بالتوافق الدراسي لتلاميذ(الحلقة الأخيرة)مرحلة التعليم الأساسي بمحلية شرق النيل بالخرطوم

This study aims to investigate the relationship between learning motivation and scholastic adjustment among basic school pupils in East Nile locality. The study also attempts to identify the differences in learning motivation among pupils according to gender, class and pupils' parental educational level. To achieve these aims, the researchers applied the descriptive-correlation method. A Stratified random sample of 570 pupils was selected from different educational sectors in East Nile Locality. Tools of data collection consisted of the following: a preliminary information form, a learning motivation scale in addition to scholastic adjustment scale for basic school pupils. The Statistical Package for Social Sciences (SPSS) has been used to analyze the data by applying the following statistical tests: Pearson correlation coefficient, t-test, Cronbach’s alpha equation and Spearman correlation coefficient. The study arrived at the following results: the pupils’ learning motivation of East-Nile Locality is statistically above the average; there is a significant positive correlation between learning motivation and scholastic adjustment among basic school pupils of East-Nile Locality; there is a positive correlation coefficient between learning motivation and pupils’ fathers’ education;. there is no statistically significant correlation between learning motivation with pupils’ mothers’ educational level; there is no statistically significant difference in learning motivation according to pupils’ class (Seventh-Eight); no statistically significant differences in learning motivation according to pupils’ gender (male-female.mm
AIWareK: Compiling PyTorch Model for AI Processor Using MLIR Framework

Deep learning compiler becomes necessary with the active research on AI hardware. This work compiles PyTorch models into target hardware codes using MLIR framework. The compiler first constructs a graph from the PyTorch model using TorchScript tracing. To construct the graph, our domain-specific parser generates an abstract syntax tree using tokens generated from the lexer. Then, the graph IR (GIR) is built and lowered into the kernel IR (KIR) and the processor IR (PIR) in MLIR framework. PIR becomes the input of the backed compiler that generates target machine codes. Experimental result shows that AIWareK compiled ResNet18 in 7.67 seconds, yielding 1.16e-03 mean absolute error.
ArtBrain-K: AI Processor based-on 5-PetaFLOPS AI Server System

We developed ArtBrain-K, an artificial intelligence server system with a performance of 5 PetaFLOPS per rack that can have a small form factor with low power, 2400W based on a proprietary artificial intelligence processor with 40 TeraFLOPS performance, and 15W power consumption. It consists of 8 artificial intelligence compute nodes with a performance of 590 TeraFLOPS and 300W power consumption which loaded with 20 ABrain-S NPU boards based on the artificial intelligence processor. Also, we developed AIWareRT, a software development environment for independent artificial intelligence processor. Compared to the existing GPU system, the performance is 3 times higher and the power efficiency is 7 times higher. It has been applied to the next-generation airport automatic immigration system and image recognition-based security system, and it can be used in fields that require enormous computing resources for data processing and learning, such as a huge neural network such as a transformer-based artificial intelligence algorithm.
New and Improved Constructions for Partially Equivocable Public Key Encryption

Non-committing encryption (NCE) is an advanced form of public-key encryption which guarantees the security of a Multi-Party Computation (MPC) protocol in the presence of an adaptive adversary. Brakerski et al. (TCC 2020) recently proposed an intermediate notion, termed Packed Encryption with Partial Equivocality (PEPE), which implies NCE and preserves the ciphertext rate (up to a constant factor). In this work, we propose three new constructions of rate-1 PEPE based on standard assumptions. In particular, we obtain the first constant ciphertext-rate NCE construction from the LWE assumption with polynomial modulus, and from the Subgroup Decision assumption. We also propose an alternative DDH-based construction with guaranteed polynomial running time.
Algoritma Backpropagation dalam Akurasi Memprediksi Kemunculan Titik Api (Hotspot) pada Wilayah Kerja Dinas Kehutanan

Forest and land fires are an annual disaster issue in Indonesia. The forest area in West Sumatra is ± 2,286,883.10 Ha and 27% or an more than 630,695 Ha of forest area categorized as critical land that has the potential to burn and be damaged. Controlling for forest and land fires in West Sumatra Province was task for Forestry Departement, part of Sumatera Barat Government. One of is task was to reduce the rate of forest destruction. Forest and land fires are an annual disaster issue in Indonesia. The forest area in West Sumatra is ± 2,286,883.10 Ha and 27% or an more than 630,695 Ha of forest area categorized as critical land that has the potential to burn and be damaged. Controlling for forest and land fires in West Sumatra Province was task for Forestry Departement, part of Sumatera Barat Government. One of is task was to reduce the rate of forest destruction. Apart from to extinguishing forest fires directly at the hotspots, preventive action are needed to reduce the possibility of forest and land fires, and one of it is by predicting the possibility hotspots in the future. One of the methods used to predict the possibility hotspots is the use of artificial neural network Backpropagation, this is because Backpropagation has the ability to learn from existing data patterns to calculate the possibility of future events. Data of hotspots that have happened previously and several supporting variables such as air temperature, humidity, rainfall and wind speed, were analyzed and grouped as the basis for the formation of an artificial neural network and for further data training. This learning is done by testing several different network architectures. The results obtained from these tests are the Performance and MSE (Mean Squared Error) values for each network architecture. The test results for each architecture will be compared to determine the best architecture that produces the most accurate predictive value and the smallest MSE. The results of this prediction will later be used as one of the considerations for the Forestry Departement for planning forest and land fire control activities in their area.
Consumer Use of E-Banking in Iraq: Security Breaches and Offered Solution

After the software revolution in the last decades, the field of information technology had a tremendous evolution that made many organizations reach the best benefits from this evolution in technologies. The banking sector evolved their old system from ordinary system to the online system. The term E-banking appears to cover almost all bank operations such as money transactions, account management, instant reports, instant notifications. E-banking offers several advantages to clients, but this opens many challenges and motivates unauthorized parties to focus on creating methods and exploiting weaknesses to attack and steal critical information that belongs to the banking system or clients. Iraqi banks recently adopted E-banking serves and made them available to all their clients. However, this shift in approach leaves many clients vulnerable to cyber-attacks. This paper presents an analytical study on Iraqi clients using E-banking as a service using real case studies. Many researchers prevent these threats by introducing novel methods to support cybersecurity specialists. This paper covers related work and the most common terms involving E-banking. It also covers the risks involved in E-banking, most common attacks, and modern security methods to prevent attacks.
IMPROVING AND DELIVERING RELEVANT WEB CONTENT USING WEB CACHING

Web caching is as important as it has ever been.Web caching technology has been widely used to enhance the performance of the web infrastructure and reduce the user-perceived network latencies.Proxy caching is a Web caching technique that aims to serve users.Web requests from one or a network of proxies located between the client and the servers hosting the original copies of the requested objects.Web caching was developed for two primary reasons: to cut back the load on web servers and to enhance the net user's experience while browsing the web.Prefetching techniques are used to boost processor's execution performance and faster fetch operations.This paper presents different approaches for improving the techniques to deliver relevant web content and an analysed study of prefetching techniques and various databases employed by caching servers and different browsers and discusses the techniques to reinforce web caching, discusses caching databases also the intended impacts of web caching and related performance measures, and focuses on server caching approaches that use a single cache to serve multiple users which is the Content Delivery Network (CDN) caching, object caching, and opcode caching and analysing the behaviour of various browsers associated with caching.
EXTRACURRICULAR WORK AS ONE OF THE WAYS TO FORM THE EDUCATIONAL SPACE OF THE UNIVERSITY

5 (13.00.04), 5.8.6 (13.00.04), 5.8.7)
Design of Leaf Detection Application using Deep Learning Convolutional Neural Network (CNN) Case Study Lambosir (Blok Leuweung Buah) Mountain Ciremai National Park

The Leuweung Buah Lambosir area of Mount Ciremai National Park is included in the rehabilitation zone, the plant diversity index in Lambosir is in the medium category.Increased knowledge and skills regarding the introduction of plant species for officers in Mount Ciremai National Park is often carried out, but for some officers there are some difficulties in identifying plants quickly and accurately.Deep learning is a branch of machine learning (ML) that uses deep neural networks to solve problems in the ML domain.This study aims to create a leaf detection application using a deep learning Convolutional Neural Network (CNN) approach.The types of leaves used in this study were 6 types of leaves including Sonokeling (Dalbergia latifolia Roxb.), Kuray (Trema orientalis), Bungur (Lagerstroemia sp) , Kibeusi (Rhodamnia cinerea), Guava Rivet (Syzygium densiflorum), and Huni (Antidesma Bunius).Tests were carried out with a total of 600 images: 400 images as training data and 200 images as testing data.Testing of each object produces an accuracy rate above 80%.
Semantic Similarity Analysis for Entity Set Expansion

Grouping objects into a common, initially unknown, category underlies several important tasks, such as query suggestion or automatic lexicon generation. However, while coming up with more things “of the same kind” is easy for humans, it is not trivial for Artificial Intelligence. This task is commonly known as the Entity Set Expansion (ESE) problem, and has been studied in different branches of AI and NLP. In this paper, we review different similarity metrics and techniques that could be applied to the ESE problem. Moreover, we decompose the problem into phases and demonstrate how to use several approaches together. In particular, we combine semantic similarity metrics with Meta Path algorithm for knowledge graphs. We discuss the results and show that the presented setting can be reused in further research into hybrid approaches to the ESE problem.
Program Gerakan Literasi Sekolah di SD Negeri Sidomulyo 2 Demak Semester Ganjil Tahun 2021/2022

The purpose of this study was to describe the implementation of GLS at SDN Sidomulyo 2 Demak. The research was conducted at SDN Sidomulyo 2 Demak, in class III and IV with 10 students. This research uses a descriptive qualitative method. The research subjects were principals, teachers, students grades III and IV. Data collection techniques using data triangulation, namely questionnaires, interviews and documentation. The results showed the GLS at SDN Sidomulyo 2 Demak was running well, it was known from the observations made in grades I to VI and the distribution of questionnaires in grades III and IV. GLS at SDN Sidomulyo 2 Demak has good with average score of 80.00%, for facilities and infrastructure has been used very well with a score 85.00% for participation of students in reading habituation activities is very good with a score 85.10%. In the habit of reading 15 minutes before learning at this time in the habituation stage. Teachers still take part in GLS implementation activities. Based on the results of this study, the conclusion are the success of GLS activities can be through reading activities as well as facilities and infrastructure that can foster student interest in the process of habituation of 15 minutes of reading before learning.
KARAKTER SISWA DALAM LITERASI RELIGIUS

The character of children or students in religious literacy is described in this study. This research attempts to shape students' characters in order to help them become more religious and to develop their linguistic abilities. The Qualitative Method was used to acquire the data for this study. The findings of this study indicate a positive effects on the character development of students. To ensure that students' learning processes are supported, literacy implementation must be done in a supportive environment. It is well known that students' character can comprehend what has been done and what would be done after using reading literacy. The quantity of kids who are uninterested in reading is the study's main barrier.
Corrigendum: The link between English foreign language teacher's professional identity and their critical thinking that leads to teacher's success in the Chinese context: Leaders motivational language as a moderator

The original version of this article has been updated.In the published article, there was a mistake in the Funding statement. The funding statement for the Key Development Project of the Department of Science and Technology was displayed as "2015CBd051". The correct statement is "Key Development Project of Department of Science and Technology (2015C03Bd051).'' Template continues on the next page  Corrigendum: The link between English foreign language teacher's professional identity and their critical thinking that leads to teacher's success in the Chinese context: Leaders motivational language as a moderator Corrigendum on: Ding F, Liu X, Amin Abdalla A, Latif Khan M and Akram F (2022) The link between English foreign language teacher's professional identity and their critical thinking that leads to teacher's success in the Chinese context: Leaders motivational language as a moderator. Front. Psychol. 13:983215. doi: 10.3389/fpsyg.2022.983215In the published article, there was an error in affiliation(s) [2]
KINDLE DIRECT PUBLISHING AND SELF-PUBLISHING AS A MECHANISM FOR RECOGNIZING THE WRITINGS OF YOUNG AUTHORS

Self-publishing is the process of publishing a work without the support of a traditional publisher.It is particularly driven by digital technologies, which have the presence of specialized applications, both expensive and free, such as Kindle Direct Publishing, leading unknown authors and beginners to reach their place in the publishing market.Therefore, the research has as its general objective the experimentation of the self-publishing process and as specific objectives: (i) to produce a fictional dystopian fantasy literary work, aimed at a young audience, (ii) to publish and disseminate these writings through the website Kindle Direct Publishing, (iii) to didacticize the fictional work in the context of the Portuguese Language classroom of the 3rd grade of High School at Escola Sesi Anísio Teixeira -Vitória da Conquista/BA and (iv) to analyze the impacts caused by the practice of selfpublishing in the social and financial areas.The methodology is qualitative and takes on an exploratory tone, being classified as action research, in view of the experimentation of the Kindle Direct Publishing website through the publication of an authorial dystopian fantasy work, its application and didacticization in the school environment.and the analysis of data subordinated to the movement exerted by self-publishing.Therefore, it is expected that authors and readers of this and new generations can enter and understand selfpublishing as an accessible, dynamic and lasting class.
AN ANALYSIS OF AFFECTIVE MEANING IN TOURISM ADVERTISEMENT

The criteria of affective meaning can be named the expression of the language user in describing the object being discussed. In this case, the aims are to provide an overview of the use of affective meaning in tourism advertisements in West Sumatra. This study used a descriptive method, which provided a description of what is in tourism advertisements. The data was taken by purposive sampling from the last two years of Tourism in West Sumatera with 17 advertisements. Note-taking and observation sheets were used to collect the data and analyzed based on each category of affective meaning. The result showed that there were several combinations of language functions in producing affective meaning, namely expressive, directive, and aesthetic functions. The affective meaning in these advertisements is intended to give an impression that is influencing and attracting the readers’ attention to the object being discussed. Last, there was no emotional affective meaning function has been found.