Reviewerly/exHarmony huggingface dataset:
Digital Content Verification Using Hyperledger BESU

One of the greatest current social challenges is the certification of digital content to guarantee its veracity and authenticity, and the possibilities offered by distributed ledger technologies thanks to the properties of the blockchain in terms of security, immutability, traceability and transparency provide a specific framework for this. This work presents the design of a prototype model within the Ethereum BESU network that can be scalable and interoperable with other DLTs. We have, therefore, studied both the regulatory and technological framework to design a tool that is capable of certifying digital content. In this work, we will only focus on the technological aspects according to the main certification modalities that exist today, and the main applications of blockchain technology for the management of certificates. We will conclude by explaining how the described prototype works as one of the central elements for the deployment of a platform specially designed in blockchain to detect fake news and fight against disinformation.
Program Synthesis Using Example Propagation

We present Scrybe, an example-based synthesis tool for a statically-typed functional programming language, which combines top-down deductive reasoning in the style of $$\lambda ^2$$ with Smyth-style live bidirectional evaluation. During synthesis, example constraints are propagated through sketches to prune and guide the search. This enables Scrybe to make more effective use of functions provided in the context. To evaluate our tool, it is run on the combined, largely disjoint, benchmarks of $$\lambda ^2$$ and Myth. Scrybe is able to synthesize most of the combined benchmark tasks.
A study on the improvement of the integrated real state investigation system for coping with the US CMMC system

Recently, thanks to the rapidly growing K-defense industry, Korea's defense industry is rising as one of the world's top 10 powerhouses, and insider information leakage and cyber hacking attacks targeting core defense industry technologies are continuously increasing. The need for defense technology protection is increasing. In response, the government enacted the Defense Industrial Technology Protection Act and conducted annual integrated fact-finding surveys on defense companies to check their cyber security systems. Meanwhile, the US government, which holds the leadership in the defense industry market, is threatening the growth of the domestic defense industry by implementing the CMMC (Cyber Security Maturity Model Certification) system and planning to require CMMC certification from companies in other countries. In this paper, an integrated fact-finding survey improvement model was designed through the analysis of the integrated fact-finding survey checklist and CMMC control items that investigate the cyber security reality of the defense industry, and a solution was proposed for elements not included in CMMC, and the CMMC system was implemented in Korea. Suggested countermeasures for a soft landing. The government and academia are reviewing various policy measures to respond to the US CMMC, such as preparing the K-CMMC certification system. Therefore, this study is expected to help settle the K-CMMC system in the future.
Digital accreditation and utilization of experiences and achievement from extra-curricular program participation: A case study of S University's digital badge development

본 연구는 S대학의 디지털 배지 개발 사례를 통해 디지털 배지 활용과 비교과 프로그램 인증 및 다양한 이해관계자의 성찰을 제공하고자 한다. 연구방법으로는 문헌분석과 실행연구방법을 활용하였다. 연구결과 첫째, 문헌분석 결과 디지털 배지는 비교과 프로그램 참여율 향상과 질 관리 및 효과적인 인증 도구로 제시할 수 있다. 둘째, 디지털 배지 적용 정책은 대학에서 비교과 프로그램의 인증도구로 디지털 배지를 적용할 때 가장 중요하게 고려해야 할 점이다. 셋째, 디지털 배지 활용에 대한 내부 부서의 다양한 요구를 수용할 수 있도록 운영자 교육을 실시해야 한다. 넷째, 대학 내에서 비교과 프로그램 이수자를 대상으로 디지털 배지를 수여할 때 디지털 배지 간 차등을 두어 수여할 수 있는 전략을 제시할 필요가 있다. 다섯째, e-포트폴리오는 디지털 배지와 함께 비교과 프로그램을 비롯한 다양한 대학 경험에 대한 성취 인증 도구로서 활용될 수 있다. 이상의 결과를 종합해보면 대학에서 비교과 프로그램 인증을 위해 디지털 배지는 강력한 인증 도구로써 활용할 수 있는 가치가 있으며, 실제 적용 사례에서 보이는 다양한 이해관계자의 성찰을 통해 대학에서 적용되고 활용할 수 있는 가능성을 제시한다.This study aimed to elucidate the use of digital badges, certification of extra-curricular programs, and reflection of various stakeholders using the case of digital badges development at S University. Literature review and action research methods were used as research methods. The study results confirmed the following. First, the literature review affirmed that digital badges could be used as alternatives to improved participation in extra-curricular programs, quality management, and more effective accreditation tools. Second, the digital badge application policy must be primarily considered when applying digital badges as a means of accreditation to extra-curricular programs at universities. Third, the person in charge of digital badges in the university should consider various functions to accommodate various demands of internal departments. Fourth, digital badges must be issued with a price difference when issuing digital badges to students who completed extra-curricular programs. Fifth, the e-portfolios can be used to recognize the achievement of various university experiences, including extra-curricular programs and digital badges. Moreover, the results corroborated that digital badges can be employed as powerful accreditation tools to certify extra-curricular programs in universities and can be applied and utilized in universities by reflecting various stakeholders in practical application cases.
Modifikasi membran polyvinylidene fluoride (PVDF) dengan penambahan polyvinyl pyrrolidone (PVP) dan kitosan dengan metode inversi fasa

One of the simplest approaches to improve membrane performance is to increase the hydrophilicity of the membrane. This article describes the manufacture of activated polyvinylidene fluoride (PVDF) based membranes using PVP and chitosan as organic additives, with the specific aim of increasing the hydrophilicity of the membranes. Variations of dope solution were made by adding 1% by weight of PVP and 1, 2, and 3% by weight of chitosan into three different PVDF polymer solutions. The effect of additives on the membrane was obtained by evaluating chemical functional groups by ATR-FTIR, morphological changes by SEM, and filtration performance. SEM images show that the presence of additives changes the morphological structure of the membrane. This change also had a significant impact on the membrane performance, as evidenced by the increased permeability of the pure water solution and the removal of dissolved humic acid. Overall, modified PVDF membranes with 1% by weight of PVP and 1, 2, and 3% by weight of chitosan resulted in much better permeability than unmodified PVDF membranes due to their excellent hydrophilicity.
An Investigation of Best Measurement Conditions for Calculating Reading CBM Slope in Monitoring Progress for Students with Learning Disabilities: An Application of Simulation Method

학습장애분야에서 CBM의 기울기는 중재전략의 효과성을 평가하는 지표로 활용되고 있지만 CBM 기울기의 측정학적 적합성을 검증하는 연구는 여전히 충분치 않은 상황이다. 본 논문에서는 특별히 측정학적으로 적합한 CBM 기울기를 산출할 수 있는 측정조건을 조사하는 연구목적을 갖고 있었다. CBM 기울기를 산출하는 최적의 측정조건을 조사하기 위해서 본 연구에서는 2가지의 독립변인(오차의 크기와 측정횟수)과 4가지의 종속변인(신뢰도, 타당도, RMSE, MSE)을 각각 설정하였다. 본 연구의 분석결과에 따르면 측정학적으로 우수한 CBM 기울기를 산출하기 위해서는 오차가 적은 CBM 자료의 수집과 함께 최소 12주 이상의 측정주기가 필요한 것으로 나타났다. 끝으로 본 연구에서 도출한 연구결과의 시사점과 향후 연구주제를 논의하였다.Despite the fact that Curriculum-Based Measurement(CBM) slopes have been used to evaluate the effectiveness of interventions in research on learning disabilities, there is a lack of empirical research for supporting the technical adequacy of CBM slope. This study examined the best conditions for calculating CBM slope. In order to examine these conditions, this study contained two independent variables(the amount of residual error and the number of data points) and four dependent variables(reliability, validity, RMSE, and MSE). Results of this study indicate that it is necessary to minimize the magnitudes of residual error and collect a minimum of 12 reading CBM data points. Implications and future directions for research are discussed.
Comparative Analysis of Multi-digit Modular Multiplication Algorithms for public key Crypto system in Big Data Security

Big data security is a significant concern today due to rapidly growing data volume, velocity, and varieties of data in nature. Data security is a major concern because during transmission through insecure channels. From its recognition, the Montgomery multi-digit multiplication algorithms are still well-accepted approaches in the numerical calculation, chaos arithmetic, and highperformance implementation of public key cryptosystems such as RSA, Diffie-Hellman, and the Elliptic curve cryptosystems. We have presented the comparative study of multi-digit integer multiplication algorithms, and their performance is evaluated in terms of CPU execution time. Montgomery modular multiplication is a good practice, among others.
Three‐Tiered Blog System Helps Guide University's Employees

Nonprofit Communications ReportVolume 21, Issue 2 p. 8-8 Useful Internal Guidelines Three-Tiered Blog System Helps Guide University's Employees First published: 09 January 2023 https://doi.org/10.1002/npcr.32123Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume21, Issue2February 2023Pages 8-8 RelatedInformation
The Correlation Filter with Adaptive Spatial and Temporal Regularization for Inland Ship Tracking

Ship tracking is an important task of inland waterway video surveillance. Inland waterway scenes are complex. Generic algorithms applied directly to inland river scenes are susceptible to performance degradation due to boat occlusion, light changes, and water ripples. In this paper, we propose the ATSR-DCF (Self-adaptive Temporal and Spatial Regularization Discriminative Correlation Filter) algorithm to improve ship tracking performance using adaptive spatiotemporal regularization and ship position incremental information. First, ATSR-DCF gets the initial frame and initial spatial and temporal regularization weights to train the correlation filter. Second, input other video frames, compute the optimized spatial and temporal regularization weights and update the filter using the Alternating Direction Method of Multipliers (ADMM). Finally, obtaining video sequence position increments constrains the subsequent position for predicting the target ship. In order to evaluate the performance of ASTR-DCF, we perform experiments using our group’s inland waterway ship dataset. The results show that the ATSR-DCF tracking performance outperforms other comparative algorithms. The tracking success rate is 80.0% and the accuracy rate is 86.6%.
Modulation type identification method of radar signal from optical frequency comb down-conversion receiving system

Compared with the traditional electronic reconnaissance receiver, the electronic reconnaissance receiving system using optical frequency comb down-conversion technology can simultaneously down-convert all the electromagnetic signals from the wide-band range (1MHz-20GHz) to the first repetition frequency interval range(DC-110MHz) for reception and measurement. This method can significantly improve the measuring speed and reduce the receiving cost. However, when the captured signal is a type with bandwidth like radar signal, the down-conversion spectrum may be aliased, resulting in the change of signal spectrum shape, which will affect the modulation type identification and frequency recovery of the signal. In order to solve the problem of modulation type identification of radar signals with spectrum aliasing after optical down-conversion, a modulation type identification method based on radar signal auto-correlation feature extraction is proposed in this paper. According to the characteristic that the auto-correlation function is insensitive to the spectrum aliasing after optical down-conversion, this method extracts the type identification features of auto-correlation envelope and its spectrum, such as skewness, kurtosis, impact factor, and finally uses SVM to identification the modulation type. Simulation results show that this identification method can accurately identify the modulation type of radar signal with spectrum aliasing after optical down-conversion, and has good anti-noise performance. When the SNR is higher than -3dB, the identification accuracy of this method for LFM and SIN after optical down-conversion is higher than 99%. For NP, BPSK, QPSK, BFSK, LFM and SIN signals with dynamic SNR between -6db and 10dB , the identification accuracy is more than 95%.
Domain-oriented information search on the Internet

The article is devoted to the study of the problem of information search on the Internet by using knowledge about the domains of the Web space. The domain information model (IM), the virtual Web environment model (VWE) and the user query model (UQ) are proposed, as well as the relationships and mapping principles between them are investigated. The possibility of providing a thematic focus, improving the quality and efficiency of the search process, improving results using an information model of domain representation is considered. Based on this model, a domain-oriented information search system for the Internet Web space has been developed. To improve the quality of the search engine and search results, a fuzzy logic approach is used, thanks to which a fuzzy domain-oriented information model of the Web space is proposed. Within the framework of the proposed models, methods have been developed for determining the content connectivity of Web documents, dividing the Web space into related Web areas, and virtual unification of Web areas.
Pengembangan Media Pembelajaran Flipbook Interaktif dalam PMRI Berbasis Youtube untuk Meningkatkan Daya Tarik Terhadap Siswa

The lack of use of learning media in learning makes students less enthusiastic in participating in learning. In learning students also need learning media that can help understand the material repeatedly so that it is necessary to develop learning media such as interactive youtube-based flipbook electronic teaching materials. This study aims to produce interactive flipbook electronic teaching materials based on the SPLDV class VIII material which have been tested for validity and reliability. This research is a development research using the ADDIE model. The subjects in this study were: 2 material experts, 2 media experts and 30 student responses. The data collection method used an instrument in the form of a rating scale with a validity assessment sheet for interactive flipbook electronic teaching materials based on SPLDV material. The data analysis technique used is qualitative analysis and quantitative analysis. The data were analyzed using the mean formula to obtain the average score. The results of the research obtained are interactive flipbook electronic teaching materials based on YouTube, SPLDV material received an assessment of 85.50% from media experts, 85.83% from material experts, and 85.73% from users or students. So it can be concluded that the interactive flipbook electronic teaching material based on the SPLDV YouTube material is very feasible at MTs Kun Karima.
A Lightweight Sentiment Analysis Framework for a Micro-Intelligent Terminal

Sentiment analysis aims to mine polarity features in the text, which can empower intelligent terminals to recognize opinions and further enhance interaction capabilities with customers. Considerable progress has been made using recurrent neural networks or pre-trained models to learn semantic representations. However, recently published models with complex structures require increasing computational resources to reach state-of-the-art (SOTA) performance. It is still a significant challenge to deploy these models to run on micro-intelligent terminals with limited computing power and memory. This paper proposes a lightweight and efficient framework based on hybrid multi-grained embedding on sentiment analysis (MC-GGRU). The gated recurrent unit model is designed to incorporate a global attention structure that allows contextual representations to be learned from unstructured text using word tokens. In addition, a multi-grained feature layer can further enrich sentence representation features with implicit semantics from characters. Through hybrid multi-grained representation, MC-GGRU achieves high inference performance with a shallow structure. The experimental results of five public datasets show that our method achieves SOTA for sentiment classification with a trade-off between accuracy and speed.
Sistem Pendukung Keputusan Penentuan Penerimaan Bantuan Pangan Non Tunai Menerapkan Metode Simple Additive Weighting (SAW)

One of the programs established by the government to reduce the burden on the community in meeting basic needs is the Non-Cash Food Assistance Program (BPNT). The Social Service of Batu Bara Regency in determining the acceptance of Non-Cash food assistance has so far been using conventional methods. This makes it less than optimal in determining which people are eligible for this selection of food aid recipients, especially the priority of several people whose names have been registered with the Batu Bara Regency Social Service. In doing this election calculation does not use specific criteria so that the alternatives obtained are not as expected. Besides that, it takes time that is not fast in determining decisions and the results are slow because it must be done by holding a meeting between employees and the head of the department which causes the results of the decision to be not on target. So the Social Service of Batu Bara Regency needs a decision support system to provide alternative choices and make it easier to determine prospective Beneficiary Families (KPM) participants to determine decision assessments for Non-Cash Food Aid Reception. The method used is by collecting data on filling out forms given to village communities and using the implementation of the Simple Additive Weighted (SAW) method as a decision support system in receiving non-cash food assistance at the Batu Bara District Social Service. The results of this research are the best with the highest score with a number of criteria, the chosen one is the name Lestari, who deserves to be recommended as receiving non-cash food assistance, there are also several other names based on the ranking in the calculation of this SPK
Design Principles for Educational Software

This interactive session at CSCL 2002 will present, and add to our ongoing study of design principles for educational technology. We are seeking to capture key findings of the field using a three-level framework, including these interlinked components: educational goals, design principles, and software features.
A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques

E-learning became the main medium of education in the world for the past two years. COVID-19 virus has pushed all the universities and academic institutions to utilize and activate E-learning platforms and systems. The sudden and urgent transformation from the regular traditional learning system to E-learning system has involved many challenges and limitations. Therefore, the need to evaluate and enhance the current E-learning mechanism in Iraq became very urgent and critical need. The target level was students at higher education institutes which include university students in Basra city. The data collected based on students’ evaluation and opinions about E-learning based on their interaction and usage during two years under COVID-19 spread era. This research involved applying data mining techniques to sample dataset and utilizing the obtained results as feedback for a proposed model suggested by the authors to measure adaptability. The proposed model is derived from the idea of the Technology Acceptance Model (TAM) with focus on the positivity as the main factor to measure adaptability. The results of the research showed approximate adaptation level of 52% which is very close compared to the actual situation in real life which involve limitations and challenges faced by Iraqi students.
GCNPart: Interference-Aware Resource Partitioning Framework with Graph Convolutional Neural Networks and Deep Reinforcement Learning

The clouding server providers usually take workload consolidation to maximize server utilization. For eliminating performance interference due to the competition among multiple shared resources, resource partitioning becomes an important problem in daily commercial servers scenario. However, partitioning the critical multiple resources coordinately is particularly challenging due to the complex contention behaviors and the large search space to be explored for finding the optimal solution. In this paper, we propose GCNPart, which focuses on allocating the optimal shared compete resource partition for colocated applications to optimize system performance. The existing resource partitioning frameworks lack analysis and good modeling of applications, resulting in inefficiencies or lack of generality. We formulate the resource partitioning problem as a sequential decision problem. GCNPart builds an accurate application performance model based on graph convolutional neural networks (GCN) to learn the mapping relationships from multiple resources to applications, and then constructs deep reinforcement learning (DRL) model to consider temporal information for real-time resource partitioning decisions. The extensive experiments evaluate that compared with the existing resource partitioning frameworks, GCNPart improves system throughput by 5.35% $$\sim $$ 26.57%.
Pengaruh Media Pembelajaran Dengan Menggunakan Aplikasi Quizizz terhadap Hasil Belajar Mahasiswa pada Mata Kuliah Matematika Diskrit

Learning outcomes become a benchmark in one's success. Choosing the right learning application can make students comfortable and happy in learning. The purpose of this study was to determine the effect of learning media using the quizizz application on student learning outcomes in discrete mathematics courses. The population used in this study were all students of the Faculty of Engineering, Putra Indonesia University. The samples used were students in semesters V A and V B. This research method used the Nonequivalent Control Group Design. To find out the effect of using the quizizz application on student learning outcomes in the fifth semester discrete mathematics course, Faculty of Engineering at Putra Indonesia Cianjur University, several tests were carried out, namely, instrument tests including validity and reliability, analysis prerequisite tests, namely normality, homogeneity, and T test. Based on the results of hypothesis testing are known through the calculation results of Tcount 2.329 &gt; Ttable 2.039 with a confidence level of 95% or α 0.05. It can be concluded that there is a positive influence on the use of the quizizz application on the learning outcomes of Discrete Mathematics fifth semester students at Putra Indonesia University, Cianjur. Keywords: Quizizz Application, Learning Outcomes