Reviewerly/exHarmony huggingface dataset:
The Effect of Using Flashcard Improving Students’ Speaking Achievement Through Drilling Technique

This research deals with classroom action research which is mainly aimed  to  improve  the students’ speaking achievement through implementing drilling technique assisted by media flashcard,  it  was conducted  at  VII-3 grade class  in  to  cycles activities. The data were classified into quantitative data and qualitative data  in  which collected through observation sheet, interview, diary note, speaking test.  The criteria of ability was 70 which based on minimum ability criterion (KKM) of SMP Swasta Bandung. Based  on  the speaking test the mean score of pre-test was 28.3, in first cycle test the mean of score was 66.6 and the second cycle test the mean of score was 83. The improvement also can be seen from the percentage of the students’ speaking achievement, in pre-test was 0% students can get point more than 70. In first cycle test was 53.4% students get point more than 70. In second cycle test 100% students got point more than 70, it means that teaching by using drilling technique can help students to improve them in speaking achievement. This technique also make the students feel enjoy, comfortable, and more creative to create the ideas without worrying make mistakes through media flashcard.
Frequency-domain-decomposition based white-light interferometry for noise-insensitive measurement

This paper proposed a frequency-domain-decomposition denoising algorithm for nano-scale measurement in white light interferometry (WLI). In this work, the captured correlogram is firstly divided into a series of short-time stationary signals, the phase distribution can then be derived as the sum of the corresponding phase components after Fourier transform. By applying windowed threshold filtering, the noises existed in phase map can be eliminated, and a denoised correlogram is precisely reconstructed. Afterwards, the surface height is retrieved through phase-frequency least-square fitting. In simulations, the phase noises with different levels are investigated. By comparing the noise deviations in the reconstructed phase map with the original one, the effectiveness on noise suppression of the proposed method is properly verified. In the experiments, a height step standard with calibrated values 182±2.0nm are tested, where the height deviations below 3nm and the repeatability of 0.5% has proved the robustness of our proposed method.
PENGEMBANGAN MEDIA “KLIK AJA” DALAM PEMBELAJARAN DARING MENYAMPAIKAN TEKS BERITA BAGI SISWA KELAS VIII

The Covid-19 pandemic is a new challenge in the world of education, especially for a teacher, because learning must be done online. Therefore, teachers must master digital skills and creative thinking patterns, especially in conveying news texts. Facing this, this study discusses the development of online-based interactive learning media. The media development was designed by utilizing the Articulate Storyline 3 software in collaboration with learning videos and Google forms which were then combined on the Linktree website. The objectives of this study include describing the development of media and the presentation/display of the "Click Aja" media in online learning to deliver news texts for class VIII students and describe the results of the effectiveness test of using "Click Aja" media in online learning to deliver news texts for class VIII students. This study uses the type of research and development method ADDIE model. Through this research method, the discussion in this study leads to the resulting product, which is a "Click Aja" learning media. The product was tested by experts and obtained an average value of 3.4 which states that the media is suitable for use. In addition, the product was also tested on students and obtained an average score of 3.51 which stated that the media was suitable for use. Although the "Click Aja" media is feasible to use, there are improvements submitted by experts, including errors in writing, the delivery of material in the learning video is less communicative and incomplete material regarding news texts.
문어 기반 학문적 문식성 교육에 대한 제언

Academic literacy is a requirement for international students to be succeed in challenging literacy tasks in the University. The aim of this study is to suggest the education of academic literacy from an ecological perspective. As a result, “collaborative learning” and “ecological language teaching strategy’ can be used in Korean education in order to develop students’ academic literacy. This paper also shows a model of essay writing class as an example.
Search Region Reduction and Ant Colony Optimization, a Short Survey

Different attempts have been made to minimize the search region if large-scale optimization problems. Reducing the search region size would deffintely improve the performance of optimization algorithms, specially ant colony optimization (ACO) algorithm. In this short survey paper, we list the most important attempts to reduce the search region.
Perancangan Security Network Intrusion Prevention System Pada PDTI Universitas Islam Raden Rahmat Malang

Security is very main in computer networks, where many devices are connected to each other to interact and exchange data without limits. Network security is also a very important issue to prioritize, one of which is to use an intrusion prevention system. At PDTI UNIRA there are often network security problems, one of which is that during the test season, the server experiences many intrusion problems. The purpose of this research is to develop a social science system based on the analysis at PDTI of Raden Rahmat Islamic University Malang. This research method uses a computer security development approach, namely the Intrusion Prevention System (IPS), by combining firewall engineering methods and Intrusion-Detection System (IDS). The result of this research is a technology that can be used to prevent attacks that will enter the local network checking and recording all data packets and recognizing sensor packets, when the attack has been identified, IPS will deny access (block) and record (log) all data packets. identified. So IPS acts as a firewall that will allow and block combined with IDS that can detect packets in detail. With a network security system, the Unira PDTI server is safer and can avoid intrusion.
Money Laundering Considerations in Blockchain based International Commerce

There is much to be welcomed concerning the role blockchain technology can play to modernise and enhance international trade and create a more level playing field and reduce costs. However, it goes without say that the technology also brings with it the prospect of abuse leading to trade based money laundering. This chapter explores how the anti money laundering (AML) legislation should respond to the use of blockchain technology in shipping and trade. Drawing on tried and tested forms of blockchain technology based trade transactions, the work examines the fault lines in the current regulatory system and questions how best these gaps should be remedied. It also stresses that even states that have banned the issue and trade of cryptoassets, such as the People’s Republic of China (PRC), would not be immune to the new challenges.
Marketing of LIS Products and Services through Social Media

The attainment of a specific level of competence that would be required or necessary for entering into professional practice in a responsible manner social media will be the perfect platform for the libraries to explore their credentials to the users, this will not only help the user to come to library it will also help in contact with library without his/her physical presence in the library. Without marketing we cannot sell or buy a product the same applies to the libraries too. The library existing and users have a right to know what is there in the library. That is about the collection and its services. This paper focuses on the various social medial tools that are used for Marketing the LIS Products and services.
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents

There has been rapidly growing interest in meta-learning as a method for increasing the flexibility and sample efficiency of reinforcement learning. One problem in this area of research, however, has been a scarcity of adequate benchmark tasks. In general, the structure underlying past benchmarks has either been too simple to be inherently interesting, or too ill-defined to support principled analysis. In the present work, we introduce a new benchmark for meta-RL research, emphasizing transparency and potential for in-depth analysis as well as structural richness. Alchemy is a 3D video game, implemented in Unity, which involves a latent causal structure that is resampled procedurally from episode to episode, affording structure learning, online inference, hypothesis testing and action sequencing based on abstract domain knowledge. We evaluate a pair of powerful RL agents on Alchemy and present an in-depth analysis of one of these agents. Results clearly indicate a frank and specific failure of meta-learning, providing validation for Alchemy as a challenging benchmark for meta-RL. Concurrent with this report, we are releasing Alchemy as public resource, together with a suite of analysis tools and sample agent trajectories.
증거기반정책과 데이터기반행정법: 미국과 영국의 법·제도 비교 및 함의

The purpose of this paper is to explore the role the data-based administrative law in data-based policy. To this end, the case of the US, which recently implemented the Evidence-based Policy Act, and the case of the UK, which actively uses public data for policy were analyzed. The Evidence-Based Policy Act of the US stipulates strategic and evaluation plans, evaluators and statistics officers for evidence-building, data advisory committees, etc. in relation to “evidence-building activities” that are closely related to the evaluation plans of the federal government. In relation to the use of public data produced by the federal government, the OPEN Government Data Act provides for a Strategic Information Resource Management Plan including the Open Data Plan, a Comprehensive Data Inventory, a Federal Data Catalogue, best practices related to data use, protection, provision and production, and committees to promote inter-agency data sharing agreements. With the aim of building a learning-oriented government organization, importance on “policy evaluation” and “policy questions”was placed. The UK's administrative data research is approaching a research network for public data. Started as part of the Secretary to the Treasury's Big Data plan in 2012, the Digital Economy Act of 2017 has a clear purpose of allowing researchers to use administrative data, as it provides a legal basis for researchers to access government data in a safe way. In this way, administrative data research acts as a bridge between government and academia. Based on such partnerships with academia, internal governance and active cooperation with the government are also being carried out. The UK recognizes the importance of public data, and the statistical agency functions as a data hub. Based on these discussions, certain implications were presented to the Korean situation as to what role data-based administration laws play in each country's data-based policies.
Long-term stable target tracking algorithm based on improved Staple

Staple algorithm has been widely proven to be an efficient target tracking method, but it is still easy to fail in some tracking scenarios such as target deformation, motion blur, and complete occlusion. This paper makes improvements to the above problems. First of all, we use a binary mask based on spatial reliability to enhance the target information in Staple's color features, which improves the tracking accuracy of the algorithm in complex scenes. Secondly, we propose a response graph evaluation index based on secondary detection, that is, the least square filter is used for convolution at the original response peak to obtain a more accurate tracking state judgment. Finally, if the current state is judged to be a failure, we use a particle filter-based motion estimation method to relocate the target, thereby improving the algorithm's tracking success rate when the target is occluded. The test results on the OTB2015 data set show that the overall accuracy of the algorithm in this paper has reached 80%, and the overall success rate has reached 73.2%, which proves the long-term stable tracking performance of the algorithm.
블록체인 기반의 물류정책·서비스 선진화 연구

Recently, due to the convergence of information and communication technology, the industrys hyperconnection-based intelligence called the 4th Industrial Revolution is being achieved. As the logistics sector is one of the innovative fields, the government and the logistics industry are pursuing the development of intelligent logistics that is linked to smart manufacturing and distribution. However, despite the needs of the times and the trend of the industry, digital transformation, which refers to the fundamental change of the digital industry, has not been progressed quickly and efficiently from the information point of view, which is the core element of the intelligent logistics. The main reasons are the relatively small business size, complex transaction structure, various positions of stakeholder participation, the security, integrity, and the reliability of information required in the creation, sharing, and processing of logistics information. With the emergence of blockchain technology which is a decentralized information management and sharing technology, global attention has been focused on the technology as one of the new forms of informatization, and the government is supporting the development of blockchain technology as a future new industry. The logistics sector has also been selected as one of the target sectors and has been recognized for the possibility of adopting blockchain technology. This study aims to examine how to use blockchain technology as a new driving factor of the logistics industrys digital transformation, which can accelerate the advancement of the logistics industry into the era of the Fourth Industrial Revolution. To this end, we identified the major problems of the domestic logistics industry and analyzed the cases using blockchain technology to derive the characteristics that can be used in the logistics industry. Based on the demands of the industry, we have identified logistics blockchain technologies that can contribute to improving logistics services and proposed logistics advancement policies to effectively utilize them.
PREVALENCE RATE OF THE SATISFACTION OF E-LEARNING METHODS AMONG THE STUDENTS STUDYING IN THE NURSING STREAM DURING THE COVID 19 PANDEMIC IN SELECTED NURSING COLLEGES

The study was designed to find suitable literature regarding e-learning methods and their application in nursing colleges.Literature of various available databases was studied and after reviewing the various literature researchers found that majority of the studies are reporting that nursing students are satisfied with e-learning methods among nursing colleges during covid 19 pandemic but still considering the number of literatures reviewed, more studies are required in this regard.Hence, In future, it will also be very interesting to study elearning methodologies and their advances as the technology gets updated on regular basis.It can also be concluded that technology tools are now an essential part of nursing education.
Multiclass Apparel Identification Based on HOG Feature Extractor using SVM and Softmax

Image classification and recognition plays an important role in many applications, like online shopping, driverless cars, automation, similar item retrieval queries, etc. In this project we have presented the identification of fashion items in an image. Given an image our model can identify whether it contains any fashion item or not. It can identify items like shirt, shoes, t-shirt, trousers, handbag and 6 other items. Our model consists of two things which are a feature extractor and a classifier. Based on research and experimental work we have selected HOG (Histogram of Oriented Gradients) as feature extraction method and two classifiers which are SVM (Support Vector Machine) and Softmax. It is a very tough task to select appropriate model for classification. It requires training and testing various models and techniques. However, we are able to achieve excellent results using our model.
STRATEGI PEMASARAN ROTI DI KING’S BAKERY DENGAN METODE ANALYTICAL HIERARCHY PROCESS (AHP)

ABSTRACT Every industry must make gradual improvements in order to be able to compete in the era of globalization. King's Bakery is a home industry that produces bread. The condition of bread marketing in the King's Bakery business has not been maximized. This study aims to determine the order of priority criteria and sub-criteria in the selection of a bread marketing strategy at King's Bakery and which strategy should be chosen by King's Bakery based on the Analytical Hierarchy Process (AHP) method. Analytical Hierarchy Process (AHP) is a method for ranking decision alternatives and selecting the best one with several criteria. The Analytical Hierarchy Process (AHP) develops a numerical value to find a ranking or priority order of various alternatives in solving a problem, based on the extent to which each alternative meets the decision maker's criteria. The results of this study obtained an assessment of the importance of the criteria in the selection of a bread marketing strategy showing the following priority or weighting scale: the first priority was place (0.546), the second and third priorities are products and distribution channels with the same value (0.231), and the fourth priority was the organization (0.104). From the results of the assessment of the level of alternative importance in the selection of bread marketing strategies, the priority scale or weights are as follows: the first priority was strategy A (3.614), the second priority was strategy C (2.366), the third priority was strategy B (2,000). The best bread marketing strategy that can be used as an alternative to improve bread marketing was strategy A, because it has the highest overall weight value. With technological innovation, it will accelerate production and facilitate marketing for the company.
Comparison of estimation error between two different low-rank Kalman-Bucy filters

This paper analyzes the estimation error of a low-rank Kalman-Bucy filter proposed by the authors. Recently the authors proposed a low-rank approximation of the Kalman filter and showed some properties like the stability condition of the estimation error dynamics. However, the estimation accuracy was only shown by numerical examples. In this paper, the estimation accuracy is analyzed and compared with another low-rank Kalman-Bucy filter introduced by another work, and we show when our proposed filter is superior to the prior one.
Komputerisasi Sistem Informasi Keanggotaan DPC PORMIKI Solo (SIKPOSO) Berbasis Android

The Solo branch of the Indonesian Association of Medical Recorders and Health Information Professionals (PORMIKI) serves various kinds of correspondence requests from members. Services that are done manually cause the service to be slow. With a well-developed information system, it is hoped that the membership service process will be faster and easier. PORMIKI Solo Membership Information System (SIKPOSO), is an information system in the form of a mobile application with the Android operating system. The form of the mobile application was chosen considering the ease of access for members of PORMIKI (Indonesian Association of Medical Recorders and Health Information Professionals). The design of SIKPOSO includes the preparation of Flowcharts, Use Case Diagrams, Entity Relationship Diagrams, Data Flow Diagrams, Activity Diagrams, Wireframes, and User Interfaces as a reference for developing membership systems that currently do not exist. The method used in the development of this system is the Prototyping method.SIKPOSO is designed to provide 6 service menus, as Request for recommendation of Practice License (SIK), Request for Membership Mutation Letter, Virtual Member Card (KTA), Membership Information, Annual Fee Information and Event Information. Evaluation of the SIKPOSO design was carried out using the SUS (System Usability Scale) questionnaire, getting the final score of 77 indicating that SIKPOSO is on a B grade, have a good rating and can be accepted by user for further development.
EDUCATION BASED ON COMPUTER SIMULATION MODEL IN INFORMATICS AND INFORMATION TECHNOLOGIES

The article In Informatics and information technology discipline it is recommended to use concepts logical scheme related to the algorithm and, on this basis, a computer simulation model. A logical scheme of the algorithm concepts has been developed, and a computer simulation model has been created, which provides information about each concept. The methodology of organizing lectures on the basis of the created computer simulation model is described
Personalized Healthy Anti-COVID Menu Generator Chatbot Based on Prolog

It is a healthy diet that creates conditions for human life, ensuring the optimal functioning of all processes in the body. Of course, a healthy diet cannot be a protection against the penetration of infection into the body, but it is the balanced and full-fledged nature of the diet that creates the conditions for the formation of a timely and adequate immune response. In order to help consumers in getting more balanced and healthy diet, we created a personalized Healthy Menu Generator Chatbot, based on Prolog Knowledge base. The user request is constructed by user in a subset of English Language by using Request Fragments from a list. Cross-translation of the user request and its execution in the Prolog Execution Environment is extensively covered in the paper.
Hybridmsbd: Malicious Social Bot Detection Using Hybrid Learning Automata-Based Malicious Social Bot Detection

Because of SM (Social Media), people are more likely to share their expertise on the internet. They may also communicate with individuals from all around the globe thanks to it. With all its attention, it has turned into a fun place to try out new attacks. User data (e.g. user-produced data) in OSNs has grown significantly in terms of volume, velocity, and variety. New techniques for gathering and analyzing such comprehensive data have been investigated as a result. By automating analytical services and improving customer service quality, SBs have proven useful. Fake news (i.e. misinformation) has had real-world repercussions for MSB, on the other hand. As a result, it is essential to identify and remove MSB (Malicious Social Bots) from OSNs the vast majority of existing MSB identification methods are quantitative in nature. Consequently, the analytical accuracy is low when using SBs since they easily imitate these features. HybridMSBD, a new method based on hybrid learning automata, was proposed for the identification of MSBs. KNN, SVM, and Naive Bayes, Random Forest and Decision Tree algorithms, were utilized as pre-processors for the ML models. A novel method is presented that combines behavior detection utilizing the HLA-MSBD algorithm to identify tweets produced by genuine individuals or bots. The first simulation findings are very promising. Experiments on the Kaggle dataset indicate that our method can outperform current state-of-the-art bot identification algorithms in performance.