Reviewerly/exHarmony huggingface dataset:
KEAKTIFAN MAHASISWA STKIP WIDYA YUWANA DALAM MENGIKUTI PERKULIAHAN

The activation of students in the lecture process is an essential task for students. Activation is the most important thing to develop student’s skills. In the learning process, students should play an active role and want to ask. Judging from the student STKIP Widya Yuwana inactivation is still lacking and still look low involvement as a student often they are reluctant to ask. Based on the background of the problem then formulated the problem formulation as follows: What is the liveliness of the lecture? What is the activation of STKIP Widya Yuwana students during this time? And what opportunities can be made to improve student activity in the lecture? The study used qualitative methods with data collection through interviews on six respondents conducted on the sixth to the thirteen April two thousand nineteen. The research instrument used is a variety of questions to know the meaning of the activation of students in the course, the activation of STKIP Widya Yuwana students in lectures and opportunities that can be made to improve student activity in lecturing.
Study of Priority Recommendation Method Based on Cognitive Diagnosis Model

In the context of personalized learning, the recommendation method aims to provide appropriate exercises for each student. And individualized knowledge status may give more effective recommendation. In this study, a priority recommendation method based on cognitive diagnosis model is proposed, and cosine similarity algorithm is applied to improve the accuracy and interpretability of recommendation. Then the performance of the methods was compared under cognitive diagnosis models. The experimental results show that the method proposed achieves more accurate results and better performance.
<i>Retracted on November 19, 2020</i> : Integration of Safety Means with Functions of Blockchain in Multi-layered Architecture of IoT for Safer Data Transmission Procedures

This Work has been Retracted by ACM because it was found to have been submitted to two conferences at the same time, which violates the ACM Prior Publication and Simultaneous Submission Policy. Raimundas Savukyans submitted his Work "Integration of Safety Means with Functions of Blockchain in Multi-layered Architecture of IoT for Safer Data Transmission Procedures" to the International Conference on Blockchain and Internet of Things (BIoT 2020) conference and ACM ICEMIS 2020 Proceedings of the 6th International Conference on Engineering and MIS. The paper was accepted and published by both conferences.
A Rest Stop on the Unending Road to Provable Security

During the past decade security research has offered persuasive arguments that the road to provable security is unending, and further that there’s no rest stop on this road; e.g., there is no security property one can prove without making assumptions about other, often unproven, system properties. In this paper I suggest what a useful first rest stop might look like, and illustrate one possible place for it on the road to provable security. Specifically, I argue that a small and simple verifier can establish software root of trust (RoT) on an untrusted system unconditionally; i.e., without secrets, trusted hardware modules, or bounds on the adversary power; and the verifier’s trustworthiness can be proven without dependencies of other unverified computations. The foundation for proving RoT establishment unconditionally already exists, and the proofs require only the availability of randomness in nature and correct specifications for the untrusted system. In this paper, I also illustrate why RoT establishment is useful for obtaining other basic properties unconditionally, such as secure initial state determination, verifiable boot, and on-demand firmware verification for I/O devices.
Construction of customized atmospheric transmission model for direct solar irradiance in localized peninsular

Taean is a small peninsular along the west coast of the mainland of Korean peninsula. It faces with the yellow sea to the west, while it is bordered with the mainland Korea to the east. The area is well known to have 1) heavy mid and high altitude air traffic, 2) busy traffic routes of ocean liners between Korea and neighboring countries and 3) complex and rapid changes in its atmospheric characteristics that tends to reduce the accuracy of regional weather forecast and therefore influencing the local industry including ocean liners. In this conference, we report a progress on customization of atmospheric transmission model suitable for direct solar irradiance measurement in the region. A large volume of direct solar irradiance and atmospheric variable data were collected over the period of 12 months in 2018. The data were obtained not only from the ground stations for low altitude, but also from the radiosonde measurement for high altitude. Initial analysis using MODTRAN showed some portions of the direct solar irradiance data that disagree with the predictions from the MODTRAN standard atmospheric models. Further in-depth study including sensitivity analysis were carried out and resulted in construction of a customized MODTRAN atmospheric model offering more accurate prediction to the measured direct solar irradiance data of the local area.
Review on credit card fraud detection and classification by Machine Learning and Data Mining approaches

The strategies for this are divided into 2 broad types: fraud detection as well as consumer activity analysis. The initial category of strategies works with controlled recognition processes at transaction stage. Transactions are classified as illegitimate or regular depending on preceding historical evidence in such systems. This dataset can then be used to construct classified models that can forecast the status of new documents (normal or fraudulent). A standard two-classification function, including rule inference, decision trees, as well as neural networks, has various model development approaches. This method has been shown to accurately identify most previously found fraud techniques, often known as identification of misuse essential to illustrate the main discrepancies in an overview of consumer behaviour and methods to fraud investigation. The system of fraud detection can identify established tricks from fraud, with a small false positive rate. Such schemes derive the sign as well as pattern of fraudulent strategies provided in the revelation data set as well as can therefore quickly decide precisely that frauds; the machine is witnessing at the moment.
Demystify squeeze networks and go beyond

Small neural networks (NNs) that have a small model size find applications in mobile and wearable computing. One famous example is the SqueezeNet that achieves the same accuracy as the AlexNet yet has 50x fewer parameters than AlexNet. A few follow-ups and architectural variants have been inspired. They were built upon ad hoc arguments and experimentally justified. It remains a mystery why the SqueezeNet works efficiently. In this work, we attempt to provide a scientific explanation to the superior performance of the SqueezeNet. The function of the fire module, which is a key component of the SqueezeNet, is analyzed in detail. We study the evolution of cross-entropy values across layers and use visualization tools to shed light on its behavior with several illustrative examples.
DETERMINING A SET OF CONDITIONS FOR AUTOMATICALLY FINDING THE BEST OPTION FOR HYBRID MACHINE TRANSLATION OF TEXT AT THE LEVELOF GRAPHEMES

The article is devoted to the Algorithmic Search for Optimal Solutions for evaluating andimproving the Quality of Hybrid Machine Translation of Text. The Object of the Research is Textson any Alphabetical Languages with different Bases (Alphabets), as well as their Translations intoother Alphabetical Languages.Currently, existing Methods and Means of Hybrid Machine Translationare characterized by a wide variety of Quality Assessment Algorithms, but the Disadvantageof these Methods is that most of them do not have Clear Criteria, Limitations and Schemes of Assessments,eventually, the Result of the Translation in most cases does not correspond to the Levelof Publication. The Aim of the Work is to determine a Set of Conditions for automatic search forthe Best Option of Hybrid Machine Translation of Text at the Level of Graphemes.The Main Tasksto be solved during the Research are the Search for Qualitative and Quantitative Conditions, includingthe maximum, minimum and average values of the Lengths of Translations, Reverse Translationsand Editorial Distances between Pairs of Texts that have the Same Meaning. The ScientificNovelty lies in use the Graphical Representation of the Model of Alphabetic Languages at theLevel of Graphemes in the Form of a Cartesian Coordinate System with a Dimension equal to aUnit Editorial Distance (by Levenstein). When solving the de Goui’s Theorem, the current Rules ofStandardization PR 50.1.027–2014 "Rules for the Provision of Translation and Special Types ofLinguistic Services", the Method of Decanonicalization and the Model "Original Text – Translation– Reverse Translation" were used. As a Result, Actual and Practically Applicable Solutionsfor the Problems under consideration are obtained. In this regard; this Work may be interest to awide range of Specialists engaged in Machine Translation and Translation Studies.
Word Cloud Generation on Clothing Reviews using Topic Model

Many social networking websites like Amazon, ShopClues, and YELP are available for sharing user reviews. Reviews given by user on social networking websites are more helpful to other people for decision making on particular product or services. So we need some effective techniques to analyses reviews given by users. Moreover, LDA topic modelling algorithm serves as an effective method for analyzing the entire corpus. In this paper, word cloud generation and word plot generation are proposed to find most frequently occurring word in the given corpus.
RANCANG BANGUN APLIKASI UJIAN AKHIR SEMESTER ONLINE UNTUK MENGUKUR PENCAPAIAN KOMPETENSI SISWA SMK NEGERI 1 NGULING

Abstract : Internet technology plays a role in creating e-learning or distance education. Learning no longer has to be done in class, but from anywhere, as long as the computer used can be connected to the internet. In fact, a person can study at universities in other countries without having to live in the country concerned.Thanks to the internet too, various books in digital form or what are referred to as ebooks or various research results can be obtained easily making it easier for anyone who intends to seek or develop knowledge.Various programs on examinations that have been made, especially those being discussed, are national examinations using the CBT (Computer Based Test) system. This exam program also raises the pros and cons of various parties. For the pros, especially the organizers in this case the government, considers that the online exam saves the budget (less paper) and the distribution of the subject matter is fast and cheap, efficient and can narrow the opportunity for question leakage.As for the cons, it can come from some schools, students and the general public, looking at this online exam is very complicated and difficult to implement. Because it has not made a thorough preparation and seemed to rush.Keywords: CBT (Computer Based Test) system, e-lerning
Effect of Word Recognition Skills on Learners’ Achievement in Reading Comprehension in Vihiga County, Kenya

Word recognition is one of the comprehension processing skills encapsulated by the interactive approach instruction. Word recognition skills enable readers to understand the meaning of comprehension passages by decoding the sound of new words. Learners in Vihiga County perform poorer in English language examinations than their peers in neighbouring counties. The performance is weaker in comprehension than in grammar sections of the English paper. Despite this, there is paucity of empirical information about the nexus between activation of word recognition skills and learners’ achievement in reading comprehension in the County. This study applied the Solomon Four-Group Design to source data from 279 primary school learners and 8 teachers in 2017. Multiple linear regression was used to generate two models, one for the experimental group (Model 1) and one for the control group (Model 2). Key results show that the influence of word recognition skills on learners’ achievement in reading comprehension was statistically significant in both groups. However, the effect was stronger in the experimental than in the control group, suggests that training teachers in the experimental group enabled learners in that group to perform better than their colleagues in the control group. Thus, activation of learners’ word recognition skills is likely to improve achievement in reading comprehension.
Academic Features Among the Non-academic: A Case of Chinese Argumentative Texts as Compared to BaREnLoB

Compared with different degrees of academic corpora(RC): BaREnLoB, this study conducted a CIA analysis to find out whether the usage features owned by Chinese English majors in their argumentative texts in WECCL2.0 (the observation corpus,OC henceforth) can demonstrate different academic features except for non academic ones.Results show some academic features among the non-academic(i.e.almost the same strong narrative features, and insufficient epistemic comments, rare depiction and classification of particular things, i.e. similar to previous findings).It shows: (i) NN2 (mostly followed by should ) and we (the usual form to refer to the author himself /herself or the research group themselves) are usually incorporated as subjects; (ii) The standard frequency (PMW) of the top 20 verbs(including be, have, find, know, become, see, etc.) and all the 55 pointed common stative ones (Zhang Z.B, 2003) between OC and RC differ much although the standard frequency(PMW) of stative verbs among the 20 top between differs slightly.(iii) the occurrences of " they/he/she + modal verbs" in OC are many times more than those in RC, even "we/you/I + modal verbs" between show the nonnatives employ much less than the natives.(iv) there are 4 out of 19 carefully-picked abstract nouns before modal verbs are in OC while none in RC.In short, this research finds that the English argumentative writings by Chinese English majors display some academic features as mirrored by the reference corpus except for some non-academic features as we found before.Finally, some implications for the teaching and research of modal verbs are discussed.
Pengembangan Model Mobile Learning Berbasis Aplikasi Android pada Mata Kuliah Sejarah ASEAN

This research is entitled Development of an Android Application-Based Mobile Learning Model in the History of ASEAN Countries in the Sriwijaya University Historical Education Study Program. This research is a type of development research that uses the development model of Dick and Carey. The purpose of this study is to develop a Mobile Learning model based on Android applications in lectures on Southeast Asian history that are valid and have an effect on effectiveness. Observation and questionnaire data show the use of the SEA-Hole Mobile Learning application (South East Asian Historic Mobile Learning) has a good impact in supporting the Southeast Asian History lecture process, such as making it easier to understand Southeast Asian History lecture material because it is supported by images and videos. Some entries from Experts and small groups are used to produce a valid application prototype. Overall the SEA-Hole Mobile Learning application has a good effect to be used as a support for mobile lectures.
Decision Tree Using Artificial Neural Network: A Proposed Model

A decision tree is one of the data mining techniques; it has a tree structure, which consists of internal node, branches, and leaf nodes which are known as decision nodes also. Decision tree works in a transparent way [1]. Unlike artificial neural networks, it shows all the possible alternatives and traces each alternative to its conclusion so that we can easily compare between various alternatives. This is the reason that in spite of being the most powerful technique for pattern recognition, the adoption of ANNs in many areas has been impeded, due to their inability to explain how they came to their conclusion. If large amounts of data are encountered, poor statistical efficiency observed in decision trees and it can be nullified by using neural nets. So, if we could take the knowledge that is acquired by an artificial neural network and express the same knowledge in a decision tree, then explaining a particular decision would be much easier. This paper proposes a model to combine decision tree with artificial neural network. This paper shows how a decision tree will behave and when it will combine with an artificial neural network. The experiment is done on a dataset, and the results can be used to propose a new model. This model is used to examine the efficiency of decision tree and the proposed model of decision tree with artificial neural network, in order to get the desired output.
Protectability and Enforceability of AI-Generated Inventions

Artificial intelligence (AI) leads to disruptive innovations in every aspect of life. This technology not only changes the rules of all data-related fields, it also either has or will soon reach the point where it generates innovation without human input. As its economic relevance increases, the question of protectability and enforceability of AI-generated inventions naturally arises. After evaluating the nature of AI-driven innovation, this chapter assesses the possibilities and restrictions of such protectability and enforceability. As will be shown, the legal system already provides instruments for IP protection, particularly patent protection. However, this technological progress poses challenges to the legal framework and to the common understanding of IP protection. Notably, current law does not allow patent protection of autonomously AI-generated inventions that were created without human contribution.
jKarma: A Highly-Modular Framework for Pattern-Based Change Detection on Evolving Data.

Abstract Pattern-based change detection (PBCD) describes a class of change detection algorithms for evolving data. Contrary to conventional solutions, PBCD seeks changes exhibited by the patterns over time and therefore works on an abstract form of the data, which prevents the search for changes on the raw data. Moreover, PBCD provides arguments on the validity of the results because patterns mirror changes occurred with any form of evidence. However, the existing solutions differ on data representation, pattern mining algorithm and change identification strategy, which we can deem as main modules of a general architecture, so that any PBCD task could be designed by accommodating custom implementations for those modules. This is what we propose in this paper through jKarma, a highly-modular framework written in Java for defining and performing PBCD.
The Position and Role of Total Quality Management in Farhangian University: Dimensions, Strategies and Outcomes

The purpose of this study was to determine the dimensions, implementation strategies, and consequences of implementing quality management at Farhangian University across the country in 1989. The method was based on the data theory approach. In this study, the statistical population consisted of experts and professors in the field of inclusive quality management at the University of Culture, who were selected through purposeful sampling method. Data were collected through semi-structured interviews. Validity and reliability of data were obtained by using participant review method and expert review. Content and face validity were confirmed by expert opinion. Content analysis method was used to analyze the interviews. Research findings suggest that the most important dimensions and components of inclusive quality management include customer satisfaction and accountability, the learning organization, and the future. Also, decentralization of education, culture of systematic thinking, effective educational planning and curriculum planning as the most important strategies as well as the professional development of cultures, new approaches to managing and becoming more mission-minded, enhancing the effectiveness of teaching and learning, and making the University of Culture flexible. The establishment of inclusive quality management is at Farhangian University. The results of 12 main dimensions and 365 subscales showed that customer satisfaction, decentralization and enhancing the effectiveness of teaching-learning process were the most important requirements.
USING PROTOTYPING METHODS TO DEVELOP THE INFORMATION SYSTEM FOR ACADEMIC ADVISORS

The development of information technology has caused many changes in various fields, especially for including education. It is related to whether ready or not ready, but online service system should be provided by educational institutions. STMIK Royal as an information technology has prepared the tools to respond to this condition. Likewise, services to all students which we found that would be done by academic advisors. And an academic advisor is a type of counselor who works with students, usually at the college level. However, they are the ones responsible for helping students in the academic process when they follow the subjects every day. Many problems must be consulted with the academic advisor. For this reason, the guardianship information system needs to be developed as a media for a guardian lecturer in carrying out his/her duties as an academic supervisor. Therefore, this system can be used online with the facility and to record every activity, for example: make daily, monthly, and annual reports. The academic advisor of information system was developed by applying the prototyping method in the development stage. The prototyping method is suitable to support the software development. By integrating this information system, it was easier, especially for an academic advisor to monitor the students and also to guided student development.
Employing Sentence Context in Czech Answer Selection

Question answering (QA) of non-mainstream languages requires specific adaptations of the current methods tested primarily with very large English resources. In this paper, we present the results of improving the QA answer selection task by extending the input candidate sentence with selected information from preceding sentence context. The described model represents the best published answer selection model for the Czech language as an example of a morphologically rich language. The text contains thorough evaluation of the new method including model hyperparameter combinations and detailed error discussion. The winning models have improved the previous best results by 4% reaching the mean average precision of 82.91%.
Querying Fuzzy RDF Knowledge Graphs Data

Knowledge graphs have become increasingly popular over the past years. The most popular data model for representing knowledge graphs is the Resource Description Framework (RDF). In an open Web environment, it is common case that the RDF knowledge graphs data from different sources may often contain inconsistent or imprecise information. Efficient querying of fuzzy RDF knowledge graphs is therefore of increasing importance. In this paper, we firstly introduce practical extensions of the RDF model to represent vagueness based on fuzzy graph. Then we extend the concept of SPARQL graph pattern making it possible to query an element-level fuzzy RDF knowledge graphs with high degree of truth. Finally, we present a backtracking algorithm for calculating the set of homomorphisms from fuzzy SPARQL graph into a fuzzy RDF graph to demonstrate our proposed methods.