Reviewerly/exHarmony huggingface dataset:
An Analysis of Information Systems Literature: Contributions to Fraud Research

This study analyzes the knowledge and methods used in information systems (IS) journals in the area of financial statement fraud. The purpose of this analysis is to provide tools and ideas to support interdisciplinary research in accounting and information systems for financial statement fraud topics. The study presents an analysis of five top ranking IS journals (MIS Quarterly, Information Systems Research, Communications of the ACM, Management Science, and Journal of MIS) and five top ranking IS conferences [International Conference on Information Systems (ICIS), Hawaii International Conference on System Sciences (HICSS), International Federation for Information Processing (IFIP), International Conference on Decision Support Systems (DSS), and Decision Sciences Institute National Conference (DSI)]. The literature found from these sources are categorized and presented by year, journal, contribution, type of study, methodology, data set usage, and research design. Although the literature varies, a common thread in many studies is the use of data mining and/or machine learning models to detect fraud.
A Perancangan Ilustrasi Board Game Mudik Dalam Keselamatan Berkendara

One thing that should come before everything else in driving is safety. If someone ignores traffic light while driving, it must be dangerous for motorists. The way to overcome this ignorance is giving information about the safety while riding motorcycle to young-adult since they like to violate the traffic law. The information about safety riding from the police seems not be delivered well to the audience, but now this information can be applied on board game. Board game needs an illustration as the main element. The illustration used must be compatible with the player to make it interesting. The illustration of board game is the main key for the game so that the message can be delivered well. The illustration of board game â€˜Mudik Yukâ€™ is designed based on the data from police regarding to violation of traffic law, especially in Indonesia. The board game â€˜Mudik Yukâ€™ is expected to reduce the number of traffic ruleâ€™s violation.&#x0D; Keywords: safety riding, Visual and Communication Design, board game, illustration
Flood Disaster Vulnerability Factors in Solok Selatan Regency

ABSTRACT&#x0D; The purpose of this research was to find the vulnerability factors of flood disaster in Solok Selatan Regency. This is a descriptive exploratory research, using primary and secondary survey as methods of data collection. The primary survey was done through semi structured interview with stakeholders, selected from government group. Secondary survey was conducted by institutional survey to obtain a general description of area and flood area in Solok Selatan Regency. To know the vulnerability factors of the floods, the researcher used an analysis technique called content analysis. The result showed that the factors of flood vulnerability in Solok Selatan were: high rainfall, poor drainage condition, slope, factor of road construction vulnerable to water, many meanders, factor of total population affected by floods, siltation caused by waste. &#x0D; &#x0D; Key words : vulnerability factors, flood disaster, Solok Selatan Regency
Monitoring Young Teachers’ Readiness to Innovation Activity in a Modern School

The relevance of monitoring the young teachers' readiness to innovate is attributed to the requirements of modern school development. The transition to a new format of relations between the subjects of the educational process dictates a new teacher to be capable of the purposeful pedagogical activity, able to comprehend personal pedagogic experience through comparing, studying and analyzing domestic and foreign practices of training and education. The purpose of monitoring is aimed at identifying young teachers' professional competences formation as the basis for achieving high results of the pedagogical activity, the development of the necessity of testing pedagogical innovations that affect the quality of education and teacher personality development. Current observation, test situations, explication and survey methods became the leading methods of monitoring the young teachers' readiness to an innovative activity under the conditions of a modern school. Monitoring included express diagnosis which took place during the pedagogical practice at the graduation course, and final diagnosis (the beginning of independent professional activity as a teacher). The article presents the system of innovative activity monitoring at the stage of "professional pedagogical training – independent professional pedagogical activity". The system includes specially designed questions for an express diagnosis, aimed at identifying the creative abilities to create and develop new ideas in the field of education and the readiness to implement in practical forms, as well as specially selected and developed test situations aimed at identifying conscious professional development.
Forming Readiness of Master’s Degree Students for Scientific and Research Activity

The article presents issues of developing readiness for the scientific and research activity among master’s degree students. The problem of forming the personal agency of the student is connected with the issues of forming readiness of the student to research activities as the process and result. The problem of forming readiness of the master’s student to research activities is connected with a number of scientific approaches: personality oriented, synergetic, cultural, personality oriented, competency-based, person-centered (anthropological), and etc. The work presents a review of Russian and foreign literature on the problem of the research. The model of forming readiness of master’s degree students to research activities is presented. In the structure of readiness to research activities, we experimentally distinguished five groups of components: need and motivation-based, axiological, cognitive and perceptual, operational and technological, subject and personality ones. The conclusion is made concerning the necessity to development and appraisal of the model and pedagogical conditions of realization of the concept of forming readiness of master’s degree students to research activities.
Penerapan Support Vector Regression (Svr) Dalam Memprediksi Jumlah Kunjungan Wisatawan Domestik Ke Bali

Bali is one of the most popular tourism sectors in Indonesia. In the arena of international tourism, the island of Bali is considered as the most famous national destination compared to other destinations. The high level of domestic tourism visits to Bali annually must be strictly noted especially for local governments and Bali provincial tourism agencies in optimizing facilities, infrastructure to the safety of tourists Visit. Therefore, it takes a method that can predict the number of tourists visiting Bali annually. One method used to predict the number of tourists visiting Bali is Support Vector Regression (SVR). SVR is a method to estimate a mapped function from an input object to a real amount based on the training data. SVR has the same properties about maximizing margins and kernel tricks for mapping nonlinear data. Results of this research. Based on forecasting using MAPE value training data obtained by 11.34% while use data testing of MAPE value obtained by 7.30%. Based on the resulting MAPE value can be categorized well for the number of tourism visitors.
Resultados preliminares sobre los efectos del aula inteligente en procesos de aprendizaje

The present study shows the preliminary results of a pilot assessment of the effects of the intelligent classroom in the learning processes of university students (N = 33). Using an experience sampling method, students reported to what extent the classes they attended in the intelligent classroom, compared to the conventional classroom, encouraged their attention, participation in class, creativity, curiosity, critical thinking, motivation to learn, and mood (hedonic tone and activation level). In addition, students reported to what extent the classroom was visually appealing. We used a repeated measures design. The experience of the same subjects in both classrooms was assessed over a period of 53 days. Right after participants finished the classes selected for the study, they received a message on their mobile phones with a link to a short questionnaire that evaluated their experience in relation to the class they had just attended. In total, 359 responses were obtained in relation to the conventional classroom and 209 in relation to the intelligent classroom. The preliminary results show a statistically significant difference in the degree of participation and the visual appeal of the classroom, with higher scores in the intelligent classroom. No more statistically significant differences were observed.
Integral Unity of Cognitive and Emotional Components of Personal and Professional Development of Teachers

The relevance of the following article is caused by transformations in the social and economic levels of the development of Russia in the modern period, implementation of new legal documents, development of new educational standards, consideration of professional needs according to which it is necessary to increase the level of personal and professional development of a pedagogue. In accordance with this, the current article is focused on the development of innovative technologies, which will lead to the efficiency of the following process. Methodological bases of the research involve the following approaches: system, personally-oriented, problem and situational, innovative–reflexive; principles: cultural identity, pedagogical and information technologies integration, cooperation, activity, supplying integral unity of cognitive and emotional components in the personal and professional teachers’ development. The article revealed the integral unity of cognitive and emotional components of learning in the process of acquiring scientific knowledge; functional algorithm of processing information was created and realized in the process of professional training of future teachers. As a technological mechanism supplying conditions for the Art (creativity), mentality and emotion control, as well as achievement of professional success on the basis of openness of emotional- image potential of the intellectual activity art-technologies are being studied.
An Emphasis of Digital Wallets for E-Commerce Transactions

Payment is one of the main parts of the business. Since from the last decade, the use of mobile devices for electronic payment has increased significantly. The current generation of individual payment systems that is replaced the traditional smart cards by mobile devices supplied with E-wallet and M-wallet functions. The spread of such E-wallet systems will depend on their security, functionality ease of use and the effectiveness of realization. E-wallet is a utility which offers users to save their money and make payments anywhere and all time. Many banks and nonbanks organizations are contesting to develop new on this filed. As customers adopt E-wallet and M-wallet. As customers adopt E-wallet and M-wallet, they becoming a cybercrime target. E-wallet provides a monetary action through smartphones which is fruitful freedom for electronic crimes. Quality of the system, quality of service and quality of information has to improve by the mobile wallet service providers for their M-wallet applications.
Design of Fuzzy Membership Functions for Predicting Student’s Knowledge Performance

A Fuzzy logic controller is a problem-solving control system that provides means for representing approximate knowledge. The output of a fuzzy controller is derived from the fuzzifications of crisp (numerical) inputs using associated membership functions. The crisp inputs are usually converted to the different members of the associated linguistic variables based on their respective values. This point is evident enough to show that the output of a fuzzy logic controller is heavily dependent on its memberships of the different membership functions, which can be considered as a range of inputs [4]. Input membership functions can take various forms trapezoids, triangles, bell curves, singleton or any other shape that accurately enables the distribution of information within the system, in as much as the shape provides a region of transition between adjacent membership functions.
Implementasi Algoritma Backpropagation dalam Memprediksi Jumlah Mahasiswa Baru pada AMIK-STIKOM Tunas Bangsa Pematangsiantar

The number of new students at AMIK-STIKOM Tunas Bangsa Pematangsiantar greatly influences the improvement and development of available facilities both academically and non-academically. In this study, the author will conduct a prediction process on the object of new students which aims to determine the number of new students at AMIK-STIKOM Tunas Bangsa Pematangsiantar by applying the backpropagation learning algorithm. Backpropagation is one method on artificial neural networks that is quite reliable in solving problems including predictions. The study uses six (6) architectural models: 3-12-1, 3-13-1, 3-14-1, 3-15-1, 3-16-1, 3-18-1, from the six architectural models obtained the best architecture with 75% accuracy, epoch 96 iterations in 1 second, namely architecture 3-16-1. The best architecture obtained is expected to be used as an illustration by the academic AMIK-STIKOM Tunas Bangsa in anticipating the development and increasing number of new students.
Extended Kalman Filter Method based on Backpropagation Neural Network in Current Sensor Online Calibration

Abstract The signal collected by current sensor will contain various noises, which will have a negative impact on the its accuracy and calibration. In order to remove unwanted noises, an extended Kalman filter (EKF) method based on backpropagation (BP) neural network is proposed in this paper. BP neural network has good adaptive ability and non-linear mapping ability. EKF can effectively filter noise and improve the calibration accuracy for non-linear systems. The signal collected by current sensor is processed by EKF and is used as the input signal of BP neural network. The trained neural network can modify the output signal of EKF, so as to improve the calibration accuracy. The angle difference and ratio difference of current sensor calibration are below 0.1, which meets the national standard and shows the effectiveness of this method.
Students’ Difficulties in Comprehending Narrative Text

Reading skill has been found to be one of difficult skills to achieve for many learners of English as a Foreign Language (EFL). Importantly, based on the preliminary study, narrative texts are deemed to be difficult. This study was conducted to investigate the students’ difficulties in reading text at a private primary school in Batu, involving 29 ninth grade students in the academic year of 2018-2019 as the samples. Employing the purposive sampling method by which the best class was selected, the researcher used10-items of a closed-ended questionnaire to collect the data. In the analysis, some aspects of the narrative text such as words, structure, language feature, character, setting, plot, moral value, and point of view were highlighted. Consistently, narrative texts were found to be the most difficult text faced by students at school. According to the English teacher, students got the difficulties because of lack of vocabulary, the use of simple past tense, and the instruction to make sense of the moral values. Further, difficulties pertain to the effort to comprehend the structure, point of view, and the words.
Feature selection and instance selection using cuttlefish optimisation algorithm through tabu search

Over the recent decades, the amount of data generated has been growing exponentially, the existing machine learning algorithms are not feasible for processing of such huge amount of data. To solve such kind of issues, we have two commonly adopted schemes, one is scaling up the data mining algorithms and other one is data reduction. Scaling up the data mining algorithms is not a best way, but data reduction is fairly possible. In this paper, cuttlefish optimisation algorithm along with tabu search approach is used for data reduction. Dataset can be reduced mainly in two ways, one is the selecting optimal subset of features from the original dataset, in other words eliminating those features which are contributing lesser information another method is selecting optimal subset of instances from the original data set, in other words eliminating those instances which are contributing lesser information. Cuttlefish optimisation algorithm with tabu search finds both optimal subset of features and instances. Optimal subset of feature and instance obtained from the cuttlefish algorithm with tabu search provides a similar detection rate, accuracy rate, lesser false positive rate and the lesser computational time for training the classifier that we obtained from the original data set.
Modeling Liability Data Collection Systems for Intelligent Transportation Infrastructure Using Hyperledger Fabric

Distributed ledger technology is transforming environments where the participating entities have low trust. Employing distributed ledgers for intelligent transportation infrastructure communications and operations enables decentralized collaboration between entities that do not fully trust each other. This chapter models a transportation event data collection system as a Hyperledger Fabric blockchain network and simulates it using a transportation environment modeling tool. Data structures model the data collected about accidents involving vehicles and witness reports from nearby vehicles and road-side units that observed the events. The chaincode developed for the collection, validation and corroboration of the reported data is presented. Network performance results for various configurations are discussed. Optimization of the network configuration parameters resulted in a 48.1% improvement in transaction throughput. The experiments demonstrate that a distributed ledger technology such as Hyperledger Fabric holds promise for the collection of transportation data and the collaboration of applications and services that consume the data.
ARROBO, Augmented Reality-Based Mobile Application for Supporting Innovative Learning in Robotics

The results of the study show that the use of technology in the classroom has a positive impact on students learning and behavior. The use of technology in education also makes students more independent in learning. One form of technology is augmented reality. Augmented reality is a technology to produce and combine virtual objects into the real world. In learning robotics, there are several problems, namely limited costs and the limited number of tools. Obstacles to learning robotics in addition to the cost and number of tools, namely the limited time and condition of the class that must be arranged so that it is not chaotic. In this study, will be discussed on the development of an augmented reality mobile application named ARROBO. The purpose of making ARROBO is to overcome the problem of limited costs and the limited number of tools. In addition to discussions about development, this paper will also be presented on the results of the feasibility test of the learning media. Based on the results of the feasibility test using ISO 25010, the results obtained in the functional suitability aspect obtained a score of 100%, the portability aspect obtained a score of 100%, media expert ratings obtained a score of 90%, and usability aspects obtained a score of 84%. In addition, the assessment of material experts obtained 100% results on aspects of material accuracy. Based on these results it can be concluded that the ARROBO application belongs to the "Very Worthy" category to use.
IIT-KGP at COIN 2019: Using pre-trained Language Models for modeling Machine Comprehension

In this paper, we describe our system for COIN 2019 Shared Task 1: Commonsense Inference in Everyday Narrations Ostermann et al. (2019).We show the power of leveraging state-of-the-art pre-trained language models such as BERT (Bidirectional Encoder Representations from Transformers) Devlin et al. (2018) and XLNet Yang et al. (2019) over other Commonsense Knowledge Base Resources such as ConceptNet Speer et al. (2018) and NELL Mitchell et al. ( 2015) for modeling machine comprehension.We used an ensemble of BERT Large and XLNet Large .Experimental results show that our model gives substantial improvements over the baseline and other systems incorporating knowledge bases and got the 2nd position on the final test set leaderboard with an accuracy of 90.5%.
State-Public Management of Vocational and Pedagogical Education in the Region

The relevance of the study is due to the positioning of teacher education as a state-public system. The purpose of the article is to develop a mechanism of state-public management of vocational and pedagogical education in the region. The methodological basis of the study was a set of principles of systematization, concretization, participativeness, allowing to establish relationships between the subjects of management. The main results of the research consist in substantiating the social partnership of organizers of pedagogical education; the creation of public institutions for the management of the quality of teacher education; integration of the subjects of management. The study involved 38 heads of educational organizations, 150 teachers, 430 students, who identified the criteria for assessing state-public management (rational, social). The significance of the results obtained is that social partnership ensures the organization of an educational consortium. The creation of public institutions for the management of the quality of education provides a public discussion of the evaluation criteria and transparency of the control procedure. The integration of the subjects of management provides networking for various logical reasons. The revealed criteria contribute to the conjugation of professional and educational standards (rational), the improvement of the system of continuous pedagogical education on the basis of consolidation and variable interaction of its subjects (social). In the course of the experiment, state-public structures of education management were created.
Privacy preserving outsourcing algorithm for two-point linear boundary value problems

&lt;p&gt;One of a powerful application in the age of cloud computing is the outsourcing of scientific computations to cloud computing which makes cloud computing a very powerful computing paradigm, where the customers with limited computing resource and storage devices can outsource the sophisticated computation workloads into powerful service providers. One of scientific computations problem is Two-Point Boundary Value Problems(BVP) is a basic engineering and scientific problem, which has application in various domains. In this paper, we propose a privacy-preserving, verifiable and efficient algorithm for Two-Point Boundary Value Problems in outsourcing paradigm. We implement the proposed schema on the customer side laptop and using AWS compute domain elastic compute cloud (EC2) for the cloud side.&lt;/p&gt;
An Angle-expressed Quantum Evolutionary Algorithm for Quadratic Knapsack Problem

Abstract The quadratic knapsack problem(QKP) is a typical combinatorial optimization problem. It is arisen in many optimization fields, but there exist no pseudo-polynomial time algorithm to solve it. In this paper, we propose an angle-expressed quantum evolutionary algorithm to solve QKP. In this algorithm, the qubits are expressed in the angle and initialized according to the value densities of their corresponding items, the rotation angle of Q-gate is determined through an analytical formula, and Hε gate is used to prevent from premature convergence. For infeasible solution, a dynamic value density is introduced to choose item to be selected or dropped. Finally, experiment demonstrates the effectiveness of the algorithm.