Reviewerly/exHarmony huggingface dataset:
LITERASI TEKNOLOGI DALAM PERSPEKTIF CALON PENDIDIK SEKOLAH DASAR: SEBUAH ANALISIS KEBUTUHAN

4.0 era is characterized by the use of massive and critical technology. Almost everyone has smartphone with 4G internet connection for communication and having information around the world rapidly. Students also get the advantage to do their assignment, get more interactive media for learning, or just for fun in social media. However, negative impact cannot be avoided if the students do not understand how to use the technology wisely. Therefore, technology literacy is needed to give the students strong basis in using technology to support their activities. This research aims to describe students’ perception toward the importance of technology literacy for students and candidate teachers. The informants were 23 PGMI students of IAIN Batusangkar who were given open-ended questionnaire about their perspective on the use of technology in teaching and learning process. The results describe that the use of technology such as smartphone wisely with a good knowledge on it is a must. Being innovative, creative, and dynamic are expected from students and candidate teachers as well.
SYNTHESIS OF СRYPTORESISTANT GENERATORS OF PSEUDORANDOM NUMBERS BASED ON GENERALIZED GALOIS AND FIBONACCI MATRIXES

Context. The problem to form generalized primitive matrixes on the Galois and Fibonacci any order over the field characteristics2 for the construction by the generators gamma functions for cryptographically stable algorithms of inline data encryption, free from the attack of Berlekamp-Messi (BM).Objective. Development of a way to eliminate the threat an attack using the BM algorithm on LFSR-generators of pseudorandomnumbers (PRN) to increase their crypto stability.Method. Linear Feedback Shift Registers (LFSR) are themselves good pseudorandom PRN generators, but they have undesirableproperties that reduce the efficiency of their use. For the registers of length shift n their internal state is a function of the previousoutput bits of the generator. Even if the feedback scheme is kept the secret, it can be determined by 2n output bits of the generator with the help of BM algorithm, which reduces the crypto-resistance of the generator PRN. The basis for single loop feedback circuits, which cover the classical LFSR-generators of PRN, are primitive polynomials.There are various ways to increase the crypto-resistance of LFSR-generators. To their number concern: introduction of nonlineartransformations, use poly register generators (as, for example, in the algorithm of encryption А5) and several others. The transition from classical LFSR-generators to generators basis on the generalized matrixes of Galois and Fibonacci leads to the fact that the algorithm of BM loses the ability to determine the unattainable polynomials generating multi-circuit feedback circuits in LFSRgenerators. The reason for this feature is that the series of bits generated by the generalized generator becomes dependent not only on the selected irreducible polynomial but also on the primitive element that participates in the creation of the feedback loop generator.Results. The PRN generators developed by LFSR were used to organize bytes of streaming information encryption.Conclusions. Statistical tests of the proposed PRN generators carried out with the help of NIST STS, and Diehard [16–18] packageshave confirmed the high quality of the generated sequences. Moreover, the generators turned out to be cryptographically resistantto BM attacks. The use of these generators in the formation of long keys, necessary, for example, in RSA encryption protocolsand other applications is promising. As an area of further researches, development of the generalized generators of PRN above a field of Galois of any characteristic.
Tricking the Trickster: Evidence for Predicted Sequential Structure in a 19-Year Online Psi Experiment

From August 2000 to December 2018, two online psi experiments based on a five-target, forced-choice protocol together collected 114 million trials from an estimated 200,000 people around the world. The hit rate combined across both experiments was consistent with a null effect. However, a planned secondary analysis, designed to detect a predicted sequential pattern in the data, resulted in a small magnitude but statistically unambiguous outcome. With a chance expected rate of po = 0.32, the combined observed p1 = 0.320502 ± 0.000044, z = 11.28, p = 1.7 × 10-29. Control tests found no evidence that this small deviation, found independently in two separate experiments, was due to human behavior such as optional stopping or response biases, nor to computational or randomization errors that might have provided participants with subtle cues. If analysis of other forced-choice psi tests replicates this effect, it would suggest the existence of an unconscious process that tends to obscure accuracy in psychic perception. Gaining a better understanding of that process might lead to more robust results in psi experiments.
Impact of Nitrous oxide(N2O) Concentrations on Atmospheric air Temperature Changes over Iraq and some Neighboring Regions

Iraq one of the most Middle East countries confronts to climate change, where it faced many environmental challenges the most important of high temperatures above the rate of the natural. The Nitrous oxide(N2O) gas work on the absorption of part of the heat inside the atmosphere and prevent the leakage into space and this leads to increase temperature of the air and knows this phenomenon of global warming, N2O has another effect on the atmosphere as it works to drain the ozone layer that protects the atmosphere from harmful ultraviolet rays. The aim of this research is to study the effect of N2O to increase their concentration in the atmosphere of temperature variation. Where the data was taken from satellites recorded by the European Centre for medium range weather forecasts (ECMWF) . This study choice Iraq and neighbor regions from latitude 27 to 37 ºN and longitude from 39 to 50 ºE for years (2003-2016), where we studied the behavior of N2O gas concentration and its relationship with air temperature variation. The result by using correlation coefficient between N2O and temperature it found that the relationship was high positive in the all stations of study, where in Sulamaniyah (Iraq) +0.8 , and also be a strong positive relationship in southern stations, as for neighboring regions also be high positive in Batman (Turkey) +0.7, and Amman (Jordan) +0.8 also in Aleppo(Syria) +0.8 ,and in Jubail (K.S.A) correlation coefficient +0.8, and in Ahwaz (Iran) be +0.8 .
BP neural network study on the quality evaluation system of innovation and entrepreneurship education in local universities

Abstract When the country vigorously advocates the goal of cultivating innovative and entrepreneurial engineering talents, the quality evaluation of innovation and entrepreneurship education has naturally become a part of the higher education system. However, there are few studies on the quality evaluation of innovation and entrepreneurship education in engineering majors in China. Firstly, through literature research, combined with the current development trend of quality evaluation of innovation and entrepreneurship education at home and abroad, BP neural network-based evaluation method was selected. Secondly, according to the three-element theory of education, namely, the three factors of educators, educators and education, and comprehensive research, the content of quality evaluation of innovation and entrepreneurship education in engineering majors in colleges and universities is determined, that is, from professional links, teaching links and students. Levels to build evaluation indicators. After establishing the evaluation index system, this paper uses Chengdu University of Technology as a research sample to issue questionnaires for engineering students in Chengdu University of Technology to obtain data for use, and to analyze and analyze the data by AHP, so as to obtain the weight of each indicator. Finally, based on the data collected by the questionnaire, the BP neural network data fitting and model training and optimization are carried out to determine the feasibility of the quality evaluation index of innovation and entrepreneurship education in engineering majors in colleges and universities, and to establish BP neural network evaluation model for engineering majors. The innovation and entrepreneurship education quality evaluation system provides new research methods and research ideas, enriches the connotation and breadth of the quality evaluation system of innovation and entrepreneurship education in engineering majors, and makes up for the shortcomings and vacancies in related fields.
Eye Detection using Helmholtz Principle

Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz &amp; Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through general description of these things. This paper utilizes these two principles to recognize and extract eye part from image. Java programming language and OpenCV library for image processing are used for this purpose. Good results are obtained from this proposed method, where 88.89% was obtained as a detection rate taking into account that the average execution time is about 0.23 in seconds.
Pemberdayaan Masyarakat Melalui Gerakan Literasi Perdesaan di Desa Cimanggu Kabupaten Bandung Barat

ABSTRACT: COMMUNITY EMPOWERMENT THROUGH RURAL LITERACY MOVEMENT IN CIMANGGU VILLAGE, BANDUNG BARAT DISTRICT. The community in Cimanggu Village, Bandung Barat Regency has a low literacy culture. This is due to various factors starting from the factor of the village government that does not support the literacy movement aimed at policy instruments, the cultural factors of the community who regard literacy as not a necessity and the factors that come from academics who do not disseminate information about the importance of literacy. Based on the above problems, the students of Cimahi School of Public Administration (STIA Cimahi) in the community engagement service launched a program in the form of rural literacy movement. To realize this, various activities were carried out starting from visits to village governments to encourage literacy policies at the village level. Conducting counselling to the community about the importance of literacy. Conducting literacy activities in children`s play environment that encourage children to make literacy activities a necessity and culture, as well as renovating a library in the village to make it easier for the community to access literacy infrastructure in the village.
Hybrid Machine Learning Models of Classifying Residential Requests for Smart Dispatching

This paper presents a hybrid machine learning method of classifying residential requests in natural language to responsible departments that provide timely responses back to residents under the vision of digital government services in smart cities. Residential requests in natural language descriptions cover almost every aspect of a city’s daily operation. Hence the responsible departments are fine-grained to even the level of local communities. There are no specific general categories or labels for each request sample. This causes two issues for supervised classification solutions, namely (1) the request sample data is unbalanced and (2) lack of specific labels for training. To solve these issues, we investigate a hybrid machine learning method that generates meta-class labels by means of unsupervised clustering algorithms; applies two-word embedding methods with three classifiers (including two hierarchical classifiers and one residual convolutional neural network); and selects the best performing classifier as the classification result. We demonstrate our approach performing better classification tasks compared two benchmarking machine learning models, Naive Bayes classifier and a Multiple Layer Perceptron (MLP). In addition, the hierarchical classification method provides insights into the source of classification errors.
Analysis and Comparison of Various Web Mining Techniques

The reason at the back of data overloading dilemma faced by internet users on internet includes: excessive web information and billions of users around worldwide. Because of this, providing the internet users with more intended data is a challenging task in web applications. The lots of information available on internet are a fertile field for applying data mining techniques. This is what we call Web Mining (WM). The research in WM deals with research from many fields like database, Artificial Intelligence (machine learning [supervised, semi supervised, unsupervised and reinforcement], neural network and natural language processing (NLP)) and information retrieval. Here, research related to web mining and their categories is highlighted. We also situate comparison of most popular algorithms used from the field of data mining in pattern discovery phase of the WM.
2D Features-based Detector and Descriptor Selection System for Hierarchical Recognition of Industrial Parts

Detection and description of keypoints from an image is a well-studied problem in Computer Vision.Some methods like SIFT, SURF or ORB are computationally really efficient.This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification.Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for.We demonstrate that this method performs better than using just one method like ORB, SIFT or FREAK, despite being fairly slower.
Uncertainty in Cognition and Social Practices

The article discusses the theoretical status of the category of uncertainty. Instead of the classical definitions of uncertainty as an ontological or epistemological concept, a composite theoretical construct is proposed. In classical science, the objectivist representation of the subject of research was preferred. With the nonclassical type of rationality, there rises problem of including subjective elements in a theoretical description. Attention to subject-subject-object methodologies is increasing due to the complication of communicative interactions in science and society in the digital era. One of the consequences of active innovative projective activity on a planetary scale and increasing risks is the perception in the public mind of uncertainty as a challenge. The author considers it appropriate to study the uncertainty-certainty as a paired category. The category of uncertainty was considered in philosophy, science, and management. The status of uncertainty as infinity and formlessness was recognized by Greek natural philosophers. Classical science developed the methodology of knowing the “infinite limit” through the construction of theoretical schemes (forms) and types of empirical testing. The paradox served as a means of destroying dogmatic schemes. In the context of increasingly complex communications in science, the importance of cognitive problems in the study of collective thinking and the personal beginning of creativity is increasing. Modern economic positivism is distinguished by its rejection of objective uncertainty, and the installation of the ability to efficiently manage exclusively accurate calculations is brought to extremes.
The Use of Pocket Dictionary and Online Word-For-Word Translation on Reading Skill: An Experimental Study at Sman 4 Kota Bima Academic Year 2018/2019

This research is aimed at comparing the impact of published pocket dictionary (PD) and online word-for- word (OWfW) translation on the students’ reading skill. The study was conducted at the second year students of SMAN 4 Kota Bima in the academic year 2018/2019. The method used was experimental study wherein two classes of students were purposively selected as experimental samples. One class of 32 students (i.e. XI Science 1) served as the pocket dictionary group and one class of 32 students (i.e. XI Science 2) were selected as the word-for-word online translation group. Each group was taught three types of reading texts (i.e. narrative, argument, and procedure) obtained from pedagogic texts in the textbooks and authentic texts from other (non-textbook) sources. Pre-test and post-test were administered to each group prior to and after the treatment. The data was analyzed by using multiple t- test formula comparing multiple dimensions of the dictionary use and the reading skills. The study shows that both PD and OWfW translations were equally effective in assisting the students with the reading skills. PD translation is more effective for skimming skill useful for general comprehension of reading texts, OWfW translation is more effective for helping students scan for specific information in the texts. The paper also discusses opportunities and challenges facing the students in using the dictionary types.
Target-Based Attention Model for Aspect-Level Sentiment Analysis

Aspect-level sentiment classification, which aims to determine the sentiment polarity of the specific target word or phrase of a sentence, is a crucial task in natural language processing (NLP). Previous works have proposed various attention methods to capture the important part of the context for the desired target. However, these methods have less interaction between aspects and contexts and can not accurately quantify the importance of context words with the information of aspect. To address these issues, we firstly proposed a novel target-based attention model (TBAM) for aspect-level sentiment analysis, which employs an attention mechanism between the position-aware context representation matrix. TBAM can generate more accurate attention scores between aspects and contexts at the word level in a joint way, and generate more discriminative features for classification. Experimental results show that our model achieves a state-of-the-art performance on three public datasets compared to other architectures.
APLIKASI TRACER STUDY BERBASIS WEB PADA UNIVERSITAS DIPONEGORO

This study aims to integrate the alumni information system which has not been integrated at Diponegoro University. The alumni information system previously encountered problems, namely the absence of alumni database application standards, and there was no policy requiring students to fill and update the alumni database system. The application designed in this study can be a medium that connects faculties and also requires that each alumni can fill in the data in the database. The system development method used in developing this system is the V model. This application has the facility to update work data and first salary when working. Information entered into the application can facilitate primary data collection for accreditation purposes. In this application alpha testing is done using the blackbox testing method and in beta testing using a questionnaire distribution method to input applications. Of the graduates in 2017 there are 4521 alumni who have filled in the data well, and there is an increase in 2018 as many as 6487 which indicates that this application can be a means to meet alumni data needs.
AI Werewolf Agent with Reasoning Using Role Patterns and Heuristics

The AIWolf project has been holding contests for these years to play the Werewolf game ("Mafia") by automatic agents.A difficulty of the Werewolf game is that the game is an imperfect information game, very small limited amount of information is shown to players, other than the player's own role information.Therefore, inference of probabilities for each player agent's role could not be confident theoretically, difficult to utter appropriate reasons when simply based on the probabilities.Focusing on a genuine seer and a fake seer, we implemented our player agent system that can make inferences depending on the progress of the game, defining role patterns based on the utterances of the genuine and fake seers.
Evolving Fuzzy Set-based and Cloud-based Unsupervised Classifiers for Spam Detection

Technological advancements has made individuals and organizations more dependent on e-mails to communicate and share information. The increasing use of e-mails has led to an increased production of unsolicited commercial messages, known as spam. Spam classification systems able to self-adapt over time, with no human intervention, are rare. Adaptation is interesting as spams vary over time due to the use of different message-masking techniques. Moreover, classification models that handle large volumes of data are essential. Evolving intelligent systems are able to adapt their parameters and structure according to the data stream. This study applies the evolving methods TEDA (Typicality and Eccentricity based Data Analytics) and FBeM (Fuzzy Set-Based Evolving Modeling) for online unsupervised classification of spams. TEDA and FBeM are compared in terms of accuracy, model compactness, and processing time. For dimensionality reduction, a non-parametric Spearman-correlation-based feature selection method is employed. A dataset containing 25,745 samples, being 7,830 spams and 17,915 legitimate e-mails, is considered. 711 features extracted from an e-mail server describe each sample.
Unified approach to witness non-entanglement-breaking quantum channels

The ability of quantum devices to preserve or distribute entanglement is essential in employing quantum technologies. Such ability is described and guaranteed by the nonentanglement-breaking (nonEB) feature of participating quantum channels. For quantum information applications relying on entanglement, the certification of the nonEB feature is thus indispensable in designing, testing, and benchmarking quantum devices. Here, we develop a direct and operational approach for the certification of nonEB quantum channels. By utilizing the prepare-and-measure test, we derive a necessary and sufficient condition for witnessing nonEB channels, which is applicable in almost all experimental scenarios. The approach not only unifies and simplifies existing methods in the standard scenario and the measurement-device-independent scenario, but also goes further allowing for certifying the nonEB feature in the semi-device-independent scenario.
Digital instruction or the digitalization of instruction in modern ICT environment

Latest research results and my experience as well underline that the disciplinary mission of digital instruction, in a stricter sense, digital pedagogy, is to reflect all challenges, tasks, and innovation options facing the digital citizens of today’s continuously changing world. In addition to acquiring the so-called key qualifications, the five generations of the digital world should be familiar with all aspects of digital competence if they want to lead a successful and productive life.