Reviewerly/exHarmony huggingface dataset:
Maxims Deviation and Politeness Scale of Uang Panai Mahar Film by Using Leech's Perspective

The lack of knowledge about the application of maxims and politeness scale in everyday life cause more violation of politeness in communication. Speech deviations also occur in the Uang Panai Mahar film which raises the cultural theme of a moral message..This study aims to discuss and describe the maxims deviation and politeness conversation from film. The data of this study are the form of maxims deviation and politeness scale by using Leech perspective. The data source in this study is Uang Panai Mahar film, which published by Makita Cinema Production, on August 25, 2016. The film lasted for 1 hour, 59 minutes and 42 seconds. This study used descriptive qualitative method. This study found out some of maxims deviations and politeness scales, they were 1) deviation of wisdom, 2) deviation of generosity, 3) deviation of rewards, 4) deviation of simplicity, 5) deviation of accuracy and 6) deviation of sympathy. Meanwhile the politeness scale of this film were 1) the loss and gain scale, 2) the choice scale, 3) the sustainability scale and 4) social distance scale.
A Hardware-Software Co-designed Low Latency AES-RC4 Cryptosystem

Security of data is a primary need for all the system. The AES-RC4 hybrid cryptosystem gives the combine advantages of Advanced Encryption Standard (AES) To data encryption and decryption, to secure the key used for data encryption-decryption Rivest Cipher 4 RC4 is used. This system is designed using the Co-designed approached where AES and RC4 run on the NIOS II integrated development environment (IDE) soft-core. The implementation is on Cyclone IV FPGA, Rijndael algorithm program supported " NIOS II + FPGA" are able to do better performance in the area of latency where it comparatively uses low resources. The results are analysed in the IDE console window of a personal computer system.
Penerapan Sistem Penunjang Keputusan Menggunakan Algoritma Naive Bayes Pada konsep Human Resource Information System (HRIS) (Studi kasus :Penerusan Kontrak Kerja Karyawan di PT. XYZ)

One of the valuable assets in a company is human resources (HR). Human Resource Information System (HRIS) has emerged as one of the drivers of competitiveadvantage and strategic decision making tool. One of the HRIS task is employee recruitment. Employees become an important role. Therefore, this research is conducted forclassification of employee status determination using the Naïve Bayes methods. One of the duties of employees is to provide service to customer in the process of purchasing goods until the payment transaction process directly. Because of the large number of contract employees at the time of certain events, it requires companies to select every three months for the continuation of the work contract period for employees according to store needs so that the company's employee payroll expenses do not exceed the budget. One of the criteria is for being able to work in flexible groups between the ages of 17 and 25 for contract employees with a minimum of high school or vocational education. The purposes of this study are to design and build a Decision Support System application for the Continuation of Employee Employment Contracts Using the Naïve Bayes Method at PT. XYZ Retail. The result of the research is the application using the naïve bayes method with an accuracy rate of 90%.
PENGARUH PENGGUNAAN TEKNOLOGI INFORMASI DAN MEDIA SOSIAL TERHADAP PRESTASI BELAJAR MAHASISWA STMIK SINAR NUSANTARA

The objectives of this study are : (1) To measure and test the effect of the use of information technology and social media on student achievement in STMIK Sinar Nusantara Surakarta. (2)To measure and test the interaction of the use of information technology and social media on student achievement in STMIK Sinar Nusantara Surakarta. The number of samples in this study were 50 respondents, with. The sampling technique uses purposive sampling.The results of the regression analysis found that there is a positive and significant influence of the use of information technology and social media on the learning achievement of students majoring in STMIK Sinar Nusantara Surakarta.T test and F test results prove that the information technology and social media variables have a positive and significant effect both partially and simultaneously on learning achievement. Based on the coefficient of determination which has a positive value of 0.397 shows that the learning achievement of students of the STMIK Sinar Nusantara Surakarta can be explained by the information technology and social media variables by 39.7%, while the remaining 60.3% is explained by other factors which was not observed in this study.Keywords: information technology, social media, learning achievement and regression
Malicious Items Detection at Public Places using Deep Learning Methods

To provide effective security in crowded or public areas in today's world is a big challenge for us.One of the major challenges is to detect or monitor potential threats such as explosive items or bombs (Abandoned luggage items).In this paper we propose an approach for automatic detection of abandoned luggage and alerting the security alliances ,We use deep learning to train the system with a set of images, these images were given to the trained system which is going to visualize the objects in the image and calculate the distance between objects if the object is person and baggage or only baggage.If the distance is greater than a threshold distance limit then the system is going to raise an alarm for the security alliances.
CrossNet: Latent Cross-Consistency for Unpaired Image Translation

Recent GAN-based architectures have been able to deliver impressive performance on the general task of image-to-image translation. In particular, it was shown that a wide variety of image translation operators may be learned from two image sets, containing images from two different domains, without establishing an explicit pairing between the images. This was made possible by introducing clever regularizers to overcome the under-constrained nature of the unpaired translation problem. In this work, we introduce a novel architecture for unpaired image translation, and explore several new regularizes enabled by it. Specifically, our architecture comprises a pair of GANs, as well as a pair of translators between their respective latent spaces. These cross-translators enable us to impose several regularizing constraints on the learnt image translation operator, collectively referred to as latent cross-consistency. Our results show that our proposed architecture and latent cross-consistency constraints are able to outperform the existing state-of-the-art on a variety of image translation tasks.
Analysis of Law Discourse Through Van Dijk Model Approach

This paper present analysis of law discourse relates to the study of language or language usage.The analysis approach that is used in this research is a critical model of discourse analysis as known as Critical Discourse Analysis (CDA) is seen in the use of speech and writing as social practice.The data collected by using a library research from manuscript related to law, and analysis model uses Van Dijk approach for analysis.The results of the research indicate that the use of certain words, sentences, certain styles is not merely seen as a way of communicating, but is seen as communicating the politics a way to influence public opinion, create support, strengthen legitimacy, and remove opponents or opponents.The significance of this research is how the reader not only get information from a law discourse but also get meaning what the writer tries to convey through the text from an analysis by using critical discourse approach.
Using Morphological Operation and Watershed Techniques for Breast Cancer Detection

&lt;pre&gt;Breast cancer is one of the leading causes of mortality between women, with one in eight women diagnosed with the disease, but early detection can reduce death rates. Therefore, continuous effort is being made to advance more effective methods for the early and effective diagnosis of breast cancer with high accuracy without human intervention. Classical attempts were manual, time- consuming and ineffective in many situations. The purpose of this work is to detect and locate the presence of malignant tissues in the breast using the morphological technique in mammogram images to diagnose breast cancer because morphology is one of the most reliable methods for early detection of breast cancer. The proposed algorithm is developed using watershed segmentation after the preprocessing is completed by the median filter to eliminate any expected noise, and contouring the tumor by morphological techniques to take the best diagnostic for breast cancer in a mammogram image. Good results are obtained for the measurements used like MSE, PSNR, SNR, entropy for the mammogram images. &lt;/pre&gt;
Registration Cards of Kazan Doctors as a Source on the History of the Russian Intelligentsia during the Civil War

Registration cards of doctors, a little-studied source on the history of the Russian intelligentsia during the Civil War, were studied.The analysis is based on more than 200 cards collected by the Health Department of the Kazan Province Executive Committee of the Council of Workers, Peasants, and Red Army Deputies in late September 1918, following the liberation of Kazan from the Komuch and White Czechs' troops.They have been stored in the State Archive of the Republic of Tatarstan.A collective portrait of the social group under consideration was created.The interaction and relations between the medical community of the large provincial city caught at the center of military activities and a new Soviet government, which used the method of questionnaire surveys as a tool of staff policy in the Soviet health care.A method was proposed for working with registration cards of doctors, both a typical example of public documentation in the first years of the Soviet era and, on the other hand, a rather specific source that requires special research tools.The information value of the studied source and its place among other questionnaire materials of the early Soviet period in the context of studying the problem of "intelligentsia and authorities" were revealed.
Peranan Keterampilan Berbahasa Inggris Dalam Industri Pariwisata

Tourism industry in Indonesia is being greater and greater. World Bank even considered as the core business of Indonesia. The development of this industry should be in line with the development of human resources’ quality, especially in communicating in English. This was designed as library research aiming at diving deeper into the roles of English in tourism dan hospitality industries. There is 1 problem analyzed through this writing which was how are the roles of English in tourism industry? The data were collected through some relevant journals on English for tourism, the roles of English in the hospitality and tourism industries, as well as the importance of English in the hospitality and tourism industries. It was found that English possesses several important roles. They are communicative role, integrative role, lingua-franca role, relationshipfostering role, usiness/ economic role, and functional role. Based on those important roles, it is essential for those who are will to work in the hospitality and tourism industries to be able to communicate in English. Keywords: Roles, Skill, English, Tourism Industry
Structured prediction models for argumentative claim parsing from text

The internet abounds with opinions expressed in text. While a number of natural language processing techniques have been proposed for opinion analysis from text, most offer only a shallow analysis without providing any insights into reasons supporting the opinions. In online discussions, however, opinions are typically expressed as arguments, consisting of a set of claims endowed with internal semantic structure amenable to deeper analysis. In this article, we introduce the task of argumentative claim parsing (ACP), which aims at extracting semantic structures of claims from argumentative text. The task is split into two subtasks: claim segmentation and claim structuring. We present a new dataset on two discussion topics with claims manually annotated for both subtasks. Inspired by structured prediction approaches, we propose a number of supervised machine learning models for the ACP task, including deep learning, chain classifier, and joint learning models. Our experiments reveal that claim segmentation is a relatively feasible task, with the best-performing model achieving up to 0.37 and 0.79 exact and lenient macro-averaged F1-score, respectively. Claim structuring, however, proved to be a more challenging task, with the best-performing models achieving at most 0.08 macro-averaged F1-score.
Development of a Hybrid Real Estate Recommender System

In the current study, the details of a real estate recommender system developed for Zingat.comare discussed.The system developed is a hybrid of collaborative and content filtering approaches.Scalable methods in both the model building phase and in the recommendation list generation phase were used to work on the data set of the project (as of 2018, 300k listings and 6 million monthly sessions).This study also explained the challenges faced in developing and implementing the system, the recommendation techniques used to overcome these challenges, and the final product used for recommendation.Based on these, future recommendations are discussed.
An Evaluation of the Assessment Measure for Novice L2 Learners' English Writing

Academic writing poses a consistent challenge in many students' university career.This study conducted a systematic diagnostic assessment to identify specific discourse strengths and weaknesses in first-year undergraduate students' English writing.Our study found that the top three prevalent weaknesses are related to overall discourse awareness, syntactic proficiency, and idea development.Based on the knowledge of students' specific strengths and weaknesses, more targeted remediation prescription can be designed and delivered for maximal support in facilitating first year undergraduate students' development of English writing proficiency in the classroom setting.
Development of Chatterbot using Python

Over recent years we have seen various customs for conversational agents.Chatterbots are conversational agents where a computer program is designed to vitalize an intelligent conversation with the users [7] .These are virtual person who can effectively talk to any human being using interactive textual skills.These are programs that work on Artificial Intelligence (AI) & Machine Learning Platform [1] .NLP plays an important role in training the chatbot.The concept of chatbots came into existence to check whether the machines could trick users and make them think that they are actually talking to humans and not robots.As this idea grow popularly, many different companies started developing chatterbots for different needs [6] .There are many platforms to build the chatbot, this paper mainly concentrates on developing chatbot using python.
Cognitive Offloading: Can ubimus technologies affect our musicality?

An interaction design that lean towards musical traits based on and constrained by our cognitive and biological system could, not only provide a better user experience, but also minimize collateral effects of excessive use of such technology to make music. This paper presents and discuss innate abilities involved in musical activities that - in the authors´ viewpoint - could be considered in design guidelines to computer music technologies, especially those related to ubimus.
A Gaussian process-based Incremental Neural Network for Online Clustering

This paper proposes a two-stage online clustering algorithm. First, it generates cluster prototypes using a Gaussian process-based Incremental Neural Network (GPINN), where 1) the network structure is updated in an online adaptive mode and 2) both combinatorial effects and the similarity between the weight vectors of nodes are considered. Second, clusters are detected by constructing the minimum spanning tree of GPINN. Besides, some of its properties are discussed. The experimental results on both synthetic data and real-world data show that our method achieves remarkable improvement in clustering accuracy compared with previous incremental neural network algorithms.
Opportunities and Challenges of implementation of Peer to Peer Block Chain Technology in the Higher Educational Institutions

According to Merriam-Webster Block chain technology is "an open, distributed ledger that can record transactions between two parties efficiently and in a verifiable and permanent way."The term "distributed ledger" refers to the fact that the ledger on which transactions are recorded is shared by several participants in the Block chain.As it is not owned or fully controlled by a single entity.Block chain is described as "open", it is typically in reference to the open-source nature of the code base that underlies most Block chain protocols.There are two types of chain exist, public and private chains that are built using open source code Now a day's Block chain technology is gaining popularity due to its extraordinary features.Block chain is having lots of application in the various fields such as banking, healthcare, Enterprises, agriculture etc.In our research paper we are discussing about the implantation of block chain technology in the higher educational fields and its opportunities and challenges.
Initial Displacement Estimation Based on ESA in Improved Digital Volume Correlation and Its Application

In order to improve the algorithm efficiency in point matching and reduce the error of displacement field in deformation calculation, an Improved Digital Volume Correlation (IDVC) method is proposed. Aimed at the problem that the accuracy of initial displacement estimation of DVC has a great influence on the convergence calculation accuracy by the sub-voxel measurement algorithm, the coordinates of the estimated points in deformation are quickly matched by the Explosion Search Algorithm (ESA), with the displacement vectors obtained. Then, the non-physical fluctuation of displacement field and the wrong strain concentration are suppressed in regularization. Finally, the deformation information obtained by correlation search is substituted into the iterative least squares algorithm to attain the sub-voxel precision displacement. The results of the simulation experiment and concrete uni-axial compression experiment show that the computational efficiency by the proposed method is 20.44% higher than that by the traditional DVC method, and that the accuracy level of displacement field measurement reaches 0.001 voxels.
Belief Functions on Distributive Lattices

The Dempster-Shafer theory of belief functions is an important approach to deal with uncertainty in AI.In the theory, belief functions are defined on Boolean algebras of events. In many applications of belief functions in real world problems, however, the objects that we manipulateis no more a Boolean algebra but a distributive lattice. In this paper, we extend the Dempster-Shafer theory to the setting of distributive lattices, which has a mathematical theory as attractive as in that of Boolean algebras.Moreover, we apply this more general theory to a simple epistemic logic the first-degree-entailment fragment of relevance logic R, provide a sound and complete axiomatization for reasoning about belief functions for this logic and show that the complexity of the satisfiability problem of a belief formula with respect to the class of the corresponding Dempster-Shafer structures is NP-complete.
SPECIAL FEATURES OF IMPLEMENTATION OF THE PROGRAM FOR DEVELOPMENT OF PROFESSIONALLY ORIENTED MANAGEMENT SKILLS MASTER,S DEGREE CANDIDATES

Statement of the problem. The modern stage in the development of education determines new requirements for the professional activity of a teacher. A modern teacher, especially a holder of a master,s degree in Pedagogical Education, should have managerial skills. Research by L.D. Gordin, M.I. Rozhkov, L.I. Umansky and others confirm this fact. The absence in pedagogical science of a unified understanding of this problem proves relevance of this study. The purpose of the article is to analyze the content, special features of the implementation of the program for the development of professionally-oriented managerial skills among future master,s degree holders and the results of experimental work on its implementation. Methodology (materials and methods). The study of the works by Russian and international scientists, normative documents in the field of education, the survey of teachers and school leaders made it possible to identify and justify professionally-oriented managerial skills of the master,s degree holders in Pedagogical Education and to develop a program for development of these skills. The article shows the content and special features of the implementation of this program, formulates and discloses three organizational and pedagogical conditions that ensure the implementation of the program: enrichment of the content of education with project training in the field of educational activity management, pedagogical support in the project environment, enhancement of the development of managerial skills by solving organizational and pedagogical tasks in the workplace. Research results. The article reveals the essence of the concept of professionally-oriented managerial skills for master,s degree candidates in Pedagogical Education, defines the main groups of these skills and their content. The program for the formation of professionally-oriented managerial skills among future master,s degree holders is presented. The stages of its implementation are highlighted and characterized. The articles also highlights the results of experimental work on the formation of professionally-oriented managerial skills among future master,s degree holders in Pedagogcial Education at the Krasnoyarsk State Pedagogical University named after V.P. Astafiev. Conclusions. As a result of the research, the content and features of the implementation of the program for the formation of professionally-oriented managerial skills of future master,s degree holders are analyzed.
Penerapan Model Pembelajaran Time Token untuk Meningkatkan Keterampilan Berbicara Siswa

The current study aimed to find out whether the learning model called “Time Token” could improve Indonesian speaking skill of the students from VA class at SDI Karang Anyar, Rejang Lebong. This study applied a classroom action research undertaking two cycles. Each cycle comprised four stages of activities ranging from planning, implementation, observation, to reflection. The techniques deployed to collect the data were: observation, test for exercise, and documentation. The data of test were analyzed with the means and percentages of learning results, in the meantime the analysis of observation data used teachers and students’ observation sheets with the criteria of good, moderate, and less. The results of the present study demonstrated that students’ speaking skill on Indonesian language lesson in VA class at SDI Karang Anyar experienced improvement after “Time Token” learning model was implemented. The forgoing could be viewed from the mean of 63.7 and the classical learning mastery of 47.6%. After the implementation of “Time Token” learning model, students’ Indonesian speaking skill in the material vis-a-vis commenting on factual matters experienced improvement from cycle I to cycle II. In cycle I, the mean of students’ speaking skill was 72.1, and it increased to 78.8 in cycle II. The learning mastery was 71.4% in cycle I and 95.2% in cycle II. The teachers’ observation result in cycle I was 32.5 categorized as good, and it increased to 37.5 categorized as good. The observation result in respect of students’ activities in cycle I was 30 categorized as moderate, and in cycle II it increased to 37 categorized as good.