Reviewerly/exHarmony huggingface dataset:
Seasonal Variation and Malaria in Endemic Mangalore City in South India

Background: In the year 2017 India has contributed to 4% of global malaria cases and Mangalore is endemic to malaria. Malaria transmission also depends on the season of the year, i.e. the wet or dry season. Regardless of huge endemicity and massive health burden, at present limited data has been documented on malaria prevalence and factors contributing to prevalence of malaria and its association with seasonal factors in Mangalore region. Objective: To study the seasonal variations in malaria burden and species prevalence in Mangalore. Settings and Design: This is a cross-sectional study conducted at District hospital. Methods and Material: Patients with microscopically confirmed malaria attending the District hospital were included in the study. Demographic details were collected from participants. Statistical Analysis Used: Descriptive statistics. Results: In this region malaria is present all around the year and Plasmodium vivax is more predominant than Plasmodium falciparum . The number of cases peaks during the rainy season suggesting that high rains provide an ideal environment for malaria transmission. Conclusions: A complex relationship exists between rainfall, temperature, occupation and malaria. Implementing malaria elimination interventions such as preventing water clogging, cleaning the water bodies and increasing awareness for use of prevention practices might help in reducing malaria burden in Mangalore.
О надежности, безопасности и читабельности языков программирования на примере языка Ада

A few small suggestions of language design reflect the author's views are presented. These suggestions are mainly related to the reliability and safety of simple, typical structures and statements in programming: typification, compile-time elaborations of variables, status of variables, high-level statements, etc. The programmers often spend working time with similar constructions. From mathematical point of view these suggestions do not effect seriously on the complexity and efficiency of calculations; they are designed exclusively to help a programmer to write reliable, secure and clear programs. These suggestions are illustrated on Ada language, which is very suitable for this purpose, but they can be applied in other languages also.
Multi-terminal Experimental System Based on Wireless Local Area Network

Abstract Aiming at the problems of single experimental data display, difficult data recording, poor human-computer interaction and low security for an experimental system, a multi-terminal experimental system based on Android operating system and wireless local area network was designed. Based on the Android operating system and wireless LAN, the system combines MySQL database, Web server, and LabVIEW software, and adopts modular design, realizes real-time collection and recording of experimental data during the experiment, and multi-parameters cross hardware display, good human-computer interface and remote status monitoring.
Hubungan Interaksi Sosial dan Motivasi belajar dengan Hasil Belajar Peserta Didik Kelas V SD

The purpose of this research was to investigate a positive and significant correlation of social interaction between students with thematic learning result, learning motivation with thematic learning result, social interactions between students with learning motivation, and social interaction between students and learning motivation together with thematic learning result. This type of research is ex-postfacto correlation. The technique of collecting data  were observation, interview, documentation study, and questionnaire. The instrument used is questionnaires using a Likert scale which previously tested the validity and reliability. The data were analyzed by using of product moment and multiple correlation. The results showed there was a positive and significant correlation of social interaction between participants with thematic learning result, learning motivation with thematic learning result, social interactions between students with learning motivation, and social interaction between students and learning motivation together with thematic learning result. Penelitian ini bertujuan untuk mengetahui hubungan yang  positif dan signifikan antara:  interaksi sosial antar peserta didik dengan hasil belajar tematik, motivasi belajar dengan hasil belajar tematik, interaksi sosial antar peserta didik dengan motivasi belajar, serta interaksi sosial antar peserta didik dan motivasi belajar secara bersama-sama dengan hasil belajar tematik.  Jenis penelitian ex˗ postfacto korelasiTeknik pengumpulan data dengan observasi, wawancara,  studi dokumentasi, dan kuesioner.  Instrumen pengumpul data berupa angket dengan menggunakan skala likert, yang sebelumnya diuji validitas dan reliabilitas serta menggunakan analisis data korelasi product moment dan multiple correlation. Hasil penelitian terdapat hubungan yang positif dan signifikan antara: interaksi sosial antar peserta dengan hasil belajar tematik,  motivasi belajar dengan hasil belajar tematik, interaksi sosial antar peserta didik dengan motivasi belajar, serta interaksi sosial antar peserta didik dan motivasi belajar secara bersama-sama dengan hasil belajar tematik. Kata kunci: interaksi sosial, motivasi, hasil belajar tematik.
Machine Learning to Perform Segmentation and 3D Projection of Abnormal Tissues by Endoscopy Images

Images obtained by endoscopy technique provides the normal direction of the tissue contour. This provides the important anatomical parameters which can be used for segmentation algorithms. Due to the variation of tissue image sizes, the values of intensity for the tissues is typically ununiformed and also have noisiness by nature. So, identifying the direction in normal by a single iteration is unreliable. A multi (factor)-iteration algorithm has been developed for estimating the direction normal to the edge of defective tissue. From experimented results, the estimation reliability is formulated by multiple iterations. The estimation post last iteration corrects the direction normally. We have obtained the balance at all points during the normal direction estimation and it is used by the Edge Detector. The implementation results obtained prove that our proposed algorithm reduces the amount of astonishing boundaries and gapes in the actual outlines. Thus improves the quality of segmentation and 3D projection. The obtained corrected output could also be used in the removal of false edges in post processing. The performance outcome of our proposed algorithm is measured at multiple iterations and results are tabulated.
The Study of the Image Orientation of the Managerial Activities of Future Teachers of Physical Education

The purpose of this study is a theoretical justification of the essence and content of the concepts of “managerial activity”, “image”, “motivation” and the description of the results of an experimental study of the image orientation of the managerial activity of future teachers of physical education. Analysis of the development of the image orientation problem of managerial activity of future physical education teachers based on the study of philosophical, psychological and pedagogical, special literature, regulatory documents and analytical materials of the Ministry of Education and Science of the Republic of Kazakhstan, generalization and interpretation of scientific data, experiment. To determine the motivation for success in the managerial and image activities of future teachers of physical education, the following methodology was applied: test “Motivation for success and fear of failure” by                A.A. Rean. The ascertaining experiment covered 3 universities from 3 cities of the Republic of Kazakhstan: the Kazakh Academy of Sports and Tourism (Almaty), West Kazakhstan State University named after M. Utemisova (Uralsk), Pavlodar State Pedagogical University (Pavlodar). The results of the ascertaining experiment showed that the process of studying the image orientation of the managerial activity of future physical education teachers corresponds to a level below the average. This study allowed us to obtain the following conclusions. The essence of the concepts “managerial activity”, “image”, “motivation” based on the analysis of scientific psychological, pedagogical and special literature was substantiated, the content of the concept of “managerial activity” was clarified. Experimental work was carried out to determine the level of image orientation of the managerial activity of future physical education teachers. The authors tried to determine the content of the concepts of “managerial activity”, “image”, “motivation” and for the first time to identify the real state of the image orientation of the managerial activity of future physical education teachers with the help of an experimental study, using the methodology “Motivation for success and fear of failure”.
SISTEM PAKAR DALAM PENENTUAN PEMILIHAN BIBIT PISANG UNGGULAN BERBASIS WEB DENGAN MENGGUNAKAN METODE FORWARD CHAINING

Bananas are native to Southeast Asia. The plant of the Musaceae tribe has the Latin name Musa paradisiaca. Banana production in Indonesia is quite large, even Indonesia became one of the largest banana producers in the world. National banana production continues to increase every year, for example from 2,308,379 tons (in 1988) to 2,417,760 tons (in 1989). The largest banana-producing region is located in Java (Suhardi et al, 2002). An expert system is a computer-based system that uses knowledge, facts, and reasoning techniques to solve problems that can usually be solved only by experts in the field. Forward Chaining is a search technique that begins with known facts, then matches those facts to the sections IF of the rules IF_THEN. Based on the results of the implementation found that the application program expert system dpat facilitate the farmers in the determination of seeds of banana seeds in accordance with the criteria and this application can run well and easy in its use.
UAV – Virtual Migration Based on Obstacle Avoidance Model

In recent years, the obstacles avoidance technology of unmanned aerial vehicles has been developed rapidly. It takes a lot of manpower to control un-manned aerial vehicles, so many researches use reinforcement learning to make unmanned aerial vehicles fly autonomously. In the real environment using rein-for cement learning to train aircraft is an expensive and time-consuming work, because reinforcement learning is a way to learn from mistakes, so there are often bumps in the learning process. In Wu’s research, they trained a good model, but the realistic environment and simulation environment differs very big, so we will train this model again and transferred to the real environment, makes unmanned aerial vehicle in the realistic environment can use cheaper and quickly achieve the same task.
MENINGKATKAN KOMPETENSI GURU DALAM MENYUSUN BUTIR SOAL BERMUTU MELALUI PROGRAM WORKSHOP DI SD KATOLIK 079 NANGARASONG, SIKKA NUSA TENGGARA TMUR

Research based on the phenomenon is still many teachers who have difficulty in planning and holding daily tests. In addition, teachers often do not realize that assessments made through daily tests are not in accordance with the learning objectives and the learning process. So a research was conducted on increasing the ability of teachers to compile daily test questions through workshops. The research method used is classroom action research with two cycles. The number of respondents studied was 13 teachers. In cycle 1 an average of 2.82 or 53.84% of teachers was met, then cycle 2 gained an average of 3.72 or 90%, fulfilling the criteria. These results indicate a significant increase in teacher competence in preparing daily test items through workshop activities
ALGORITMA FP-GROWTH UNTUK MENGANALISA POLA PEMBELIAN OLEH-OLEH

Ummi Aufa Judge Center is one of the companies that provide typical souvenirs of West Sumatra. Visitors who come are guests from outside of West Sumatra, the time given guide for shopping is very limited, and the placement of goods in the store is not in accordance with consumer behavior in buying goods simultaneously in one time. This study aims to increase sales at the Center By-By Ummi Aufa Hakim. The data to be processed in this study is taken from invoice sales transaction. Data is processed by the Association Rule  method using FP-Growth Algorithm, for testing results done with applications that have been designed using MySQL PHP programming language. The results of the test obtained the Association Rule s of products purchased simultaneously in one time, ie if you buy 250g Yellow Whisk, then buy Sj. Balado Redah 250gr with 20% support value and Confidence value 100%, if buy Ganepo 250gr, then buy Sj. Red Balado with 20% support value and Confidence 100% value, and if buy Krk. Small Kaliang 250gr, then buy Sj. Balado Redah 250gr with 20% support and Confidence 100%. From the test results can be seen that the application of data mining using FP-Growth Algorithm can be used to analyze consumer shopping patterns, and can be a recommendation in the layout of the product on the preparation rack. So the products are often purchased simultaneously placed adjacent by the store
Predictive Maintenance of Water Purification Unit for Smart Factories

In recent years, the applications of the smart factory are very popular. Predictive maintenance is one of the issues. Some research achieved the goal of predictive maintenance with Artificial Intelligence (AI). Here we focus on the local scrubber (LSR) system, a water purification and recycling system. This paper proposed a machine learning model to solve predictive maintenance problem. The device learns the pattern of input data through the RNN model and classify the different state of device. We can know the current situation of the device and judge whether it is about to be replaced. As far as we know, this is the first predictive task maintenance in the LSR system and has an accuracy of 84% in the datasets of different years. The smart factory will come true while the LSR system can be reduce cost, manpower, time and money with predictive maintenance.
Integer Programming Approach to the Data Traffic Paths Recovering Problem

In this paper, we propose a novel approach to recovering path relationships in communication networks. The path relationship is one of the key input data which is necessary for network operation and maintenance. We have a continuous network transformation, upgrades, expansions, service allocations, thus the network physical topology and paths relationship are permanently changing with high frequency. Our approach is aimed at recovering the path relationships through flow information of each arc in the network. Getting the flow information is not a big technical problem and its control is included in the basic toolbox for network monitoring. We consider two scenarios which lead us to integer linear programs. The both of them minimize the flow deviation, where in the first one we look for a directed spanning tree (r-arborescence) and, in the second one—more general origin/destination paths (OD-paths). We propose mixed integer linear programming formulations for both problems. Their feature is that they contain the non-polynomial number of constraints which are considered implicitly by the cutting planes approach. The preliminary computation results showed that the large-scale instances of the first scenario can easily be solved. At the same time, the optimal solutions of second scenario problems can be found only on small- and medium-size instances, which inspires for the further research.
Недвоичные криптографические функции для генерации блоков подстановок симметричных шифров

In the paper considers the traditional way of describing S-blocks through a set of component Boolean functions.non-binary functions were used to represent s-blocks compactly and formalize the method of generating them. Some results of computational search for S-blocks were presented using the proposed approach, where the generated S-blocks have improved properties based on non-linearity and autocorrelation indicators.
Building on the Basics: Validation, Authentication, and Plugins

In the previous chapter, we were able to show you how to get your first tiny app up and running. Now, we’ll add the topping to the pizza. Before we dive into validating our requests, we organize them. After organizing our code, we validate our input using a library called Joi (pronounced joy), authenticate our routes, and build a minimal plugin to appreciate modularized code.
Control of a Set of Unicycle-Like Robots Using an Approximate Linearisation

The paper deals with an alternative approach to control of a group of unicycle-like robots. The proposed algorithm is based on an approximate linearisation taking advantage of a dynamic feedback employing a transverse function. As a result, unicycle-like robots can be roughly perceived as unconstrained planar systems for which typical potential-like navigation methods can be used. In this paper both position and orientation stabilisation problem are discussed and a basic navigation algorithm for dynamic and static circular obstacles is proposed. The considered control/navigation method is verified numerically for the selected simulation scenario.
Pedagogical Conditions for Developing Special Competencies of Pre-service Primary School Teachers Using the Project Method

Today, the improvement of the quality of higher education requires a deep understanding of education, its essence, and purpose, the selection of its current tasks, trends, and prospects for development. To ensure the development of special competencies of HEI graduates, it is necessary to develop their project-related skills during the whole period of training, when studying all disciplines of the curriculum. It implies the simplest problem tasks and complex real projects demanded by vocational educational and industrial institutions. In accordance with the analysis of psychological and pedagogical literature, the authors have identified five groups of dissertation studies that are the theoretical foundation for the research of various aspects of the development of special competencies of pre-service primary school teachers using the project method, and carried out experimental research, during which special competencies were developed using the project method in school practice.
PERFORMANCE EVALUATION OF THE ENHANCED HASH ALGORITHM USING VECTOR ANDHASH FUNCTION

Hashing is well-known due to its usefulness and rapid access to data in many Information Technology areas such as in networking and NLP. It i s alsovery useful in the fields of Information Retrieval, as well as, Text Mining. Items are distributed in the hash table by the hash function. However,collision occurs when more than one items have the same value hashed. The collision resolution will resolve such problem. The algorithm wasenhanced by modifying the lookup procedure using another hash function and Vector data structure, to improve the time consumed during lookupwhile resolving the collision. The objectives are to determine the success rate of the modified hashing algorithm in resolving hash collisions; toevaluate the performance and compare the modified hashing Algorithm with the original linked list chained algorithm using the same stringdatasets in terms of Lookup time, Work Efficiency; and the count of Memory Accesses in the search procedure, as well as its Time Complexity.Results showed that the enhanced hashing algorithm has successfully resolved collision on any table and data sizes. The Big O notation analysisshowed that the time complexity of the search operation is O(1). It also guarantees that every search operation can achieve 1 or 2 memory accesseson different data and table sizes.
BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.
Answer Set Programming in Proofdoku

Proofdoku is an AI-based game design that extends Sudoku. In addition to playing by the rules of the traditional logic puzzle, players must explain their reasoning. An AI system checks this reasoning and provides hints that guide the player to discover new reasoning patterns for themselves. Co-developing the game design and the AI system, implemented using the technology of Answer Set Programming (ASP), guided us to include features that depend on high-complexity combinatorial search and optimization. We developed Proofdoku to better understand the implications of designing and deploying game systems that depend on ASP for live interaction. This paper offers design tradeoffs and makes suggestions for future deployments of ASP-backed game designs.
Speech Signal Analysis for Language Identification Using Tensors

Language detection is the first step in speech recognition systems. It helps these systems to use grammar and semantics of a language in a better way. Due to these reasons, active research is being carried out in language identification. Every language has specific sound patterns, rhythm, tone, nasal features, etc. We have proposed an approach based on Tensor that uses MFCCs for determining the characteristic features of a language that can be used to identify a spoken language. Tensor based algorithms perform quite well for higher dimensions and scale quite well as compared to classic maximum likelihood estimation (MLE) used in latent variable modeling. Also, this approaches does not suffer from slow convergence and require fewer data points for learning. We have conducted language identification experiments on native Indian English and Hindi for some chosen speakers, and an accuracy of around 70% is observed.
Inference-Based Strategy Alignment for General-Sum Differential Games

In many settings where multiple agents interact, the optimal choices for each agent depend heavily on the choices of the others. These coupled interactions are well-described by a general-sum differential game, in which players have differing objectives, the state evolves in continuous time, and optimal play may be characterized by one of many equilibrium concepts, e.g., a Nash equilibrium. Often, problems admit multiple equilibria. From the perspective of a single agent in such a game, this multiplicity of solutions can introduce uncertainty about how other agents will behave. This paper proposes a general framework for resolving ambiguity between equilibria by reasoning about the equilibrium other agents are aiming for. We demonstrate this framework in simulations of a multi-player human-robot navigation problem that yields two main conclusions: First, by inferring which equilibrium humans are operating at, the robot is able to predict trajectories more accurately, and second, by discovering and aligning itself to this equilibrium the robot is able to reduce the cost for all players.