Reviewerly/exHarmony huggingface dataset:
A NOVEL PRIVACY PRESERVING BASED ENSEMBLE DEEP LEARNING FRAMEWORK FOR LARGE DIMENSIONAL MEDICAL DATASETS

With the rapid growth of data size, computing power and high dimensionality, it is essential to implement a novel privacy preserving model in deep learning framework. However, most of the traditional machine learning applications are integrated in deep learning framework on large databases, it is essential to secure the large sensitive patterns that are generated by the machine learning approaches before uploading to the cloud storage. As a result, how to design and implement a novel privacy preserving deep learning model (PPDLM) over high dimensional cloud data becomes a challenging task. Traditional privacy preserving deep learning frameworks are depends on data transformation approaches rather than the cryptographic approach due to high computational memory and time in cloud computing. In the real time multi-user applications, multiple datasets are distributed across the multiple users for privacy preserving. As the data size of multi-user applications increases, traditional PPDLM models require high computation memory and time for preserving the machine learning patterns. To overcome these problems, a novel data partitioning based privacy Preservation deep learning model is implemented on high dimensional datasets. Experimental results proved that the present system has high computational accuracy with privacy in the patterns compared to the existing models.
JigsAR: A Mixed Reality System for Supporting the Assembly of Jigsaw Puzzles

Augmented reality used to be only possible for science fiction. However, nowadays it is used in different areas for the improvement of human life. Even jigsaw puzzles could be improved by AR, and that’s the purpose behind JigsAR: transforming a classic into something new. JigsAR is a web-based solution that is made with Javascript to improve the assembly of a jigsaw puzzle. JigsAR uses color quantization and image histograms to compare the piece with a database and indicate to the user the three most probable correct places. Two hypotheses were tested with twenty-five users to evaluate the tool effectiveness. In the end, the user test results are discussed from the point of view of ergonomics and technology usage.
An Intelligent Tutoring System with Adaptive Exercises Based on a Student’s Knowledge and Misconception

Assessment is an important part of learning that should be not only to assess students' knowledge, but also any misconceptions they might make. The teacher may have difficulty in identifying it because of the diversity of students' abilities. To solve this problem, we propose an Intelligent Tutoring System (ITS) that offers adaptive exercises. In adaptive exercises, the next problem to be solved by a student is chosen by considering her performance during learning. Unlike former ITS that is mostly based on students' knowledge, the proposed ITS uses students' knowledge and misconceptions to perform adaptation. This paper discusses the implemented learning scenario and domain model structure to support adaptive exercises. Furthermore, it discusses information about the student recorded in the student model and how it is organized and inferred to find the most appropriate problem.
METODE MERKLE HELLMAN UNTUK ENKRIPSI DAN DEKRIPSI PESAN WHATAPP

Encryption is a method of changing message data (plaintext) into password data (ciphertext), while decryption is a method of converting ciphertext to plaintext. WhatsApp Messenger is a messaging application for smartphones that is basically similar to BlackBerry Messenger. The WhatsApp Messenger application uses a 3G, 4G or WiFi internet connection for data communication. By using WhatsApp, we can do online chat, share files, exchange photos and so on. The algorithm used is 2 (two) types, namely symmetric algorithms and asymmetries algorithms. Merkle-Hellman Knapsack is a cryptosystem that uses the asymmetries algorithm. The Merkle-Hellman Knapsack implementation used uses xor logic. The key length is used between 8 to 72 bits. This capability makes Merkle-Hellman Knapsack have strong security with a short key length. Whereas the aim to be achieved is to apply the Merkman-Hellman Knapsack cryptosystem using the Visual Studio 2010 Programming Language
Expediting the convergence of evolutionary algorithms by identifying promising regions of the search space

Evolutionary algorithms (EAs) are widely used for optimization. Their use is particularly beneficial for problems where underlying objective functions and/or constraints are highly non-linear / black-box and the classical exact techniques cannot be applied. However, EAs evolve a population of solutions over a large number of generations by applying variation operators and selection schemes. The migration of population towards the optimum solution can be slow and require a large number of function evaluations. In this paper, we propose to expedite this convergence by identifying smaller sub-spaces that potentially envelope the optimum using `bump hunting', followed by intensification of offspring generation in these regions. We implement the method within a Differential Evolution (DE) framework and demonstrate the improvement over a range of benchmark test problems.
Algorithmic Approach for Cash Withdrawal Problem in ATM

Since the banks are not open 24x7, there was a need for customers of the bank to withdraw cash anytime during the day. So, the Automatic Teller Machine to satisfy this need. There may be situations where you need emergency cash and your Automatic Teller Machine (ATM) is not able to dispense cash of the desired amount. This may be due to insufficient currency or lack of avail-ability of the required denominations. Now, imagine that your ATM is smart and it helps you to withdraw cash easily. It does so, by giving you an amount that is nearest to the requested amount. It can use either the dynamic or greedy technique to map the requested amount to the nearest amount it can dispense. We have to make sure that the transaction is legitimate and also that the cash requested by the customer is for an emergency. For this purpose, the proposed system adds a module to dispense cash in the above-mentioned scenario.
Ironic Process Theory In Softball Pitching: How Knowing Information About An Opponent’s Strengths Affects Performance

INTRODUCTION: As athletic competition and college athletics continue to grow and flourish, there is an increased emphasis on game preparation. Collegiate softball pitchers are expected to handle an immense amount of pressure, perform with precision, and incur few errors. PURPOSE: Examine the Ironic Process Theory related to fast pitch softball pitching and to determine how knowing information about an opponent’s strengths affects experienced pitcher’s performance under pressure. METHODS: Experienced college softball pitchers (n = 12) were recruited as subjects. Each pitcher was randomly instructed through two 30 pitch phases (a high and low pressure phase) with two different conditions: black target only condition (BOTC) or black and red target condition (BRTC). Subjects were asked to aim and hit the black target and avoid the red target. The black target represented the weakness of the opponent and the red target represented the strength of the opponent. Performance pressure was measured before each phase using the Mental Readiness Form (MRF-3) (Krane, 1994). RESULTS: Pre-MRF-3 reached statistical significance across the between-subjects factor of pressure, [t(22) = 3.102, p = 0.005] with a mean difference of 4.75 (95% C.I. 1.57 to 7.92) indicating that the pressure situation induced an increase in perceived anxiety and stress. ANCOVA did not reach statistical significance on the main effects of black targets hit nor the interactions terms for black targets hit by MRF-3 and black targets hit by Pressure. This finding asserts that there was no difference in performance between BRTC and BOTC across pressure after adjusting for perceived anxiety. There was no statistically significant difference of red target hit between the high pressure and low pressure situations, d = 0.25 (95% C.I. -0.463 to 0.963), t(22) = 0.723, p = 0.963. DISCUSSION: Practically speaking, the pitchers in this study did perform more effectively in the high pressure situation. Although different from previous Ironic Theory research, it is important to note this increased ability for pitchers to hit a desired target while under pressure. Even if not statistically significant, this can help pitchers and coaches understand the link between pressure and performance more effectively, and add training components to improve in stress situations.
A Multilingual Study of Multi-Sentence Compression using Word Vertex-Labeled Graphs and Integer Linear Programming

Multi-Sentence Compression (MSC) aims to generate a short sentence with the key information from a cluster of similar sentences. MSC enables summarization and question-answering systems to generate outputs combining fully formed sentences from one or several documents. This paper describes an Integer Linear Programming method for MSC using a vertex-labeled graph to select different keywords, with the goal of generating more informative sentences while maintaining their grammaticality. Our system is of good quality and outperforms the state of the art for evaluations led on news datasets in three languages: French, Portuguese and Spanish. We led both automatic and manual evaluations to determine the informativeness and the grammaticality of compressions for each dataset. In additional tests, which take advantage of the fact that the length of compressions can be modulated, we still improve ROUGE scores with shorter output sentences.
Local microclimatic impacts of utility scale photovoltaic solar parks

&amp;lt;p&amp;gt;Solar photovoltaic (PV) capacity has risen exponentially, with the majority deployed as ground-mounted solar parks, across the world. Deployments are projected to continue, leading to further land use change with implications for the hosting environment, including perturbations in ecological processes that underpin the supply of natural capital and ecosystem services. Whilst alterations to within solar park climate of magnitudes known to effect ecosystems processes have been quantified, the spatial extent remains unclear. In this study, we use remote sensing and field data to provide evidence of a solar park land surface temperature (LST) cool island. Specifically, we quantify a LST cooling of up to 2.3 &amp;amp;#8451; outside the solar park boundary, with the effect declining rapidly with distance from the solar park but extending up to 730 m away. The magnitude of cooling observed is sufficient to alter ecosystem processes, including greenhouse gas emissions with implications for the carbon intensity of the electricity produced. Consequently, we need to better understand the local climatic impacts of solar parks and associated cascading impacts on ecosystem function to establish the broader environmental co-benefits and costs of this rapidly growing means of low carbon electricity production.&amp;lt;/p&amp;gt;
A Perturbed Self-organizing Multiobjective Evolutionary Algorithm to solve Multiobjective TSP

Travelling Salesman Problem (TSP) is a very important NP-Hard problem getting focused more on these days. Having improvement on TSP, right now consider the multi-objective TSP (MOTSP), broadened occurrence of travelling salesman problem. Since TSP is NP-hard issue MOTSP is additionally a NP-hard issue. There are a lot of algorithms and methods to solve the MOTSP among which Multiobjective evolutionary algorithm based on decomposition is appropriate to solve it nowadays. This work presents a new algorithm which combines the Data Perturbation, Self-Organizing Map (SOM) and MOEA/D to solve the problem of MOTSP, named Perturbed Self-Organizing multiobjective Evolutionary Algorithm (P-SMEA). In P-SMEA Self-Organizing Map (SOM) is used extract neighborhood relationship information and with MOEA/D subproblems are generated and solved simultaneously to obtain the optimal solution. Data Perturbation is applied to avoid the local optima. So by using the P-SMEA, MOTSP can be handled efficiently. The experimental results show that P-SMEA outperforms MOEA/D and SMEA on a set of test instances.
The Meaning and Challenges of Lifelong Education as Viewed by Embodied Learning

이 연구는 최근 학습론에서 관심이 대두되고 있는 몸학습에 관한 개념정립과 의미 탐색을통해 몸의 철학적 자리에서 바라보는 평생교육의 의미와 과제를 살펴보는데 목적을 둔다. 이를 위해 문헌자료에 기초한 몸학습의 구성요소인 몸, 지식, 감정과 영성 간의 인과적 관계를탐색하였다. 몸학습 구성요소 탐색에 기초한 개념지도 작성을 시도하였으며, 이를 근간으로미래사회 패러다임 전환에 터한 평생교육이 나아가야할 방향성을 논의하였다. 연구의 결과 및시사점은 다음과 같다. 첫째, 몸학습은 몸, 지식, 감정과 영성의 메커니즘을 통해 역동적으로순환하고 있는 것으로 나타났다. 또한 제작된 몸학습의 개념지도를 통해 몸학습은 몸에 한정된 이론적 체계가 아닌 통합적 얼개를 지닌 것으로 밝혀졌다. 몸학습은 앞으로의 평생교육 방향을 제시할 강력한 추동체이자, 평생교육을 총체적으로 보는 시각을 높일 수 있는 기제이므로, 몸학습에 대한 다양한 연구가 수반되어야 할 것이다.The purpose of this study is to examine the lifelong education viewed from the philosophical position of the body through concept establishment and semantic exploration of embodied learning, which has recently been drawing attention in learning theories. For this, the causal relationship between body, knowledge, emotion, and spirituality, which are components of embodied learning based on literature data, was explored. This study attempted to prepare conceptual maps based on exploration of embodied learning components, and based on this, discussed the future direction of lifelong education in the paradigm shift of the future society. The results and implications of the study are as follows. First, embodied learning was found to circulate dynamically through mechanisms of body, knowledge, emotion, and spirituality. In addition, through the concept map of the embodied learning, embodied learning has an integrated structure, not a theoretical system limited to the body. As embodied learning is a powerful driving force for suggesting the future direction of lifelong education, and a mechanism to enhance the overall view of lifelong education, various studies on embodied learning will have to be involved.
Peningkatan Keterampilan Menulis Karangan Deskripsi Melalui Metode Discovery dengan Menggunakan Media Gambar pada Mahasiswa Program Studi Pendidikan Bahasa dan Sastra Indonesia STKIP Pontianak

This study aims to improve students' writing skills on descriftive essay by using the Discovery method aided by the media image. This research was a type of classroom action research. The subjects of this study were students of the Indonesian Language and Literature Study Program STKIP Pontianak amounting to 35 people. The data collected were divided into two categories, namely quantitative and qualitative data. Techniques for collecting qualitative data, namely increasing learning activity activity data, used observation sheets and recording sheets, while for quantitative data collection used test instruments and student performance test. The data collected were described and analyzed using qualitative analysis techniques. The conclusions of the study illustrate the method of finding through image media has made students' writing skills in descriptive essay improved. Students give a good and enthusiastic response when using the discovery method through image media. Based on data and tests that have been done writing skills of students in writing descriptions before doing the action of 60.27%. Then after being given action in the first cycle, student skills reached 72% and in the second cycle student skills increased to 79%.
SOCIAL AND PSYCHOLOGICAL PROBLEMS OF THE POINT-RATING SYSTEM FOR EVALUATING EMPLOYEES’ WORK IN EDUCATIONAL INSTITUTIONS

Digital security in the modern world is one of the leading practical and theoretical trends. Many practitioners and theorists are working to improve digital security, usually completely ignoring the costs of this process, which is very necessary, but not as univocal as it is presented to the state and transnational corporations (TNCs) sponsoring the research. The purpose of the study is to analyze the socio-psychological aspects of the use of information and communication technologies (ICT) in managing university and school education. Research methodology and techniques. The paper presents the theoretical analysis of the problem of the socio-psychological dangers of using ICT in managing higher education and school education; it also summarizes the included and non-included observations over the processes and results of the implementation of the point-rating system and the use of ICT in university education. The results of the study. The systems «Virtual school» and «Virtual university», developed and implemented in order to optimize managing processes and increase the accessibility of education in schools and universities, face serious socio-psychological, managerial and legal problems. One of the main problems is the problem of sporadic or systemic violation of personal and organizational security. This problem arose not only because there is no culture of relationships in the digital environment. It arose because moral, conventional- ritual and legal normsб both in the real and in the «virtual» world, ceased to be real regulators of relations. The real regulators in this environment are the norms of the community that modifies all aspects of its existence. Teachers, administrations, the state face a really complicated challenge, which is to restore Russian education as the best education in the world, restore it as a sphere of culture, not business, re-orientate education to develop individual and culture, and not serve even the best «direct»needs of production and economics. However, morally meaningful and based on moral standards, participatory, developing educational technologies are not the unattainable future, but a developed tradition, which researchers and teachers are ready to support and restore.
An investigation on Challenges in the Implementations of Literary Components in English classroom

This study mainly focused on an investigation of challenges in the implementations of literary components in English classroom.The study was basically conducted at Ambicho Gode Primary School Grade Eight students in particular.Data, to achieve this study, were collected with questionnaire, semi-structured interview and textual analysis.To conduct this research, random and available sampling techniques were employed to select sample students and sample English language teachers respectively.The findings of the study shows that the basic challenges in the implementations of literary components are students' lack of motivation to learn, complexity of language employed in the production of literary components, the medium of instruction, lack of trainings for English teachers, absence of sufficient imaginative works in the library, time allotted for the lessons or the curriculum designed for the text, large classroom size, etc.The text is designed different poems, role plays, flash fictions, non-fictional writings like biographies of prominent persons, piece of oral traditions like fables, folktales and Essay writings such as narrative, expository and descriptive types etc.
Метод бидекомпозиции частичных булевых функций

The problem of bi-decomposition of a Boolean function is to represent a given Boolean function in the form of a given logic algebra operation over two Boolean functions and so is reduced to specification of these functions. Any of the required functions must have fewer arguments than the given function. A method of bi-decomposition for an incompletely specified (partial) Boolean function is suggested, this method uses the approach applied in solving the general problem of parallel decomposition of partial Boolean functions. The specification of the given function must be in the form of a pair of matrices. One of them, argument matrix, can be ternary or binary and represents the definitional domain of the given function. The other one, value matrix, is a binary column-vector and represents the function values on the intervals or elements of the Boolean space of the arguments. The graph of orthogonality of the argument matrix rows and the graph of orthogonality of one-element rows of the value matrix are considered. The problem of bi-decomposition is reduced to the problem of a weighted two-block covering the edge set of the orthogonality graph of the value matrix rows by complete bipartite subgraphs (bicliques) of the orthogonality graph of the argument matrix rows. Every biclique is assigned with a disjunctive normal form (DNF) in definite way. The weight of a biclique is the minimum rank of a term of the assigned DNF. According to each biclique of the obtained cover, a Boolean function is constructed whose arguments are the variables from the term of minimal rank on the DNF.
LibGuides: Digital Learning Guide: Home

This guide was created as part of emergency planning in case we need to close school for weeks at a time
Comparison of different techniques and stains for direct diagnosis of Trichinella spiralis

Background: The aim of Trichinella inspection is to reliably detect larvae in meat at levels which are capable of causing human trichinellosis. Trichinoscopy is a rapid, cost effective but is less sensitive in detection of low muscle larvae (ML)numbers. Artificial digestion is more convenient, and flexible, but may destroy immature larvae. Baermann technique may enhance the efficiency of diagnosis. Giemsa and Leishman stains provide identical contrasting coloration as Hematoxylin and Eosin (H-E) with the both advantages of that they can be used for staining non-histological sectionsand rapid preparation.The primary aim of the study was to compare the efficiency of digestion and Baermann techniques for detection of ML in muscles. Secondary aim was detection of ML by Geimsa and Leishman stain and their comparison with routinely used stain H-E. Methods: Muscles from 36 mice orally infected with Trichinella spiralis encysted larvae were examined. Larvae from 1 g samples of different muscles were recovered by digestion and Baermann techniques after different dose of infection. Muscle samples were prepared for staining with Giemsa, Leishman and H-E. Results: Number of larvae recovered by Baermann was higher recovered by digestion method (P ˃0.5). Leishman stain was the best stain for rapid detection of ML after 30 min followed in validity by Geimsa then H-E. Conclusion: Baermann concentration technique showed higher sensitivity than digestion method. Leishman stain is superior to Giemsa stain as it takes less time. Both stains are considered good alternative to H-E for rapid and easy diagnosis of trichinellosis in post-mortem animals.
Dialogue act based expressive speech synthesis in limited domain for the Czech language

This paper deals with expressive speech synthesis in a dialogue. Dialogue acts - discrete expressive categories - are used for expressivity description. The aim of the work is to create a procedure for development of expressive speech synthesis for a dialogue system in a limited domain. The domain is here limited to dialogues between a human and a computer on a given topic of reminiscing about personal photographs. To incorporate expressivity into synthetic speech, modifications of current algorithms used for neutral speech synthesis are made. An expressive speech corpus is recorded, annotated using a predefined set of dialogue acts, and its acoustic analysis is performed. Unit selection and HMM-based methods are used to synthesize expressive speech, and an evaluation using listening tests is presented. The listeners asses two basic aspects of synthetic expressive speech for isolated utterances: speech quality and expressivity perception. The evaluation is also performed for utterances in a dialogue to asses appropriateness of synthetic expressive speech. It can be concluded that synthetic expressive speech is rated positively even though it is of worse quality when comparing with the neutral speech synthesis. However, synthetic expressive speech is able to transmit expressivity to listeners and to improve the naturalness of the synthetic speech.