Reviewerly/exHarmony huggingface dataset:
A Study on the Organizational and Legislation Improvement of the National Crisis Management System

이 논문의 연구목적은 국가위기관리체제의 문제점을 비판하고 그에 따른 효율적 방안을 제시함으로써 국가위기 관리체제의 발전과 국민안전증진에 기여하는 목적을 두고자 한다. 이 연구를 위해 국가위기관리의 법체계와 조직 체계를 조사하였으며 지금껏 연구된 논문과 기사 자료를 활용하는 방법으로 연구를 수행하였다. 또한 이 논문의 연구결과 는 현행 위기관리 조직 체계는 일부 조직을 통합적으로 정비하고자 하는 노력이 있지만 근본적으로는 통합적 위기관리에 실패하였으며 현행 법체계 역시 법령의 다원적 분산으로 인해 국가통합위기 관리에 저해되고 있음을 확인하였다. 결론적으로 통합적 국가위기관리 조직 체계의 구축을 위하여 국가위기 관리부를 신설해야하며, 법적으로도 통합위기 관리를 위한 통일적 법령체계 구축을 수립해야 한다.The purpose of this paper is to contribute to the development of the national crisis management system and the enhancement of public safety by criticizing the problems of the national crisis management system and presenting efficient measures accordingly. For this study, the legal system and organizational system of the national crisis management were investigated and the research was carried out in a way that utilizes the research papers and article data. In addition, the research results of this paper confirmed that although the current crisis management system is trying to integrate some organizations, it failed to manage them fundamentally, and that the current legal system is also impeded by the management of the national integrated crisis due to the plural distribution of laws. In conclusion, the government should establish a national crisis management department to establish an integrated national crisis management system, and legally establish a unified legal system for integrated crisis management.
Research on Data Center System Design of Server Virtual Machine Based on Cloud Computing

The so-called informationization of education is to introduce advanced modern information technology in the traditional education, teaching and management. Compared with ordinary undergraduate colleges, colleges and universities start late and their information construction is also in a backward stage. Since the end of the last century, the Ministry of Education has proposed that China's higher education has developed rapidly in order to develop vigorously in higher vocational education. The control system is rather lengthy and the system scale is large, resulting in a larger data. The training room will be set up in the colleges and universities to be responsible for the management and maintenance of data. The main functions include: maintaining the safe operation of the server, effectively ensuring data security, being able to respond to and respond to accidents in a timely and effective manner and flexibly managing and distributing effectively. Resources, etc. This paper aims to introduce mainstream cloud computing technology into the information management system of the training room to form a data center system with more efficient operation, more flexible data processing and lower cost.
Try It Before You Buy It: Library Residencies as Experiential Learning

Poster presentation given at the 2019 Association of Library and Information Science Educators (ALISE) Conference on September 24, 2019 in Knoxville, TN.
Use of Web 2.0 Tools and Services by the Library Professionals in Lagos State Tertiary Institution Libraries: A Study

With the growing recognition of the potentials of web 2.0 tools, a lot of academic libraries are adopting the technologies and investing heavily in training programs for their staff in order to improve their operations. This study investigated the use of web 2.0 tools and services by the library professionals in Lagos State tertiary institution libraries. Review of the literature was carried out on the availability of use, purpose of use, extent of use, and competency level required for the use of web 2.0 tools in tertiary institution libraries in Lagos State, Nigeria. Challenges and solutions were also proffered. The findings revealed that web 2.0 tools have great potentials for library service provision although they are a relatively new concept. The uses of web 2.0 tools were mostly for communication, research, collaboration, and leisure purposes; however, the extent of the use for service delivery was about average. This indicated that web tools were not sufficiently and efficiently used. Findings also revealed that the respondent librarian in the study area possessed a moderate level required skill needed in web-based technology environment. However, there is need to address certain limiting factors, such as technical hitches like unstable internet access, erratic power supply, and restrictive institutional policies, in order to take full advantage of web 2.0 tools for providing innovative library services and drawing patrons to the library. Based on the findings of the study, it is recommended that library managers in the study area should be provided with uninterrupted electricity power supply to overcome the erratic power situation experienced now, periodic training and re-training programs should be provided to librarians, this in effect will equip librarians with the necessary skill, and policies should be formulated that will guide the conduct and usage of web 2.0 tools for implementation.
CNN^{2}: Viewpoint Generalization via a Binocular Vision

The Convolutional Neural Networks (CNNs) have laid the foundation for many techniques in various applications. Despite achieving remarkable performance in some tasks, the 3D viewpoint generalizability of CNNs is still far behind humans visual capabilities. Although recent efforts, such as the Capsule Networks, have been made to address this issue, these new models are either hard to train and/or incompatible with existing CNN-based techniques specialized for different applications. Observing that humans use binocular vision to understand the world, we study in this paper whether the 3D viewpoint generalizability of CNNs can be achieved via a binocular vision. We propose CNN^{2}, a CNN that takes two images as input, which resembles the process of an object being viewed from the left eye and the right eye. CNN^{2} uses novel augmentation, pooling, and convolutional layers to learn a sense of three-dimensionality in a recursive manner. Empirical evaluation shows that CNN^{2} has improved viewpoint generalizability compared to vanilla CNNs. Furthermore, CNN^{2} is easy to implement and train, and is compatible with existing CNN-based specialized techniques for different applications.
Mobile Blasting Robot Obstacle Avoidance Planning

Aiming at the obstacle avoidance of the movable blasting robot, this paper proposes a method based on the improved artificial potential field method to solve the problem of obstacle avoidance when the robot moves to the target point. Based on the traditional artificial potential field method, one of the problems is that the end point of the target is unreachable, and another problem is that the safety distance of the robot in actual work is not considered. An improved artificial potential field method is proposed to solve the above problems and the robot can successfully complete the obstacle avoidance movement. In addition, a multi-robot obstacle avoidance method based on the follower leadership method is proposed to achieve the obstacle avoidance of multiple robot working together. Under the joint action of these two algorithms, multiple robots can accurately avoid obstacles and reach the target point. Simulation results demonstrate the effectiveness of the proposed method.
Penerapan Algoritma Bee Colony Untuk Optimasi Rute Wisata Pulau Belitung

The number of tourist attractions on Belitung Island that can be reached makes it difficult for travelers to find the optimum route, both in terms of distance, time, and costs incurred to travel from one tourist spot to another. One of the factors that influence the amount of expenditure when traveling is transportation costs. The thing that is closely related to transportation is the distance traveled, too much waste of time on the way to the tourist attractions due to the wrong choice in the route taken. Based on the existing problems, optimization is needed in finding the optimum route from the initial position to the destination position using the Bee Clony Algorithm.
An Approach to Case-Based Reasoning Based on Local Enrichment of the Case Base

This paper describes an approach to case-based reasoning by which the case base is enriched at reasoning time. Enrichment results from the local application of variations to seed cases: new hypothetical cases are created which get closer and closer to the target problem. The creation of these hypothetical cases is based on structures associated to the problem and solution spaces, called variation spaces, that enable defining a language of adaptation rules. Ultimately reaching the target problem (exactly or nearly) allows the system to deliver a solution. Application of the proposed approach to machine translation shows behind state-of-the-art, but promising results.
Underwater image segmentation based on fast level set method

Image segmentation is a fundamental process in image processing that has found application in many fields, such as neural image analysis, and underwater image analysis. In this paper, we propose a novel fast level set method (FLSM)-based underwater image segmentation method to improve the traditional level set methods by avoiding the calculation of signed distance function (SDF). The proposed method can speed up the computational complexity without re-initialisation. We also provide a fast semi-implicit additive operator splitting (AOS) algorithm to improve the computational complex. The experiments show that the proposed FLSM performs well in selecting local or global segmentation regions.
EFEKTIVITAS MODEL PEMBELAJARAN JIGSAW PADA KETERAMPILAN MENULIS BAHASA PERANCIS

This research aims to describe student’s writing ability before and after using Jigsaw model, the effectiveness of Jigsaw model in improving writing skills, and the opinion of students. This study applies descriptive quantitative method in form of pre-experimental design. Instruments that are used in the form of tests and questionnaires. The sample of this research is 32 characteristics writing skill of 6th semester French Education students. Based on the research result, the researcher can conclude that the students have been able to write the argumentative text nicely. The test result showed that the average test score after using the Jigsaw model is 8.9. It means, the average posttest score is higher than the average pretest score, up to 1.7%. Meanwhile, the results of the questionnaire show that students like writing but they find so much difficulty in making a writing or a text, and most students give a positive impression for the Jigsaw model.
Identify Criminal Records in Social Media using Sentiment Analysis

Today it is important to recognize important criminal data hide in social media data within some unimportant text. It is also possible to hide criminal records in twitter data. So first it is required to unhide data. Next the analysis of these data are required for crime investigation. This process requires the knowledge of different techniques of steganography but also to analyse data for finding sentiment analysis of the data for finding criminal information. This paper initially reviews various techniques of data hiding and retrieval of data and then analysing data for finding criminal words using sentiment analysis. It is assumed here that the analysis is required for finding any criminal records hidden within the data.
Content Equivalence Analysis of Health News Translation: A Bakerian Approach

The primary purpose of the present paper is to investigate content equivalence in the English to Persian translation of General Health News based on Baker's model. A descriptive qualitative study was designed and 10 texts from English and Farsi versions of Iran Newspaper were randomly selected. To assess the translation quality of the selected texts, the researcher compared the original and translated texts at word, phrase and sentence level and tabulated the obtained data and estimated the frequency and percentage of translation inadequacies. The results revealed that most errors in the English translations were rooted in the textual domain where the translators have misunderstood the general concept of the source context. This was followed by semantic errors. The third place was given to the errors in the pragmatic domain which mainly addressed the purpose and meaning of the concepts presented in the source language. The least frequently occurred errors were related to grammatical errors which mainly covered prepositions and tenses. Research on content equivalence, in general, can help experts assess the quality of the translated text. Research on content equivalence of particular texts can lead to detecting translation problems, translation errors and translation inadequacies in that particular field.
ADVANCED TEACHING AND LEARNING METHOD FOR ENGINEERING AND TECHNOLOGY STUDENTS AIMING AT THE STRATEGIC DEVELOPMENT OF THE INDUSTRY 4.0

In recent years, job candidates are currently required not only professional knowledge and skills but also English specifically implemented in particular occupations. Since then English for specific purposes (ESP) is the latest trend which has exponentially developed. The majority of universities have deployed diverse ESP courses in order to help learners address communicative needs as well as practices of particular professions. Ho Chi Minh City University of Transport has also provided interesting ESP courses supposed to assist engineering and technology students in their future careers. Not only inspired by the need to enable the learners of these courses to increase their knowledge of terminology in their fields but also integrating technology in language teaching and learning, this paper aims to suggest Quizlet a mobile and web-based study application as a tool to facilitate specialized vocabulary acquisition for learners of English for engineering and technology as well as for those who are learners of English for specific purposes in general. Thanks to Quizlet, both teachers and students will take full advantages from this innovative method that is probably proliferating their new learning and teaching experiences. Although the merits outweigh in this sphere, it is obvious that Quizlet should not be compulsory, but combined with other strategies to eventually give fruitful assistance to meet learners’ increasing demands on the verge of the industrial revolution 4.0.
Semi-supervisedly Co-embedding Attributed Networks

Deep generative models (DGMs) have achieved remarkable advances. Semi-supervised variational auto-encoders (SVAE) as a classical DGM offers a principled framework to effective generalize from small labelled data to large unlabelled ones, but it is difficult to incorporate rich unstructured relationships within the multiple heterogeneous entities. In this paper, to deal with the problem, we present a semi-supervised co-embedding model for attributed networks (SCAN) based on the generalized SVAE for the heterogeneous data, which collaboratively learns low- dimensional vector representations of both nodes and attributes for partially labelled attributed networks semi-supervisedly. The node and attribute embeddings obtained in a unified manner by our SCAN can benefit not only for capturing the proximities between nodes but also the affinities between nodes and attributes. Moreover, our model also trains a discriminative network to learn the label predictive distribution of nodes. Experimental results on real-world networks demonstrate that our model yields excellent performance in a number of applications such as attribute inference, user profiling and node classification compared to the state-of-the-art baselines.
PENGEMBANGAN BAHAN AJAR PPKn BERBASIS CITIZENSHIP BEHAVIOR DALAM MENINGKATKAN PENGETAHUAN KEWARGANEGARAAN

Developing teaching  materials  PPKn is  a  dimension  of  citizenship which can support behavior students, in lifesocial, therefore the need application of behavior citizenshipin  school basic will very can be useful,considering education todaycitizenship  still there are some shortcomings  that  become  obstacles as is that happened  in the field, wrongthe otheris the teacher's  understanding of PPKn that’s pelled out difficult, Morepitch again still reference curriculumis very limited, especiallyon  rootscience about PPKn as what has been implemented in schools. Learning this emphasize existence sourcethe supported teaching materials support researchas well asprovidinga  better knowledge. Developingingredientsteach PPKn based on Citizenship Behavior (CB ) in order to improve  knowledge  grade V elementary school students this corresponding with four relations concepts PPKn learning as pect that proven  effective  improve  knowledge  grade V students Elementary school. The results of the study could be proved that  theim  provement of  students’ knowledge  about  PKn  was  higher  than  before they learned the instructional  materials. This  research  would  provide  benefits  for  teacher  education. as  an  indicator  quality  of  teaching  and  learning  process. This  educational  product recommended  for teachers  at  elementary  schools  to  be  easier  for  them  to  focus  on  citizenship  behavior  improvement.
Professional training of youth as an integral part of the content of the professional organizations of the scientific and technical intelligentsia of the Ukrainian foreign state of the first third of the twentieth century

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Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm

Searching and sorting, by no doubt, represent two of the most fundamental and widely encountered problems in computer science. Given a collection of objects, the goal of search is to find a particular object in this collection or to recognize that the object does not exist in the collection. A major goal of computer sciences is to understand and develop a solution for the particular problem.  Typically solving the problem involves at least four steps: (1) design an algorithm, (2) analyze the correctness and efficiency of the procedure, (3) implement that procedure in some programming language, and (4) test that implementation.  An important issue is to describe the efficiency of a given procedure for solving a problem. Informally, usually we speak in terms of  “fast” or “slow” programs, but the absolute execution time of an algorithm depends on many factors such as: the size of the input,  the programming language used to implement the algorithm, the quality of the implementation and  the machine on which the code is run (a supercomputer is faster than a laptop). In this paper we will analyze the performances of a searching algorithm, precisely the chunk algorithm. In analyzing the efficiency of chunk algorithm, we will only concentrate on searching items, using the Chunk-Search Algorithm, on one-dimensional arrays with integers. We wanted to see how does different chunk size, input size (i.e., the “speed” of the algorithm as a function of the size of the input on which it is run), and the machine on which the code is run.
Biotechnical monitoring system for determining person's health state in polluted environment using hybrid decisive rules

Setting exposure criteria to environmental pollutants is dependent on a range of interrelated variables, therefore it is complicated to understand and model exposure levels. Fuzzy logic is a convenient approach to integrate expert judgment and mathematical modelling in one predication model. Monitoring health state of population is useful tool to develop and calibrate parameters of fuzzy logic model. Analysis of the indistinct decisive rules making a basis of creation of knowledge bases of expert systems, solving problems of monitoring of a state of environment and health of humans on the basis of collectives of the hybrid mathematical models working with diverse structure of data in the absence of their exact analytical description are considered. Disease risk was analysed for populations living in two environmental conditions, one a polluted mining community (Zheleznogorsk city) and the other a cleaner environment community (Kursk city). Diseases screening for polluted area was conducted and analysed.
IMPROVING THE STUDENTS’ WRITING SKILL IN COMPOUND COMPLEX SENTENCE THROUGH MIND MAPPING AT GRADE X OF SMA METHODIST-2 KISARAN IN SCHOOL YEAR 2014/ 2015

This research was mainly intended to figure out whether concept mapping can improve the students‟ writing ability. The subjects of the study were the grade X students of SMA Methodist-2 Kisaran in 2014/2015 school year. The result of the data analysis of the post-test score in cycle I showed the mean score of 64.07. The result of data analysis of the post-test score obtained by the subjects under study in cycle II  pointed out the increasing mean score of 78.45. The grand mean figure of the post-test score obtained by the subjects under study in cycle I was 64.07 and in cycle II was 78.45. These findings clearly showed that concept mind mapping could improve the students‟ writing skill in compound complex sentence. The result of the data analysis of questionnaire score showed the comparative percentages figures of 63.6% for option A, 35% for option B, 1.4% for option C and 0% for option D. The result comparative percentages figure clearly showed the students attitude and motivation in learning writing skill of compound complex sentence changed positively. Key words: improving writing skill, compound complex sentence, mind mapping mapping.
Abstract Completion, Formalized

Completion is one of the most studied techniques in term rewriting andfundamental to automated reasoning with equalities. In this paper we presentnew correctness proofs of abstract completion, both for finite and infiniteruns. For the special case of ground completion we present a new proof based onrandom descent. We moreover extend the results to ordered completion, animportant extension of completion that aims to produce ground-completepresentations of the initial equations. We present new proofs concerning thecompleteness of ordered completion for two settings. Moreover, we revisit andextend results of M\'etivier concerning canonicity of rewrite systems. Allproofs presented in the paper have been formalized in Isabelle/HOL.
Linear shrinkage estimation of the variance of a distribution with unknown mean

In estimation of the variance of a distribution with unknown mean, the paper suggests the linear shrinkage estimators motivated from a Bayesian perspective. The so-called Stein’s truncated estimator of the variance can be derived as the linear shrinkage estimator when the distribution is normal. The method of the linear shrinkage estimation is extended to non normal distributions and to linear regression models. The linear shrinkage estimator with the optimal weight estimate, derived without assuming normality, is shown to have a good numerical performance for several distributions.
Transmogrified Imputation Algorithm for Clustering Data in Missing Data Imputation

This research proposes to implement transmogrification process in the Imputation procedures to overcome the challenges in missing values. Appropriate data pre-processing methods in data mining plays significant role to ensure good quality of data. The data pre-processing tasks include identification of outliers, smoothening noisy data and overcoming inconsistent data. Issues related to data incompleteness, still remains a challenge to many researchers. The transmogrified method uses mathematical approach and Index segmentation based Imputation Algorithm for missing data imputation. The databases were used to demonstrate the performance of the proposed method. The proposed algorithm is evaluated by extensive experiments and comparison with KNNI, MSC, AHC, EM-GMM and FEM-GMM The results showed that the proposed algorithm has better performance than the existing imputation algorithms in terms of classification accuracy.