Reviewerly/exHarmony huggingface dataset:
Importance of training need and development in telecom industry-with reference to KSA (city Jazan)

Kingdom of Saudi Arabia is the largest and fast growing sector in telecommunication. A study on one of the Human resource practice training and development of telecom industry in Saudi Arabia is taken in consideration in this paper. The main objective of this paper is to know about training its need and its importance for growing the effectiveness of the organization. Training and development is the main concern area for the organization effectiveness. Training is the essence of the organization in today’s era. It plays a vital role in effectiveness of organization. Training is usually conducted when a new employee introduce to an organization or in other situations like updating of technology in company, promotion of an employee, or grooming, enhancing skills in present employees etc. It is a continuous process in every company it may be on the job or off the job. Training is beneficial in two ways to employers and employee as well. When an employee is trained well as per the need of the organization it directly effects to the performance and it results to the productivity of the organization. Proper training and trained employees results in quality manpower of the company. This study reveals the importance of the training need and methods of training in telecom sector in Saudi Arabia.
DEFAMILIARIZATION OF CHARACTER IN ANTOINE DE SAINT EXUPERYâ€™S THE LITTLE PRINCE

Defamiliarization is a device of art to make things unfamiliar by a process of making strange (estrangement) to increase the difficulty and length the perceptions. The Little Prince, a novella by Antoine De Saint Exupery presents the defamiliarized characters which appear strange and unfamiliar. To recognize them, the characterâ€™s familiarity should be identified by the schemata study before came into defamilarization. Experiencing the artfulness of object will give the reader chance to discover any kind of perceived meaning without inhibition for their judgments. This study uses qualitative method in terms of close reading technique in scrutinizing Antoine de Saint Exuperyâ€™s The Little Prince. The discussion is conducted through its characters. Although those device are common objects, they appeared strange to open the readerâ€™s mind into any possible assumptions, meaning, and interpretation.
Library Guides: Readings Online User Guide: Use tools to generate citations for your list

Guide for academic staff using Readings Online. RIS files include citation details for readings. These can be imported from scholarly databases & your reference management software, e.g. Zotero, Mendeley or Endnote.
An ensemble multi-objective particle swarm optimization approach for exchange rates forecasting problem

In this paper, the authors propose an ensemble multi-objective particle swarm optimisation approach (named EMPSO) for forecasting the currency exchange rate chain. The proposed algorithm consists of two main phases. The first phase uses a multi-objective particle swarm optimisation algorithm to find a set of the best optimal particles (named leaders). The second phase then uses these leaders to jointly calculate the final results by using the soft voting ensemble method. The two objective functions used here are predictive error and particle diversity. The empirical data used in this study are six different sets of currency exchange rates. Through comparison results with other evolutionary algorithms and other multi-objective PSO algorithms, the proposed algorithm shows that it can achieve better as well as more stability results on experimental data sets.
Coherence in Machine Translation Output

Coherence is a cognitive process. It plays a key role in argumentation and thematic progression. To be characterised by appropriate coherence relations and structured in a logical manner, coherent discourse/text should have a context and a focus. However, it receives little attention in Machine translation systems that considers the sentence the largest translation unit to deal with, the fact that excludes the context that helps in interpreting the meaning (either by human or automatic translator). In addition to that, Current MT systems suffer from a lack of linguistic information at various stages (modelling, decoding, pruning) causing the lack of coherence in the output. The present research aims at, first, capturing the different aspects of coherence, and second, introducing this notion in texts generated by machine translation based on sentence-by-sentence basis, in order to see and discuss the several phenomena that can lead to incoherent document translations with different language pairs.
Investigation on Aggregated Weighted Ensemble Framework for Data Stream Classification

Ensemble-based data stream classification process is the most active research work in strengthening the efficacy of ensemble-based data stream classification process. This research is carried out in two different dimensions. First is focused on devising novel ensemble-based data stream classification algorithms to enrich data stream classification task. The second dimension is focused on formulating novel frameworks which propose the novel strategies to aggregate the results of the off-the-shelf classification algorithms. The proposed research work expounds a novel aggregated weighted ensemble framework that aggregates the results of off-the-shelf classification algorithms for data stream classification. The architecture and working principles of the proposed framework, and its role in confronting concept drifts in the data stream classification task are experimentally investigated. Theoretical justifications and empirical evaluation are made on the proposed framework, and accentuate the competency of the proposed framework in terms of accuracy.
Multimodal data fusion algorithm applied to robots

Abstract In recent years, the use of multimodal human-computer interaction technology to achieve the enhancement of human intelligence has become a new topic in human-computer interaction research. When the robot can’t react correctly in a single mode, it is necessary to realize multimodal fusion. To this end, this paper proposes a multimodal fusion algorithm that applies the data obtained by the CNN feature layer to the decision-level. The speech recognition text is semantically matched with the text in the text library, and the similar probability vector is returned. At the same time, the similarity probability vector of the gesture recognition is obtained, and the data is filtered by the threshold, and the set of high probability data codes is assigned to the two modes. The intersection operation, and the final instruction is sent to the robot. The experimental results show that the influence of environmental factors on the single channel result is reduced, and the single mode ambiguity problem is eliminated. The multi-channel fusion algorithm with additional weight is more accurate than the common multi-channel fusion algorithm. At the same time, it has also been well received by many test users.
3D Natural Interaction for an Augmented Reality System

3D natural interaction is one of the topics actively investigated, by both researchers and developers, in order to provide more systems allowing users to interact with the 3D contents in an easy and an intuitive manner by using natural body inputs. In this work, we present an augmented reality system in which the user can interact naturally using the voice to select and manipulate 3D objects. Two ways are used to integrate vocal commands in the system (i) using the Speech Recognition API (Windows) as an offline solution (ii) using Speech Services (IBM Watson) as on the cloud solution. Furthermore, we show our application meant to teach the DNA molecule's 3D form, this application is capable of visualizing the whole molecule as well as its different components, it provides the user by multiple annotations to enhance their information and knowledge, also several voice commands can be used by pronouncing either simple words or longer phrases in a natural way.
Control of the “Cataphoresis” Process by Artificial Intelligence

The automotive industry is constantly seeking performance to remain competitive in a constantly changing market. This article discusses the modelling of an industrial process “cataphoresis” of a large automobile manufacturer via neural networks in order to control and optimize it in order to obtain the desired quality results at the lowest cost.
Finite Open-World Query Answering with Number Restrictions

Open-world query answering is the problem of deciding, given a set of facts, conjunction of constraints, and query, whether the facts and constraints imply the query. This amounts to reasoning over all instances that include the facts and satisfy the constraints. We study finite open-world query answering (FQA), which assumes that the underlying world is finite and thus only considers the finite completions of the instance. The major known decidable cases of FQA derive from the following: the guarded fragment of first-order logic, which can express referential constraints (data in one place points to data in another) but cannot express number restrictions such as functional dependencies; and the guarded fragment with number restrictions but on a signature of arity only two. In this paper, we give the first decidability results for FQA that combine both referential constraints and number restrictions for arbitrary signatures: we show that, for unary inclusion dependencies and functional dependencies, the finiteness assumption of FQA can be lifted up to taking the finite implication closure of the dependencies. Our result relies on new techniques to construct finite universal models of such constraints, for any bound on the maximal query size.
Assessing the Influence of Conflict Profile Properties on the Quality of Consensus

Asserting a high quality of data integration results frequently involves broadening a number of merged data sources. But does more always mean more? In this paper we apply a consensus theory, originating from the collective intelligence field, and investigate which parameters describing a collective affects the quality of its consensus, which can be treated as an output of the data integration, most prominently. Eventually, we identified, either analytically or experimentally, adjusting which properties of the conflict profile (input data) asserts exceeding expected integration quality. In other words-which properties have the biggest influence and which are insignificant.
TINDAK TUTUR DIREKTIF GURU DALAM PROSES PEMBELAJARAN BAHASA INDONESIA DI SMKS PENERBANGAN NUSANTARA KETAPING

This research is motivated by the problem of misunderstanding between students and teachers in the learning process. This misunderstanding occurs because students are not able to understand the intentions and goals of the teacher. The goals and objectives of the teacher cannot be well received by students because the form of speech acts that teachers use are not appropriate to the situation when they speak. The purpose of this study is to describe the politeness of language in the speech acts of the teacher directive in learning Indonesian at Nusantara Ketaping Flight SMKS, which is limited to the types of speech acts asking and begging. The results of the study showed that the forms of speech acts were instructed and begged that the teacher used in the learning process, both directly and indirectly. Keywords: speech acts, directive, teacher, learning
LibGuides: Hospitality: Home

A comprehensive guide to all the resources the Library service provides to support you with your course.
Play Views and Templating with Scala

By default, views in Play are HTML and they can be made dynamic using the Scala expression language. In fact, you can return a JSON or XML response as well if necessary. Let’s focus first on HTML Scala views and how the Play template engine helps you to create modular, expressive, and fluid views. Even though the template engine uses Scala as the expression language, this is not a problem for Java developers. The Scala language used in templates is very simple. As you saw in Chapter 1 , the template engine used by Play is Twirl. Recall that the template files must be named {name}.scala.{ext}. The ext can be html, js, xml, etc. Play prefers convention or configuration. When you compile, the compiler will generate Scala source files and they will be compiled along with the rest of the source code.
THE USE OF SELF-REFLECTIVE STRATEGIES IN TEACHING READING FOR STUDENTS OF VOCATIONAL SENIOR HIGH SCHOOL AT SMKN 1 LAMONGAN

This study aims to describe the use of self-reflective strategies in teaching reading at a vocational senior high school. Self-reflective strategies used in enhancing the students of vocational senior high school to reflect their comprehension on the given reading materials. This activity was considered effective in order to practice and drill the students’ critical thinking. The strategies should be implemented repeatedly to make the students more skillfully creating their comprehension on the given reading materials by integrating the keywords extracted from the given reading materials. This study was implemented in experimental design at two classes of Institutional Finance Accounting department (Akuntansi Keuangan Lembaga/AKL) class Xth. The experimental class was class Xth AKL1 that it consisted of 35 students. The control class was class Xth AKL2 consisted of 34 students. Class Xth AKL1 was chosen as the experimental class based on the class’ mean of the pretest that it was 2 points lower than class Xth AKL2. The () of the pretest score from class Xth AKL1 was 76. The of the post-test score from the experimental class was 86. The N-Gain score after having treatment from class Xth AKL1 was 70.7 in percentage. It can be assumed that this strategy was adequately effective to apply to the students on the reading subject reflecting their reading comprehension and therefore, the students could adjust the strategies to achieve their profound reading comprehension.
Segmentation of Chart Images Using H-Means Algorithm

For chart analysis it is necessary to segment region of interest from background for better understanding of distinctive pieces of charts. Many different methods such as thresholding, clustering, compression-based methods etc. are proposed for image segmentation. But one of the simplest and unsupervised algorithm is k-means clustering algorithm. K means algorithm cannot generate value of K (number of clusters) pertaining to any input image at real time. It has specified cluster numbers for all types and pattern of images which results into improper segmentation of images. Thus a novel method H-Means algorithm is suggested in this paper which decides the number of clusters at real time depending upon the input image. H-means algorithm uses histogram to decide number of clusters by extracting peaks for each image and segments foreground from background. An image database of info charts over 5280 images covering 10 categories of chart images is introduced to the research community.
Deep Learning Method to Identify the Demographic Attribute to Enhance Effectiveness of Sentiment Analysis

Sentiment analysis and machine-learning techniques play an important role in analyzing social media networks datasets. The customers, who have different levels of demographic attributes pouring views, reviews and feedback on various products and services in social media networks everyday life, this enormous data emerged as major source to extract knowledge to take appropriate decision by companies and business organizations. Most of the sentiment analysis processes ignoring various demographic attributes of customers such as sex, age, occupation, income, location, etc. Different levels of demographic attributes of a customer have their own custom purchase preferences. Depending on the sex, customers will have different preferences, habits and taste of purchasing items. The proposed method focused on sex demographic attribute analysis of the customer to yield effective low-level analysis results. The major challenge in the proposed method is identifying the sex (Male/Female) of the customer by using South Indian names. The proposed system implemented using multi-layer perceptron deep learning method and achieved best train and test accuracy results than decision tree, random forest, k-neighbors, support vector machine (SVM), Naive Bayes. The low-level demographic attribute feature extraction analysis enhanced the effectiveness of the sentiment analysis.
Design and Development of Information System for SMB II Museum Collection Management

This paper discusses the design and development of an information System for museum collections management to improve its performance for preserving Palembang cultural artifacts stored in Sultan Mahmud Badaruddin II (SMB II) Museum. This developed information system effectiveness to manage the museum collections where the information can be saved and retrieved by user efficiently Therefore the information can be access and utilized for service quality improvement of the museum. Hopefully, it can protect, improve understanding, and dissemination of cultural heritage as the identity of the Palembang Society.
Secure Data Packet in MANET Based Chaos-Modified AES Algorithm

Security is one of the more challenging problem for wireless Ad-Hoc networks specially in MANT due their features like dynamic topology, no centralized infrastructure, open architecture, etc. that make its more prone to different attacks. These attacks can be passive or active. The passive attack it hard to detect it in the network because its targets the confidential of data packet by eavesdropping on it. Therefore, the privacy preservation for data packets payload which it transmission over MANET has been a major part of concern. especially for safety-sensitive applications such as, privacy conference meetings, military applications, etc. In this paper it used symmetric cryptography to provide privacy for data packet by proposed modified AES based on five proposed which are: Key generation based on multi chaotic system, new SubByte, new ShiftRows, Add-two-XOR, Add-Shiftcycl.
RRT를 활용하여 향상된 이종의 개미군집 기반 경로 계획 알고리즘

Path planning is an important problem to solve in robotics and there has been many related studies so far. In the previous research, we proposed the Heterogeneous-Ants-Based Path Planner (HAB-PP) for the global path planning of mobile robots. The conventional path planners using grid map had discrete state transitions that constrain the only movement of an agent to multiples of 45 degrees. The HAB-PP provided the smoother path using the heterogeneous ants unlike the conventional path planners based on Ant Colony Optimization (ACO) algorithm. The planner, however, has the problem that the optimization of the path once found is fast but it takes a lot of time to find the first path to the goal point. Also, the HAB-PP often falls into a local optimum solution. To solve these problems, this paper proposes an improved ant-inspired path planner using the Rapidly-exploring Random Tree-star (RRT*). The key ideas are to use RRT* as the characteristic of another heterogeneous ant and to share the information for the found path through the pheromone field. The comparative simulations with several scenarios verify the performance of the improved HAB-PP.
Semiparametric two-sample mixture components comparison test

We consider in this paper two-component mixture distributions having one known component. This is the case when a gold standard reference component is well known, and when a population contains such a component plus another one with different features. When two populations are drawn from such models, we propose a penalized Chi-squared type testing procedure able to compare pairwise the unknown components, i.e. to test the equality of their residual features densities. An intensive numerical study is carried out from a large range of simulation setups to illustrate the asymptotic properties of our test. Moreover the testing procedure is applied on two real cases: i) mortality datasets, where results show that the test remains robust even in challenging situations where the unknown component only represents a small percentage of the global population, ii) galaxy velocities datasets, where stars luminosity mixed with the Milky Way are compared.
ROCK PAINTING:EKSPLORASI TEKNIK MELUKIS3 DIMENSI PADA MEDIA BATU

The creation of Rock Painting: Exploration of 3-dimensional paintingtechniques on rock media is an experiment in the use of media in painting toenrich the realm of contemporary art. To support the presentation of the work tomake it look more meaningful it will be displayed together with the Noah ShipReplica, with the theme Representation of Noah's Ark Ship with Rock Painting.If the stone has been considered worthless then a rock art creator is likea sparkling gem. Painting on stone media that has a porous surface, and is curvedand irregularly requires certain skills. The Creation Process includes;Exploration, Design and Formation. The material used in the creation ofpaintings on the stone media is Acrylic Gouache, water and brushes. From theresults of the creation carried out it was found that the right technique forpainting on special stone media to achieve the goal of creation using naturalisttechniques and / or styles.
A REVIEW OF DIFFERENT MACHINE LEARNING ALGORITHM FOR DIGIT CLASSIFICATION

Handwritten digit recognition is the ability of a computer or a machine to interpret and receive intelligible handwritten input from various sources such as cameras, tablets, photographs and other devices. Today handwritten digits are used in checks, smart calculators etc. A complete handwriting recognition system handles formatting problem, reduce classification error, and recognize the broken digits. In this review paper, some recent techniques are conferred like SVM, k-NN, ANN, SDGBBPNN, SICoNNet and Classifiers fusion for digit recognition. The purpose of using these techniques is only to enhancing system capability of recognition. This paper gives brief description of techniques used particularly for digit recognition and provides idea which technique is appropriate.
THE EFFECT OF APPLYING ENGLISH NATIVE SPEAKER VIDEO ON THE STUDENTS’ ENGLISH PRONUNCIATION ACCURACY AT THE FIFTH SEMESTER STUDENTS AT THE ENGLSIH STUDY PROGRAM OF THE TEACHER’S TRAINING AND EDUCATION FACULTY THE UNIVERSITY OF SISINGAMANGAR

This research is an Experimental research design, the problem of the research is; Does the application of videos significantly affect on the students’ pronunciation accuracy? And the objective of the study is to find out whether the application of videos significantly affect on the students’ pronunciation accuracy. The sample of this research is the fifth semester students of English Study Program Faculty of Teacher’s Training and Education The University of Sisingamangaraja XII Tapanuli (UNITA) in Academic Year 2018/2019. There were three phases in conducting the research; Pre-test phase, Treatment, and Post-test within in four weeks. The instrument used to collect the data was pronunciation accuracy with thirty questions or words to be pronounced. Based on the data gathered and its analysis, in which the mean score of pre-test is lower than the mean score of post-test or 10.23809524 1.684. In other words, the Null Hypothesis (Ho) is rejected and the Alternative Hypothesis (Ha) is accepted. As a conclusion, there is a significant effect of the application of videos on the students’ pronunciation accuracy. Finally, based on the research conclusion, the researcher would like to recommend of using videos in dealing especially with English Phonology and Pronunciation.