Reviewerly/exHarmony huggingface dataset:
Degree of Effectiveness of Computer-Based Systems in Achieving International Accreditation Standards (CAEP) at the Faculty of Educational Sciences at University of Jordan

The study aims to reveal the degree of effectiveness of computer-based systems in achieving international accreditation standards (CAEP) at the Faculty of Educational Sciences at the University of Jordan. The study sample consists of individuals purposely selected from all the 85 faculty members at the Faculty of Educational Sciences at the University of Jordan. To achieve the objectives of the study, a descriptive and analytical approach is used. The study instrument is prepared and developed and electronically distributed during the second semester of the academic year 2019/2020, and the number of respondents to study instrument is (77) faculty members.The study shows that the degree of effectiveness of computer-based systems in applying the standards of (CAEP) from the viewpoint of faculty members is of high level. In light of the results of the study, the researcher recommends measuring the level of effectiveness of computer-based management information systems used in universities periodically to develop them and increase the level of effectiveness of these systems, and continuously update the computer-based systems used so that the Faculty of Educational Sciences at the University of Jordan can obtain international accreditation and achieve (CAEP) standards.Keywords: The University of Jordan, international accreditation, CAEP standards, the effectiveness of computer-based systems.
Online Learning Implementation Training for Teachers of SDN Bangetayu Kulon

The partner in this community service was SDN Bangetayu Kulon, Genuk, Semarang. The teachers experienced difficulties to conduct online learning and assessment. Whatsapp had been their main platform to deliver the material and weekly evaluation to their students. The output targets in this PKM were: (1) creating and operating an online classroom in Edmodo; (2) creating online assessments using Kahoot! and Quizizz; (3) evaluating students learning achievement based on the online assessment. The methods used in this PKM were lecturing, question and answer, and direct practice. The results showed that all teachers have succeeded to create and manage an online class in Edmodo and conducting online assessments by using Kahoot! and Quizizz.
Modeling the Impact of Investment on Population Welfar

Improving of investment capital that flows into country’s economy is transformed into productive or innovative capital and has a significant impact on improving the purchasing power of the population. Banerjee’sresearch(BanerjeeandDuflo,2011)states the need to invest in the development of education and science to overcome poverty in the world. As a resultoftheseresearches,fivemillionIndianchildrenhave benefited from effective corrective educational programs at schools. That is, investments flowing into the economies of countries should be directed in innovative educational programs. However, the search for new ways to support and develop the economy is taking place at a time when many countries are experiencing stagnation, reduction of production and innovation activities financing
Information Architecture Front and Center: In Conversation with Keith Instone

Interview about enterprise information architecture practices, the changing role of the information architect, the importance of the Academics and Practitioners Roundtable to support research and academia in the field of IA.
Offline Odia Handwritten Characters Recognition Using WEKA Environment

Optical character recognition (OCR) is an image analysis technique in the document where digital images (scanned) that contain handwritten script or machine printed script is used as input into a system to convert it to editable machine readable text format. In the current era, OCRs development for regional script is an active field of cutting edge as research, such as Odia, Telugu and Bengali. Particularly, in Odia language, it is a great challenge to an OCR inventor due to various categories of character in the alphabet. Further it is also required to combine the different letter in Odia, and many characters are roundish similar in loop. In this paper, WEKA software has been used to build classification model for offline character recognition. Hence, this research work has been attempted toward development of a novel algorithm for classification of offline handwritten Odia character recognition using Naive Bayes and decision table in WEKA environment.
Towards a parallel corpus of Portuguese and the Bantu language Emakhuwa of Mozambique

Major advancement in the performance of machine translation models has been made possible in part thanks to the availability of large-scale parallel corpora. But for most languages in the world, the existence of such corpora is rare. Emakhuwa, a language spoken in Mozambique, is like most African languages low-resource in NLP terms. It lacks both computational and linguistic resources and, to the best of our knowledge, few parallel corpora including Emakhuwa already exist. In this paper we describe the creation of the Emakhuwa-Portuguese parallel corpus, which is a collection of texts from the Jehovah's Witness website and a variety of other sources including the African Story Book website, the Universal Declaration of Human Rights and Mozambican legal documents. The dataset contains 47,415 sentence pairs, amounting to 699,976 word tokens of Emakhuwa and 877,595 word tokens in Portuguese. After normalization processes which remain to be completed, the corpus will be made freely available for research use.
Feature Replacement and Combination for Hybrid ASR Systems.

Acoustic modeling of raw waveform and learning feature extractors as part of the neural network classifier has been the goal of many studies in the area of automatic speech recognition (ASR). Recently, one line of research has focused on frameworks that can be pre-trained on audio-only data in an unsupervised fashion and aim at improving downstream ASR tasks. In this work, we investigate the usefulness of one of these front-end frameworks, namely wav2vec, for hybrid ASR systems. In addition to deploying a pre-trained feature extractor, we explore how to make use of an existing acoustic model (AM) trained on the same task with different features as well. Another neural front-end which is only trained together with the supervised ASR loss as well as traditional Gammatone features are applied for comparison. Moreover, it is shown that the AM can be retrofitted with i-vectors for speaker adaptation. Finally, the described features are combined in order to further advance the performance. With the final best system, we obtain a relative improvement of 4% and 6% over our previous best model on the LibriSpeech test-clean and test-other sets.
MUONS path planning performance for a vehicle with complex suspension in Unreal

We present an overview of MUONS: the Michigan tech Unstructured and Off-road Navigation Stack. MUONS is a ROS-based point-cloud-based navigation stack designed to enable traversal of complex terrain that may exceed vehicle kinematic limits. We originally developed MUONS for small to mid-size skid-steer autonomous ground vehicles with no suspension. In this work we examine how MUONS performs on a simulated full-scale vehicle with complex suspension elements. By comparing the performance of the full-scale and mid-size vehicle we aim to identify the critical vehicle linkages that must be included in our simulation model. We also aim to understand the necessary changes and modifications required to adapt MUONS to full-scale Ackerman steering autonomous ground vehicles with complex suspensions.
USING EVOLUTIONARY GAMES THEORY FOR PLAYERS BEHAVIOR ANALYSIS IN COMPETITIVE SHOOTING GAMES: A LITERATURE REVIEW

The paper is dedicated to the overview of current state of the evolutionary games approach to the building of environments to analyze players behavior. The evolutionary game theory applications differ from the orthodox game theory. Initially, it was used to address problems in evolutionary biology and later was suited for broader range of problems.We will oversee the development of the evolutionary games theory in finance and its applications in behavior analysis in competitive gaming. The paper is focused on replicator dynamics, learning model based on it and its possible application to behavior analysis based on fuzzy algorithms and approaches used in economics to be applied to the new emerging field of cybersports.
The Feasibility of Information Technology Infrastructure according to the Regulation of the Minister of National Education No.40 of 2008: A Case Study at SMK Palembang City

The feasibility of infrastructure to determine the level and feasibility of Information Technology Vocational Schools in Palembang City. Based on research according to Permendiknas No. 40 of 2008 contains computer laboratory furniture, including: the ratio of the number of student chairs and desks, the ratio of the number of teacher chairs, computer equipment, and educational media. This research methodology uses quantitative methods, where the data collection method is obtained from a questionnaire of information users as respondents. Data analysis used SPSS version 20 for data processing. The analysis results obtained according to Permendiknas No. 40 of 2008 and referring to O'Brien's theory, namely as follows: SMK Negeri 1, SMK Negeri 2, SMK Negeri 3, SMK Negeri 4, and SMK Negeri 5 Palembang, the achievement in the category is less feasible, namely with an average percentage of 5.6% , while 27.77% with a decent category achievement and 66.7 with very decent category.
Symbolic dynamics for radar target maneuver detection

In radar target tracking, knowledge of the true dynamics of target motion is paramount for accurate state estimates. In this paper, we propose a method of target maneuver detection utilizing symbolic dynamics. We demonstrate its ability to compete with other commonly used maneuver detectors. This is done through simulations performing target maneuver detection.
Δημιουργία υβριδικού συστήματος παροχής συστάσεων με την αξιοποίηση τεχνικών ανάλυσης συναισθήματος (sentiment analysis) των αξιολογήσεων χρηστών σε ηλεκτρονικές συναλλαγές

Internet’s ceaseless development has instigated major changes over the last decades, both in the way people get informed and communicate and the public’s consumer habits. Electronic commerce accounts for a modern alternative to purchasing, however, the vast mass of available information in online shopping can make for a complicated process. Recommender Systems are called to solve these challenges by locating products or services according to each user’s interests. In this thesis, we consider the theoretical basis of Recommender Systems, as well as the methods used in electronic commerce in order to facilitate users’ browsing experience by proposing products and services that match their needs. We introduce applications and algorithms of Machine Learning and analyse Recommender Systems’ combinations with Machine Learning algorithms that have been created in order to generate more efficient suggestions. Later on, we develop a Recommender System that deploys a data base with products from Amazon and implements suggestions according to the Model-based Collaborative Filtering System model, based on the products that are being sold and the users’ reviews. Afterwards, we implement the same Recommender System model, combined with Natural Language Processing. Finally, we inspect the results from both models and evaluate them based on efficiency.
Integrated Monitoring System to Improve the Procurement Process through Provider with an End-User Development Approach (Case Study: XXX Institute)

This study aims to identify problems in procurement activities through providers at XXX Institute and to provide solutions to improve the procurement process through providers with an integrated system design to monitor the procurement process at XXX Institute. XXX Institute under the authority of Government that services in education and training. XXX institute are required to follow the procedures and rules set by the government to achieve the procurement objectives as stipulated in Presidential Regulation No. 16 Tahun 2018. Based on the identification problems, some obstacles is still existing in the procurement activities at XXX Institute due to negligence of procurement parties. An integrated monitoring system is needed for procurement parties to monitor the procurement process, so that the impact of procurement inconsistencies can be systematically resolved. In this research, the theories uses the PIECES Framework and the FAST method developed by Whitten and Bentley (2007) to identify problems in the system and create a system design to overcome these problems. The system design uses the end-user development system design process. According to Marshall B. Romney (2018) end-user development is a computer-based application which is the users can manage and develop the system. The result of the system design is a system to monitor every process of procuring goods or services at XXX Institute.
Growing Neural Gas Based Space Structure Learning for Feature Vector Composed of Multiple Properties

Space recognition is one of the most important capabilities for intelligent autonomous robots that work in unknown environments. For realizing the space recognition, Growing Neural Gas (GNG) based approaches have been proposed by many researches since the GNG can learn a space structure and generate a topological structure simultaneously. However, GNG cannot preserve the space information if the input vector is composed of multiple properties. For solving this problem, this paper proposes GNG with Different Topologies (GNG-DT) that has the multiple topological structures according to the number of properties. In addition, the learning result of GNG-DT does not depend on the scale in the input vector. Finally, we conduct on several experiments for evaluating our proposed method by comparing to other conventional approaches, and discuss the effectiveness of our proposed method.
Secure Data Access Control with Cipher Text Update and Computation Outsourcing in Fog Computing for Internet of Things

Fog Computing is a region of Computer Science that is under steady construction and development, and related to data security, the worldview turns out to be more solid and secure for IoT's edge stages. The verification of limited memory devices has serious issues since memory utilization is high when applied with different models that have the motivation behind shared confirmation. In this paper, we propose the Novel cipher text-based encryption model (NCEM) which has an information access control plot dependent on Ciphertext-Policy it give information privacy, fine-grained control, and mysterious validation in a multi-authority fog computing framework. The sign cryption and plan cryption overhead for the client is altogether diminished by redistributing the bothersome calculation tasks to fog hubs. The proposed conspire is demonstrated to be secure in the standard model and can give trait repudiation and public unquestionable status. The security analysis, asymptotic multifaceted nature examination, and implementation results demonstrate that our construction can offset the security objectives with useful effectiveness in calculation.
Analisis Kesalahan Penulisan Ejaan Dalam Soal Uas Bahasa Indonesia Tingkat SMP

Final Examination (UAS) is one of the evaluation tools used to determine the development of learning outcomes that have been carried out for one semester. Therefore, in its implementation must be prepared carefully, including in making questions. but in reality when preliminary observations and analyzes of some Final Examination Semester (UAS) questions especially in Indonesian Language at junior high school level, there are still many questions that contain language errors, especially errors in spelling writing. The purpose of this study, namely: 1) Describe the form of writing errors in letters or the use of letters in the Indonesian junior high school level final examination and explain the correct form of questions. 2) Describe the form of writing punctuation errors in Indonesian junior high school final examination and explain the correct form of questions. 3) Describe the form of writing errors in junior high school level Indonesian final examination and explain the correct form of questions. The method used in this study is a qualitative description. The data in this study are in the form of writing spelling in the matter of Indonesian Junior High School UAS. Data collection techniques are done by listening and note taking. While the data analysis technique is done by the lingual equivalent method. The results of this study indicate that the analysis of spelling errors in the Indonesian UAS level at the junior high school level is mostly found in the use of punctuation which is as much as 50%, then followed by the use of letters 32.5% and writing words 17.5%.
Review of standards for creating training materials in learning management systems

Creating educational content requires certain rules for creating content, as well as a number of specific stages of its creation, mechanisms and tools that are directly involved in this process. This paper provides an overview of the standards of creation, maintenance of electronic learning materials using learning management systems, as well as analysis and evaluation of their use of ontological systems. Four generations of standards for the creation and maintenance of e-learning materials and a description of each of them: the name of the standards for creating and maintaining the life cycle of e-learning course, as the basic principle of grouping e-learning materials. For some standards, the abbreviation of the standard name and a description of the features of the version are provided. Separately for each such standard the architecture and features of construction of a training course as the carrier of the educational information, its structural features, the applied software interface, principles of construction of electronic educational content with use of the above-stated standards are described. The question of further prospects for their development remains unanswered. Issues related to the process of designing the components of the training course, establishing links and relationships between them are considered separately. In particular, this review is an attempt to consider the standards of the course as allowing to create materials using ontological systems with hierarchical structuring of teaching materials and its subsequent support, as well as to assess the availability of tools to create ontologies as components for the presentation knowledge. In case of a negative answer, a constructive solution to this problem should be offered.
Robust and Non-Degradable System for Detection and Forecast of Earthquake Based on IoT and Machine Learning

The crust of the earth releases stored energy suddenly which produces the seismic waves. These waves can shake the surface of the earth which is called an earthquake. Mostly frequent earthquakes are seen in the areas which fall under seismic zone but they can appear in any geographical region. Earthquake takes only a few seconds to damage life and property in a broad stretch of land. At the point when quakes happen in urban regions, the outcomes of these catastrophes are essentially more horrific due to the losses and degree of the harm to the living bodies and property that is caused. After the earthquake, its aftershocks and Tsunami are having a high probability to occur which further creates fear among individuals living in the influenced region. Hence, there is a need for designing an innovative system for the detection and forecast of earthquakes which will be the best solution for a sustainable society.In this paper, we primarily concentrate on the investigation of the current scenario for earthquake detection, its prediction techniques and the problems associated with them. First, we analyze the various existing methods of detection using wireless sensor nodes and then IP based WSN and the Internet of Things (IoT). Then we analyze the data acquisition techniques using various protocols. Then we analyze the data processing and earthquake forecasting techniques. Based on the above discussions we analyze the shortcomings and propose a system for the solution.
Peningkatan Hasil Belajar IPA Melalui Implementasi Model Pembelajaran Discovery Learning di Sekolah Dasar Kota Banda Aceh

Science is learning that is very closely related to human life, many natural instruments are directly involved in teaching and learning processes. One of the objectives of this study is to see the effect of the Discovey Learning model on student learning outcomes, the Discovery Learning learning model is a learning process that can involve mentally and physically students, so that the learning obtained can last a long time in the memory of students. This research was conducted at SD N 55 Banda Aceh, after observing the learning process of students showing less than optimal results. It can be seen from the learning outcomes before the application of the Discovery Learning model the average learning outcomes are 37 while the average obtained after the application of the Discovey Learning Model is 73. In addition, based on the results of the calculation of the hypothesis that have been determined by the hypothesis acceptance rules, accept Ha If tcount&gt; ttable, the results obtained are degrees of freedom (dk = n-1 = 34-1 = 33) and the significant value is α = 0.05, for this calculation the t-table is 2.19. From the above calculations using the t-test shows that tcount&gt; ttable (2.19&gt; 1.697). The results of the analysis of the average N-gain obtained reached 50 which was categorized as moderate.
호소수 수질변동에 따른 GAC/MF시스템에 의한 정수처리

Membrane filtration technology has been applied to drinking water treatment and, grown steadily with public demand for high water quality and strict regulations. Membranes are considered a promising material to provide better quality drinking water by removing bacteria, viruses, microorganisms as well as particulate and organic matter. This study aims to investigate the effect of granular activated carbon (GAC) adsorption as a pretreatment before membrane filtration (MF) processes and evaluate the performance of GAC/MF systems for the treatment of lake water. Specifically, on water that has a relatively safe drinkable quality, which will depend on seasonal changes. Applied filtration rates during this experiment were <100 m/d for GAC and 0.5 m3/m2.d for MF. As a result, both GAC bed and GAC/MF system achieved more than 90% efficiency in removing turbid and organic matters corresponding to UV254 and dissolved oxygen carbon (DOC). This indicates that the GAC adsorption and filtration was considerably effective for reducing foulants. The transmembrane pressure (TMP) at increased MF rates was in proportion to the increased humic acid rates in the range of 2 to 10 mg/.L These results indicate that the addition of a GAC bed prior to the membrane filtration process is necessary for cost-effective lake water treatment due to both efficient reductions of organic and turbid matter and membrane fouling mitigation due to reduction of the TMP.
One Plaintext Attack on the BFV Scheme

The issue of data security is one of the key issues of using homomorphic data encryption algorithms. In this article, we investigate the computational indistinguishability of the homomorphic encryption scheme BFV. We propose a scenario in which attackers can find out the secret key, which can potentially lead to information leakage. We show that the postulate of the BFV scheme to increase the level of security by introducing an additional error is erroneous.