Reviewerly/exHarmony huggingface dataset:
Jambi City Tourism Information System Design

The very rapid development of technology helps a lot in terms of disseminating information to be faster, more accurate, and not limited by place and time. Technology in the tourism sector is not only used as a promotional medium, but technology is also a learning medium for entrepreneurs in the tourism sector so it is important for the tourism sector to have an information system as a medium for disseminating information. The Jambi City Tourism Information System is an information system that contains a collection of information data that summarizes information about the region, province or tourism place in the city of Jambi which is compiled in a web-based information system, with this information system it can make it easier for the public to obtain information, accelerating the service of information sources. The design of the tourism information system in the city of Jambi is built in a web-based form with system design assisted by several tools such as the programming language PHP, Javascript, MySQL, Xampp, and Adobe Dreamweaver.
EFFORTS TO IMPROVE ACADEMIC SERVICE GOVERNANCE THROUGH OPTIMIZATION OF INFORMATION TECHNOLOGY AT GORONTALO STATE UNIVERSITY

&lt;p&gt;In maintaining the existence of the State University of Gorontalo, a quality higher education management system is needed to be able to adapt to the dynamics of change. Good governance of the State University of Gorontalo is a condition that ensures a synergistic process between internal elements and the support of external parties, as well as mutual control carried out by related components within an organization. This study aims to analyze what efforts can be made to improve the governance of academic services through optimizing information technology at the State University of Gorontalo. This research method is qualitative. Data collection was carried out through a literature study by tracing the sources of previously written writings obtained from various sources, journals, documentation books, the internet, and libraries. The results of the study show that efforts that can be made to improve the governance of academic services at the State University of Gorontalo are through structuring the management of functional aspects consisting of (1) Management of the academic service system centered on a curriculum that is adapted to the national curriculum, structuring the educational process cycle starting from student admissions. until graduation, and the arrangement of the Teaching and Learning Process; (2) The development and management of human resources starts from determining the number, quality, and effective teaching staff and education staff in accordance with the needs of higher education institutions to arranging pensions, dismissals, and severance pay for human resources; (3) The management of the financial performance system, namely the process of managing funds from receipt to use of the budget, can be properly accounted for based on applicable regulations; and (4) Improving facilities and infrastructure services by preparing all equipment/materials for the smooth implementation of the educational process. includes planning, procurement, storage of equipment items, maintenance, and removal.&lt;/p&gt;
Federal Depository Library Program (FDLP) Academic Library Websites A webometric analysis of academic libraries participating in the FDLP

The purpose of this study is to evaluate the website content of academic libraries participating as selective depositories in the FDLP to examine legal compliance and accessibility to electronic government information.
Reflection of Conditional Independence Structure to Noise Variability for Noise Robust Text Dependent Speaker Verification

In the field of speaker verification (SV), the development of noise-robust systems is a challenge for their deployment in real-world environments. Noise variability compensation is a common strategy for increasing the robustness to noise variations. The performance of noise compensation depends on how well the noise variability, which is inherent in within-class variability, is estimated. However, to date, there is no information about the true noise variability that could reduce the gap between the empirical and true statistics. Most studies assume that true noise covariates are independent. This study aims to demonstrate the assumption that true noise variability has a conditional independence structure rather than an independence structure. This assumption was motivated by our previous findings, which revealed that optimal within-class variability has a conditional independence structure in text-dependent speaker verification (TD-SV) in clean environments. This indicates that the optima of all the variabilities in within-class variability, except noise variability, has a conditional independence structure; however, it is unknown whether this is also true for optimal noise variability. Our assumption was supported by the experimental results obtained under noisy TD-SV trials using systems built with graphical least absolute shrinking and selection operator-based probabilistic linear discriminant analysis, which achieved up to 10% relative equal error rate improvements.
Web Sites Need Much More User-Driven Interactivity

Websites present information or services but often do not allow users to provide feedback or ask questions. The topic of this paper is to first discuss various types of interactivities that are currently available, and then explain what one would expect from advanced systems. The article makes it clear that much has still to be developed. We start by mentioning a number of currently used approaches and show that they almost exclusively belong to a category we call “provider-driven”. They miss the very desirable possibility of what we call “user-driven” feedback that is, at the most, available in a very rudimentary form. We then present some user-driven feedback attempts that culminate with a description of some of the features of a new system NID (for Net-Interactive Documents). We analyze and describe the first results obtained and, finally, summarize to show what future systems should provide.
Pengaruh Model Picture And Picture terhadap Hasil Belajar Siswa pada Subtema 2 Hidup Rukun dengan Teman Bermain pada Kelas II SD Negeri 091316 Pematang Raya

The purpose from research is to know the effect model picture and picture to study result students at subtema 2 hidup rukun dengan teman bermain to class II SD Negeri 091316 pematang raya.this research is a experiment with design quasi experiment.design used in research is pretest and posttest sample fro. Research in class experiment is class II-A class in SD negeri 091316 pematang raya and research sample in control class is students II-B class in SD negeri 091316 pematang raya.based analysis result and from explain from research data by test result hypothesis with t-test where t-table : 3,69 if score significant (2- tailed) &lt; 0,05 ,so can different significant from result study students to experiment class and control class.the result from this research the score significant (2-tailed) : 0,001.so Ho not significant and ha significant.based the results from the effect model picture and picture to result study students in sub tema 2 hidup rukun dengan teman bermain in class II SD negeri 091316 Pematang Raya
An Interaction Effort Score for Web Pages

There is a lack of automatic evaluation models to measure the user experience (UX) of online systems, especially in relation to the user interaction.In this paper we propose the interaction effort score as a factor that contributes to the measure of the UX of a web page.The interaction effort is automatically computed as an aggregation of the effort on each interactive widget of a page, and for all users that have interacted with them.In turn, the effort on each widget is predicted from different micro-measures computed on the user interaction, by learning from manual UX expert ratings.This paper describes the evaluation of the interaction effort of different web forms, and how it compares to other metrics of usability and user interaction.It also shows possible applications of the interaction effort score in the automatic evaluation of web pages.
TbNet: three-branch network to guide deep completion

The depth maps obtained from current LiDAR scans are relatively sparse, while dense depth maps are needed. In this paper we propose a fusion-based RGB image and semantic image to jointly guide the deep completion. The RGB images, semantic images, and sparse depth images are fused after feature extraction, respectively. Specifically, we first perform depth estimation on the RGB image to generate the color depth. Then the color depth is fused with the semantic image to estimate the semantic depth. Finally, the color depth and semantic depth together lead to the complementation of the sparse depth map. To generate more accurate dense depth maps. In this paper, the fusion module (AFF) is added in some branches to fuse the color depth and semantic depth sparse depth maps. Under the test of public dataset KITTI, the experimental results show that the depth map predicted by the proposed depth completion model in this paper is more accurate compared with the backbone of the depth completion method guided by RGB only.
Preface

Social media study and analysis brings researchers from many fields into a single setting. Even though the tasks of these researchers are varied, data visualization and analytics plays an important role. For industry and academics alike, visualization of social media data helps with hypothesis formation and supports the explanation of phenomena. This second workshop on social media visualization is a venue for the presentation of research and applications of visualization to social media data. Its goal is to bring together researchers and industry practitioners interested in visual and interactive techniques for social media analysis, particularly in social sciences and humanities as well as in industry.
A Model for Learning Cause-Effect Relationships in Bayesian Networks

The study of causality has its origins more than 300 years ago; several disciplines have focused efforts on explaining the natural causal process, for example, Cognitive Psychology (CP) and Artificial Intelligence (AI). Performing a causal inference may be a simple task for humans, for that there are multiple efforts to replicate and explain causality based on prior knowledge. From CP, there have been proposals that aim to describe how are learned naturally cause-effect relationships, and from AI, multiple algorithms have focused on estimating or predicting causality, such as the intervention of variables in Bayesian Networks (BN). However, this method requires prior knowledge that indicates the cause-effect direction within the connections in the network. Our principal goal is an integrated algorithm for the construction of graphical models (CBN) such from datasets can learn the causal relationships giving direction to the arcs and identify causes-and-effects within the network. The results obtained with this approach have been encouraging. The CBNs acquired can be used to intervene variables and estimate causal probabilities. We have tested with real datasets from repositories and comparing our results with an algorithm (and two metrics) belonging to the AI.
The implementation of choral reading method in improving student’s reading fluency

This study aims to improve students' Students Reading Fluency through Choral Reading Method at the Seventh Grade Students of SMP N. 1 Botupingge. This research is a Classroom Action Research (PTK). The subjects of this study are the students of grade VII SMP N. 1 Botupingge who numbered 22 students. This study consists of two cycles. Each cycle consists of four stages, namely planning, implementation, observation, and reflection. Data collection techniques used in this study is test observation, and documentation. The research instruments used include the observation sheet, the test of reading fluency (accuracy, Rate, and Prosody) and documentation. The collected data were analyzed using qualitative descriptive analysis technique and supported by quantitative data. The results of this study indicate that the implementation of choral reading can improve students’ reading fluency in students of class VII SMP N. 1 Botupingge both in terms of process and product. The improved processes can be seen in student activities in the learning process. This is indicated by the increase of students in attention to learning, enthusiastic liveliness, and atmosphere of learning in the classroom more conducive. Improving process quality has a positive impact on product quality improvement. This is seen in the test results of reading fluency starting from cycle 1 up to cycle 2. Based on this result, it can be concluded that choral reading method can improve students’ reading fluency at seventh grade of SMP N. 1 Botupingge.
Improvement Accuracy Identification and Learning Speed of Offline Signatures Based on SqueezeNet with ADAM Backpropagation

Signatures play an essential role in human life because they are used as an authentication approach in organizations such as banks, businesses, and legal authorities. In offline signature identification, dynamic information such as velocity of the stroke, hand vibration, signature image position and pen pressure from the signature writing process is lost, so offline analysis has less information and as a result the identification becomes more complicated. Currently, from various websites, there are many electronic documents that contain offline signatures. This leads to the problem of offline signature identification. Offline signature identification can be viewed as part of the Fine-Grained Visual Classification (FGVC) problem. FGVC research is a challenge because there are problems with fine-grained datasets and it can quickly become a big problem due to factors such as angle of view, tilt, and the location of objects in the image. In recent years, Convolutional Neural Networks (CNN) are a powerful and very successful approach for identification purposes. In this research, a CNN with small networks architecture namely SqueezeNet is optimized using Adaptive Moment Estimation (ADAM) to achieves high accuracy and learning speed, it is trained using four public signature datasets, namely BHSig260-Bengali, BHSig260-Hindi, CEDAR, UTSig and then it is tested to identify the original signature samples taken from each dataset. The optimized SqueezeNet achieves better results compared with other deep learning or machine learning algorithms. The optimized SqueezeNet takes under 3 minutes to train networks for each dataset and its identification average accuracy reaches above 99,79% for each dataset.
Help Transformer Improve Performance in Automatic Mathematics Word Problem-Solving

Solving Mathematics Word Problem (MWP) is a basic ability of humanity, which can be mastered by most students at a young age. The existing artificial intelligence system is not good enough in numerical questions, like MWPs. The hard part of this problem is translating natural language sentences in MWP into mathematical expressions or equations. In recent researches, the Transformer network, which proved a great success in machine translation, is applied to automatic mathematic word problem-solving. While previous works have only shown the ability of Transformer model in MWP, how multiple factors such as encoding, decoding, and pre-training affect the performance of Transformer model has not received enough attention. The study is the first to examine the role of these factors experimentally. This paper proposes several methods to improve Transformer network performance in MWPs under the basis of previous studies, achieves higher accuracy compared to the previous state of the art. Pre-training on target tasks dataset improves the translation quality of the Transformer model greatly. Different token encoding and search algorithms also benefit prediction accuracy at the expense of more training and testing time.
Are Crescia and Piadina the Same? Towards Identifying Synonymy or Non-Synonymy between Italian Words to Enable Crowdsourcing from Language Learners

We introduce a method to generate candidate pairs of related Italian words sharing (or not) synonymous relations from the ConceptNet knowledgebase. The pairs are intended to generate questions for a vocabulary trainer which combines exercises to enhance vocabulary skills with the implicit crowdsourcing of linguistic knowledge about the semantic relations between words. Our method relies on the idea that pairs of synonyms in a language tend to translate to pairs of synonyms in other languages. We generated 85k candidate pairs of Italian synonyms that can be used to produce questions for both teaching (3.8k pairs) and crowdsourcing purposes (80k pairs). Follow-up efforts are however needed in order to generate a complementary set of questions.
Evaluation of Success Factors in Adopting Artificial Intelligence in E-Learning Environment

This paper focuses on assessing the critical success factors [CSF]in the adoptionofartificial intelligence (AI) technology in E-learning. It is a quantitative assessment study based on the students and teachers’perceptions of United Arab Emirates the Joint Command and Staff College (JCSC). Data was collected using questionnaire survey where the questionnaire was distributed to a total of 240 JCSC students and teachers of the college however only 207 completed forms were received. The questionnaire contained 20 CSF in seven group to investigate the level of importance of each CSF in adopting AI and E-learning using 5-points Likert scale. The data was analysed descriptively using SPSS software package. The results of the analysis found that eighteen of twenty CSFs considered in the investigation are reported as high level of importance. The most important CSF is that “AI systems able to compute big data for improving teaching” with having the highest mean score of 4.04 in adopting AI technology in E-learning for the UAE military colleges. In term of factors’ group, the most important group is “making education more interesting’’ with having mean score of 3.98. however, further analysis found that respondents having higher degree picked personalizationgroup while respondent having a lot of teaching experience respondents picked performance monitoringgroup of factors as the most critical success factors groups. The findings from this study are very helpful in formulating strategies for the promotion of AI advanced technology in the education system and getting its maximum benefits.
Adaptive Joint Interdependency Learning for 2D Occluded Hand Pose Estimation

Hand pose estimation based on 2D RGB images has drawn increasing research interest due to its many practical applications, such as Human-Computer Interaction (HCI) and Virtual Reality (VR). However, most existing methods focus on learning hand structure and key point representations, which cannot well exploit the joint interdependency of 2D occluded hand pose estimation. In this paper, we propose an adaptive joint interdependency learning network (AJIL) for 2D occluded hand pose estimation by adaptively learning hand joint interdependency, including three sub-networks. First, a cascade multi-task mask-learning subnetwork is used to learn hand pose structure. Then, a modified transformer encoder is designed to exploit the high spatial relationship between the hand joints. Lastly, the joint correlation is obtained from the multi-view hand pose images via 21 long short-term memory (LSTM). Extensive studies on three widely used datasets including the CMU Panoptic Hand, Large-Scale Multiview Hand Pose, and also our newly established pen-holding hand pose (PHHP) images dataset which is conducted to evaluate our proposed method. Experimental results show that our proposed method can achieve a very competitive 2D hand pose estimation performance when compared with the baseline models.
APPLICATION OF SENAYAN LIBRARY MANAGEMENT SYSTEM (SLIMS) FOR LIBRARY COLLECTION AND INFORMATION MANAGEMENT AT RELIGIOUS TRAINING CENTER OF ACEH

Library management ideally use an automation system to provide optimal services. However, the library management in The Religious Education and Training Center of Aceh (BDK Aceh) has been done manually, which impacted on less effective and efficient performance. Therefore, it is important to optimize the library management at BDK Aceh. This study focused on describing the stages in optimizing the collection management of the BDK Aceh library through Senayan Library Management System (SLiMS) application. Sources of data in this study were the Head of BDK Aceh, librarian, staffs, and trainers of BDK Aceh. This study showed seven stages of SLiMS utilization; (1) coordinating and consulting, (2) downloading and installing SLiMS into the library computer, (3) uploading the bibliographic data of library collections on the SLiMS application, (4) uploading the cover of library collections, (5) setting the SLiMS online to the internet, (6) socializing the automation system, (7) evaluating the automation system. This library management using SLiMS at BDK Aceh has resulted in five outputs, namely: (1) bibliographic databases in digital form, (2) video tutorials on the use of automation systems, (3) an online library with the website librarybdkaceh.com, (4) online circulation services, and (5) automatic library membership cards. The use of the SLIMs escalates performance in library collections managements, thus resulted in better service quality which suits the regulations of the industrial revolution. Users can easily browse information about library collection and access the BDK Aceh library anywhere and anytime through the website. In addition, users can get quick and accurate information about library collections. Keywords: Library Management, Library Automation System, SLIMS
A Software Defect Location Method based on Static Analysis Results

Code-graph based software defect prediction methods have become a research focus in SDP field. Among them, Code Property Graph is used as a form of data representation for code defects due to its ability to characterize the structural features and dependencies of defect codes. However, since the coarse granularity of Code Property Graph, redundant information which is not related to defects often attached to the characterization of software defects. Thus, it is a problem to be solved in how to locate software defects at a finer granularity in Code Property Graph. Static analysis is a technique for identifying software defects using set defect rules, and there are many proven static analysis tools in the industry. In this paper, we propose a method for locating specific types of defects in the Code Property Graph based on the result of static analysis tool. Experiments show that the location method based on static analysis results can effectively predict the location of specific defect types in real software program.
The essence and structure of military skill

The article deals with the issues of military competence, the integrative quality of officers, representing a set of professionally significant qualities, the ability and willingness to solve professional problems and tasks that arise in real situations of military activity, using knowledge, skills, abilities, professional and life experience, values and culture. The military-professional skill of military labor and including military-professional knowledge, skills and abilities, which are, on the one hand, the prerequisites for the successful activity of the future officer, on the other hand, neoplasms, they themselves develop and are enriched with knowledge in the course of study and service of the future specialist.