Reviewerly/exHarmony huggingface dataset:
Cross-View Image Translation Based on Local and Global Information Guidance

The cross-view image translation task is aimed at generating scene images from arbitrary views. However, due to the great differences in the shapes and contents of the various views, the quality of the generated images is degraded. Small objects, such as vehicles' shapes and details, are not clear, which causes them to be structurally inconsistent with the semantic map used to guide the generation process. To solve this problem, we propose a novel generative adversarial network based on a local and global information processing module (LAGGAN) to recover the image's details and structures. The network will further combine the input viewpoint image and the target semantic segmentation map to guide the generation of the target image from another viewpoint. The proposed LAGGAN includes a two-stage generator and a parameter-sharing discriminator. LAGGAN uses a new local and global information processing module (LAG) to generate high-quality images from various views. Moreover, we integrate dilated convolutions into the discriminator to capture the global context, which can enhance the discriminative ability and further adjust the LAG module. Therefore, most semantic information can be preserved, and the details of the target viewpoint images can be translated more sharply. Quantitative and qualitative evaluation on both CVUSA and Dayton datasets attest to the fact that our method, LAGGAN, presents satisfactory perceptual results and is comparable to state-of-the-art methods on the cross-view image translation task.
Exploiting Syntactic and Semantic Information for Textual Similarity Estimation

The textual similarity task, which measures the similarity between two text pieces, has recently received much attention in the natural language processing (NLP) domain. However, due to the vagueness and diversity of language expression, only considering semantic or syntactic features, respectively, may cause the loss of critical textual knowledge. This paper proposes a new type of structure tree for sentence representation, which exploits both syntactic (structural) and semantic information known as the weight vector dependency tree (WVD-tree). WVD-tree comprises structure trees with syntactic information along with word vectors representing semantic information of the sentences. Further, Gaussian attention weight is proposed for better capturing important semantic features of sentences. Meanwhile, we design an enhanced tree kernel to calculate the common parts between two structures for similarity judgment. Finally, WVD-tree is tested on widely used semantic textual similarity tasks. The experimental results prove that WVD-tree can effectively improve the accuracy of sentence similarity judgments.
Design of Video Teaching System Based on Virtual Reality Technology

&lt;p&gt;With the progress of the times and the development of network technology, great changes have taken place in the mode of education and teaching, and the traditional mode of education and teaching has been unable to meet the current teaching situation and requirements. Under this background, many scholars have developed a variety of teaching models adapted to the background of the times, which has achieved good results. In order to realize the reform and innovation of teaching mode, this paper designs a film and television teaching system based on virtual reality technology. In the era of Internet of Things and big data, Internet of Things technology is used as support to realize the transmission and sharing of teaching information in film and television teaching system. In the research, data mining technology is used to collect relevant data of teaching resources and teaching information, and relevant algorithms in data mining are used to realize data processing. Experiment of film and television teaching system in different stages of education system and the application of film and television teaching theory courses, experiment courses for students and education development index are analyzed. According to the end of the experiment, the influence of results show that the film and television teaching system in the use of elementary school, junior high school, high school and university level are 25.32%, 31.44%, 18.46% and 47.76% respectively. The film and television teaching system plays a significant role in students’ experimental course scores. The use of the film and television teaching system has raised the development index of education and teaching in each stage of education from 1.12, 1.33, 1.47 and 1.36 to 2.14, 2.21, 2.36 and 2.44 respectively, indicating that the film and television teaching system has a certain promoting effect on the development of education and teaching.&lt;/p&gt;
A Scientific Marketplace

Cognitive science thrives on the diversity of its (sub-)disciplines, and topiCS is the ideal journal for bringing the diversity to bear. In this welcome address as its incoming Executive Editor, I outline my view of the journal and my vision for how to sustain its inviting and integrative power.
The Impact of Computer Assisted Language Learning (CALL) Use of English Vocabulary Enhancement

This study aims at improving students’ comprehension on English vocabulary using computer and finding out the effectiveness, efficiency and the attractiveness of Computer Assisted Language Learning (CALL) in English learning. It was carried out at SMP Sunan Giri Gresik by using proactive action research method and intervention action model. The participants belonged to 3 different class groups. Thirty of them were from 7th grade (Amanah class) and thirty-two of them from (Hidayah class). The other 30 participants from (Inayah class). The data were collected and analyzed by using mixed method approach. Instruments used for collecting data in this study are questionnaires, documents, observation check list, interview, and achievement tests. The results showed that the treatments give affect positively for students especially treatment on cycle 2. It also can be seen by the students’ involvement actively during learning process. Computer assisted learning especially using software gave students chance to explore their English skill especially the vocabulary through interacting directly with computer by doing exercises given individually in pair or group. From the explanation above it can be concluded that English learning in junior high school can be improved with the help of computer assistance in this matter called Computer-Assisted Language Learning (CALL) mainly to improve English vocabulary.&#x0D; Keywords: Computer-assisted language learning (CALL), English vocabulary, Students’ comprehension
Efficient Robot Skills Learning with Weighted Near-Optimal Experiences Policy Optimization

Autonomous learning of robotic skills seems to be more natural and more practical than engineered skills, analogous to the learning process of human individuals. Policy gradient methods are a type of reinforcement learning technique which have great potential in solving robot skills learning problems. However, policy gradient methods require too many instances of robot online interaction with the environment in order to learn a good policy, which means lower efficiency of the learning process and a higher likelihood of damage to both the robot and the environment. In this paper, we propose a two-phase (imitation phase and practice phase) framework for efficient learning of robot walking skills, in which we pay more attention to the quality of skill learning and sample efficiency at the same time. The training starts with what we call the first stage or the imitation phase of learning, updating the parameters of the policy network in a supervised learning manner. The training set used in the policy network learning is composed of the experienced trajectories output by the iterative linear Gaussian controller. This paper also refers to these trajectories as near-optimal experiences. In the second stage, or the practice phase, the experiences for policy network learning are collected directly from online interactions, and the policy network parameters are updated with model-free reinforcement learning. The experiences from both stages are stored in the weighted replay buffer, and they are arranged in order according to the experience scoring algorithm proposed in this paper. The proposed framework is tested on a biped robot walking task in a MATLAB simulation environment. The results show that the sample efficiency of the proposed framework is much higher than ordinary policy gradient algorithms. The algorithm proposed in this paper achieved the highest cumulative reward, and the robot learned better walking skills autonomously. In addition, the weighted replay buffer method can be made as a general module for other model-free reinforcement learning algorithms. Our framework provides a new way to combine model-based reinforcement learning with model-free reinforcement learning to efficiently update the policy network parameters in the process of robot skills learning.
Using a Program Based on Mobile Computer - Supported Collaborative Learning and Social Media Applications in Developing Student Teachers' EFL Creative Reading Skills and Cultural Awareness

The study aimed to investigate the effectiveness of using a program based on mobile computer - supported collaborative learning (MCSCL) and social media applications in developing EFL creative reading skills and cultural awareness among student teachers at the Faculty of Education. The design of the study was a mixed research methodology. It combined both quantitative and qualitative methods of collecting data. The participants of the study were sixty (N= 60) students enrolled in third -year English section at the Faculty of Education, Benha University, Egypt. They were tested before and after the treatment. They were taught through using a program based on mobile computer -supported collaborative learning (MCSCL) and social media applications. The instruments of the study included an EFL creative reading skills test, an EFL cultural awareness scale and a semi-structured interview. The results of the study revealed a statistically significant difference between the mean scores of the study participants in the pre and post administrations of the EFL creative reading skills test and cultural awareness scale in favor of the post administrations. These results were ascribed to mobile computer - supported collaborative learning (MCSCL) and social media applications.
Bi-Objective Workflow Scheduling on Heterogeneous Computing Systems Using a Memetic Algorithm

Due to the high power bills and the negative environmental impacts, workflow scheduling with energy consciousness has been an emerging need for modern heterogeneous computing systems. A number of approaches have been developed to find suboptimal schedules through heuristics by means of slack reclamation or trade-off functions. In this article, a memetic algorithm for energy-efficient workflow scheduling is proposed for a quality-guaranteed solution with high runtime efficiency. The basic idea is to retain the advantages of population-based, heuristic-based, and local search methods while avoiding their drawbacks. Specifically, the proposed algorithm incorporates an improved non-dominated sorting genetic algorithm (NSGA-II) to explore potential task priorities and allocates tasks to processors by an earliest finish time (EFT)-based heuristic to provide a time-efficient candidate. Then, a local search method integrated with a pruning technique is launched with a low possibility, to exploit the feasible region indicated by the candidate schedule. Experimental results on workflows from both randomly-generated and real-world applications suggest that the proposed algorithm achieves bi-objective optimization, improving makespan, and energy saving by 4.9% and 24.3%, respectively. Meanwhile, it has a low time complexity compared to the similar work HECS.
ADOPTION OF EDUCATIONAL TECHNOLOGY: STUDY ON HIGHER EDUCATION 

This study aims to examine the adoption of innovation technology (e-learning) in universities in Indonesia, by emphasizing individual internal factors that influence adoption.The internal factors analyzed in this study are user motivation, perceived ease of use, trust and personal innovativeness.This research is a type of survey research with the respondents being lecturers at the University.This study used a questionnaire to obtain data, and data were analyzed using structural equation modeling (SEM).The results of data analysis indicate that not all proposed hypotheses are accepted.There is one hypothesis that is not supported, namely the hypothesis of the influence of personal innovativeness on e-learning adoption.The influence of motivation on e-learning adoption, and trust in e-learning adoption is supported.Likewise, the effect of perceive ease of use on trust is also supported.
THE VISUALISATION OF MUHAMMADIYAH MUSEUM USING AUGMENTED AND VIRTUAL REALITY TECHNOLOGY

There is a lot of media for promotion. The brochure is still widely used because of its simple, portable, and easy to carry anywhere. However, in this age of sophistication, the brochure is not effectively used for the millennial generation. Augmented Reality (AR) and Virtual Reality (VR) have been applied to many applications such as education, tourism, advertising, and news reports. With the rapid development of VR and AR technology, there are higher continuously requirements for enhancing brochure media effectiveness. AR and VR provide a potential solution for interaction between person and brochure as new emerging information technology. In this research, AR and VR are used to better educate tourists and visitors about the museum they choose to visit. Muhammadiyah Museum and its historical collection used as an example of applying AR and VR to the brochure as a promoting media. The Multimedia Development Life Cycle (MDLC) method applied to develop AR and VR. AR and VR system was tested by 30 under graduation students with 74.92% of acceptance. This research shows the AR and VR brochure is very feasible successfully sent information about the various kinds of historical collections in museum Muhammadiyah and very helpful as promoting media.
Locally Adaptive Thresholding for Single-Shot Structured Light Patterns

Image thresholding is a challenging task due to its sensitivity to environmental variations and degradation in the quality of the captured image. Although many image thresholding methods have been introduced, most of them require the fine tuning of a thresholding parameter that is not suitable for single-shot structured light (SSSL) based projector-camera applications. In this paper, we introduce a locally adaptive thresholding method with automatic parameter selection based on the local statistics of the distinct image partitions. For assessing the proposed scheme, we introduce an evaluation that relies on mapping SSSL patterns between the camera and projector spaces. Experimental results demonstrate the effectiveness of the proposed technique by maintaining the thresholding accuracy of the baseline method, without the need to fine tune the obtained thresholding parameter or any noticeable change in the qualitative results.
Development of Intelligent Information System for Digital Cultural Contents

A significant amount of digital cultural contents is shared online, but learners do not know where subject matter content is or how to find it. Therefore, there is a need for a service to improve educational quality by effectively providing relevant information in response to searches for content that is useful to learners. This study developed and tested the usability and utility of an intelligent information system that effectively searches and visualizes digital cultural contents. The system collects data on digital cultural contents, automatically classifies them, and creates content triple data to automatically display the results with a 3D timeline, knowledge network map, and keyword relation network map through content search, triple search, and keyword search. We also conducted a survey and in-depth interviews to verify users’ satisfaction with respect to the use and utility of the system. For the experiment, we developed survey questions to measure user satisfaction and conducted in-depth interviews regarding the system’s utility with a total of 65 subjects. The results show that the response for satisfaction with regard to the use and utility was generally “satisfied”. In addition, the system stability was evaluated as “high”.
The history and recent advances of Natural Language Interfaces for Databases Querying

Databases have been always the most important topic in the study of information systems, and an indispensable tool in all information management systems. However, the extraction of information stored in these databases is generally carried out using queries expressed in a computer language, such as SQL (Structured Query Language). This generally has the effect of limiting the number of potential users, in particular non-expert database users who must know the database structure to write such requests. One solution to this problem is to use Natural Language Interface (NLI), to communicate with the database, which is the easiest way to get information. So, the appearance of Natural Language Interfaces for Databases (NLIDB) is becoming a real need and an ambitious goal to translate the user’s query given in Natural Language (NL) into the corresponding one in Database Query Language (DBQL). This article provides an overview of the state of the art of Natural Language Interfaces as well as their architecture. Also, it summarizes the main recent advances on the task of Natural Language Interfaces for databases.
Sistem Informasi Evaluasi Perkuliahan dengan Sentimen Analisis Menggunakan Naïve Bayes dan Smoothing Laplace

A good lecture is certainly a goal so that students achieve maximum learning outcomes. In order for good lecture quality, lecture evaluation needs to be done,beside lecturer professional competency training. In order to improve the quality of lectures, Departement Informatics of Madura University (UNIRA) evaluates lecturers' performance in each semester. Form of evaluation is a questionnaire that filled out by students.Results of the questionnaire, then it is analyzed to find out whether the comments are positive, negative, or neutral. The method that can be used to solve the problem of sentiment classification analysis is Naïve Bayes that combined with text processing techniques.The data comments that collected are 342. After grouping the comments by subject, there were 31 comments for subject Human and Computer Interaction (HCI). In this data comments then performed data cleaning, data transformation, text processing and labeling. Then classifying comments using Naïve Bayes with Smoothing Laplace. Results of accuration obtained an accuracy to 80%. The results of implementation Naïve Bayes algorithm with Smoothing Laplace, it can be seen the sentiment analysis of the subjects that lectures taught.
Blockchain in construction industry: challenges and opportunities.

Construction Industry is currently evolving around the world. On the other hand, despite the technological advancement across most sectors, construction industry remains amongst laggards in digitalization. Currently, engineering business is facing technological disruption ahead of the fourth industrial revolution; one of which is the blockchain technology! Blockchain is new to construction industry, its challenges and opportunities are yet to be fully realized. This study explores the challenges and potential opportunities of blockchain in the construction industry through extensive review of literature within the blockchain domain vis-a-vis construction business domain. The study presents challenges under three categories (technical, regulation and social), and the potential opportunities in to improving efficiency and reducing conflict through transparency and trust. That will ultimately create value for money in the procurement of construction works. Recommendations are made based on the study finding to advance the research on blockchain applications in to the construction industry.
Dutch Named Entity Recognition and De-Identification Methods for the Human Resource Domain

The human resource (HR) domain contains various types of privacy-sensitive textual data, such as e-mail correspondence and performance appraisal. Doing research on these documents brings several challenges, one of them anonymisation. In this paper, we evaluate the current Dutch text de-identification methods for the HR domain in four steps. First, by updating one of these methods with the latest named entity recognition (NER) models. The result is that the NER model based on the CoNLL 2002 corpus in combination with the BERTje transformer give the best combination for suppressing persons (recall 0.94) and locations (recall 0.82). For suppressing gender, DEDUCE is performing best (recall 0.53). Second NER evaluation is based on both strict de-identification of entities (a person must be suppressed as a person) and third evaluation on a loose sense of de-identification (no matter what how a person is suppressed, as long it is suppressed). In the fourth and last step a new kind of NER dataset is tested for recognising job titles in tezts.
SWOT-analysis as a strategic management tool of the quality training of the future educational institution head

The article presents the results of the empirical analysis of the system of training future heads of educational institutions under the master's educational program, which showed that quality management of future leaders depends on setting standards, updating educational programs, highly qualified staff, quality organization of the educational process and effective management.The study empirically confirms and theoretically proves that it is very important for a higher education institution to really see the levers that it can manage -internal resources, as well as to understand the factors that are outside the sphere of influence -external threats.
Investigating the determinants and growth of financial technology depth of penetration among the heterogeneous Africa economies

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PEDAGOGICAL CONDITIONS FOR IMPLEMENTING EDUCATIONAL ENGINEERING IN HIGHER EDUCATION

УДК 378.14 ПЕДАГОГИЧЕСКИЕ УСЛОВИЯ РЕАЛИЗАЦИИ ОБРАЗОВАТЕЛЬНОГО ИНЖИНИРИНГА В ВЫСШЕЙ ШКОЛЕ Зиннурова А.Ф. 1 , Габдулхаков В.Ф. 2 behavior of people in their chosen profession), and value (formation of professional values and beliefs).Integration presupposed the implementation of interdisciplinary links between physical culture and musicalaesthetic, cognitive-communicative culture.Interactivity was designed to increase interest in the chosen profession.Testing the effectiveness of such engineering revealed an increase in interest in physical education classes, cognitive and communicative spheres of communication.