Reviewerly/exHarmony huggingface dataset:
Knowledge Graphs Effectiveness in Neural Machine Translation Improvement

Neural Machine Translation (NMT) systems require a massive amount of Maintaining semantic relations between words during the translation process yields more accurate target-language output from Neural Machine Translation (NMT). Although difficult to achieve from training data alone, it is possible to leverage Knowledge Graphs (KGs) to retain source-language semantic relations in the corresponding target-language translation. The core idea is to use KG entity relations as embedding constraints to improve the mapping from source to target. This paper describes two embedding constraints, both of which employ Entity Linking (EL)---assigning a unique identity to entities---to associate words in training sentences with those in the KG: (1) a monolingual embedding constraint that supports an enhanced semantic representation of the source words through access to relations between entities in a KG; and (2) a bilingual embedding constraint that forces entity relations in the source-language to be carried over to the corresponding entities in the target-language translation. The method is evaluated for English-Spanish translation exploiting Freebase as a source of knowledge. Our experimental results show that exploiting KG information not only decreases the number of unknown words in the translation but also improves translation quality.
E-Voting system using Blockchain technology

Nowadays, normal voting using EVM(Electronic voting machine) which stores the votes of each voter in a centralized database.And after researching many different evoting applications, most of the application used centralized data storage as the database.As, these centralized databases stores the complete data at a single location and is easy hackable and can be tampered with.Hence, due to this the data can be inconsistent while voting count and will not provide us with the correct result.Hence, using blockchain technology, we create a decentralized application where the tampering of data becomes almost impossible as Blockchain uses the decentralized algorithm for the data storage where the data is stored at a single location.The main objective of E-voting system using blockchain is to create a e-voting system underneath using a blockchain technology.This system is just like a normal voting system, of which same process is conducted on e-voting which used to be conducted on the normal paper-based voting with the use of mobile, web browser for the voting purpose by the voters.Therefore, this paper will give a review of blockchain technology and how this technology will be used in E-voting system.
The Effect of Rational Based Beliefs and Awareness on Employee Compliance with Information Security Procedures: A Case Study of a Financial Corporation in Israel

Aim/Purpose: This paper examines the behavior of financial firm employees with regard to information security procedures instituted within their organization. Furthermore, the effect of information security awareness and its importance within a firm is explored. Background: The study focuses on employees’ attitude toward compliance with information security policies (ISP), combined with various norms and personal abilities. Methodology: A self-reported questionnaire was distributed among 202 employees of a large financial Corporation Contribution: As far as we know, this is the first paper to thoroughly explore employees’ awareness of information system procedures, among financial organizations in Israel, and also the first to develop operative recommendations for these organizations aimed at increasing ISP compliance behavior. The main contribution of this study is that it investigates compliance with information security practices among employees of a defined financial corporation operating under rigid regulatory governance, confidentiality and privacy of data, and stringent requirements for compliance with information security procedures. Findings: Our results indicate that employees’ attitudes, normative beliefs and personal capabilities to comply with firm’s ISP, have positive effects on the firm’s ISP compliance. Also, employees’ general awareness of IS, as well as awareness to ISP within the firm, positively affect employees’ ISP compliance. Recommendations for Practitioners: This study can help information security managers identify the motivating factors for employee behavior to maintain information security procedures, properly channel information security resources, and manage appropriate information security behavior. Recommendation for Researchers: Researchers can see that corporate rewards and sanctions have significant effects on employee security behavior, but other motivational factors also reinforce the ISP’s compliance behavior. Distinguishing between types of corporations and organizations is essential to understanding employee compliance with information security procedures. Impact on Society: This study offers another level of understanding of employee behavior with regard to information security in organizations and comprises a significant contribution to the growing knowledge in this area. The research results form an important basis for IS policymakers, culture designers, managers, and those directly responsible for IS in the organization. Future Research: Future work should sample employees from another type of corporation from other fields and should apply qualitative analysis to explore other aspects of behavioral patterns related to the subject matter.
Segment Medical Image Using U-Net Combining Recurrent Residuals and Attention

Medical image segmentation is the key to decide the issue of medical images in clinical practice that can provide a reliable basis. The development of medical image segmentation technology not only affects the development of other related technologies in medical image processing, such as visualization 3D reconstruction, but in the analysis of biomedical images also occupies an extremely important position. With the application of deep learning algorithms in medical image segmentation, medical image segmentation technology has made significant progress. In this paper, we discuss the segmentation method of 2D medical images about U-net variant network. Use the U-net combing recurrent residual model and attention model to segmented the image can get better result.
A Systematic Literature Review: User Experience (UX) Elements in Digital Application for Virtual Museum

This paper presented a review of user experience (UX) elements in digital application and proposed a conceptual framework of UX for virtual museum application.The aims of this paper are to identify the elements of UX and propose a conceptual framework according to the UX elements that were identified.The research was conducted by using systematic literature review (SLR) approach based on Scopus and Web of Science databases, with specific inclusion and exclusion criteria.The UXelements that were identified were used to formulate UX model for virtual museum application.This study had identified effectiveness, efficiency, satisfaction and attractiveness as the most reliable UXelements for conceptual framework based on the findings in the SLR analysis.In addition, the conceptual framework contained three groups of constructs to improve the performance quality of virtual museum application, namely virtual museum features, UX factors and UX response.The proposed conceptual model can be a guideline for virtual museum application development.
Enhancement Processing Time and Accuracy Training via Significant Parameters in the Batch BP Algorithm

The batch back prorogation algorithm is anew style for weight updating.The drawback of the BBP algorithm is its slow learning rate and easy convergence to the local minimum.The learning rate and momentum factor are the are the most significant parameter for increasing the efficiency of the BBP algorithm.We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm.We used several data set for testing the effects of the dynamic learning rate and dynamic momentum factor that we created in this paper.All the experiments for both algorithms were performed on Matlab 2016 a.The stop training was determined ten power -5.The average accuracy training is 0.9909 and average processing time improved of dynamic algorithm is 430 times faster than the BBP algorithm.From the experimental results, the dynamic algorithm provides superior performance in terms of faster training with highest accuracy training compared to the manual algorithm.The dynamic parameters which created in this paper helped the algorithm to escape the local minimum and eliminate training saturation, thereby reducing training time and the number of epochs.The dynamic algorithm was achieving a superior level of performance compared with existing works (latest studies).
What is the motivation of Norwegian and New Zealand teacher educators for using digital technology when teaching?

There is a gap between policies regarding the use of digital technology in higher education in Norway and what is practiced. Therefore, we have conducted a comparative study of teacher education in Norway and New Zealand. Using Herzberg’s two-factor theory, this study investigates what motivates teacher educators to use digital technology when teaching. Although the professional application of digital tools is more frequent in New Zealand than in Norway, the ability to use digital technology seems to be greater in Norway than in New Zealand. Based on Meier’s formula (performance = abilities × motivation), teacher educators’ performance is considered a result of their abilities and motivation. This indicates that motivation is a key element in understanding why the use of digital tools is more frequent amongst New Zealand teacher educators. When explaining their motivation for using digital technology, Norwegian teacher educators mentioned nine motivation factors and nine hygiene factors. The hygiene factors relate to the mandatory policy and the work conditions when teaching online. New Zealand teacher educators explained their motivation with 14 motivational factors and only four hygiene factors. New Zealand teacher educators seemed to be more motivated to work with digital technology than their Norwegian counterparts. This lack of motivation is one reason that could explain why the application of digital tools seemed lower in Norway than in New Zealand. Norwegian teacher educators explained that the main reason they use digital tools is the top-down implementation of government policy. Therefore, a fundamental challenge in the use of digital technology in Norway is the policy related to its implementation; as a part of the job environment, policy creates job dissatisfaction. Teacher educators from both countries highlighted achievement and policy as their main reasons for using digital technology, but Norwegian teacher educators were especially critical of their own country’s policy.
An Outlier Detection Algorithm for Electric Power Data Based on DBSCAN and LOF

With the planning of smart grids, how to use electric power data will become the key to development. In order to ensure the accuracy of electric power data and to mine event information behind the data, this paper proposes a new outlier detection method, which combines DBSCAN and LOF algorithm, KDBLOF. KDBLOF introduces the idea of k-Nearest Neighbor into DBSCAN and replaces Eps and MinPts by input K, which can solve the difficulty of the original DBSCAN in parameter determination. Compared to the original LOF algorithm, KDBLOF no longer needs to calculate the LOF value for each object, but only the object with lower density in a cluster or the object located at the cluster boundary. In the simulation of this paper, only the LOF value of the objects of about 20% of the original dataset needs to be calculated, which effectively reduces the amount of calculation. In this paper, the NSL-KDD dataset is used for simulation. The results show that the proposed method has better outlier detection effect than DBSCAN and LOF.
GUI3DXBot: An Interactive Software Tool for a Tour-Guide Mobile Robot

Nowadays, mobile robots begin to appear in public places. To do these tasks properly, mobile robots must interact with humans. This paper presents the development of GUI3DXBot, a software tool for a tour-guide mobile robot. The paper focuses on the development of different software modules needed to guide users in an office building. In this context, GUI3DXBot is a server-client application, where the server side runs into the robot, and the client side runs into a 10-inch Android tablet. The GUI3DXBot server side is in charge of performing the perception, localization-mapping, and path planning tasks. The GUI3DXBot client side implements the human-robot interface that allows users requesting-canceling a tour-guide service, showing robot localization in the map, interacting with users, and tele-operating the robot in case of emergency. The contributions of this paper are twofold: it proposes a software modules design to guide users in an office building, and the whole robot system was well integrated and fully tested. GUI3DXBot were tested using software integration and field tests. The field tests were performed over a two-week period, and a survey to users was conducted. The survey results show that users think GUI3DXBot is friendly and intuitive, the goal selection was very easy, the interactive messages were very easy to understand, 90% of users found useful the robot icon on the map, users found useful drawing the path on the map, 90% of users found useful the local-global map view, and the guidance experience was very satisfactory (70%) and satisfactory (30%).
New Personal Tax Collection Management System Based on Artificial Intelligence and Its Application in the Middle Class

Abstract Personal income tax is a kind of tax that is generally collected by all countries in the world, and it is also one of the important sources of fiscal revenue in China. With the increasing diversity of people’s income, there is a large tax gap under the same income. The purpose of this paper is to study the new personal tax collection management system based on artificial intelligence and its application in the middle class. This paper first introduces the meaning of personal income tax and the new content of the new personal income tax law, and studies the application of the new personal income tax collection system in the middle class. Then this paper studies the algorithm of SVM. Based on this theory, this paper designs and implements a new personal tax collection management system. The system is mainly divided into three functional modules: data source, risk identification, response and query statistics. In this paper, the performance of the system is tested, and the experimental results show that the system designed in this paper can meet the actual needs. When the number of concurrent transactions reaches 200, the average response time of the transaction does not exceed 3 seconds.
Augmented Physics’ Lab: Magnetic Field Use Virtual Learning Media for 21st Century Students

The 21 st century has brought a paradigm change that shifts conventional learning towards technology-based learning. PISA data shows that Indonesia only achieved a score of 382, while TIMSS stated that the percentage of correct answers to the problem of understanding was always higher than the matter of application. This indicates that HOTS students in Indonesia have not yet developed optimally. This investigation intends to create worksheets for students implemented by augmented reality on magnetic field substance. This investigation was development research which used the Dick and Carey method. The product can display 3-Dimensional simulations. According to an investigation, the validation result of the students’ worksheets already met the criteria very well in terms of material with a percentage of 95%, in terms of media with a percentage of 86.8% and terms of learning with a percentage of 81%, and product trials by teachers with a percentage of 98%. Meanwhile, trials of students obtained an N-gain result of 0.64 which interpreted an increase in students' high-level thinking skills in the medium level. Therefore, it could be assumed that augmented physics' lab has been suitable for students' higher-order thinking skills. Keywords: Augmented Reality, HOTS, Virtual Learning DOI: http://dx.doi.org/10.23960/jpf.v8.n1.202007
STAKEHOLDERS MANAGEMENT IN A UNIVERSITY: ANALYSIS OF THEIR IMPORTANCE WITH AHP

At present, problems appear in every decision taken by people or companies.It is because each part has its own interests, normally different than each other, and they have to take care of them over the rest to achieve a high level of success in terms of following their objective.Literature about this subject is very extensive and varied.But it seems that research is mostly focussed on social field, talking about social objectives, mission and values of companies and institutions.In case of universities, the main concern is the change of directive from creating knowledge to keeping this knowledge and earn prestige and economic compensation.This paper shows the management of a university focused on the relation with its stakeholders and how can they affect or influence in decisions, and moreover, it will be giving a critic point of view about the priorities between each one.Conclusions will be supported by an Analytic Hierarchy Process and contrasted with some experts in the field, with the objective of giving a vision of how can traditional management system of universities improve in the future and focus on its main mission as social creators of knowledge.
Use of color information for structured-light 3D shape measurement of objects with shiny surfaces

Objects with shiny surfaces cannot be directly measured using the conventional structured-light method. To cope with this problem, in this paper, we propose a novel method for removing the saturated components in an image. First, the specular pixels in the image are identified using a highlight extraction algorithm. Then, based on the reflection component separation (RCS) theory, the diffuse and specular components of these specular pixels are separated. For objects with shiny surfaces, use of the RCS approach destroys the color information of highlighted pixels with a large specular reflection component. As such, finally, the color information of the highlighted pixels is recovered using an image repair process. Experimental results indicate that 95% of the highlights in the images were eliminated. The highlight caused by the strong reflecting surface can be well suppressed. This proposed method effectively overcomes the interference of reflected light and provides a feasible solution to the problems associated with the structured-light measurement of objects with smooth surfaces.
WHATSPEAK: Audiovisual Digital Assessment in Enhancing Confident and Independent Speaking Skills

Fluent speaking skills in English are considered major requirements in the growth of universal civilization as the fluency of spoken words allow a person to be well understood in the designated area.Learners are expected to forward ideas confidently and independently.However, they faced challenges in managing simple English communication among their circle.Therefore, the implementation of WhatsApp based audiovisual tasks were infused action research to enhance learners' speaking skills.The research was conducted among learners aged eight in a rural primary school in the district of Cameron Highlands, Pahang, Malaysia.Results were collected from pre-test and post-test, observation and survey.Data revealed that learners were involved actively in collaborative speaking sessions by exchanging ideas confidently and independently.Significantly, their spoken Performance Level improved as they began to socialize and prompt proper language usage in the interactions through the aid of pictures, videos and audios.Researchers had suggested the incorporation of genuine learning and assessment of speaking skills via WhatsApp based audiovisual materials as an effective effort in eventually producing confident and independent English speakers.
MENGEMBANGKAN KEMAMPUAN KOGNITIF DALAM MENGENAL KONSEP BILANGAN 1 – 10 MELALUI MEDIA TELUR ANGKA PADA ANAK USIA 3 – 4 TAHUN

Cognitive ability to recognize the concept of numbers is very important to be introduced early on, so children are accustomed to easily solving simple problems related to numbers. The problem found by researchers is that children have difficulty when asked to numerate objects, numerically order numbers, and connect images of objects with numbers according to the amount. In an effort to address this problem, the educator introduces new media, namely the number egg media made from used materials and designed as attractive as possible so that students were motivated to learn. This study aims to determine whether there is cognitive development in recognizing the concept of numbers 1-10 in children aged 3-4 years in the Playgroup Al-hikmah Kweden Karangrejo Ngasem District Kediri Regency between before and after the action. The research method used is classroom action research conducted in three cycles. This research involved subjects of 3-4 years old children totaling 18 students. The analysis technique in this research is quantitative descriptive technique by comparing learning completeness between the time before and after the action. The results obtained in the first cycle of 50%, and in the second cycle of 63.8%, while in the third cycle of 81.9%. From the results of the study it can be concluded that through the egg media numbers can develop cognitive abilities in recognizing the concept of numbers 1-10 in children aged 3-4 years.
Non-revisiting Coverage Task with Minimal Discontinuities for Non-redundant Manipulators

A theoretically complete solution to the optimal Non-revisiting Coverage Path Planning (NCPP) problem of any arbitrarily-shaped object with a non-redundant manipulator is proposed in this work.Given topological graphs of surface cells corresponding to feasible and continuous manipulator configurations, the scheme is aimed at ensuring optimality with respect to the number of surface discontinuities, and extends the existing provable solution attained for simply-connected configuration cell topologies to any arbitrary shape.This is typically classified through their genus, or the number of "holes" which appear increasingly as configurations are further constrained with the introduction of additional metrics for the task at hand, e.g.manipulability thresholds, clearance from obstacles, end-effector orientations, tooling force/torque magnitudes, etc.The novel contribution of this paper is to show that no matter what the resulting topological shapes from such quality cell constraints may be, the graph is finitely solvable, and a multistage iterative solver is designed to find all such optimal solutions.
Implementation of Fuzzy Logic Technique in a Decision Support Tool: Basis for Choosing Appropriate Career Path

The authors implemented a fuzzy logic technique to develop a mobile based decision support tool called Generalized STEM-College Aptitude Test (GSTEM-CAT).It is an application that can recommend to the college applicant what appropriate university program can be enrolled based on ones' personality type and knowledge strength.Moreover, the students may enjoy GSTEM-CAT application because they see graphical objects associated to personality type test.The developed tool was evaluated by the respondents and based on the evaluation results, the software satisfied its implied functions and is functional, usable and reliable.Hence, it can be already used by the students and school administrators to assess and recommend set of college program that the student may take up, therefore providing opportunities for successful program completion.