Reviewerly/exHarmony huggingface dataset:
Facial Expression Recognition Based on K-SVD Dictionary Learning and OMP Compression Perceptual Reconstruction

Because of the non-contact and non-compulsory characteristics, emotional recognition has become a mainstream biometric technology, which is widely used in computer vision. As one of the branches of sentiment analysis, facial expression recognition is often affected by the attitude of the collector and the illumination of the environment. In the process of facial image collection, with the changing factors such as lighting and camera angle, the construction of a facial dictionary using samples will be affected to a certain extent. So that the test samples can not be linearly reconstructed by using the dictionary. This will lead to a decrease in the accuracy of recognition. To reduce the interference caused by misaligned faces and uneven gray distribution, a facial expression recognition method based on K-means Singular Value Decomposition (K-SVD) dictionary learning and Orthogonal Matching Pursuit (OMP) compressed perceptual reconstruction is proposed in this paper. Multi-task Convolutional Neural Networks (MTCNN) is used for face alignment and then use histogram equalization to preprocess. Finally, K-nearest Neighbor (K-NN) algorithm is used for facial expression recognition. After preprocessing, the new algorithm eliminates part of the nonlinear noise of the samples, and the recognition accuracy is improved from 20.8% to 67.8%, which improves the performance of facial expression recognition effectively.
A Study on the Factors of Changes in Unification Education Policy: Focusing on New Security-oriented Unification Education

This paper used Kingdon's multiple streams framework to analyze why the unification of the education policy was changed in 2008. As analytical results, in the problem steams, unification education reflects the reality as it is and strengthens security due to the opposition to the proliferation of weapons of mass destruction, domestic politicization of North Korea policy, discussion of North Korea's sudden change, North Korea's nuclear development, and the Cheonan and Yeonpyeong Island incidents. In the political streams, President Lee Myung-bak took office, who had the idea that overall change was necessary in the policy of appeasement toward North Korea. Support for North Korea policy by the Koreans, the spread of negative awareness about North Korea and unification, the spread of public opinion to reinforce the weakened sense of security, created conditions for changes in unification education. In the policy streams, Proposals that the existing education for unification needed to be changed suggested. These three streams were able to combine with the creation of policy opportunities such as 'change of government to conservatives' and 'the Cheonan/Yeonpyeong Island incident', leading to policy changes.&#x0D;
An Efficient Approach for Converting 2D Medical Images Into Non Immersive VR Model

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Implementation of Generative Model Based Solver for Mathematical Word Problem With Linear Equations

Solving math word problems automatically with a computer is an interesting topic. Instead of statistical methods and semantic parsing methods, recently, deep learning model based methods are used to solve MWPs. We experimented with different deep learning generative model that directly translates a math word problem into a linear equation. In this paper, four MWP solvers using the Sequence-to-Sequence (Seq2Seq) model with a attention mechanism were implemented, i.e., Seq2Seq, BiLSTM Seq2Seq, convolutional Seq2Seq, and transformer models. Then, performance analysis for the 4 MWP solvers has performed on MaWPS (English) and Math23K (Chinese) MWP datasets. Experiment shows that both the Seq2Seq model and the transformer model showed similar performance in translating into simple linear equations, but the transformer model showed the best performance in translating into more complex linear equations.
Explicit Study on Design and Development of Content-based Image Retrieval in Medical Imaging

Digital Image Databases and documentation provide lot of research areas. Significant among them is, the Content Based Image Retrieval (CBIR) research area for manipulating large amount of image databases and archives. The development in the field of medical imaging system has lead industries to conceptualize a complete automated system for the medical procedures, diagnosis, treatment and prediction. There is a continuous research in the area of CBIR systems typically for medical images, which provides a successive algorithm development for achieving generalized methodologies, which could be widely used. The achievement of such system mainly depends upon the strength, accuracy and speed of the retrieval systems. Content Based Image Retrieval (CBIR) system is valuable in medical systems as it provides retrieval of the images from the large dataset based on similarities. The aim of this paper is to discuss the various techniques, the assumptions and its scope suggested by various researchers and setup a further roadmap of the research in the field of CBIR system for medical image.
FinTech Econometrics: Privacy Preservation and the Wisdom of the Crowd

After a brief overview of FinTech, this survey paper focuses on two timely topics in econometrics related to privacy and transparency issues: (1) Econometrics for sensitive financial data with privacy preservation in the era of big data. (2) The wisdom of the crowd and prediction markets, in the presence of new information from anonymous individual level trading data.
Pelatihan Komputer Bagi Guru SMP Taman Rama Jimbaran

This social engagement is done in order to improve understanding and performance of the teachers of Taman Rama Jimbaran Junior High School (TRJ-JHS) where there is no teachers that have the background study in Informatics and Technology. There are only 5 classes n TRJ-JHS. This small numbers of classes has caused less number of teaching periods. The solution to solve this problem is by assigning the teachers to teach other subjects that were not their background of study before. Based on the regulation of Educational Ministry Number 15 Year 2018, verse 4 poin 3 stated that “The implementation of learning process is 24 period per week as the minimum total and 40 periods per week as the maximum total. This lack of knowledge has made teachers found difficulties especially regarding the topics about Algorithm and programs. Purposes of study are to improve the level of knowledge and performances also it will enable the teachers to teach the students appropriately based on the competency gained. Method used was online conference through Ms Team. Main findings of this social engagement are: the eagerness of the Principal and teachers of TRJ-JHS to improve level of knowledge and performances by giving feedback through practices. There were 2 times evaluations after 3rd and 4th meetings by reconsidering difficulties on the process. The teachers are able to understand the topics especially on Algorithm and the skills in making and editing the learning videos. The results of pre-test and post-test has shown the improvement where at the pre-test out of 20 participants, 16 failed while 4 passed the passing score 76 and the results of post-test was all participants can get the scored 76 and above. Finally, this improvement is expected to be applied properly and appropriately for students especially for the subject Informatics and technology.
The Current Status of Foreign Literature Education in Elementary, Middle, and High School Language Education and Direction of Development into International Literature-Culture and Communication Education

The study analyzed the historical aspects of foreign literature education in the Korean language curriculum and the current status of foreign literature education in Korean language textbooks, and presented the direction of foreign literature education into international literature-culture and communication education. As the Korean language curriculum is gradually expanding the scope of foreign literature, educational conditions in terms of international communication are in place. However, looking at the aspects of the Korean language textbook, which was realized in reality, there were parts where the Korean language textbooks, and curriculum were at odds, and elements of foreign literature contained in Korean language textbooks were biased. Therefore, it was proposed to expand the view of foreign literary education philosophy to the international stage and pursue hierarchization, balancing, and diversification of foreign literary education contents within the school level and school level.
Can intermediary and disintermediary be compatible in coordination management: affordance, fusion and actualization of blockchain and conventional systems

Purpose This study investigates into how organizations enable the compatibility between intermediary role of conventional systems with disintermediary potentials of blockchain toward the coordination of multiple actors in operations management. Design/methodology/approach The data were collected from 31 interviewees of the case organizations. We conduct an in-depth case study of successful BC implementation in operations management, by using affordance-actualization (A-A) theory as the theoretical lens. Findings This study identifies the incompatibility between the affordances of conventional systems and blockchain in coordination/operations management and offers a process model in which a fusion phase enables the affordances to be compatible and then to be actualized. The fusion phase extends A-A theory by transposing and connecting in the context of operations management. The result also shows that blockchain technology has decentralized potentials to address the issues caused by centralized organizations or information systems, while not to replace the intermediary roles of centralized organizations or information systems. Originality/value This study makes important theoretical contributions to the literature on blockchain used in operations management, the roles of blockchain enablement and affordance-actualization theory. The findings can also help IT practitioners to implement BC-based applications effectively.
The Tip of the Buyer: Extracting Product Tips from Reviews

Product reviews play a key role in e-commerce platforms. Studies show that many users read product reviews before a purchase and trust them to the same extent as personal recommendations. However, in many cases, the number of reviews per product is large and extracting useful information becomes a challenging task. Several websites have recently added an option to post tips —short, concise, practical, and self-contained pieces of advice about the products. These tips are complementary to the reviews and usually add a new non-trivial insight about the product, beyond its title, attributes, and description. Yet, most if not all major e-commerce platforms lack the notion of a tip as a first-class citizen and customers typically express their advice through other means, such as reviews. In this work, we propose an extractive method for tip generation from product reviews. We focus on five popular e-commerce domains whose reviews tend to contain useful non-trivial tips that are beneficial for potential customers. We formally define the task of tip extraction in e-commerce by providing the list of tip types, tip timing (before and/or after the purchase), and connection to the surrounding context sentences. To extract the tips, we propose a supervised approach and leverage a publicly available dataset, annotated by human editors, containing 14,000 product reviews. To demonstrate the potential of our approach, we compare different tip generation methods and evaluate them both manually and over the labeled set. Our approach demonstrates particularly high performance for popular products in the Baby, Home Improvement, and Sports &amp; Outdoors domains, with precision of over 95% for the top 3 tips per product. In addition, we evaluate the performance of our methods on previously unseen domains. Finally, we discuss the practical usage of our approach in real-world applications. Concretely, we explain how tips generated from user reviews can be integrated in various use cases within e-commerce platforms and benefit both buyers and sellers.
Exploring a mobile-based language learning intervention to improve English language acquisition and acculturation among migrants in Australia

Abstract This exploratory Australian study tested a novel mobile-based language learning service intervention (via WhatsApp) called ‘Chatloop’ with 31 newly arrived migrants. This intervention was offered in tandem with the traditional Adult Migrant English Program (AMEP) classroom curriculum. A mixed methods approach was employed to trial the intervention of Chatloop with AMEP students at two Queensland TAFE campuses. Quantitative data were gathered to measure changes in participants’ English proficiency, and qualitative interviews gathered narratives about the experience of using Chatloop. Chatloop intervention group participants perceived it to be an interactive learning service that significantly improved their reading and writing skills, acculturation, and enhanced social connections. Being able to access Chatloop on their mobile device 24/7 was deemed to be an added advantage as compared to traditional classroom learning; it provided an opportunity to learn more about Australian culture and communication patterns, at their convenience. These findings suggest that such mobile interventions can be a valuable means of enhancing migrant’s English language learning and warrants future research.
The Shariah Framework for Smart Contracts, an Original Analytical Study

A smart contract is a contract that brings together two or more parties that can be programmed electronically and then execute its terms automatically, once certain events or specific conditions are met and it depends on blockchain technology. This paper intends to elucidate this contract at the practical level, and then explains the legal frameworks from Islamic Perspective, by mentioning examples of legal contracts named in Islamic jurisprudence and shows similarities along with an analysis of the jurisprudential problems. The research concluded that there are jurisprudential contracts that are consistent with smart contracts, even in some parts through which the framework of the contract can be constructed from the jurisprudential point of view. The research used the descriptive and analytical method. The researchers concluded that a smart contract can be used in Islamic business framework as long as it meets the requisite legal elements as required under the Shariah principles.
Fast bilateral complementary network for deep learning compressed sensing image reconstruction

Great progress has been made in deep learning image reconstruction, but there are still problems that need to be improved, such as the extraction of image texture details and the improvement of the overall contour quality of the image, and how to reduce the transmission cost is also the focus of research. This paper proposes a fast bilateral network suitable for both grayscale and color image reconstruction. In the compression network, bilinear interpolation, fully connected layer and convolutional neural network are selected for image compression. The reconstruction network is divided into two parts: the texture path and contour path, the former reconstructs the remaining texture details of the image, and the latter performs deep contour reconstruction. The bilateral complementary residual connection method transfers the texture information to the contour path and improves the contour quality, and the improvement of the contour quality can improve the learning of texture details. Through a large number of data tests, it shows that the network in this paper has achieved comparable or better results in terms of image reconstruction quality, time-consuming and robustness against noise. It solves the problem of memory consumption for storing a large number of images, and also provides convenience for shortening space and time during image transmission.
Advocacy for the Development of Teacher Leadership in the Context of ECC Reforms in China

China's development is inseparable from the reform of education, so ECE is very important in the development of Chinese society. Based on this reason, this paper introduces the three reform waves of communist Chinese society under the influence of western culture. Because the professional level of kindergarten teachers does not match the concepts and requirements of the three preschool curriculum reforms in Chinese society, this paper analyzes the solutions based on this problem and holds that the leadership of kindergarten teachers should be vigorously developed.
Multi‐objective memetic approach for the optimal web services composition

Abstract Service composition is the process of combining a set of elementary or atomic services. The aim is to produce a new composite service to satisfy the user's request that cannot be satisfied by the atomic services. Combining multiple services is a complex problem that has been the subject of several research studies. The meta‐heuristic approaches are good techniques that have been used to solve several complex problems in various domains. These techniques are able to discover promising search regions and locate good quality solutions in reasonable time without exploring the whole solution space. In this paper, we deal with the problem of optimal web service composition by using meta‐heuristic approaches. Given a set of services and a set of tasks to be completed, the problem is to find the best set of services composition to complete all tasks where each service must be assigned to a given task. This problem can be modelled as a combinatorial optimization problem with a set of objective functions that need to be optimized. We search for a composite service that allows us to execute the considered tasks and offers the best quality of services (QoS). More precisely, we search for an execution plan that indicates for each task the assigned service. First, we propose a multi‐objective local search based meta‐heuristic (MO‐LS) and a multi‐objective genetic algorithm (MO‐GA) to handle our problem. Then we propose a multi‐objective memetic algorithm (MO‐MA) that combines the two methods LS and GA. The role of GA is to detect promising regions to be explored. The role of LS is to exploit efficiently the potential regions created by GA. Four objective functions are used to compute the Pareto optimal set of solutions. The main objective is to minimize cost and time and to maximize availability and reputation and produce a good composite service. The three proposed approaches namely MO‐LS, MO‐GA, and MO‐MA are evaluated on some datasets generated randomly and on the well‐known QWS dataset to select the best fit services in terms of maximum or minimum aggregated end‐to‐end QoS parameters. The numerical results are encouraging and demonstrate the effectiveness of the proposed MO‐MA for the web service composition.
JSwarm: A Jingulu-Inspired Human-AI-Teaming Language for Context-Aware Swarm Guidance

Bi-directional communication between humans and swarm systems begs for efficient languages to communicate information between the humans and the Artificial Intelligence (AI)-enabled agents in a manner that is most appropriate for the context. We discuss the criteria for effective teaming and functional bi-directional communication between humans and AI, and the design choices required to create effective languages. We then present a human-AI-teaming communication language inspired by the Australian Aboriginal language of Jingulu, which we call JSwarm. We present the motivation and structure of the language. An example is used to demonstrate how the language operates for a shepherding swarm guidance task.
Management model of the COVID-19 pandemic in socially vulnerable communities

Introduction Several public policies were proposed to reduce the negative impact of COVID-19 pandemic. This work aimed to determine how a management model is capable of strengthening the community network, providing support, healthcare and channelling public government’s aid during COVID-19 pandemic situation. Methods It is an intervention study that tested the effectiveness of a management model for both healthcare and essential goods access in a socially vulnerable neighbourhood called ‘Puente de Fierro’ in La Plata the capital of Buenos Aires State, Argentina, during the COVID-19 pandemic. Altos de San Lorenzo suburb area was considered as control group. Variables studied were: level of contagion and death due to the SARS-CoV-2 virus; access to food, medicine and other goods; strengthening of community networks; performance of government programmes in territory. Results A new management paradigm was tested by moving essential goods towards the people, instead of making the people move to obtain those benefits. Accessibility to ‘Food Bag’ and ‘Food Bank’ were significantly increased, a reduction of contagion level and mortality rate for COVID-19 was achieved (2.3/100 000 vs 3.6/100 000 inhabitants in control area; and ‘fatality rate’ was 2.8% vs 3.6%, respectively). Support was also provided to installed in local stores virtual payment devices for food cards acceptance. Conclusion The management model based in healthcare and goods and service supplies during COVID-19 pandemic reduced the negative impact of disease and its measures of isolation in socially vulnerable neighbourhoods.