Reviewerly/exHarmony huggingface dataset:
Ddacsdc: Dynamic Data Access Control And Secure Deduplication In Cloud

Cloud storage is one of the important services provided by cloud computing. It helps cloud users to overcome the drawback of limited resources usage, so that they can increase their storage capacity without enhancing their devices. In order to ensure the privacy and security to the data user, data is encrypted before uploading it in cloud. If we store a encrypted data in the cloud it consume more storage space. It is a difficult task to share encrypted data among the authorized users. Many schemes have been introduced to manage the storage space and access to the encrypted data in the cloud. The existing Heterogeneous Data Storage Management (HDSM) scheme introduced a authorized party with data owner to manage the data access control based on their interest. There is no option to add a new user to access for the file already exists in cloud. This process cannot achieve deduplication process and security efficiently. To address the limitations of the existing scheme a Dynamic Data Access Control and Secure Deduplication in Cloud (DDACSDC) has been proposed that provides dynamic data access permission to the new data user by verifying them based on their request. This new technique helps to improve system efficiency by performing better data deduplication process, minimize the cloud storage space utilization and reduce the data uploading time. To make system more secure and maintain data privacy Identity-based Proxy Re-encryption Scheme (IB-PRE). The performance analysis shows that the proposed scheme provides better security and improves system efficiency as compared to the existing scheme.
Tuning into Blockchain: Challenges and Opportunities of Blockchain-Based Music Platforms

Blockchain technology is an intensely discussed enabler of large-scale societal and economic change, but the circumstances under which different industries succeed or fail in implementing blockchain are not yet sufficiently understood. One example is the music industry, in which the promise of blockchain is not yet fulfilled, despite a growing number of ambitious blockchain providers. This paper explores the challenges and opportunities of blockchain-based music platforms. Grounded in an exploratory qualitative case study within the music industry at seven organizations and related literature, we iden- tify three main challenges for digital music business, namely: 1) Inconsistent and incomplete music metadata, 2) Historically grown complex licensing structures, and 3) Inefficient and non-transparent royalty payouts. We provide insight into how blockchain may address these challenges by means of a decentralized global song database that allows for automatic royalty payouts. Our results inform re- searchers and practitioners how the music industry may create value from blockchain-based music platforms. We offer a nuanced and balanced view on value creation with blockchain and outline a path for further research and development on blockchain-based solutions for the music industry.
Five-year plan – for the "Five" (Review of the Yearbook on Science, Education and Business Issues)

The review of five Yearbooks is presented, the key directions of the analysis of the interaction between education, science and business are highlighted, the main authors are named, and the prospects for its further publication are characterized. Innovations in this direction are described.
Causes of Interest Lack in Learning English at the Ihya'ul Ulum DDI Baruga, Majene, West Sulawesi

The purpose of this research is to find out the ability of students ansd then to motivate students to develop interest in learning in English subjects in one of our targeted schools, namely Baruga Ihyaul Ulum DDI Boarding School, this school is a school that has not been established for too long in terms of interests and abilities are still minimal especially the area including remote areas. The population of this study was mostly students of class X and class XI. This research is a qualitative research that does not require numbers to be analyzed. The results of the observations that we have obtained are giving motivation to students and fostering their confidence that can build students' interest in learning. The method that we use in this study is by interviewing the school to find out the state of learning and learning English in the school and giving motivation to students.
Professional Practice: A Case Study of Collaborations between Education and Industry

Collaboration between university and industry has brought societal and educational benefits by promoting research and innovation, providing industry training, and promoting access to resources and technology for both academia and industry. University, industry, and government collaboration known as the triple helix was proposed in the 1990s. However, industry and university collaboration has had a long history with best practices being updated as we learn more about specific fields, needs of collaborators, and advances in research and technology.This case study aims to find the best practices for collaboration between education and industry in a project-based educational program known as Professional Practice for students studying in the field of information technology. During this four-week program, students worked on assignments formulated by the participating companies. They were guided by company-assigned supervisors, who were interviewed before and after the program. The students too were asked to fill out surveys before and after the program. From the analyses of the results of the interviews and surveys, several recommendations and ways to improve collaboration between education and industry are presented.
Multi Head Self Attention Mechanism Based Multi-scale Spatial-Temporal Mixed Text Classification Method Research

In text classification tasks, convolutional method can extract local features of text, but it ignores context semantic information and long-distance dependency. The mechanism of long-term and short-term memory can make up for this shortcoming, but it cannot extract local features of text effectively. Therefore, this paper proposes a Multi Head self Attention mechanism based Multi-scale Spatial- Temporal mixed text classification model (MHA-MST). We use the multi head self attention mechanism to focus on the words that have a significant impact on classification, use multi-channel CNN with convolution kernels of different sizes extract local features of texts with different granularity, use stack Ordered Neurons-Long Short-Term Memory(ON-LSTM) extract context semantic information and long-distance dependency, the spatial-temporal mixed features extracted by multi-channel CNN and stacked ON-LSTM are sent to softmax classifier to obtain classification results. The experimental results on Taobao review data set and THUCNews data set show that the proposed MAHMCO model achieves better classification results than other models.
Importance and problems of e book in nowadays education system

This International event is another small endeavor in the direction to bring together the experienced intellectual on one hand, and the young inquisitive minds on the other hand, to develop new thoughts, new ideas and new strategies to combat the challenges of changing pattern of world demand.I extend a warm welcome to all the participants from across the world to this mega event and hope that two days scientific deliberations of this august congregation will go a long way in shaping the philosophy and action, and make a valuable contribution to the field of Research and Development.
Neural Methodius Revisited: Do Discourse Relations Help with Pre-Trained Models Too?

Recent developments in natural language generation (NLG) have bolstered arguments in favor of re-introducing explicit coding of discourse relations in the input to neural models. In the Methodius corpus, a meaning representation (MR) is hierarchically structured and includes discourse relations. Meanwhile pre-trained language models have been shown to implicitly encode rich linguistic knowledge which provides an excellent resource for NLG. By virtue of synthesizing these lines of research, we conduct extensive experiments on the benefits of using pre-trained models and discourse relation information in MRs, focusing on the improvement of discourse coherence and correctness. We redesign the Methodius corpus; we also construct another Methodius corpus in which MRs are not hierarchically structured but flat. We report experiments on different versions of the corpora, which probe when, where, and how pre-trained models benefit from MRs with discourse relation information in them. We conclude that discourse relations significantly improve NLG when data is limited.
Exploration on the Path of Vocational Education Serving Urban and Rural Integration Development Based on Rural Revitalization Strategy

The rural revitalization strategy has been implemented in China for a period of time, but the effect of the early rural revitalization strategy has not reached the expectation, which makes the relevant domestic organizations and even leaders reflect and find that in order to achieve the goal of rural revitalization, what we should really do is to strengthen the hematopoietic capacity of rural areas. Under the result of this reflection, the country puts forward the policy of urban-rural integration development around the general characteristics of rural areas. Guided by the policy, the field of vocational education should make efforts to provide vocational education services to rural areas and cultivate more excellent vocational talents. Talents will enable the rural areas to connect with the city, and finally achieve the goal of urban-rural integration development, Rural revitalization Strategy has really started. In order to provide good vocational education services to rural areas, this paper will carry out research, mainly discusses the relationship between vocational education and urban-rural integration development, points out the main reasons for hindering urban-rural integration development, and finally puts forward the development path from the perspective of vocational education.
Technical debt reduction using epsilon-Nash equilibrium for the perturbed software refactor game model

Technical debt (TD) is a metaphor that is one of the reasons for software to become obsolete. The process of refactoring can be effectively applied to reduce the technical debt and the improvement of other vital quality attributes such as abstraction, inheritance and coupling. This paper discusses a refactoring model that can be applied for an object oriented software system for improved quality by applying the concepts of game theory. A multi-player perturbed software refactor game model is developed, that models inheritance, abstraction, coupling and the technical debt, as multiple players of the game. An optimal strategy for refactoring the source code is arrived by calculating the ε-Nash equilibrium of the perturbed game. The results attained are compared against the popular genetic algorithm (GA), artificial bee colony (ABC) and simulated annealing (SA) optimisation algorithms, taking three open source Java project samples.
OVERVIEW OF NEOBANKS MODEL AND ITS IMPLICATIONS FOR TRADITIONAL BANKING

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The Impact of Non-Cognitive Characteristics on the Higher Education Choice-Making: An Economist Perspective

The article presents a review of literature systematizing findings on the contribution of non-cognitive skills to higher education choice-making. The concept of higher education choice-making in this paper embraces the decision to embark on a college degree, the probability of successful degree completion, the choice of academic discipline, and other related aspects. A priority focus is given to publications in economics since the economic approach differs a lot from approaches in other social sciences. In addition, the article explores the methodological characteristics of non-cognitive skills research in economics. The results of literature analysis point to the relevance of non-cognitive skills in explaining individual educational choices and allow drawing some inferences for education policy.
Online training of schoolchildren in informatics based on web platform with interactive posters: Theory and experience of implementation

The article examines the theoretical and practical aspects of organizing online teaching of informatics to schoolchildren using interactive posters, developed by a teacher on a web platform. The possibilities of online teaching of schoolchildren using various electronic media as well as resources and services of the Internet are discussed. The multidimensional capabilities of interactive electronic tools for the inclusion of students in various types of educational and cognitive activities during network interaction are analyzed. The concepts of “multidimensional didactic tools” and “interactive posters” are revealed, acting as an innovative teacher’s tools for managing and enhancing the cognitive activity of students. Particular attention is paid to the analysis of the design and creation of interactive posters by the teacher and the educational interaction of students with these posters based on the web platform. The characteristics of the capabilities of popular services for creating interactive posters are described. The experience of using interactive posters in teaching informatics at school based on the web platform is revealed. The authors’ approach to the use of tools of popular services for creating and integrating content and controls into interactive posters is proposed.
Improving The Eighth Grade Students’ Vocabulary Mastery Of Smp Negeri 15 Banda Aceh By Using Cognitive Learning Strategy

The study was aimed to find out if there is a significant difference between the eighth grade students of SMP Negeri 15 Banda Aceh who are taught vocabulary by using cognitive learning strategy and those who are taught without using cognitive learning strategy. The experiment was conducted from February 12th, 2019 to February 16th, 2019 at SMP Negeri 15 Banda Aceh. This study is conducted by using quantitative research and in this case is an experimental study. The population of this study is all students of the eighth grade students of SMP Negeri 15 Banda Aceh in academic year 2019/2020. The total population is 40 students who are composed of two classes; class VIII-1 and class VIII-2. While the sample of this study is taken from two classes of the two classes. One class is an experimental group and one another is as control group. In this study, the students of class VIII-1 are taken as experimental group and the students of class VIII-2 are taken as control group. Every group consists of 20 students thus the total sample is 40. Choosing class as experimental and control group is done randomly. The data were gotten through test; pre-test and post - test. The data were analyzed by using SPSS 18.0. The result of the study shows that there is a significant difference between the eighth grade students of SMP Negeri 15 Banda Aceh who are taught vocabulary by using cognitive learning strategy and those who are taught without using cognitive learning strategy. It can be proven from the result of this study where the result of t-test of post-test of the both group is 4.616. While the result of t-table with the level of significance 0,05 is 0,668. Thus, t-test (4.616) is greater than the t-table (0,668). Based on the result of the study, English teachers of SMP Negeri 15 Banda Aceh especially those who teach vocabulary should implement cognitive learning strategy in teaching and learning process because the implementation of the strategy can increase the students’ vocabulary mastery. KEYWORDS: Vocabulary, Cognitive Learning Strategy.
Towards Identifying Augmented Reality Unique Attributes to Facilitate Chemistry Learning

Augmented Reality (AR) applications have the potential to improve students’ Chemistry learning performance. By identifying the unique features and affordances of this technology, we can design more effective tools to facilitate the learning process of abstract concepts. We developed Periodic Fable in the Wild, an AR serious game as an instrument to conduct design-based research. The game aims to facilitate the learning of abstract concepts related to the Periodic Table by children (9 to 13 years old). We intend to optimize our game by continuing our research with our target audience, analysing their feedback, making refinements and continuing testing.
Data mining techniques are being used to map the number of foreign guests at Indonesian star hotels

Statistics on foreign tourist arrivals show an upward trend in recent years. This is beneficial because foreign exchange in the tourism sector is generated by spending by foreign tourists visiting Indonesia. Mapping the number of tourists who visit Indonesia is necessary to determine the extent of a region's natural potential. The number of foreign guests at Indonesia's star hotels is one indicator that can be used. The goal of this study is to use data mining techniques to visualize the mapping pattern of the number of foreign guests at five-star hotels in order to obtain important information. The Central Statistics Agency (abbreviated BPS) provided the data for the number of foreign guests at five-star hotels in 2017-2019. Clustering with the k-medoids technique is the data mining method employed. The Davies-bouldin index (DBI) operator is used to calculate the number of clusters. The number of good clusters was 3 (k=3), with cluster 0 (low) = 20 provinces, cluster 1 (normal) = 23, and cluster 2 (high) = 1 province, and a DBI value of 0.215 (k=3). According to the study's findings, the province of Bali is one of the areas with the greatest potential for foreign tourist visits (high cluster). Meanwhile, there are 20 provinces with a low number of foreign visitor visits, so this can be used to assess how to increase the number of foreign visitor visits to the province.
Introducing new horizons in teaching science

Preface to the AAPP supplementary issue collecting the proceedings of the international conference on “New Horizons in Teaching Science” (18 th - 19 th  June 2019; Messina, Italy).
Theses@HKU: Finding Theses

This workshop introduces some of the databases that are available tolocate academic theses and dissertations, covering in particular:HKU thesesHKU Scholars HubWorldwide thesesProQuest dissertations and theses A&I (PQDT)Digital Dissertation ConsortiumChinese theses中國知網 (China National Knowledge Infrastructure)臺灣博碩士論文知識加值系統 (National Digital Library of Theses and Dissertations in Taiwan)
Hubungan Bimbingan Keluarga terhadap Hasil Belajar Matematika Siswa Kelas V SD Inpres 12/79 Cellu II

The problem in this study is the lack of guidance for students families so that it has an impact on the results of learning mathematics students. This research is a quantitative research with a correlational design that aims to determine wether there is a relationship between family guidance and learning outcomes for V grade students of SD Inpres 12/79 Cellu II. The results showed that there was a significant relationship between family guidance and mathematics learning outcomes for V grade students of SD Inpres 12/79 Cellu II with t-count (5,567) is greater (>) the t-table value (1,697), which means H 0 is rejected and H 1 is accepted. Based on the analysis of the date above, it can be concluded that family guidance will have an impact on the mindset of students in learning so that it will affect the motivation and learning outcomes of students in the classroom. So, the better the family guidance, the better students learning outcomes will be. From these conlisions,, the impact resulting from this study is know that good family guidance will improve student learning outcomes.
Registers in Facebook Postings Used by Online Marketers in West Borneo

The present study aims to describe the registers used by online marketers in three-private Facebook fan pages in West Borneo. Different from the previous research of registers in online marketing on Facebook, the present study scrutinizes the linguistic features including the form and function of lexical marking of the used registers using domain, taxonomy, and componential data analysis proposed by Spradley (1980) and Santosa (2017). The domain analysis classifies the types of the sold goods namely electronics, fashion, food and beverages, properties, and vehicles. Using descriptive qualitative research method, the researcher describes what registers used in promoting and asking for the goods in Facebook postings. Thus, the postings were gingerly observed as the objects of this study. The analysis of the registers found 70 registers consisting of 48 words and 22 phrases used in online trading. According to the domain and function of the registers, the study found: in the domain of electronics, there were 4 registers which function as offering, 1 as interest, and 2 as bargaining; in the domain of fashion, there were 13 registers as offering; (3) in the domain of food and beverages, there were 11 registers as offering; in the domain of properties, there were 15 registers as offering, 1 as bargaining, and 4 as dealing; in the domain of vehicles, there are 9 registers as offering, 4 as interest, 4 as bargaining, and 2 as dealing. The result of analysis also revealed that most of the registers were dominated by code mixing considering the structure of the two or more languages used in the same utterances. Those would be very beneficial relating to the business world.
A Fast Underwater Image Stitching Algorithm with Adaptive Adjustment of Attitude Angle

In underwater image acquisition process, due to the impact of water currents and other disturbances, the movement posture of the underwater machine will be unstable, which could lead to unusual problems such as twisting of underwater image capture. These factors will increase the error rate of feature point matching and lead to the failure of panoramic image mosaic. In this regard, we propose a new, highly applicable underwater image stitching algorithm. Firstly, the posture angle adjustment link is added to the underwater image processing, and the angle deflection problem of the underwater image is effectively improved by using the posture angle information. Secondly, the feature points of underwater images are extracted based on the accelerated robust feature (SURF) algorithm. Then, the reference image is matched with the feature points of the image to be registered, and effective feature point pairs are obtained by screening. Finally, the images are stitched based on OpenCV to obtain a good panoramic image. After experimental analysis and comparison, our method can increase the number of matching feature point pairs between images. In addition, the Euclidean distance is significantly shortened during the matching process, which further makes the matching of feature points more accurate. Our method satisfactorily overcomes the adverse effects of actual underwater operations and has a better application prospect.
An Efficient Method for a Specific Case of Detecting Impulse Noise on Scanned Documents

This paper explains a method used to detect the presence of impulse noise in a set of scanned documents as a part of OCR preprocessing. As the document set is supposed to be processed in large scale, the primary concern of the noise detection method was efficiency within existing project constraints. Following the nature of noise, the method seeks to detect the presence of noise in document margins. The method works in two stages. First stage is margin detection, based on color spectre analysis. Second stage is noise recognition in margin samples, based on a pixel contrast score. The resulting implementation proved efficient both in terms of detection accuracy and algorithmic complexity.