Reviewerly/exHarmony huggingface dataset:
Digital Etiquette and Its Specification (Philosophical and Methodological Aspect)

Introduction . Digital etiquette is a new type of etiquette that defines the rules of behavioral culture in the digital environment of the Internet. It is also shown that digital etiquette is not only a new type of communicative interaction, but also is one of the new socio-cultural phenomena of digital civilization, as well as modern convergent knowledge of a theoretical and applied nature, which is formed at the intersection of humanitarian and technological knowledge and is currently in the process of its formation. Methodology and sources. The work is based on the application of the methodology of historical-philosophical, cultural-philosophical, axiological and interdisciplinary approaches to the consideration of digital etiquette as a new communicative phenomenon of modern reality. The works of russian and foreign authors are devoted to the etiquette theme in the digital and non-digital environment as a source base, as well as modern scientific research are used in digital communications, including digital humanities. Results and discussion. Based on the analysis presented in the article according to the definition of etiquette as a phenomenon and as a concept, its essential features and distinctive characteristics, the specific features of digital etiquette are identified, including value attitudes that are determined by the properties of the third-generation Network (in particular, such as Digital- and Phygital-interaction, actualization of the reputational component of behavioral culture on the Internet, personalization of branding, etc.), which generally indicated the interdisciplinary nature of the new etiquette and the general trend of its development as a digital humanitarian knowledge. Conclusion. The role and importance of the behavioral culture of Network users at the personal and corporate levels becomes very important in modern realities. However, first of all, this applies to representatives of the younger generation-generation Z, which has defined personal freedom as the main value of its existence in society. In this regard, the role of the educational component, including its etiquette component, is objectified in the entire educational system. In particular, within the higher school, digital etiquette training is the training of digital humanitarian knowledge, which represents the unity of educational and educational in the formation of a behavioral culture that reflects the challenges of the new era.
SELECTED THEORIES ON CRIMINALISATION OF HACKING

Hacking or unauthorised access is criminalised in many jurisdictions, including Malaysia, Singapore, the United Kingdom, Hong Kong, and a few other countries. Hacking is the act of gaining access through the computer system or network without proper authority or exceeding the original authority given to him. Many commentators and researchers have reported on the conceptual and legal aspects of hacking. However, hacking's theoretical, conceptual, and legal aspects have remained under-researched. Therefore, this paper's primary objective is to outline the various theories, which could inform the criminalisation of hacking. The theories of routine activities, deterrence theory, social learning and self-control, general strain theory, and deviant subcultures are deliberated in this paper alongside illustrations within the context of hacking. This paper will shed light on the body of literature and contribute to a better understanding of hacking criminalisation from various theories discussed in this paper. Future research should be directed to provide empirical evidence of applying the theory to hacking criminalisation.
Serious Game Design for Virtual Dolphin-Assisted Learning

Virtual dolphin-assisted therapy (DAT) can be used to treat children with autism spectrum disorder (ASD), where interactions with virtual dolphins can be enabled by Virtual Reality (VR) technology. With the aid of VR, it is possible to reproduce an immersive environment with virtual objects to replicate the real-world DAT interactions. Using VR to create human–virtual dolphin interactions in an immersive setting allows DAT to be carried out virtually, protecting both participants, children and dolphins, from any harm or infections. The aim of recreating a DAT VR environment is also to make the treatment cheaper and more readily accessible to the masses of children with ASD. It can control the treatment environment and ensure the safety of the participants and those parties involved. A VR serious game, 3D Virtual Pink Dolphin is developed in Nanyang Technological University, which is running on both PC with single display screen and a 3D immersive room with 320-degree curved screens. The experiment has been conducted with children from a special needs school in Singapore.
Online probabilistic label trees

We introduce online probabilistic label trees (OPLTs), an algorithm that trains a label tree classifier in a fully online manner, without any prior knowledge about the number of training instances, their features and labels. OPLTs are characterized by low time and space complexity as well as strong theoretical guarantees. They can be used for online multi-label and multi-class classification, including the very challenging scenarios of one- or few-shot learning. We demonstrate the attractiveness of OPLTs in a wide empirical study on several instances of the tasks mentioned above.
Regional Cooperation Action of Poverty Alleviation by Education in China: Documentary of Pairing Assistance Action in Changxing County, Zhejiang Province

Poverty alleviation by education is the soul of reshaping the development of impoverished areas. In the implementation of poverty alleviation, the collaborative model of impoverished areas driven by developed regions is essential for China’s poverty alleviation work. In 2016, Changxing County, Huzhou City, Zhejiang Province, and Zhijin County, Bijie City, Guizhou Province, established a counterpart support relationship. According to Zhijin County’s education assistance needs, Changxing County has gathered its strength to implement management input, demonstration guidance, and training guidance for its weak schools. With vocational education as the starting point, Zhijin County has been “remodeled” and “implanted” education assistance and has achieved a win-win situation. This article takes the education counterpart support activities of Changxing County and Zhijin County as an example to explore the path and methods of regional education assistance in China under the vision of collaboration.
The Implementation of Computer-Assisted Language Learning (CALL) in the EFL Setting: A Case Study in a Secondary School in Indonesia

In this digital era, we cannot ignore that the use of Computer Assisted Language Learning (CALL) has given many benefits for both teachers and students in English instruction, especially in facilitating the students with an enjoyable and interesting learning experience. This research is a case study which aimed to investigate: 1) How is the implementation of CALL in the EFL setting, 2) How are the students’ attitude toward the use of CALL in English teaching and learning process, 3) How are the students’ achievement after the implementation of CALL in English teaching-learning process. The Subjects of this research were 30 students at SMA Laboratorium UM Malang. The data of this research were collected from the interview, observation checklist, questionnaire, and tests. The result of this research revealed that the implementation of CALL gave a positive effect on the students' achievement and broaden students' experience in learning English based on authentic context. Moreover, the students also presented positive responses toward the used of CALL in the English teaching-learning process.
An Assistive Solution to Assess Incoming Threats for Homes

35th Annual Assistive Technology Conference Scientific/Research Proceedings, San Diego, 2020
Construction of a Sharing Mode Based on VR Technology in the Context of Big Data

Abstract With the advancement of science and technology in recent years, the era of big data has gradually matured, and the era of intelligence has gradually penetrated into ordinary life. The improvement of technology around the world not only promotes the improvement of the quality of human life, but also has a direct impact on the operating mode of companies in all walks of life. Intelligent products are gradually replacing simple manual work projects. As the core technology of computers, VR technology has been widely used in various fields of social life. As the most imaginative and promising industry in the 21st century, virtual reality technology will completely change people’s lifestyles. Virtual reality technology (English name: Virtual Reality, abbreviated as VR) is a new practical technology developed in the 20th century, including computers, electronic information and simulation. Including all technologies, the basic realization method is the computer VR environment to make people feel immersed in the environment. With the development of social productivity and science and technology, the demand for VR technology in various fields also increases. VR technology has made considerable progress and has become a new field of science and technology, and a proposal to establish a shared model system has been proposed. It aims to improve the state of the technology research and development industry and solve its pain. By combining VR technology with sharing, we will promote the reform of the sharing model, open public scientific and technological knowledge resources to those in need, expand the depth of access to technical knowledge, and increase the difficulty of current Internet knowledge. It aims to solve and improve the quality and satisfaction of people’s knowledge needs.
Academic Paper Recommendation Method Combining Heterogeneous Network and Temporal Attributes

In the case of information overload of academic papers, the demand for academic paper recommendation is increasing. Most of the existing paper recommendation methods only utilize scholar friendship or paper content information, and ignore the influence of temporal weight on research interest, and hence they are hard to obtain good recommendation quality. Aiming at this problem, the method HNTA for academic paper recommendation based on the combination of heterogeneous network and temporal attributes is proposed. HNTA firstly constructs a heterogeneous network composed of different types of entities to calculate the similarity between two papers, and then the temporal attribute is introduced into scholars’ research interests which are divided into instant interests and continuous interests to calculate the similarity between scholars and papers. Finally, by weighting the above two similarities, the purpose of recommending papers to scholars is achieved. Overall, HNTA can not only comprehensively utilize both relationships of scholars and the content information of papers, but also it considers the impact of the temporal weight of scholars' research interests. By conducting comparative experiments on the data set of the real academic social network: SCHOLAT, the results show that HNTA performs better than traditional paper recommendation methods.
Differentiable game mechanics

Deep learning is built on the foundational guarantee that gradient descent on an objective function converges to local minima. Unfortunately, this guarantee fails in settings, such as generative ad...
An Efficient Search Scheme Over Encrypted Data On Mobile Cloud

Cloud storage provides storage at a low cost. But users are concerned about issues like data privacy and security, which inhibit them from storing files on the cloud storage. We can secure data in the cloud by a simple and usual technique of encrypting the data and which later decrypted during file download. But encryption creates overhead on mobile devices. The mode of communication turns more complex while data retrieval from cloud storage to the user device. Mobile has limited bandwidth and battery which makes the encrypted search very challenging. The proposed system with Traffic and Energy-saving Encrypted Search (TEES) algorithm is a bandwidth-efficient encrypted search in the mobile cloud. This proposed architecture offloads the computation, optimizes the communication between, and maintains the data privacy without degrading the performance of the mobile. TEES limits the computation time, saves energy consumption and network traffics while retrieving the files.
Unlinkable Updatable Hiding Databases and Privacy-Preserving Loyalty Programs

Abstract Loyalty programs allow vendors to profile buyers based on their purchase histories, which can reveal privacy sensitive information. Existing privacy-friendly loyalty programs force buyers to choose whether their purchases are linkable. Moreover, vendors receive more purchase data than required for the sake of profiling. We propose a privacy-preserving loyalty program where purchases are always unlinkable, yet a vendor can profile a buyer based on her purchase history, which remains hidden from the vendor. Our protocol is based on a new building block, an unlinkable updatable hiding database (HD), which we define and construct. HD allows the vendor to initialize and update databases stored by buyers that contain their purchase histories and their accumulated loyalty points. Updates are unlinkable and, at each update, the database is hidden from the vendor. Buyers can neither modify the database nor use old versions of it. Our construction for HD is practical for large databases.
Challenges of applying artificial intelligence responsibly at scale in healthcare

Objective: This article aims to present a case study on the main challenges of applying artificial intelligence (AI) in a scalable manner, following the precepts of the research field on responsible AI in the health area. Method: During the referred period, data were collected on operation, medical reports and examinations of the telemedicine system studied, which were analyzed and compared in different ways. Results: As a result, two different perspectives of the theme were defined, one regarding operational requirements, which are linked to the daily use of such technology, and another to technical requirements, which are related to the essential characteristics of these tools. Both were illustrated through reports and data from practical and real examples. Conclusion: From this set of information, some more critical points were raised and discussed, highlighting the caution necessary to work with AI in health and its benefits.
Review on Gradient Descent Algorithms in Deep Learning Approaches

Deep learning (DL) is assuming an inexorably significant part in our lives. It has effectively affected cancer diagnosis, precision medicine, self-driving cars, predictive forecasting, speech recognition, and so forth. The meticulously high-quality element extractors utilized in the traditional learning, grouping, and example recognition frameworks are not adaptable for enormous measured informational collections. By and large, relying upon the complex intricacy, deep learning can likewise defeat constraints of prior shallow networks that forestalled productive preparing and reflections of progressive portrayals of multi-dimensional preparing information. Deep Neural Network (DNN) utilizes different (deep) layers of units with exceptionally streamlined algorithms and architectures. The paper audits a few streamlining strategies to improve the exactness of the preparation and diminish preparing time.
A new Feature Reduction Algorithm Based on Fuzzy Rough Relation for the Multi-label Classification

The paper aims to improve the multi-label classification performance using the feature reduction technique. According to the determination of the dependency among features based on fuzzy rough relation, features with the highest dependency score will be retained in the reduction set. The set is subsequently applied to enhance the performance of the multi-label classifier. We investigate the effectiveness of the proposed model againts the baseline via time complexity.&#x0D; Keywords: &#x0D; Fuzzy rough relation, label-specific feature, feature reduction set&#x0D; References&#x0D; [1] Richard Jensen, Chris Cornelis, Fuzzy-Rough Nearest Neighbor Classification and Prediction. Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing, 2011, 310-319.&#x0D; [2] Y.H. Qian, Q. Wang, H.H. Cheng, J.Y. Liang, C.Y. Dang, Fuzzy-Rough feature selection accelerator, Fuzzy Sets Syst. 258 (2014) 61-78.&#x0D; [3] Quang-Thuy Ha, Thi-Ngan Pham, Van-Quang Nguyen, Minh-Chau Nguyen, Thanh-Huyen Pham, Tri-Thanh Nguyen, A New Text Semi-supervised Multi-label Learning Model Based on Using the Label-Feature Relations, International Conference on Computational Collective Intelligence, LNAI 11055, Springer, 2018, pp. 403-413.&#x0D; [4] Daniel Kostrzewa, Robert Brzeski, The data Dimensionality Reduction and Feature Weighting in the Classification Process Using Forest Optimization Algorithm, ACIIDS, 2019, pp. 97-108.&#x0D; [5] Nele Verbiest, Fuzzy Rough and Evolutionary Approaches to Instance Selection, PhD Thesis, Ghent University, 2014.&#x0D; [6] Y. Yu, W. Pedrycz, D.Q. Miao, Multi-label classification by exploiting label correlations, Expert syst, Appl. 41 (2014) 2989-3004.&#x0D; [7] M.L. Zhang, LIFT: Multi-label learning with label-specific features, IEEE Trans, Pattern Anal, Mach, Intell 37 (2015) 107-120.&#x0D; [8] Suping Xu, Xibei Yang, Hualong Yu, Dong-Jun Yu, Jingyu Yang, Eric CC Tsang, Multi-label learning with label-specific feature reduction, Knowledge-Based Systems 104 (2016) 52-61. https://doi.org/10.1080/24751839.2017.1364925.&#x0D; [9] Thi-Ngan Pham, Van-Quang Nguyen, Van-Hien Tran, Tri-Thanh Nguyen, Quang-Thuy Ha, A Semi-supervised multi-label classification framework with feature reduction and enrichment, Journal of Information and Telecommunication 1(4) (2017) 305-318.&#x0D; [10] M. Ghaemi, M.R. Feizi-Derakhshi, Feature selection using forest optimization algorithm, Pattern Recognition 60 (2016) 121-129.&#x0D; [11] M.L. Zhang, Z.H. Zhou, ML-KNN: A lazy learning approach to multi-label learning, Pattern Recognition 40 (2007) 2038-2048.&#x0D; [12] M.Z. Ahmad, M.K. Hasan, A New Approach for Computing Zadeh's Extension Principle, MATEMATIKA. 26(1) (2010) 71-81.&#x0D; [13] Richard Jensen, Neil Mac Parthaláin and Qiang Shen. Fuzzy-rough data mining (using the Weka data mining suite), A Tutorial, IEEE WCCI 2014, Beijing, China, July 6, 2014.&#x0D; [14] D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets, Int. J. Gen. Syst. 17 (1990) 191-209.
Monetary Policy and the Future of Central Banking

The chapter highlights the state of monetary policy in Africa and explores the challenges that central banks face as they address the increasingly complex forces at work in the global economy. It sequences the evolution of monetary policy from the time of World War II under the Bretton Woods system to the more recent forward-looking monetary policy in advanced economies and relates it to influencing the evolution of monetary policy frameworks in Africa. Some challenges affecting African countries are identified, including the collapse of commodity prices, persistent high interest rates spreads, and limitations of high frequency data that constrain monetary authorities’ abilities to take corrective actions in a timely manner. The chapter concludes by providing seven principles towards increasing the effectiveness of monetary policy for countries seeking to move towards forward-looking monetary policy frameworks.
Pre Treatment of Raw Water Through the Coagulation Process, Filtration, Absorption, and Ion Exchange in Drinking Water

Health risks relating to pollutants can generally be caused by, among other things, industrial and agricultural activities. Whereas e Coli bacteria constitute a parameter in water use. This study investigates the ability in reducing the parameters of Total Dissolved Solids, turbidity, total hardness, chloride, manganese, and total coliform through the coagulation, filtration, absorption, and ion exchange processes as a pre-treatment for drinking water treatment. The method used was as follows: the processing of raw water material begins Coagulant Aid to the coagulant tank, then using polypropylene sediment in the filtration treatment on the housing filter. Then the following treatments are successively conducted; Ferrolite and Manganese Greensand in the housing filter as a function of absorption, and for ion exchange synthetic anions and cations are used in FRP tubes. To conclude, pre-treatment of raw water through the coagulation process, filtration, absorption, and ion exchange in drinking water treatment can set aside: Total Dissolved Solid was 1,360 mg/L (21%), turbidity was 6.3 scale of NTU (95%), total hardness was 265 mg/L CaCO3 (16%), chloride was 292 mg/L Cl- (10.5%), Manganese 1.235 mg/L Mn (close to 82%), and Total Coliform 3,140 MPN/100 mL (60%).
Effectiveness of WhatsApp Messages Regarding Improved Agricultural Production Technology

Agricultural information can play very important role in the development of small farmers. By using communication technologies farmers can increase their production and income. In the perspective of the mobile phones farmers can directly communicate with buyers and customers for selling their produce at good price. In remote areas farmers are still facing many problems in using technologies due to lack of infrastructure and awareness. Most of the farmers still depend on old traditional methods in agriculture due to lack of knowledge, illiteracy and trainings. WhatsApp technology has provided a platform for farmers to share their knowledge and information among each other on crucial time for market rates and weather information. WhatsApp messenger is a proprietary, cross platform instant messaging application for smart phones. In addition to text messaging, users can send images, video, and audio media messages. The study conducted in Dewas district showed that the WhatsApp was able to increase the knowledge of the farmers on soybean production technology and was farmers were at high to low level of knowledge regarding social media based technical information.
Adaptive Approximate Policy Iteration

Model-free reinforcement learning algorithms combined with value function approximation have recently achieved impressive performance in a variety of application domains. However, the theoretical understanding of such algorithms is limited, and existing results are largely focused on episodic or discounted Markov decision processes (MDPs). In this work, we present adaptive approximate policy iteration (AAPI), a learning scheme which enjoys a $\tilde{O}(T^{2/3})$ regret bound for undiscounted, continuing learning in uniformly ergodic MDPs. This is an improvement over the best existing bound of $\tilde{O}(T^{3/4})$ for the average-reward case with function approximation. Our algorithm and analysis rely on online learning techniques, where value functions are treated as losses. The main technical novelty is the use of a data-dependent adaptive learning rate coupled with a so-called optimistic prediction of upcoming losses. In addition to theoretical guarantees, we demonstrate the advantages of our approach empirically on several environments.