Reviewerly/exHarmony huggingface dataset:
FAIR-AREA: A Fast AI-Based Joint Optimization of Rate Adaptation and Resource Allocation for DASH

Video streaming service has been consuming a massive amount of Internet traffic during recent years. Even though Dynamic Adaptive Streaming over HTTP (DASH) has become the mainstream technology for improving users' Quality of Experience (QoE), the competing of multiple independent DASH streams could degrade the QoE and make unfair resource allocation. With the support of Software Defined Networking (SDN), it is possible to jointly optimizing resource allocation and bitrate adaptation in this competing scenario. In this paper, we propose FAIR-AREA, a fast Artificial Intelligence based joint optimization of rate adaptation and resource allocation of DASH service. With FAIR-AREA, we can solve this complex optimization problem only in milliseconds and achieve near optimal performance at the same time.
A conceptual framework for improving buyers’ innovation through cloud procurement technology. The mediating role of relational capital

International markets are becoming volatile and uncertain, and companies which hope to survive must establish extremely responsive collaborative relationships with their suppliers. Companies have focused on investing in highly sophisticated information technology (IT) to facilitate supplier integration and foster the acquisition of knowledge conducive to innovation. This study aims to explore the innovation capacity of companies in terms of products and services, the responsiveness to demand, and the decrease in the life cycle of products through the use of cloud computing (CC) on the procurement process. The study will also investigate empirically the important role of internal IT advancement as an antecedent to integrating suppliers on firms adopting CC. Finally, we will analyse the mediating role of relational capital in this form of integration and its impact on the development of innovation. Keywords: Supplier-buyer, Innovation, Cloud computing procurement, Relational Capital.
User Experience of Creativity Support Tools – A Literature Review in a Management Context

Creativity Support Tools or Creativity Support Systems are a wellstudied subject in the research of computer science and information systems. Whether the User Experience of Creativity Support Tools or Creativity Support Systems has been likewise sufficiently researched, shall be examined. A systematic literature search was conducted to investigate the current state of scientific literature. This review provides a brief overview of open and superfluous research areas in the field of User Experience for the development of Creativity Support Tools for business or management purposes. A total of 19 papers were selected and coded, sorted to concepts and assigned to the various phases of the creative process. The results of the analysis have shown that there is a need for further research in this field.
THE EFFECT OF USING STORYBOOKS ON READING INTERESTS AND LEARNING OUTCOMES OF GRADE IV ELEMENTARY SCHOOL STUDENTS

This study aimed to investigate the effect of the use of storybooks on reading interest and learning outcomes in fourth grade students of Elementary School XIII Buleleng District. Of the 157 students of the population, 64 students were designated as samples drawn by random sampling technique. Data collected by the reading interest questionnaire, while learning outcomes data collected by objective tests. Data analysis technique used in this research is Manova. The result of the research shows that: 1) There are differences of reading interest between students who are taught by accompanying by a story book and taught only using the 2013 Curriculum Book on learning Subtheme of My Neighborhood in fourth grade students of Elementary School XIII Buleleng District, 2) there is a difference in learning outcomes between students who were taught by accompanied by a story book and taught only using the 2013 Curriculum Book on learning Subtheme of My Neighborhood in fourth grade students of Elementary School XIII Buleleng District, 3) there are differences of simultaneous reading interest and learning outcomes between students who were taught accompanied by a story book and taught only using the 2013 Curriculum Book on learning Subtheme of My Neighborhood in fourth grade students of Elementary School XIII Buleleng District. Keyword: Storybook, Learning Outcomes, Reading Interest
A Study on the Value Added Criterion of Rules of Origin under FTAs with the US and EU: Focusing on Automotive Sector

Purpose – This study deals with a strategic plan for meeting the value added criteria effectively, which is one of the methods of determining origin used in preferential trade such as FTA. Automobile products, one of the major Korean export items, were selected to give a practical use against the FTA requirements. Design/methodology – This study is based on the value-added criteria of the Korea-US and Korea-EU FTAs that apply various value-added criteria. The Korea-US FTA adopts the RVC method based on the integration, deduction and net cost methods, while the MC method is employed in the Korea-EU FTA. The methodology used in this work is an extended literature review, analysis of the value-added criteria applied to automobile products under Korea-US and Korea-EU FTA with some secondary statistics. Findings – Based on in - depth analysis of the value - added criteria requirements for automobile products stipulated in the Korea - US FTA and the Korea - EU FTA, two strategic considerations are suggested. First is ‘appropriate value-added strategy’ and the second is ‘strategy of changing production and trade structure’. The second strategy is a bit used in Korea but this is not considered best if the first strategy is ignored or forgotten. The second one is meaningful when this becomes inevitable. Research limitations/implications – This study is primarily designed to assist Korean auto mobile industry players exporting to EU and USA but this may help to auto part or material producers in FTA counter party territories being EU or USA as the preferential tariffs are applied on a inter region basis. A further research other than auto mobiles using other major FTAs might be followed later. Originality/value – There has been so far little research on strategic factors to meet the value-added origin requirements. This study, therefore, is expected to contribute facilitating the decision of FTA origin and to improve the utilization of FTA by allowing exporting companies using value added criterion to more smoothly meet origin requirements. This will also enable the tax authorities to utilize the value-added criterion to validate effectively the origin of imports where preferential tariffs are applied.
Cascade Wide Activation Multi-Scale Networks for Single Image Super-Resolution

In recent years, convolutional neural network (CNN) has made great progress in the field of single image super-resolution (SR). There is a strong correlation between multiple scales in SR, which has not been fully utilized by the previous works. In this paper, we first propose a new network structure based on WDSR, which is called JWDSR. JWDSR takes full advantage of the features generated by the residual blocks and leads to a better Peak Signal to Noise Ratio (PSNR). We then propose a cascaded multi-scale JWDSR network called CMDSR. CMDSR fully employed the correlation between multi-scale networks and supports multi-scale SR calculations. Experiment results on benchmark data sets show that CMDSR can get higher PSNR faster with fewer parameters than the previous works.
The Heritage Data Reuse Charter: from principles to research workflows

There is a growing need to establish domain-or discipline-specific approaches to research data sharing workflows. A defining feature of data and data workflows in the arts and humanities domain is their dependence on cultural heritage sources hosted and curated in museums, libraries, galleries and archives. A major difficulty when scholars interact with heritage data is that the nature of the cooperation between researchers and Cultural Heritage Institutions (henceforth CHIs) is often constrained by structural and legal challenges but even more by uncertainties as to the expectations of both parties. The Heritage Data Reuse Charter aims to address these by designing a common environment that will enable all the relevant actors to work together to connect and improve access to heritage data and make transactions related to the scholarly use of cultural heritage data more visible and transparent. As a first step, a wide range of stakeholders on the Cultural Heritage and research sector agreed upon a set of generic principles, summarized in the Mission Statement of the Charter, that can serve as a baseline governing the interactions between CHIs, researchers and data centres. This was followed by a long and thorough validation process related to these principles through surveys 1 and workshops 2. As a second step, we now put forward a questionnaire template tool that helps researchers and CHIs to translate the 6 core principles into specific research project settings. It contains questions about access to data, provenance information, preferred citation standards, hosting responsibilities etc. on the basis of which the parties can arrive at mutual reuse agreements that could serve as a starting point for a FAIR-by-construction data management, right from the project planning/application phase. The questionnaire template and the resulting mutual agreements can be flexibly applied to projects of different scale and in platform-independent ways. Institutions can embed them into their own exchange protocols while researchers can add them to their Data Management Plans. As such, they can show evidence for responsible and fair conduct of cultural heritage data, and fair (but also FAIR) research data management practices that are based on partnership with the holding institution.
Construction, Characterization, Estimation and Performance Analysis of Selection Generalized Nakagami Distributions with Environmental Applications

In this article, a selection of Nakagami distribution is investigated.Some properties of the model with some plots of the density function are illustrated.Additionally, weighted of the one-sided Gaussian distribution, Generalized Rayleigh distribution are discussed as a special case of Generalized Nakagami distribution.In addition, maximum likelihood estimators are investigated with numerical methods and are compared by four sub-models with a real wave height data set.Finally, a simulation study is presented for parameters.
Factors that influence the intention to use cryptocurrency among the public in Kuala Lumpur / Fatin Nursyakirah Halim

The purpose of this study was to determine the factors that influence the intention to use cryptocurrency among public in Kuala Lumpur. The independent variables consist of four factors including awareness, subjective norm, transaction processing and perceived behavioural control. Meanwhile the dependent variable of this study is intention to use cryptocurrency. A total of 79 usable questionnaires was keyed in and analysed by using SPSS software. Furthermore, this research has used purposive sampling to obtain accurate data from targeted respondents. All the data were collected for the purpose to create analysis of descriptive, reliability and regression analysis. In this study, findings show that there were three independent variables that have a significant and positive relationship towards intention to use cryptocurrency which are awareness, transaction processing and perceived behavioural control. From this study we can see, the finding is useful for body of knowledge, industry players and policy makers.
Calculating Confusion and Diffusion of Symmetric Cryptographic Algorithms

Sensor data management is a major component of the Internet of Things(IoT) environment.In this study, we provide a short overview through providing an analysis on wireless sensor networks and sensor databases.Second, we discuss concept of efficient sensor data transmission to cope with unstable sensor nodes and wireless communication failures.To enhance the energy-efficiency and stability of data transmission in this unstable wireless sensor network environment, a new sensor-aware dynamic transmission scheme is proposed.In detail, the classification method for sensoraware transmission mode was devised and the dynamic transmission method was applied to the unstable nodes.The proposed dynamic transmission management skills minimize battery waste and communication failures of unstable sensor nodes.Consequently, unnecessary communication costs and battery energy can be reduced, and overall energy balance can be maintained in the sensor data network.
DETERMINATION OF THE SOIL SOUNDING DEPTH FOR THE EARTHING RESISTANCE CALCULATION OF SUBSTATIONS 35 KV

Purpose. Determination of the minimum required sounding depth for calculation of the earthing resistance for substations with a voltage class of 35 kV. Methodology. For each ratio of electrical resistivity values of soil layers, earthing resistance was calculated with changing of the layers separation depth from 0.4 m to hmax, where hmax is the layers separation depth in a two-layer soil at which the earthing resistance value becomes the same as in a uniform soil. Results. In the experiments carried out, a family of curves was obtained that describes the effect of separation depth of soil layers for various combinations of soil electrical resistivities and geometric dimensions of the earthing arrangement. The accumulated statistical data for substations with a voltage class of 35 kV made it possible to determine the required sounding depth depending on the maximum size of the earthing arrangement and the probability of the relative resistivity falling into the corresponding range of values. An algorithm is proposed for determining the required investigation depth by Wenner method as part of the electromagnetic diagnostics of the earthing arrangement of existing substations with a voltage class of 35 kV. Originality. For the first time, a probabilistic relationship was established between the ratio of the electrical resistivity of soil layers, the size of the earthing arrangement, and the necessary depth investigation of the geological medium. As a result it has been proven that there are substations for which the required sounding depth does not exceed the maximum size of the earthing arrangement. Practical value. The use of the algorithm developed in this work allows increasing the accuracy of the earthing resistance calculation of electrical installations with voltages above 1 kV operating in a network with isolated neutral.
Blockchain Development for Increased Transparency and Novel Incentives Structures with Wearables in mHealth

Blockchain technologies are heavily used in concepts to disrupt monetary platforms or supply chain applications, while there are other potentially well-suited sectors. Individual, personal data like in the sector of wellbeing and health lifestyle is fragmented across multiple silos, and here, blockchains offer a real solution. The blockchain technology is able to increase transparency, provide traceability while keeping pseudonymity, and therefore, enables novel incentive concepts. Towards this end, we implement a prototype for adoption of medical standard information using the Ethereum blockchain on a WearOS device. We found that deploying and running blockchain smart contracts on a consumer smart watch is feasible. While proof of concept was shown for quantified health monitoring, vast developments pose a high technical barrier, with limited documentation available. Further identified obstacles relate to the multifarious, cross-platform means needed for integration into broader projects.
A survey of open-source speech recognition software for voice actuated control

Nowadays, speech recognition technologies are actively developing and find application in various fields, such as controlling a computer using voice, dictating texts, and human-computer interaction or communicating with a computer on an intellectual level.Non-contact and natural for human ways of interacting with a computer, based on automatic recognition and synthesis of speech, text, gesture and tactile information, as well as paralinguistic information, including non-verbal aspects of speech and text information, are especially relevant.Much attention is paid to creating an accessible environment for people with disabilities and disabilities.An important means of ensuring accessibility and improving the quality of life, social interaction, and integration into society for people with disabilities are computer facilities and specialized information systems.In this paper we presented a series of experiments and analyzed the opensource software for voice actuated control.Simon is a software for Internet surfing, mailing, managing multimedia applications that can be adapted to the needs of older people.To work with the acoustic model, we need to either have our own model or load it from the library.The speech recognition was evaluated using two criteria, they are WER and Latency.The analysis of the software for recognition of continuous speech showed that at present there is no universal system for recognizing continuous speech that would be capable of self-learning, would be speaker-independent, resistant to noise, and have a low error rate.The considered software solutions at the moment are not universal and accurate, the speech recognition error greatly depends on the presence of extraneous medium and high-frequency noise, as well as on the microphone quality.
2020 Market Analysis of Applied Nanotechnology Summit China

The global nanotechnology market was valued at $1,055.1 million in 2018, and is projected to reach $2,231.4 million by 2025, growing at a CAGR of 10.5% from 2020 to 2025. Nanoscience and nanotechnology are the study of nanoparticles and devices, which find their application across all the science fields such as chemical, bio-medical, mechanics, and material science among others. Nanotechnology market encompasses the production and application of physical, chemical, and biological systems and devices at scales ranging from individual atoms or molecules to around 100 nanometers.
NEURAL NETWORK FUNDAMENTAL DAN IMPLEMENTASI DALAM PEMROGRAMAN

Nowadays machine learning and deep learning are becoming a trend in the world of information system. They are actually is part of an artificial intelligence domain. However, so many people don’t understand that machine learning and deep learning are built using neural networks. Therefore, in order to understand how machine learning and deep learning works, we must understand the basic concept of the neural network first. In this article, the writer describes the basic theory, math function of a neural network, and the example of implementation into the java programming language. The writer hopes that this article may help to understand neural network which is the core of machine learning and deep learning.
An Empirical Study on Performance Improvement of Hospital Medication Delivery Systems Based on Feasibility Analysis

According to United Nations statistics, there were one billion older people in 2017, accounting for about 13% of the global population. It is estimated that by 2050, the elderly population will grow to 2.1 billion, accounting for about 21% of the total population. The rapid increase in the elderly population will impose a heavy financial burden on the country's medical services. The government is reviewing the important challenges facing its welfare system. One solution is to automate the healthcare system through the Internet of Things and network communications, thereby reducing staff costs and maximizing total revenue. Because the professional complexity of medical operations is more specific than other areas, this study proposes system integration strategies to improve drug delivery performance. Considering the economic benefits of the medical field, this study conducts an empirical study based on feasibility analysis. The resulting economic benefits promote interdisciplinary collaboration between medical teams and provide quality medical services.
A STUDY OF READINESS FOR USING SOCIAL MEDIA IN AGRICULTURAL EXTENSION IN ASSIUT GOVERNORATE

This research attempts generally to discuss the readiness for using social media in agricultural extension in Assiut governorate, and it endeavors particularly to reach the following aims: (1) Measuring readiness of the extension organization in Assiut governorate to start providing agricultural extension services using social media from the viewpoint of extension employees; (2) Exploring the willingness of farmers in some villages in Assiut governorate to obtain agricultural extension services using social media, and to identify the most significant determinants of the willingness to use social media; (3) Knowing about the respondents’ views about the advantages, disadvantages and suggestions of using social media in agricultural extension. The study was conducted on two groups of respondents who use at least one of social media tools; the first was comprised of 86 extension employees in Assiut governorate, and the second was a sample of 120 farmers selected from four villages in Assiut governorate. Data were collected using questionnaire form during the   period from November to December 2018. Frequencies, percentages, arithmetic mean, and stepwise multiple regression analysis were used for data presentation and analysis. The results indicated a decrease in the extension organization’s readiness for using social media from the viewpoint of extension employees, while farmers have a high willingness to use social media to obtain extension services. Therefore, it is necessary to use the recommendations of improving the extension organization’s reediness to use social media, in order to exploit the high willingness of farmers, and start using social media to provide extension services in Assiut governorate through implementing an initial initiative through farmers who use social media, and then the initiative can be expanded to include non-users through their family members who are using social media, taking into account the respondents’ suggestions for the successful use of social media in the provision of agricultural extension services.
Using Artificial Neural Networks to Derive Process Model Activity Labels from Process Descriptions

Recently, Artificial Neural Networks (ANN) have shown high potential in the area of Natural Language Processing (NLP). In the area of sentence compression, the application of ANNs has proven to outperform existing rule-based approaches. Nevertheless, these approaches require a decent amount of training data to achieve high accuracy. In this work, we aim at employing ANNs to derive process model labels from process descriptions. Since the amount of publicly available pairs of text and process model is scarce, we employ a transfer learning approach. While training the compression model on a large corpus consisting of sentence-compression pairs, we transfer the model to the problem of deriving label descriptions. We implement our approach and conduct an experimental evaluation using pairs of process descriptions and models. We found that our transfer learning model keeps high recall while losing performance on precision and compression rate.