Reviewerly/exHarmony huggingface dataset:
PERANCANGAN APLIKASI PEMESANAN CATERING BERBASIS MOBILE ANDROID

Ordering catering is an activity undertaken by customers to buy products in the form of food packages. In Cimahi Catering catering ordering process is done by customers by coming directly to the location or calling to Cimahi Catering. Based on interviews with the authors related parties, in the process of ordering catering there are some customers who complain about the order process is due to take time, energy and more costs. In the case of recording data ordering was deemed less effective because the data is still conventional. This is at risk of logging errors. As a solution of these problems the authors build an Application Ordering Catering Based Android Mobile to assist in the process of ordering catering by customers and the management of reservation data catering by the Cimahi Catering. Research methodology used is Extreme Programming method. In making this application the author uses android programming base and MySQL as the data storage. This application is made to efficiently time, effort and produce accurate information. The results of testing the built application has a performance that suits the needs of the user. Based on the results of User Acceptance Test get a positive response with 85% percentage. Keyword: Android, application, catering, mobile, ordering, uat
Development and Validation of Digital Literacy Competency through the Elementary School and Middle School Physical Education Classes

The purpose of this study was to develop and validate the digital literacy competency through the physical education classes. To accomplish this purpose, 300 students from middle schools in seoul and gyeonggi area were chosen as subjects for this study. To verify internal validity, preliminary survey given out to 295 middle school students, descriptive statistics, reliability analysis, factor analysis and confirmatory factor analysis were executed. The principal component analysis reduced the students’ responses to a 5-dimensional construct: information organization ability, comprehensive thinking ability, self learning, cooperative learning, device capability. The result of confirmatory factor analysis was shown as a x²=1196.556, GFI=.898, NFI=.908, CFI=.932, RMSEA=.054, RMR=.076. The result of this study, the digital literacy competency through physical education classes scale was shown as a validation and reliability.
Factors in the Portability of Tokenized Assets on Distributed Ledgers

The tokenization of assets deployed to distributed ledger technology is increasingly cited to revolutionize financial services by allowing traditionally illiquid assets to be bought and sold on primary and secondary markets increasing asset liquidity, transparency and reducing transaction completion time. To realize these benefits it is important the token is transferrable, that is, portable from one distributed ledger to another. In this paper we survey current interoperability architectures and smart contract languages, identifying factors affecting the portability of tokenized assets. We propose a portability maturity model that can be used to help assess the current state of technology and supporting market infrastructure.
A ‘Crypto Tax Assessment Index (C-TAI)’ for oil and gas industry

In addition to conventional taxes, host oil and gas producing countries impose a "crypto tax", including sustainability-related taxes similar to environmental taxes and social sphere development costs. These taxes aim to maximize government taxes which are collected to ensure operational efficiency and sustainable development. In contrast, multinational oil companies look beyond conventional taxes by performing a thorough assessment of "crypto tax" while deciding investment locations. Extractive industry taxation literature is limited in offering a scrupulous index. In particular, how a robust index is constructed and tested for these quasi-taxes. Therefore, the issues surrounding the construction and testing of Crypto Tax Assessment Index (C-TAI) underpins the relevance and motivations of this study. Specifically, this study aims to examine the construction and testing of a C-TAI in guiding policymakers and investors concerning crypto taxes. A properly constructed Index would enable governments to undertake environmental and sustainability assessment, knowing that the index suited their particular petroleum fiscal policy. The Malaysian marginal oil field sector was established to test internal and external validities and model fit indices of the C-TAI through surveying the opinions of experts in this field. Taking these views and opinions into consideration, in constructing an appropriate C-TAI, researchers can use the index address possible questions relating to the effects of crypto taxes on individual oil and gas projects or the overall petroleum sector of a country. For instance, how useful the constructed C-TAI could be in the examination the effect of crypto taxes on the profitability of a mature basin? How does the constructed C-TAI could be used in relation to the effect of crypto taxes on the profitability of marginal oil fields and the investment climate of a frontier petroleum basin? In answering these questions, it is anticipated that a properly constructed and robust C-TAI would help to guide policymakers and investors in understanding the importance of a C-TAI for crypto taxes, including sustainable developments.
Stochastic Model of the Simple Cyber Kill Chain: Cyber Attack Process as a Regenerative Process

The proposed model extends the Markov model of the simple cyber kill chain already published in the literature by assumption of any continuous probability distribution of adversaries’ and defenders’ activity time. The description of the chain is based on the cyber kill chain concept initially introduced by Lockheed Martin’s researchers as the intrusion kill chain. The model includes the assumption of repeatability of cyber-attacks. On this basis, the stationary probabilities of staying of the attack process in individual phases were determined.
A Study in Bitcoin Volatility through Economic Factors

As a result of the United States (U.S) -China trade conflict, the recent instability of the stock market has led many people to invest in Bitcoin, a commodity that many previous studies have interpreted as a safe asset. However, recent Bitcoin market price fluctuations suggest that the asset’s stability stems from speculative purchasing trends. Therefore, classifying the characteristics of Bitcoin assets can be an important reference point in analyzing relevant accounting information. To determine whether Bitcoin is a safe asset, this study analyzed the correlation between Bitcoin and economic indicators to verify whether gold and Bitcoin responded similarly in time series analyses. These show that the regression explanatory power between the price of gold and bitcoin is low, thus no relation between the two assets could be drawn. Additionally, the Granger causality analyses of six individual economic variables and Bitcoin did not establish any notable causality. This can be interpreted that short-term price fluctuations have a significant impact on the nature of Bitcoin as an asset.
Design of Dance Game Using Wearable Device for Older Adults

South Korea is heading for a super-aged society, and this phenomenon of compressed aging will lead to a variety of complex and problems for older adults. In this paper, we propose dancing game content targeting older adults to improve their health and quality of life in the era of aging society. In order to design dance game for older adults, we examined the previous studies focusing on health maintenance and activity improvement through the existing exercise. Also, the study investigated the previous research findings about the physical exercise game for older adults, and the dance game currently being served. Exercise is a necessary action to ensure a healthy and independent quality of life for mental, physical and societal reasons. It is important to examine the physical, cognitive, and mental changes in the aging process and propose an exercise program based on the intensity, frequency, and time of the dance. In this study, we designed a dancing game for older adults who can exercise safely and happily while checking the heart rate using a wearable device such as Gear S3 which can be worn on the wrist. The proposed dance game is a combination of exercise, music, and gaming so that the study expect that it will attract and encourage older adults to exercise safely and consistently.
EdgeSum: Edge-Based Video Summarization with Dash Cams

The following topics are dealt with: cloud computing; Internet of Things; learning (artificial intelligence); virtual machines; mobile computing; security of data; resource allocation; scheduling; software engineering; regression analysis.
[Determination of Heavy Metal Geochemical Baseline Values and Its Accumulation in Soils of the Luanhe River Basin, Chengde].

A total of 351 surface soil samples (0-20 cm) were collected from the Luanhe River Basin in Chengde City (a typical area of concentrated mineral resources) and analyzed for 12 heavy metals (Cu, Ni, Cd, Cr, Pb, Zn, Hg, V, Ti, Mn, As, and Co). The geochemical baseline values of the heavy metals were determined using the reference element method and the cumulative frequency curve method. Furthermore, the spatial structure and distribution characteristics of the heavy metals were assessed based on PCA and geostatistical analysis. The accumulation of heavy metal pollution in different types of soil and in association with different land use patterns was also evaluated using a geological accumulative index. The results showed that the geochemical baseline values of V, Ti, Cd, Pb, Mn, and Co in the surface soils of the Luanhe River Basin were higher than their background values for Hebei Province. In contrast, the geochemical baseline values of As, Zn, Cr, Cu, Ni, and Hg were lower than their background values. The average accumulation index of the surface soils followed the order of Cd > Pb > Cu > Ti > Mn > Zn > Cr > Ni > Co > V > Hg > As. More than 80% of the soil samples were categorized as having no accumulation or moderate accumulation of Pb, Ti, V, As, and Co, while over 70% of the soil samples were categorized as having no accumulation or moderate accumulation of Hg, Mn, Ni, Cu, As, Cd, and Cr. With respect to different soil types, the average accumulation index of heavy metals followed the order of fluvo-aquic soil>cinnamon soil>brown soil. With respect to land use types, the accumulation index of heavy metals followed the order of industrial and mining land > shrub forest land > agricultural land > woodland and grassland. The accumulation of Pb and Cd in the surface soils of agricultural land was relatively high in comparison to the other elements, with 27.69% and 25.38% of the samples being above the moderate accumulation level, respectively. The iron group elements Ti, V, Co, Ni, and Cr are likely to derive from naturally high geological background sources, while the spatial patterns of Cd, Pb, Zn, Mn, Cu, and As were associated with the combination of parent material and anthropogenic inputs. The accumulation of Hg was mainly influenced by human activities.
DIGITAL DOCUMENT: AN OLD ENTITY IN A NEW PHENOMENON

The article deals with the problem of the essence of the digital document as a social phenomenon. The paper analyses the standard established identification characteristics of the digital document, as well as the ideas about its essential characteristics in Russian and foreign science. The author expresses her opinion on the problem and presents the proof, founded on the study of a digital document on the basis of philosophical, social, and activity-oriented approaches and on the theory of social self-organization, which forms the scientific novelty of the article. The author comes to the conclusion that a digital document appeared as a result of the new technological information revolution, just like written and typewritten (man-made) documents appeared as a result of the agricultural and industrial revolutions. Therefore, the essence and the social role of a digital document remain unchanged. The identification feature of a digital document, as well as of a document in analogue format, is its form (structure), including the content and the metadata. Regardless of the form of representation, in analogue format or digital, the document retains its essential properties of an evidentiary and legal force, and the essential functions – information and instrumental, which allow a digital document to serve as an information resource and a social tool. In understanding the essence of a digital document, it is important to take into account not only its relationship with the information system in which its entire life cycle takes place, but also its social role as an instrument of socially and legally significant action and social selforganization.
Shaping the behaviour of feedback instruments with complexity-controlled gain dynamics

Feedback instruments offer radical new ways of engaging with instrument design and musicianship. They are defined by recurrent circulation of signals through the instrument, which give the instrument ‘a life of its own’ and a ’stimulating uncontrollability’. Arguably, the most interesting musical behaviour in these instruments happens when their dynamic complexity is maximised, without falling into saturating feedback. It is often challenging to keep the instrument in this zone; this research looks at algorithmic ways to manage the behaviour of feedback loops in order to make feedback instruments more playable and musical; to expand and maintain the ‘sweet spot’. We propose a solution that manages gain dynamics based on measurement of complexity, using a realtime implementation of the Effort to Compress algorithm. The system was evaluated with four musicians, each of whom have different variations of string-based feedback instruments, following an autobiographical design approach. Qualitative feedback was gathered, showing that the system was successful in modifying the behaviour of these instruments to allow easier access to edge transition zones, sometimes at the expense of losing some of the more compelling dynamics of the instruments. The basic efficacy of the system is evidenced by descriptive audio analysis. This paper is accompanied by a dataset of sounds collected during the study, and the open source software that was written to support the research.
A Multilayer Deep Learning Framework for Auto-content Tagging

With the rapid and recent development of Internet of things (IoT), Bigdata, the most fundamental challenge is to explore the large volume of data from heterogeneous data sources (logs, audio, video, reports, news, social media, etc.). The tools and techniques that are being used in successful transforming of structured data into business intelligence simply do not work when it comes to unstructured data. An estimated 80% of data held by firms today are unstructured. We have powerful computations tools such as graphics processor units (GPUs) for complex calculations and Hadoop, spark for Bigdata management still technology is lacking in complete utilization of available data. Deep learning is a powerful tool to resolve the issues related to data, such as automatic extraction of complex data and representation of large volume unsupervised and uncategorized raw data. But extracted data do not have any standard format. In the survey of Bigdata mining system and IoT systems, it has been found that a layer is needed in Bigdata mining framework that can work on structured, unstructured and semi-structured data and can integrate the complete raw data. The proposed framework is a multilayer deep learning model that performed the clustering of unstructured huge text data followed by classification layer, CNN, to extract features and classify the raw data clusters in parallel manner. Conversion of unstructured data in standard format by automates content tagging helps decision-making systems to easily identify the related data and increase the data utilization.
A Comparative Study of Model-Free Reinforcement Learning Approaches

This study explores and compares three model-free learning methods, namely, deep Q-networks (DQN), dueling deep Q-networks (DDQN) and state-action-reward-state-action (SARSA), while detailing the mathematical principles behind each method. These methods were chosen as to bring out the contrast between off-policy (DQN) and on-policy (SARSA) learners. The DDQN method was included as it is a modification of DQN. The results of these methods and their performance on the classic problem, CartPole were compared. Post-training, testing results for each of the models were as follows: DQN obtained an average per episode reward of 496.36; its variant and improvement, DDQN obtained a perfect score of 500 and SARSA obtained a score of 438.28. To conclude, the theoretical inferences were decisively reaffirmed with observations based on descriptive plots of training and testing results.
Survey on Fuzzy Associative Classifications Techniques and Their Performance Evaluation with Different Fuzzy Clustering Techniques Over Big Data

In the current trend of data science research lot of works concentrated over scaling conventional data classification algorithms towards handling massive datasets referred as Big data. The standard of classification algorithms evaluated based on their accuracy, interpretability and intuitiveness. It is well proved in studies that the using fuzzy generalization in classification will improves the above three factors of classification model. Considering the importance of fuzzy associative classification models this article revise their inception to current extension to MapReduce frameworks. The primary challenge in such techniques is in deciding which clustering technique is well suited for extracting fuzzy generalization parameters. Considering that an experimental study conducted on various clustering algorithms extended to MapReduce framework and their performance evaluated based on effectiveness of the generated fuzzy parameters with respect to classification accuracy.
Hidden multipartite entanglement in Gaussian cluster states

Gaussian continuous-variable cluster states are a unique quantum information resource as they currently scale up experimentally to much larger sizes than any qubit platform. We derive the first general criterion for a pure Gaussian state not to be expressible as a canonical cluster state, and show that such Gaussian states must then display hidden entanglement. This applies to experimentally relevant deviations from Gaussian cluster states, such as variations of the squeezing parameter from mode to mode, which cannot be captured by the infinite squeezing limit.
Fast measurement partitioning algorithm for multiple extended target tracking

For tracking of multiple extended targets with unknown and varying target number, the measurements partitioning is indispensable and plays an important role in achieving good performance. However, the number of possible partitions grows very fast with the increasing of total number of measurements, which causes heavy computational burden. Thus this Letter proposes a fast measurement partitioning algorithm, in which the target predictive information is explicitly considered and used to determine the clustering centres for measurement partitioning. To guarantee its robustness, the target predictions are further modified when the target number is overestimated. This flexible strategy reduces the dependence on original predictive information and significantly improves the accuracy of partitioning results. Besides, the proposed algorithm greatly reduces the partition number by fully considering possible changes of the number of newborn targets and spawned targets. It not only eliminates unreasonable and redundant measurement partitions for tracking performance improvement, but also fits well with the tracking of newborn targets and spawned targets. Simulation results verify the benefit of what the authors proposed.
[Cd Accumulation and Risk Assessment for Arable Soils in the Karst Region of Northern Luodian, Guizhou].

Background levels of cadmium (Cd) in carbonate rock areas of Guizhou Province are high. In order to understand the characteristics of Cd in arable soils in these karst areas, the soils in the northern county of Luodian were selected as the study object. By comparing soils in non-karst areas, the distribution characteristics of soil Cd were studied by combining geostatistical analysis and GIS, and the potential ecological risk index and health risk were used to evaluate the potential level of risk to adults and children. The results show that the arable soil Cd content in this karst area is significantly higher than that in non-karst areas (P<0.05), with a geometric mean of 1.33mg·kg-1 and 0.27 mg·kg-1, respectively. In comparison, the geometric mean of soil Cd content in forested land in the same areas is 1.57mg·kg-1 and 0.22 mg·kg-1, respectively. Based on "soil pollution risk control standards", the Cd content of 90% and 22% of arable soil samples was higher than the risk screening value and the risk control value for karst and non-karst areas, respectively. The areas with medium and high Cd values were mainly distributed in the karst areas, presenting medium to strong ecological risks and extremely strong ecological risks, respectively. In contrast, the areas with the lowest Cd concentrations were distributed in the non-karst areas of Jiaoyan, presenting low potential ecological risk. The health risk assessment showed that the non-carcinogenic risk and carcinogenic risk of the three exposure pathways for adults and children in the karst areas are significantly higher than those in the non-karst areas, but the Cd content in the soil does not present non-carcinogenic and carcinogenic risks to local residents. Overall, the problem of Cd pollution in arable soils in the karst area of northern Luodian, Guizhou, is prominent. Therefore, the study of the risks posed by Cd pollution to the soil-plant-human system should be strengthened, and appropriate measures should be taken to prevent and control Cd pollution in the areas at risk.
Information Technology and the Experience of Creating a Database on the History of the 20th Century in the Personalities

This article is devoted to the description of the experience of creating a database in which more than 36 thousand people are collected. Originally developed for informational purposes, this database and the Internet resource created on its basis have been recognized not only in Russia, but also abroad. On the basis of the collected data on historical personalities, numerous scientific historical studies were conducted. These studies were made possible thanks to a well-designed data structure and clarity of the presentation of the material. Gained invaluable experience working with personal information sources. Implemented mechanisms for displaying geographic data of personalities using the Open street map, Google map and Yandex map services. Services have been developed for creating multimedia collections based on personal data, a service for preparing publications of personal reference books. The article describes the prospects for the development of historical database tools to simplify the conduct of historical research, namely: identifying hidden links between database objects, creating multidimensional data representations, and applying retrospective geocoding methods.