Reviewerly/exHarmony huggingface dataset:
BLOCKCHAIN AND IOT INTEGRATED APPROACH FOR A TRUSTED AND SECURED PROCESS TO MANAGE THE TRANSPORTATION OF DANGEROUS GOODS

The domain of transport and supply chain of goods is todaystrongly impacted by the digital technologies similarly to thelogistic enterprises providing them. Due to their critical nature.Not only these services are required to be correct but atraceability of the end-to-end process of transportation hasto be provided. The inuence of cutting edge technologiessuch as the Internet of Things (IoT) and blockchain enablesa new level of transparency and real-time verication of theprocess of transport. The impact of the IoT attributes toimproving the quality of services in several domains so itdoes in transportation. The capacity of IoT devices to generatereal-time information is essential to monitor processand other daily activities in the domain of transport. In thearea of dangerous goods transportation, this is even morecritical since stakeholders of the supply chain need to shareand exchange information in a trustful manner. Sensitive informationabout the transportation process should veriedbefore shared as well as protected from any unauthorizedaccess and changes. For a trusted and transparent processof transport, the data captured by IoT devices to monitorthe transportation of goods, should remain consistent, reliableand with proved integrity properties. In this paper, wepresent a research that highlights how the potential of theblockchain and IoT technologies can be eciently integratedin order to secure information exchange in an end-to-endprocess of transport of dangerous goods (TDG). Firstly, weexamine the process of TDG from the perspective of stakeholdercollaboration i.e., information ow. Secondly, we proposea model that supports an end-to-end TDG based on thePermission to make digital or hard copies of all or part of this work for personal orclassroom use is granted without fee provided that copies are not made or distributedfor profit or commercial advantage and that copies bear this notice and the full citationon the first page. To copy otherwise, or republish, to post on servers or to redistributeto lists, requires prior specific permission and/or a fee.regulatory framework. Third, we integrate blockchain andIoT technologies for securing information sharing during theprocess of TDG. Hence, we show how the transparent providesthe righ level of abstractions to the process of TDG. Aproof of concept applying our approach has been developedand tested.
Container-Based Internet-of-Things Architecture Pattern: Kill Switch

Containers are a method of virtualization. Advantages of containers include increasing utilization of bare-metal resources, and adding security isolation properties to various types of systems. These advantages make containers well-suited for applicable Internet-of-Things devices. This paper defines and describes our ‘kill switch’ Internet-of-Things container architecture pattern, aimed at enforcing multiple modes of application functionality. To our knowledge, this is a new and novel pattern that could lead to further research in the area. An example implementation that modifies the Docker engine, and an implementation using a Go script demonstrate that implementing the kill switch is feasible and achieves desired functionality.
The Impact of Culture on Humorous Ads: An Abstract

Humor in advertising targets a very heterogeneous audience simultaneously on the local and national even international scale. While it is universally practiced, practices of humor are nevertheless extremely varied, and it use in advertising may require adaptation when communicating in different contexts (Alden et al. 1993).As advertising is strongly based on the culture of the country (Ozdemir and Hewett 2010), on tradition and on a specific mode of communication (Newman 2004; Tungate 2007), it can register strongly in this context which will impact the understanding and perception of the message it wants to convey and influence consumer behavior and purchasing decisions. (Palmatier et al. 2006). Considering this, some advertising campaigns would be totally impossible to export (De Wulf et al. 2001) while others might require some adaptation to suit different cultural contexts (Alden et al. 1993).The question of standardization and adaptation of advertising campaigns on the international scale has been the subject of extensive research (Schmid and Kotulla 2011). However, reviews of existing literature show doubt on the results of the previous research (Birnik and Bowman 2007). In the case of humorous ads, companies are advised to “standardize” in their international communication (Alden et al. 1993) and at the same time to “adapt” their strategies even locally on their national markets (Rutigliano 1986).Considering that the proportion of international advertisements using humorous appeals can reach up to 50% of TV advertising campaigns in US, while similar statistics can be observed in other countries and other types of communication (Millward Brown Brand report), and the huge and growing global advertising spending which represented $550 billion dollars in 2016 (McKinsey, Wilkofsky Gruen Associate: © Statista 2017), it appears essential to understand the stimulus of humor in ads tendency with a cross cultural comparison. The objective of this research is to understand the cultural differences in terms of humor in ads and the influence of culture in the consumer perception and behavior.
Research on Teaching Reform and Practice of Single Chip Microcomputer

In view of the common problems in the teaching of single-chip microcomputer in undergraduate colleges, the teaching mode of single-chip microcomputer course is driven by projects and based on competition is proposed, and the experimental training content is integrated into the teaching of single-chip microcomputer course, and the subject competition is used as the platform of single-chip microcomputer teaching, so as to cultivate the students' comprehensive design and application ability of single-chip microcomputer.
The Role Of Management Control System On Firm Performance

The aim of the study is to investigate the extent to which the use of management control system areinteractive and diagnosticallyenhance firm performance both environmental and customer performance by mediating good corporate governance.  In order to generate the aim of the study, we conduct a survey study on one of the country’s leading state-owned industries managers. We analyze a 39 usable data using structural equation model, in particularly SmartPLS. The result of the study found that Interactive control use has a direct effect on environment performance and indirect effect through good corporate government that can lead to the improvement of environmental performance.  However diagnostic control use only has a positive effect on environment performance. This study implies that interactive and diagnostic control uses endorse the improvement of environment performance.
GAMESTORMING AS A TOOL IN MAKING DECISIONS BY BUSINESS

The article substantiates the expediency of using gamestorming by Russian business, which allows to improve the communication skills of employees, generate new, build a strategy for the development of a commercial organization. Gamestorming technique is simple and available for use. The authors substantiate the use of the most convenient tool gamestorming by managers of a commercial organization. The conclusion about the need for business cooperation between higher education and business was made. As a result, an effective option of public-private partnership can be obtained, pursuing the formation of an innovative model of the economy.
POTENTIAL BENEFITS AND OBSTACLES OF CLOUD COMPUTING IMPLEMENTATION IN HIGHER EDUCATION INSTITUTIONS(HEIs): A DELPHI STUDY

In the education sector, cloud computing is an apparent innovation to guarantee the accessibility and sharing of assets through virtualization. This research aims to identify the potential benefits and obstacles of cloud computing implementation for the Learning Management System (CC-L) in Malaysia Higher Education Institutions (HEIs). Although the literature has discussed the benefits and obstacles caused by the implementation of cloud computing, the analysis needs to be done in the perspective and context of the relevant research. Therefore, the Delphi survey technique used to identify the potential benefits and obstacles among experts from HEIs and cloud service vendors. This finding expected to drive on how to overcome their limited resources to address the obstacles identified in cloud computing implementation success. Hence, the gap in the literature addresses in this study by focusing on different perspectives and countries. The result indicates the agreements of eight benefits and seven obstacles recommended that belief could support a decision of cloud computing implementation.
The Web of Data is partially unavailable, so what?

More and more knowledge graphs are becoming available on the Web, many of them accessible via queryable interfaces, such as SPARQL endpoints. These knowledge graphs are often linked to each other and in doing so form the so-called Web of Data. The great strength and potential of exploiting these links is that we can obtain answers for queries that would not yield any results over the knowledge graphs if considered individually. However, one of the fundamental problems is that Web-accessible knowledge graphs are not always available when we would like to access them. This means that the exact same query issued at different points in time might have different results or, in the worst case, no results if one of the knowledge graphs that are essential to answer the query is (temporarily) not available. Often this is caused by crashes of the server hosting the knowledge graph - a problem that is deeply rooted within the architecture of the current Web of Data, i.e., relying on data providers to keep interfaces and knowledge graphs available and accessible. Building upon the basics of federated query processing over knowledge graphs, this talk will discuss challenges as well as strategies on how to overcome the unavailability problem and keep the data available and queryable.
Querying Data Using SQL

Finally! We have our data loaded and ready in Databricks – multiple exciting datasets to investigate. Now it’s time to start playing around with them. We’ll start by using one of the oldest data languages around.
Robust Detection of Adaptive Spammers by Nash Reinforcement Learning

Online reviews provide product evaluations for customers to make decisions. Unfortunately, the evaluations can be manipulated using fake reviews (spams) by professional spammers, who have learned increasingly insidious and powerful spamming strategies by adapting to the deployed detectors. Spamming strategies are hard to capture, as they can be varying quickly along time, different across spammers and target products, and more critically, remained unknown in most cases. Furthermore, most existing detectors focus on detection accuracy, which is not well-aligned with the goal of maintaining the trustworthiness of product evaluations. To address the challenges, we formulate a minimax game where the spammers and spam detectors compete with each other on their practical goals that are not solely based on detection accuracy. Nash equilibria of the game lead to stable detectors that are agnostic to any mixed detection strategies. However, the game has no closed-form solution and is not differentiable to admit the typical gradient-based algorithms. We turn the game into two dependent Markov Decision Processes (MDPs) to allow efficient stochastic optimization based on multi-armed bandit and policy gradient. We experiment on three large review datasets using various state-of-the-art spamming and detection strategies and show that the optimization algorithm can reliably find an equilibrial detector that can robustly and effectively prevent spammers with any mixed spamming strategies from attaining their practical goal. Our code is available at this https URL.
A música na Ciência da Informação: uma análise de domínio da temática no Brasil no período de 1972 a 2018

EnglishThe objective was to analyze the Brazilian scientific production on music in the field of Information Science, identifying as the object music, has been gaining space in interdisciplinary research, allowing the visualization of such object as a domain in Information Science (CI). A descriptive study, rooted in domain analysis, presents as a corpus 124 academic productions (journal articles, articles from the annals of events, dissertations and theses), published from 1974 to 2018. It was observed that the predominant category of analysis is that dealing with music under a documental bias, focused on studies of organization of musical collections with respect to the processes of cataloguing, classification and indexation of these information resources. However, it is observed the emergence of other perspectives of analysis in works that have directed their research on sociocultural aspects about the object, especially with regard to music as an informational resource of memory and social representation. portuguesObjetivou-se analisar a producao cientifica brasileira sobre musica no âmbito da Ciencia da Informacao, identificando como o objeto “musica”, vem auferindo espaco em pesquisas interdisciplinares, permitindo a visualizacao de tal objeto enquanto dominio na Ciencia da Informacao (CI). Estudo de natureza descritivo, arraigada sob analise de dominio, apresenta como corpus 124 producoes academicas (artigos de periodicos, artigos provenientes de anais de eventos, dissertacoes e teses), publicados no periodo de 1974 a 2018. Observou-se que a categoria de analise predominante e a que trata a musica sob um vies documental, voltado a estudos de organizacao de acervos musicais no que tange aos processos de catalogacao, classificacao e indexacao desses recursos informacionais. Porem, observa-se a emergencia de outras perspectivas de analise em trabalhos que tem direcionado suas pesquisas sobre aspectos socioculturais acerca do objeto, sobretudo no que se refere a musica enquanto recurso informacional de memoria e representacao social.
Level of Metacognition Development of University Students in the Process of Studying of Psychological and Pedagogical Disciplines

The article is devoted to studying the level of metacognition development among university students. The results of thesis research of the level of metacognition development of university students in the process of psychological and pedagogical disciplines study are presented.Theoretical justification of the metacognition notion is given in this work. The analysis of domestic and foreign sources for metacognition researches is conducted. The level of metacognition development among students of specialty Education was analyzed and the results of the research were interpreted. Metacognitive characteristics of the personality, metacognitive behaviour, as well as types of reflection and metacognitive inclusion and awareness in educational activities are practically considered.
Real-Time 2D Avatar Lip Syncing for the on Demand Interactive Chatbots

Avatar lip syncing plays a vital role in making a speech animation realistic. There have been a number of studies in this domain due to its various applications in fields like animation, gaming and the recent use in the education and the business domains for interactive chat-bots. In this paper, the authors pre- sent a method to achieve avatar lip sync in real-time where, when a text is entered, the avatar utters it out with pauses corresponding to the punctuation. This thereby creates a feeling that the avatar is actually speaking. Most of the previous works involve the usage of 3D avatars and a facial mesh, and locating the positions of motion as the speech is generated. This involves key-frame positioning during the time lapse of the speech. This may involve some skilled animators and may make some naive developers anxious about the idea of usage of lip syncing in their possibly basic projects. The goal of this work is to provide a similar experience of lip sync with a 2D image of the 3D model. In this work, the authors identify words in the text entered, extract phonemes and do a standard mapping of the phoneme to viseme. Thus, they overlay the images of the avatar, corresponding to the visemes to create an illusion of lip sync with the speech.
Model-Free Robust Reinforcement Learning with Linear Function Approximation.

This paper addresses the problem of model-free reinforcement learning for Robust Markov Decision Process (RMDP) with large state spaces. The goal of the RMDPs framework is to find a policy that is robust against the parameter uncertainties due to the mismatch between the simulator model and real-world settings. We first propose Robust Least Squares Policy Evaluation algorithm, which is a multi-step online model-free learning algorithm for policy evaluation. We prove the convergence of this algorithm using stochastic approximation techniques. We then propose Robust Least Squares Policy Iteration (RLSPI) algorithm for learning the optimal robust policy. We also give a general weighted Euclidean norm bound on the error (closeness to optimality) of the resulting policy. Finally, we demonstrate the performance of our RLSPI algorithm on some benchmark problems from OpenAI Gym.
News Headline Corpus Construction and High Frequency Word Extraction

It is a fascinating research topic to use the high-frequency words in the news headlines to compare the cultural values of China and the United States. However, the amount of information on various types of news websites is huge on the Internet. If no adopting any intelligent tools it is difficult to obtain information that meets certain conditions (such as specific content for a specific time period) and conduct specialized research. Therefore, this paper proposes a complete solution. First it designs a targeted crawler tool for news headline crawling. The tool can be flexibly set according to the user’s needs, and is targeted to specific content such as specific headlines or Web content that meets certain conditions, with the advantages of fast crawling speed, low computing and network resource overhead. Then, by using the crawler tool to achieve a quick crawling of the news headlines of the Xinhuanet (Chinese) and VOA (English) websites for a specific time period, a news headline corpus is constructed for comparison research. Based on the improved TF-IDF algorithm, high-frequency word is extracted in the headline corpus, which provides good data preparation for the study of Sino-US cultural value orientation differences.
The Application Status and Enlightenment of Smart Phones in College Classroom Learning

With the continuous advancement of Internet technology, terminal devices represented by mobile phones have begun to deeply integrate into people’s lives. Mobile phones affect people’s lives, learning and value orientation. According to the latest issue of the “Statistical Report on the Development of China’s Internet Network”, the number of Chinese netizens reached 802 million. Among them, the number of mobile Internet users has reached 788 million, and the proportion of Internet users accessing the Internet through mobile phones is as high as 98.3%. Young students already account for a very high proportion of the total number of netizens. With the rapid development of the Internet, the rapid update of knowledge has made smartphones an indispensable tool for college students’ daily life and learning. This paper uses questionnaires to obtain the current situation of college students using mobile phone learning in daily classroom learning, and through the analysis of the data, it provides some inspiration for better use of mobile phone learning in course learning, and better integrates mobile phone and course teaching. Provide a guiding strategy.
Heterogeneous Island Models and Their Application to Recommender Systems and Electric Vehicle Charging

In this paper we describe a general framework for parallel optimization based on the island model of evolutionary algorithms. The framework runs a number of optimization methods in parallel with periodic communication. In this way, it essentially creates a parallel ensemble of optimization methods. At the same time, the system contains a planner that decides which of the available optimization methods should be used to solve the given optimization problem and changes the distribution of such methods during the run of the optimization. Thus, the system effectively solves the problem of online parallel portfolio selection. The proposed system is evaluated in a number of common benchmarks with various problem encodings as well as in two real-life problems — the optimization in recommender systems and the training of neural networks for the control of electric vehicle charging.
Mobile Technology Facilitated Chemistry Learning in School: A Systematic Review from 2010 to 2019

Over the last ten years, mobile learning issue in chemical education have been discussed around the world. However, the trend of applying mobile technology in chemical education still lack systematic analysis. In this study, a meta review of the studies published in academic journals, indexed by Scopus, from 2010 to 2019 was conducted to analyze nationalities, authors, journals, learning strategies, and research methods. The results revealed that the use of mobile technologies in chemical education have been increased in the past decade. It was also found that mostly mobile technologies have been applied in scientific experiment for chemistry learning as a learning tool. In addition, mobile learning strategies have seldom been adopted in inquiry learning, contest, and collaborative learning. In contrast, it was found that the number of studies using a system development has increased in recent years. Besides, most studies reported the process of using mobile devices in a laboratory, while students’ psychomotor domain were rarely analyzed.
Set, exchange, measure, repeat

Quantum InformationSuccessful protocols for quantum information processing and quantum computation depend on the reliable storage and manipulation of the quantum state of a qubit. Qubits, however, are prone to errors because complete isolation from the environment is not possible. Methods for correcting these errors must also contend with the fact that direct measurement of a qubit destroys it. Xue et al. describe a repetitive quantum nondemolition method on a two-qubit system in which the state of the main qubit is mapped onto a second qubit that acts as an ancilla. Repeated measurement of the ancilla qubit allows the main qubit to be maintained and read out with higher fidelity. Such a protocol provides a route to robust quantum information processing in solid-state systems.Phys. Rev. X 10 , 021006 (2020).
Labor Intensity Evaluation Technique in Software Development Process Based on Neural Networks

Software development process is actively studied by experts from different spheres of science and different view points. However the degree of success of projects in the development of software intensive systems (Software Intensive Systems, SIS) has changed insignificantly, remaining at the level of 50% inconsistency with the initial requirements (finance, time and functionality) for medium-sized projects. The annual financial losses in the world because of the total failures are counted by hundreds of billions of dollars. Its high complexity leads to constant mistakes in labor intensity evaluation, and even new agile development paradigm does not solve this problem. In this paper an approach to retrospective labor intensity evaluation in software development process based on neural networks is proposed. This technique provides impersonal expertise of program code developed during the sprint in agile paradigm. Experiments performed on the real life software project show the effectiveness of proposed technique.