Reviewerly/exHarmony huggingface dataset:
Regulating smart contracts: An efficient integration approach

A smart contract is a digital protocol (software code) that enables automated monitoring and executing contract’s provisions without the need for intermediaries. Blockchain technology allows implementing smart contracts through a distributed ledger, but has no reliable way of enforcing legal rules. For example, in networks such as Bitcoin, it is possible to engage in illegal activities such as money laundering and dealing in weapons. In addition, it is impossible to enforce and audit legal costs such as taxes and duties. This research has devised a plan that allows official institutions to enforce the rules and audits efficiently during automatic execution process of smart contracts. This article discusses five important challenges in applying legal rules to Blockchain: the accreditation to the contracting parties’ and the goods’ nature, collecting legal costs, enforcing territorial laws and auditing. We present “Hyper Smart Contract”, a method for regulating Blockchain-based smart contracts and assess the limitations of the current generation of smart contracts on Ethereum to ensure a proper implementation of this plan. The performance of proposed method evaluated on a motivation application.
An Overview on Deep Learning in Image Super-Resolution for Advanced Machine Vision System

Image spatial resolution means the ability of the sensor to measure the smallest pixel size object.It focuses on recovering a less resolution (LR) image to high resolution (HR) image observations.Due to the exceptional research and application realizations of machine learning at home and abroad, the implementation effect of machine learning algorithms in image super resolution will be enormous.For this, deep learning has become a powerful learning tool for computer vision works.Furthermore, the performance of image super-resolution methods is showing significantly improved by using deep learning.In this paper, the basic image super-resolution methods based on deep learning have been discussed in detail along with the latest applications using super-resolution techniques.In addition, the current open issues and challenges for future research work are discussed.Finally, the main application areas of image superresolution based on deep learning domain are presented.
K 대학 치기공학과 재학생의 전공몰입이 학업 중도포기에 미치는 영향

Purpose: This experiment aims to provide the fundamental resources in developing a programme intended to prevent students from dropping out of their academics by promoting students to develop an optimistic psychological state, through analysis of the factors that influence students’ commitment to their major. Methods: A self-administered questionnaire was conducted from 19th of November of the year 2018, till 1st of December of the same year, with dental technology students located in W city as the subject. 261(93.2%) of the participants’ responses were used for the final analysis. Results: A negative association between factors of commitment to major and factors of academic dropout decision were portrayed to be of statistical significance (p<.01), and factors of commitment to major that influence dropping out of their academics were shown to be that of ‘autotelic experience’ (p<.001) with a negative ( - ) relationship, and ‘change in a sense of time’ (p<.01) with a positive ( + ) relationship of statistical significance, while the explanatory power of the model was shown to be 33.6%. Conclusion: In order to prevent dental technology students from dropping out of their academics, following their entrance, To achieve this, the department must consider the implementation of, aside from subject matters of the major, other various extra-curricular programmes, and programmes in which the supervisor is consistently providing consultations that are tailored to each individual student.
Virtual learning in qualitative research in graduate students

The purpose of the research is to carry out the analysis of the virtual learning process of qualitative research in postgraduate university students during the health emergency. The methodology used is of a socio-critical paradigm, of a multi-case study, at an exploratory level. The population was made up of doctoral students in education and public management and governance from Lima universities. The instruments used were observable products of learning management, in-depth interviews, both with experts in qualitative research, students and teachers. The research allowed an approximation to reality with the use of the various mechanisms that ICT, despite their incipient dominance, both in the data collection and in the analyzes carried out, showing that connectivism does not distort learning or learning. investigation.
Forms in Space. AR Experiences for Geometries of Architectural Form

Learning through the direct experimentation of models, in their variety of manifestations and hybridizations that we know today, is undoubtedly a very powerful aid in the acquisition of knowledge.Specifically on architectural form, this aid is even more important, because it helps not only to understand the form of existing architecture, but even more to imagine and design new ones.The research here presented, focusing on this double objective, cognitive and creative, proposes and experiments new ways of integrating and interacting with heterogeneous models -both physical and virtual -conceived for a scenario of musealization of the architectural form.A place where the user interacts and experiences the properties and peculiarities of form, in perceptive continuity between real and virtual space.
The PPSI Peer Social Conversation Protocol

The “Social Conversation” protocol was developed through Dr. Ofira Rajwan Ben-Shlomo’s doctoral dissertation under the supervision of Prof. Nirit Bauminger-Zviely.
Quality of Experience Measurement for Video Streaming Based On Adaptive Neural Fuzzy Inference System

Technological development in recent years leads to increase the access speed in the networks that allow a huge number of users watching videos online. Video streaming is one of the most popular applications in networking systems. Quality of Experience (QoE) measurement for transmitted video streaming may deal with data transmission problems such as packet loss and delay. This may affect video quality and leads to time consuming. We have developed an objective video quality measurement algorithm that uses different features, which affect video quality. The proposed algorithm has been estimated the subjective video quality with suitable accuracy. In this work, a video QoE estimation metric for video streaming services is presented where the proposed metric does not require information on the original video. This work predicts QoE of videos by extracting features. Two types of features have been used, pixel-based features and network-based features. These features have been used to train an Adaptive Neural Fuzzy Inference System (ANFIS) to estimate the video QoE.
Pengembangan digital library dengan pendekatan UX

In 2015 Yanki Pranata has developed a digital library prototype. This prototype has a feature to read the collection online, but it was not implemented due to several shortcomings such as the display system that has not used the UX approach and an error occurred when displaying the journal. Therefore, in this study, the development of the digital library prototype was carried out using the UX approach and refining existing features. This study uses the NodeJs programming language and MySQL database for prototype development, as well as personas as a tool to study user desires and UEQ to conduct UX assessments on digital library systems. The UEQ assessment was carried out on 30 respondens. The results of the increase in Attractiveness 16.02, Perpicuity 2.37, Efficiency 33.77, Dependability 5.27, Stimulation 7.37, Novelty 17.64, from a comparison of prototypes using UX and prototypes that do not use UX. This shows that the UX approach is successful. This success is felt by the ease of using the system and understanding how to use the system
Writing Your Own Python Scripts

In the previous chapter, we have covered all the basics of Python. Here, we will take a look at essential control flow statements and will learn how to structure a program. We will learn how to use for and while loops and compose custom functions. Also, we will get familiar with a decisive Python data structure – dictionary.
Pengembangan Sistem Informasi Manajemen untuk Penilaian Siswa SD Al Islah Surabaya

In the world of education, the use of information and communication technology offers an enormous number of opportunities. One of the potential benefits of information and communication technology for education is to support the organization and management of learning. One of the organizations in Indonesia that does not utilize a management system is school institutions, especially elementary schools. SD Al Islah Surabaya in recording student grades using manual methods. Although it did not cause problems, this method of recording was deemed ineffective and inefficient. The purpose of developing this application is to make it easier for teachers to make assessments and minimize errors in inputting values and streamline the work of teachers. The desired result is the creation of a website-based application in which there are features for organizing student grades. In this study, the test results show that the application built has good performance. And the target user also gives a positive value to this application. So that the development of this application can be concluded that the application can be accepted by users and can improve performance effectively and efficiently
Learning of Fuzzy Rules for Avoidance of a Moving Obstacle in a Mobile Robot

To coexist with human, a robot has to avoid obstacles based on human-like flexible decisionmaking. In this article, we recorded the angle and speed when a human operates a robot to avoid a moving obstacle on a developed computer simulator. Using obtained data, fuzzy rules to decide the moving direction and speed at every moment were derived as follows: as input variables, distance to obstacle, angle to obstacle, speed of obstacles, and moving direction of obstacle, were adopted. As output variables, steering angle and moving speed of robot were adopted, where it is noted not only angle but also speed is considered compared to other prior researches. Based on fuzzy-neural networks method, two networks having 4 inputs and 1 output were prepared. A membership function of input variable has 5 isosceles triangles. Fuzzy rules, number of which is 625 (=54), were assumed. Optimal center and width of each triangle were obtained so as that the network reproduces the trajectories of simulation experiment with minimum errors. The proposed method based on obtained fuzzy rules was compared with the conventional potential method and reinforcement trajectory learning method. The robot avoided flexibly and smoothly a moving obstacle like human with both short mileage and small crash rate by using proposed method on the simulator.
Saving Plan and Internet Bandwidth for Cost Optimization of Cloud Services Google, Azure, and AWS

Changing the game for organizations around the world helps them increase business speed, improve flexibility, and improve cloud performance, transform our approach to building and delivering applications. Usability - resource creation, cost utilization, and performance remain a natural concept behind Cloud Computing.The business's ability to adapt to changes in business conditions quickly and efficiently and to achieve cost reductions and financial growth is the speed of the business. Thecloud enables flexibility and robustness that promotes new functionality and faster development and distribution.The cloud promotes transparent communication and improved collaboration and business reduction, simplified IT performance, increased product productivity, and greater ability to respond to customer needs that contribute to faster business.The process of increasing the cost of unspecified resources is the purpose of my research on proposals to individuals and companies to follow.
Literature Study: Highway Traffic Management with Sentiment Analysis and Data Mining

In today's era, technology is growing rapidly, many of the latest technologies are in great demand by the Indonesian people, one of which is social media. Various social media such as Facebook, Twitter, Instagram, have become very popular applications for various ages, including teenagers, adults, and the elderly. Social media has a positive impact that can help people convey the latest information through posts on their respective accounts. Social media can disseminate information in a short time, this is why social media is an interesting application to research. The problem of road traffic congestion is strongly influenced by the number of vehicles that pass every day. A large number of private vehicles and public vehicles that pass greatly confuses the atmosphere of highway traffic. Congestion often occurs during working hours. Road congestion also often occurs when an unwanted incident occurs. Sentiment analysis algorithms and data mining algorithms can be combined to find information on traffic jams through social media such as Facebook, Twitter, Instagram, and other social media. The results show that sentiment analysis methods and data mining algorithms can be used to find information about current traffic jams through social media. The conclusion from this literature study can be seen that the K-Nearest Neighbor data mining algorithm is the best choice to overcome road traffic congestion, which will then be further developed in the form of highway traffic management modeling.
Exchanging registered users’ submitting reviews towards trajectory privacy preservation for review services in Location-Based Social Networks

In Location-Based Social Networks (LBSNs), registered users submit their reviews for visited point-of-interests (POIs) to the system providers (SPs). The SPs anonymously publish submitted reviews to build reputations for POIs. Unfortunately, the user profile and trajectory contained in reviews can be easily obtained by adversaries who SPs has compromised with. Even worse, existing techniques, such as cryptography and generalization, etc., are infeasible due to the necessity of public publication of reviews and the facticity of reviews. Inspired by pseudonym techniques, we propose an approach to exchanging reviews before users submit reviews to SPs. In our approach, we introduce two attacks, namely review-based location correlation attack (RLCA) and semantic-based long-term statistical attack (SLSA). RLCA can be exploited to link the real user by reconstructing the trajectory, and SLSA can be launched to establish a connection between locations and users through the difference of semantic frequency. To resist RLCA, we design a method named User Selection to Resist RLCA (USR-RLCA) to exchange reviews. We propose a metric to measure the correlation between a user and a trajectory. Based on the metric, USR-RLCA can select reviews resisting RLCA to exchange by suppressing the number of locations on each reconstructed trajectory below the correlation. However, USR-RLCA fails to resist SLSA because of ignoring the essential semantics. Hence, we design an enhanced USR-RLCA named User Selection to Resist SLSA (USR-SLSA). We first propose a metric to measure the indistinguishability of locations concerning the difference of semantic frequency in a long term. Then, USR-SLSA can select reviews resisting SLSA to exchange by allowing two reviews whose indistinguishability is below the probability difference after the exchange to be exchanged. Evaluation results verify the effectiveness of our approach in terms of privacy and utility.
Model of Developing Ideological Competence in Students

This article describes the model and structural basis of the process of developing ideological and ideological competence in students. This model reflects the methodological, practical and evaluation-result blocks, defines the social order, goals and objectives, its algorithmic stages, organizational conditions, evaluation criteria and levels for the development of ideological and ideological competence in students.
Designing the Strategy Map with Combined Approach of Anp and Dematel

Strategy map is a human based activity that combines the knowledge and organizational managers’ opinions. This point of view is a kind of group decision making that is determined by our existing relation between the accepted objectives of experts and organizational decision makers (DM). In this study, to design a strategy map for Fanap Company, the combined approach of Analytical Network Process (ANP) and Decision Making Trial and Evaluation (DEMATEL) were applied to determine the systematic interactions between criteria and the relationship between criteria, respectively. In this paper, the results about the importance of relations between strategic objectives level by combined approach, were compared to the importance of relations between AHP strategic objectives level, calculated by Fanap Company’s experts and managers. The final results showed that the importance of strategic relations between BSC levels to achieve the strategic objectives in this company in combined approach was more than AHP method.
Primary school wins national English award

Joseph Cash Primary School has been announced as the winner in the 2019 Tes Schools Awards for English Teacher or Team of the Year! The school has been ...
Graduation Day: Slightly Larger Programming Projects

In this chapter, we examine several slightly larger programming projects in Python, C#, and Java than so far presented. These projects are designed to demonstrate some of the most relevant concepts discussed in this book: variables, loops, file access, and threading. If you are able to decipher these little projects' innards, you can safely say you have a level of understanding on the basics of the three programming languages featured in this book. And if you still feel unsure about your skills as a coder at this point, this chapter can help you clarify some concepts.
Encryption Device Based on Wave-Chaos for Enhanced Physical Security of Wireless Wave Transmission

We introduce an encryption device based on a compact wave-chaotic cavity to enhance the physical security of wireless communication. The proposed encryption device is composed of a compact quasi-2D disordered cavity, where transmit signals pass through to be distorted in time before transmission. On the receiving end, the signals can only be decrypted when they pass through an identical cavity. In the absence of a proper decryption device, the signals cannot be properly decrypted. If a cavity with a different shape is used on the receiving end, vastly different wave propagation paths will prevent the signals from being decrypted, causing them to appear as noise. We experimentally demonstrate the proposed concept in an apparatus representing a wireless link.
Analysis of online physical education class acceptance intention of university liberal arts class participants applying TAM model

This study was executed to investigate the relationship between in-class flow, perceived usefulness, perceived ease of use, acceptance intention among university students of online physical education class. The questionnaire was used for research tools. This study was conducted by collecting data from 341 university students in Seoul and Gyeonggi Province. Data was collected using the method of non-probability sampling, convenience sampling. Collected data were analyzed by using SPSS statics 24.0 and AMOS 22.0 programs. Frequency analysis, internal consistency analysis and Cronbach
The Intersection of Ip and Artificial Intelligence (Ai)

In 1956 at the Dartmouth Summer Research Project on Artificial Intelligence, John McCarthy coined the term “Artificial Intelligence,”1 which he would define as “the science and engineering of making intelligent machines.” The usage/capabilities of artificial intelligence (AI) as a technology have been accelerating ever since, as computing power has grown exponentially, and more research has been devoted to artificial intelligence and its use cases. As a result, artificial intelligence has become an umbrella term that encompasses everything from Natural Language Processing/Understanding (NLP) to Machine Learning to Robotics to Deep Learning, and much more. Think of it as Cognitive Computing…a range of technologies that mimic the human brain and take actions.
Travel to Southeast Asia: Learning About Southeast Asia through Augmented Reality

‘Travel to Southeast Asia’ application is one of Augmented Reality (AR) technology. Learn about Southeast Asia is very important and has been emphasized in high schools. However, there are some students who are bored and not interested in learning geography especially related to foreign countries due to lack of exposure and information about it. So, the main purpose of this project is to develop an educational application based on Augmented Reality for students to interest them in learning about Southeast Asia. Students also can identify eleven countries in Southeast Asia by using this application and gain some knowledge related to the countries. Unity software is the main software to develop this Augmented Reality because Unity engine can support the high quality of audio and visual effects to ease the development of the project. This project developed by using ADDIE Model as a dynamic and flexible guideline for building effective training and performance support tools. This research was evaluated by among 15 students from Sultan Idris Education University who pursuing a Bachelor of Education (Geography) with Honor by using quantitative methods through online questionnaire. This questionnaire was distributed to the respondents for evaluation based on Usefulness, Satisfaction and Ease of Use (USE) questionnaire. As a result of the questionnaire, majority of respondents gave positive feedback and interested with ‘Travel to Southeast Asia’ application. Based on the research, learning about Southeast Asia using Augmented Reality provides better knowledge and understanding.
Sistem Pendukung Keputusan Pemilihan Perumahan Menggunakan Metode Simple Additive Weighting Di Kecamatan Tualang Prawang

The development of housing at this time is increasing rapidly and become the basic needs of every human being, it is caused by high demands on the needs of housing as a residence for everyone. During this time consumers make housing choices based on information from others, observing housing and experience by not considering the criteria needed to cause new problems for consumers after buying housing, such problems such as inconvenience as a housing owner. Simple Additive Weighting method is used to determine the preference value of each alternative, then do the ranking process that can select the best alternative from a number of alternatives. In testing the functionality of the system 100% goes well, while the usability testing with 20 respondents and 10 questions obtained an average value of 81.3% of the results of the presentation can say that the user agrees with the systemKeywords: Decision Support System, Simple Additive Weighting, Housing Selection..