Reviewerly/exHarmony huggingface dataset:
Ethical Concerns and Opportunities in Binding Intelligent Systems and Blockchain Technology

Intelligent systems are becoming increasingly complex and pervade a broad range of application domains, including safety-critical systems such as e-health, finance, and energy management. Traditional approaches are no longer capable of addressing the demand for trust and transparency in these applications. Hence, the current decade is demanding intelligent systems to be autonomous, and in particular explainable, transparent, and trustworthy. To satisfy such requirements, and therefore to comply with the recent EU regulations in the matter (e.g., GDPR), intelligent systems (e.g., Multi-Agent Systems - MAS) and technologies enabling tamper-proof and distributed consensus (e.g., Blockchain Technology - BCT) are conveying into reconciling solutions. Recently, the empowerment of MAS with BCT (and the use of BCT themselves) has gained considerable momentum, raising challenges, and unveiling opportunities. However, several ethical concerns have yet to be faced. This paper elaborates on the entanglement among ethical and technological challenges while proposing and discussing approaches that address these emerging research opportunities.
Research on the Identification of IoT Devices Based on Higher-Order Spectra

With the development of wireless communication technology, IoT devices have been widely used in many fields. However, the security of the wireless network is being confronted with a series of new threats and challenges. Radio frequency fingerprinting is a physical-layer method for wireless network security. The higher-order spectra analysis is a powerful tool for non-linear, non-Gaussian processes and non-minimum phase systems. Bispectrum is the simplest higher-order spectra with order 3. In this paper, we studied the feature extraction method based on steady-state signal of wireless devices through 4 integrated bispectrums. An experiment under the real IoT devices working environments has evaluated the performance of the feature extraction method.
Fusion Segmentation of Head Medical Image with Partially Annotated Data

In this paper, there are 2 head computed tomography (CT) scan datasets: one with vision related organs pixel annotations and the other with auditory related organs pixel annotations. We aim to train a single neural network for vision related organs and auditory related organs segmentation at the same time with these 2 partially annotated datasets. An idea generating from co-operative training method will be applied to complete the lacking annotations of each dataset. However, it is not a proper way to treat the predicted annotations as the real annotations from professional doctors. To address this error, a semi-supervised method is chosen. Compared to the baseline method, our training pipeline is able to complete 2 segmentation tasks within only one model, and we have proved that it outperforms the baseline method. To some extent, using partially annotated medical image datasets can help to solve the problem that the scarce source of professionally annotated medical image data. What’s more, the proposed method will achieve better performance.
Comparison of Text Data Compression Using Yamamoto Recursive Codes and Punctured Elias Codes

Abstract This research aims to study the efficiency of two variants of variable-length codes (i.e., Yamamoto Recursive codes and Punctured Elias codes) in compressing texts. The parameter being examined are the ratio of compression, the space savings, and the bit rate. As a benchmark, all of the original (uncompressed) texts are assumed to be encoded in American Standard Codes for Information Interchange (ASCII). The overall result shows that the Punctured Elias codes are consistently more efficient to compress texts than Yamamoto Recursive codes.
LibGuides: Online Learning: Library Services & Sources: Virtual Services

Library Services and Sources for Online Classes A description of our various online services
Correlation filters based on temporal regularization and background awareness,

Information about background appearance and previous tracked frames is significant for effectively discriminating a target from a complex scene. In this paper, we propose a novel tracker called temporal regularization and background-aware correlation filter (TRBACF) tracker based on the theory of correlation filter. In the proposed TRBACF tracker, an improved circular shift operation for collecting training samples is used to obtain more background information, which can enhance the discrimination ability of the learned correlation filters. Furthermore, to ensure the long-term tracking performance, a temporal regularization term is added to the appearance model of the classical correlation filter. The developed appearance model can take advantage of the similarity of the filters in the adjacent frames and improve the learned filter to be more adaptive to variations in the scene. Extensive experimental results on various challenging videos demonstrate that the proposed TRBACF tracker achieves superior accuracy than some state-of-the-art trackers.
Improving the Students’ Reading Comprehension by Using Think Talk Write (TTW)

This research was designed to improve the students` reading comprehension through Think Talk Write at the first-grade students of SMKN 1 Lasusua. The research problem was “The reading comprehension of the first- grade students of SMKN 1 Lasusua is low”. The design of this research was collaborative Classroom Action Research (CAR).In this research, there were two cycles. The first cycle was not success because the result of the students’ test did not fulfill the KKM, so there was the next cycle. The second cycle was success because the result of the student test achieved the KKM mandatory by the school. In addition, this research must get score of 70 to fulfill the Minimum Mastery Criterion – Kriteria Ketuntasan Minimal (KKM). It could be seen in the average score, it was 68.6 in the first cycle, and there were only 17 students from 35 students got greater score than or equal 70. This score increased to be 74.77 in the second cycle, there were 26 from 35 students got score greater than or equal 70. It means that this research was successful. Based on the findings, the conclusion is Think Talk Write strategy could improve the students` comprehension in reading at the first-grade students of SMKN 1 Lasusua.
The Use of Talking Chips Technique in Teaching Speaking

This research aim to identify how the implementation of Talking Chips technique can improve the students’ speaking ability. The population is student of grade X SMAN 3 MAJENE. The sample of this study was only one class and total number of students was 30 students. Research method that used is quasi-experimental design. This study was conducted by using multiple pre-test and post-test. During the treatments, there were problems related to classroom management, fluency and comprehensibility. Those problems could be minimized. After posttest, there were still problems, but the problems were fewer than previous ones because students had showed the awareness in speaking English. The research findings show that the implementation of talking chips could improve the students’ speaking skill in delivering speech and the classroom situation of speaking class. The improvement of students speaking skill includes: 1) Students had enough vocabulary to deliver speech; 2) the students were able to pronounce the word correctly during delivering the speech; 3) the students could produce the sentences grammatically correct; 4) the students delivered the speech more fluent. The improvement of classroom situation includes: a) the class was more alive because the students’ participate actively during the speaking class; b) there was an equal participation during the speaking class; c) the students were motivated to speak English than Indonesian. It can be concluded that the implementation of talking chips can improve the students speaking ability in delivering speech and the classroom situation. It is hoped that this result can give other teachers inspiration to implement talking chips in their classroom.
Marketing innovations: Opportunity and challenges- A study on Haveri city

The importance of innovation in the current business strategy modern day’s technology is one of the most powerful weapons to a successful company. This marketing innovation construct and its associated strategic activities are clearly distinguished from product and process innovation, better-enabling researchers and practitioners to identify new and updated paths from innovation to firm performance. Marketing innovation and technology is one of the factor surveys along with rival competitors and along with long term substance in the market. Technology is helping to increase produces qualities product and easy to distributes. Innovation and technology will provide customer loyalty and reach the target group. The innovation has been executed in many companies and they are running their business successfully. They are Nestle, windows operator, and various cell phones, etc. To conclude if you’re trying to enhance your marketing activity or create new things or new development products hence, this paper attempts to find the opportunities and challenges to the organization and innovations products under the study area.
The Specific Features of Public Relations Maintained by Libraries, Acting as Cultural Institutions

Showing the specificity of the work of the contemporary library, and the variety of its tasks, which go far beyond the lending of books. The specificity of the library’s public relations concerning different aspects of its activity. The internal and external functions of the library’s public relations and their specificity. The significant question of motivating the social environment to use the offer of libraries, and simulta-neously the need to change the negative perception of the library, which discourages part of its poten-tial users from taking advantage of its services. The negative stereotypes of librarians’ work perpetuated in the public consciousness and their harmful character. The need to change the public relations of libra-ries and librarians with a view to improving the realization of the tasks they face. Showing the public relations tools which may serve to change the image of librarians and libraries with particular emphasis on social media. This article is a review article, highlighting selected research on the librarian’s stereo-type and suggesting actions that change the image of librarians and libraries.
The effect of changing the domain sequence in an English diagnostic test

The sequence of test domains might affect test-takers’ scores in an English diagnostic test, in particular, for the students whose English language proficiency is low. However, there is a little literature on the relationship. This study investigated the effect of the different domain sequence on test-takers’ scores at a college level. The previous test for a non-curricular English program for beginner level consisted of the domain order: reading, grammar, vocabulary, and conversation. In the study, a new diagnostic test was developed based on the results of examining test validity of the test items and instructor interview. The domain order of the new test was modified into the one: grammar, and conversation, and reading which included vocabulary part. 133 students at a Korean university were given both of the tests. The results firstly indicated that examining the test validity resulted in different difficulty of the domain order and unbalanced difficulty assignment. Secondly, a paired t-test showed that there was statistically significant difference between the two means of the test scores. Thirdly, the results of a post-survey revealed that they preferred the order of the new test to that of the previous test. Some suggestions are discussed in terms of the order of test domains and test scores.
Hybrid KFCM-PSO Clustering Technique for Image Segmentation

In this paper, an image segmentation algorithm is proposed which is Kernel-based Fuzzy c-means using Particle Swarm Optimization (KFCM-PSO). This algorithm uses kernel function as it is a generalized distance metric that maps data points into high-dimensional plane where the data points are more clearly separable. Kernel-based Fuzzy c-means are integrated with Particle Swarm Optimization because the traditional Fuzzy c-means algorithm falls into local optima problem whereas PSO is a global optimization algorithm. Comparison of the proposed algorithm with existing FCM, KFCM, and FCM-PSO algorithms is done and the results show that the proposed algorithm gives better results than others.
Building Our First Android Game: Sphere Shooter

That’s it, we’re now ready to build an actual 3D mobile game in Unity! In this chapter, we’re going to make a simple game. Basically, our game character will be a cube with a turret (we’ll be calling this a tank). Using two joysticks, a player can move the tank and fire bullets. Next, we’re going to make an enemy and spawn copies of it. Enemies will try to go in the same direction as the player’s tank, and the aim of the game will be to destroy them before they succeed.
ANALYSIS OF PERCEIVED USEFULNESS AND SATISFACTION AS FACTORS INFLUENCING LEARNING CONTINUANCE INTENTION: A SYSTEMATIC REVIEW

The aim of this study was to conduct a systematic review research concentrating on studies regarding continuance learning intention. 30 empirical research articles published on the learning continuance intention between 2006 and 2019 were re-analyzed in order to answer the questions raised. The main findings of this study are all the articles reviewed reported a significant influence of satisfaction on continuance intention and for the perceived usefulness only one article reported in significant correlation between perceived usefulness and continuance intention. In addition it was equally found that most of the researchers either adapted or adopted Daviss 1989 instrument for measuring perceived usefulness. Therefore, to increase the applicability of continuance intention research future studies could investigate continuance intention on school subject area.
Sorry, Shodan is not Enough! Assessing ICS Security via IXP Network Traffic Analysis.

Modern Industrial Control Systems (ICSs) allow remote communication through the Internet using industrial protocols that were not designed to work with external networks. To understand security issues related to this practice, prior work usually relies on active scans by researchers or services such as Shodan. While such scans can identify public open ports, they are not able to provide details on configurations of the system related to legitimate Industrial Traffic passing the Internet (e.g., source-based filtering in Network Address Translation or Firewalls). In this work, we complement Shodan-only analysis with large-scale traffic analysis at a local Internet Exchange Point (IXP), based on sFlow sampling. This setup allows us to identify ICS endpoints actually exchanging Industrial Traffic over the Internet. Besides, we are able to detect scanning activities and what other type of traffic is exchanged by the systems (i.e., IT traffic). We find that Shodan only listed less than 2% of hosts that we identified as exchanging Industrial Traffic. Even with manually triggered scans, Shodan only identified 7% of them as ICS hosts. This demonstrates that active scanning-based analysis is insufficient to understand current security practices in ICS communications. We show that 75.6% of ICS hosts rely on unencrypted communications without integrity protection, leaving those critical systems vulnerable to malicious attacks.
Robust feature modeling for face authentication in smart device

As smart devices become widespread, security has emerged as a crucial problem for users. Biometrics is an effective means of user authentication that has been applied to smart devices. Face authentication has been widely studied in this context because of its short interaction time and quick authentication. In this paper, we propose robust feature modeling for face authentication in smart devices. Our approach uses coefficients of low-rank representation as a measure of similarity between samples. Label regression and reconstructed label information are then used to supervise feature subspace learning. We added three types of noise and interference to three public face datasets to simulate potential problems in face authentication on smart devices. The results of the experiment show that our proposed approach can achieve better authentication performance than conventional methods.
Aplikasi Pemesanan Jasa Tour Guide Dan Vacation Planner Di Bali Berbasis Mobile

E-Tourism is a technological innovation through e-commerce in the field of tourism. E-Tourism provides a tourism service to tourists online and the organization of tourism marketing has become more accessible. This study aims to produce a mobile-based Tour Guide and Vacation Planner booking service information system which is expected to be beneficial for tourists in planning and making their visit easier while in Bali. This application is expected to make it easier for tourists to make holiday planning in Bali so as to create an efficient and appropriate plan for tourists, and ultimately have an impact on the tourism sector in Bali. This research applies to the waterfall method. This research is based on the results of tests using interview methods and filling out questionnaires for people who play a role in tourism.
Particle physics phenomenology with Python 3: $e^- + \bar{\nu}_e \to e^- + \bar{\nu}_e$ scattering in the Fermi theory

In this work, we develop an algorithm in Python 3 to compute the theoretical prediction of the electron and electron anti-neutrino scattering cross section using two different numerical methods: {\it i)} Riemann sums and {\it ii)} Monte Carlo integration. We compare the precision among these two methods and the theoretical result. Finally, the theoretical prediction is compared with the result obtained with MadGraph 5 which is commonly used to provide theoretical predictions for the LHC. With this project, we would like to encourage students to use programming languages as a tool for the study of new physics.
Geogebra como herramienta de transformación educativa en Matemática

The investigation allowed us evaluate the effects the application of GeoGebra to the students of Basica superior in the teaching of Matematicts Subject in order to solve reasoning problems and communicate matematicts.This study was done in two phases: the first one was the application of traditional teaching, in the second step, was use the software GeoGebra. At the end of each phase the respective evaluation was done to the educaters.  Its resuls after the use of GeoGebra were significative in the teaching of matematicts.The hermeneutics about this subject Starts from writing, comprehention and interpreting the concepts Writing in the texts and also the personal experiences of teachers in order to get a wide view about this subject.Finally the triangular between the theory, the author´s experiences and the results of the research concludes that: The moment the teacher innoves the ways of teaching Matematics, the students seems to learn in a better and fast way the objectives gave to them, and also the students are able to construct their own knoledge, this knoledge allows them to put into practics right away in the resolution of daily problems, by doing this they generate generate a significative learning concerning to matematicts in conexion with GeoGebra.
A Study on the Real Estate Broker Qualification System in the Fourth Industrial Revolution

This study sought an adaptive development plan for the real estate brokerage qualification system under the background of the Fourth Industrial Revolution. The adaptive development measures presented in this study are as follows. First, a lifelong education system that reflects academic characteristics according to changes in future society should be established and preceded. Second, the qualification test should be phased out from the test type to the process evaluation system. Third, the essential requirements for working experience should be institutionalized in the process evaluation process. Fourth, introducing a system of brokerage remuneration education and unopened maintenance education. Customized remuneration education for the opening and the unopened real estate agent shall be introduced. Fifth, in the question of qualification examination for licensed real estate agent, the method of examination and the questions given in consideration of environmental changes shall be improved. It is necessary to promote the upgrading of the qualification problem that can be qualified as an expert by aiming at solving practical understanding problems rather than simply memorizing them. Sixth, the institution certification system for course evaluation and practical education should be introduced. Finally, a test subject and evaluation system should be added to assess the ethics of real estate agents. This is because it takes a considerable period of time to form brokerage ethics.
A Pilot Study on Argument Simplification in Stance-Based Opinions

Prior work has investigated the problem mining arguments from online reviews by classifying opinions based on the stance expressed explicitly or implicitly. An implicit opinion has the stance left unexpressed linguistically while an explicit opinion has the stance expressed explicitly. In this paper, we propose a bipartite graph-based approach to relate a given set of explicit opinions as simplified arguments for a given set of implicit opinions using three different features (a) sentence similarity, (b) sentiment and (c) target. Experiments are carried out on a manually annotated set of explicit-implicit opinions and show that unsupervised sentence representations can be used to accurately match arguments with their corresponding simplified versions.
A Counterfactual Quantum Key Distribution Protocol Based on the Idea of Wheeler’s Delayed-Choice Experiment

This paper elaborates the idea of Wheeler’s delayed-choice experiment, analyzes the process of bomb detection based on the idea, and introduces a counterfactual quantum distribution protocol. The protocol can detect the eavesdropping behavior accurately and timely and fundamentally eliminate the eavesdropper’s access to communication information.
AUTOMATIC WASTE SEGREGATION SYSTEM USINGCONVOLUTIONAL NEURAL NETWORKS

Automatic Waste Segregation is the process of classifying and separating waste objects into several categories forfurther treatment, it acts as a middle process between cumulative collection and waste treatment. Improper wastetreatment not only causes pollution but also increases the overall cost of the waste treatment process, hence a properwaste segregation mechanism needs to be implemented before treatment. The paper is a successful attempt ofcreating a waste segregation mechanism with minimal cost and with minimal human intervention at household levelwith the help of deep learning specifically Convolutional Neural Network (CNN), image recognition and Internet ofThings (IoT). The model classifies a waste as either biodegradable or non-biodegradable and segregates waste intoseparate compartments using a flap mechanism, the proposed model also sends feedback to the user in real time aswhen the bin requires maintenance. The neural network is trained using a large dataset consisting of approx. 13000images combined with suitable hidden layers, 70-30 % images were used for training and testing respectfully. Theproposed model gives accuracy of 92%. The classification and segregation happens in real time which helps toreduce overall human efforts and reduces cost of overall process.