Reviewerly/exHarmony huggingface dataset:
The Rise and Fall of Virtual Reality

In Pygmalion’s Spectacles, Stanley G. Weinbaum describes “a movie that gives one sight and sound. Suppose now I add taste, smell, even touch ... Suppose I make it so that you are in the story, you speak to the shadows, and the shadows reply, and instead of being on a screen, the story is all about you, and you are in it. Would that be to make real a dream?” Such a fantastical description may sound familiar. Virtual reality (VR) describes technology that allows a user to experience an entirely virtual world. Though VR is often seen as a cutting-edge technology of the modern day, its core concepts originated much earlier. In fact, Pygmalion’s Spectacles was written in 1935, and some of the foundational VR technology was created even earlier. With VR existing for decades, what has prevented it from fully catching on? To answer this, we’ll have to start at the very beginning.
Image Edge Extraction by Artificial Intelligence Schemes for UAV Autonomous Navigation

We present here the application of an image processing strategy for autonomous navigation in order to estimate the position of an Unmanned Aerial Vehicle (UAV) equipped with Synthetic Aperture Radar (SAR) sensors.Patches of the SAR images are compared to georeferenced satellite optical images, by first applying an image edge detection algorithm on all the images, and the UAV position is determined from the correlation matrix obtained from resulting segmented images.The performance of three edge detectors are compared: the Canny approach, an artificial neural network (radial base function), and a fuzzy system.
Computer simulation study on heat transfer of surrounding rock in mine roadway of coal mine enterprises

The thesis theory combined with computer simulation, according to the thermal theory, the heat transfer process of the surrounding rock in the coal mine roadway is simplified into an unstable state process, and the influencing factors of the unstable heat transfer coefficient of the surrounding rock are found, and the computer experimental system is used as the basis. At the same time, the paper constructs an experimental receipt according to the similarity theory, and uses the concrete specimen simulation like the thermal performance of the surrounding rock of coal mine as the coal mine roadway to realize the real-time simulation of the heat transfer process of the roadway. The unstable heat transfer coefficient of the surrounding rock under different wind speeds and ventilation specimens was tested to find the law of variation. Finally, in the actual coal mining industry, different roadways are selected for borehole temperature measurement, and the temperature record body with temperature recording function is used for measurement. The calculation formula of the original rock layer temperature at different depths of the mine area is obtained, and the accuracy of the model is verified.
How Efficient are University Library Portals of NIRF Ranked Indian Universities

Seeing the underlying value of having a unified interface to update users about library services and activities, most libraries have developed library portals. The paper aims to evaluate the contents and services of top ten NIRF ranked university library portals and score them in the classes of Excellent, Good, Average and Poor. Further, the study aims to investigate the most preferred type of content available on Indian university library portals. The top ten NIRF ranked university library portals were evaluated using a checklist based framework covering broad categories such as Information about general, information about the library’s physical collection, Information about subscribed e-resources, information regarding the library’s services, and Information regarding the use of social Web technologies. Findings suggest that six of the selected library portals were rated in the ‘Average’ class(scores 40-60 %), which shows that most of them lack essential user-oriented information. JNU’s library portal carries maximum information for their users scoring maximum University Score of 28(62.22 %). Among the selected library portals 49.23 per cent prominently provide information about the library’s collection, followed by general information(46 %) and information regarding library services(35.33 %). Only one portal exploits social networking features. The study report that the Indian university library portals suffer from issues like currency, transparency, visibility of collection, availability of online services, and uniformity. The findings of the study will help the portal development team to select the most common category of content describing information about services and facilities available on library portals. The existing portals can also improve their interface based on the findings of the present study. Assessment of existing university library portals of the national top ten university library portals in India is the first attempt to evaluate this kind of sample. The study’s value lies in its evaluation framework, that’s minimal in nature covering the minimum information categories that must be available on any university library portal.
Robot Coalition Formation Based on Fuzzy Cooperative Games over Blockchain-Based Smart Contracts

In production cyber physical systems robots perform most operations. On the way to Industry 4.0 robots have to be automated and perform operation in coalition to reach common goals. The paper describes an approach to dynamic formation of coalitions of autonomous robots based on the integration of fuzzy cooperative games and smart contracts. Each robot is viewed as an agent, negotiating and bidding with others during the coalition forming for distribution of joint winnings. It is necessary to find combination of robots in way to maximize efficiency of joint work, while the efficiency of the entire coalition is unknown beforehand. A cooperative game with fuzzy core is used to form a coalition of robots allowing coordinating the actions of individual members to achieve a common goal, as well as to evaluate and distribute the overall benefit. To implement the negotiation process and record the composition of the coalition and the responsibilities of individual participants, it is proposed to use the smart contract technology, which now become a part of the blockchain technology. Smart contracts are proposed to be used as entity holding requirements and expected winnings of each participant in the immutable structure of a blockchain network. The final agreement can also be stored by all participants in form of smart contract that contains the distribution coefficients of the winnings given all the conditions of participation in the coalition. The availability of smart contracts to all participants in the coalition makes it possible to ensure joint control over the fulfillment of the task assigned to the coalition.
Investigating the phonetic expression of successful motivation

The present study provides a comprehensive acoustic phonetic analysis of motivational speech by collecting, annotating and processing 50 minutes of speech data representing less and more successful degrees of motivation.The analysis shows significant differences regarding the acoustic phonetic features f 0 (median, range, variation), intensity (median, range) and speaking rate.We observe inconsistent results for the variation of intensity, pointing to the necessity of a more fine-grained analysis of this feature.This study provides first support for the existence of a specific motivational speaking style.
Gradient-driven unsupervised video segmentation using deep learning techniques

We propose a three-dimensional video segmentation method using deep learning convolutional neural nets. The algorithm utilizes the local gradient computed at each pixel location together with the global boundary map acquired through deep learning methods to generate initial pixel groups by traversing from low to high gradient regions. A local clustering method is then employed to refine these initial pixel groups. The refined subvolumes in the homogeneous regions of video are selected as initial seeds and iteratively combined with adjacent groups based on intensity similarities. The volume growth is terminated at the color boundaries of the video. The oversegments obtained from the above steps are then merged hierarchically by a multivariate approach yielding a final segmentation map for each frame. The results show that our proposed methodology compares favorably well, on a qualitative and quantitative level, in segmentation quality and computational efficiency, with the latest state-of-the-art techniques utilizing the video segmentation benchmark dataset.
Interest Estimation for Images Based on Eye Gaze-based Visual and Text Features

This paper presents an estimation method of user-specific interests for images. The proposed method computes a projection which maximizes the correlation between “eye gaze data which are collected while watching images” and “visual and text features” by utilizing Canonical Correlation Analysis (CCA). Since eye gaze data reflect user's interests, new visual and text features calculated by using obtained projections can be also expected to reflect user's interests. Then accurate estimation of user-specific interests for images via Support Vector Machine (SVM) becomes feasible from these features. Experimental results show the effectiveness of our method.
Selection of Optimum Mother Wavelet Function for Turkish Phonemes

In this paper, we propose the selection of most suitable mother wavelet function for Turkish phonemes using discrete wavelet transform. The determination of most similar mother wavelet function to the signal has been a challenge in speech processing. The optimum mother wavelet function for Turkish phonemes have been determined by using quantitative measures which are energy and Shannon entropy, information theoretic measures which are joint entropy, conditional entropy, mutual information, and relative entropy from wavelet coefficients of the phonemes. In this study, 101 potential functions were investigated to determine the most appropriate mother wavelet. Experimental results show that the most appropriate wavelet functions for /ç/ and /ş/ phonemes which are unvoiced fricatives have been found as Bi-orthogonal 3.9 and Bi-orthogonal 5.5, respectively. By considering all the results, it is seen that the Bi-orthogonal 3.1 and Discrete Meyer wavelet functions are the most suitable mother wavelets for all other phonemes.
SentiFilter: A Personalized Filtering Model for Arabic Semi-Spam Content based on Sentimental and Behavioral Analysis

Unwanted content in online social network services is a substantial issue that is continuously growing and negatively affecting the user-browsing experience.Current practices do not provide personalized solutions that meet each individual's needs and preferences.Therefore, there is a potential demand to provide each user with a personalized level of protection against what he/she perceives as unwanted content.Thus, this paper proposes a personalized filtering model, which we named SentiFilter.It is a hybrid model that combines both sentimental and behavioral factors to detect unwanted content for each user towards pre-defined topics.An experiment involving 80,098 Twitter messages from 32 users was conducted to evaluate the effectiveness of the SentiFilter model.The effectiveness was measured in terms of the consistency between the implicit feedback derived from the SentiFilter model towards five selected topics and the explicit feedback collected explicitly from participants towards the same topics.Results reveal that commenting behavior is more effective than liking behavior to detect unwanted content because of its high consistency with users' explicit feedback.Findings also indicate that sentiment of users' comments does not reflect users' perception of unwanted content.The results of implicit feedback derived from the SentiFilter model accurately agree with users' explicit feedback by the indication of the low statistical significance difference between the two sets.The proposed model is expected to provide an effective automated solution for filtering semi-spam content in favor of personalized preferences.
Internet of Medical Things (IOMT): Trends and Challenge

Since the transformation from paper records to digitized Electronic Health Records (EHRs), patient data are coonly updated and then sent by doctors to specialists in other hospitals among other transactions.The problem is that caregivers are not banks, where financial information is locked up and not shared.This unencrypted information is vulnerable to profit-hungry hacker attacks.Moreover, healthcare is rapidly moving to a completely digitized environment, and, as a result, many devices have been introduced to the hospital ecosystem and bedside workflows to help extend and streamline care throughout the hospital.As hospitals move to achieve real-time visibility into their different systems and applications, reduce time away from the patient bedside, and increase the quality of care, new technology has come in to play to improve interoperability of these systems and components.Robust tools, ubiquitous devices and clinical modern networks like the IoMT (Internet of Medical Things) have allowed clinicians to become more efficient and mobile with patient care.Unfortunately, this new technology has also opened the door to increased risk and new potential points of exposure for healthcare IT infrastructures.This article discusses the challenges and the suggested steps needed to reduce vulnerabilities against such security attacks.
Analysis and Design of Web-Based Knowledge Management System for Real Estate Property

The term knowledge management (KM) was introduced in 1986, at the European management conference (American Productivity and Quality Center).This concept then developed rapidly and attracted the attention of many parties.In the last decade knowledge management has become one of the methods of increasing the productivity of an organization, company, or agency.This is understandable because competition no longer relies on natural resources, but instead moves to the optimal use of human resources.Utilization of human resources through the potential for creativity and innovation is done in order to increase the productivity of an organization.One of important knowledge is product knowledge, product knowledge is clearly needed by business people as its main capital in its business activities.The deeper knowledge of the products sold will facilitate the process of marketing the product to the customer.Product knowledge is also one element of good service, because how can we provide the best service if we do not know the advantages or disadvantages of the product.
Oracle or Teacher? A Systematic Overview of Research on Interactive Labeling for Machine Learning

Machine learning is steadily growing in popularity – as is its demand for labeled training data. However, these datasets often need to be labeled by human domain experts in a labor-intensive process. Recently, a new area of research has formed around this process, called interactive labeling. While much research exists in this young and rapidly growing area, it lacks a systematic overview. In this paper, we strive to provide such overview, along with a cluster analysis and an outlook on five avenues for future research. Hereby, we identified 57 relevant articles, most of them investigating approaches for labeling images or text. Further, our findings indicate that there exist two competing views how the user could be treated: (a) oracle, where users are queried whether a label is right or wrong versus (b) teacher, where users can offer deeper explanations in the interactive labeling process.
Minimal representative set for a system of frequency classes of underdetermined words

In this work, we list all possible characteristic polynomials of the Frobenius endomorphism for genus 3 hyperelliptic curves of type y 2 = x 7 + ax 4 + bx over finite field F q of characteristic p > 3.
Applying Modified TF-IDF with Collocation in Classifying Disaster-Related Tweets

Disaster-related tweets classification refers to posted tweets on twitter during the time-critical events (e.g., natural, human-made) that are group together according to pre-defined categories (e.g., donations, awareness, help, etc.).The purpose of classification is to deliver the conveyed messages to suitable authorities on time for requiring needs for immediate action.The classification works well if terms that are extracted from tweets are carefully selected or referred to as good attributes that can best label the uncategorized tweets.The Term Frequency -Inverse Document Frequency (TF-IDF) helps classifier to extract useful features.Hence, TF-IDF naturally works on distinct terms.However, a single term occasionally can be ambiguous, which means that when a separate term used for indexing, could carry numerous connotations.The distinct term can sometimes too broad, which means it does not have a discerning power to discriminate terms, for example, from the two individual terms "college" and "junior".These two terms are not adequate to differentiate "college junior" from "junior college" [1].Hence, applying traditional TF-IDF in text classification can reduce classification efficacy.Thus, a combination of terms known as collocation is introduced as an improvement to TF-IDF to boost the text classification effectiveness.This paper aims to provide an analysis of the efficacy of tweets classification by applying improved TF-IDF with collocation.This experiment utilizes tweets dataset from the CrisisLex website.The performance evaluation metrics considered are confusion matrix, precision, recall, and F1 score.The result shows that there is a favorable increase in the proposed study as compared to traditional TF-IDF through said evaluation metrics vary from 4% to 24%.The study also establishes that RandomForest consistently outperforms that two other compared classifiers.
Xerus Optimization Algorithm (XOA): a novel nature-inspired metaheuristic algorithm for solving global optimization problems

Over the recent years, many research has been carried out on applying the optimization approach to science and engineering problems. Thereby, numerous metaheuristic algorithms have been developed for solving such type of challenge. Despite an increase in the number of these algorithms, there is currently no specific algorithm which can be employed to optimize all varieties of problems. In the current research, a novel metaheuristic algorithm for global and continuous nonlinear optimization, named as Xerus Optimization Algorithm (XOA) has been introduced. XOA has been inspired by group living and lifestyle of cape ground squirrels (Xerus inauris), by taking into account their co-operation in living together, hunting, and communication, etc. In order to evaluate the efficiency of XOA, algorithms for 30 different benchmarks have been analyzed and compared to some novel and renowned metaheuristic algorithms. The simulation response illustrates a significant improvement in  the performance of the novel XOA, in comparison to the algorithms presented in the literature. The proposed algorithm can be employed for many applications that require a solution to different optimization problems.
‘EARTHBOT’- The Smart Sanitation Robot

With the increasing waste production rates, solid waste management has become the need of the hour. Dumped unmanaged wastes causes severe harm to humans and also drastically affects the environment. It also causes various climatic changes and hinders the economic growth of countries. Environmentally sound waste management techniques touches various critical aspects of development of a country. Thus, this paper proposes an idea of ‘Earthbot’ which is smart enough to both collect waste and segregate them. The paper also discusses the possible waste management solutions, after segregation of waste is done by the robot.
Educational Opportunities of Natural Science Motivation for Students with Special Educational Needs: the Viewpoint of Natural Science Teachers

The article discusses how (in what ways) natural science educations teachers motivate students with special educational needs in order to encourage students’ motivation to learn. Researches reveal that students with learning needs have experienced a variety of learning difficulties, which often causes the loss of their learning motivation and even willingness to attend school. In nowadays school, which aim is to ensure proper education for each pupil, the teacher has to pay special attention to developing pupils’ learning motivation. The article presents a study aimed at finding out how to effectively educate children with special educational needs in general education schools. In the survey participated 146 teachers of nature study, who have experience in working with students with special educational needs. The results of the study revealed that teachers rely on the provisions of the Teachers’ Ethics Code to encourage students to work independently and persistently. This is a very new insight, as the Teachers’ Ethics Code was approved only on 11 June 2018 by order No. V-561 of the Minister of Education and Science. From the teachers’ point of view, for students with special educational needs to increase learning motivation teachers use interesting innovation teaching methods, practical work, use of ICT, creation of educational environments, oral and written honors, gratitude. Also, they use fair evaluation, better marks for progress, even if it is small, adopted tasks, create the conditions for success, pursuit to raise interest, attention, encouragement, communication, cooperation.
Security of Data Access in Fog Computing using Location-based Authentication

Many organizations, such as military, financial, and banking organizations, implement strict security policies for securing and protecting data from any possible attack.Moreover, these institutions use the Internet of things (IoT) and fog computing for communication and storage that require new solutions to confirming the login process between the two techniques.A methodology for increasing the security for fog computing is proposed in this research.The proposed methodology provides authentication that is based on the location of the device that will perform fog computing during communication, thereby ensuring the secure login to data and legal verification.Furthermore, the proposed methodology is simulated using the LabVIEW simulator with different case studies.Results show that location-based authentication increases authentication confidence and security.