Reviewerly/exHarmony huggingface dataset:
Load Balancing in Cloud Computing Environment Using CloudSim

Cloud computing has been built on the advancement of distributed computing and virtualization concept for offering effortless accessibility of the resources from various sources. It offers efficient access to many organizations to obtain services from the cloud service providers. The concept of virtualization is its advantage which leads to its extensive application. Through virtualization concept, it offers services to the users on demand basis. So, the cloud service providers consider the resource allocation to various servers, which needs to be done efficiently. So, we need cloud simulation and modeling tool for creating cloud as per necessity in cloud computing. Load balancing using these simulators is the task which is considered in this paper. CloudSim tool is used for verification of the load balancing modifying the number of brokers or number of virtual machines.
Conducting HCI Research on Stigma

My research area lies at the intersection of stigma, technology, and HCI research methods. In the case of HIV, design of technology has focused on medication adherence and treatment management and less on exploring how people living with HIV can cope with HIV-related stigma more directly via the use of technology. Additionally, HCI research on HIV has relied on face-to-face studies. My dissertation work thus focuses on two aspects: (1) HCI research conducted remotely via the Internet; and (2) the design of technology that could help individuals cope with HIV-related stigma. My prior work has already explored the first aspect. At the moment, I am planning a study that would involve remote asynchronous and synchronous co-design workshops. There are several contributions of my dissertation work. First, it provides insights, lessons, and best practices to conduct HCI research with a stigmatized population remotely. Second, it explores the use of current technology to cope with public HIV-related stigma; and, third, it explores the speculative design of technology that could help people cope with HIV-related stigma more directly.
Technology of preparation of natural waters for irrigation

Abstract Research and search for the most effective and cost-efficient ways of water treatments is relevant today. We propose the use of a natural sorbent as a filter load of a sorption filter for the preparation of natural water for irrigation of crops. The object of study is the water of the Volga River in the Volgograd region. In this work, we propose the use of a sorption filter for purification of natural water, where natural zeolite will be used as a filter load. Before the experiment, a chemical analysis was performed to determine the contaminants in the water and their concentrations. The fractions of zeolite were selected using fractional sieves. Based on the results of sedimentation, the optimal fraction of natural zeolite in terms of absorption properties and contact time with the studied water was selected. Based on the results, the statistical processing of the experimental data was performed and the dependences presented in the form as a power model were obtained. Thus, on the basis of the conducted studies, it can be concluded that it is advisable to use a sorption filter with a zeolite filter load for the preparation of natural waters to be used in irrigation.
Bitcoin Blockchain Steganographic Analysis

Steganography has been used as a way to hide data in files or in messages traveling on communication channels. Its use can be worrisome when it is used without proper authorization. Recently, it has been detected that there are arbitrary files included in the public blockchain of the Bitcoin cryptocurrency. The main concern arises when such data inserted contains objectionable content, thus compromising blockchain platforms. In this context, this paper presents an analysis of the Blockchain of Bitcoin, based on some proposals for the use of steganography in blockchains and on detection methods of steganographic data. Additionally, it is shown that we found no evidence of steganography data in Bitcoin using these techniques. We conclude by showing that there is no specific approach, so far, for steganalysis in blockchains.
Dewarping Document Image Techniques: Survey and Comparative Study

In recent years, everyone has his/her own handheld digital devices such as PDAs and camera phones which are used to capture any documents, for example, posters, magazine and books. This is the simplest way to disseminating and collecting information. Unfortunately, the snapshot of this document in an uncontrolled environment has been suffering from different perspectives and geometric distortions, especially when a picture is taken from rolled document, page of thick book, multi-folded documents and crumpled pages. In such cases, the most common distortion appeared is warping text lines. In this paper, we present a survey and a comparative study of document image dewarping techniques which aim to solve the curled lines and geometric distortion problems. We introduce a new classification of the available dewarping document image techniques and investigate their available datasets. Finally, we present the evaluation metric to test these techniques.
Culturally Themed Educational Tools for Enhancing Learning in Southeast Asian Secondary Schools

The paper is part of a multi-country analysis and uses two countries in an initial study and a benchmark to identify how culture can improve learning outcomes with redesigning technological tools for Southeast Asian secondary schools. This paper presents two studies: The first study focuses on assessing the impact of cultural attributes in digital tools used in classroom learning among teachers and students in Malaysian and Indonesian secondary schools with 168 teachers and 491 students. The results reveal low use of technology and digital tools in classroom activities by teachers, and both the Malaysian and Indonesian data show similar results of low usage technology tools (never to monthly). This finding contradicts the United Nations Educational, Scientific and Cultural Organization’s (UNESCO) 2012 statistics, according to which Malaysia is at 91% in terms of information and communications technology (ICT) infrastructure in schools with Internet access. The second study was designed to test a culturally themed prototype with 84 students in Jakarta, Indonesia, which resulted in improved learning outcomes among students who participated in an experiment using a ‘festive cultural theme’ activity based on a mobile game. The study suggests, Southeast Asian schools to use technology with cultural theme to stimulate classroom activities.
Research on the Cultural Shaping and Value Realization Path of Digital Media Art Based on Multimedia Technology

Abstract With the development of computer multimedia technology and the application of wireless Internet technology, digital media art is a new art form constantly creating new miracles in the art field. Although many traditional artists still have doubts about the artistic expression of digital media, but it can’t stop digital media showing its pride in the new media and art platforms. Based on digital technology and modern media, this new art form combines perceptual thinking with rational thinking. At the beginning of the digital media birth, it showed extraordinary cultural charm and artistic tension. This paper mainly studies the cultural shaping and value realization of digital media art, and the goal is to promote the value of digital media.
Multi-view Clustering via Multiple Auto-Encoder

Multi-view clustering (MVC), which aims to explore the underlying structure of data by leveraging heterogeneous information of different views, has brought along a growth of attention. Multi-view clustering algorithms based on different theories have been proposed and extended in various applications. However, existing of most MVC algorithms are shallow models. They learn structure information of multi-view data by mapping multi-view data to low-dimensional representation space directly, which ignore the Non-linear structure information hidden in each view. This weakens the performance of multi-view clustering to a certain extent. In this paper, we propose a multi-view clustering algorithm based on multiple Auto-Encoder, named MVC-MAE, to cluster multi-view data. MVC-MAE algorithm adopts Auto-Encoder to capture the non-linear structure information of each view in a layer-wise manner. To exploit the consistent and complementary information contained in different views, we also incorporate the local invariance within each view and consistent and complementary information between any two views. Besides, we integrate the representation learning and clustering into a unified step, which jointly optimizes these two steps. Extensive experiments on three real-world datasets demonstrate a superior performance of our algorithm compared with 13 baseline algorithms in terms of two evaluation metrics.
Enhancing the Feature Retrieval Process with Scoping and Tool Support

Software Product Lines (SPLs) are commonly adopted with an extractive approach, by performing a reengineering process in legacy systems, when dealing with variability and reuse became challenging. As a starting activity of the process, the legacy systems are analyzed to retrieve, categorize, and group their features in terms of commonality and variability. Due to the importance of this feature retrieving, we proposed the Prepare, Assemble, and Execute framework for SPL reengineering (PAxSPL). PAxSPL aims at guiding users to customize the feature retrieval for their scenario. In an initial evaluation of the PAxSPL in a real-world scenario, we could observe the need for including scoping activities and implementing a tool to make the framework more adoptable in practice. In this paper, we describe how we performed these improvements. We performed the evolution of PAxSPL by including SPL scoping concepts and activities into our framework as well as developing a supporting tool. We also conducted a pilot study to evaluate how PAxSPL allows instantiating a scenario where the SPL reengineering were conducted. The results show that all artifacts, activities, and techniques from the scenario could be properly represented. However, we also identified a potential limitation during the assembly of techniques regarding parallel activities. The main contribution is PAxSPL_v2 that makes the framework more adherent to industries performing the reengineering of legacy systems into SPLs.
N-way Diff: Set-based Comparison of Software Variants

Software is frequently developed in many similar copies, called forks or cloned software variants. During this development, pairwise comparison is routinely used for finding differences between the cloned copies, assessing their similarity, and merging the content. However, analyzing the similarity of a large group of variants using pairwise comparison is a relatively difficult task, as the number of compared pairs grows quadratically with the number of variants. Furthermore, the result of such group of pairwise comparisons is difficult to visualize. In this paper, we discuss the problem of N-way comparison of cloned software variants. We represent the N-way comparison result as a model of N intersecting sets. By aggregating the sets along the system decomposition hierarchy, we construct the sets at every level of the system structure (files, folders, and whole systems). We define a generalized approach for set model construction, and instantiate it for an N-way diff on the textual code representation. We propose set-based visualizations for the N-way comparison, which scale for more than ten component variants and MLOC-sized components. We evaluate the approach by applying it to several groups of industrial software system variants and by performing a controlled experiment with a comparison of 5 software forks. In the experiment, the group using set-based comparison solved the tasks in 58% less time and with 92% fewer incorrect answers than the group using pairwise comparison. Finally, we propose a generalization of the approach beyond software, to enable set-based comparison and similarity visualization for hierarchically structured models and data, for example genomes.
Credit Card Fraud Prediction and Classification using Deep Neural Network and Ensemble Learning

The use of credit card has increased dramatically as a mode of payment in current times. As the number of credit card user is rising the frauds and identity thieves are also increasing. However, the prediction of if a transaction is faulty is a challenging task for banks. In this manuscript we are comparing predictive accuracy of the customer&#x0027;s default payment using Ensemble learning. We are going to create a model and use that model to predict which transaction is faulty. Moreover, we have applied four algorithms (Na&#x00EF;ve Bayes Classifier Algorithm, Logistic Regression, Decision Trees and Deep Belief Network) to the dataset and then used ensemble learning to get the final result. We compare our study with the result of ensemble learning using three algorithms (Na&#x00EF;ve Bayes Classifier Algorithm (Gaussian), Logistic Regression, Decision Trees) applied to the same dataset. The results of this paper will indicate the significance of deep belief network algorithm and that our proposed model which is ensemble learning combining the four algorithms perform better in predicting the default of credit card clients and portrays extreme precision.
Computer Aided Fracture Diagnosis Based on Integrated Learning

Fracture refers to the complete or partial rupture of bone structure, which requires accurate diagnosis by orthopedic surgeons and treatment methods. Therefore, it is of great significance to study automatic fracture detection. In this paper, in order to solve the problem of low accuracy of fracture image determination caused by incomplete feature extraction of traditional features, a deep learning method is used to build a convolutional neural network model framework, and a fracture image detection method based on deep features and integrated learning is proposed. Using data enhancement to preprocess the MURA image data set, when extracting image features, Alexnet is used as a feature extractor to obtain sufficiently effective image features, and when training the classifier, the idea of integrated learning in machine learning is adopted. Train the classifiers after feature extraction, and give them different weight values according to the contribution of each classifier, to achieve better performance than a single classifier, and improve the accuracy of image classification. The experimental results of this method on the MURA data set show its good classification performance.
The Inverse Edit Term Frequency for Informal Word Conversion Using Soundex for Analysis of Customer’s Reviews

Background: E-commerce/ M-commerce has emerged as a new way of doing businesses in the present world which requires an understanding of the customer’s needs with the utmost precision and appropriateness. With the advent of technology, mobile devices have become vital tools in today’s world. In fact, smart phones have changed the way of communication. The user can access any information on a single click. Text messages have become the basic channel of communication for interaction. The use of informal text messages by the customers has created a challenge for the business segments in terms of creating a gap pertaining to the actual requirement of the customers due to the inappropriate representation of it's need by using short message service in an informal manner. Objective: The informally written text messages have become a center of attraction for researchers to analyze and normalize such textual data. In this paper, the SMS data have been analyzed for information retrieval using Soundex Phonetic algorithm and its variations. Methods: Two datasets have been considered, SMS- based FAQ of FIRE 2012 and self-generated survey dataset have been tested for evaluating the performance of the proposed Soundex Phonetic algorithm. Results: It has been observed that by applying Soundex with Inverse Edit Term Frequency, the lexical similarity between the SMS word and Natural language text has been significantly improved. The results have been shown to prove the work. Conclusion: Soundex with Inverse Edit Term Frequency Distribution algorithm is best suited among the various variations of Soundex. This algorithm normalizes the informally written text and gets the exact match from the bag of words.
On the Vulnerability and Generality of K–Anonymity Location Privacy Under Continuous LBS Requests

With the development of personal communication devices, location-based services have been widely used. However, the risk of location information leakage is a fundamental problem that prevents the success for these applications. Recently, some location-based privacy protection schemes have been proposed, among which K-anonymity scheme is the most popular one. However, as we empirically demonstrated, these schemes may not preserve satisfactory effect in trajectory-aware scenarios. In particular, we propose a new attack model using public navigation services. According to the empirical results, the attack algorithm correlates a series of snapshots associated with continuous queries, eliminating some of the less likely routes, and seriously undermining the anonymity of the query, thereby increasing the probability of attack. In order to defend against the proposed attacks, two enhanced versions of K-anonymity mechanism are proposed for this attack model, which further protects the user’s trajectory privacy.
Equivalence of the Classical Rubber Hand Illusion and the Virtual Hand Illusion

Computer technologies implementation into the body illusions research is increasing because they allow to controllably model complex processes that cannot be realised in ordinary life. It was previously demonstrated that the rubber hand illusion may be reconstructed in the virtual setting and cause similar changes in the somatoperception when the virtual hand begins to feel like your own. This result suggests that the phenomenological experience obtained in the classical illusion and in its virtual reality version has much in common. However, a direct experimental comparison of the two illusion variants has not been made, therefore, in this research we studied the equivalence of the rubber and virtual hand illusions (RHI and VHI). The sample consisted of 16 subjects (18—25 years). As registration methods we used a subjective sense of ownership of an artificial limb and the proprioceptive drift of the real hand towards the illusory hand. The analysis has proved the equivalence of illusions.
Tell Me About Your Day: Designing a Conversational Agent for Time and Stress Management

Growing interest in applications of AI in healthcare has led to a similarly elevated interest in fully integrated smart systems in which disparate technologies, such as biometric sensors and conversational agents, are combined to address health problems like medical event detection and response. Here we describe an ongoing project to develop a supportive health technology for stress detection and intervention and discuss a pilot application for one component, the conversational agent.
Creation of a Cost-Efficient and Effective Personal Assistant Robot using Arduino &amp; Machine Learning Algorithm

This paper represents a personal assistant robot called Metacarpus. This shows one of the modern implementations of such revolutionary project which not only showcases a regular assistant, whereas, it has been designed to be controlled by the user's voice, recognize his instruction and assist any disabled people in any type of endangerment, to accompany him/her in any difficult situation where they can't handle themselves. In this project, Metacarpus was designed with a well-engineered mechanical design. It speaks with people, understands the owner, and recognizes people's faces& voices. It can do all works which a secretary is doing, including medical operations, army carrier, path detector for the disabled, etc. Metacarpus is a convenient, handy, transportable, and intelligent robot. We used Arduino UNO Microcontroller, Raspberry Pi, Motor Drivers, Buck Converters, DC Motors, Servo Motors, Actuators, and other miscellaneous electrical components in this project. This project uses an efficient Neural Network algorithm to detect objects with high accuracy. It is showing positive results in making autonomous decisions, recognizing users, and making intelligent decisions by themselves.
Word Cloud Analytics of the Computer Science Research Publications’ Titles over the Past Half Century

The field of computer science is becoming increasingly important as almost every aspect of our lives is more and more dependent on computers and the Internet. As a result, computer hardware and software technology are rapidly increasing in power and sophistication. Consequently, the data and the research topics and publications in this field are also evolving rapidly. In this study we used the data form the Computer Science Bibliography DBLP database for the research publications in the field of Computer Science the past 50 years. Further on, we analyze the articles (journal publications) and proceedings as categories with larger numbers of entries and that provide more significant outcomes. The overall dataset is split in decades and for better demonstration of the information and the evolving topics, text visualization tool was applied.The results generated by using word clouds provide a much faster and easier way to detect the topics and other changing details about the publications in each decade of the past half century.
THE MODAL LOGICS OF KRIPKE–FEFERMAN TRUTH

Abstract We determine the modal logic of fixed-point models of truth and their axiomatizations by Solomon Feferman via Solovay-style completeness results. Given a fixed-point model $\mathcal {M}$ , or an axiomatization S thereof, we find a modal logic M such that a modal sentence $\varphi $ is a theorem of M if and only if the sentence $\varphi ^*$ obtained by translating the modal operator with the truth predicate is true in $\mathcal {M}$ or a theorem of S under all such translations. To this end, we introduce a novel version of possible worlds semantics featuring both classical and nonclassical worlds and establish the completeness of a family of noncongruent modal logics whose internal logic is nonclassical with respect to this semantics.
Exploiting Extended Reality Technologies for Educational Microscopy

Exploiting extended reality technologies in laboratory training enhances both teaching and learning experiences. It complements the existing traditional learning/teaching methods related to science, technology, engineering, arts and mathematics. In this work, we use extended reality technologies to create an interactive learning environment with dynamic educational content. The proposed learning environment can be used by students of all levels of education, to facilitate laboratory-based understanding of scientific concepts. We introduce a low-cost and user-friendly multi-platform system for mobile devices which, when coupled with edutainment dynamics, simulation, extended reality and natural hand movements sensing technologies such as hand gestures with virtual triggers, is expected to engage users and prepare them efficiently for the actual on-site laboratory experiments. The proposed system is evaluated by a group of experts and the results are analyzed in detail, indicating the positive attitude of the evaluators towards the adoption of the proposed system in laboratory educational procedures. We conclude the paper by highlighting the capabilities of extended reality and dynamic content management in educational microscopy procedures.