Reviewerly/exHarmony huggingface dataset:
Interdisciplinarity of Information Science Research: Introduction

Purpose/Thesis: The article aims to present and discuss some introductory reflections on the nature of interdisciplinarity of research conducted in the field of information science and its effect on the reorganization of the institutional setting of the discipline.Approach/Methods: This is a conceptual review article based on theoretical considerations and critical analysis of the concept of interdisciplinarity and the features of interdisciplinary approaches employed in information science research and its effect on the position of information science in university structure.Results and Conclusions: The concept of interdisciplinarity is discussed with reference to two aspects of the development of science: specialization and integration. The article presents selected typologies of interdisciplinarity and discusses the changes in the perception of the concept of discipline. Interdisciplinarity has been discussed as an inherent feature of information science. The types of interdisciplinarity that best correspond to the specificity of the interdisciplinary approach used in information science research has been indicated. Referring to previous studies, the article sketches the most characteristic interdisciplinary connections of information science. In general, the review shows that apart from the permanent relationship with social sciences, in particular with library science and computer science, the relationships between information science and other disciplines are variable and quite loose. Stronger relationships are most often generated through practical activity in related disciplines, in which specialized information services are the most developed and widely used.Originality/Value: The view that information science is by its very nature an interdisciplinary field of research is common among information researchers and information professionals. Much research has been done on the interdisciplinary connections of the discipline, however, by the best author’s knowledge, few of them analyzed the specificity of interdisciplinarity of this field of research. This article attempts to initiate an in-depth discussion on this issue.
Diagnostic Performances of the Susceptibility Vessel Sign on MRI: Methodological Issues

To the Editor Diagnostic Performances of the Susceptibility Vessel Sign on MRI for the Prediction of Macroscopic Thrombi Features in Acute Ischemic StrokeJournal of Stroke and Cerebrovascular DiseasesVol. 29Issue 11PreviewIn 20%–40% of cases the etiology of acute ischemic stroke (AIS) remains uncertain despite complete diagnostic investigation.1 Correlations between the histological microscopic features of the thrombus and the TOAST (Trial of Org 10 172 in Acute Stroke Treatment) categories have been found.2–5 However, from the macroscopic point of view, only one case report has considered the chromatic visual aspect of the retrieved thrombus.6 Recently, the “white” visual aspect of the thrombus at the moment of withdrawal has been related to atypical etiologies, in particular infective endocarditis. Full-Text PDF
Weighted LDA Using Metadata for Extracting Topics Needed by Teachers

This paper proposes a method for weighted latent Dirichlet allocation (LDA) using metadata for extracting topics with latent needs by teachers. The proposed method enables us to identify and display contents needed by teachers. Specifically, by improving the original LDA through weighting of word frequencies using metadata that reflects teachers' needs (e.g. Likes), the proposed method enables extraction of topics that are not only common to many contents but also needed by teachers. Experiments using contents on Forestanet, i.e., the largest Web service for teachers in Japan, verify the effectiveness of the proposed method.
Encrypted Traffic Categorization Based on Flow Byte Sequence Convolution Aggregation Network

Traffic categorization aims to classify network traffic into major service types. A modern deep neural network based on temporal sequence modeling is proposed for encrypted traffic categorization. The contemporary techniques such as dilated convolution and residual connection are adopted as the basic building block. The raw traffic files are pre-processed to generate 1-dimensional flow byte sequences and are feed into our specially-devised network. The proposed approach outperforms other existing methods greatly on a public traffic dataset.
3D tracking system at maximum solar emissivity with microcontroller

In this paper a smart real-time tracking and positioning for a solar cell or solar panel in order to maximize the solar energy recovered from the electromagnetic radiation from the Sun. The idea of the paper is to use a mathematical transform from the Cartesian coordinates to spherical coordinates, with the mechanical part implementation based on two changes (the azimuth change and angular change) using two actuators, made of precision stepper motors. The system will position and correct the positioning of the solar panel by reading in real-time the instantaneous current on a test load (different from the real charging circuit load), the current is digitized using the internal analog to digital convertor of a microcontroller and stored in a memory buffer. The position for the maximum solar electromagnetic radiation that can to reach the solar panel is determined by periodic scanning for the maximum generated current. In order to scan for the maximum current, the solar cell's orientation is changed for the horizontal angle and azimuth. The solar panel will be rotated in small increments a few degrees in both directions and the instantaneous current will be recorded along with the orientation. The rotations will be for the horizontal angle and azimuth (up and down). A two steps algorithm is used to determine each local maximum. The first step determines the average component using the analog to digital convertor with lower resolution. The second step involves a higher resolution search in the vicinity of the maximum from step one. The higher resolution current data will be stored in a memory buffer along with the corresponding horizontal position and azimuth. With the latest current data and the values stored in the memory buffer, the microcontroller will perform corrections to the position of the solar panel.
Sorting Algorithms and Their Execution Times an Empirical Evaluation

One of the main topics in computer science is how to perform data classification without requiring plenty of resources and time. The sorting algorithms Quicksort, Mergesort, Timsort, Heapsort, Bubblesort, Insertion Sort, Selection Sort, Tree Sort, Shell Sort, Radix Sort, Counting Sort, are the most recognized and used. The existence of different sorting algorithm options led us to ask: What is the algorithm that us better execution times? Under this context, it was necessary to understand the various sorting algorithms in C and Python programming language to evaluate them and determine which one has the shortest execution time. We implement algorithms that help create four types of integer arrays (random, almost ordered, inverted, and few unique). We implement eleven classification algorithms to record each execution time, using different elements and iterations to verify the accuracy. We carry out the research using the integrated development environments Dev-C++ 5.11 and Sublime Text 3. The products allow us to identify different situations in which each algorithm shows better execution times.
A Decadal Walkthrough on Energy Modelling for Cloud Datacenters

Cloud computing is the growing field in the industry, and every scale industry needs it now. The high scale usage of cloud has resulted in huge power consumption, and this power consumption has led to increase of carbon footprint affecting our mother nature. Thus, we need to optimize the power usage in the cloud servers. Various models are used to tackle this situation, of which one is a model based on link load. It minimized the bit energy consumption of network usage which includes energy efficiency routing and load balancing. Over this, multi-constraint rerouting is also adapted. Other power models which have been adapted are virtualization framework using multi-tenancy-oriented data center. It works by accommodating heterogeneous networks among virtual machines in virtual private cloud. Another strategy that is adopted is cloud partitioning concept using game theory. Other methods that are adopted are load spreading algorithm by shortest path bridging, load balancing by speed scaling, load balancing using graph constraint, and insert ranking method.
Notare e far notare la bellezza del testo: il punto di vista di alcuni glottodidatti arabi sul gusto letterario

Abstract The role of literary taste ( taḏawwuq adabī ) in the learning and teaching of Arabic as a Foreign Language is an aspect needing further investigation nowadays, especially in non-Arab research environments. In this sense, the present contribution explores the debates on literary taste put forth by some significant Arab scholars and educators, and the resulting theories on the role of the Arabic language teacher and teaching philosophies. It puts them in connection with contemporary orientations in the field of modern language teaching ( i.e . peer tutoring, holistic techniques and autonomy in language learning) not avoiding reporting some unique features ( e.g . representation, good pronunciation, etc.) that enrich the discourse on literary taste and its implications in the teaching practice.
ANTHROPOLOGIZATION OF SCIENCE: FROM THE SUBJECT OF COGNITION TO THE RESEARCHER’S PERSONALITY

Purpose. With the consideration of anthropological tendencies in modern science, the purpose of the article is to analyze the problem of the subject of cognition, philosophical-psychological rationale for the need to complement it by the concept of "the researcher’s personality". Theoretical basis. The authors rely on post-non-classical methodological tools and basic principles of complexity theory (autopoiesis, auto-eco-organization, synergy, syzygy, targeted and cyclic determination), as well as theoretical provisions of epistemological constructivism (enactivism), the results of theoretical and empirical psychological studies. In them, authors revealed psychological features of the potential of self-realization of a person prone to innovation and research activities and transfessionalism, including the resources and reserves of the researcher’s personality. Originality. The concept of the subject of (scientific) cognition is expanded by the concept of "researcher’s personality" and derivative concepts that describe the dynamics of self-harmonization of originative co-generative strengths and opportunities of self-realization of an enlightened person, reveal the degree of correlation in the cognition of the subjective and objective dimensions of his life. It is substantiated that further analysis of the problem of anthropologization of science requires appropriate onto-epistemological grounds that reveals the unity of cognition-education-skill as an essential characteristic of the maturity of the researcher’s personality of scientific knowledge. Conclusions. In the context of anthropological shifts in modern science, the philosophical-psychological analysis of the problem of the subject of cognition is actualized. The psychological research proves the advisability of using the "researcher’s personality" concept as a basic one for understanding the formation of an enlightened human-creator, capable of auto-eco-organization, self-transcendence, and syzygy with the Universe at different levels of innovational research activity. The self-realization of the researcher-personality is a way-search for the authenticity of the multiform unity of life, the personal meaning of scientific truth, and the self-harmonization of the originative co-generative co-determinative strengths in the knowledge of an enlightened person. Including the concept of the subject of cognition in the ontology of the unity of difference-multidimensional poly-essential autopoetic integrity, the anthropologization of science is intended to revive the ancient idea in the unity of truth ("ἀλήθεια"), education ("παιδεία") and skill ("τέχνη") of a scientist, defining the ideal of a modern human-transfessional.
Light Weight Automatic Modulation Classification for Edge Devices in Spectrum Sensing Wireless Networks

With the aid of software-defined radio (SDR) technologies, the recent progress in automatic modulation classification of high accuracy using deep neural networks (DNNs) may play an increasingly important role in spectrum monitoring. However, the computational demand brought by the stochastic gradient descent method in the training process is unbearable in edge devices. In this paper, we proposed a lightweight trained neural network for an Internet of thing (IoT) chip by separating the learning process from the inference process. Besides, we analyzed the influence of the size of the convolution kernel and the length of the sampling samples on the calculation and memory usage of the neural network Experimental results on actual datasets show that the proposed network occupies about 700kb of memory, and requires a single sample floating-point operation per second (FLOPs) of about 400k, while achieving high accuracy of 95.58% at a signal-to-noise ratio (SNR) from -10 to 19dB.
Exploration of the Security of Free Data Encryption Applications for Cloud Storage

Abstract Cloud storage has become an urgent need in the digital age, especially for companies with high level of work collaboration and mobile workers. To prevent data in cloud storage from being accessed illegally, the data must first be encrypted before being uploaded. However, encrypting data separately with cloud data storage media is considered to be less efficient and less secure. To that end, several data encryption applications designed specifically for cloud storage appeared in the market. However, which application is suitable for your requirement, needs to be further investigated. For this premise, in this research, an exploratory study of the security of several free applications of data encryption called Boxcryptor, Cryptomator, and nCrypted Cloud was conducted based on security parameters defined in ISO/IEC 25010. The results showed that two of five security parameters, integrity, and authenticity, are not satisfied by all the applications being reviewed, but Cryptomator outperformed the other two applications.
An implementation of SM4 algorithm based on mask

Abstract Aiming at the problem of SM4 algorithm resisting power attack, this paper studies the implementation structure and S-box characteristics of SM4 algorithm, constructs the S-box realized by multiplication mask, and designs a semi random mask circuit implementation scheme of SM4 algorithm. In this scheme, the middle values of the first six rounds and the last six rounds of SM4 algorithm are completely random masked, and the intermediate values of the middle 24 rounds are fixed mask, which reduces the consumption of random masks. After security analysis, the scheme can resist the first-order power consumption attack, and has less random number consumption and lower implementation area.
Locomotive and Cognitive Trade-Offs for Target-based Travel

Target-based travel has become a common travel metaphor for virtual reality (VR) applications. Three of the most common target-based travel techniques include Point-and-Instant-Teleport (Teleport), Point-and-Walk-Motion (Motion), and Automatic- Walk-Motion (Automatic). We present a study that employed a dual-task methodology to investigate the user performance characteristics and cognitive loads of the three target-based travel techniques, in addition to several subjective measures. Our results indicate that the Teleport technique afforded the best user travel performances, but that the Automatic technique afforded the best cognitive load.
Efficient fair conjunction for structurally-recursive relations

We present a new, fair, conjunction evaluation strategy for relational programming language miniKanren. Unlike the original left-biased conjunction, our approach controls the order of conjunct execution based on the intrinsic properties of relation definitions. We present both the formal study of conjunction fairness and practical evaluation, which demonstrates the essential improvement in terms of both performance and convergence.
E-Commerce application for selling “Blue Salt” products and general fish maintenance tools for koi fish treatment

Abstract In maintaining koi fish, extra care is needed and must be done carefully. The use of information systems in the sale of fish care products is needed for marketing and sales development. This study aims to evaluate the influence of website applications for the sale and marketing of products from “Blue Salt”. Data collected by conducting interviews with the owner of “Blue Salt”. This website application provides information about “Blue Salt” products and makes it easy for customers to place an order. because this web site application can be opened anywhere and anytime, customers are able to find out information about the products sold and can buy products without having to come directly to the store. This web application also hopes to help the owners of “Blue Salt” to market their products and expand their markets.
Patenting Blockchain: Mitigating the Patent Infringement War

The blockchain web platform, most famous for its use in support of Bitcoin, is a sophisticated and unique technology, which many believe is the next disruptive technology that will span across a vast range of industries. Scholars identified more than ten features of this technology that makes it, like no other: open-ledger, encrypted, everlasting, accessible to all, enables peer to peer transactions, fast, global, trustworthy, decentralized, consensus mechanisms, and irreversible. By embracing all of these features, blockchain technology offers an alternative tool to traditional multi-player economic models for conducting transactions without the necessity of relying on third parties.This article addresses the misperception of blockchain, perceiving it, similarly to the common understanding of the Internet, as an open platform, accessible to the public, with free entry and most important, in the public domain. Hardly anyone thought to consider protected intellectual property (IP) rights in regard to this technology, that was coined democratic. However, this concept, that there is only one public domain blockchain platform that serves all or that blockchain platforms are free from any IP rights is false. This article alleges, for the first time, that unlike the common perception, not only is blockchain technology patentable, but the U.S. Patent Office granted patents in blockchain platforms and keeps on examining inventions of new and different types of blockchain technologies. This false assumptions may be based on misunderstanding the technology of different types of blockchain platforms or on the legend about the unknown figure, entity or artificial intelligence (AI) system, named Satoshi Nakamoto, who mysteriously created the technology and donated this platform technology, in 2009, without identifying him/her/itself, for the benefit of society.Additionally, this paper innovatively takes a step further and investigates, the implications of patent law concerning blockchain technology, in order to unveil the emerging risks of patent infringements, which users are unaware of while naively using blockchain platforms. By understanding the peer-to-peer multi-player structure of these platforms, one can evaluate the threat the inevitable patent infringements may cause. This article further argues that this threat will become more crucial and weighty with the rising popularity of blockchain platforms. Finally, this research not only points out unexpected legal and economic risks, but also proposes a simple solution to mitigate this potential patent minefield.
VM Migration for Secure Out-of-band Remote Management with Nested Virtualization

Infrastructure-as-a-Service clouds provide out-of-band remote management of the systems in virtual machines (VMs). This management method enables users to manage their systems even on several types of failures inside VMs. In this method, users access virtual devices of their VMs, but virtual devices are not sufficiently protected against untrusted cloud operators. For secure out-of-band remote management, previous work securely runs shadow devices outside an untrusted virtualized system using nested virtualization. However, the states of shadow devices are lost during VM migration. In this paper, we propose USShadow for continuing secure out-of-band remote management after VM migration. USShadow enables the migration manager inside the virtualized system to transparently and securely save and restore the states of shadow devices outside it. We have implemented USShadow, which supports Xen and KVM as virtualized systems. Then, we confirmed that USShadow could continue virtual serial console and that the migration overhead was negligible.
Vehicle Identification in Haze Based on V-System and Dense Convolution Network

Haze increases the possibility of accidents. Therefore, it is important to improve the accuracy of the vehicle identification system in such a situation. This research proposes an image pre-processing algorithm for the system. Firstly, the accuracy is enhanced by the Single Scale Retinex algorithm. Secondly, the pictures are processed by V-system processing. Finally, the pre-processed pictures are identified by dense convolution network. The results show that the algorithm's accuracy is 0.93% higher than the traditional method.
Generative Adversarial Network for Robust Regression using Continuous Dataset

Recently, advanced neural network, which is implementing technical method, has focus on dealing with image classification problems. Unlike classification problems, regression provides a value of output in complex and sophisticated continuous datasets. Though nonlinear models can perform regression better than linear model as Linear Regression(LR), the difficulty to make robust model still remain. In this paper, our purpose is to design training architecture for robust regression. We approach Neural Network known as nonlinear regression to solve limitation of Linear Regression. Additionally, Our architecture uses a new artificial Neural Network(NN) based on adversarial architecture by using the Generator(G) and Discriminator(D). The Discriminator shows the better performance while competing with the Generator and learning regression problem as same time. In evaluation experiments, we compare our proposed model with baseline models including Linear Regression and Neural Network using continuous real world data. We split four datasets into train and test sets as 90:10 and evaluate them by using Mean Squared Error(MSE) function. In summary, our model trained with Generative Adversarial Network(GAN) shows better performance than the baseline models.
Vision-based 2D Vibration Displacement Measurement of Hoisting Vertical Rope in Mine Hoist

In this paper, a non-contact, unmarked computer vision measurement method is presented and applied to measure the two-dimensional (2D) vibration displacement of hoisting vertical ropes. In this method, the primary work is to perform camera calibration of monocular vision using a neural network (NN) model. Then, in the image sequence, a straight line perpendicular to the hoisting rope is added by digital image processing (DIP) method, and their intersection region is regarded as the measuring target. Digital image correlation (DIC) algorithm at sub-pixel level is applied to locate the measuring target in image sequence. This method is used to measure the vibration displacement of an actual hoisting rope in mine, and the measurement results of three targets on the rope are consistent with tiny amplitude differences, which indicates that this method is feasible for the vibration measurement of hoisting vertical rope.