Reviewerly/exHarmony huggingface dataset:
Penerapan Data Mining pada Tata Letak Buku Di Perpustakaan Sintong Bingei Pematangsiantar dengan Metode Apriori

The library is a place that has a large collection of knowledge books, magazines and other media that are arranged or arranged in a certain way so that it is easy for users to use properly and well. In placing books in the library, books are placed according to the book category given the numbering. However, the placement of books has not been regulated by looking at the level of books that are often borrowed and many visitors find it difficult to find books that are often borrowed. So it is necessary to create a system using a priori data mining method to determine the pattern of book layout arrangement in the library, this system can help to make it easier to determine the layout of the book as needed. Based on the results of the implementation of RapidMiner, the highest combination pattern of library book layout is Pure Science and Social Sciences with 50% support and 86% confidence. General Works and Pure Science were obtained with 41% support and 83% confidence. Furthermore, Public Works and Social Sciences with 41% support and 83% confidence.
Special Issue on Applied Machine Learning

Machine learning (ML) is one of the most exciting fields of computing today [...]
Sistem Informasi Pengolahan Data Atlet Berbasis Web Pada Disporabudpar Tangerang

Information system needs cover almost all areas of life. Accurate, fast, and relevant information is needed in organizations. But in reality, due to the lack or limited use of information systems, sometimes it is not in sync with the wishes and expectations that are to be realized. Disporabudpar Tangerang Regency is an organization that needs to develop information technology that can change its data processing. The athlete data processing system at Disporabudpar is still in the form of manual files using documents and the stored data is still in the form of Ms. Word and Excel. This can slow down the process of inputting and processing data as well as the risk of errors and inaccuracies in writing which can cause the reporting process to take a lot of time. The research analysis method uses Waterfall and Unified Modeling Language (UML) as a design method based on the PHP programming language with MySQL database. Due to the above, a web-based athlete data processing information system is needed to be implemented at the Tangerang Disporabudpar.
SISTEM ANALISA ASET KENDARAAN DINAS KOPERASI USAHA KECIL DAN MENENGAH BERBASIS WEB

This study, entitled Web-Based Small And Medium Business Cooperation Vehicle Asset Analysis System aims to create a computerized system for managing vehicle asset management in which the vehicle assets are still manual. The system design method used is using the waterfall method. The tools used by front end developers use Javascript, CSS and Html, while back end developers use PHP, and the web server uses Xampp. The results of this research can make it easier to record data on official vehicles and manage them in the office of small and medium enterprises cooperatives.&#x0D; &#x0D; Keywords : Accounting Information, System, Asset, Website
Underwater Image Enhancement Techniques: An Exhaustive Study

Abstract: This paper discusses the various different techniques and their comparative study that will help us for improving underwater image enhancement, These underwater images usually suffer from motion blur effect due to turbulence in the flow of water and non-uniform illumination and limited contrast, Due to the presence of distortion captured underwater image needs to be processed in different ways because the underwater images captured in deep low light environment are of worst quality and these images are low contrast, cause blurring effect, limited range visibility, low contrast, hazy, light transportation is very less, scattering, absorption, noise, natural light absorption, dispersion, color variations, clarity of image is reduced, absence of natural colors, quality of the image degrades and these underwater images cannot be directly used for various computer vision techniques, experiments, object tracking system, scientific research, marine biology research, underwater vehicles, detecting system, counting system, submarine operations, underwater navigation system, disaster prevention system, maintenance of oil rigs. When captured in the underwater environment as compared to images from a clearer environment, The turbid nature of water due to the presence of particles such as minerals, salt, sand, planktons is the major obstacle in the area of underwater research. These particles produce haziness in the deep underwater captured images and it is suitable for use and many other fields. Different methods made for processing of these underwater images there are different filtering techniques, enhancement techniques preprocessing and image restoration techniques are available and some of them are discussed in this paper with their results. Keywords: Underwater Image, Image Enhancement, Image Dehazing, Light Scattering, Filtering Technique, Pre-processing Technique, Haze Environment, Multi-scale wavelet.
Critical Understanding of Security Vulnerability Detection Plugin Evaluation Reports

Integrated development environment (IDE) plugins aimed at detecting web application security vulnerabilities can help developers create secure applications in the first place. Most of such IDE plugins use static source code analysis approaches. Although several empirical studies evaluated the plugins and compared their precision and recall of detecting web application security, few follow-up studies tried to understand the evaluation results. We analyzed more than 20,000 vulnerability reports based on 7,215 distinct test cases spanning 11 categories of web application vulnerabilities to understand the evaluation results of three open-source IDE plugins, namely, SpotBugs, FindSecBugs, and Early Security Vulnerability Detector (ESVD), which aimed at detecting security vulnerabilities of Java-based web applications. Our results identify many factors besides the source code analysis approach that can dramatically bias the detection performance. Based on our insights, we improved the studied plugins. In addition, our study raises the alarm that, without solid root cause analyses, the evaluation and comparisons of security vulnerability detection approaches and tools could be misleading. Thus, we proposed a guideline on reporting the evaluation results of the security vulnerability detection approaches.
Popular online libraries with Ukrainian content

New historical stage of development of society in the XXI century determines the need for transformation of scientific and practical activity of modern scientific libraries, improvement and development of certain provisions of library science, harmonization of library theory and practice with the basic requirements of the modern online community. The outlined problems should be facilitated by the Law of Ukraine "On the National Program of Informatization" (№ 74/98-BP of February 4, 1998), which regulates the processes of providing citizens and society with timely, reliable and complete information through the widespread use of Internet technologies. The place, role and prospects of functioning in the information space of electronic libraries with Ukrainian-language content are investigated in the article. The ten most popular modern libraries are reviewed by their structure, tasks, content and content, openness of information and more. A brief overview of the works of Ukrainian researchers and the UNESCO-approved European Digital Heritage Charter is presented.The issue of creating online libraries is topical, and therefore, in the information and library environment, various aspects of their activity are being actively studied. First of all, it is important to pay attention to the connection of electronic libraries with the educational needs of high and high school students. Today, virtual library resources are one of the most productive areas for digital technology development, and we can confidently predict their intense development in the near future.
Implementation of ACPO Framework for Digital Evidence Acquisition in Smartphones

A forensic investigator or analyst should implement an appropriate digital forensic framework to acquire valid digital evidence to be presented at court. Choosing an unsuitable digital forensic framework with the investigation process may lead to failure at acquiring or maintaining complete digital evidence. Missing a step or turning a certain step into another irrelevant step may lead to unclear results and invalid conclusions. Digital evidence extracted from risky electronic evidence cannot be accepted by the court. Accordingly, a forensic investigator or forensic analyst should refer to a structuralized standard structure to perform well.Several internal digital forensic frameworks are available, one of which is the Good Practice Guide for Computer-based Electronic Evidence [1], an English issuance by ACPO (Association of Chief Police Officers) in cooperation with 7Safe. The digital forensic framework is commonly called the digital forensic framework from ACPO or the ACPO Framework. This research brings into focus the analysis of the percentage of success rate for using the ACPO digital forensic framework or the ACPO Framework in comparison with another digital forensic framework, i.e., NIST Framework. This research is also aimed at examining the performance of a mobile forensic tool, i.e., Cellebrite’s UFED Touch2 in comparison with another mobile forensic tool for digital evidence acquisition in smartphones.The research objects were smartphones containing deleted WhatsApp messages. This research successfully implemented the ACPO Framework for digital evidence acquisition in smartphones using Cellebrite’s UFED Touch2 as the mobile forensic tool.
Assessing the Influence Level of Food Safety Public Opinion with Unbalanced Samples Using Ensemble Machine Learning

Assessing the public opinion on food safety events constitutes an important job of government regulators. To optimize the government’s management of food safety affairs, a promising way is to use artificial intelligence to improve the efficiency of food safety public opinion assessment. In this paper, we model the assessment of public opinion influence as a text classification task. The whole model adopts the ensemble learning framework, and it integrates naive Bayes, support vector machine, extreme gradient boosting, convolutional neural network, long- and short-term memory network, FastText, and BERT classification methods into the framework to form an ensemble learner. The ensemble learner is able to classify textual public opinion into high, medium, and low influence levels by learning from the samples assessed by human experts. To overcome the problem of unbalanced samples, we propose a sample generation method consisting of synonym replacement and semantic filtering to increase the number of high-influence samples. Real public opinion data collected from the Food Safety Department of the Chinese government are used for experiment. Extensive comparison of the proposed method with baseline methods proves the effectiveness of the ensemble learner and the sample generation steps.
Surveillance FPV Drone with Obstacle Avoidance System

The unmanned air vehicle (UAV) is mostly used in inspection and surveillance operations recent. The UAV is also termed as vertical take-off landing (VTOL), since it is capable of vertical take-off and landing without need of a runway. The big tunnels, infrastructure and large bridges are inserted using UAV by photographic inspection. UAVs are also used for surveillance purposes by the military and by the security guards. Since this is a new technology of the last decade, deep research has to be done. UAVS have the cross structure arrangement to which the rotor blades are attached at the end points of cross beams. These rotors are driven by the DC brush motors and motors are powered by the lithium ion rechargeable battery. The working principle of quad- rotors is the same as the chopper by controlling the rpm of each rotor blade, due to which the gyroscopic torque will act and the vehicle will move in the desired direction. To hold the quad- rotor at a stationary position at some height constant rpm of all rotors has to be maintained. This signal is given by the controller from some distance, which is received by the, and then it processes the signal and drives the motor via the flight controller and drives the rotors. A quad- rotor is equipped with a high quality camera for photography and video shooting during surveillance. Since a quad rotor is manoeuvring in air, the wind may exert a drag force and take it along with it and the quad rotor may hit any obstacle or inspection objects. To avoid this, it is equipped with the ultrasonic sensors which is capable of sensing the obstacle and realize collision avoidance between wall or any object.
NaGAN: Nadir-like Generative Adversarial Network for Off-Nadir Object Detection of Multi-View Remote Sensing Imagery

Detecting off-nadir objects is a well-known challenge in remote sensing due to the distortion and mutable representation. Existing methods mainly focus on a narrow range of view angles, and they ignore broad-view pantoscopic remote sensing imagery. To address the off-nadir object detection problem in remote sensing, a new nadir-like generative adversarial network (NaGAN) is proposed in this paper by narrowing the representation differences between the off-nadir and nadir object. NaGAN consists of a generator and a discriminator, in which the generator learns to transform the off-nadir object to a nadir-like one so that they are difficult to discriminate by the discriminator, and the discriminator competes with the generator to learn more nadir-like features. With the progressive competition between the generator and discriminator, the performances of off-nadir object detection are improved significantly. Extensive evaluations on the challenging SpaceNet benchmark for remote sensing demonstrate the superiority of NaGAN to the well-established state-of-the-art in detecting off-nadir objects.
A BOT-ENABLED APPROACH FOR WEB SERVICE DISCOVERY

With the wide adoption of service-oriented architectures, many service-based systems (SBSs) and mashups composed ofWeb services have been developed. Meanwhile, web service discovery, as a crucial component to guarantee the quality ofWeb service
[Research Progress and Application of Digital Pathology Technology in Bone Marrow Morphology].

Advances in digital pathology technology have enabled pathologists and laboratory physicians to perform quick, easy, accurate and reproducible analysis of digital images of tissues and cells with the aid of electronic screens and software tools, rather than relying solely on traditional optical microscopy observations. The conventional clinical cytology testing practice is to be replaced by a digital workflow, which includes both digital imaging and image analysis. This article provides an overview of the basic principles of digital pathology techniques, the advances of development of device in cytology digital pathology, and their clinical applications in bone marrow morphology, and existing problems and prospects of digital pathology application in hematology.
A descriptive analysis of cite units from the perspectives of content and linguistic expressions

Background.While the use of citations for assessing research impact is well-studied, there is little work that investigates the content introduced into the citing documents through citations and the linguistic expressions used to represent the cited contentObjectives.This study analysed the types of content introduced into citing documents using the citations (cited content) and units of linguistic expressions used to represent the cited content.Methods.We classified the expressions representing the cited content according to the unit of linguistic expressions (terms and clauses) and classified the cited content into conceptual categories.We adopted different frameworks for the classification of cited content represented by terms and clauses.The categories for terms were domain specific and the categories for clauses took into account subjectivity and generality.We also described the detailed categories of cited content with examples and provided seven types of cited content for clauses.Results.We found that among the expressions representing cited content, terms constituted about 40% and clauses constituted about 60%.The majority of the cite terms were domain specific; and 35% of the cite terms referred to unique concepts.Of the cite clauses, 50% were objective and term-specific, 40% were objective and general, and 10% were subjective.
Automating the Design of Complex Systems

Abstract This chapter discusses the issue of whether it is possible to automate the design of rather complex workflows needed when addressing more complex data science tasks. The focus here is on symbolic approaches, which continue to be relevant. The chapter starts by discussing some more complex operators, including, for instance, conditional operators and operators used in iterative processing. Next, we discuss the issue of introduction of new concepts and the changes of granularity that can be achieved as a result. We review various approaches explored in the past, such as constructive induction, propositionalization, reformulation of rules, among others, but also draw attention to some new advances, such as feature construction in deep NNs. It is foreseeable that in the future both symbolic and subsymbolic approaches will coexist in systems exhibiting a kind of functional symbiosis. There are tasks that cannot be learned in one go, but rather require a sub-division into subtasks, a plan for learning the constituents, and joining the parts together. Some of these subtasks may be interdependent. Some tasks may require an iterative process in the process of learning. This chapter discusses various examples that can stimulate both further research and some practical solutions in this rather challenging area.
Empirical Analysis of Limits for Memory Distance in Recurrent Neural Networks

Common to all different kinds of recurrent neural networks (RNNs) is the intention to model relations between data points through time. When there is no immediate relationship between subsequent data points (like when the data points are generated at random, e.g.), we show that RNNs are still able to remember a few data points back into the sequence by memorizing them by heart using standard backpropagation. However, we also show that for classical RNNs, LSTM and GRU networks the distance of data points between recurrent calls that can be reproduced this way is highly limited (compared to even a loose connection between data points) and subject to various constraints imposed by the type and size of the RNN in question. This implies the existence of a hard limit (way below the information-theoretic one) for the distance between related data points within which RNNs are still able to recognize said relation.
Introduction

Summary This chapter starts by describing the organization of the book, which consists of three parts. Part I discusses some basic concepts, including, for instance, what metalearning is and how it is related to automatic machine learning (AutoML). This continues with a presentation of the basic architecture of metalearning/AutoML systems, discussion of systems that exploit algorithm selection using prior metadata, methodology used in their evaluation, and different types of meta-level models, while mentioning the respective chapters where more details can be found. This part also includes discussion of methods used for hyperparameter optimization and workflow design. Part II includes the discussion of more advanced techniques and methods. The first chapter discusses the problem of setting up configuration spaces and conducting experiments. Subsequent chapters discuss different types of ensembles, metalearning in ensemble methods, algorithms used for data streams and transfer of meta-models across tasks. One chapter is dedicated to metalearning for deep neural networks. The last two chapters discuss the problem of automating various data science tasks and trying to design systems that are more complex. Part III is relatively short. It discusses repositories of metadata (including experimental results) and exemplifies what can be learned from this metadata by giving illustrative examples. The final chapter presents concluding remarks.
Art School of the Krasnoyarsk Region: Formation Features Analysis Through the Prism of the Fractal Concept

The article is based on a study aimed to the possibility of applying the fractal concept for the region’s artistic life study and the formation of its professional art education system. There are main features of the application of the fractal concept in this study, its subject is the activity of creative leaders at the initial stage of the formation of the professional art education system in Krasnoyarsk at the turn of the XIX–XX centuries. Historical analysis and historiographic approach for studying the formation of art education makes it possible to determine the key origin points of the regional art school, and due to use of an anthropological approach the role of the individuals in the periphery artistic life reveals, as well as the launch and coordination of self-organizing processes. There were a set of factors which determined the unique appearance of the regional art culture and the features of its educational tradition at the initial stage of the professional art education system formation which were manifested primarily through the activities of creative leaders: M. A. Rutchenko and P. I. Ivanov-Radkevich, who could be called as anthropological fractals. The main directions of their work and artistic and teaching methods made it possible to determine the basic provisions for the development of the culture of the region and important steps towards the historical, geographical and ethnographic self-identification in the culture and art of Krasnoyarsk
BlockChain-A Countermeasure for Security and Privacy in Domotics

Due to improvements in information &amp; communication technology &amp; growth of sensor technologies, Internet of Things is now widely used in smart homes for optimal resource management&amp;ubiquitous sensing. In smart homes, many IoT devices are linked together via gateways.Importance of gateways in smart homes cannot be overstated, but their centralised nature exposes them tovariety of security threats, including integrity, certification, &amp; availability. In this paper, we propose blockchain-based smart home gateway network to address these security vulnerabilities. This network guards against likely smart home gateway attacks. In smart home setting with limited resources, devices such as sensors &amp; actuators are connected&amp; communicated indispersed manner. One ofproblems in this sector is data storage&amp; safe transmission sinceinformation is sensitive&amp; contains lot of personal information fromhome network. Authors of this study have created3-tier architecture IoT-Fog-Cloud for safe &amp; efficient data processing. Data may be analysed &amp; monitored in real time with fog computing. Identity is one of thread models for IoT-based smart homes. Finally, this article focuses on Blockchain Technology, which has potential to overcome IoT application security problems. We built suggested network using Ethereum blockchain technology &amp; tested it against industry standards for security, such as security response time&amp; accuracy. We also propose some possible solutions to these security &amp; privacy problems in IoT based on blockchain to illustrate how blockchain helps to IoT.