Reviewerly/exHarmony huggingface dataset:
A Novel Method to Improve the Retrieved Multilingual Documents Score

With an ever-increasing number of resources on the Web, different language resources such as newspapers, magazines, and articles have become available. This demands for an improved technique in the information retrieval to extirpate the communication barrier among languages. Search engines are the cornerstones for informational contents and the link between the two parties of publishing and retrieval of content. Moreover, the search for information is no longer narrowed to users of the native language of the original source. Most of the non-English users such as Arabic speakers are unable to express the terms in their own language. Also, the terminologies written in the native language of the source are acquired from the English language. This challenge drives users to use mixed terms (multilingual terms) to get better results, especially in the scientific domain. This paper attempts to address the problem of documents retrieval using multilingual queries. When users use mixed queries, the results of the multilingual documents will dominate the top of the retrieved documents rather than other relevant documents, and the scores of the mixed documents obtain extra weight values that are not really part of their actual weighting value. This paper proposes a novel method to improve the results of the retrieved documents by adjusting the score of multilingual documents. For experiments, we used a mixed test collection containing mixedlanguage documents (Arabic and English). The results showed that the proposed method led to an enhanced performance in documents retrieval from multilingual queries which made them relevant, effective and accurate thus proving that our approach is more reliable than other traditional approaches.
On Improving Text Generation Via Integrating Text Coherence

Automatic text generation techniques with either extractive-based or generative-based methods are becoming increasingly popular and widely used in industry. In contrast to existing extractive-based text generation approaches that ignore the text coherence, our proposed approach integrates both keyword coverage and text coherence into our optimization framework. In this paper, we employ the semantics-based coherence and syntax-based coherence metrics to evaluate the text coherence. Extensive experiments on a real corpus demonstrate that our method outperforms baselines overall regrading ROUGE and Human evaluation metrics. Our model provides new insights on how to utilize coherence measures to arrange the sentences extracted by keyword covering method. The proposed method has been deployed on a real system to help generate coherent text.
Application Programming Interfaces

In this chapter we demonstrate the use of several publicly available services, including Twitter and Google Maps. If you wish to complete the exercises and examples in this chapter on your own, you may wish to apply for a developer account on each of these services now so that you have it available when you are ready. One reason to do this is that Twitter accounts must go through an approval process than can take several days, and you may wish to have it done before beginning the homework for this chapter.
Effect of the Application of TEA Algorithm on the Development of Secure Phone Application Android Smartphones

Android smartphone technology is growing rapidly. It is indicated that by utilizing the features of internet telephone service via the Voice over Internet Protocol (VoIP), users are able to make conversation easily and inexpensively. However, with the development, the internet telephone service used is unnecessarily safe for use. One of the solutions proposed is to make end-to-end encryption. This research applied TEA algorithm for encryption into the VoIP client of Sipdroid in Android smartphones. The objective of the research is to find out the effect of the application of TEA algorithm for encryption into the VoIP client of Sipdoid by investigating the performance of TEA algorithm in view of mean opinion score (MOS), delay, and throughput in VoIP. The results of measurement and calculation show that the application of TEA algorithm produced quality speech with R factors of 72.11676-75.01362 smaller than no TEA algorithm application with those of 84.79064-85.38539. Meanwhile, the effect of VoIP performance on such application generated a much larger delay of 0.018084 to 0.024327 seconds compared to no TEA algorithm application with a delay of 0.006071458 to 0.009465105 seconds. The results indicate that the application of TEA algorithm could more effectively contribute to the security of VoIP client practice, particularly in Android smartphones.
Collaborative Filtering Recommendation Algorithm Based on Random Forest Filling

Aiming at the sparsity problem of data set in the field of information recommendation, a collaborative filtering recommendation algorithm based on random forest filling is proposed. First, ID3 algorithm is adopted to construct the decision trees and the random forest is composed of the decision trees. Then, according to the steps of the proposed filling algorithm, the missing values of the data set are predicted using random forest and then be filled. Besides, the mean and the mode filling methods are used for a contrast. Finally, the collaborative filtering recommendation algorithm is tested for the datasets processed by different methods. Experimental results show that compared with the general recommendation algorithm and the recommendation algorithm based on the mean and the mode filling, the proposed recommendation algorithm based on random forest filling significantly improves the F value of the recommendation result and further guarantees the quality of the recommendation result.
Skeletal saliency map computation based on projection symmetry analysis

Skeleton is one of the simplest but powerful tools for shape representation and analysis, which encodes the original shape by one less dimension but can retain the topological information well. Inspired by the observation that the skeleton also serves as a symmetry axis, we propose to compute the skeleton by symmetry analysis of the given shape. In implementation, we define the skeletal saliency map by using the projection symmetry measurement. Firstly, the primitive boundary is extracted. Then, for each pixel p in the shape, we project its four neighboring pixels onto the boundary. The saliency of p is estimated by the maximum distance along the boundary between the two projections. Finally, a clean skeleton is reported by a simple truncation operation. The proposed method can produce a two-pixel-wide skeleton with correct topology and avoid any additional post-processing. Furthermore, it is also robust to boundary noise. Extensive experiment results validate these nice properties of the proposed method, which shows that it outperforms the state-of-the-art methods.
AI to Solve the Data Deluge: AI-Based Data Compression

The massive amounts of data, growing as we speak, are one of the, if not the, most accountable reasons of today’s AI systems which on many tasks exhibit human grade performance. Thanks to the enormous amounts of image data that machines can be trained to recognize scenes and steer cars. Quantities of medical imagery lead to machine provided diagnostics, sensor data allows us to detect natural disasters before they occur, and to prepare for them. Times are exciting since researchers find new applications to AI at astonishing pace. However, there is a small concern. How will we handle the ever-growing amounts of data? The consensus is that storage is cheap, yet with load of data it is expensive and unsustainable. The amount of live streamed data is also increasing. In other words, we are well advised to consider data compression again. In this chapter, we will introduce traditional compression terminology and techniques, before surveying novel approaches proposed by industry and academia. It sounds contradictory, but AI may just as well help us to address this problem.
LPLian: Angle-Constrained Path Finding in Dynamic Grids

We consider the problem of planning angleconstrained paths in dynamic 2D environment represented as a grid. We propose an extension of the LIAN algorithm, which is tailored to solve the problem on static grids, by combining it with the prominent Lifelong planning approach. We describe the resultant algorithm, LPLian, and evaluate it empirically in the series of simulated experiments. The results of the evaluation clearly show that LPLian outperforms the naive approach of replanning with LIAN from scratch for a well-defined class of the problems by a factor of 2x.
Appilication of K-Means algorithm to predict consumer interest according to the season on place reservation and food online software

Abstract The background of what this report discussed is the problem on the food menu due to the unsold food menu causes that make the restaurant loose their money because of the unused food menu. In this case K-Means can be used to cluster consumer interest where the interest will be adjusted with the season. K-Means algorithm will be used in software to find consumer interest from existing sales data, in this case can be said as data mining where the data will be made and sorted by customer’s interest like summer or rainy season. The determination of these problems based on the season due to consumer interest that will be more easily to calculated when we following the season in Indonesia where Indonesia itself is a tropical country which has a diverse diet. With the grouping of data from sales data restaurant can determine the menu of food and beverages in accordance with consumer interest where the menu will be adjusted to the season in Indonesia that is summer and rainy season. And the results of data processing will be implemented on online reservation software and food reservations previously made in previous research entitled Online Food Place and Food Packages In Food Garden Miko Mall. This is intended to facilitate the restaurant to determining in the purchase settings of feed ingredients. If there is a lot of menus sold then raw materials will be reproduced and if there is a food menu that is less enthusiastic or the sale is spelled out less then the raw material will be reduced.
The scientific and research centers of Ukraine of library science

The article is devoted to the analysis of the activity of leading research institutions in the field of library science in Ukraine at the present stage. Using the methodological basis of the systematic approach and the content analysis method of scientific publications and open access resources, the author investigates the achievements of Ukrainian librarianship. The purpose of the article is to analyze the main directions of activity of the scientific institutions of the librarian branch in 2010s; the problems of the dissertation researches aimed at improving the activity of the library social institute; the development of professional communication through scientific events and periodicals. Among the main objects of research are the Institute of Library Science, Institute of Information Technologies and the Center for Social Communication Research of the Vernadsky National Library of Ukraine; Lviv National Scientific Library of Ukraine named after V. Stefanyk; State Scientific and Pedagogical Library of Ukraine named after V.O. Sukhomlinsky; National Scientific Agricultural Library of NAAS of Ukraine. The article also analyzes the achievements of scientific schools of Kharkiv State Academy of Culture, Kyiv National University of Culture and Arts, National University «Lviv Polytechnic». The conclusion is that the main tendencies of library investigations carried out in research centers - leading libraries and institutions of higher education of Ukraine include: the development of interdisciplinary research, in which the library as a social institute becomes an active component of public communications, global information influences; development of researches devoted to scientific and informational support of branch science (educational, agrarian) in the context of European integration and globalization processes; the librarianship investigation from the media space point of view, in particular in the system of public use of social media, or as an equal partner in its creation; increasing attention to interaction and coordinated formation of consolidated information resources of libraries, archives and museums. The study may be followed up as the study of the experience and prospects of international cooperation in the field of scientific activities, especially library science, as well as librarianship issues, which are covered in scientific communication - in professional journals, scientific forums, etc.
Cyber Economic Crime Typology

This chapter explores the typology of cybercrimeCybercrime with theoretical briefing is explained and attempts to create a classification of cyber economic crimeCyber economic crime . The chapter explains various approaches like technological, criminological, psychological and sociological approaches to classify the cybercrimesCybercrime . Cyber economic crimesCyber economic crime are classified on the basis of modus used, amount of proceeds of crime, type of criminals or nature of threat agentThreat agents and nature of victim or target. Classification based on the role of technology and dependence on technology is also considered. Most prevalent crime types are discussed in detail like phishingPhishing , ransomwareRansomware , and credit/debit card frauds in cyberspaceCyberspace .
A research on face cognition method with deep ensemble learning and feedback mechanism

Face recognition technology is an important research field for deep learning. In order to overcome the shortcomings of traditional open-loop face cognition mode and deep neural network structure, and to imitate human cognition model with real-time evaluation of cognitive results and self-optimized regulation of feature space and classification criteria, drawing on the theory of closed-loop control theory, this paper explores a face intelligent cognition method with deep ensemble learning and feedback mechanism. Firstly, based on the DEEPID neural network, a multi-layer feature space of face images from the global to the local is established. Secondly, based on feature separability evaluation and variable precision rough set theory, a face cognition decision information system model with dynamic feature representation is established from the perspective of information theory, to compact the multilayer feature space. Thirdly, the ensemble random vector functional-link net is used to construct the classification criterion for the compacted multi-layer feature space. Finally, the entropy measure index of face recognition results is constructed to provide a quantitative basis for the self-optimization adjustment mechanism of face feature space and classification criteria. The experimental results show that the proposed method can effectively improve the recognition rate of face images compared with the existing methods.
Tacit Knowledge in Software Testing: A Systematic Review

This paper presents a systematic review of tacit knowledge in software testing. The main objectives of conducting this systematic review is to identify and synthesize issues and challenges regarding tacit knowledge in software testing, its influential factors that affect the tacit knowledge creation, sharing, use and transfer among software testers, its impacts on software testing, and the research methods being undertaken by the selected reviewed studies. Systematic Literature Review (SLR) is used for reviewing 14 primary studies that focus specifically on tacit knowledge in software testing. This paper provides significant evidences on the importance of tacit knowledge in software testing that will direct further directions for knowledge management (KM) and software testing practitioners and researchers.
Optimization of Multi-way Join Cost Using System R* and SharesSkew

In a distributed environment relations are stored at different sites. To perform algebraic operations such as join, the relations are to be transferred from one site to the other in such a way that the total communication cost is minimized. This paper deals with the problem of computing the transmission cost using two approaches. The first uses System R* algorithm approach when the data is of non-skew nature and the second uses SharesSkew algorithm when the data has skews i.e., same value for a specific join attribute, named as Heavy Hitter (HH). Rules of the two algorithms to be followed for performing join are specified and by illustrating with Banking System, the communication cost is evaluated.
Development of Cost Effective Motion Capture System based on Arduino

In recent years, motion capture is predominantly used in biomedical and entertainment industry. The widespread use of motion capture in entertainment industry has deployed revolutionary changes in the field. At the same time, motion capture technology enhances the quality of human lives with its contribution to perform motion study in the applications like medical diagnosis and rehabilitation. Many research works have been carried out to make the technology as more accurate, versatile and viable to use in other fields. On the other hand, optical system also gains research interest with its extended applications in big industries and facilities. But they are very expensive and requires a large setup with various other limitations that makes optical system unaffordable for many small-scale industries and applications. This research work proposes a system based on inertial sensing is observed as a more accurate model when compared with the existing optical system and it also overcomes many other major drawbacks like flexibility and initial costing. System consists of MPU6050 integrated with Arduino Uno board. The output is serially given to computer via Arduino board, on which the output is presented in unity software. Complementary filter is used to integrate data from sensors.
VLSI Implementation of Reed Solomon Codes

Reed Solomon(RS) codes are error correction codes that are widely used in communication systems. RS codes exhibits high error correction capability as compared with other error correction codes. Encoding is the process of adding parity bits to the input messages. The input message and parity bit together form the codeword. The input of the decoder can contain errors. In decoding, the original message is retrieved by applying different algorithms to the codeword. This paper uses LFSR for encoding and the Peterson Gorenstein Zierler algorithm for decoding. This work is aimed at execution of RS codes using different technologies. The Reed Solomon encoding and decoding is done using Octave, Vivado, Cadence tools. The data is tested for a single error and two errors. The system is implemented and synthesized in Application Specific Integrated Circuit (ASIC) and Field Programmable Gate Array (FPGA). Timing analysis has been done and GDSII file has been generated.
A Knowledge Visualization Course for the Era of Data Science

Big data applications, as well as the whole myriad of applications arisen through the evolution of the body of knowledge commonly known as Data Science brings new challenges to CS-related courses curricula. The demands imposed in CS-related courses by the recent development of data-oriented application makes that visualization skills became an important part of both undergraduate and graduate formation. In this sense, this paper presents a syllabus for a Knowledge Visualization course, adaptable to both undergraduate and graduate levels, which aims to contribute to systematize the competences, skills and attitudes regarding data, information and knowledge visualization that are expected to be developed by future professionals.
Getting Started with Python

This chapter introduces basic Python concepts that will be used throughout the remainder of this text. If you are already familiar with another programming language, such as R, many of the concepts here will be analogous. If you are approaching Python as your first programming language (and it is a good choice for that purpose), you may benefit from working through this material alongside another introductory text such as Shaw (Learn python the hard way, 2013).
Design and Implementation of PC-based DRM Multiplex Generator

With the development of digital broadcasting technologies, Digital Radio Mondiale (DRM) has become one of the most popular digital broadcasting standards in the world. The DRM Multiplex Generator is an important part of the DRM system, which can generate the digital DRM multiplex to the DRM channel encoder. This paper presents a design and implementation of a PC-based DRM multiplex generator, which multiplexes all the DRM services and generates output streams in Multiplex Distribution Interface (MDI) format. The results show that the system can accomplish multiplex and meet requirements of the DRM standard.
Deep Puff: Censoring via Machine Learning Cigarette Use

The problem of smoking is an extremely relevant issue. There is a need for reducing smoking among the population, especially children. The aim is to develop an automated solution for cigarette censoring. The application of the automated censoring of cigarettes in images or videos may have a positive effect on the problem of reducing smoking among the population, also minimizing the risk of a child being affected by harmful information. In the process of creation of the solution, various segmentation models and loss functions were tested. The solution is based on the DeepLab architecture for image semantic segmentation, which extracts the cigarette pixels from the image. These pixels are then transformed, so the cigarette in the image becomes unidentifiable. Achieved results are considered to be satisfactory, removing cigarettes with minimal disruption to the image. Mean Intersection over Union of 0.791 shown by DeepLab in the segmentation task and pixel swapping method simplicity are combined in the overall good performance.
Comparison of communication performance of block coding methods in different channels using DWT

In this study, the audio transmission performance of some block coding methods in wavelet and non-wavelet cases is compared. For this purpose, a communication system has been established in the MATLAB environment for the transmission of the audio signal for 5 s. The comparison of the transmission performance of the block codes was performed separately in different parameters of additive white Gaussian noise, Rician and Rayleigh channels. At the same time, it is determined which discrete wavelet transform (DWT) family is suitable in terms of transmission performance for block coding methods and how DWT level affects transmission performance is investigated. Four DWT families at different levels were applied to the audio signal for linear block coding, Hamming, Cyclic, Bose–Chaudhuri–Hocquenghem, Reed–Solomon, encoded channels, and bit error rate and mean squared error performances were compared.