Reviewerly/exHarmony huggingface dataset:
Panel Data Analysis of Press Freedom and Women Empowerment

More equal economic, social and political rights for women have long been part of civil and political right movements. It is widely believed that women’s rights are important for greater economic prosperity, good governance and social equality. However, women are still being discriminated in many parts of the world. How women’s rights can be protected? To answer this question, the literature has highlighted the importance of free media in promoting women’s rights. The extant literature on media and women rights, however, is largely limited to descriptive analysis and theoretical arguments. Moreover, the available evidence is confined to few case studies and anecdotal stories, which cannot be generalized globally. This study contributes in the literature by empirically investigating the relationship of press freedom with women empowerment using a large panel of 160 countries from 1996 to 2011. For empirical analysis, the ordered logit method is used. The empirical finding confirms that press freedom is an effective tool to empower women’s economic, political and social rights. Findings of the study are shown to be robust to different specifications, sub-samples, regional controls and different forms of women empowerment.&#x0D; JEL Classifications Codes: C23, J16, Z10
Following the FAD: Folk Attributions and Theories of Actual Causation

© 2016, Springer Science+Business Media Dordrecht. In the last decade, several researchers have proposed theories of actual causation that make use of structural equations and directed graphs. Many of these researchers are committed to a widely-endorsed folk attribution desideratum (FAD), according to which an important constraint on the acceptability of a theory of actual causation is agreement between the deliverances of the theory with respect to specific cases and the reports of untutored individuals about those same cases. In the present article, we consider a small collection of related theories of actual causation, including a purely structural theory and two theories that supplement the structural equations with considerations of defaults, typicality, and normality. We argue that each of these three theories are meant to satisfy the FAD, and then we present empirical evidence that they fail to do so for several variations on a simple scenario from the literature. Drawing on our previous work on the responsibility view of folk causal attribitons, we conclude by offering a solution that allows the latter two theories to satisfy the FAD for these cases. The solution is to give up on concerns with typicality and focus on injunctive norms in supplementing the graphical modeling machinery.
A Block Cipher Design Using Recurrent Neural Networks

&lt;p&gt;As security has become a necessary component for business applications in many areas, research of new cryptography technology is desirable, especially the highly secure and efficient data encryption technique. A new block cipher designed based on recurrent neural networks is proposed for first time in the project. Recurrent neural networks have dynamics characteristics and can express functions of time. By introducing recurrent neural networks to cryptography, the proposed block cipher releases the constraint on the length of secret key. The inherited high by parallel processing capability of neural networks can also improve the encryption performance greatly. The recurrent neural networks make the block cipher strong to resist different cryptanalysis attacks and to provide data integrity and authentication service at the same time. The design of the proposed block cipher is presented and analyzed in detail. Simulation results provide illustrations. The proposed block cipher is flexible to be implemented either in software or in hardware for efficient data encryption purpose.&lt;/p&gt;
Fast practical online exact single and multiple pattern matching algorithms in highly similar sequences

With the advent of high-throughput sequencing technologies there are more and more genomic sequences of individuals of the same species available. These sequences only differ by a very small amount of variations. There is thus a strong need for efficient algorithms for performing fast pattern matching in such specific sets of sequences. In this paper, we propose efficient practical algorithms that solve on-line exact pattern matching problem in a set of highly similar DNA sequences. We first present a method for exact single pattern matching when k variations are allowed in a window which size is equal to the pattern length. We then propose an algorithm for exact multiple pattern matching when only one variation is allowed in a window which size is equal to the length of the longest pattern. Experimental results show that our algorithms, though not optimal in the worst case, have good performances in practice.
The Comprehensive Analysis Speech Recognition System

Automated computer speech detection has been a goal of research for almost four decades. The idea underlying the development of a voice recognition system is that it is beneficial for people to communicate with a computer, robot or another device via speech. Researchers want to utilize people's voices in an integrated environment to provide customers comfort and flexibility in today's era. Speech recognition is dependent on the input voice signal. It enables the computer to transform the voice signal to text or instructions using the technique of recognition and understanding. This article describes the fundamental concept of speaking recognition, types of voice recognition, difficulties with speech recognition, several ways to gather characteristics, and different pattern-matching algorithms to identify the different speakers. The technology of voice recognition is inspired by a wide vocabulary automated speech recognition system which allows languageindependent operation and continuous speaking in a foreign language.
USING CHAIN MASSAGE GAME TO SUPPORT YOUNG LEARNERS’ VAK LEARNING STYLE

This research discusses the involving chain massage to accommodate young learners' learning style in which is conducted at grade 4 of one elementary school in Bandung. The aim of this research are (1) involving chain massage games in teaching English to the young learner, especially in grade 4 of an elementary school in Bandung, (2) finding out teacher’s and children’s responses toward the implementation of chain message in TEYL. This research uses a qualitative study where there are 40 students and one English teacher as the participants. The findings of this study show that chain messages can be considered as an effective activity of TEYL.The children seem to learn English more excitedly by game. With regard to the teacher, chain message game creates classroom activities more interesting and joyful because the children’s are involved in. Moreover, this game is also support different learning style of the children, visual, auditory and kinesthetic. However, the teachers found some obstacles in implementing the technique because they still children who easily get bored.
Bright - Proposed Family of Lightweight Block Ciphers for IoT-Enabled Smart Environment

Lightweight security algorithms are tailored for resource-constrained environment. To improve the efficiency of an algorithm, usually, a tradeoff is involved in lightweight cryptography in terms of its memory requirements and speed. This paper proposes a software-oriented new family of lightweight block ciphers, BRIGHT. Proposed family of ciphers support a range of block and key sizes for constraint environment. BRIGHT family has 6 variants and all variants fulfill Strict Avalanche Criteria and key sensitivity test. It is believed that BRIGHT family of ciphers provides better security and performance in IoT-enabled smart environment. Our aim, while designing BRIGHT is to enhance the cipher for IoT applications. For this, we have used the concept of key whitening that helps to resist against attacks like MITM and brute-force. Round permutation in BRIGHT results in stronger and faster diffusion and provides resistance against linear, differential, impossible differential, related-key rectangle, biclique, MITM, and statistical saturation attack which is likely to be applied to GFN based ciphers. BRIGHT using round constant thwarts attacks like rotational cryptanalysis, self-similarity, invariant attack, related-key attacks, and weak key attacks.
Blockchain Technology and Intellectual Property – A Basic Introduction

Blockchain technology is predicted to have a major impact on the Intellectual Property (IP) ecosystem.More and more projects are being launched, both in the public and private sector.The World Intellectual Property Organization (WIPO) has built up a Blockchain Task Force and is preparing a new WIPO Standard to encompass all types of IP rights and the entire IP lifecycle 2 ; the German Government published a strategy paper on blockchain with a chapter on applications in the creative arts sector 3 ; a European Blockchain Service Infrastructure is being built up 4 ; the European Union Intellectual Property Office (EUIPO) established an Anti-Counterfeiting Forum as part of the broader EU strategy to create a blockchain ecosystem 5 and now has its own blockchain for trademarks and designs in the EU 6 .Furthermore, LVMH, with brands such as Louis Vuitton, developed its own blockchain to track luxury goods 7 ; Kodak started a blockchain initiative for image rights management 8 ; music and film streaming are offered on blockchain platforms 9 ; sports clubs discuss microlicensing of their IP rights 10 ; digital fashion is created for distribution using blockchain 11 .Moreover, news abounds of Non-Fungible Tokens (NFTs) representing basically everything imaginable-both digital and physical-in the IP ecosystem, to track the origin of art and all manner of products.However, interestingly enough, as early as 2012 a whitepaper was published linking the idea of smart property by Nick Szabo and digital collectibles to blockchain and at the same time introducing the first kind of NFTs, colored coins 12 .
Booster in High Dimensional Data Classification using CNN and Decision Tree Algorithm

Classification problems in high dimensional data with small number of observations are becoming more common especially in microarray data. The performance in terms of accuracy is essential while handling sensitive data particularly in medical field. For this the stability of the selected features must be evaluated. Therefore, this paper proposes a new evaluation measure that incorporates the stability of the selected feature subsets and accuracy of the prediction. Booster in feature selection algorithm helps to achieve the same. The proposed work resolves both structured and unstructured data using convolution neural network based multimodal disease prediction and decision tree algorithm respectively. The algorithm is tested on heart disease dataset retrieved from UCI repository and the analysis shows the improved prediction accuracy.
Sources of information about books and the role of media in promoting of reading among Kremenchuk student youth

The paper highlights the results of an empirical study of sources of obtaining information about books and the role of mass media in the promotion of reading among Kremenchuk student youth. The methodological basis of the study was the social and communication paradigm. A set of research methods was used to achieve the goal: theoretical to determine the state of development of the problem, the definition of conceptual apparatus; empirical (survey) to identify the role of media in reading promotion. The survey was conducted in the framework of the project "Book in virtual space". As a result of empirical research, the hypothesis that mass media plays an important role in the popularization of reading, particularly among student youth was confirmed. The study showed that the main media kinds, from which young people receive information about books, are online media and websites of publishing and book-selling organizations. The indirect ways of book promoting are considered by students to be a priority over direct advertising and promotion of books. The mass media is the main source of information about books; this determines the importance of expanding the communication channels of libraries with the audience, first of all, by accessing the virtual space. The generalized analysis of respondents' comments and wishes testifies to students' understanding of the role of reading in human development and the need for its promotion.
Preface

Abstract The second edition of the International Conference on Innovative Technology, Engineering and Sciences 2020 (iCITES 2020), organized by Universiti Malaysia Pahang through its Alumni Society held on 22 nd December 2020. Owing to the COVID-19 pandemic, this edition of the conference was held virtually to avoid unnecessary travel that might aggravate the spread of the virus. The overarching themes of the conference were Green and Frontier Materials, Innovative Robotics and Automation, Renewable and Green Energy, Sustainable Manufacturing, as well as Data Analytics. More than 170 submissions were received for iCITES2020 and were reviewed in a single-blinded manner, and 97 papers were agreed upon by the reviewers to be accepted and published in this volume of IOP Conference Series: Materials Science and Engineering. It is worth noting that the proceedings of the first edition of the conference was also published in IOP: MSE. The editors would like to express their gratitude to all the authors who submitted their papers. The authors whom had their work accepted were requested to present their findings live in multiple parallel sessions that are slotted according to the aforesaid overarching themes through Microsoft Teams for a period of 10 minutes each including question and answer session. The conference had brought a new outlook on cutting-edge issues shared through the keynote speeches by Assoc. Prof. Dr. Han-Lim Choi (Korea Advanced Institute of Science and Technology), Mr. Jamie Steel (EDF Energy), Dr. Rabiu Muazu Musa (Universiti Malaysia Terengganu), Dr. Miles Stopher (University of Cambridge), Assoc. Prof. Dr. Kazem Reza Kashyzadeh (RUDN University) and Mr. Jee Kwan Ng (IDIR Solutions). Finally, the editors hope that readers find this volume informative and we would like to thank IOP for undertaking the publication of this volume. We would also like to express our gratitude to the Organizing Committee and the Advisory Committee for their hard work in ensuring the success of the conference. The Editors, Dr. Zulhelmi Ismail Dr. Ashwin Charles Benedict Dr. Noormazlinah Ahmad Assoc. Prof. Dr Khairunisa Muthusamy Mr. Ismail Mohd Khairuddin Assoc. Prof. Dr. Ahmad Salihin Samsudin Dr. Nasrul Hadi Johari Dr. Mohd Fadzil Rahim Dr. Muhammad Yusri Ismail Mr. Muhammad Amirul Abdullah Dr. Anwar P.P. Abdul Majeed Mr. Jessnor Arif Mat Jizat Dr. Mohd Azraai Mohd Razman Dr. Ahmad Fakhri Ab Nasir Dr. Mohamad Shaiful Abdul Karim Assoc Prof Dr. Abdul Aziz Jaafar Dr. Lim Wei Hong
Automated Mission Planning for Mobile Robots Using Embedded Gpu

Mission planning is a fundamental problem in mobile robotics.Domainindependent planners and the PDDL language provide a standard and flexible framework for solving it.However, such planners have high requirements for computing resources which are at a premium on mobile platforms; also, they are single-threaded CPU-based and hence do not scale well.GPGPU-enabled onboard computers such as NVIDIA Jetson family boast high TFLOPs and energy efficiency, but no automated planners described in scientific literature are able to take full advantage of them.This paper describes a new automated planner running entirely on the GPU and its application for service mobile robot mission planning.
Transfer Learning Based Traffic Sign Recognition System for Surveillance Application

Road Traffic Recognition is very important in many applications, such as automated deployment, traffic mapping, and vehicle tracking. Proposed traffic sign recognition system tails the transfer learning method that is frequently used in neural network uses. The benefit of expending this technique is that the initially network has been trained with a rich set of features appropriate to a wide range of images. Once the network is trained , learning can be transferred to the new activity adjustment to the network. Firsthand Indian traffic sign dataset is used.New results exhibit that the suggested method can accomplish modest outcomes when matched with other related techniques.
The Combinatorial Analysis of n-Gram Dictionaries, Coverage and Information Entropy based on the Web Corpus of English

We research n-gram dictionaries and estimate its coverage and entropy based on the web corpus of English.We consider a method for estimating the coverage of empirically generated dictionaries and an approach to address the disadvantage of low coverage.Based on the ideas of Kolmogorov's combinatorial approach, we estimate the n-gram entropy of the English language and use mathematical extrapolation to approximate the marginal entropy.In addition, we approximate the number of all possible legal n-grams in the English language for high order of n-grams.
Research on Cache Transition Techniques for Semantic Graph Parsing for Optimizing Search Process using Text Mining

This paper elaborates the transition system that gives the standard transition-based dependency parsing techniques for generating the graph. It is essential to know the standard transition techniques for all graphical problems. Cache transition technique plays a vital role in optimizing the search process in various text mining applications. This paper provides an overview on cache transition technique for parsing semantic graphs for several Natural Language Processing (NLP) applications. According to this paper, the cache is having the fixed size m, by tree decomposition theory according to which there is a relationship between the parameter m and class of graphs produced by the theory
An Accession for Image Denoising by Multiple Filter and Correlative Examination for Random Impulse Noise

Denoising an image is a significant problem in the processing of digital images. Any impulse noise damages the image and the aim of denoising is to remove noise and restore the high-quality image as much as possible. This paper aims to develop a method to discriminate between corrupted and uncorrupted pixels and develop a novel filter to denoise the image. It is also necessary to consider images with different level of noise of various applications to develop an optimal system to remove the noise for further processing. In this paper different filtering techniques such as Median-Filter (MF), Weighted -Median-Filter (WMF),Centre-Weighted Median filter (CWMF), and adaptive centre weighted median filter (ACWMF) are used for denoising, also a novel filter Asymmetric Trimmed Median Filter(ATMF) is designed which outperforms compared to the filters designed earlier. Experimentation is carried by considering the dataset size of 700 noisy images. The average PSNR value of proposed system is 28.12%(DB).
Sindhi Handwritten Text Recognition Using SVM

In Sindhi Language, handwritten text feature extraction is such a challenging task for all scholars, because different people write in different styles or manners, to analyze each text is such a complex problem. Feature extraction of text segmentation, classifying each character and labelling for training data to recognize text for different handwritings and testing for analyzing features of providing handwritten text data .In this research, SVM (support vector machine) is used for analyzing and tokenizing each character or word of Sindhi Language text and transform into suitable information with efficiency &amp; accuracy. The research is not only useful for improving the knowledge of Sindhi Handwritten Text Recognition but it can be beneficial for other recognition systems
Communication Strategy for Children with Speech Delay

&#x0D; Delay in talking to children certainly has an impact on the stages of its development so that it requires a communication strategy from both parents and teachers to stimulate the child's speaking ability. This study aimed to describe the application of communication strategies and the effect of their application on children's communication skills. This research is qualitative research using a case study method involving students, parents and kindergarten teachers in Jumni City, Palopo. The results of observations and interviews were then analyzed using thematic content analysis techniques. Based on observations and interviews conducted, it was found that parents implemented various strategies, such as speaking slowly and clearly, routinely inviting talking and using hand movements. While, the teacher implements strategies to correct word pronunciation errors, invites storytelling and uses body movements. Through the application of this strategy, the child's ability to speak is getting better and the principle of two-way communication can occur where students are able to channel their desires, imagination, and emotions. Thus, it is hoped that communication strategies can be developed and implemented by parents and teachers to the fullest.
Evaluation of Parallel System using Process Algebra

In this paper we discuss method for efficiency testing of a concurrent processes execution system. We use the concept of process algebra, it is an algebraic technique for the study of execution of parallel processes. Mathematical language is use for building models of computing system which make records about the execution of the procedure. We use PEPA tool, TAPA tool for making model. These tools provide formal explanation of computing system models. The execution related data about the system will be use to check the execution efficiency of the procedure. Here we use concept of markov chain analysis for execution of the concurrent processes.
Cybercrime Regulation through Laws and Strategies: A Glimpse into the Indian Experience

Cybercrimes in India is increasing at an alarming rate. Though various legal provisions under the conventional criminal laws including form the Indian Penal Code, could be used to regulate the cybercrimes, yet the changing nature of these crimes necessitated adoption of a new law framework. Thus, the Indian Information Technology Act was enacted in 2000 but seldom could regulate cybercrimes since it focused on promoting and facilitating e-commerce and e-governance. This Act underwent amendment in 2008 to accommodate provisions essential to regulate cybercrimes as well as protect data and privacy on cyber space. In addition to the law, other strategies were designed and adopted to better regulate cyber offences including announcing cyber security policies, constituting institutions to take care of certain concerns including those relating to critical infrastructure information, etc. This paper aims to provide an overview of the approach adopted in India primarily the legal approach adopted to regulate cybercrimes. Additionally, other strategies adopted by India is also reviewed in brief. Despite these, since cybercrimes are technical as well as dynamic in nature, there is a need to constantly review and revise nation’s strategies, which is also one of the objects of this paper.