Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis on New Currency in Kenya using Twitter Dataset

Social media sites recently became popular, it is clear that it has major influence in society. Twitter is one of these sites, full of people’s opinions, where one can truck sentiment express about different kinds of topics. Sentiment analysis is one of the major interesting research areas nowadays. In this paper, we focused on Sentimental insight into the 2019 Kenya currency replacement. Kenyans citizens expressed their reaction over new banknotes. We perform sentiment analysis of the tweets from twitter using the Multinomial Naïve Bayes algorithm. We split our dataset using k-folder cross validation since we had limited amounts of data, so to achieve unbiased prediction of the model we obtained an average accuracy of 75.3%.
Corporate Governance Transparency in Small Listed Entities: The Case of Malta

Purpose: The objectives of this study are to examine whether a lack of transparency is a common corporate governance feature of listed entities (“MLEs”) in the small European state of Malta and, if so, to assess the possible implications of such a stance. Design/Approach/Methodology: In order to achieve such research objectives, a predominantly qualitative mixed methodology was adopted. This involved carrying out thirteen semi-structured interviews with MLE and audit firm representatives, these being supported by an examination of the corporate governance statements of MLEs for the 2015-2017 periods. Findings: Results show a general lack of transparency in corporate governance reporting, with a common MLE tendency to comply only at a superficial level with the principles of good corporate governance and thus to often fail to sustain an appropriate level of transparency and governance structures. Practical Implications: It is recomended to increase company and shareholder awareness so as to help towards further improving current attitudes. Originality/Value: The study is particularly envisaged to contribute towards encouraging stakeholders in small-state contexts to reassess their current perspectives towards corporate transparency.
Tectonics and Neotectonics of the Mesopotamian Plain: A Critical Review

The Mesopotamian Plain is a part of the Mesopotamia Foredeep of the Zagros Foreland Basin and is a part of the Zagros Fold – Thrust Belt. The plain covers the central part of Iraq and extends south ...
OSFPMiner: An Optimal Weighted Traversal Software Patterns Miner Based on Complex Network

The weighted traversal pattern is important in software system for a better understanding of the internal structure and behavior of software. To mine important patterns of software, a complex network-based Optimal Software Fault Patterns Miner is presented. By analyzing the multiple execution traces of software and the relations among functions, we establish the Weighted Software Execution Dependency Graph model ultimately. The traversal database is generated through depth-first search strategy and the extraction of software path traversals. According to the downward-closure property, a pruning strategy is adopted by Weighted Frequent Candidate Pattern Tree to cut off more unpromising patterns in advance. A set of important patterns is derived without repeated calculation. The experimental results show that the proposed approach has good performance in the number of weighted frequent candidate patterns and time efficiency.
Counterfeiting scalable detection image based system for e-commerce

Counterfeiting in e-commerce raises issues this paper addresses through a specialized large-scale reverse image search engine called e-CoS, with a serverless based architecture for high performance. The system is tested in the area of online counterfeiting with promising results. In order to generalize the solution unprecedented cooperation and information sharing are required between all stakeholders of e-commerce with a key part being reserved for the general public. The prospect of such mass adoption is made possible by the growing ethical concerns of modern-day consumers, fueled by the enormous negative social and economic impact of counterfeiting.
Exploration of media block chain technologies for JPEG privacy and security

Privacy and security, copyright violations and fake news are emerging challenges in digital media. Social media and data leaks increase risk of user privacy. Creative media particularly images are often susceptible to copyright violations which poses a serious problem to the industry. On the other hand, doctored images using photo editing tools and computer generated images may give a false impression of reality and add to the problem of fake news. These problems demand solutions to protect images and associated metadata as well as methods that can proof the integrity of digital media. For these reasons, the JPEG standardization committee has been working on a new Privacy and Security standard that provides solutions to support privacy and security focused workflows. The standard defines tools to support protection and integrity across the wide range of JPEG image standards. Related to image integrity, blockchain technology provides a solution for creating tamper proof distributed ledgers. However, adopting blockchain technology for digital image integrity poses several challenges at the technology level as well as at the level of privacy legislation. In addition, if blockchain technology is adopted to support media applications, it needs to be closely integrated with a widely adopted standard to ensure broad interoperability. Therefore, the JPEG committee initiated an activity to explore standardization needs related to media blockchain and distributed ledger technologies (DLT). This paper explains the scope and implementation of the JPEG Privacy and Security standard and presents the current state of the exploration on standardization needs related to media blockchain applications.
Local Concurrency in Text Block Search Tasks

The relevant problem of text analytics tools development is real-time mode establishment via data processing operations parallelizing.The use of the local parallel (LP) approach is advantageous.The classification of search algorithms for text blocks, which are candidate for local parallel (LP) approach implementation, was presented.The advantages of LP approach implementation were regarded.The variants of bit and segmental word-patterns processing in text block search tasks were proposed and exemplified.Perspectives and certain threats to its implementation were studied in terms of Boyer-Moore algorithm.
Penerapan Algoritma Rule Base dengan Pendekatan Hexadesimal pada Transliterasi Aksara Bima Menjadi Huruf Latin

Aksara Bima is a text-based information exchange media that has never been lost. At this time the Bima script began to be studied again indicated, with researchers who began to explore the history and stages of the process of digitizing the characters including the Bima script. Thus providing hope for the use of characters in community activities. One problem faced when wanting to learn the characters felt by the community is the different forms of characters in Latin letters and there are fixed rules when writing characters that make the process of writing characters feel difficult. So the writing of characters in daily activities in community activities still cannot be said to be massive due to these problems. In this study, the writer will develop an algorithm that can facilitate the learning activities of characters, which is specialized in the process of reading the Bima Script. The method adopts the concept of machine learning that is applied to the process of transliteration of Bima, into Latin letters. With a string replacement algorithm that is optimized by using hexadecimal numbers. The results obtained from this transliteration process in the form of system accuracy that reaches 90.64% of 171 implemented rule base.
Attestation Using Visual Cryptography (3,3) Scheme

Visual Cryptography is a technique in cryptography which is used to encrypt the images and all other visual information.And this cryptography is different from all other cryptographic techniques, because of its decryption process and it is done mechanically.In general, visual cryptography image is encryption is limited up to two shares only.In this paper we propose a complete new and different way of authentication(attestation) which helps to provide more security than other authentication systems by using the Visual Cryptography (3,3) Scheme.
Nondeterministic Fuzzy Simulation and Bisimulation

Chinese Journal of ElectronicsVolume 29, Issue 2 p. 297-303 ArticleFree Access Nondeterministic Fuzzy Simulation and Bisimulation Hui Deng, Hui Deng School of Electro-Mechanical Engineering, Xidian University, Xi'an, 710000 ChinaSearch for more papers by this authorZhi Li, Corresponding Author Zhi Li zhli@xidian.edu.cn School of Electro-Mechanical Engineering, Xidian University, Xi'an, 710000 ChinaSearch for more papers by this author Hui Deng, Hui Deng School of Electro-Mechanical Engineering, Xidian University, Xi'an, 710000 ChinaSearch for more papers by this authorZhi Li, Corresponding Author Zhi Li zhli@xidian.edu.cn School of Electro-Mechanical Engineering, Xidian University, Xi'an, 710000 ChinaSearch for more papers by this author First published: 01 March 2020 https://doi.org/10.1049/cje.2020.01.007AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract As the abstraction and equivalent technologies, simulation and bisimulation have been applied to the simplifications of some classical and uncertain models structures. The studies of the more generalized simulation and bisimulation technologies have not proceeded yet. With this problem in mind, we introduce the concepts, lemmas, theorems of nondeterministic fuzzy simulation and bisimulation, as well as the relevant proofs. According to the definitions of nondeterministic fuzzy simulation and bisimulation, we propose nondeterministic fuzzy quotients and a series of quotienting algorithms to generate the minimization of nondeterministic fuzzy simulation and bisimulation. By comparison with previous quotienting algorithms, we show that our quotienting algorithms are more generalized. This kind of quotienting algorithms not only suit for Nondeterministic fuzzy Kripke structure(NFKS), but also Fuzzy Kripke structure(FKS) and classical Kripke structure. Volume29, Issue2March 2020Pages 297-303 RelatedInformation
Application of Historical Burn Analysis Method in Determining Agricultural Premium Based on Climate Index Using Black Scholes Method

Farmers often suffer losses due to crop failure. The failure of the harvest is influenced by one of them is flooding, especially in Bandung which is quite frequent rain. Therefore one of the government's efforts to minimize losses from crop failures is the existence of an agricultural insurance program. The insurance system used is climate index insurance where the climate index is not plant insurance. This study aims to get a large premium to be paid by farmers using the Black-Scholes method. Meanwhile, to determine the climate index using the Historical Burn Analysis method. The results of this study are getting a variety of trigger values and exit values as well as the amount of premium that must be paid by farmers every planting season. Trigger values represent the minimum full payment limit. The exit value represents the maximum limit for no payment. The premium value obtained based on the selected trigger value also varies and is large enough so that it can be considered by farmers in choosing an agricultural insurance policy. Therefore, the method used must still be investigated to adjust to farmers, especially in Bandung.
Perception of elementary school teachers on Laro Ng Lahi in Quirino, Isabela

The purpose of this study is to determine the Perception of Selected Elementary School Teachers on Laro ng Lahi in Quirino, Isabela. The participants of this study were ten (10) selected Elementary School Teachers, five (5) from Generation X and five (5) from the Millenials. The researchers utilized qualitative research through face to face interviews. The responses were analyzed through descriptive coding using the thematic analysis. Based on the gathered data’s, Laro ng Lahi is still being played by pupils despite their access to advanced technologies and some of these are Tumbang Preso, Sipa, Patintero, Tagu-Taguan, Chinese Garter, Sungka, Luksong Tinik, Luksong Baka, Holen, Tug of War, Agawang Sisiw, Bum-Bum Lata, Agawan ng Panyo, Agawan ng Base, and Siyato. The importance of Laro ng Lahi can be classified according to its benefit in terms of health, culture, social aspiration, and values. Laro ng Lahi can be preserved employing continuous engagement in the respective houses and classroom integration by considering the use of native materials.
Naïve Bayes Algorithm for Classification of Student Major’s Specialization

Majors are important in determining student specialization. If there is an error in the direction of the student, it will certainly affect the education of subsequent students. In SMA Negeri 1 Kampar Timur, there are two majors, namely Natural Sciences and Social Sciences. To determine these majors, it is necessary to reference the average value of student grades from semester 3 to semester 5 which includes the average value of Islamic religious education, Indonesian, Citizenship Education, English, Natural Sciences, Social Sciences, and Mathematics. Naive Beyes algorithm is an algorithm that can be used in classifying majors found in SMA Negeri 1 Kampar Timur. To determine the classification of majors in SMA Negeri 1 Kampar Timur, training data and test data are used, respectively at 70% and 30%. This data will be tested for accuracy using a confusion matrix and produces a fairly high accuracy of 96.19%. With this high accuracy, the Naive Bayes algorithm is very suitable to be used in determining the direction of students in SMA Negeri 1 Kampar Timur.
Profitability Analysis of Banks: Comparative Study of Domestic and Foreign Banks in Kosovo

Purpose:The purpose of this study is to compare the financial performance of domestic and foreign banks in the banking sector of Kosovo over the period 2008-2018.In order to evaluate the financial performance of banks in Kosovo, both domestic and foreign ones, we have analyzed the financial reviews of these banks for 10 years (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018), subsequently drawing the financial reports. Design/Methodology/Approach:To give an answer to the research question whether banks with foreign capital in Kosovo are more profitable than banks with local capital we have firstly revies the literature to find out what different authors have found in recent researches concerning this area and the methods and models used in collecting, processing and analyzing data.The processing of the data of the above-mentioned reports has been done by the STATA software program, specifically using linear regression, Fixed Effect, Random Effect, Hausman Taylor Regression and GMM modelling.Findings: Based on the empirical results of this study, we conclude that all independent variables (return on equity, net sales to net assets ratio, profit margin ratio) are significant at 5% level of statistical confidence.Return on equity and profit margin have a positive impact on increasing the return on assets of commercial banks in Kosovo, while increasing the ratio of net sales / net assets has a negative impact on return on assets.Practical Implications: This paper will provide a detailed analysis of the profitability of commercial banks in Kosovo, and through comparative analysis will determine which banks are most profitable, those with foreign capital or banks with domestic capital.Originality/Value: This research paper highlights an empirical analysis based on real data, financial reports of the Central Bank of Kosovo and on the financial statements of commercial banks in Kosovo.Given that these results are evident, they are a good reflection for all decision-makers in regulating and supervising commercial banks.
Novel Quantum Trajectory Approaches to Simulation of Electron Backscatter Diffraction

We present two quantum trajectory approaches for the simulation of electron backscatter diffraction (EBSD). The quantum trajectory approaches are based on Schrödinger equation and they yield excellent agreements with experimental patterns. Meanwhile, they are particle models that allow ones to intuitively understand the processes of electron diffraction in a classical way. Besides, the approaches have significant advantages in computation efficiency. Because of the accuracy, intuitiveness, and efficiency, the trajectory approaches allow us a deeper understanding of the physical processes of EBSD.
Fast Number Theoretic Transform for Ring-LWE on 8-bit AVR Embedded Processor

In this paper, we optimized Number Theoretic Transform (NTT) and random sampling operations on low-end 8-bit AVR microcontrollers. We focused on the optimized modular multiplication with secure countermeasure (i.e., constant timing), which ensures high performance and prevents timing attack and simple power analysis. In particular, we presented combined Look-Up Table (LUT)-based fast reduction techniques in a regular fashion. This novel approach only requires two times of LUT access to perform the whole modular reduction routine. The implementation is carefully written in assembly language, which reduces the number of memory access and function call routines. With LUT-based optimization techniques, proposed NTT implementations outperform the previous best results by 9.0% and 14.6% for 128-bit security level and 256-bit security level, respectively. Furthermore, we adopted the most optimized AES software implementation to improve the performance of pseudo random number generation for random sampling operation. The encryption of AES-256 counter (CTR) mode used for random number generator requires only 3184 clock cycles for 128-bit data input, which is 9.5% faster than previous state-of-art results. Finally, proposed methods are applied to the whole process of Ring-LWE key scheduling and encryption operations, which require only 524,211 and 659,603 clock cycles for 128-bit security level, respectively. For the key generation of 256-bit security level, 1,325,171 and 1,775,475 clock cycles are required for H/W and S/W AES-based implementations, respectively. For the encryption of 256-bit security level, 1,430,601 and 2,042,474 clock cycles are required for H/W and S/W AES-based implementations, respectively.
Non-Parallel Voice Conversion System With WaveNet Vocoder and Collapsed Speech Suppression

In this paper, we integrate a simple non-parallel voice conversion (VC) system with a WaveNet (WN) vocoder and a proposed collapsed speech suppression technique. The effectiveness of WN as a vocoder for generating high-fidelity speech waveforms on the basis of acoustic features has been confirmed in recent works. However, when combining the WN vocoder with a VC system, the distorted acoustic features, acoustic and temporal mismatches, and exposure bias usually lead to significant speech quality degradation, making WN generate some very noisy speech segments called collapsed speech. To tackle the problem, we take conventional-vocoder-generated speech as the reference speech to derive a linear predictive coding distribution constraint (LPCDC) to avoid the collapsed speech problem. Furthermore, to mitigate the negative effects introduced by the LPCDC, we propose a collapsed speech segment detector (CSSD) to ensure that the LPCDC is only applied to the problematic segments to limit the loss of quality to short periods. Objective and subjective evaluations are conducted, and the experimental results confirm the effectiveness of the proposed method, which further improves the speech quality of our previous non-parallel VC system submitted to Voice Conversion Challenge 2018.
Learning with Concept Drift Detection based on Sub-concepts from k Time Sub Windows

Concept drift detection has attracted much interest recently, due to its pervasive nature in the massive amount of streaming data available for analysis. Traditional concept drift detection methods, based on the monitoring performance of a base learner on a whole time window of data stream, are not sensitive enough to sub-concept drifts and discover them late or not at all. This is because, when aggregated together, the sub-concepts that form a concept are not precisely described. To solve this problem, we propose the kTSW ( k Time Sub-concepts Window) based framework that divides instances from a whole time window into k sub-concept windows, and then builds a drift monitor for each sub-concept window. Once a sub-concept window’s instances have experienced a concept drift, we update the learned model. We propose three schemes with different base learner numbers for our framework. Each of the schemes takes advantage of a different degree of sub-concept knowledge. Two real data sets are used to verify the validity of our method in data stream classification. Experimental results show that our method is able to obtain higher accuracy and recall than methods based on a whole time window.
Convolutional auto encoders for sentence representation generation

In this study, we have proposed an alternative approach for sentence modeling problem. The difficulty of the choice of answer, the semantically related questions and the lack of syntactic closeness of the answers give rise to the difficulty of selecting the answer. The deep learning field has recently achieved a pivotal success in semantic analysis, machine translation, and text summaries. The essence of this work, inspired by the human orthographic processing mechanism and using multiple convolution filters with pre-rendered 2-Dimension (2D) representations of sentences, input or output size is to learn the basic features of the language without concerns. For this reason, the semantic relations in the sentence structure are learned by the convolutional variational auto-encoders first, and then the question and answer spaces learned by the auto-encoders are linked with proposed intermediate models. We have benchmarked five variations of our proposed model, which is based on Variational Auto-Encoder with multiple latent spaces and able to achieve lower error rates than the baseline model, which is the base Convolutional LSTM.
An Adaptive Lockstep Synchronization Method for Scene Collaborative Editing of 3D Geometry

The collaborative and interactive scene editing in 3D geometry is an efficient method for field group work, but there are relatively few studies in this area at present. It is known that the existing methods for collaborative interaction editing are lockstep synchronization methods, which can solve the problem of multi-node synchronization editing. However, the existing lockstep synchronization method uses a fixed synchronization interval. When the network environment is not stable or the network of each node is different, the adaptability is poor. In order to realize the collaborative and interactive editing scene in 3D geometry, this paper presents a method of adaptive lockstep synchronization. Compared with the existing lockstep synchronization method, this method uses the adaptive synchronization interval instead of the fixed synchronization interval, thus resolving the drawbacks of the fixed synchronization interval lockstep synchronization method. The experimental results show that this method can realize the collaborative and interactive scene editing in 3D geometry under different network environments.