Reviewerly/exHarmony huggingface dataset:
Knowledge Management Capability in Nepalese Commercial Banks

This study focuses on exploring the state of knowledge management capability (KMC) in Nepalese commercial banks and develop as well as validate its dimensions. A survey research strategy was adopted to achieve the study objective and the descriptive research design was followed to explore the state of KMC in Nepalese commercial banks. The population of this study was comprised of all 27 commercial banks of Nepal. To achieve sufficient sample size and generalization of the result, the sample frame for this study included 9 commercial banks. At least 20 employees from each organization were approached to respond about the existence of KMC in their respective organizations. Altogether 250 questionnaires were distributed, out of this 180 questionnaires were returned, the response rate was 72%, which may be taken highly satisfactory in survey research design. The exploratory factor analysis (EFA) of KMC was done to extract the latent factors or dimensions from the measured items. All three dimensions of KMC were found in unsatisfactory state. The private sector banks were found to have a better position in all three dimensions of KMC than the public sector banks. Further, the EFA of KMC items revealed for dimensions of KMC: knowledge acquisition, knowledge sharing-employees, knowledge sharing-management and knowledge utilization.
Sistem Informasi Manajemen Pelayanan pada Klinik Pratama Dengan Metode CRM

Information systems become the main thing in a company, in terms of supporting the development of the business. Information systems can facilitate the performance of a business entity. With the existence of an information system, it is expected that a business can be more optimal in managing business reporting both needed by internal and external parties. To be able to provide effective and efficient services, computer-based services that need to be done. The method used in making this application is the Prototyping method with this method is a method for building a software that is not too large and human resources involved in a limited amount. The steps taken are planning, analysis, system design, implementation. The purpose of making this application is to facilitate patients in the service of information and examinations. As well as saving addresses and energy by building this prototype system. There is also a strategy developed in the form of customer relationship management (CRM) is a strategy used by companies to manage interactions with customers and potential customers. CRM helps organizations streamline processes, build customer relationships, increase sales, improve customer service, and increase profitability. The results of the research found in making proptotypes at the Sri Panimbing Klaten Clinic are able to provide information that can be accessed anywhere and at any time as well as online reservation services that make it easy for patients, doctors, and administrators to conduct the queue process.
Interior coordination image retrieval with object-detection-based and color features

This paper presents a new interior coordination image retrieval method using object-detection-based and color features. Interior coordination requires consideration of objects’ positional information and the overall atmosphere of the room simultaneously. However, similar image retrieval methods considering the coordination characteristics have not been proposed. In the proposed method, we extract different types of features from interior coordination images and realize the similar interior coordination image retrieval based on our newly derived features.
Efficiency of LSB steganography on medical information

The development of the medical field had led to the transformation of communication from paper information into the digital form. Medical information security had become a great concern as the medical field is moving towards the digital world and hence patient information, disease diagnosis and so on are all being stored in the digital image. Therefore, to improve the medical information security, securing of patient information and the increasing requirements for communication to be transferred between patients, client, medical practitioners, and sponsors is essential to be secured. The core aim of this research is to make available a complete knowledge about the research trends on LSB Steganography Technique, which are applied to securing medical information such as text, image, audio, video and graphics and also discuss the efficiency of the LSB technique. The survey findings show that LSB steganography technique is efficient in securing medical information from intruder.
A Question-Answering System that Can Count

This paper proposes a conceptual architectural design of Question-Answering (QA) system that can solve “counting” problem. Counting problem is the inability of QA system to produce numerical answer based on retrieved rationale (in text passage) containing list of items. For example, consider “How many items are on sale?” as question and “Currently shampoo, soap and conditioner are on sale” as retrieved rationale from text passage. Normally, system will produce “shampoo, soap and conditioner” as an answer while the ground truth answer is “three”. In other words, system is simply unable to perform the counting process needed in order to correctly answer such questions. To solve this problem, QA system architecture with following components is proposed: (1) A classifier to determine if given question requires a counting answer, (2) A classifier to determine if current system’s answer is not numeric, and (3) A counting method to produce numerical answer based on given rationale. Despite looking like a whole system, the proposed architecture is actually a modular system whereby each component can operate independently (allowing each component to be separately implemented by other systems). In essence, this paper intents to demonstrate a general idea of how the defined problem can be solved using a modular system, that hopefully also opens up more flexible enhancements in the future.
Aspect-based sentiment analysis: movie and television series reviews

Aspect based sentiment analysis (ABSA) is a methodology used in various fields for analyzing the reviews of customers to project an overall opinion on any different product or service. With the evolution of the internet, people are provided with a time saving cheap procedure like this, to express viewpoints to a mass audience. With the intension of gaining market value, numerous fields are bestowed the chance in collecting information from the internet, free of charge. The application of Machine Learning (ML) methods for the procedure of evaluation regarding aspects connected to TV series and movies, has not been initiated. This would be a novel progression for the film industry. Research under this study focuses on implementing ABSA on TV series or movies based on sub aspects of genre as well as sub aspects of cast and crew. As the initial step, web scraping can be used for data collection from social media. Next, data is processed to generate adequate results for anyone who needs a broader understanding on significance of a TV series or a movie related to the aspects mentioned earlier. To collect information belonging to each aspect is further analyzed. The accuracy of the results of the suggested system has been gained high as 79% and above. In conclusion, the accuracy of the solution is greatly successful compared to the previous tasks with high market value.
The Effectiveness of Students’ Listening Skill by Using Podcast at The Second Grade of SMK Negeri 6 Balikpapan

Listening is one of necessary skill in learning English and also the patent skill in English language beside speaking, writing, and reading. Listening is considered as the most basic skill because it is firstly used by learners when they begin to learn a language, especially spoken language. In addition, unconsciously, listening is much more used in classroom than other skills. Nowadays, listening is the most difficult skill for many students to understand. The aim of this research was to find out the empirical data which could determine whether there is a significant effect of using podcast on students‘ listening skill at the second grade of SMK Negeri 6 or not. The method used was quantitative method with quasi-experimental research as its design. The samples of this research were 25 students of TITL 1 class as the experimental class and 25 students of TITL 2 class as the controlled class. Those samples were elected by using purposive sampling. To collect the data from both classes, this research used a listening test provided in a pre-test and post-test as the research instrument. Based on the result of the research, data from both pretest and post-test were calculated and analysed by using IBM SPSS Statistic 21. And the result revealed that the post-test mean score of the experimental class was greater than that of the controlled class, namely (80.88 &gt; 77.04). It meant that the experimental class and the controlled class were different significantly in their posttest mean score. Then, the result of hypotheses analysis showed that tobserve was higher than ttable (2.098 &gt; 1.677) and the significance 2-tailed (P) was lower than the alpha (0.041 &lt; 0.05). It meant that H0 was rejected and Ha was accepted. Thus, it can be considered that using podcast has given significant effect on students‘ listening skill. In addition, the result was also measured by using cohen‘s d effect size measurement to know the strenght of the effect. And the result showed that using podcast in teaching listening gave a moderate effect on students‘ listening skill with the effect size of 0.51.
A Decentralized Secure Email System based on Conventional RSA Signature

Recently, many users have been attacked by phishing or targeted malicious email, and thus email has become completely untrustworthy. So we gradually need to make email communications more secure. Of course, we can digitally sign, encrypt and decrypt emails by secure email systems such as S/MIME and PGP, which are two standards developed for that purpose. However, these two systems are seldom used and then have some drawbacks: the trust mode of PGP is only suitable for small-scaled organizations, and S/MIME cannot run away from the troubling operations such as the certificate application. In this paper, we propose a decentralized and large-scaled secure email system using conventional RSA signature embedding ID (e.g., email address), which is used in the communication scene among unspecified multi-organization. More importantly, our system needs neither a public certificate nor voucher (e.g., CA or trusted user) for mail security by employing the new type of key trust level. Since the reliability of email is decided by user itself rather than is decided by other vouchers, we can say that our system is truly decentralized.
ICTs in Inclusive Education for Sensory and Physical Disabilities

The current paper examines the role of Information and Communication Technologies (ICTs) in the inclusion of students with sensory and physical disabilities. Our main goal is to present the importance of ICTs and highlight their contribution to the smooth and equal inclusion of these children in the educational system and society. Thus, the research team of this paper presents specific examples of ICTs that aid children with visual and hearing impairments and physical disabilities. We followed the method of bibliographic review of articles, focusing on articles from the last five years. However, we considered it necessary to include also some older articles for a more complete and accurate review of the topic. According to the results of the research, ICTs provide an attractive and supportive environment for the students with special needs as well as equal opportunities regarding their inclusion. Since we live in the world of information and the digital revolution, we have to adapt to modern reality and prioritize the use of ICTs in education. Lastly, ICTs help the students with sensory and physical disabilities to overcome the barriers that exist in traditional educational systems which would lead to the reduction of social exclusion.
Efficient Differentially Private F₀ Linear Sketching

A powerful feature of linear sketches is that from sketches of two data vectors, one can compute the sketch of the difference between the vectors. This allows us to answer fine-grained questions about the difference between two data sets. In this work we consider how to construct sketches for weighted F₀, i.e., the summed weights of the elements in the data set, that are small, differentially private, and computationally efficient. Let a weight vector w ∈ (0,1]^u be given. For x ∈ {0,1}^u we are interested in estimating ||x∘w||₁ where ∘ is the Hadamard product (entrywise product).Building on a technique of Kushilevitz et al. (STOC 1998), we introduce a sketch (depending on w) that is linear over GF(2), mapping a vector x ∈ {0,1}^u to Hx ∈ {0,1}^τ for a matrix H sampled from a suitable distribution ℋ. Differential privacy is achieved by using randomized response, flipping each bit of Hx with probability p < 1/2. That is, for a vector φ ∈ {0,1}^τ where Pr[(φ)_j = 1] = p independently for each entry j, we consider the noisy sketch Hx + φ, where the addition of noise happens over GF(2). We show that for every choice of 0 < β < 1 and e = O(1) there exists p < 1/2 and a distribution ℋ of linear sketches of size τ = O(log²(u)e^{-2}β^{-2}) such that: 1) For random H∼ℋ and noise vector φ, given Hx + φ we can compute an estimate of ||x∘w||₁ that is accurate within a factor 1±β, plus additive error O(log(u)e^{-2}β^{-2}), w. p. 1-u^{-1}, and 2) For every H∼ℋ, Hx + φ is e-differentially private over the randomness in φ. The special case w = (1,… ,1) is unweighted F₀. Previously, Mir et al. (PODS 2011) and Kenthapadi et al. (J. Priv. Confidentiality 2013) had described a differentially private way of sketching unweighted F₀, but the algorithms for calibrating noise to their sketches are not computationally efficient, either using quasipolynomial time in the sketch size or superlinear time in the universe size u.For fixed e the size of our sketch is polynomially related to the lower bound of Ω(log(u)β^{-2}) bits by Jayram & Woodruff (Trans. Algorithms 2013). The additive error is comparable to the bound of Ω(1/e) of Hardt & Talwar (STOC 2010). An application of our sketch is that two sketches can be added to form a noisy sketch of the form H(x₁+x₂) + (φ₁+φ₂), which allows us to estimate ||(x₁+x₂)∘w||₁. Since addition is over GF(2), this is the weight of the symmetric difference of the vectors x₁ and x₂. Recent work has shown how to privately and efficiently compute an estimate for the symmetric difference size of two sets using (non-linear) sketches such as FM-sketches and Bloom Filters, but these methods have an error bound no better than O(√{{m}}), where {m} is an upper bound on ||x₁||₀ and ||x₂||₀. This improves previous work when β = o (1/√{{m}}) and log(u)/e = {m}^{o(1)}. In conclusion our results both improve the efficiency of existing methods for unweighted F₀ estimation and extend to a weighted generalization. We also give a distributed streaming implementation for estimating the size of the union between two input streams.
Need of Sentiments Analysis with CF for Quality Recommendations

Recommendation system (RS) help user for purchasing the right product of their interest within the affordable right price. Presently many RS make use of only filtering methods to recommend products to the user which is not taking care of the quality of products. Quality of products can be found from textual reviews available on various e-commerce websites and hence this RS performs Sentiment Analysis (SA)of extracted relevant textual reviews along with Collaborative Filtering (CF) to give accurate and good quality recommendations to the user. Reviews are analyzed using optimized Artificial Neural Network (ANN) which shows notified improvement than traditional ANN on real-time extracted data of reviews.CF performance is proved by using the standard dataset of movilense used in many research papers. Results show high recall and accuracy of CF for the recommendation of products to the target user.
Study for the Validation of the FeetMe® Integrated Sensor Insole System Compared to GAITRite® System to Assess the Characteristics of the Gait in Patients with Multiple Sclerosis (4038)

Thursday, April 30April 14, 2020Free AccessStudy for the Validation of the FeetMe® Integrated Sensor Insole System Compared to GAITRite® System to Assess the Characteristics of the Gait in Patients with Multiple Sclerosis (4038)Anabel Granja Domínguez, Anja Hochsprung, Susana Palao Duarte, Cristina Páramo Camino, Aurora Alemán Rodríguez, Carmen Durán, Guillermo Navarro, Ana Venegas, Maria José Moreno, Basilio Hernández, and Guillermo IzquierdoAuthors Info & AffiliationsApril 14, 2020 issue94 (15_supplement)https://doi.org/10.1212/WNL.94.15_supplement.4038 Letters to the Editor
The Experimental Composition Improvisation Continua Model: A Tool for Musical Analysis

Among improvisers and composers today there is a resurgence of interest in experimental music (EM) practices that welcome contingency; engaging with unforeseen circumstances as an essential component of the music-making process, and a means to sonic discovery. I propose the Experimental Composition Improvisation Continua (ECIC) as a model with which to better understand these experimental musical works. The historical Experimental Music movement of the 1950s and 60s is briefly revisited, and the jazz tradition included as an essential protagonist; both being important historical movements leading to the formulation of ideas around contingent musical practices. The ECIC model is outlined as providing a means to observe the interactions and continua between composition and improvisation on the one hand and more or less experimentally conceived music on the other. This model is applied as an investigative and comparative tool to three distinctive works in order to illuminate the presence or otherwise of various experimental interactions within them. The works are: “Spiral Staircase” – a composition by written by Satoko Fujii in late 2007, John Cage’s 4′33″ , and a performance of “My Favorite Things” by the John Coltrane Quartet. Further possible applications of the ECIC are suggested in the conclusion.
Reading habits of secondary school students in Serbia

Reading habits are an essential aspect for creating a functionally literate society and for its positioning at the global level. In this regard, the aim of this paper is to examine quantities and contents that high school students read, including compulsory reading and other books that do not belong to this corpus. We also tried to examine students? opinions about ways that could contribute to their motivation to read books, to consider their reading habits keeping in mind the family context and the use of library services, as well as to determine whether reading books is related to gender, academic achievement, the type of school that the students attend, the class and the education of their parents. Students (N=1378) from high schools and secondary vocational schools from several cities in Serbia participated in the research. A questionnaire was used, constructed for the purposes of this study. The results show that adolescents are reluctant to read reading materials contained in the curriculum. The majority of students read books outside of this corpus, and they most often read comics, science fiction, crime and romance novels. More than one fifth of students do not recognise any way that would motivate them to read books. Since there has been no visible improvement in this area in teaching practice over the last decade, it would be desirable to introduce and affirm optional subjects that would contribute to improving the reading habits of high school students (especially in secondary vocational schools).
Analysis of twitter sentiment in COVID-19 era using fuzzy logic method

The sentiment is an assessment of attitudes towards certain events or things. Collecting opinion is known as a sentiment from existing data. This technique can also help analyze the opinions given by people in assessing certain objects. The best available source for gathering sentiment is the internet. In the era of the Covid-19 pandemic, many people access social media, especially Twitter to give their opinion on certain objects. Twitter is known as the social media that is accessed by users to post their opinions online. By using soft computing, especially fuzzy logic, it is possible to design, create and build bots that can analyze user opinions on Twitter. This model is used for data sentiment analysis on Twitter.
Secure Voting System Using Block Chain Technology

The element of safety and transparency is a danger to the standard scheme (offline) from still rampant election. General elections still use a centralized scheme, which is managed by one organization. Some of the issues that can arise in traditional electoral systems are with an organization that has complete control over the database and system. Block chain technology is one of the alternatives because it encompasses a decentralized system and many consumers own the entire database. Block chain itself was used as the decentralized banking system in the Bit coin scheme. One of the cheating sources of database manipulation can be reduced by implementing Block chain in the allocation of databases on e-voting devices. This study uses Block chain algorithms from every booth location to discuss the recording of voting results. Unlike Bit coin with its Work Proof, this thesis suggested a technique based on a predetermined scheme turn for each node in the Block chain constructed.
Smart Digital Forensic Framework for Crime Analysis and Prediction using AutoML

Over the most recent couple of years, the greater part of the information, for example books, recordings, pictures, clinical, forensic, criminal and even the hereditary data of people are being pushed toward digitals and cyber-dataspaces.This problem requires sophisticated techniques to deal with the vast amounts of data.We propose a novel solution to the problem of gaining actionable intelligence from the voluminous existing and potential digital forensic data.We have formulated an Automated Learning Framework ontology for Digital Forensic Applications relating to collaborative crime analysis and prediction.The minimum viable ontology we formulated by studying the existing literature and applications of Machine learning has been used to devise an Automated Machine Learning implementation to be quantitatively and qualitatively studied in its capabilities to aid intelligence practices of Digital Forensic Investigation agencies in representing, reasoning and forming actionable insights from the vast and varied collected real world data.A testing implementation of the framework is made to assess performance of our proposed generalized Smart Forensic Framework for Digital Forensics applications by comparison with existing solutions on quantitative and qualitative metrics and assessments.We will use the insights and performance metrics derived from our research to motivate forensic intelligence agencies to exploit the features and capabilities provided by AutoML Smart Forensic Framework applications.