Reviewerly/exHarmony huggingface dataset:
Estimating the Secret Message in the Digital Image

In this paper, a new method for estimating the secret message in the digital image.The actual concept involved in this paper is that the secret message is embedded into the cover image at random pixel in the last two positions of the LSB.Due to this technique, the length restriction of the LSB method of hiding the data is enhanced.Since the previous two bits of the Least Significant Bits are altered the possibility of having a substantial content of information is possible.This technique will overcome the problems faced by many other steganography techniques like LSB, Filtering, Masking, etc...In the face of having only short messages embedded into the image.
Curves over Finite Fields and Permutations of the Form x k

We consider the polynomials of the form $P(x)=x^k-\gamma \mathrm{Tr}(x)$ over $\mathbb{F}_{q^n}$ for $n\geq 2$. We show that $P(x)$ is not a permutation of $\mathbb{F}_{q^n}$ in the case $\gcd(k, q^n-1)>1$. Our proof uses an absolutely irreducible curve over $\mathbb{F}_{q^n}$ and the number of rational points on it.
Bayesian semiparametric latent variable model with DP prior for joint analysis: Implementation with nimble

Multiple responses of mixed types are naturally encountered in a variety of data analysis problems, which should be jointly analysed to achieve higher efficiency gains. As an efficient approach for joint modelling, the latent variable model induces dependence among the mixed outcomes through a shared latent variable. Generally, the latent variable is assumed to be normal, which is not that flexible and realistic in practice. This tutorial article demonstrates how to jointly analyse mixed continuous and ordinal responses using a semiparametric latent variable model by allowing the latent variable to follow a Dirichlet process (DP) prior, and illustrates how to implement Bayesian inference through a powerful R package nimble. Two model comparison criteria, deviance information criterion (DIC) and logarithm of the pseudo-marginal likelihood (LPML), are employed for model selection. Simulated data and data from a social survey study are used for illustrating the proposed method with nimble. An extension of DP prior to DP mixtures prior is introduced as well.
ADJUSTING GENERAL ELECTRIC MULTIFACTOR PORTFOLIO MODEL FOR FUZZY ANALYSIS OF SBUS PERFORMANCES

Traditional General Electric Multifactor portfolio model is designed to serve as a strategic tool for analyzing strategic business units (SBUs) in diversified organizations and it can be used for optimally allocating resources among those various SBUs.Some of the limitations related to the implementation of this model refer to the difficulties in identifying and assessing critical internal and external criteria required for the matrix construction and in its inability to precisely determine the numerical value for the certain criteria.Since Fuzzy sets theory represents a strict mathematical framework for dealing with the problems of imprecision and making decisions under ambiguous conditions, the aim of this paper is to introduce an alternative approach to the quantification of the General Electric Multifactor portfolio model which includes the utilization of fuzzy logic.In that sense, specific characteristics of fuzzy triangular numbers are applied to the standardized GE/McKinsey matrix in order to extract the optimal strategy solutions and adequately handle the uncertainty and imprecision associated with the subjective assessment of Strategic Business Unit (SBU) performances based on two dimensions: industry attractiveness and internal business strength.
BluePass: A Mobile Device Assisted Password Manager

With the growing number of online accounts a user possesses, managing passwords has been unprecedentedly challenging.Password managers have emerged to help users managing their passwords.However, state-ofthe-art cloud based password managers are vulnerable to data breach and a master password becomes a single point of failure.To address these security vulnerabilities, we propose BluePass, a password manager that stores the password vault (i.e., the set of all the encrypted site passwords of a user) locally in a mobile device and a decryption key to the vault in the user computer.BluePass partially inherits the security characteristics of two-factor authentication by requiring both a mobile device and a master password to retrieve and decrypt the site passwords.BluePass leverages short-range nature of Bluetooth to automatically retrieve site passwords and fill the login fields, providing a hand-free user experience.
Private cloud storage implementation using OpenStack Swift

The use of distributed and parallel computer systems is growing rapidly, requiring an appropriate system to support its work processes. One technology that supports distributed computer systems is cloud computing. This system can generate the need to maximize the use of existing computing resources, one of which is in the form of cloud-based storage. The computer laboratory of Informatics Department of Petra Christian University has very large resources, but they have not been optimized in the utilization of existing storage devices. This condition gives the idea to utilize computers in the laboratory with cloud, so the storage can be used well. This implementation used the OpenStack cloud framework, which could provide IaaS service. From some existing OpenStack services, storage management used OpenStack Swift on its processing. OpenStack Swift is a cloud-based storage service that leverages various computing resources. After the implementation process, testing was done by way of data management, so storage could store, retrieve, and delete data. In addition, testing was also done by turning off some physical machines to ensure cloud services could remain well accessible, and measure the speed of data transfer in cloud storage. The resulting data was used to evaluate the cloud storage systems that had been created.
A comparison between the secp256r1 and the koblitz secp256k1 bitcoin curves

&lt;p&gt;&lt;span&gt;Bitcoin uses elliptic curve cryptography for its keys and signatures, but the specific secp256k1 curve used is rather unusual. The ECDSA keys used to generate Bitcoin addresses and sign transactions are derived from some specific parameters. Due to this characteristic, several questions come up concerning Satoshi’s choice of this curve rather than that of the NIST standard secp256r1 curve. Former President Dan Brown’s address to Bitcoin users on the Bitcoin talk.org online forum concerning the use of secp256k1 in Bitcoin of SECG showed his surprise to see someone uses SECG secp256k1 instead of secp256r1 of NIST.&lt;/span&gt;&lt;span&gt;In this article, we will analyze the random secp256r1 curve and the Koblitz Secp256k1 curve (parameters, equation, automorphism…), by giving the strengths and weaknesses of each one of them, in order to justify the choice of Bitcoin’s creator, and then we will tackle the mining using the new graphic cards.&lt;/span&gt;&lt;/p&gt;
Exploratory Factor Analysis for Software Development Projects in Mexico

Time and risk management have always been major concerns in a continuously growing number of processes or methodologies used to develop all kinds of useful products and services. Software like any other industry not only needs the most appropriate development methodology but also an efficient project management strategy that is capable of estimating and managing development times and any potential risks as best as possible in order to deliver high quality software products and services on time. Hence, the success or failure of software development projects depends on the efficiency by which several key factors such as cost, time, and risks are managed and how other software development factors influenced them. This paper presents an exploratory factor analysis to study the effects produced primarily on time planning caused by common factors observed in outsourced software development projects such as communication, teamwork, personnel training, among others. In our work, we also build a structural model in which we analyze the relationships between sets of dependent and independent variables derived from the responses of a survey applied to 32 Mexican organizations that subcontracted their software development projects to outsourcing providers. The results are presented and the reliability of our model was validated using the SmartPLS software.
PERFORMANCE EVALUATION OF MULTIPLE TRANSFORM WATERMARKING SYSTEM FOR PRIVACY PROTECTION OF MEDICAL DATA USING PSNR AND NC

This paper presents the performance evaluation of a developed multiple transform watermarking system for privacy protection of medical data using Peak Signal to Noise Ratio (PSNR) and Normalized Cross-Correlation (NC).The PSNR was used to evaluate the imperceptibility of the system, while the NC was used to evaluate the robustness of the system under the various attacks include: Gaussian noise, pepper and salt noise, sharp enhancing, image cutting, image compression, low pass filter and image rotation.The obtained result showed that the similarity between original image and watermarked image has PSNR of 52.4595dB as compared to the existing system of 50.0285dB.This indicates that the proposed scheme can conceal the watermark better, and as well retains the image quality.
POLITENESS PRINCIPLE: PRESIDENT JOKO WIDODOâ€™S SPEECH ACT IN VIDEO BLOG

ABSTRACT&#x0D; The aim of the research is analyzing the utterances of Mr. Joko Widodo as president of Indonesia with vloggers. In this study, the writer analyzes the rules of president conducting his utterances at vloggersâ€™ vlogs. The vlogs taken from skinnyindonesian24 which has 1.3M subscribers and Arif Muhammad which has 1.5M subscribers (data per November 25, 2018). The data taken and analyzed both qualitative and quantitative data. The elaboration of the methods used to measure language politeness, to count the data whether politenes or not. The data taken from Arif Muhammadâ€™s vlog (1.596.033 subscribers) which entitle Ngevlog bareng Presiden and SkinnyIndonesian24 were created by brothers Andovi da Lopez and Jovial da Lopezâ€™s vlogwho have 1.344.548 subscribers entitleHow to Become a President. The result of this research imply both of the vlogs Mr. Joko Widodo applies politeness strategies even in informal situation both vlogs. He acts extraordinary pragmatic forces and high politeness. So that, the audience gets the emotion, sympathy and persuasion of those who watches of them at vlog.&#x0D; Keywords: politeness principal, speech acts, vlog, pragmatics
THE DESIGN OF EXPERT SYSTEM FOR DETERMINING THE INITIAL DIAGNOSIS OF TROPICAL INFECTIOUS DISEASES IN INDONESIA WITH NAIVE BAYES METHOD-BASED ANDROID

Tropical infectious diseases are frequent, serious and concerning for the people in Indonesia. Tropical infectious diseases can be fatal and cause death. But if we diagnose them earlier and get proper treatment, the story can be changed. In this research will make a mobile application using Naive Bayes and Forward Chaining methods for early diagnosing tropical infectious diseases including typhoid fever, dengue fever, tuberculosis, malaria, and measles. The process of this application will start with input of the symptoms felt by users, after the data collected, system will calculate the data with Naive Bayes formula. This application using 147 data training from interviewed with the experts. Based on the tests by System Usability Scale method shows above average users rating 73.875 %, which means the results of the application are acceptable. And Confusion Matrix method shows performance of the application as high as 76.74 %.
Bodygramming. Embodying the computational behaviour as a collective effort

(2019). Bodygramming. Embodying the computational behaviour as a collective effort. The Design Journal: Vol. 22, Running with Scissors: 13th International Conference of the European Academy of Design, Dundee, 10-12th April, 2019, edited by Louise Valentine, Joanna Bletcher and Leon Cruickshank, pp. 1423-1437.
The Now and Future MarcEdit: A Day-Long Workshop

On Thursday, June 7, as part of the NASIG 2018 preconferences, Terry Reese led a day-long workshop entitled “The Now and Future MarcEdit: A Day-Long Workshop.” MarcEdit, a metadata editing utility, was originally designed and created by Reese in 1999 at Oregon State University. The workshop focused on the enhancements and other changes made to the program by the MarcEdit 7 update, released at the end of 2017. The workshop also provided an overview of the basic functionalities of MarcEdit, using examples provided by Reese coupled with questions from audience members.
Publisher Correction: Information flow reveals prediction limits in online social activity

The original and corrected figures are shown in the accompanying Publisher Correction.
A Bibliometric Investigation of Cloud Computing and Education Research

The educational system comprises a variety of teaching and learning activities and these activities have also benefited from the adoption of cloud computing technologies.The aim of this study was to quantify and analyze the volume of research outputs chronicling the adoption of cloud computing in education using bibliometric methods.A bibliometric analysis was carried out on 840 documents published from 2011-2017 and retrieved from the SCOPUS database based on defined search terms relating to cloud computing and Education.The analysis results revealed that there was an increase of interests in cloud computing and education research since 2011.King Abdulaziz University in Saudi Arabia was the most productive institution in this domain, whereas, China emerged as the country with the highest contribution to this cloud computing and education research.Mariya Shyshkina of National Academy of Sciences in Ukraine emerged as the most prolific author in cloud computing and education research.The trend of cloud computing and education research revealed it had a major impact on engineering education as well as, higher education than elementary and secondary school education.The publication trend in the domain of cloud computing and education portend growth in the future.
Deplyoing Advance Data Analytics Techniques with Conversational Analytics Outputs for Fraud Detection

This paper outlines the application of various classification methods and analytical techniques to identify a potential fraud.The aim of this document is to showcase the usefulness of such classification and analytical techniques for fraud detection.Considering the fact that there are hundreds of statistical methods and procedures to perform such analysis.In this paper, I would like to present a hybrid fraud detection method by using the Bayesian Classification technique to identify the risk group; followed by Benford's Law (The Law of First Digit) to detect a fraudulent transaction done by the identified risk group.Though this analysis focuses on the healthcare dataset, however, this technique can be replicated in any industry setup.Also, by adding the Voice of the Customer data to these classification and statistical methods, makes this analysis even more powerful and robust with improved accuracy.
PROFESSIONAL COMPETENCES OF MUSIC TEACHER: ATTITUDE OF STUDENTS

The importance of the teacher's role in society is predetermined by developing and everincreasing advances in science, technology and social relations, which also create new demands for young people and adults.This article analyses expectations of students (pre-service music teachers) about the competences of a contemporary music teacher.The concept of the professional music teacher is revealed and validated; successful professional activities of music teachers are also highlighted.The data of the qualitative research (content analysis) related to the music teacher's personal traits, general pedagogical and subject-specific competences are introduced.It has been revealed that scholarly music teachers have certain traits, which reveal themselves through the teacher's professionalism, competence, personal qualities and values.
A Knowledge-Based Filtering Method for Open Relations among Geo-Entities

Knowledge graphs (KGs) are crucial resources for supporting geographical knowledge services. Given the vast geographical knowledge in web text, extraction of geo-entity relations from web text has become the core technology for construction of geographical KGs; furthermore, it directly affects the quality of geographical knowledge services. However, web text inevitably contains noise and geographical knowledge can be sparsely distributed, both of which greatly restrict the quality of geo-entity relationship extraction. We propose a method for filtering geo-entity relations based on existing knowledge bases (KBs). Accordingly, ontology knowledge, fact knowledge, and synonym knowledge are integrated to generate geo-related knowledge. Then, the extracted geo-entity relationships and the geo-related knowledge are transferred into vectors, and the maximum similarity between vectors is the confidence value of one extracted geo-entity relationship triple. Our method takes full advantage of existing KBs to assess the quality of geographical information in web text, which is helpful to improve the richness and freshness of geographical KGs. Compared with the Stanford OpenIE method, our method decreased the mean square error (MSE) from 0.62 to 0.06 in the confidence interval [0.7, 1], and improved the area under the receiver operating characteristic (ROC) curve (AUC) from 0.51 to 0.89.
LANGUAGE LEARNING STRATEGIES EMPLOYED BY SUCCESSFULL STUDENTS IN DEVELOPING ENGLISH-SPEAKING PERFORMANCE

This research aimed to discover the language learning strategies used by successfull students in developing speaking performance in speaking performance at English Language Education Program in Universitas Muhammadiyah Sorong. This research used qualitative method in the form of descriptive qualitative. the participants of this research were taken from the third semester of English Language Education Program in Universitas Muhammadiyah Sorong with the total 6 students. The participants were the students who gained score A in speaking class. Based on the data gathered, the result showed that the students applied both of Direct and Imdirect learning strategies in developing their speaking English Language Education Program in Universitas Muhammadiyah Sorong, namely social strategies, metacognitive strategies, affective strategies in Indirect Strategy and memory strategies, cognitive strategies, and compensation strategies in Direct Strategy. From those of six strategies applied, most of the students tended to apply Indirect Strategy that was social strategies by asking help, working in pair, practicing with the proficient user of English and making small group discussion.
Virtual microscopy enhances the reliability and validity in histopathology curriculum: Practical guidelines

<ns4:p>This article was migrated. The article was not marked as recommended. Digital pathology innovation and application in medical education have paved the path for a significant shift in the advancement of the medical curriculum. The new technology of virtual microscopy is a proven reliable and valid pedagogy method for histopathology learning objectives, and assessments. The current transformation has brought educators around the globe nearer towards the goal of achieving competence in Curriculum Inventory in the medical curriculum. This paper emphasises the practical tips and guidelines for cost-effective implementation and the successful use of Virtual Microscope technology to enhance the histopathology curriculum in a medical school.</ns4:p>
A Survey on the Effectiveness of Hololens and Augmented Reality in Education

Augmented Reality or AR is a largely used term since the invention of Microsoft Hololens and the use of AR in mobile applications. With the help of advanced AR, information about the real world of the user has become interactive and digitally manipulable. Augmented or mixed reality (AR or MR) has recently become easily accessible to professionals, with the release of Microsoft's Hololens. Hololens is an untethered, fully self-contained Windows 10 computer that rests comfortably on user's head and lets a user create holograms, that appear in the world around the user, just as if they are real objects. The user can interact with AR applications through head movements, gestures and voices. This survey paper is the starting phase of planning a project to do in educational field to enhance interests of computer engineering students using various existing application ideas in learning and hence analysing the effectiveness of Hololens for Augmented Reality applications in various interests of education.
Application of Extension Neural Network Type 2 and Chaos Theory to the Electrocardiogram Recognition System

In this study, we combined the extension neural network type 2 (ENN2) with the chaos theory in the electrocardiogram (ECG) recognition system.The self-developed hardware measurement circuit and LabVIEW human-machine interface were used to measure and capture ECG signals.The master-slave chaos system was adopted to change the stored ECG data into a chaotic dynamic error distribution graph to obtain the chaotic eye coordinates of specific ECG signals.ENN2 was used for recognition.There were 36 research subjects.The first half of the data were measured using the signal capture circuit, while the second half were provided by the medical center of Massachusetts Institute of Technology (MIT).According to the results of analysis, the proposed method has a high accuracy when applied to the classification of ECG recognition, with a recognition rate of up to 89%.Hence, the automatic diagnosis ECG system designed in this study can effectively categorize irregular heart rhythms and reduce the huge labor cost for reading.
Extensions of the Caucal Hierarchy?

The Caucal hierarchy contains graphs that can be obtained from finite graphs by alternately applying the unfolding operation and inverse rational mappings. The goal of this work is to check whether the hierarchy is closed under interpretations in logics extending the monadic second-order logic by the unbounding quantifier $$\mathsf U$$ . We prove that by applying interpretations described in the MSO+ $$\mathsf {U^{fin}}$$ logic (hence also in its fragment WMSO+ $$\mathsf U$$ ) to graphs of the Caucal hierarchy we can only obtain graphs on the same level of the hierarchy. Conversely, interpretations described in the more powerful MSO+ $$\mathsf U$$ logic can give us graphs with undecidable MSO theory, hence outside of the Caucal hierarchy.
Convolutional Neural Network based Recognition of Myanmar Text Warning Sign for Mobile Platform

Recognizing text image from mobile phone is a challenge task for limited capacity and processing power.And also the accuracy of the system is important for text image recognition system.In this paper, we aimed to develop a Text Image Recognition System for mobile environment using Myanmar Character Dataset.Firstly, the image captured from mobile phone's camera and then segment each connected character using Connected Labeling Algorithm.After that, this connected components passed through layer by layer into the Convolutional Neural Network to recognize the words in a given warning text sign.This paper present Myanmar character recognition from various warning text signboards using end to end recognition of Convolutional Neural Network.