Reviewerly/exHarmony huggingface dataset:
ANOMALY DETECTION IN DOCUMENT VERIFICATION SYSTEM USING DEEPLEARNING IN HYPERLEDGER

The educational industry is being integrated with technology and it has raised various challenges in maintaining the documents of academic details for each candidate in a longer period.The individual seeks higher education or recruiting for any industry then the verification of documents holding academic details is essential as well as to provide a reliable solution to avoid any academic fraud.Thus verification of certificates is done by blockchain in a completely decentralized transparent manner.Hyperledger Indy provides a digital identity that is rooted in blockchain for all records involved in the verification process.Records used for verification must not hold any anomalies to provide accurate data.Detecting anomalies is essential and increases the efficiency of the system.In this paper, an anomaly detection model is proposed for academic records data using deep learning by Keras on the top of the TensorFlow.Experimentation involves deep learning algorithms using the facial recognition model specifying some features like image size, facial weight, and width processing time all that are considered.The test results show that the proposed system model provides high performance, with high efficiency and low cost includes the minimum amount of processing time.By detecting, the anomalies using ML algorithms assure the trustworthiness of the documents involved with more transparent transactions.
Other Silicates: The Al2SiO5 Polymorphs, Cordierite, Staurolite, Epidote, Chlorite and Serpentine

In this article, important aluminosilicate and silicate minerals with metamorphic, igneous/pegmatitic and hydrothermal origins are described. These are: andalusite, kyanite, sillimanite, cordierite, staurolite, epidote, tourmaline, chlorite and serpentine. Andalusite, kyanite, sillimanite, staurolite and cordierite are important minerals in metamorphic rocks as their presence can provide key information regarding P-T conditions. The epidote and chlorite groups are particularly common in low-T hydrothermal alteration (greenschist facies) of basic igneous rocks and/or those containing ferromagnesian minerals. Tourmaline is a characteristic mineral of fractionated granites and associated hydrothermal alteration systems and is often used in the gem industry. The serpentine group of minerals is typically formed from the hydrothermal alteration of olivine and pyroxene; the fibrous chrysotile variety has been used extensively (as asbestos) in industry due to its thermal and chemical resistance qualities.
Digital forensics in private Seafile cloud storage from both client and server side

Nowadays, some people and organisations are unwilling to store their information on public clouds due to security and privacy problems. With increased use of established cloud services by cloud software, it is possible for malicious users to use these services for criminal purposes, so digital forensic investigations of these cloud services are necessary. Seafile cloud storage is one of popular cloud that is free and open source. In this paper, we document a series of digital forensic experiments on Seafile cloud storage service with the aim of providing forensic researchers and practitioners on both the client and server sides of Seafile. Data remnants are checked on client systems in virtual machines which running Windows 10 Home operating system and on a server with Windows Server 2012 R2 operating system. Different circumstances are created for digital forensic examinations. Correspondingly, Seafile client software and multiple browsers are used for interaction with Seafile cloud server.
Exploring the Effectiveness of Audacity Readers’ Theatre in Increasing Reading Motivation and Fluency Among Lower Primary ESL Learners

Being constantly motivated and capable to read fluently is one of the crucial aspects that should be acquired by an individual. This receptive skill is necessary in order to be able to decode written information and symbols of a language. The inability to read fluently imposes great threats to individuals as it may affect decoding skills and literacy. Low motivation and dysfluency in reading are regarded as the most blatant issues faced by learners in reading. This case study aimed to explore the effectiveness of Audacity Readers’ Theatre in increasing Year 2 pupils’ motivation and fluency in reading. The three Year 2 pupils were purposively selected due to their inability to read fluently and lack of motivation in reading. The main instrument used was the observation checklist where the lessons were observed and recorded by two observers. The pupils were interviewed to find out how Audacity Readers’ Theatre motivated and helped them to read more fluently. The researcher wrote journals after the lessons to keep a record on pupils’ behaviour and improvement throughout the lessons. Thus, the data from the semi structured interview and journal were used to triangulate the data from the observation checklist. The data which was analysed using thematic analysis illuminated on how Audacity Readers’ Theatre aided the pupils in heightening their motivation level and reading more fluently. The findings of the study revealed the necessity of incorporating Audacity Readers’ Theatre in the primary ESL classrooms to remedy problems of low motivation and dysfluency in reading.
Designing Strategic Games With Preestablished Nash Equilibrium Through Artificial Inference and Global Learning

This work presents significant results obtained by the application of global optimization techniques to the design of finite, normal form games with mixed strategies. To that end, the Fuzzy ASA global optimization method is applied to several design examples of strategic games, demonstrating its effectiveness in obtaining payoff functions whose corresponding games present a previously established Nash equilibrium. In other words, the game designer becomes able to choose a convenient Nash equilibrium for a generic finite state strategic game and the proposed method computes payoff functions that will realize the desired equilibrium, making it possible for the players to reach the favorable conditions represented by the chosen equilibrium. Considering that game theory is a very significant approach for modeling interactions between competing agents, and Nash equilibrium represents a powerful solution concept, portraying situations in which joint strategies are optimal in the sense that players cannot benefit from individually modifying their current strategies provided that other players do not change their strategies as well, it is natural to infer that the proposed method may be very useful for strategists in general. In summary, it is a genuine instance of artificial inference of payoff functions after a process of global machine learning, applied to their numerical components.
Demo

Visual tags (e.g., barcodes, QR codes)have become a prominent method of conveying digital information. Existing tags commonly rely on obtrusive visual patterns. Some methods of imperceptibly encoding data include using screens~\citekennedy2013visually or UV ink~\citemeruga2012security, complicating the tags with active components or requiring special manufacturing processes. We propose \name, a new design paradigm of passive visual tags which utilizes light polarization to unobtrusively encode data. \name\ consists of a thin, inexpensive polarizing film with layers of birefringent materials (e.g., everyday transparent tapes) judiciously applied atop. The birefringent layers disperse the polarization direction of outgoing light rays, resulting in color patterns only visible when viewed through a second polarizer. Such patterns are utilized to encode data. This color-changing feature can be used to boost the robustness of tag detection and support arbitrary tag shapes and designs that are not bound by geometric restrictions. In this demo, we present real-time decoding of invisible \name s with a mobile device.
Collusion Attacks in XOR Based RG-VSS

Visual secret sharing (VSS) is a well-known technique from the past few decades for data security. Recently, XOR based VSS has attracted many researchers due to its lossless or good visual quality of reconstructed secret image. Cheating in visual cryptography based VSS was introduced by Horng et. al. in 2006. Cheating occurs when a dishonest participant presents fake share and performs stacking of fake share with honest participants who have genuine share, thereby revealing the fake secret image instead of the original secret image. Cheating occurs when some XOR based VSS are exposed to collusion attacks. Here, in this paper, we have demonstrated and proved that there is a security issue in existing XOR based VSS schemes.
A Simulation Study on Latent Transition Analysis for Examining Profiles and Trajectories in Education: Recommendations for Fit Statistics

Latent transition analysis is an informative statistical tool for depicting heterogeneity in learning as latent profiles. We present a Monte Carlo simulation study to guide researchers in selecting fit indices for identifying the correct number of profiles. We simulated data representing profiles of learners within a typical pre- post- follow up-design with continuous indicators, varying sample size (N from 50 to 1000), attrition rate (none/10% per wave), and profile separation (entropy; from .73 to .87). Results indicate that the most commonly used fit index, the Bayesian information criterion (BIC), and the consistent Akaike information criterion (CAIC) consistently underestimate the real number of profiles. A combination of the AIC or the AIC3 with the adjusted Bayesian Information Criterion (aBIC) provides the most precise choice for selecting the number of profiles and is accurate with sample sizes of at least N = 200. The AIC3 excels starting from N = 500. Results were mostly robust towards differing numbers of time points, profiles, indicator variables, and alternative profiles. We provide an online tool for computing these fit indices and discuss implications for research.
Cross-VM Branch Prediction Analysis Attack: Scope Assessment and Simulation

Growing scope of cloud computing has made cloud security a challenging parameter. Among all the security parameters, virtualization security requires primary focus as it hides internal resource sharing details of the system. Side Channel Attack (SCA) is an attack that exploits the shared resource for extracting the private key of a cryptographic algorithm. Considering the significance of virtualization security, we need to analyze the SCA in a virtualization environment. In this paper, we target the Branch Prediction Analysis (BPA) Attack, one type of SCA. We have carried out an analysis to verify the scope of various BPA attack launching methods in virtualization environment along with the simulation. We have also analyzed the scope of existing solutions handling BPA attack.
An analysis of lexicogrammatical development in English textbooks in Turkey: A usage-based construction grammar approach

Abstract This article measures the syntactic development indices in grade 5-12 English textbooks in Turkey. Through a usage-based construction grammar approach, it argues that the textbooks show an inconsistent development in verb-argument constructions (VAC) and other usage-based indices. The study employs an automatic software tool that detects variations in these indices and runs a statistical analysis on a corpus compiled by the author. Statistically significant results demonstrate that textbooks lack lexicogrammatical variation. As such, learners who use these textbooks are likely to experience a limited array of VACs that are limited in lemma-construction combinations. Findings also indicate that learners may not be exposed to the conventional usage patterns and frequencies of VACs when compared against a reference corpus. These findings may have an influence on the learners’ generalization process, their low-proficiency level in English, and poor idiomatic uses of the language.
Cross Opposition Based Differential Evolution Optimization

Differential Evolutionary (DE) Algorithms is one of the most popular metaheuristic approach. For optimization purpose DE is very useful to solve various kind of problems. In addition to that the paper offers a Cross-Opposition Based Differential Evolution (CODE). An impression of Opposition-based learning (OBL) is incorporated in population initialization phase and in step of crossover. The performance of algorithm is analysed for different mutation strategies of DE and various other existing approaches. Results demonstrated that the algorithm outperform in terms of convergence speed, versatile population and dimension size.
Agile Software Development: Reusability and Customizability is key to Competitive Advantage

The study addresses the research issue of how software firms can compete in a dynamic industry through creating agile software development processes. It gives an insight into what a firm needs to do to equip its software process engineers to create flexible processes which can be customized specifically for the customer or reused for another customer without having to recreate them. Can these perceived process dimensions impact the competitive advantage of the firm? Survey design was used to collect responses from 100 software firms. Senior managers in the delivery departments were taken as respondents. The model and hypothesis were assessed on AMOS using structural equation modelling for path analysis. The results suggested that firms that can reuse the codes and customize the services specific to customers through training and development initiatives taken for employees are able to create competitive advantage in the industry. The improvement in the processes be having direct impact on the economic efficiency of the firm.
PENGEMBANGAN SISTEM INFORMASI AKADEMIK BERBASIS WEB SEBAGAI SISTEM PENGOLAHAN NILAI SISWA DI SMK NEGERI 1 KUDUS

This research aims to produce an information system of grade processing to allow the teacher in manage a report card of student grade. This information system is intended for use in vocational high school. This information system is web based, so it can be accessed by teacher to manage grades and students can see the result of their study. Method of this research is research and development (R&amp;D) that implemented in SMK Negeri 1 Kudus. The data collection techniques are interview, quesioner and documentation. The Development of Academic Information System as a Web Based on Processing System of Student Grade in SMK Negeri 1 Kudus carried out with five stages : (1) Communication is discussions between researchers with the school about developing the system, (2) Planning is the planning needs of the functional, software and hardware requirements of the system are developed, (3) Modeling is the stage of system design that focuses on data processing. This phrase begins with the making of Usecase Diagram, Flowchart, DFD (Data Flow Diagram), ERD (Entity Relationship Diagram), Design of data base tables and their relationships and manufacturing design of interface system, (4) Construction is the stage where the design has been created, implemeted into the code (programme), (5) Deployment is the testing phrase to SMK to get feedback on the feasibility and development of a system which further. The final value of this research is 93,1% from expert system, 85,3% from the teacher and administration staff and 82.,4 % from the students, so it means that the system is highly feasible to be used.
Application of physical techniques for establishment of homogeneous and heterogeneous intersecting strokes between laser toner and writing pen inks

In questioned document examination, establishing the sequence of crossing lines has always been a complex task for a forensic document examiner. This study aims to determine the sequence of homogeneous and heterogeneous crossing lines prepared by using laser printer and writing pen inks (ballpoint and gel pens) through optical methods. The samples were examined under stereomicroscope and LED microscope. The outcomes were based on examination of intersection under LED microscope and stereomicroscope. It was observed that stereomicroscope gave 100% accurate results in establishing the sequence of crossing lines of laser printer and writing pen inks (of same and different colours). Under LED microscope, the only feature observed was compression of laser toner stroke by ballpoint and gel pen ink lines.
Voice Recognition System Through Machine Learning

Human voice recognition by computers has been ever developing area since 1952. It is challenging task for a computer to understand and act according to human voice rather than to commands or programs. The reason is that no two human’s voice or style or pitch will be similar and every word is not pronounced by everyone in a similar fashion. Background noises and disturbances may confuse the system. The voice or accent of the same person may change according to the user’s mood, situation, time etc. despite of all these challenges, voice recognition and speech to text conversion has reached a successful stage. Voice processing technology deserves still more research. As a tip of iceberg of this research we contribute our work on this are and we propose a new method i.e., VRSML (Voice Recognition System through Machine Learning) mainly focuses on Speech to text conversion, then analyzing the text extracted from speech in the form of tokens through Machine Learning. After analyzing the derived text, reports are created in textual as well graphical format to represent the vocabulary levels used in that speech. As Supervised learning algorithm from Machine Learning is employed to classify the tokens derived from text, the reports will be more accurate and will be generated faster.
A Prediction of Emotions for Recognition of Facial Expressions using Deep Learning

Automated facial expression recognition can greatly improve the human–machine interface. Many deep learning approaches have been applied in recent years due to their outstanding recognition accuracy after training with large amounts of data. In this research, we enhanced Convolutional Neural Network method to recognize 6 basic emotions and compared some pre processing methods to show the influences of its in CNN performance. The preprocessing methods are :resizing, mean, normalization, standard deviation, scaling and edge detection . Face detection as single pre-processing phase achieved significant result with 100 % of accuracy, compared with another pre-processing phase and raw data.
FuzzSemNIC: A Deep Fuzzy Neural Network Semantic-enhanced Approach of Neural Image Captioning

Abstract Neural image captioning (NIC) is considered as a primitive problem artificial intelligence (AI) in which creates a connection between computer vision (CV) and natural language processing (NLP). However, recent attribute-based and textual semantic attention based models in NIC still encounter challenges related to irrelevant concentration of the designed attention mechanism on the relationship between extracted visual features and textual representations of corresponding image’s caption. Moreover, recent NIC-based models also suffer from the uncertainties and noises of extracted visual latent features from images which sometime leads to the disruption of the given image captioning model to sufficiently attend on the correct visual concepts. To solve these challenges, in this paper, we proposed an end-to-end integrated deep fuzzy-neural network with the unified attention-based semantic-enhanced vision-language approach, called as FuzzSemNIC. To alleviate noises and ambiguities from the extracted visual features, we apply a fused deep fuzzy-based neural network architecture to effectively learn and generate the visual representations of images. Then, the learnt fuzzy-based visual embedding vectors are combined with selective attributes/concepts of images via a recurrent neural network (RNN) architecture to incorporate the fused latent visual features into captioning task. Finally, the fused visual representations are integrated with a unified vision-language encoder-decoder for handling caption generation task. Extensive experiments in benchmark NIC-based datasets demonstrate the effectiveness of our proposed FuzzSemNIC model.
Approximating the finite Mellin and Sumudu transforms utilizing wavelet transform

In this study, some approximates for the finite Wavelet transform of different classes of absolutely continues mappings are presented using Wavelet transform of unit function. Then, with the help of these approximates, some other approximates for the finite Mellin and Sumudu transforms are given.
The Application of the Innovative Approaches in Communication and the Educational Processes

The influence and impact of innovations in a society is not identical and some innovations penetrate a society more radically: the influence of others may only be incremental. For example, in tourism a radical impact on marketing communication processes has come with the development of ICT technologies. Johanesson et al. (2001), Dosi (1982) associated revolutionary change with radical innovation, and the process of continual change and implementation of novelty considered as incremental innovation. Despite a more radical character, incremental innovations stem from market needs and are strategically easier to proceed with because a process of the implementation can be planned. The article will deal with the concepts of the innovative social technologies and their application in the teaching process. It means the study of successful cases, where the clusters of intelligence based on the diffusion of knowledge and the co-operation and mutual communication and partnership of the educational institutions with the innovative businesses.
Requirements Elicitation Technique Selection: A Five Factors Approach

Requirements Engineering phase is well recognized as a root of Software Development Life Cycle (SDLC) by research community. Requirements are elucidated through requirements elicitation methods conceded by requirement analyst. Requirements elicitation phase is planned and strategized to get complete acquaintance about user’s requirements and expectations. Current software industries having massive necessity to help requirements analyst in requirements elicitation process to carry out precise manner. Correct and refined requirements lead to successful software projects. Vague and incorrect requirements possibly will result in the defective software project. For successful software development, it is vital to recognize precise and accurate requirements for the software project. The progression of information technology has presented various requirements elicitation techniques and therefore analysts are provided with various likely options. Generally, the analyst selects elicitation technique according to company practice or their individual knowledge and skills. It is undefined on the selection of best elicitation techniques for certain situations under particular constraints and circumstances. Several guidelines do exist in literature for technique selection but most technique are theoretical rather than practical. In this research paper, deep knowledge of principal elicitation techniques is explained. After that a five facets model is proposed to select elicitation technique in which major aspects are project characteristics, software development process categories, organizational characteristics, stakeholder characteristics and analyst characteristics. We also demonstrate the suitability of the proposed framework via case studies and verified how the model uses relative knowledge of problem domain to select appropriate requirements elicitation technique for the software under construction.