Reviewerly/exHarmony huggingface dataset:
Information Seeking Behavior Through Internet Technology in Library Users, Chidambaram Town

The field of library and information looks at an is a remarkable interdisciplinary area of study, drawing as it does upon, for instance, the heads considers, programming designing correspondence studies and librarianship similarly as periphery subjects, for instance, Psychology, Linguistics and bits of knowledge to be viable in library and information mulls over must be envisioned as an authentic, composed and sensible whole while holding a versatility and responsiveness to change. Moreover, LIS tutoring and getting ready must consolidate a strong realistic section which must be totally given food to inside the instructive program. The arranging of instructive projects for this irrefutably huge subject which needs in different settings thought or denial of explicit topics and once in a while offering emphasis to certain individual focuses, for instance, information Technology is tangled and complex. The current examination intends to find the information searching for direct through web development in library customers, Chidambaram town. An instances of 125 library customers picked self-assertively were thought of. Basic data were accumulated by using a coordinated gathering booked. All the library customers were represented the a couple of requests in a comparative style and they were taught the explanation with respect to examine. Cross association and Chi-square test were applied to test the hypotheses. The disclosures and observations are the result a lot of the understandings made during the examination of assessment.
The Foreign Remittances, Long Term Sustainable Economic Growth Nexus in Pakistan: An Empirical Analysis Using Bound Testing Approach

Remittances are considered vital for the progress of any economy.  These are the finances that are sent by the immigrants and assist the nations to achieve their basic needs and to boost the living standard.   This research focuses on the effectiveness of foreign remittances regarding inflation and economic growth. The data used for this study are taken for the period 1972-2018 as yearly based. To check the stationary of the data Augmented Dickey-Fuller (ADF) test is used and the methodological framework includes the Autoregressive Distributed Lag (ARDL) model that concluded that the study concludes that foreign remittances have an optimistic and momentous relation with the economic growth of Pakistan. Thus, it should emerge that remittances are a superior tool to address transient poverty which occurs due to the shocks whether at the domestic or general level rather than a structural scarcity.
The effects of Assistive technology learning in a language course

Technology assisted learning is a phenomenon that has greatly changed the way learning is undertaken in the 21st century. Developments in information and communication technologies have led to the emergence of smart phones such as Blackberries and iPhones. The concept of mobile assisted learning, which is a subset of technology assisted learning, has emerged as a result of these technological developments. This paper is going to examine how technology assisted learning influence the effectiveness of the learning process. The following is a qualitative research where 20 male and 20 female university language instructor were interviewed, the results of the study show that mobile-assisted learning can improve grammar skills among students studying English, that Mobile-assisted learning is one of the best alternatives that can be used to compliment or replace face to face learning, that use of iPhone and Blackberry assisted learning has a potential of distracting students. Future research should be done on ways of improving mobile assisted learning so that this phenomenon can be adopted and replicated globally. Research should also focus on content and curriculum development. Future research should also be conducted to investigate whether the potential negative effects of mobile aided learning are valid.
Gradient Back-Propagation Algorithm in the Multi layer Perceptron: Foundations and Case Study

Training a multi-layer neural network is sometimes difficult, especially for novices in Artificial Intelligence. Many people believe that this training must be relayed to computers in order to be able to perform these ultra-powerful calculations. As a result, we can't figure out what is going on behind these calculations, thinking that there is too much mathematics, making it difficult for humans to understand what is at stake. Far from this mythical caricature stuck to neural networks. The training of a neural network consists in finding synaptic weights such that the output layer allows to classify with precision the observed values of a training set with the aim of allowing the created model to present generalisation capacities on examples that it will never have encountered during the training phase.
A Novel Data Hiding Approach Using Addition and Multiplication on Groups of Three Pixels

Due to the development of quantum computers in recent years, the topic of quantum image processing (QIP) in data hiding has begun to draw increasing attention. Also, since more and more digital image are transmitted via the internet, data hiding becomes feasible. The aim of data hiding algorithms is to raise the hiding capacity and preserve the original image quality. However, both goals are contradictive to each other. This paper presents an irreversible approach of data hiding in the spatial domain. Different from the traditional LSB methods, the proposed technique firstly divides the image into groups of three consecutive pixels and disassembles the bit sequence with secret message. Then, based on the combinations of addition and multiplication for the dissembled sets, the odd-even relationship among those three pixels are calculated and used to adjust their pixel values and embed the secret message. Experimental results have shown that the hiding capacity can reach to 41.67% and the image quality can be preserved.
MAHAMGOSTAR.COM AS A CASE STUDY FOR ADOPTION OF LARAVEL FRAMEWORK AS THE BEST PROGRAMMING TOOLS FOR PHP BASED WEB DEVELOPMENT FOR SMALL AND MEDIUM ENTERPRISES

Laravel is currently known as the best programming tool for PHP-based web development that is very interactive and intuitive, for more information please visit Laravel.com and learn more about this Framework for PHP as a kind of programming language. Hence, Small and Medium Enterprises (SMEs) with low budget and human resources are one of the major groups that tend to use Laravel, which is a web application framework with expressive, elegant syntax. For achieving the benefit of this technology as a new innovation, a multitude of factors influence the adoption of Laravel was conducted and funded by research department of Maham Gostar Company which could be reached at their verified company’s official website, https://www.mahamgostar.com/, additionally, this company pioneer in Information Technology (IT) solutions for SMEs and has been sponsored all kinds of start-up projects. To create and evaluate our proposed model, we found many factors which affect on adoption of Laravel as a new innovation, these decisive factors must be systematically evaluated prior to making the decision to adopt innovation solutions. The purpose of this study is to identify these factors and determine the extent to which they influence the adoption of Laravel for SMEs’ projects. Therefore, the project describes a research model that is based on the diffusion of innovation (DOI) theory and the technology, organization and environment (TOE) framework. Based on our previous study, research model was developed to test seven variables, which are: relative advantage, compatibility, security concerns, cost cost savings, technology readiness, top manager support, competitive pressure and regulatory support. Data would have been collected by survey questionnaires from a sample of SMEs that all of these SMEs would have been accepted for our sampling method and research scope due to their infrastructures and Laravel adoption have been verified by our expertise’s who involved more than one decade in this area. There would be many experts as our sampling method needs have been involved in information technology department from those SMEs would be selected to fill the questionnaires. The Smart PLS tool would been used for data analysis as the perfect tools for evaluating our proposed model. The results of the data analysis generally would have been supported the model, as well as all of the proposed hypotheses. In summary, the results of this research would be shown relative advantage, compatibility, security concerns, cost savings, technology readiness, top manager support, competitive pressure and regulatory support were found to have significant influence on adoption of Laravel for SMEs.
Android Studio In-Depth

Long-time users of IDEs like Android Studio usually develop a very strong, very parochial view of how important their chosen IDE is – not only to their productivity but also to their enjoyment of writing applications. In this chapter, my goal is to expose and explore some of the key features of Android Studio that will make you more productive and happier as you build your Android applications.
Optimasi Metode Particle Swarm Optimization (PSO) Pada Prediksi Penilaian Apartemen

One property that is currently being glimpsed by investors is an apartment. Property consulting companies as one of the service provider companies that become a link between apartment owners and apartment enthusiasts, have an important task in terms of providing information about the assessment of the offered institutions. This study will conduct a trial on the accuracy of apartment assessment predictions using the Support Vector Machine (SVM) method, then will be compared again with the results of the accuracy of the assessment method Support Vector Machine (SVM) combined using the optimization method Particle Swarm Optimization (PSO). The results of the combination of the application of SVM and PSO are used to optimize attribute selection in apartment valuation to improve the accuracy of using the SVM method. This study shows that the Particle Swarm Optimization (PSO) Support Vector Machine (SVM) method is a pretty good method of data classification, because it can seen from the increase in accuracy of 2.84% and AUC of 0.003. Subjects (attributes) that affect apartment valuation are seen from rent prices (price range), city (apartment location), size (area), furnisihing (equipment), bedroom (number of bedrooms), bathroom (number of bathrooms) and maids badroom (number of maid rooms). The results of the attribute testing showed that city attributes (apartment locations), furnisihing (equipment) and maid badroom (number of maid rooms) greatly influenced the valuation of an apartment.
Specificity of Students’ Emotional Exhaustion in the Context of Online Learning

in the article the specificity of emotional exhaustion of students in the conditions of online learning, characterized by an average level of emotional exhaustion, determined by: high reduction changes in educational and professional motivation; higher than the average degree of reduction changes in educational achievements; medium: exhaustion in the emotional sphere, exhaustion of a psychoemotional nature, distance from personal training, inadequate selective emotional response, reduction changes in the duties of the educational and professional type, resistance (resistance) to stress factors of online learning; below the average degree: disorientation of an emotional and moral nature, depersonalization processes, a deficit of emotional manifestations, exhaustion, tension, disorders of the psychosomatic and psychovegetative spectra, detachment of the personal plan, detachment of the emotional plan, experiencing circumstances of a traumatic nature, anxiety-depressive symptoms, saving emotions of the extended spectrum; low: personal dissatisfaction and the state of depression
EVALUASI TINGKAT USABILITAS WEB MOBILE PERGURUAN TINGGI NEGERI MENGGUNAKAN METODE USABILITY TESTING

Pademi Covid 19 has brought big changes to community activities. Digitalization is seen in various aspects, both industry, government and private institutions. The impact of this pandemic has also caused several industrial sectors to lay off their employees. Bank Indonesia released the industrial sector affected by Covid 19, including the education sector. The PSBB, which is implemented by the government, makes educational activities carried out from home, the learning process is carried out through digital media, not only that the registration process for prospective students and students is also carried out through digital media. Thanks to the Covid 19 Pandemic, internet users via mobile devices have also increased very rapidly. User experience in interacting with the web is something that must be considered by web designers and developers to provide convenience. Usability is a theory used to measure the quality of user interaction with an information system based on both web and mobile applications. From the results of this study, it can be concluded that the level of usability of the college mobile web can be concluded that the responsive design used as a mobile method by the college web has a high level of usability through the aspects of designing for a goal, layout, visual and interaction design and navigation.
Media Ecologies of the ‘Extractive View’: Image Operations of Material Exchange

AbstractExtraction displaces materials and reorganises habitats by accumulating resources – a process that renders populations and natural reserves as extractable data to be mobilised in systems of metabolic exchange. In contemporary practice, collecting, sorting, and processing this data require a complex interoperability between sensors, computing platforms, and databases before they are made into earth observation images. Following the scholarly research on the instrumentality of aerial survey in histories of extractive colonialism, this essay sheds light on the extractive capacity of remote sensing technologies in contemporary mining industries. Engaging with the media infrastructures of resource exploration, the inquiry revisits Heidi Scott’s theory of ‘colonialism’s vertical third dimension’ and extends it from the physical to the sensory, numerical, and temporal domains of extractivism. After Sean Cubitt’s classification of mediated earth observation, the three geomedia, the discussion is organised in three parts: electromagnetic sensing, numerical translations, and financial futures. A media-archaeological analysis of earth observation systems brings forth the extractive codes of the remote view by revealing its selective, vectoral, and speculative capacities in tapping the earth and ordering its resources into materials of exchange.Keywords: extractive view, mining industries, remote sensing, geomedia, digital image, aerial surveillance, urbanisation, datafication
Word Sense Disambiguation using Neural Networks

Word Sense Disambiguation (WSD) is the task of removing ambiguity in different senses of words. It is a core research field in computational linguistics dealing with the automatic assignment of senses to words occurring in a given context [11]. Humans are inherently good at WSD and distinguish senses used in words through spoken language. Computers on the other hand have difficulties identifying correct senses of words. Various advancements have been made in the task of disambiguation using mainly four approaches: Knowledge-based, Supervised, Semi-Supervised, and Unsupervised. Better understanding of the human language will help computer’s performance in various applications such as search engine optimization, information retrieval, information extraction, software assistants, and voice command interpretation. The objective of this work is to present a supervised neural network machine learning model using various algorithms dedicated to the task of maximizing accuracy of sense detection. The input layer of the neural network will consist of nodes having binary values depending on the presence or absence of frequently occurring context words related to the ambiguous words. The output layer will consist of nodes equal to the number of senses the ambiguous word has. Training and testing of the model will be done using lexical resources such as SemCor or OMSTI. Accuracy will be calculated based on All- Word tasks from SemEval International Workshops
PROBLEM BASE LEARNING MENGGUNAKAN FLATFORM MOODLE BERBASIS MOBILE UNTUK MENINGKATKAN MODEL PEMBELAJARAN DI PENDIDIKAN TINGGI

This study aims to improve and enhance the learning model in higher education by using a problem-based learning (PBL) model approach with a mobile-based Moodle platform. The data tested in this study consisted of 46 respondents, 20 lecturers and 26 students. The method used in this research is research and development in the Information Systems Audot Subject. The results showed that 80% of lecturers and 82.83% of students stated that this approach was practical to be used in the learning process. Therefore, this study can be a reference in the implementation of learning using the PBL approach with the Mobile-based Moodle platform at universities in Indonesia.
Performance Evaluation of Outlier Rules for Labeling Outliers in Multidimensional Dataset

The output of outlier detection algorithm applied to multidimensional dataset usually consists of scores defining the level of abnormality of each instance. However, this process per se does not identify the outlying instances. For this purpose, it is common to use an outlier rule to convert outlier scores into labels. The problem is therefore to determine an appropriate outlier rule, based on certain patterns of the scores alone. In order to deal with this problem, we studied and evaluated several traditional robust outlier rules following a pragmatic approach. The analysis of the results was facilitated by an evaluation measure developed by us. This measure was proved to be more effective than traditional measures involving only true positive and true negative rates. By using this measure, we were able to study the behaviour of different outlier rules whose performances were evaluated under varying skewness and contamination level.
Evaluating User Perception of Multi-Factor Authentication: A Systematic Review

Security vulnerabilities of traditional single factor authentication has become a major concern for security practitioners and researchers. To mitigate single point failures, new and technologically advanced Multi-Factor Authentication (MFA) tools have been developed as security solutions. However, the usability and adoption of such tools have raised concerns. An obvious solution can be viewed as conducting user studies to create more user-friendly MFA tools. To learn more, we performed a systematic literature review of recently published academic papers (N = 623) that primarily focused on MFA technologies. While majority of these papers (m = 300) proposed new MFA tools, only 9.1% of papers performed any user evaluation research. Our meta-analysis of user focused studies (n = 57) showed that researchers found lower adoption rate to be inevitable for MFAs, while avoidance was pervasive among mandatory use. Furthermore, we noted several reporting and methodological discrepancies in the user focused studies. We identified trends in participant recruitment that is indicative of demographic biases.
Goal-Centered Problem-Oriented Teaching Mode of EST Based on Superstar Platform

In order to solve the problem of low teaching effect of traditional teaching mode of English for science and technology, this paper innovatively proposes a goal problem oriented teaching mode of English for science and technology based on superstar platform.Through the analysis of the teaching objectives, teaching design and teaching effect of the mode, we can see that the teaching mode can stimulate students' interest in learning, promote curriculum teaching, effectively improve the quality of talent training, achieve the goal of talent training, and promote the development and construction of the school.
SFU-HW-Objects-v1: Object labelled dataset on raw video sequences

SFU-HW-Objects-v1 is a dataset of object labels for a set of raw video sequences. The dataset can be useful for the cases where both object detection accuracy and video coding efficiency need to be evaluated on the same dataset.This dataset was originally deposited in the Simon Fraser University institutional repository.
Library Guides: Virtual Library Orientation: Information for Parents

Welcome new students! Here is an overview of MSU Library - your resource for all of your information needs.
A Digital Framework for CSR Donations using Blockchain for Disaster Victims

This paper proposes the adoption of consortium blockchain technologies as a more efficient and effective means of transferring funds from corporate donors as part of corporate social responsibility to victims of natural disaster. The main benefit envisaged is that post-disaster disruptions to normal lives can be minimized or normal lives can resume better than the current situation as donation mechanism relies largely on manual and centralized processes. Using blockchain, corporations can donate fund anytime and this is especially useful for small and medium enterprises (SMEs) where they can donate in small amounts in a consistent manner to a fund setup for a disaster relief and recovery that disaster victim can use whenever required. The use case for this blockchain is corporate donors donating funds to victims of strong wind disaster in Brunei Darussalam. Through smart contracts of Ethereum, corporations incorporate details of donations and set out other requirements. A Brunei Government’s agency use of set of criteria can be used as part of the smart contract terms and conditions. These smart contracts can be part of decentralized applications that can be deployed to the blockchain network using cryptographic mechanisms to ensure security and integrity of the transactions. By this way, more companies are motivated to participate in donations while ensuring that victims can receive much needed assistance in the shortest time possible without solely relying on centralized bureaucratic processes.
Secure Encryption then Compression Systems using Encryption Algorithms

A new grayscale-based block scrambling image encryption algorithm is introduced to enhance the security of Encryption-then-Compression (EtC) systems, which are used to securely transmit images over an untrusted channel provider. This algorithm is designed to improve the security of Encryption-then-Compression (EtC) systems. A smaller block size and a greater number of blocks are possible with the proposed scheme in comparison to the new encryption system. In spite of the fact that the original image contains three colour channels, photos encrypted using the suggested approach contain less colour information because grayscale images are used to encrypt the information. These features, among other things, improve security against threats such as jigsaw puzzle solvers and brute-force assaults, among others. Apart from that, even though the encrypted photos do not contain any colour information, it allows for colour sub-sampling, which can increase the compression speed of the photos. In an experiment, encrypted photos were uploaded to and then downloaded from social networking sites, and the results revealed that the suggested approach is successful for ETC systems while still maintaining excellent compression performance by utilising advanced compression algorithms.