Reviewerly/exHarmony huggingface dataset:
Handwritten Signature and Text based User Verification using Smartwatch

Wrist-wearable devices such as smartwatch hardware have gained popularity as they provide quick access to various information and easy access to multiple applications. Among the numerous smartwatch applications, user verification based on the handwriting is gaining momentum by considering its reliability and user-friendliness. In this paper, we present a novel technique for user verification using a smartwatch based writing pattern or style. The proposed approach leverages accelerometer data captured from the smartwatch that is further represented using 2D Continuous Wavelet Transform (CWT) and deep features extracted using the pre-trained ResNet50. These features are classified using an ensemble of classifiers to make the final decision on user verification. Extensive experiments are carried out on a newly captured dataset using two different smartwatches with three different writing scenarios (or activities). Experimental results provide critical insights and analysis of the results in such a verification scenario.
Effect of Nitrogen Oxides on Shortwave Solar Radiation in Atmosphere for Selected Iraqi Stations

Abstract It is known that the incoming solar radiation is subject to interaction with the components of the Earth’s atmosphere. This reaction is expressed by the mechanisms of absorption, scattering and reflection. The occurrence of each mechanism depends on the size of the particles in relation to the wavelength of the incoming radiation. The study of the interaction of solar radiation with atmospheric components, including aerosols, has attracted long scientific interest; this interaction is associated with climate change issues. Among the components in the atmosphere, attention was paid to human-derived nitrogen dioxide (NO 2 ) in the troposphere, as it was found that anthropogenic aerosols play an important role in its interaction with incoming solar radiation. For this reason, the behavior Nitrogen Oxides gas has been studied with the elements of solar radiation to know the effect of Nitrogen Oxides gas on shortwave solar radiation (Surface net solar radiation (SSR) Surface net solar radiation, clear sky (SSRC) Surface solar radiation downwards (SSRD) TOA incident solar radiation (TISR) Top net solar radiation (TSR)) by using data the European Center for Medium-Range Weather Forecasts (ECMWF) as the monthly mean at the time (12:00 pm) for ten years (2009 - 2018) over selected stations in Iraq (Mosul, Baghdad, Basra).
Semantically Enhanced Web Service for Global Supply Chain Disruption Management

The recent coronavirus pandemic has now unleashed a global supply chain crisis across a huge number of organizations, stemming from a lack of understanding and flexibility of the multiple layers of their global supply chains and a lack of diversification in their sourcing strategies. One of the technical options to mitigate the pandemic is to automate business processes by which heterogeneous data integration is encouraged. The convergence of Semantic Web with service-oriented computing is manifested by Semantic Web services technology. It addresses the major challenge of automated, interoperable, and meaningful coordination of web service composition in industrial applications – such as apparel business. Automatic service composition may dramatically improve the development efficiency of web service applications. This chapter proposes an approach to automatically process semantic service composition (SSC) using description logics (DLs) to provide well-defined semantics. Also, this chapter explains the role of ontologies in the architecture of the Semantic Web.
Comparing psychological characteristics with organizational conflicts and occupational innovation barriers

This study aims to assess the auditor's psychological characteristics (self-consciousness, envy, prejudice, trust, cautiousness, happiness, agility, shyness, aggressiveness, forgiveness) on organizational conflicts and occupational innovation barriers in Iraqi audit firms. In other words, the study attempts to answer the question that “whether the psychological characteristics of the auditor can settle the organizational conflicts and occupational innovation barriers of audit firms or not.”,The statistical population includes 195 employed auditors in Iraqi audit firms, among whom 131 participants are selected using the Cochran sampling method in 2020.,The results show a positive and significant relationship between auditors' psychological characteristics, organizational conflicts and occupational innovation barriers in audit firms.,Since no study is carried out so far on the effect of different types of psychological characteristics on organizational conflicts and occupational innovation barriers in Iraqi audit firms, this paper can provide useful information and contribute to science and knowledge development.
Analysis of COVID-19 Rebound Based on Natural Language Processing

The novel coronavirus epidemic hasn't finished in the world. The number of people who come down with this disease keeps increasing. Besides, people make some comments on the website, which may be related to the epidemic situation. This work will analyze this relationship and make some suggestions to governments. First, the crawler is used to get the data of public emotion. NLP is the main method in this work, which can classify the words we get based on an emotion dictionary. In the end, we do some further analysis and give the warning line of confirmed cases by regression, whose value is around 30 people.
ENABLING DATA SECURITY IN CLOUD COMPUTING THROUGH REMOTE DATA INTEGRITY AUDITING

Health-records are an essential information for everyone. User cannot carry all the health records of a patient everywhere whenever required, as it may lead to misplacing of documents and may get placed in the wrong hands. To solve this obstacle, remote data integrity audit proposal has been introduced, that facilitates the sharing of data and hides crucial data ensuring the condentiality of the information stored in the cloud. The proposed system aims at preserving user privacy in an Electronic Health Records (EHR) system using the blockchain technology (EHR-BT). The scheme generates blocks of equal length of the le with condential data and turns the signatures of data blocks into legitimate le access data blocks. With the integrity audit phase, signatures are used to certify the integrity of the le, as well as ensures the privacy and immutability of information.
Development of an Advanced Solar Tracking Energy System

Abstract This paper describes the design of an advanced solar tracking system development that can be deployed for a range of applications. The work focused on the design and implementation of an advanced solar tracking system that follow the trajectory of the sun’s path to maximise the power capacity generated by the solar panel. The design concept focussed on reliability, cost effectiveness, and scalability. System performance is of course a key issue and is at the heart of influencing the hardware, software and mechanical design. The result ensured a better system performance achieved. Stability issues were also addressed, in relation to optimisation and reliability. The paper details the physical tracker device developed as a prototype, as well as the proposed advanced control system for optimising the tracking.
Probabilistic Graph Matching with Multiplicative Updating Algorithm for Correspondence between Remote Sensing Images

Point correspondence is an important problem in remote sensing images matching task which lays the foundation for the image registration task. Due to the existence of the rotation transformation and the large scale, and the change of scenery between the two obtained images, the point correspondence problem is still challenging. Tradition algorithms such as the SIFT and SURF aim at using the point appearance to find the point correspondence. However, when the above situations happens, the appearance based algorithms will fail to solve the problem. In this paper, the structural information between points is introduced to the correspondence problem and a spectral graph matching algorithm is proposed based on the probabilistic scheme and the multiplicative updating scheme. The proposed algorithm has three advantages compared with the traditional algorithms. First, incorporating the structural cues to the matching problem makes it more robust to the large scale and the geometric transformation. Second, the best assignment between points which is interpreted by a probabilistic manner is figured out by ranking the probabilities. Third, the optimization problem is solved by an approximate spectral method efficiently and a multiplicative updating algorithm is introduced to ensure the final discrete solution. Experiments on the real remote sensing images validate the effectiveness of the proposed algorithm.
Reply to “Comment on ‘Quick Estimation of the Magnitude and Epicentral Distance Using the <i>P</i> Wave for Earthquakes in Iran’ by Reza Heidari” by Sahar Nazeri, Jamaledin Baniamerian, and Zaher Hossein Shomali

Reply| May 04, 2021 Reply to “Comment on ‘Quick Estimation of the Magnitude and Epicentral Distance Using the P Wave for Earthquakes in Iran’ by Reza Heidari” by Sahar Nazeri, Jamaledin Baniamerian, and Zaher Hossein Shomali Reza Heidari Reza Heidari * 1Department of Earth Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran *Corresponding author: r.heidari@srbiau.ac.ir Search for other works by this author on: GSW Google Scholar Bulletin of the Seismological Society of America (2021) 111 (3): 1663–1664. https://doi.org/10.1785/0120200324 Article history first online: 04 May 2021 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Reza Heidari; Reply to “Comment on ‘Quick Estimation of the Magnitude and Epicentral Distance Using the P Wave for Earthquakes in Iran’ by Reza Heidari” by Sahar Nazeri, Jamaledin Baniamerian, and Zaher Hossein Shomali. Bulletin of the Seismological Society of America 2021;; 111 (3): 1663–1664. doi: https://doi.org/10.1785/0120200324 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search Recently, a comment named “Comments on “Quick Estimation of the Magnitude and Epicentral Distance Using the P Wave for Earthquake in Iran by R. Heidari,” was submitted to BSSA by Nazeri et al. (2021). The authors have commented on the validity and accuracy of the developed empirical relationships for an earthquake early warning system (EEWS), using B−Δ approach by Heidari (2016). After carefully reading the comment, I find their statements that my work is wrong to be untrue and not valid. In the B−Δ and C−Δ approaches used in EEWS, the... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
Stage performance layout design based on artificial intelligence technology

The main purpose of stage performance arrangement is to improve the audience’s satisfaction with the stage performance. For this purpose, the stage performance arrangement design method based on artificial intelligence technology was explored. In the process of stage performance action retrieval, the offline link uses the method of frame distance definition based on quaternion in artificial intelligence technology to construct the structure of motion database digraph; the real-time link determines the corresponding vertex and edge in the digraph. According to the vertices and edges in the directed graph, the performer’s trajectory was determined, and the multi-resolution filtering algorithm in artificial intelligence technology was used to extract the motion path in the performer’s trajectory. The target path of stage performance arrangement was obtained by mapping the performer’s motion path through zoom processing. Based on the goal path, by arranging the control position of the performer’s root joint and correcting the direction of the performer, the movement track of the performer in the stage performance process was reconstructed, and the stage performance layout design was realized by combining with the position arrangement of the stage performance motion segment. The experimental results show that the method can accurately plan the performers’ path and improve the user’s satisfaction with the stage performance.
A Paper on the Concept of Cloud Computing

Cloud computing is a basic practice of using a network through remote server hosted on the internet to store, access, manages data on demand services. It is pay as per use. Cloud computing provides access to shared resources instead of personal or local server. It saves time and cost for the organisations. This technology is completely dependent on internet where client data is stored on the server and maintain in the data centre by the cloud providers such as Google (Drive), Microsoft (Azure), Amazon (AWS) etc. It comes in emerging domain and it is acclaimed throughout the world. There are some security issues also whenever the data placed on the server or internet. This research paper mainly focuses on the cloud computing concepts, cloud infrastructure and security issues. This research paper also analyses the challenges present in cloud computing. It provides us means by which we can access the applications as utilities over the internet. Through cloud computing Business application can be customize online such as create and configure.
SERVICE ON THE GO (SERVEGO): Online Service Booking Application

Service On The Go is an online service booking application developed to provide users with access to multiple services in electrical repair, electrical wiring, plumbing repair services, and online home maintenance. Besides, this application also provides a platform for users who are experts in their services areas to promote and share their skills through the Internet. The purpose of ServeGo is to allow the user to find the contact of the person who provides the repair services. It also can solve the problem of the handyman who is facing the difficulty to promote and share their services. Hence, the application can save the time of users who need the services immediately. The app is developed by using Android Studio and Firebase. Android Studio is an official integrated development environment (IDE) for Android application development while Firebase is a service that enables helping the user to manage the centralized database via the cloud. The modules which are notification module, request module, booking status module, payment module, rating module, GPS module are added to implement the application.
Enhancing the Distribution of Idle Cost for Scheduling Tasks without Setup Cost in Cloud Computing

Issues of task scheduling in the centre of cloud computing are becoming more important, and the cost is one of the most important parameters used for scheduling tasks. This study aims to investigate the problem of online task scheduling of the identified job of MapReduce on cloud computing infrastructure. It was proposed that the virtualized cloud computing setup comprised machines that host multiple identical virtual machines (VMs) that need to be activated earlier and run continuously, and booting a VM requires a constant setup time. A VM that remains running even though it is no longer used is considered an idle VM. Furthermore, this study aims to distribute the idle cost of the VMs rather than the cost of setting up them among tasks in a fair manner. This study also is an extension of previous studies which solved the problems that occurred when distributing the idle cost and setting up the cost of VMs among tasks. It classifies the tasks into three groups (long, mid, and short) and distributes the idle cost among the groups then among the tasks of the groups. The main contribution of this paper is the developing of a clairvoyant algorithm that addressed important factors such as the delay and the cost that occurred by waiting to setup VM (active VM). Also, when the VMs are run continually and some VMs become in idle state, the idle cost will be distributed among the current tasks in a fair manner. The results of this study, in comparison with previous studies, showed that the idle cost and the setup cost that was distributed among tasks were better than the idle cost and the setup cost distributed in those studies.
Supervised Classification Using Graph-based Space Partitioning for Multiclass Problems

We introduce and investigate in multiclass setting an efficient classifier which partitions the training data by means of multidimensional parallelepipeds called boxes. We show that multiclass classification problem at hand can be solved by combining the heuristic minimum clique cover approach and the k-nearest neighbor rule. Our algorithm is motivated by an algorithm for partitioning a graph into a minimal number of cliques. The main advantage of a new classifier called Box classifier is that it optimally utilizes the geometrical structure of the training set by reducing the 1-class classification problem to a single nearest neighbor problem. We discuss computational complexity of the proposed Box classifier. The extensive experiments performed on the simulated and real data from UCI Machine Learning Repository for binary and multiclass problems show that in almost all cases the Box classifier performs significantly better than k-NN, SVM and decision trees.
Weight Estimation from an RGB-D camera in top-view configuration

The development of so-called soft-biometrics aims at providing information related to the physical and behavioural characteristics of a person. This paper focuses on body weight estimation based on the observation from a top-view RGB-D camera. In fact, the capability to estimate the weight of a person can be of help in many different applications, from health-related scenarios, to business intelligence and retail analytics. To deal with this issue, a TVWE (Top-View Weight Estimation) framework is proposed with the aim of predicting the weight. The approach relies on the adoption of Deep Neural Networks (DNNs) that have been trained on depth data. Each network has also been modified in their top section to replace classification with prediction inference. The performance of five state-of-art DNNs have been compared, namely VGG16, ResNet, Inception, DenseNet and Efficient-Net. In addition, a convolutional auto-encoder has also been included for completeness. Considering the limited literature in this domain, the TVWE framework has been evaluated on a new publicly available dataset: “VRAI Weight estimation Dataset”, which also collects, for each subject, labels related to weight, gender, and height. The experimental results have demonstrated that the proposed methods are suitable for this task, bringing different and significant insights for the application of the solution in different domains.
Secure Suite: An Open-Source Service for Internet Security

Internet security is constantly at risk as a result of the fast developing and highly sophisticated exploitation methods. These attacks use numerous media to take advantage of the most vulnerable of Internet users. Phishing, spam calling, unsecure content and other means of intrusion threaten Internet users every day. In order to maintain the security and privacy of sensitive user data, the user must pay for services that include the storage and generation of secure passwords, monitoring internet traffic to discourage navigation to malicious websites, among other services. Some people do not have the money to purchase privacy protection services and others find convoluted euphemisms baked into privacy policies quite confusing. In response to this problem, we developed an Internet security software package, Secure Suite, which we provide as open source and hence free of charge. Users can easily deploy and manage Secure Suite. It is composed of a password manager, a malicious URL detection service, dubbed MalURLNet, a URL extender, data visualization tools, a browser extension to interact with the web app, and utility tools to maintain data integrity. MalURLNet is one of the main components of Secure Suite. It utilizes deep learning and other open-source software to mitigate security threats by identifying malicious URLs. We exhaustively tested our proposed MalURLNet service. Our studies show that MalURLNet outperforms four other well-known URL classifiers in terms of accuracy, loss, precision, recall, and F1-Score.
Interest Rate Spread as the 'Power of Growth' on Financial Profitability of Banks in Africa

The high-interest rate has postured solemn distresses to the administration, managers, firms, and the masses. Commercial banks in Africa, principally, are exasperated to use the policy rate to bring down loaning charges. Interest rate charges though have sustained to persist gluey downwards. This study considered the impact of interest rate as the power of growth on financial profitability and examine the causal link amid the measurement variables (bank credit, savings, non-performing loans, and interest rate) between 2000 and 2016. The countries used in this study were investigated as a whole panel and individually per country. First, considering the results from homogeneity assessment and Pesaran CD's checks, we detect the presence of heterogeneity and cross-sectional correlations for the explored data. Second, the CADF and CIPS panel unit root tests report that the variables are non-stationary at their stages but become stationary at their first transformations. Third, the Westerlund-Edgerton panel bootstrap cointegration test shows that the variables are cointegrated and hence possess a structural long-run relationship. Forth, results from the PMG estimator through the panel ARDL model show that; (1) A two-way connectedness is verge by bank credit and FP in the long-period and short-run; (2) A positive and significant one-way cause running from NPLs to BC, a one-way cause amid interest rate and bank credit and lastly one-way causality only in the long-period for NPLs and SAV are evidenced; (3) The PMG estimator through the panel ARDL framework is evidenced to be very significantly effective to the application of Granger causatives test. Though different parameter estimates are evidenced, the results are generally consistent with that of the PMG in terms of connections.
A Novel Approach to Measurement of the Transverse Velocity of the Large-Scale Objects

This paper presents a novel approach for measuring the transverse velocity of large-scale objects based on stereo vision. The suggested approach uses a high-speed stereo camera located perpendicular to the traffic lane, and consists in matching frames from the left and right cameras. Compared to methods based on monocular vision, this approach solves the problem of dependence of object speed on distance. The proposed algorithm is part of a system for non-contact measurement of large-sized objects and has a calculated measurement error that does not exceed 1.5% of the measured speed up to 30 km/h while having low computational complexity.
Editorial on Artificial Intelligence

Artificial Intelligence (AI) alludes to the reproduction of humanintelligence in machines that are modified to think like peopleand copy their activities. The term may likewise be applied to anymachine that shows characteristics related with a human brain,for example, learning and critical thinking. A subset of ArtificialIntelligence is machine learning, which alludes to the idea thatthe computers can naturally gain new information without beinghelped by people.