On-line Verification Research Articles

DETECTION OF HANDWRITTEN SIGNATURE FORGERY USING CNN

Hand verification and phony discovery is the process of vindicating autographs automatically and incontinently to determine whether the hand is real or not. There are two main kinds of hand verification static and dynamic. stationary, or offline verification is the process of vindicating a document hand after it has been made, while dynamic or online verification takes place as a person creates his/ her hand on a digital tablet or an analogous device. The hand in question is also compared to former samples of that person's hand, which set up the database. In the case of a handwritten hand on a document, the computer needs the samples to be scrutinized for disquisition, whereas a digital hand which is formerly stored in a data format can be used for hand verification. The handwritten hand is one of the most generally accepted particular attributes for verification of identity, whether it may for banking or business. The sub-sphere of machine literacy that's deep literacy allows us to train a model with the help of deep literacy algorithms. This is enforced in a complicated neural network model trained to classify and descry the forged hand from a collection of image samples which consists of two different sets of images, say real and forged image sets. We constructed a complicated neural network model from scrape to prize features from a given dataset. The image is given as input, and it tells whether a hand is forged or not. This will help descry the fraud. KEYWORDS: CNN, Forgery, Signature

Research Progress and Prospects of Intelligent Digital Equipment

In response to the development trend of unmanned and intelligent weapons and equipment for the future, intelligent digital equipment, as a “digital brain”, can be deeply integrated into various links such as equipment development and upgrading, experimental verification, and operational support, to lead to leapfrog development of the operational support for future intelligent equipment. First, intelligent digital equipment allows the physical equipment to make adaptive adjustments and boost operational efficiency during combat. Second, it helps the equipment build a capability of perceiving its status and thus improves the operational readiness of equipment in normal times. Third, it allows equipment fault isolation for diagnosis and thus improves the completion rate of missions in combat. Fourth, it provides intelligent guidance for operation training and enhances the efficiency of use and training. Fifth, it achieves online upgrading and verification of functionalities, and changes and upgrades the maintenance mode. This paper introduces the concept of digital equipment and the research outcomes concerning digital twin around the world from 2010 to 2020, and reviews the research progress in the United States and China. It presents the problems faced by the research, and puts forward solutions and research prospects.

Runtime Assurance for Safety-Critical Systems: An Introduction to Safety Filtering Approaches for Complex Control Systems

Run Time Assurance (RTA) Systems are online verification mechanisms that filter an unverified primary controller output to ensure system safety. The primary control may come from a human operator, an advanced control approach, or an autonomous control approach that cannot be verified to the same level as simpler control systems designs. The critical feature of RTA systems is their ability to alter unsafe control inputs explicitly to assure safety. In many cases, RTA systems can functionally be described as containing a monitor that watches the state of the system and output of a primary controller, and a backup controller that replaces or modifies control input when necessary to assure safety. An important quality of an RTA system is that the assurance mechanism is constructed in a way that is entirely agnostic to the underlying structure of the primary controller. By effectively decoupling the enforcement of safety constraints from performance-related objectives, RTA offers a number of useful advantages over traditional (offline) verification. This article provides a tutorial on developing RTA systems.

Signature Verification Using Python

Abstract: Each individual has a distinctive signature that is primarily used for personal identification and the confirmation of significant papers orlegal transactions. Static (offline) and dynamic signature verification come in two flavours (online). After a signature has been made, it can be verified using a methodknown as static verification. For a lot of documents, off line signature verification is ineffective and slow. Online biometric personal verification, such as fingerprints, eye scans, etc., has increased in recent years as a way to get over the limitations of offline signature verification. Convolution neural network (CNN)-based offline signature verification is proposed inthis study. We can extract more accurate representations of the image content using a neural network model called CNN. In order to improve categorization, CNN starts with the raw pixel datafrom the image, trains the model, and then automatically extracts the features. CNN's key advantage over its forerunners is that it automatically identifies significant features without human supervision and that it predicts images with the highest degree of accuracy of any algorithm.

Voter’s Poll Precinct Search

One of the biggest problems during election day is the congestion of voters in the areas where names, precinct numbers, sequence numbers, and voting status were verified. This is caused by the lack of a fast and effective system for doing the task. Few elections passed, and the said processes are done in a manual process. Recently, the Commission on Election launched an online precinct search and verification system but, the system failed to perform according to what is needed because it collects many user data the query proceeds and is very dependent to an internet connection which made it less usable in areas with poor internet connection. The mentioned gaps made the researchers think about how to improve the current system and make it more usable particularly in areas with poor internet connection. Using the Agile: Scrum methodology of software engineering, the researchers interviewed the election officer assigned in the town of Candijay. According to the election officer, having a system that would be able to search names, precinct numbers, sequence numbers, and verify voting status that runs without depending on an internet connection is the best solution to fasten the process and lessen voter congestion. The Voter’s Poll Precinct Search system has been developed based on the statements of the election officer and the current system. It is a localized system that runs on both web and mobile applications that searches voters’ information and status using a smartphone that aims to fasten the process of finding voter poll precincts, sequence numbers, and voter verification. The researchers made the clienteles answer the software usability questionnaire and received good feedback. Therefore, based on the data, the researchers concluded that the system successfully performed its designed task. Keywords: Mobile Application, Web Application

Blockchain-Based E-Certificate Verification and Validation Automation Architecture to Avoid Counterfeiting of Digital Assets in Order to Accelerate Digital Transformation

The security and confidentiality of data are very important for institutions. Meanwhile, data fabrication or falsification of official documents is still common. Validation of the authenticity of documents such as certificates becomes a challenge for various parties, especially those who have to make decisions based on the validity of the document. Scanning-based signatures on printed and digital documents are still relatively easy to counterfeit and yet still difficult to distinguish from the original. The traditional approach is no longer reliable. Solutions to these problems require the existence of data security techniques, seamless online verification of the authenticity of printed documents, and e-certificates quickly. The objective of the study is to model the e-certificate verification process via blockchain and proof-of-stake consensus methods and use MD5 encryption. The data or identity listed on the e-certificate is secured with an embedded digital signature in the form of a QR code and can be checked for the truth online. A combination of technologies capable of suppressing or removing counterfeiting of digital assets will accelerate digital transformation across spectrums of modern life. The resulting architectural model can be used as a starting point for implementing a blockchain-based e-certificate verification and validation automation system.

Offline Signature Verification Using Image Processing

A person’s signature is merely a handwritten sign that closely resembles his/her name, frequently stylized and distinctive, and that expresses the person’s identity, intent, and consent. Two types of verifications are present. They are online signature verification and offline signature verification. Generally, Offline Signature verification is less efficient and slower process compare to online verification when come to the situation having larger number of documents and files to verify with in less time. Over the years, many researchers have developed so many methods for signature verifications to help the people or organizations to find whether the signature of a particular person is forged or genuine. To overcome this problems; In this paper we introduced a simple method to improve the verification of the signature in Image Processing using Convolution Neural Networks(CNN). Signature Verification it is used to authenticate various kinds of documents, including cheques, draughts, certificates, approvals, letters, and other legal ones, such verification is crucial for preventing document forgery and falsification. Previously, to verify a signature, it was manually checked against copies of real signatures. This straightforward approach might not be sufficient given that forgery and signature fraud techniques are becoming more sophisticated as a result of improving technology.

Machine Learning-Based Stator Current Data-Driven PMSM Stator Winding Fault Diagnosis

Permanent magnet synchronous motors (PMSMs) have become one of the most important components of modern drive systems. Therefore, fault diagnosis and condition monitoring of these machines have been the subject of many studies in recent years. This article presents an intelligent stator current-data driven PMSM stator winding fault detection and classification method. Short-time Fourier transform is applied in the process of fault feature extraction from the stator phase current symmetrical components signal. Automation of the fault detection and classification process is carried out with the use of three selected machine learning algorithms: support vector machine, naïve Bayes classifier and multilayer perceptron. The concept and online verification of the original intelligent fault diagnosis system with the potential of a real industrial deployment are demonstrated. Experimental results are presented to evaluate the effectiveness of the proposed methodology.

Ultra-high dose rate dosimetry for pre-clinical experiments with mm-small proton fields

PurposeTo characterize an experimental setup for ultra-high dose rate (UHDR) proton irradiations, and to address the challenges of dosimetry in millimetre-small pencil proton beams. MethodsAt the PSI Gantry 1, high-energy transmission pencil beams can be delivered to biological samples and detectors up to a maximum local dose rate of ∼9000 Gy/s. In the presented setup, a Faraday cup is used to measure the delivered number of protons up to ultra-high dose rates. The response of transmission ion-chambers, as well as of different field detectors, was characterized over a wide range of dose rates using the Faraday cup as reference. ResultsThe reproducibility of the delivered proton charge was better than 1 % in the proposed experimental setup. EBT3 films, Al2O3:C optically stimulated luminescence detectors and a PTW microDiamond were used to validate the predicted dose. Transmission ionization chambers showed significant volume ion-recombination (>30 % in the tested conditions) which can be parametrized as a function of the maximum proton current density. Over the considered range, EBT3 films, inorganic scintillator-based screens and the PTW microDiamond were demonstrated to be dose rate independent within ±3 %, ±1.8 % and ±1 %, respectively. ConclusionsFaraday cups are versatile dosimetry instruments that can be used for dose estimation, field detector characterization and on-line dose verification for pre-clinical experiments in UHDR proton pencil beams. Among the tested detectors, the commercial PTW microDiamond was found to be a suitable option to measure real time the dosimetric properties of narrow pencil proton beams for dose rates up to 2.2 kGy/s.

HOLDING SCHOOL OLYMPIADS ON COMPUTER SCIENCE IN PANDEMIC CONDITIONS

The COVID-19 pandemic has changed attitudes to the educational process around the world, including Ukraine. Considering the importance of the Students Olympiad in computer science (CS) for the formation of future IT professionals in Ukraine, it was necessary to quickly develop appropriate approaches and safe formats for all stages of this Olympiad. Based on a survey of organizers, a review of Olympiads in CS in countries such as Azerbaijan, Bulgaria, Armenia, Georgia, Latvia, Lithuania, Moldova, Poland, Croatia, and the Czech Republic was observed, and the format of the World Olympiad in Singapore was analyzed. Based on the analysis conducted and taking into account the importance of strict observance of all competition rules, including integrity and the importance of social contacts of all participants in the Olympic movement, it was decided that only the online format is insufficient and there was developed a safe format for the third and fourth stages of the competition, that includes a combination of in-person, online and mixed formats. Detailed requirements for each of these formats are formulated. Due to a significant increase in the load on the e-olymp server online verification system, the relevant software has been updated. The article provides detailed information on the holding of all four stages of the All-Ukrainian Students Olympiad in CS in a pandemic condition during 2019/2020 and 2020/2021 academic year using established formats and an improved verification system and describes a typical algorithm of the participant's actions. Therefore, new competition rules are detailed and innovative, taking into account unexpected circumstances in the whole world. They were tested and they proved their effectiveness, so they were also used for the finals of the Ukrainian Junior Olympiad in Informatics and the Ukrainian Girls’ Olympiad in Informatics. Since there is uncertainty about the pandemic in Ukraine, the article proposes to apply the proposed rules to hold all future stages of the Olympiad in Informatics during a pandemic at the official level.

ScQ cloud quantum computation for generating Greenberger-Horne-Zeilinger states of up to 10 qubits

In this study, we introduce an online public quantum computation platform, named as ScQ, based on a 1D array of a 10-qubit superconducting processor. Single-qubit rotation gates can be performed on each qubit. Controlled-NOT gates between nearest-neighbor sites on the 1D array of 10 qubits are available. We show the online preparation and verification of Greenberger-Horne-Zeilinger states of up to 10 qubits through this platform for all possible blocks of qubits in the chain. The graphical user interface and quantum assembly language methods are presented to achieve the above tasks, which rely on a parameter scanning feature implemented on ScQ. The performance of this quantum computation platform, such as fidelities of logic gates and details of the superconducting device, are presented.

Investigating the Impact of Test Case Density and Execution Variety on Fault Localization for Novice Programs

Programming Online Verification Exam (OE) system has been widely used in algorithm education and practice since it can automatically analyze program results (e.g., correct or incorrect) after executing the submitted programs with corresponding test cases. OE systems can provide both execution results and error information so that novice programmers can get feedback quickly. If the submitted program cannot pass all the test cases, the novice programmers will get wrong-answer feedback, and they have to find and fix the errors in the program. Automated program fault localization techniques, which can locate the errors in programs under test automatically, thus help novice programmers fix the errors quickly. However, the performance of current automated fault localization techniques is limited due to the high-density test cases in novice programs of OE system. In this paper, we analyze the impact of test case density (TCD) and execution variety on fault localization performance and propose a method to reduce TCD to improve fault localization precision for novice programs. To evaluate the performance of our method, we conduct a number of empirical studies on 1199 real fault diagnosis algorithm related novice programs, and the experimental results show that using improved test cases through our method for fault localization in OE system can enhance the precision of fault localization for novice programs. Specifically, after decreasing the test cases’ density, the improvement of fault localization accuracy ranges from 0.6% to 17.34% in terms of the Expense metric, and from the Accuracy@N metrics, the number of faulty statements that can be found increases in most cases.

True-Data Testbed for 5G/B5G Intelligent Network

Future mobile communications will shift from supporting the internet of everything (IoE) to facilitating interpersonal communications beyond fifth-generation (B5G) and sixth-generation (6G) mobile communications. Intelligent communications with full integration of big data and artificial intelligence (AI) will play a key role in improving network efficiency and providing high-quality service. The AI-powered mobile communications require vast volumes of data to be collected from a real network environment for systematic testing and verification because it is a rapidly growing paradigm. As a result, we create the first true-data testbed for 5G/B5G intelligent networks (TTIN), which includes on-site experimental 5G/B5G networks, data collection and storage, and an AI engine and network optimization. True network data collecting, storage, standardisation, and analysis are possible in the TTIN, allowing for data-driven networks and system-level online verification of important B5G/6G technologies.

Computer-Aided and AILDE Approaches to Design Novel 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors.

4-Hydroxyphenylpyruvate dioxygenase (HPPD) is a pivotal enzyme in tocopherol and plastoquinone synthesis and a potential target for novel herbicides. Thirty-five pyridine derivatives were selected to establish a Topomer comparative molecular field analysis (Topomer CoMFA) model to obtain correlation information between HPPD inhibitory activity and the molecular structure. A credible and predictive Topomer CoMFA model was established by “split in two R-groups” cutting methods and fragment combinations (q2 = 0.703, r2 = 0.957, ONC = 6). The established model was used to screen out more active compounds and was optimized through the auto in silico ligand directing evolution (AILDE) platform to obtain potential HPPD inhibitors. Twenty-two new compounds with theoretically good HPPD inhibition were obtained by combining the high-activity contribution substituents in the existing molecules with the R-group search via Topomer search. Molecular docking results revealed that most of the 22 fresh compounds could form stable π-π interactions. The absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction and drug-like properties made 9 compounds potential HPPD inhibitors. Molecular dynamics simulation indicated that Compounds Y12 and Y14 showed good root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values and stability. According to the AILDE online verification, 5 new compounds with potential HPPD inhibition were discovered as HPPD inhibitor candidates. This study provides beneficial insights for subsequent HPPD inhibitor design.

A novel approach for verifying selective user identity attributes online using open banking APIs

In this work, we propose a novel workflow to tackle the problem of verifying individuals’ identities online assuming banks as a central source of truth. The existing process for this involves auth mechanisms from privately held companies, where the data do not have any physical backing by an authorized entity, reducing its credibility. Alongside, the online verification methods used are unsophisticated, like passwords and OTPs, and anyone can easily impersonate with access to one’s devices and credentials. Considering alternatives like national identity cards to prove data, one needs to verify original documents again and again physically, decreasing customer’s inspiration for the activity. One more issue to tackle is excessive data getting shared during authentication can serve maliciously against the users. Companies utilize this data for digital profiling of users and targeting advertisements. Hence, only data attributes of utmost necessity should get shared. We have tried to create a web app named Canfirm to demonstrate the possibilities, workflow and use of open banking APIs.

An Online Verification System of Employee Classification using Machine Learning Approach

Abstract: Over years there have been an extraordinary need of simple and abstained method for check result/declaration to diminish the level or testament falsification and to facilitate the pressure and furthermore save the hour of authentication confirmation which is finished physically today, a business or anyone concern should come or send agent to secondary school to confirm a particular endorsement, some business never did and this has come about on tolerating produce endorsement. Observing appropriate possibility for an open job may be an alarming assignment, particularly when there are many applicants. It can block group progress for getting the legitimate individual on the appropriate time. A robotized method of "Resume Classification and Matching" could truly facilitate the dreary course of fair screening and shortlisting, it would unquestionably expediate the competitor determination and dynamic cycle. This framework could work with an outsized number of resumes for first characterizing the appropriate classifications utilizing different classifier, whenever grouping has been done then according to the work portrayal, top up-and-comers could be positioned utilizing content-based suggestion, utilizing cosine similitude and by suing KNN to recognize the CVs that are closest to the given expected set of responsibilities.

Comprehensive Analyses of Ferroptosis-Related Alterations and Their Prognostic Significance in Glioblastoma.

Background: This study was designed to explore the implications of ferroptosis-related alterations in glioblastoma patients. Method: After obtaining the data sets CGGA325, CGGA623, TCGA-GBM, and GSE83300 online, extensive analysis and mutual verification were performed using R language-based analytic technology, followed by further immunohistochemistry staining verification utilizing clinical pathological tissues. Results: The analysis revealed a substantial difference in the expression of ferroptosis-related genes between malignant and paracancerous samples, which was compatible with immunohistochemistry staining results from clinicopathological samples. Three distinct clustering studies were run sequentially on these data. All of the findings were consistent and had a high prediction value for glioblastoma. Then, the risk score predicting model containing 23 genes (CP, EMP1, AKR1C1, FMOD, MYBPH, IFI30, SRPX2, PDLIM1, MMP19, SPOCD1, FCGBP, NAMPT, SLC11A1, S100A10, TNC, CSMD3, ATP1A2, CUX2, GALNT9, TNFAIP6, C15orf48, WSCD2, and CBLN1) on the basis of “Ferroptosis.gene.cluster” was constructed. In the subsequent correlation analysis of clinical characteristics, tumor mutation burden, HRD, neoantigen burden and chromosomal instability, mRNAsi, TIDE, and GDSC, all the results indicated that the risk score model might have a better predictive efficiency. Conclusion: In glioblastoma, there were a large number of abnormal ferroptosis-related alterations, which were significant for the prognosis of patients. The risk score-predicting model integrating 23 genes would have a higher predictive value.

Global virtual teams management system: project manager guide

Global virtual teams (GVTs) are a recent organizational adaptation created to meet the needs of globalizatized marketplace. GVTs are essentially teams that are distributed across national boundaries and concerned through advanced information and communication technology (ICT) such as email, instant messaging, and video conferencing. The research on GVTs is important in the information system (IS) field because GVTs are dependent on information communication technology and the use of other technologies; GVTs also consists of people from different cultures. This paper tried to answer two research questions. The first one is: what are the GVTs problems facing the project manager (PM). A literature review was conducted to answer the first research question. The second one is: how to develop system as a guide for PM. The system was developed by Visual Studio 2019. Online model verification was conducted within 6 experts from IT industry. After developing the system, it was validated by eleven developers (non-functional test/black-box testing) and 3 developers/programmers (functional test/white-box testing) from the same industry. The result of model verification confirmed that the model can help the PM. Also, the non-functional test/black-box testing and functional test/white-box testing was confirmed.

Social Media Policies in U.S. Television Newsrooms: Changes over Time

This study analyzes survey data, gathered in 2014 and 2020, regarding local television newsrooms’ social media policies (SMPs). The purpose of the study is to explore changes to these policies. As part of this inquiry, the researchers investigate if and in which ways newsroom SMPs are evolving in four areas: journalists’ professional and personal social media activities; social media sources and content; audience complaints; and ownership of on-air talents’ accounts. The researchers found a significant increase of guidelines regarding what is and is not appropriate on the professional and personal social media of journalists, with little distinction made between these types of accounts. Although newsrooms have implemented policies to articulate what is appropriate conduct and a majority have revised policies, those guidelines don't always address the contemporary issues journalists face, specifically online threats and verification of user-generated content. The researchers found an increasing percentage of news outlets retain ownership of on-air talents’ professional accounts.

ONLINE THERMODYNAMICS EDUCATION UNDER PANDEMIC TIMES, IN CONSTANTA MARITIME UNIVERSITY

As well known, the day of 11 March 2020 will remain in the history as the day in which The World Health Organization (WHO) has declared COVID-19 a pandemic. Under these circumstances, the international higher education was forced to remove the campus activities in online. Constanta Maritime University is one of the universities across the world which moved the educational process from face- to- face to online learning. This was a challenging task for the academic, managing and technical administration and for the students, as well. This paper focuses on the disciplined entitled Thermodynamics 1, encountered in the curricula of the Electromechanics Faculty, Constanta Maritime University. The paper describes the steps done during the online education along the semester, both by students and lecturers. At the end of the semester, students and lecturers had to face another challenge: the online examination. Since in the new conditions, the students had to gain the same knowledge as during the classic educational process, we are providing the results obtained by our students. Their exam was scheduled on June 26, 2020. The number of students attending the online examination was 108. The online report for the examination, available on the online platform of the university, indicates that online 17 students were not able to pass the examination (grade 5). The same chart data shows that 19 students have obtained grades in the range (8,00- 8,50), while 2 students obtained grades in the range (9, 50- 10,00). These results are considered to be encouraging for lecturers and students. This type of examination it is seen as a potential long term examination manner, given its benefits: online generation of the test, online verification and not last, transparency.