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About 6,099 papers for “Intelligent verification”
Guiming Luo, Graziano Chesi, Xiaoyu Song et al. · Journal of Applied Mathematics · 2013
System modeling tends to have many complex features, and uncertainties often lead to numerous complications and influence many important aspects related to its applications. Intelligent modeling merges mathematical and computer based approaches, and it utilizes pioneering new scientific methods and cutting-edge technologies.
Cited by 0Open access
Guiming Luo, Xiaoyu Song, Yang Xiao-jing et al. · Journal of Applied Mathematics · 2014
Cited by 1Open access
Kamlesh Kumari, Sanjeev Rana · International Journal of Engineering & Technology · 2018
Signature verification is important in banking, legal, financial transactions for security purpose. Offline signature verification is a complex task because active information i.e. temporal information is missing in static image. There is no standard feature extraction method for offline signature identification as in case of other behavior modalities e.g. in automatic speech recognition like LPCC (Linear Predictive Ceptral Coefficients).Our research presents an intelligent algorithm for feature extraction based on image difference of genuine signature image and questioned signature image. Six features i.e. average object area, entropy, standard deviation, mean, Euler no., and area are analyzed. Best results are reported using combination of Average Object Area, Mean, Euler No. and Area. CEDAR (Center of Excellence for Document Analysis) database is used for offline signature verification. The database consists of static signature samples taken from 55 users. The Proposed algorithm is quite efficient as it is less computationally. Experiments are performed with both models i.e. Writer-Independent (WI) system and Writer-Dependent.
Cited by 2Open access
Sanika Ghute, Omair Bhombal, Yashwant Jadhao et al. · 2026
Abstract: Elections that are free, fair, and transparent are a fundamental component of any democracy, which makes it necessary to ensure that the voting process is secure, transparent, and efficient. There are a number of challenges associated with traditional voting systems, including waiting time, the possibility of human error, manipulation, and delayed results. To overcome these problems, the proposed project introduces a smart voting machine, which ensures a safe, transparent, and efficient voting process using an electronic voting system. The system has been designed using an embedded system, a keypad, a camera module, and a display unit. The system ensures that every voter is verified before voting, thus preventing unauthorized access to the voting system. After the user is verified, he/she can proceed to vote by using the keypad, which ensures that the vote is recorded instantly. The system has a display unit that shows the user immediate feedback, while an alert system detects invalid votes. This approach enhances the overall efficiency, accuracy, and security of the voting process while reducing manual effort and operational costs. Due to its compact structure, low power consumption, and scalable design, the system can be effectively implemented in educational institutions, organizations, and small-scale local elections, ensuring a transparent and dependable voting mechanism.
Cited by 0
John W. Baugh, Gopalakrishna Reddy Kakivaya · Journal of Computing in Civil Engineering · 2000
Intelligent transportation systems (ITS) represent a major initiative to improve roadway and travel conditions, not by building roads, but by drawing on new technologies in computing, sensing, and communications. However, these technologies are extremely complex and, while some demonstration projects have tested stand-alone systems, the broader architectural and standardization issues are still under development. The use of complex technologies in a safety-critical system such as ITS and at the scale envisioned requires a very careful study of the interaction between its various subsystems. This paper describes an approach for modeling the temporal aspects of ITS systems as well as their logical coordination using finite state verification tools. The approach is demonstrated by verifying safety properties of an automated traffic signal at a road intersection.
Cited by 1
Monika Darebnikova, Marek Penhaker, M Cerny et al. · 2012
The result of this work was to compare and verification of intelligent mechatronics system for biochemists blood bleedings. It was therefore a comparison of the shaker and done a few tests that have been tasked to investigate the influence of the surrounding environment. Verification of long-term technical correctness biochemists blending of blood preceded the shooting, processing and subsequent analysis of the signal containing information about the vibration shakers grids. It was created and realized by measuring the string to capture and long-term online monitoring devices of blood derivatives. Furthermore, the library implemented in MATLAB, enabling more detailed mathematical analysis of measured data. The work is devoted to relatively well-defined issues, with emphasis on the analysis of measured data. It is not about finding a specific physical device error, but only analyzes the functions that the treatment did not show substantial deviations activities.
Cited by 0
Abdulsahib, Muna Ghazi · Iraqi Journal of Computer Communication Control and System Engineering · 2024
Kinship verification is the process of using observable characteristics, including facial features or other biometric data, to ascertain whether two people are familial related. Current approaches to kinship verification encounter multiple challenges, despite their significance in fields such as biometric security, family reunification, and forensic investigations. The most accurate way to confirm kinship is by DNA analysis, which is expensive, time-consuming, and invasive; in contrast, the traditional methods using manual comparison and facial recognition are more prone to human mistake. Visual verification of kinship among family members can be difficult to reliably rely on due to genetic variability, aging, and environmental influences. Automated methods that can reliably and efficiently confirm kinship using non-invasive methods are required, especially in situations where immediate identification is essential, like in the investigation of missing persons cases and disaster response. This study explores the use of different verification kinship techniques, ranging from various machine learning techniques reaching to up-to-date deep learning techniques. Finally, this study will discuss the datasets, preprocessing, methodology, advantages, disadvantages, and performance measures of selected state-of-the-art studies of kinship verification, and present the best technique used in kinship verification with the most related dataset. Index Terms— Kinship verification, Deep learning, Machine learning.
Cited by 0Open access
B. Hoang, A. Atai · 2002
The authors describe a methodology for service verification testing of a private virtual network service. The objective of service verification testing is to ensure that all network element capabilities function properly from an end-to-end call processing perspective and that all the features for a given IN (intelligent network) service work as specified in technical requirements. The methodology described is to use a test network which, as much as possible, emulates a given IN service architecture and customer environment, and to thoroughly exercise in a systematic fashion all the features, using an automated test system. The test system is described, and some of the lessons learned from the actual field tests are also presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cited by 0
Min Xu, Lisong Wang · EAI/Springer Innovations in Communication and Computing · 2020
Cited by 0
Kazumi Nakamatsu, Kenji Kawasumi, Atsuyuki Suzuki · 2005
We have developed an annotated logic program called an Extended Vector Annotated Logic Program with Strong Negation(abbr. EVALPSN), which can deal with defeasible deontic reasoning and contradiction. We have already applied EVALPSN to safety verification and control such as railway interlocking safety verification. In this paper, we show pipeline valve safety verification to avoid liquid mixture accidents with a simple example for brewery pipeline control.
Cited by 0
R.M. Aguilar, V. Muñoz, M. Noda et al. · Expert Systems with Applications · 2007
Cited by 18
Ibukun Phillips, Robert Kenley · 2022
Intelligent Transportation Systems (ITS) have been touted and proven to be an advanced-technology improvement in transport systems and commuters’ operational performance, efficiency, and safety. The nature of ITS as an integrated metasystem of information and data, operational management, safety, ICT infrastructure, and logistic systems permits their observation as a System of Systems (SoS). In addition, the prevalence of real-time information processing and the subsequent data explosion requires the utilization of Artificial Intelligence (AI) solutions. ITS characteristics depict them as AIbased SoS, which presents challenges to the verification and certification of these systems. This paper will frame ITS as Systems of Systems, considering their SoS classification from literature while outlining the role of AI applications in fostering effective and adequate mobility for these systems. With the understanding of the architecture and nature of ITS, it becomes easier to understand how the emergence and the complexity of modeling and evaluating these systems, among other challenges, contribute to the verification difficulty that will be encountered – key to certifying these systems. We propose some solutions from literature meant to serve as components of a holistic suite of solutions towards resolving the verification challenges posed by AI-based Systems of Systems like ITS.
Cited by 5
<p>Zhang Jiang, Lv Kunshan, Tan Yao, Yu Jingtong</p> · Academic Journal of Engineering and Technology Science · 2024
In response to the severe situation of frequent accidents in crowded places globally in recent years, this study aims to develop an advanced intelligent crowd evacuation system. This paper employs an improved Multi-Column Convolutional Neural Network (MCNN) algorithm for deep learning to segment crowds from images for subsequent feature extraction. Through data sampling, training, and analysis, the images are mapped to crowd density maps, enabling the system to prevent excessive crowd density in advance. Additionally, in scenarios of overcrowding, where there is a lack of real-time planning for escape routes in densely populated areas and a low success rate of evacuation, a dynamic and real-time escape route indication system is designed. This system utilizes monitoring data and the Dijkstra dynamic optimization algorithm to calculate the shortest path, directing crowd evacuation based on the principles of optimality and speed. Simulation data demonstrates that this can improve the effectiveness of crowd evacuation.
Cited by 0Open access
Xingqian Li, Haoyu Zhao, Hongwei Zhao et al. · 2017
The current intelligent robots lack a certain degree of security, can not accurately identify the user. Embedded devices exist in the existing face recognition is not accurate enough, the depth of learning resources and other issues is not enough. We presented a new type of ResNet face recognition model for transplanting in embedded devices. We used the machine to learn to face the face detection, and extracted 68 face key points, the use of depth residual network algorithm for further identification, and ultimately compared the European distance to determine and identify the user. Experiments show that the scheme has the advantages of good precision and good accuracy, and can be used in the intelligent robot system.
Cited by 2
2021
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Robert E. Uhrig, Darryl J. Wrest, J. Wesley Hines · 2007
. The intelligent approach to instrument surveillance and calibration verification described here was developed for use in nuclear power plants utilizing digitized data available in the Plant Computer. Data from Florida Power Corporations Crystal River #3 Nuclear Power Plant was recorded and applied to a five-layer autoassociative neural network (AANN) which is trained using a special robust training method. Plant variables that have some degree of coherence with each other constitute the inputs to the network. The relationships between the different variables are embedded in the neural network weights by the training process. As a result, the output can be a correct version of an input pattern that has been distorted by noise, missing data, intermittent faults, or non-linearities. Once the network has been trained with normal operational data using a robust training method, this system has been shown to successfully monitor the selected plant variables for sensor drift or failure by...
Cited by 0
Jurnal Mekanikal, Lim Boon Han, Musa Mailah · 2005
In this paper, the practical development of a novel but yet simple, low cost and user-friendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing stage of the acquired signature signals involving the use of a number of common feature extraction techniques is rigorously highlighted. An intelligent feature of the system is made possible through the application of a multilayer feedforward neural network that is used together with suitable algorithms to complement the verification process. The results of the study showed that the system is effective and promising in identifying correct human signatures presented to the system.
Cited by 0
Yahyaabadi, Amin · Mspace (University of Manitoba) · 2021
Abstract This research develops a drone testbed that enables the rapid development, validation, and qualification of novel spacecraft and drone control algorithms, control hardware, and remote sensing technologies. The drone testbed facilitates advanced navigation and control research by emulating a multitude of dynamic environments, which provides an easily accessible framework for using new technologies in industrial applications. This research introduces an intelligent system identification method to determine the dynamics and aerodynamic parameters of the drone using Particle Swarm Optimization (PSO), a metaheuristic algorithm. This method provides the knowledge of the system's dynamics that is needed for the environment emulation.
Cited by 0Open access
Diletta Cacciagrano, Flavio Corradini, Rosario Culmone et al. · Journal of Ambient Intelligence and Smart Environments · 2018
Intelligent Environments (IEs) are physical spaces where Information Technology (IT) and other pervasive computing technologies are combined in order to achieve specific goals for the users and the environment. IEs have the goal of enriching user experience, increasing awareness of the environment. A number of applications are currently being deployed in domains ranging from smart homes to e-health and autonomous vehicles. Quite often IE support human activities, thus essential requirements to be ensured are correctness, reliability, safety and security. In this paper we present how a set of techniques and tools that have been developed for the verification of software can be employed in the verification of IE described by means of event-condition-action rules. More precisely, we reduce the problem of verifying key properties of these rules to satisfiability and termination problems that can be addressed using state-of-the-art Satisfiability Modulo Theory (SMT) solvers and program analysers. Our approach has been implemented in a tool called vIRONy. Our approach has been validated on a number of case studies from the literature.
Cited by 9Open access
Ximiao Sun · Lecture notes in electrical engineering · 2024
Cited by 0