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2011 International Conference on computer Software and Modeling(ICCSM 2011)

作者： Navid Hashemitaba Ahdieh Sadat Khatavakhotan Siew Hock Ow Department of Software Engineering Faculty of Computer Science and Information TechnologyUniversity of Malaya

The distributed connectivity model presented in this article provides a strategic perspective for development plan using distributed infrastructures and tools for global organizations with e-learning *** on e-education,using virtual world unique features,supporting medical education and treatments,and modifying consumption patterns are four main dimensions of the Four-Faceted Distributed Connectivity Model(FFDC) in this *** and redefinition of groups in organizations and equipping them with ICT tools,and providing formal communication with related departments round the globe,are two necessary rules for implementing the FFDC *** two rules are the needed infrastructure for FFDC model.

关键词： Distributed Connectivity,Global Village,information technology Infrastructure,E-Learning,Telecommunication Facilities

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Improvement of EEG signal-based emotion recognition based on feature learning methods

Improvement of EEG signal-based emotion recognition based on...

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Conference on Artificial Intelligence and Robotics and Asia-Pacific International Symposium

作者： Malihe Mohamadi Amir Masoud Ekhtekhari Moghadam Faculty of Computer and Information Technology Engineering Islamic Azad University Qazvin Iran

ISBN: (纸本)9781728128436

Emotion is inevitable in human life. Today's knowledge is looking for new ways to recognize emotions, without considering of facial expression. One of the new methods for detecting emotions is the use of electroencephalogram signals (EEG). Using signal processing techniques and feature learning methods and with the help of decision tree on EEG signals to improve emotion recognition, a new method for improving emotion recognition is presented in this paper. The proposed method focuses on reducing the number of electrodes used in signal recording and the use of brain alpha waves, and extraction and characterization of characteristics based on received signals, and attempts to improve emotion recognition. Signals are classified using DT decision tree classification after recording, processing and extraction of the property by the two methods of PCA and PSD with. The proposed algorithm has been recorded on 10 people watching 2 videos and 8 happy and sad images. The results obtained from the three pairs of electrodes provide an acceptable improvement percentage. Given a decrease in the number of electrodes and a reduction in processes, an 88.73% improvement is shown in the recognition of emotions of happiness and 86.31% of improvement in detecting emotions of sadness.

关键词： Electroencephalography Feature extraction Decision trees Electrodes Emotion recognition Principal component analysis Brain modeling

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New possibilities for memory acquisition by enabling DMA using network card

New possibilities for memory acquisition by enabling DMA usi...

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IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: technology and Applications

作者： Štefan Balogh Miroslav Mydlo Faculty of Electrical Engineering and Information Technology Institute of Computer Science and Mathematics Bratislava

Direct memory access is one of the techniques used in forensic analysis and rootkit detection. Unfortunately, it can also be misused in various attacks. E.g., the firewire attack enabled bypassing of Windows authorization by reading the user password stored in memory. Thus, for security reasons, firewire port is usually disabled in many computers. This motivates a search for a new ways of enabling direct memory access. Another potential avenue for DMA enabled memory access seems to be the network card. We designed a new solution for direct memory access, based on a custom NDIS protocol driver that can send (on request of the local executable program) the contents of the computer memory over the network. Our new method allows an unexpected type of the direct memory access, which is independent of the processor, and its control capabilities. This is a strong advantage in rootkit detection, because the rootkit cannot take any action to hide itself while the memory is scanned.

关键词： Forensics computers Protocols Random access memory IEEE 1394 Standard Kernel

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Adaptive skin color classification technique for color-based face detection systems using integral image

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International Review on computers and Software 2011年第1期6卷 32-39页

作者： Tabatabaie, Zahra Sadri Rahmat, Rahmita Wirza Udzir, Nur Izura Kheirkhah, Esmaeil Department of Multimedia Systems Faculty of Computer Science and Information Technology University Putra Malaysia Department of Computer Engineering Faculty of Engineering Islamic Azad University Mashhad Branch Iran

Among the various features of human face, skin colour is a more powerful means of discerning face appearance. Numerous skin colour models, which model the human skin colours in different ways, have been proposed by researchers. Furthermore, there are a number of colour spaces which are adopted in skin colour modelling. In particular, the colour-based segmentation is a significant step in any colour-based face detection approach which uses skin-colour models to classify an image into skin and non-skin regions. Varying illumination is one of the most frequent challenges in face detection systems. A change in the light source distribution and in the illumination level (indoor, outdoor, highlights, shadows, non-white lights) affects the appearance of an object (such as human face) in a scene and produces changes in terms of object colour and shape. An adaptive skin colour classification technique, which considerably resolves around the above mentioned problems in case of illumination conditions and shadow, has been proposed and presented in this paper. The proposed method first identifies those pixels that have illumination problem using integral image and then the pixels are adjusted using an adaptive gamma intensity correction method to rectify negative effect of illumination problems. The experiments showed that the proposed method significantly improves the process of a color-based face detection system in terms of both detection rate and accuracy. © 2011 Praise Worthy Prize S.r.l.

关键词： Color

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Putting the practice into software engineering education

Putting the practice into software engineering education

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International Conference on Software engineering: Education and Practice

作者： J. Miller C. Mingins Faculty of Information Technology School of Computer Science and Software Engineering VIC Australia

The paper describes a subject called Software engineering Practise, which introduces software engineering concepts to students in a generalist computing degree. The course has three aims: to establish a foundation of good practice which will form the basis for a personal software improvement process in subsequent studies and in professional life; to introduce object oriented design in a context firmly embedded in software engineering; and to give students a taste of working in groups on a reasonably large project. The success of this course is due to the way in which the object oriented design, the software engineering process aspects and the project work so well together to bring the concepts associated with each part of the course to life and to reinforce each other in a relatively realistic context. Other aspects, which contribute to the success of the course, such as the team approach to course management, individual student assessment, and choice of development environment, are also highlighted.

关键词： Software engineering Electrical capacitance tomography Programming Environmental management computer science education computer science information technology Software design Reflection

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Performance Evaluation of Linux Operating Systems

Performance Evaluation of Linux Operating Systems

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International Conference on Smart Systems and Technologies (SST)

作者： Marko Boras Josip Balen Kresimir Vdovjak Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9781728197593

ISBN: (纸本)9781728197609

Recently, Linux has undergone a significant progress and since it provides many helpful features to companies and home users, it has become one of the most commonly used operating systems in IT industry. Considering the popularity of available Linux distributions, three Linux desktop distributions were selected for further evaluation. The idea of this paper is to evaluate performance and compare three different Linux distributions and their influence on processor, memory, graphics system and disk drive performance. Measurements were performed with a three different benchmarking tools specialized for a specific computer component. All Linux operating system distributions were installed on the same desktop computer and based on the achieved performance measurement results it was concluded that the best results were achieved by using Pop!_OS 20.04. Linux distribution, which is very surprising because it is a relatively new distribution on the market.

关键词： Operating systems Linux Benchmark testing Tools Random access memory Graphics processing units Disk drives

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Facial age estimation using hybrid Haar wavelet and color features with Support Vector Regression

Facial age estimation using hybrid Haar wavelet and color fe...

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Artificial Intelligence and Robotics (IRANOPEN)

作者： Maral Arvanaghi Jadid Mahdi Rezaei Faculty of Computer and Information Technology Engineering Islamic Azad University Qazvin Iran

ISBN: (纸本)9781538628638

Face appearance is one of the most important visual features of human which varies significantly over the aging. Therefore, automatic age estimation is a demanding research topic in the field of facial feature analysis. In the task of age estimation, feature extraction is the first influential step which highly effects on a learning method and its obtained results. The second important step of an age estimation system is training of pattern recognition method based on the extracted feature vector. Considering the importance of the feature extraction and training steps, this paper utilizes the combination of Haar wavelet transform and color moment approaches to extract full-informative and influencing feature elements of face image. To improve the training step, the paper trains a Support Vector Regression (SVR) model, based on the extracted feature vector for age estimation. Experimental results of the proposed method are performed on FG-NET and MORPH datasets and prove the superiority of the method compared with the state-of-the-art methods.

关键词： Feature extraction Image color analysis Face Estimation Wavelet transforms Aging

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Multi-object Paper Money Recognition technology Based on AlexNet Model 3

Multi-object Paper Money Recognition Technology Based on Ale...

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3rd IEEE International Conference on Frontiers technology of information and computer, ICFTIC 2021

作者： Bi, Haiyue Tian, Zhiqiang Ye, Tong Yue, Jingxiong University of Alberta Faculty of Science Edmonton Canada Wuhan University of Technology Department of Logistics Engineering Wuhan China Shanghai Maritime University College of Information Engineering Shanghai China Jiangsu University School of Computer Science and Communication Engineering Zhenjiang China

ISBN: (纸本)9781665406055

The use of physical currency is currently the most widely used method of transaction. The pattern recognition technology of paper currency has a wide range of applications, such as self-checkout machines, ATMs, vending machines, and devices for the blind. In modern society, there are more and more convenience stores. If they can have the RMB recognition system, they will save energy from cashiering. That is the reason for choosing this research Direction. However, it fails to identify images rotated over a certain angle or with excessive noise at first, and it cannot be 100% exact that the accuracy of our work now. But it will be perfected. To realize the function, this paper proposed a neural network model, which can accurately identify RMB. The best performance of the image process can be achieved by utilizing the Automatic white balance, the Automatic brightness, and the Automatic de-noising. Then it is time to cut and extract the image. At last, the image is put into the neural network model for recognition. The defect of this study is that it ignores the influence of possible fluctuation of image quality on the recognition results in the real situation. The related work established a Radial Basis Function Network based on notes interesting features and correlations between images. The image processing technology is used to improve image quality. Through the above methods, the work can identify all kinds of RMB. Moreover, it can already ensure that the success rate of RMB identification can reach more than 90%. © 2021 IEEE.

关键词： Image quality

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Ensemble Transfer Learning for Lymphoma Classification

Ensemble Transfer Learning for Lymphoma Classification

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Marija Habijan Irena Galić Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9798350391886

ISBN: (纸本)9798350391893

The classification of lymphoma types using deep learning models presents a promising avenue for enhancing diagnostic accuracy in medical imaging. This study evaluates the effectiveness of multiple pre-trained convolutional neural networks (CNNs), namely VGG-19, DenseNet201, MobileNetV3, and ResNet50V2, in classifying three common types of lymphoma: chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and mantle cell lymphoma (MCL). We tailored each model via transfer learning to adapt to the specific task of lymphoma classification. Our results indicate that DenseNet201 achieved the highest accuracy with 98.04%, followed by ResNet50V2, MobileNetV3, and VGG-19 with accuracies of 90.13%, 89.07%, and 87.11% respectively. Additionally, an ensemble approach combining all four models demonstrated a significant performance improvement, achieving an accuracy of 98.89%. These findings underscore the potential of advanced CNN architectures and ensemble methods in improving the diagnostic processes for lymphoma through medical imaging, offering a robust tool for clinical support and a pathway toward automated diagnostic systems.

关键词： Deep learning Adaptation models Accuracy Computational modeling Microprocessors Transfer learning computer architecture

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Evolutionary and Biologically Inspired Music, Sound, Art and Design 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Penousal Machado Juan Romero Adrian Carballal

ISBN: (数字)9783642291425

ISBN: (纸本)9783642291418

This book constitutes the refereed proceedings of the First International Conference on Biologically Inspired Music, Sound, Art and Design, EvoMUSART 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoCOP, EvoBIO, and EvoApplications. Due to its significant growth in the last 10 years, this 10th EvoMUSART event has become an Evo* conference in 2012. The 15 revised full papers and 5 poster papers presented were carefully reviewed and selected from 43 submissions. They cover a wide range of topics reflecting the current state of research in the field, including theory, generation, computer aided creativity, computational creativity, and automation.

关键词： Computation by Abstract Devices Programming Techniques computer Communication Networks Image Processing and computer Vision Artificial Intelligence computer Appl. in Arts and Humanities

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