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Encoding Spatial Context for Large-Scale Partial-Duplicate Web Image Retrieval

Journal of computer Science & technology 2014年第5期29卷 837-848页

作者：周文罡李厚强卢亦娟田奇 Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Department of Electronic Engineering and Information Science University of Science and Technology of China Department of Computer Science Texas State UniversitySan Marcos TX 78666 U.S.A. MemberACMIEEE Department of Computer Science University of Texas at San AntonioSan Antonio TX 78249 U.S.A. Senior MemberIEEE

Many recent state-of-the-art image retrieval approaches are based on Bag-of-Visual-Words model and represent an image with a set of visual words by quantizing local SIFT（scale invariant feature transform） features. Feature quantization reduces the discriminative power of local features and unavoidably causes many false local matches between images, which degrades the retrieval accuracy. To filter those false matches, geometric context among visual words has been popularly explored for the verification of geometric consistency. However, existing studies with global or local geometric verification are either computationally expensive or achieve limited accuracy. To address this issue, in this paper, we focus on partialduplicate Web image retrieval, and propose a scheme to encode the spatial context for visual matching verification. An efficient affine enhancement scheme is proposed to refine the verification results. Experiments on partial-duplicate Web image search, using a database of one million images, demonstrate the effectiveness and efficiency of the proposed *** on a 10-million image database further reveals the scalability of our approach.

关键词： large-scale image retrieval spatial context coding spatial verification affine estimation

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Integration of cultural dimensions into software localisation testing of assistive technology for deaf children

Integration of cultural dimensions into software localisatio...

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2011 5th Malaysian Conference in Software Engineering, MySEC 2011

作者： Ping, Tan Ping Chan, Chiu Po Sharbini, Hamizan Julaihi, Azlina Ahmadi Department of Computing and Software Engineering Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Malaysia Department of Information Systems Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Malaysia Department of Computer System and Comm. Technologies Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Malaysia

ISBN: (纸本)9781457715310

Lack of hearing ability hinders deaf children from mastering grammar in language studies. Unfortunately, such software targeting Malay language is limited. This paper attempts to generate new approach in handling such software. These include detection of defects when switching into local languages, date format and accommodating the local laws. The acceptance of international software for local use goes beyond just these aspects. For this purpose, software that supports the multi-languages is evaluated. The main research question of this paper: The lack of cultural dimensions in localisation testing of assistive technology decreases the effectiveness of localisation testing of the localised software. On the account of cultural dimensions, Hofstede's Cultural Dimensions will be experimented to study which cultural dimensions are most suited for such software. From our empirical results, the failure rate of the testing is higher compared to incorporating culture dimensions. © 2011 IEEE.

关键词： Audition

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Application of genetic algorithm and tabu search in software testing 11

Application of genetic algorithm and tabu search in software...

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Proceedings of the Fourth Annual ACM Bangalore Conference

作者： Rathore, Abhishek Bohara, Atul Prashil, R. Gupta Prashanth, T. S. Lakshmi Srivastava, Praveen Ranjan Computer Science and Information System Department Birla Institute of Technology and Science Rajasthan Pilani 333031 India

ISBN: (纸本)9781450307505

This paper presents a technique for automatic test-data generation in software testing. The proposed approach is based on genetic and tabu search algorithms. It combines the strength of two metaheuristic techniques and produces efficient results. The conventional approach for test-data generation using genetic algorithm is modified by applying a tabu search heuristic in mutation step. It also incorporates backtracking process to move search away from local optima. The experimental results show that the algorithm is effective in providing test data and its performance is better than simple genetic algorithm. Copyright 2011 ACM.

关键词： Tabu search

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Comparison of website content measurement of selected Mongolian institutions 08

Comparison of website content measurement of selected Mongol...

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2nd International Conference on Theory and Practice of Electronic Governance, ICEGOV'08

作者： Tsend, Ganbat Department of Information System Computer Science and Management School Mongolian University of Science and Technology Ulaanbaatar Mongolia

ISBN: (纸本)9781605583860

The development and implementation of e-Mongolia National Program requires government organizations to deliver information and services to individuals and businesses through several channels. Some of these channels include the use of Internet technologies. Among them, website is one of the most important. The aim of this study is to assess the content of Mongolian websites and make a comparison across different sectors, including government, banks, universities, etc. The assessment considers the type, amount and scope of content published in websites. Copyright 2008 ACM.

关键词： Websites

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Supervised Machine Learning-Based Prediction of COVID-19

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computers, Materials & Continua 2021年第10期69卷 21-34页

作者： Atta-ur-Rahman Kiran Sultan Iftikhar Naseer Rizwan Majeed Dhiaa Musleh Mohammed Abdul Salam Gollapalli Sghaier Chabani Nehad Ibrahim Shahan Yamin Siddiqui Muhammad Adnan Khan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of CIT Faculty of Applied StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Minhaj University LahoreLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan

COVID-19 turned out to be an infectious and life-threatening viral disease,and its swift and overwhelming spread has become one of the greatest challenges for the *** yet,no satisfactory vaccine or medication has been developed that could guarantee its mitigation,though several efforts and trials are *** around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely *** this regard,healthcare experts,researchers and scientists have delved into the investigation of existing as well as new *** situation demands development of a clinical decision support system to equip the medical staff ways to timely detect this *** state-of-the-art research in Artificial intelligence(AI),Machine learning(ML)and cloud computing have encouraged healthcare experts to find effective detection *** study aims to provide a comprehensive review of the role of AI&ML in investigating prediction techniques for the COVID-19.A mathematical model has been formulated to analyze and detect its potential *** proposed model is a cloud-based smart detection algorithm using support vector machine(CSDC-SVM)with cross-fold validation *** experimental results have achieved an accuracy of 98.4%with 15-fold cross-validation *** comparison with similar state-of-the-art methods reveals that the proposed CSDC-SVM model possesses better accuracy and efficiency.

关键词： COVID-19 CSDC-SVM artificial intelligence machine learning cloud computing support vector machine

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Design and implementation of a dynamic reconfigurable classroom for cooperative learning

Design and implementation of a dynamic reconfigurable classr...

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3rd IEEE International Conference on Intelligent Networking and Collaborativesystems, INCoS 2011

作者： Kondo, Hideki Narahara, Hiroyuki Department of Mechanical Information Science and Technology Faculty of Computer Science and System Engineering Kyushu Institute of Technology Iizuka Japan

ISBN: (纸本)9780769545790

In order to practically examine a new type of class, in which cooperative learning is taken into consideration, we designed and built a classroom. This classroom, in which furniture and a flexible ICT basis are both designed reconfigurable, supports much more complex interactions between learners than in a traditional classroom. Two months' observation of the activities in the classroom shows that many aspects of the reconfigurations have encouraged complex interactions within cooperative learning. © 2011 IEEE.

关键词： Collaboration Cooperative Learning Dynamic Reconfigurable Classroom Dynamic scheduling Education information science Materials Multicore processing Servers classroom furniture complex interaction computer aided instruction cooperative learning dynamic reconfigurable classroom flexible ICT furniture

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Audio steganography applications using auditory features watermarking 2

Audio steganography applications using auditory features wat...

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2nd International Conference on Mechanical, Electronics, computer, and Industrial technology, MECnIT 2018

作者： Banjarnahor, Jepri Siregar, Saut Dohot Sihombing, Oloan Turnip, Mardi Purba, Windania Aisyah, Siti Banjarnahor, Jaidup Department of Information System Faculty of Technology and Computer Sciences Universitas Prima Indonesia Indonesia Medan Indonesia

Watermarking is a technique for hiding data or information on a digital multimedia (image, sound and video) and is not visible to the ordinary eye and is resistant to digitization (editing media, noising, blurring, etc.). While audio watermark is defined as a technique of hiding data or confidential information into an audio data for "boarding" (audio host), people do not aware of the existence of additional data on the data host. Coding phase is hiding data by exchanging the original phase of the initial segment of the sound signal with the absolute phase of the watermark signal, while maintaining the relative phase between the signal segments using different phase segments of the original signal. When the phase difference between the original signal and the modified signal is small, the difference in sound produced is not detected by human hearing. To recognize ownership of multimedia content, testing is done first by combining the cover and watermark files. Experiment result on audio files shows that audio files successfully compressed on 50% efficiency without reducing the duration of the audio. After compression process, One of our audio sample which size is 3.37MB can be reduce to 1.68MB without reducing the duration of the audio. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Audition

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SFC: A Three Layer Smart Phone-Fag-Cloud Framework for Defending Against JavaScript Code Injection Vulnerabilities on OSN 8

SFC: A Three Layer Smart Phone-Fag-Cloud Framework for Defen...

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8th International Conference Confluence on Cloud Computing, Data Science and Engineering, Confluence 2018

作者： Gupta, Shashank Gugta, B.B. Birla Institute of Technology and Science Department of Computer Science and Information System Pilani Rajasthan333031 India

ISBN: (纸本)9781538617182

This article introduced a Fog centric model in the proximity of smart phone devices and virtual Cloud Data Centers (CDC) that senses and avoids an execution of JavaScript code injection vulnerabilities on Online Social Network (OSN). Such offline CDC statically computes the features of clustered-sanitized compressed patterns of JavaScript attack vectors embedded in the HTTP response messages and inject them on the online edge servers of Fog Computing network. The online edge web server dynamically re-computes the features of JavaScript code and compares these features with the statically calculated features in offline mode. Any discrepancy observed in these features will alarm the signal of injection of malicious script code on the edge server. The prototype of our Fog centric framework was developed in Java and installed on the offline virtual machines of Cloud platforms and online edge servers of Fog computing architecture. The online evaluation results exposed that the JavaScript attack vectors sensing rate of our work is high with tolerable rate of False Negatives (FNs), False Positives (FPs) and lesser overall performance overhead during the peak congestion of generation of sanitized HTTP response on the fog nodes. © 2018 IEEE.

关键词： Fog

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Earthquake Prediction Using Deep Neural Networks 8

Earthquake Prediction Using Deep Neural Networks

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8th International Conference on Advanced Computing and Communication systems, ICACCS 2022

作者： Bhargava, Bharat Pasari, Sumanta Birla Institute of Technology and Science Pilani Department of Computer Science and Information System Rajasthan Pilani India

ISBN: (纸本)9781665408165

Reliable prediction of earthquakes has numerous societal and engineering benefits. In recent years, the exponentially rising volume of seismic data has led to the development of several automatic earthquake detection algorithms through machine learning approaches. In this study, we propose a fully functional and efficient earthquake detector cum forecaster based on deep neural networks of long-short-term memory (LSTM) units. The model captures inherent temporal characteristics of earthquake data. For illustration, we consider an earthquake catalog from the Himalaya and its neighboring regions. The proposed LSTM model shows satisfactory performance for small to medium-sized earthquakes. We also implement a baseline artificial neural network (ANN) model to perform a suitable comparison. It is observed that both ANN and LSTM models fail to produce desired result for large events. © 2022 IEEE.

关键词： Long short-term memory

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N-dimension data visualization spaces for academic programmes quality monitoring in Nigeria higher education

N-dimension data visualization spaces for academic programme...

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2019 World Congress on Engineering and computer Science, WCECS 2019

作者： Igbape, Emadomi M. Idogho, Philipa O. Department of Statistics and Computer Science Management Information System Department of Computer Science Auchi Polytechnic Nigeria School of Evening Studies Department of Office Technology School of Information and Communication Technology Auchi Polytechnic Nigeria

ISBN: (纸本)9789881404879

In recent times, especially in Nigeria and other developing countries, numerous factors, hinged on poor financing, inadequate facilities to cope with explosive population of school age children and youth, poor methods of educational services delivering, and globalization issues in education have aggregately affected Quality Assurance (QA) in education. This has continued to draw concerns from government, industry and other stake holders in international education. Regulatory bodies of various nationalities have put in place a number of QA methods and procedures. Implementing these procedures with manual methods does not yield desirable results due to obvious administrative, financial and resources challenges. It becomes necessary to develop and integrate environment specific information technology (IT) tools in the administration of education and implementation of QA processes. This paper focuses on visualization of data generated from the multifarious activities and academic transactions in higher education system and models the framework for utilizing these data to achieve desirable QA results. This data visualization spaces forms an integral component of the development of generic application for quality monitoring in Higher Education. © Newswood *** right reserved.

关键词： Quality assurance

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