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7th International Conference on Contemporary computing and Informatics, IC3I 2024

作者： Bisht, Girish Singh Jain, Arpit Bansla, Vandna Sharma, Khemraj Bhutia, Rudramani Kumar, Vikas Tula's Institute Department of Computer Science & Engineering Dehradun248001 India Koneru Lakshamaiah Education Foundation Department of Computer Science & Engineering A.P. Vadessahwaram India Shivalik Engineering College Dehradun248001 India Nanhua University Doctoral Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering A.P. India Dev Bhoomi Uttrakhand University School Engineering and Computing Uttrakhand Dehradun India

ISBN: (纸本)9798350350067

Copy-move forgeries often exploit homogeneous regions in images with large-scale attacks to either highlight or conceal target objects. These manipulations are simple to execute but challenging to notice. Forgery detection techniques like Copy-Move Forgery Detection (CMFD) cannot detect these forged documents because they are unable to identify a sufficient number of effective keypoints in homogeneous areas, leading to inaccurate and inefficient results. SURF stands for Speeded-Up Robust Features and is used in this paper along with A-KAZE and Scale-Invariant Feature Transforms. According to our experiment, A-KAZE offers superior detection performance under diverse attacks, especially when it comes to large-scale attacks targeting homogeneous regions. A-KAZE is found to be more accurate than SIFT, SURF, and A-KAZE when applied to the NB-CASIA dataset, achieving detection accuracies of 89.2%, 93.9% and 98.98%.) © 2024 IEEE.

关键词： Image analysis

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Connecting image similarity retrieval with consistent labeling problem by introducing a match-all label

Connecting image similarity retrieval with consistent labeli...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： P.W.H. Kwan K. Kameyama K. Toraichi Doctoral Program Graduate School of Engineering University of Tsukuba Tsukuba Ibaraki Japan Institute of Information Sciences and Electronics Tsukuba Advanced Research Alliance University of Tsukuba Japan

The authors' previous work in image similarity retrieval by relaxation labeling processes (2001) required adding local constraints to obtain an initial set of compatible objects and labels on pairs of images to ensure labeling consistency at convergence. This approach suffers from the problem of over-specified constraints that leads to potentially invaluable information being prematurely removed. To address this problem, we introduce the idea of a Match-all label for objects that failed these constraints. It serves to give them a defined labeling probability as well as allowing them participate in global correspondences through the compatibility model. We show that this enhanced formulation still meets the conditions for a theorem on labeling consistency in Hummel and Zucker (1983) to be satisfied. At convergence, the set of objects and their most consistent labels constitute a best partial labeling for the pair of images.

关键词： Joining processes Image retrieval Labeling Convergence Image segmentation Content based retrieval Image databases Trademarks information retrieval Color

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Classification Based on Texture Analysis for Synthetic Hazy Image from Mount Kelud Haze Image Density 8

Classification Based on Texture Analysis for Synthetic Hazy ...

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8th International Conference on Electrical, Electronics and information engineering, ICEEIE 2023

作者： Nugroho, Fresy Basid, Puspa Miladin Safitri A. Arif, Yunifa Miftachul Diah, Norizan Mat Bahtiar, Firma Sahrul Nurhayati, Hani Kurniawan, Fachrul Priandani, Nurizal Dwi Dermawan, Dodik Arwin Universitas Islam Negeri Maulana Malik Ibrahim Informatics Engineering Faculty of Science and Technology Malang Indonesia School of Computing Sciences College of Computing Informatics and Media Universiti Teknologi Mara Shah Alam Malaysia Library and Information Science Universitas Islam Negeri Maulana Malik Ibrahim Faculty of Science and Technology Malang Indonesia Manajemen Informatika Program Vokasi Universitas Negeri Surabaya Surabaya Indonesia

ISBN: (纸本)9798350340501

This paper classifies the simulations of homogeneous synthetic images, heterogeneous synthetic hazy images, and original hazy images taken from CCTV (Close Circuit Television) of Mt. Kelud crater using the GLCM (Gray Level Co-Occurrence Matrix) method. The average feature values obtained using the GLCM (Gray Level Co-Occurrence Matrix) method are used to compare the similarity of gray feature values of the three and then classify thin, medium, and thick images. The results for classifying thin haze, medium haze, and thick haze on the homogeneous synthetic hazy image test data obtained an accuracy value of 50%, a precision value of 46%, and a sensitivity value of 65%. As for the classification of thin, medium, and thick fog on heterogeneous synthetic hazy images, test data obtained an accuracy value of 42%, a precision value of 32%, and a sensitivity value of 48%. © 2023 IEEE.

关键词： Textures

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On a criterion of selecting the best mother wavelet based on fluency wavelet analysis

On a criterion of selecting the best mother wavelet based on...

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： K. Katagishi T. Urushiyama K. Toraichi K. Wada F. Yoshikawa S. Morokami KDD R&D Labs. Saitama Japan Institute of Information Sciences & Electronics University of Tsukuba Doctoral Program in Engineering University of Tsukuba College of Engineering Systems University of Tsukuba

This paper proposes a new criterion to select the mother wavelet suited for precisely detecting characteristic points on signals, such as non-differentiable points and discontinuous ones, and estimating the periodicity of each signal. The criterion is based on fluency wavelet analysis. We introduce the signal space /sup m/S, by which signals are characterized, spanned by piecewise polynomials of degree (m-1) with a parameter of only (m-2) times continuous differentiability and then formulate the fluency wavelet analysis. In addition, we introduce new parameters /spl lambda//sup (1/) and /spl lambda//sup (2/), and then generalize the fluency wavelet analysis. By varying both parameters /spl lambda//sup (1/) and /spl lambda//sup (2/), piecewise polynomials with an asymmetric property can be generated. Generalized "fluency wavelet analysis" can analyze waveforms nearby the above singular points more precisely.

关键词： Wavelet analysis Continuous wavelet transforms Polynomials Signal analysis Wavelet transforms Hilbert space Research and development Laboratories Systems engineering and theory Fourier transforms

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Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi Mazhar ul Haq Fahim Arif Khursheed Aurangzeb Noor ul Ain Javed Ali Khan Saddaf Rubab Muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

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Evaluation of signature files as set access facilities in OODBs 93

Evaluation of signature files as set access facilities in OO...

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Proceedings of the 1993 ACM SIGMOD international conference on Management of data

作者： Yoshiharu Ishikawa Hiroyuki Kitagawa Nobuo Ohbo Doctoral Degree Program in Engineering University of Tsukuba Tsukuba City Ibaraki 305 Japan Institute of Information Sciences and Electronics University of Tsukuba Tsukuba City Ibaraki 305 Japan

ISBN: (纸本)9780897915922

Object-oriented database systems (OODBs) need efficient support for manipulation of complex objects. In particular, support of queries involving evaluations of set predicates is often required in handling complex objects. In this paper, we propose a scheme to apply signature file techniques, which were originally invented for text retrieval, to the support of set value accesses, and quantitatively evaluate their potential capabilities. Two signature file organizations, the sequential signature file and the bit-sliced signature file, are considered and their performance is compared with that of the nested index for queries involving the set inclusion operator (⊆). We develop a detailed cost model and present analytical results clarifying their retrieval, storage, and update costs. Our analysis shows that the bit-sliced signature file is a very promising set access facility in OODBs.

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An Efficient Three-Factor Authenticated Key Agreement Technique Using FCM Under HC-IoT Architectures

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Computers, Materials & Continua 2022年第7期72卷 1373-1389页

作者： Chandrashekhar Meshram Agbotiname Lucky Imoize Sajjad Shaukat Jamal Parkash Tambare Adel R.Alharbi Iqtadar Hussain Department of Post Graduate Studies and Research in Mathematics Jayawanti Haksar Government Post-Graduation CollegeCollege of Chhindwara UniversityBetul460001M.P.India Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkokaLagos100213Nigeria Department of Electrical Engineering and Information Technology Institute of Digital CommunicationRuhr University44801BochumGermany Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia Water Resources&Applied Mathematics Research Lab Nagpur440027India College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar

The Human-Centered Internet of Things(HC-IoT)is fast becoming a hotbed of security and privacy *** users can establish a common session key through a trusted server over an open communication channel using a three-party authenticated key *** of the early authenticated key agreement systems relied on pairing,hashing,or modular exponentiation processes that are computationally intensive and *** order to address this problem,this paper offers a new three-party authenticated key agreement technique based on fractional chaotic *** new scheme uses fractional chaotic maps and supports the dynamic sensing of HC-IoT devices in the network architecture without a password *** projected security scheme utilized a hash function,which works well for the resource-limited HC-IoT *** results show that our new technique is resistant to password guessing attacks since it does not use a ***,our approach provides users with comprehensive privacy protection,ensuring that a user forgery attack causes no ***,our new technique offers better security features than the techniques currently available in the literature.

关键词： Three-party authenticated key agreement anonymity fractional chaotic maps Chebyshev polynomial password table human-centered internet of things(HC-IoT)

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DEVELOPMENT of GEOSPATIAL information INTEGRATED with BIG DATA to AGRICULTURAL HAZARD MONITORING in WEST JAVA

DEVELOPMENT of GEOSPATIAL INFORMATION INTEGRATED with BIG DA...

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2022 Annual Conference, ASPRS 2022

作者： Virtriana, R. Riqqi, A. Anggraini, T.S. Fauzan, K.N. Ihsan, K.T.N. Mustika, F.C. Atmaja, F.W. Suwardhi, D. Harto, A.B. Sakti, A.D. Deliar, A. Soeksmantono, B. Wikantika, K. Remote Sensing and Geographic Information Sciences Research Group Faculty of Earth Sciences and Technology Institut Teknologi Bandung Bandung40132 Indonesia Center for Remote Sensing Institut Teknologi Bandung Bandung40132 Indonesia Center for Spatial Data Infrastructure Institut Teknologi Bandung Bandung40132 Indonesia Master Program of Geodesy and Geomatics Engineering Faculty of Earth Sciences and Technology Institut Teknologi Bandung Jl. Ganesha No.10 Bandung40132 Indonesia Doctoral Program of Geodesy and Geomatics Engineering Faculty of Earth Sciences and Technology Institut Teknologi Bandung Jl. Ganesha No.10 Bandung40132 Indonesia

Food security is highly dependent on three aspects, namely food availability, food access, and food utilization. The availability aspect depends on food supply which is identical to agricultural productivity. West Java Province is the third national rice producer with 16.6%, but West Java Province is the most extensive rice consumer, around 21.1% of the total national rice consumption. Agricultural productivity can decline due to natural hazards such as floods and droughts. Monitoring floods and droughts in paddy fields are necessary to prevent decreased agricultural productivity. This study aims to monitor the rice fields from the dangers of flooding and drought every month. Agricultural hazard monitoring is divided into two parameters, namely static parameters and dynamic parameters. Dynamic parameters are observed every month so that the hazard index is generated on a monthly scale. GIS and Remote sensing data are integrated to perform agricultural hazard modelling. Furthermore, this agricultural hazard modelling results will be strengthened by using big to provide information about an almost real-Time event that can be accessed through the Application program Interface (API) service. This study uses a data mining system from Drone Emprit that performs data mining on Twitter and news portals with machine learning technology (probabilistic classifier) and Natural Learning Process. The results obtained are around 15,000 data from January 1 to November 1, 2021, and 37.9% of them are identified by location based on the city or district level in West Java Province. It is hoped that the policy-maker can consider the area of agricultural land that requires assistance to increase productivity and plan a policy to support agriculture in West Java in the future. © 2022 R. Virtriana et al.

关键词： Agriculture

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Self-Compassion Around the World: Measurement Invariance of the Short Form of the Self-Compassion Scale (SCS-SF) Across 65 Nations, 40 Languages, Gender Identities, and Age Groups

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Mindfulness 2025年 1-28页

作者： Swami, Viren Tran, Ulrich S. Voracek, Martin Aavik, Toivo Ranjbar, Hamed Abdollahpour Adebayo, Sulaiman Olanrewaju Afhami, Reza Ahmed, Oli Aimé, Annie Akel, Marwan Al Halbusi, Hussam Alexias, George Ali, Khawla F. Alp-Dal, Nursel Alsalhani, Anas B. Álvarez-Solas, Sara Amaral, Ana Carolina Soares Andrianto, Sonny Aspden, Trefor Argyrides, Marios Aruta, John Jamir Benzon R. Atkin, Stephen Ayandele, Olusola Baceviciene, Migle Bahbouh, Radvan Ballesio, Andrea Barron, David Bellard, Ashleigh Bender, Sóley Sesselja Beydaǧ, Kerime Derya Birovljević, Gorana Blackburn, Marie-Ève Borja-Alvarez, Teresita Borowiec, Joanna Bozogáňová, Miroslava Bratland-Sanda, Solfrid Browning, Matthew H. E. M. Brytek-Matera, Anna Burakova, Marina Çakır-Koçak, Yeliz Camacho, Pablo Camilleri, Vittorio Emanuele Cazzato, Valentina Cerea, Silvia Chaiwutikornwanich, Apitchaya Chaleeraktrakoon, Trawin Chambers, Tim Chen, Qing-Wei Chen, Xin Chien, Chin-Lung Chobthamkit, Phatthanakit Choompunuch, Bovornpot Compte, Emilio J. Corrigan, Jennifer Cosmas, Getrude Cowden, Richard G. Czepczor-Bernat, Kamila Czub, Marcin da Silva, Wanderson Roberto Dadfar, Mahboubeh Dalley, Simon E. Dany, Lionel Datu, Jesus Alfonso D. de Carvalho, Pedro Henrique Berbert de Holanda Coelho, Gabriel Lins De Jesus, Avila Odia S. Debbabi, Sonia Harzallah Dhakal, Sandesh Di Bernardo, Francesca Dimitrova, Donka D. Dion, Jacinthe Dixson, Barnaby Donofrio, Stacey M. Drysch, Marius Du, Hongfei Dzhambov, Angel M. El-Jor, Claire Enea, Violeta Eskin, Mehmet Farbod, Farinaz Farrugia, Lorleen Fian, Leonie Fisher, Maryanne L. Folwarczny, Michał Frederick, David A. Fuller-Tyszkiewicz, Matthew Furnham, Adrian García, Antonio Alías Geller, Shulamit Ghisi, Marta Ghorbani, Alireza Martinez, Maria Angeles Gomez Gradidge, Sarah Graf, Sylvie Grano, Caterina Gyene, Gyöngyvér Hallit, Souheil Hamdan, Motasem Handelzalts, Jonathan E. Hanel, Paul H. P. Hawks, Steven R. Hekmati, Issa Helmy, Mai Hill, Tetiana Hina, Farah Holenweger, Geraldine Hřebíčková, Martina Ijabadeniyi, Olasupo Augustine Imam, Asma İ School of Psychology and Sport Science Anglia Ruskin University Cambridge United Kingdom Centre for Psychological Medicine Perdana University Kuala Lumpur Malaysia Department of Cognition Emotion and Methods in Psychology Faculty of Psychology University of Vienna Vienna Austria Institute of Psychology University of Tartu Tartu Estonia Department of Psychology Istinye University Istanbul Turkey Department of Psychology and Behavioural Studies Ekiti State University Ado-Ekiti Nigeria Department of Art Studies Tarbiat Modares University Tehran Iran Department of Psychology University of Chittagong Chattogram Bangladesh Department of Psychoeducation and Psychology Université du Québec en Outaouais Saint-Jérôme Canada INSPECT-LB: National Institute of Public Health Clinical Epidemiology and Toxicology Beirut Lebanon School of Pharmacy Lebanese International University Beirut Lebanon Department of Management Ahmed Bin Mohammad Military College Doha Qatar Faculty of Psychology Panteion University of Social and Political Sciences Athens Greece Royal College of Surgeons Ireland-Bahrain Adliya Bahrain Department of Midwifery Faculty of Health Sciences Munzur University Tunceli Turkey Department of Oral Medicine and Diagnostic Sciences Vision College of Dentistry and Nursing Vision Colleges Riyadh Saudi Arabia Facultad de Salud Universidad Internacional de La Rioja Logroño Spain Science and Technology of Southeast Minas Gerais Federal Institute of Education Barbacena Brazil Department of Psychology Universitas Islam Indonesia Yogyakarta Indonesia Department of Psychology Aberystwyth University Ceredigion United Kingdom Department of Psychology Neapolis University Pafos Paphos Cyprus Department of Psychology De La Salle University Manila Philippines Department of General Studies The Polytechnic Ibadan Nigeria Department of Psychology University of Ibadan Ibadan Nigeria Health Research and Innovation Science Centre Faculty of Health Sciences Klai

Objectives: The 12-item Self-Compassion Scale–Short Form (SCS–SF) is a widely used instrument for the assessment of self-compassion. To date, there have been few examinations of this instrument’s psychometric properties, particularly across nations and languages. Therefore, we used data from the Body Image in Nature Survey (BINS) to assess measurement invariance of the SCS–SF across nations, languages, gender identities, and age groups. Methods: Participants (N = 56,968) from 65 nations completed the SCS–SF in 40 languages. Using these data, we tested various hypothesised models of the SCS–SF in the total sample and, using multi-group confirmatory factor analysis, tested for invariance of the optimal model across national groups, languages, gender identities, and age groups. Results: In the total dataset, we found that an 11-item, 2-factor model (i.e., SCS-11) provided best fit to the data, with the two factors tapping distinct constructs of compassionate and uncompassionate self-responding. The SCS-11 was found to be partially scalar invariant across national groups and languages, and fully scalar invariant across gender identities and age groups. There was wide variation in latent means for the two factors, particularly across national groups and languages. Further analyses showed negligible associations between the two factors and sociodemographic variables, including marital status, financial security, and urbanicity. Conclusions: Our results suggest that it may be possible to derive a stable 2-factor model of the SCS–SF for use in cross-cultural research, but also highlight the likelihood of cross-national and cross-linguistic variations in the way that self-compassion is understood. © The Author(s) 2025.

关键词： Cross-cultural Measurement invariance Multi-group confirmatory factor analysis (MG-CFA) Self-Compassion Scale Short Form

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A fault-tolerant evolvable face identification chip

A fault-tolerant evolvable face identification chip

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International Conference on Neural information Processing

作者： M. Yasunaga T. Nakamura I. Yoshihara Institute of Information Sciences and Electronics University of Tsukuba Tsukuba Ibaraki Japan Doctoral Program of Engineering University of Tsukuba Tsukuba Ibaraki Japan Cooperative Research Center Miyazaki University Miyazaki Japan

We have developed a new design methodology for face identification chips using a genetic algorithm. In the design, face images are transformed to truth-tables and they are evolved to obtain generalization ability. Digital circuits are synthesized by using the evolved truth-tables. Parallelism in the data can be embedded in the circuits by this direct hardware implementation of the face images. A face identification chip prototype has been developed by synthesizing the evolved truth tables to logic circuits. The circuit size of the chip was 1334 gates for one person on average, and this was small enough to be implemented onto a standard FPGA (field programmable gate array) chip. The chip identified a face image at 400 ns and achieved an identification accuracy of 97.2% in average. Furthermore, a high identification accuracy of more than 90% was maintained even under 18% faulty gate ratio and this high fault tolerance degraded gracefully as the faulty gate ratio increased.

关键词： Fault tolerance Fault diagnosis Circuit synthesis Field programmable gate arrays Circuit faults Design methodology Genetic algorithms Digital circuits Hardware Prototypes

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