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  Subjects -> ENGINEERING (Total: 2515 journals)
    - CHEMICAL ENGINEERING (210 journals)
    - CIVIL ENGINEERING (219 journals)
    - ELECTRICAL ENGINEERING (120 journals)
    - ENGINEERING (1320 journals)
    - ENGINEERING MECHANICS AND MATERIALS (403 journals)
    - HYDRAULIC ENGINEERING (57 journals)
    - INDUSTRIAL ENGINEERING (84 journals)
    - MECHANICAL ENGINEERING (102 journals)

ENGINEERING (1320 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 8)
3D Research     Hybrid Journal   (Followers: 21)
AAPG Bulletin     Hybrid Journal   (Followers: 8)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 6)
ACS Nano     Hybrid Journal   (Followers: 309)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 7)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 3)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 10)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 9)
Advanced Journal of Graduate Research     Open Access  
Advanced Nonlinear Studies     Hybrid Journal  
Advanced Science     Open Access   (Followers: 6)
Advanced Science Focus     Free   (Followers: 5)
Advanced Science Letters     Full-text available via subscription   (Followers: 11)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 5)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 9)
Advances in Engineering Software     Hybrid Journal   (Followers: 28)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 14)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 23)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 29)
Advances in Nonlinear Analysis     Hybrid Journal  
Advances in Operations Research     Open Access   (Followers: 12)
Advances in OptoElectronics     Open Access   (Followers: 6)
Advances in Physics Theories and Applications     Open Access   (Followers: 16)
Advances in Polymer Science     Hybrid Journal   (Followers: 45)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 50)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 3)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 6)
AIChE Journal     Hybrid Journal   (Followers: 35)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access   (Followers: 1)
Al-Nahrain Journal for Engineering Sciences     Open Access  
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 27)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 10)
American Journal of Engineering Education     Open Access   (Followers: 12)
American Journal of Environmental Engineering     Open Access   (Followers: 16)
American Journal of Industrial and Business Management     Open Access   (Followers: 25)
Anadolu University Journal of Science and Technology A : Applied Sciences and Engineering     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Pure and Applied Logic     Open Access   (Followers: 3)
Annals of Regional Science     Hybrid Journal   (Followers: 8)
Annals of Science     Hybrid Journal   (Followers: 7)
Antarctic Science     Hybrid Journal   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 6)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 20)
Applied Clay Science     Hybrid Journal   (Followers: 6)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 14)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 7)
Applied Sciences     Open Access   (Followers: 3)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 6)
Arab Journal of Basic and Applied Sciences     Open Access  
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 9)
Arid Zone Journal of Engineering, Technology and Environment     Open Access   (Followers: 2)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 2)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 9)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
AURUM : Mühendislik Sistemleri ve Mimarlık Dergisi = Aurum Journal of Engineering Systems and Architecture     Open Access  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Automotive Experiences     Open Access  
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Avances en Ciencias e Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Batteries     Open Access   (Followers: 6)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 28)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 1)
BER : Motor Trade Survey     Full-text available via subscription  
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 1)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 3)
Beyond : Undergraduate Research Journal     Open Access  
Bhakti Persada : Jurnal Aplikasi IPTEKS     Open Access  
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Bilge International Journal of Science and Technology Research     Open Access  
Biofuels Engineering     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 11)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering     Hybrid Journal   (Followers: 2)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 20)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 35)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 8)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomicrofluidics     Open Access   (Followers: 5)
BioNanoMaterials     Open Access   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 40)
Bitlis Eren University Journal of Science and Technology     Open Access  
Black Sea Journal of Engineering and Science     Open Access  
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 13)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 14)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers Droit, Sciences & Technologies     Open Access  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 31)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 44)
Carbon Resources Conversion     Open Access   (Followers: 1)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 6)
Case Studies in Thermal Engineering     Open Access   (Followers: 6)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 7)
Catalysis Science and Technology     Free   (Followers: 8)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 7)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal  
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencia y Tecnología     Open Access  
Ciencias Holguin     Open Access   (Followers: 3)
CienciaUAT     Open Access   (Followers: 1)
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 13)
City, Culture and Society     Hybrid Journal   (Followers: 23)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
Clinical Science     Hybrid Journal   (Followers: 8)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 6)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 3)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 3)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 15)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Communications in Information Science and Management Engineering     Open Access   (Followers: 4)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 29)
Composite Interfaces     Hybrid Journal   (Followers: 7)
Composite Structures     Hybrid Journal   (Followers: 291)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 228)
Composites Part B : Engineering     Hybrid Journal   (Followers: 270)
Composites Science and Technology     Hybrid Journal   (Followers: 202)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access   (Followers: 1)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Optimization and Applications     Hybrid Journal   (Followers: 9)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)

        1 2 3 4 5 6 7 | Last

Journal Cover
3D Research
Journal Prestige (SJR): 0.222
Citation Impact (citeScore): 1
Number of Followers: 21  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Online) 2092-6731
Published by Springer-Verlag Homepage  [2352 journals]
  • Fabric Defect Detection Adopting Combined GLCM, Gabor Wavelet Features and
           Random Decision Forest
    • Authors: Nilesh Tejram Deotale; Tanuja K. Sarode
      Abstract: In image analysis and pattern recognition activity, one of the most salient characteristics is texture. The global region of images in spatial domain has an enhanced processing effect with the help of co-occurrence matrix and in the frequency domain for the admirable performance such as multi-scale, multi-direction local information is obtained from Gabor wavelet. The consolidation of gray-level co-occurrence matrix and Gabor wavelet is utilized to fabric image feature texture eradication. In classification phase, random decision forest (RDFs) Classifier is applied to classify the input fabric image into defective or non-defective. RDFs are a novel and outfit machine learning strategy which fuses the element choice. Nevertheless, RDFs exhibit a lot of advantages when compared with other modeling approaches within the category. The main advantages are, RDFs can handle both the continuous and discrete variables, RDFs does not overfit as a classifier, and run quick and productively when taking care of expansive datasets. Graphical In this paper the consolidation of gray-level co-occurrence matrix (GLCM) and Gabor wavelet is utilized to fabric image feature texture eradication. In classification phase, random decision forest (RDFs) classifier is applied to classify the input fabric image into defective or non-defective.
      PubDate: 2019-01-14
      DOI: 10.1007/s13319-019-0215-1
      Issue No: Vol. 10, No. 1 (2019)
       
  • Encryption of 3D Point Cloud Using Chaotic Cat Mapping
    • Authors: Chaochuan Jia; Ting Yang; Chuanjiang Wang; Binghui Fan; Fugui He
      Abstract: 3D point clouds, a new primitive representation for objects, are spreading among thousands of people through internet software. Thus, the privacy preserving problem of the 3D point cloud should be widely concerned by more and more people. To ensure the safe transmission and use of point cloud, two schemes of encryption have been proposed by using chaotic cat mapping in this paper. The two encryption schemes are tested by using various types of 3D point clouds. In addition, these proposed encryption algorithms are analyzed through key space, sensibility, statistical and encryption time analysis. These analysis results show that the two proposed schemes can resist the common existing cipher attacks and are effective encryption methods for 3D point cloud encryption. At the same time, the two promising encryption algorithms can guarantee the security of the 3D point cloud model transmitted on the Internet. Graphical
      PubDate: 2019-01-05
      DOI: 10.1007/s13319-018-0212-9
      Issue No: Vol. 10, No. 1 (2019)
       
  • IoT Based Framework: Mathematical Modelling and Analysis of Dust Impact on
           Solar Panels
    • Authors: Alisha Makkar; Anisha Raheja; Rashmi Chawla; Shailender Gupta
      Abstract: The solar photovoltaic performance is governed by manifold parameters viz. temperature, irradiance, dust on solar module, photoactive material, panel orientation. Among these dust is a critical impediment, as its accumulation on panel surface degrades its productivity; while frequent cleaning sessions affect module’s life and result into PV destruction. Accordingly, the need to know dust thickness responsible for deteriorating panel’s capability and adequate cleaning time of solar panels to produce optimum yields is requisite. This paper aims to discern a right cleaning time, owing to a particular dust thickness so as to conserve the panel efficiency using internet of things (IoT). The mathematical correlations of PV efficiency and current with thickness of accumulated dust are derived using linear regression. Further, these equations are associated with an IoT-based platform which remotely monitors and records PV output current; thereafter dust thickness corresponding to a significant current reduction is estimated. For this, experimental data of 46 inverters with total 114,819.30 kWh productions in a month with an average of 4416.13 kWh/day is accessed and the results pertaining to mathematical analysis exhibit a decline in current by 1 A with 5.51 × 10−3 mm thickness of dust.
      PubDate: 2019-01-04
      DOI: 10.1007/s13319-018-0214-7
      Issue No: Vol. 10, No. 1 (2019)
       
  • Hybrid Multi-level Regularizations with Sparse Representation for Single
           Depth Map Super-Resolution
    • Authors: Doaa A. Altantawy; Ahmed I. Saleh; Sherif S. Kishk
      Abstract: Limited spatial resolution and varieties of degradations are the main restrictions of today’s captured depth map by active 3D sensing devices. Typical restrictions limit the direct use of the obtained depth maps in most of 3D applications. In this paper, we present a single depth map upsampling approach in contrast to the common work of using the corresponding combined color image to guide the upsampling process. The proposed approach employs a multi-level decomposition to convert the depth upsampling process to a classification-based problem via a multi-level classification-based learning algorithm. Hence, the lost high frequency details can be better preserved at different levels. The adopted multi-level decomposition algorithm utilizes \(l_{1} ,\) and \(l_{0}\) sparse regularization with total-variation regularization to keep structure- and edge-preserving smoothing with robustness to noisy degradations. In addition, the proposed classification-based learning algorithm supports the accuracy of discrimination by learning discriminative dictionaries that carry original features about each class and learning common shared dictionaries that represent the shared features between classes. The proposed algorithm has been validated via different experiments under variety of degradations using different datasets from different sensing devices. Results show superiority to the state of the art, especially in case of upsampling noisy low-resolution depth maps.
      PubDate: 2018-12-03
      DOI: 10.1007/s13319-018-0208-5
      Issue No: Vol. 9, No. 4 (2018)
       
  • Research on 3D Simulation of Fabricated Building Structure Based on BIM
    • Authors: Dongmei Zhao; Yanhong Yao
      Abstract: In order to solve the problem of low accuracy and poor analysis of traditional fabricated building structure, the new BIM-based 3D simulation method for fabricated building structure is proposed. Drawings and related documents are obtained from the database. Through the REVIT software, the 3D simulation model is drawn by the BIM technical team and the fabricated building structure is simulated in 3D. The design of the REVIT platform is realized by three stages: structural space constraint relationship determination, geometric component generation and color processing. The spatial mesh structure is used to describe the geometric components, and the homomorphic filtering is used to process the colors. The bounding box and the hierarchical bounding box method are used to detect the collision of the steel structure. For static combinations, the bounding box method is used to implement collision detection, and the hierarchical bounding box method is used to detect dynamic combinations. The experimental results show that the proposed method can effectively realize the 3D simulation of the fabricated building structure, and the detection results are accurate, the overall performance is excellent, and the user satisfaction is high.
      PubDate: 2018-11-21
      DOI: 10.1007/s13319-018-0209-4
      Issue No: Vol. 9, No. 4 (2018)
       
  • Optimal Design of the Floating Body of the Device of Interception and
           Diversion for Oil Pollution Based on AQWA and MOGA
    • Authors: Ya-hui Wang; Jian-ting Wang; Min-le Zhang; Lin-feng Wu; Tao Zhang
      Abstract: For the specific conditions of the physical characteristics of the oil pollution and the installation location, the overall design of the floating body was carried out. And it was parametrically modeled with Creo4.0. The AQWA was used to analyze the hydrodynamic performance of the floating body. Then the multi-objective optimization design parameters and target parameters were determined. Within the main design parameters of the floating body, using the design of experiment of the space filling design and AQWA, the design parameters were discretized, and representative samples were extracted and refined. On the basis of constructing the response surface using artificial neural network, the global optimization was performed using MOGA, and the Pareto front was obtained. The optimal solutions of the candidate points obtained and the simulation solutions under the optimal main design parameters are compared, and there is a certain deviation between the two. In engineering applications, the results of numerical optimization should be verified again to determine whether the selected candidate points are suitable. In addition, the numerical simulation results before optimization are compared with those after optimization, and the optimized floating body has better hydrodynamic performance. Graphical
      PubDate: 2018-11-19
      DOI: 10.1007/s13319-018-0197-4
      Issue No: Vol. 9, No. 4 (2018)
       
  • Evaluation of Supervised Learning Algorithms Based on Speech Features as
           Predictors to the Diagnosis of Mild to Moderate Intellectual Disability
    • Authors: Gaurav Aggarwal; Latika Singh
      Abstract: Due to age-bound onset of symptoms used for diagnosis of mild to moderate intellectual disability, early diagnosis of these problems has long been a difficult issue. The diagnosis includes tests pertaining to intellectual functioning and adaptive behaviours including communication skills etc. In this paper, it is proposed to use speech features as an early indicator of the disorder which can be used to train machine learning algorithms for differentiating between speech of normally developing children and children with intellectual disability. In this paper, speech abnormalities are quantified using acoustic parameters including Linear Predictive Cepstral Coefficients, Mel Frequency Cepstral Coefficients and spectral features in speech samples of 48 participants (24 with intellectual disability and 24 age-matched controls). A training dataset was created by extracting these features which was used for learning by various classifiers. The experiments show promising results where Support Vector Machine gives an accuracy of 98%. Consequently, a well-trained classification algorithm can be used as an aid in early detection of mild to moderate intellectual disability.
      PubDate: 2018-11-08
      DOI: 10.1007/s13319-018-0207-6
      Issue No: Vol. 9, No. 4 (2018)
       
  • Research on Virtual Reconstruction Technology of Tujia Brocade Handcrafts
    • Authors: Gang Zhao; Hui Zan; Bingbing Di; Wenjuan Zhu; Yali Yu
      Abstract: The colorful Tujia brocade culture is formed through thousands of years’ inheritance, development, and creation in China. However, the influence of the Tujia brocade culture has been gradually weakened for the restrictions of regional and economic development. Also the traditional brocade handcrafts are on the verge of disappearing. Consequently, it is important and necessary to reconstruct traditional Tujia brocade skill by using digital protection technology. Lots of researchers have studied the reconstruction of cultural scenes through the virtual simulations of character movements in the field of intangible cultural heritage, and most studies focus only on limb movements or only on detailed hand movements, while few of them have combined the limb movements and detailed hand movements. According to the characteristics of Tujia brocade craftsmanship, a solution of virtual reconstruction of the traditional Tujia brocade handcrafts to solve the difficult problem for the simultaneous synthesis of limb movements and detailed hand movements was presented in this paper. The solution used Kinect (Kinect for windows v2) and Leap motion to capture the limb movements and detailed hand movements respectively. Then it established traditional process motion data set of Tujia brocade by integrating limb and detailed hand movement data. Finally, it adopted mean smoothing algorithm to manipulate the motion data and drove the character model to realize the virtual reconstruction of the traditional Tujia brocade handcrafts. Multiple simulation and system fluidity test results showed that the proposed method could solve the problem of simultaneous synthesis of limb movements and hand movements in virtual reconstruction of traditional handcrafts effectively. Graphical
      PubDate: 2018-11-02
      DOI: 10.1007/s13319-018-0206-7
      Issue No: Vol. 9, No. 4 (2018)
       
  • Non-linear Cryptosystem for Image Encryption Using Radial Hilbert Mask in
           Fractional Fourier Transform Domain
    • Authors: Priyanka Maan; Hukum Singh
      Abstract: An asymmetric image encryption scheme has been proposed in the fractional Fourier transform (FRT) domain, using a radial Hilbert mask in the input plane and a random phase mask based in the frequency plane. The use of a radial Hilbert mask provides an addition of extra encryption parameter along with the asymmetric scheme which is non-linear where the encryption and decryption keys are different. The encrypted image resulting from the application of FRT is attenuated by a factor and combined with the asymmetric scheme to provide an encrypted image. The decryption process is the reverse of the encryption. The designed scheme has been implemented digitally using MATLAB R2014a (8.3.0.532). By analysing the decryption results using input images the strength and efficacy of the proposed scheme has been established. The performance assessment of the method has been evaluated in terms of peak signal-to-noise ratio, mean-squared-error (MSE). The proposed scheme provides increased security.
      PubDate: 2018-10-19
      DOI: 10.1007/s13319-018-0205-8
      Issue No: Vol. 9, No. 4 (2018)
       
  • Feature Matching Improvement through Merging Features for Remote Sensing
           Imagery
    • Authors: Shahid Karim; Ye Zhang; Ali Anwar Brohi; Muhammad Rizwan Asif
      Abstract: Feature matching is the core stage for object recognition, tracking and several applications of computer vision. Low resolution images have various limitations with respect to spatial, spectral, pixel and temporal information which reduces the performance of image processing approaches. We have combined SURF features with FAST and BRISK features individually in order to provide an optimal solution for feature matching. Furthermore, feature matching has exploited through combined features and compared the performance with state-of-the-art methods. Lastly, RANSAC and MSAC were utilized to eliminate the wrong matches to get optimal feature matches. The experimental results show that the combination of FAST–SURF and BRISK–SURF perform feature matching optimally according to the number of feature matches and estimated time.
      PubDate: 2018-10-17
      DOI: 10.1007/s13319-018-0203-x
      Issue No: Vol. 9, No. 4 (2018)
       
  • A Self-Supervised Learning Method for Shadow Detection in Remote Sensing
           Imagery
    • Authors: Shoulin Yin; Jie Liu; Hang Li
      Abstract: Recent research progress in shadow detection has leveraged the development of remote sensing and computer vision. Since shadows of buildings, trees, bridges in one image can provide useful information about the scene to help people understand the shape, feature or estimate their locations and orientations of original objects, especially for damaged objects. In this study, a novel shadow detection algorithm for remote sensing imagery, called self-supervised learning method is proposed. The aim of this work is to generate shadow ratio threshold automatically without human interaction. To alleviate the traditional drawbacks of shadow detection, we fully combine supervised and unsupervised shadow detection method to suggest a self-supervised learning method, which supports us a strongly clue with establishing the relation of shadow and its original object. Subsequently, we benefit from gray-scale histogram to extract shadow segments, then shadow outlines are obtained. Finally, we assess the shadow detection performance of the proposed approach by comparing our results with the state-of-the-art methods. The results reveal the applicability and precision of the proposed self-supervised learning shadow detection technique.
      PubDate: 2018-10-17
      DOI: 10.1007/s13319-018-0204-9
      Issue No: Vol. 9, No. 4 (2018)
       
  • Contrast Enhancement Technique Based on Lifting Wavelet Transform
    • Authors: Megha Goyal; Bharat Bhushan; Shailender Gupta; Rashmi Chawla
      Abstract: Contrast enhancement is an indispensable process for improving the subjective quality and information content of an image. Adjustment in the relative brightness and darkness of an image is done in order to attain the same. This paper employs lifting wavelet transform (LWT) to enhance the image since it is computationally inexpensive. The application of LWT results in the low and high frequency components. The former components that contain most of the information are enhanced using CLAHE algorithm while the latter are kept unchanged. In addition, a weighted average matrix which controls the level of enhancement is used to acquire the enhanced output image. To measure the efficacy, the proposed technique is implemented in MATLAB-2013 and evaluated on the basis of several performance metrics such as: absolute mean brightness error, average information content, Contrast Improvement Index, degree of entropy unpreserved, Structural Similarity Index, Universal Quality Index. From experiment, it can be observed that the results obtained from proposed algorithm are better than or comparable to other popular techniques in literature in almost all the parameters undertaken.
      PubDate: 2018-10-12
      DOI: 10.1007/s13319-018-0201-z
      Issue No: Vol. 9, No. 4 (2018)
       
  • Multi-objective Optimization of Permanent Magnet Adjustable Speed Driver
           Base on RSM Model and NSGA-II
    • Authors: Xinquan Yin; Yaping Zhang; Jun Wang
      Abstract: To optimise the structure of a permanent magnet adjustable speed driver (PMASD), a multi-objective optimization design method for increasing the output torque and reducing the eddy current loss was proposed. Firstly, the three-dimensional finite element method model of a PMASD was established, the influence of the main configuration parameters in the PMASD on the output torque and the eddy current loss was analyzed, and the reasonable range of the parameters was determined. When taking the minimal eddy current loss and maximum output torque as the optimal objectives, the secondary response surface numerical model equation was built using the Central Composite Design experimental method and the Response Surface Methodology. Then, while ensuring that the output torque of the PMASD is not less than the rated torque, the NSGA-II was used to perform multi-objective optimization based on the response surface model and the Pareto optimal solution sets for two objectives was obtained. Finally, the minimal eddy current loss model and maximum output torque model were selected to compare with the initial model that was not optimized. The simulation results proved that the output torque of the minimal eddy current loss model increased by 6.54% based on the reduction of eddy current loss by 0.81% and the output torque of the maximum output torque model increased by 24.41% based on an increase in eddy current loss of 10.51%: the performance of both optimization models had been improved significantly. The optimization results show that this method improves the transmission performance of the PMASD.
      PubDate: 2018-10-11
      DOI: 10.1007/s13319-018-0202-y
      Issue No: Vol. 9, No. 4 (2018)
       
  • Offline Handwritten Signature Verification Using Cylindrical Shape Context
    • Authors: Pradeep N. Narwade; Rajendra R. Sawant; Sanjiv V. Bonde
      Abstract: Offline handwritten signatures is a convincing evidence form of biometrics for verification. However, the verification of offline handwritten signatures is challenging task because of the variations in handwritten signatures. To address this difficulty, this paper proposes a new approach to represent the shape. In this newly proposed approach, the signature pixels are represented by: (1) Gaussian Weighting Based Tangent Angle, to represent the curve angle at the reference pixel; (2) a new shape descriptor, i.e. cylindrical shape context is proposed for a detailed and accurate description of the curve at corresponding pixel. Experimental results show that desired pixel matching results are obtained by using cylindrical shape context which automatically increases the accuracy of verification of offline handwritten signatures. The shape dissimilarity measures are computed and given to the Support Vector Machine with Radial Basis Function (RBF) kernel for classification of signature. The results obtained using GPDS synthetic signature database, UTSig persian offline signature database, and MCYT-75 offline signature database shows the effectiveness of proposed cylindrical shape context.
      PubDate: 2018-10-11
      DOI: 10.1007/s13319-018-0200-0
      Issue No: Vol. 9, No. 4 (2018)
       
  • Metaheuristic Techniques for Detection of Optic Disc in Retinal Fundus
           Images
    • Authors: Jyotika Pruthi; Shaveta Arora; Kavita Khanna
      Abstract: Eye diseases like glaucoma and diabetic retinopathy are known to be the thieves of eye-sight that are responsible for causing the vision loss worldwide. Automatic detection of such diseases with the help of the digital color fundus photography helps in early diagnosis and treatment. From the fundus images, optic disc is required to be analyzed to diagnose the disease. In this paper, a technique has been proposed for locating optic disc through metaheuristic techniques namely Ant Colony Optimization algorithm, Bacterial Foraging Optimization, Firefly algorithm, Cuckoo Search algorithm and Krill Herd algorithm. A comparison has been made amongst all of them and also with existing disc detection techniques. The bacterial foraging algorithm has shown the best results as it has obtained 99.55% accuracy with DiaRetDB1 database, 100% accuracy with HEI-MED database, 100% with DRIVE database and 98% with STARE database.
      PubDate: 2018-10-01
      DOI: 10.1007/s13319-018-0198-3
      Issue No: Vol. 9, No. 4 (2018)
       
  • Modeling and Optimization of Tool Wear and Surface Roughness in Turning of
           Al/SiCp Using Response Surface Methodology
    • Authors: Rashid Ali Laghari; Jianguang Li; Zhengyou Xie; Shu-qi Wang
      Abstract: Nowadays metal matrix composites are widely utilized in major industries such as aerospace and automotive because of their excellent properties in association with non-reinforced. This research work is attempted to analyze the consequence of cutting parameters on tool life and surface quality. The experimental work is consist of turning Al/SiCp (45%SiCp) weight with uncoated Carbide tools and the effect of three machining parameters including depth of cut, feed, and speed. Tool life and surface roughness have considered as process response for investigation. The predictive model has been developing to optimize the machining parameters in accordance to Box–Behnken design in Minitab 17, the contour plots the surface plot and response optimizer have made to study the influence of machining parameters and their interactions. ANOVA was carried out to identify the key factor affecting the tool life and surface roughness. The maximum tool life is 10.511 (min) and least surface roughness was observed 0.044 μm. The abrasion and adhesive have the principle wear mechanism observed in machining process. Response surface methodology (RSM) approach have used to optimize the machining parameters, and the RSM model found more than 95% confidence level.
      PubDate: 2018-09-24
      DOI: 10.1007/s13319-018-0199-2
      Issue No: Vol. 9, No. 4 (2018)
       
  • Improvement of Large-Vehicle Detection and Monitoring on CPEC Route
    • Authors: Muhammad Ibrar; Jianing Mi; Shahid Karim; Asif Ali Laghari; Shakir Muhammad Shaikh; Vishal Kumar
      Abstract: Satellite imagery is being used to monitor agriculture fields, vehicle detection, surveillance and remote sensing. In this paper, we proposed large-vehicle detection to monitor the status on route of China Pakistan economic corridor (CPEC). In the present experiments, the region of interests extracted from more than thousand images through different angles to train machine for large-vehicle detection using RCNN, Fast-RCNN, Faster-RCCN and Cascade methods. The training images were enhanced through contrast change and image sharpening to avoid errors during detection of vehicles on route. Results show that the proposed method is promising for large-vehicle detection on CPEC route. The Faster-RCNN is more promising due to fast computational speed with high precision and recall rate. Furthermore, the developed dataset is also useful for future CPEC applications such as large-vehicles/trucks tracking, detection and identification. Graphical
      PubDate: 2018-09-03
      DOI: 10.1007/s13319-018-0196-5
      Issue No: Vol. 9, No. 3 (2018)
       
  • An Effective DOS Attack Detection Model in Cloud Using Artificial Bee
           Colony Optimization
    • Authors: Jitendra Kumar Seth; Satish Chandra
      Abstract: Denial of service (DOS) attack is a serious threat in the cloud which causes unavailability of cloud services to genuine users. Firewalls alone are not able to detect DOS attack because of the dynamic nature of the attack and masked identity. This paper proposes a cloud-based DOS attack detection model (CDOSD) which is setup through key feature selection using a new binary version of Artificial bee colony optimization (BABCO) and decision tree (DT) classifier. The DT classifier is utilized because it has superior learning speed than other classification algorithms and BABCO is used for feature selection from the dataset. The real-time DOS attack tools are used to perform the attacks on cloud host. It has been observed that the CDOSD detects DOS attack on cloud host with high accuracy and a very low false positive rate. The features of the dataset are significantly reduced by BABCO which provides a low dimension of computation space for training and classification. The proposed scheme is also compared with the other existing models and found superior in performance. The proposed methodology may help the cloud service providers to design more secure cloud environment. Graphical
      PubDate: 2018-09-03
      DOI: 10.1007/s13319-018-0195-6
      Issue No: Vol. 9, No. 3 (2018)
       
  • A Novel n-Rightmost Bit Replacement Image Steganography Technique
    • Authors: Aditya Kumar Sahu; Gandharba Swain
      Abstract: Image steganography is a technique for hiding the secret data in a carrier image. This paper proposes a novel n-right most bit replacement image steganography technique to hide the secret data in an image, where 1 ≤ n ≤ 4. The major objectives of the proposed technique are, (1) improving the peak signal to noise ratio (PSNR), (2) improving the embedding capacity (EC), (3) avoiding the fall of boundary problem (FOBP), and (4) robustness against salt and pepper noise and RS attack. Initially, the n-right most bits for each pixel and the n-bits of the secret data are converted to decimal values. Then, using the difference between these two decimal values the original pixels are readjusted to produce stego-pixels. From the experimental results it is observed that PSNR is higher for lower value of n and the EC is larger for the higher value of n. Furthermore, it is also experimentally investigated that the proposed technique is resistant to steganalytic attacks.
      PubDate: 2018-12-17
      DOI: 10.1007/s13319-018-0211-x
      Issue No: Vol. 10, No. 1 (2018)
       
  • Energy-Efficient Target Tracking Algorithm for WSNs
    • Authors: Chunming Wu; Chen Zhao; Haoquan Gong
      Abstract: In order to solve the problem of node energy consumption in wireless sensor networks, an energy-efficient tracking cluster structure is proposed. The structure of the tracking cluster is determined by the cooperation between the auxiliary node and the cluster head node, and avoids the redundant nodes participating in the tracking. In order to balance the energy consumption of cluster head nodes, the method predict the position of target in next time by making auxiliary nodes track algorithm, then according to the prediction results, the nodes near prediction position are woken up in advance to reduce the energy consumption in the whole net. In the process of tracking, the loss recovery mechanism is adopted to solve the target loss phenomenon, and the continuous tracking of the target is completed. Finally, experiments are carried out with the improved particle filter algorithm. The simulation results show that the proposed algorithm can reduce the energy consumption of the nodes under the condition that the tracking accuracy is satisfied. Make the whole network energy consumption more balanced.
      PubDate: 2018-12-08
      DOI: 10.1007/s13319-018-0210-y
      Issue No: Vol. 10, No. 1 (2018)
       
 
 
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