Subjects -> MEDICAL SCIENCES (Total: 8359 journals)
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MEDICAL SCIENCES (2268 journals)            First | 1 2 3 4 5 6 7 8 | Last

Showing 201 - 400 of 3562 Journals sorted alphabetically
Audiology - Communication Research     Open Access   (Followers: 10)
Auris Nasus Larynx     Full-text available via subscription  
Australasian Journal of Ultrasound in Medicine (AJUM)     Hybrid Journal  
Australian Coeliac     Full-text available via subscription   (Followers: 1)
Australian Family Physician     Full-text available via subscription   (Followers: 3)
Australian Journal of Medical Science     Full-text available via subscription   (Followers: 2)
Autopsy and Case Reports     Open Access  
Avicenna     Open Access   (Followers: 3)
Avicenna Journal of Clinical Medicine     Open Access  
Avicenna Journal of Medicine     Open Access   (Followers: 1)
Bangabandhu Sheikh Mujib Medical University Journal     Open Access   (Followers: 1)
Bangladesh Journal of Anatomy     Open Access   (Followers: 2)
Bangladesh Journal of Bioethics     Open Access  
Bangladesh Journal of Medical Biochemistry     Open Access   (Followers: 4)
Bangladesh Journal of Medical Education     Open Access   (Followers: 2)
Bangladesh Journal of Medical Microbiology     Open Access   (Followers: 4)
Bangladesh Journal of Medical Physics     Open Access   (Followers: 1)
Bangladesh Journal of Medical Science     Open Access  
Bangladesh Journal of Medicine     Open Access   (Followers: 1)
Bangladesh Journal of Physiology and Pharmacology     Open Access  
Bangladesh Journal of Scientific Research     Open Access   (Followers: 1)
Bangladesh Medical Journal     Open Access  
Bangladesh Medical Journal Khulna     Open Access  
Basal Ganglia     Hybrid Journal  
Basic Sciences of Medicine     Open Access   (Followers: 2)
Batı Karadeniz Tıp Dergisi / Medical Journal of Western Black Sea     Open Access  
Baylor University Medical Center Proceedings     Hybrid Journal  
BBA Clinical     Open Access  
BC Medical Journal     Free  
Benha Medical Journal     Open Access  
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
Bijblijven     Hybrid Journal  
Bijzijn     Hybrid Journal   (Followers: 1)
Bijzijn XL     Hybrid Journal  
Bio-Algorithms and Med-Systems     Hybrid Journal   (Followers: 2)
BioDiscovery     Open Access   (Followers: 2)
Bioelectromagnetics     Hybrid Journal   (Followers: 2)
Bioelectronic Medicine     Open Access   (Followers: 1)
Bioengineering & Translational Medicine     Open Access  
Bioethics     Hybrid Journal   (Followers: 17)
Bioethics Research Notes     Full-text available via subscription   (Followers: 14)
Biologics in Therapy     Open Access  
Biology of Sex Differences     Open Access   (Followers: 2)
Biomarker Research     Open Access   (Followers: 3)
Biomarkers in Medicine     Hybrid Journal   (Followers: 2)
BioMed Research International     Open Access   (Followers: 4)
Biomédica     Open Access  
Biomedical & Life Sciences Collection     Full-text available via subscription   (Followers: 3)
Biomedical and Biotechnology Research Journal     Open Access   (Followers: 1)
Biomedical Engineering     Hybrid Journal   (Followers: 17)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 6)
Biomedical Engineering Research     Open Access   (Followers: 7)
Biomedical Informatics Insights     Open Access   (Followers: 8)
Biomedical Journal     Open Access   (Followers: 3)
Biomedical Materials     Hybrid Journal   (Followers: 7)
Biomedical Microdevices     Hybrid Journal   (Followers: 8)
Biomedical Optics Express     Open Access   (Followers: 6)
Biomedical Photonics     Open Access  
Biomedical Reports     Full-text available via subscription  
Biomedical Research Reports     Full-text available via subscription   (Followers: 2)
Biomedical Safety & Standards     Full-text available via subscription   (Followers: 8)
Biomedical Science and Engineering     Open Access   (Followers: 7)
BioMedicine     Open Access  
Biomedicine Hub     Open Access  
Biomedicines     Open Access   (Followers: 1)
Biomedika     Open Access  
Biomolecular and Health Science Journal     Open Access   (Followers: 1)
Biophysics Reports     Open Access  
BioPsychoSocial Medicine     Open Access   (Followers: 8)
Biosalud     Open Access  
Biostatistics & Epidemiology     Hybrid Journal   (Followers: 1)
Birat Journal of Health Sciences     Open Access  
BIRDEM Medical Journal     Open Access   (Followers: 1)
Birth Defects Research     Hybrid Journal  
Birth Defects Research Part A : Clinical and Molecular Teratology     Hybrid Journal   (Followers: 3)
Birth Defects Research Part C : Embryo Today : Reviews     Hybrid Journal  
BJR|Open     Open Access  
BJS Open     Open Access   (Followers: 1)
Black Sea Journal of Health Science     Open Access  
BLDE University Journal of Health Sciences     Open Access  
Blickpunkt Medizin     Hybrid Journal  
BMC Biomedical Engineering     Open Access  
BMC Medical Ethics     Open Access   (Followers: 21)
BMC Medical Research Methodology     Open Access   (Followers: 9)
BMC Medicine     Open Access   (Followers: 13)
BMC Obesity     Open Access   (Followers: 8)
BMC Proceedings     Full-text available via subscription   (Followers: 1)
BMC Research Notes     Open Access   (Followers: 4)
BMC Sports Science, Medicine and Rehabilitation     Open Access   (Followers: 34)
BMH Medical Journal     Open Access   (Followers: 2)
BMI Journal : Bariátrica & Metabólica Iberoamericana     Open Access  
BMJ     Hybrid Journal   (Followers: 1744)
BMJ Case Reports     Hybrid Journal   (Followers: 26)
BMJ Evidence-Based Medicine     Hybrid Journal   (Followers: 2)
BMJ Global Health     Open Access   (Followers: 3)
BMJ Innovations     Hybrid Journal   (Followers: 6)
BMJ Leader     Hybrid Journal  
BMJ Open     Open Access   (Followers: 42)
BMJ Open Quality     Open Access   (Followers: 19)
BMJ Open Science     Open Access   (Followers: 1)
BMJ Sexual & Reproductive Health     Hybrid Journal   (Followers: 2)
BMJ Surgery, Interventions, & Health Technologies     Open Access  
Bodine Journal     Open Access  
Boletín del Consejo Académico de Ética en Medicina     Open Access  
Boletín del ECEMC     Open Access  
Boletin Médico de Postgrado     Open Access  
Boletín Médico del Hospital Infantil de México     Open Access  
Bone     Hybrid Journal   (Followers: 18)
Bone and Tissue Regeneration Insights     Open Access   (Followers: 2)
Bone Marrow Research     Open Access   (Followers: 2)
Bone Reports     Open Access  
Bosnian Journal of Basic Medical Sciences     Open Access  
Bozok Tıp Dergisi / Bozok Medical Journal     Open Access  
Brachytherapy     Full-text available via subscription   (Followers: 6)
Brain and Development     Full-text available via subscription   (Followers: 5)
Brain Connectivity     Hybrid Journal   (Followers: 5)
Brain Impairment     Full-text available via subscription   (Followers: 2)
Brazilian Journal of Medical and Biological Research     Open Access  
Brazilian Journal of Medicine and Human Health     Open Access  
Brazilian Journal of Pain (BrJP)     Open Access  
Brazilian Journal of Physical Therapy     Open Access   (Followers: 1)
Breastfeeding Review     Full-text available via subscription   (Followers: 18)
British Journal of Biomedical Science     Full-text available via subscription   (Followers: 7)
British Journal of General Practice     Full-text available via subscription   (Followers: 38)
British Journal of Hospital Medicine     Full-text available via subscription   (Followers: 16)
British Medical Bulletin     Hybrid Journal   (Followers: 6)
Buddhachinaraj Medical Journal     Open Access  
Bulletin Amades     Open Access  
Bulletin de la Société de pathologie exotique     Hybrid Journal   (Followers: 1)
Bulletin of Legal Medicine     Open Access  
Bulletin of Medical Sciences     Open Access  
Bulletin of the History of Medicine     Full-text available via subscription   (Followers: 18)
Bulletin of the Menninger Clinic     Full-text available via subscription  
Bulletin of The Royal College of Surgeons of England     Free  
Bulletin of the Scientific Centre for Expert Evaluation of Medicinal Products     Open Access  
Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz     Hybrid Journal   (Followers: 6)
Burapha Journal of Medicine     Open Access  
Burns     Hybrid Journal   (Followers: 10)
Cadernos de Naturologia e Terapias Complementares     Open Access   (Followers: 1)
Calcified Tissue International     Hybrid Journal   (Followers: 2)
Canadian Bulletin of Medical History     Hybrid Journal  
Canadian Family Physician     Partially Free   (Followers: 13)
Canadian Journal of Pain     Open Access   (Followers: 2)
Canadian Journal of Rural Medicine     Full-text available via subscription   (Followers: 1)
Canadian Medical Association Journal     Open Access   (Followers: 17)
Canadian Medical Education Journal     Open Access   (Followers: 10)
Canadian Prosthetics & Orthotics Journal     Open Access  
Cannabis and Cannabinoid Research     Hybrid Journal   (Followers: 1)
Cardiac Electrophysiology Clinics     Full-text available via subscription   (Followers: 1)
Care Management Journals     Hybrid Journal   (Followers: 5)
Case Reports     Open Access  
Case Reports in Acute Medicine     Open Access  
Case Reports in Clinical Medicine     Open Access   (Followers: 1)
Case Reports in Clinical Nutrition     Open Access   (Followers: 1)
Case Reports in Medicine     Open Access   (Followers: 2)
Case Reports in Transplantation     Open Access  
Case Reports in Vascular Medicine     Open Access  
Case Reports in Women's Health     Open Access   (Followers: 4)
Case Study and Case Report     Open Access   (Followers: 5)
CBU International Conference Proceedings     Open Access   (Followers: 3)
Cell & Bioscience     Open Access   (Followers: 6)
Cell Adhesion & Migration     Open Access   (Followers: 9)
Cell and Molecular Response to Stress     Full-text available via subscription   (Followers: 2)
Cell and Tissue Transplantation and Therapy     Open Access   (Followers: 2)
Cell Cycle     Full-text available via subscription   (Followers: 6)
Cell Death and Differentiation     Hybrid Journal   (Followers: 7)
Cell Death Discovery     Open Access   (Followers: 1)
Cell Health and Cytoskeleton     Open Access   (Followers: 1)
Cell Medicine     Open Access   (Followers: 6)
Cell Research     Hybrid Journal   (Followers: 8)
Cell Transplantation     Open Access   (Followers: 4)
CEN Case Reports     Hybrid Journal  
Central African Journal of Medicine     Full-text available via subscription  
Ceylon Journal of Medical Science     Open Access  
Ceylon Medical Journal     Open Access  
Chattagram Maa-O-Shishu Hospital Medical College Journal     Open Access  
Chiang Mai Medical Journal     Open Access  
ChiangRai Medical Journal     Open Access  
Chimerism     Full-text available via subscription  
Chinese Journal of Integrative Medicine     Hybrid Journal   (Followers: 3)
Chinese Journal of Natural Medicines     Full-text available via subscription   (Followers: 1)
Chinese Medical Journal     Open Access   (Followers: 10)
Chinese Medical Record English Edition     Hybrid Journal  
Chinese Medical Sciences Journal     Full-text available via subscription   (Followers: 2)
Chinese Medicine     Open Access   (Followers: 2)
Chinese Medicine     Open Access   (Followers: 4)
Chisholm Health Ethics Bulletin     Full-text available via subscription   (Followers: 1)
CHRISMED Journal of Health and Research     Open Access   (Followers: 2)
Christian Journal for Global Health     Open Access  
Chronic Diseases and Translational Medicine     Open Access  
Chronic Illness     Hybrid Journal   (Followers: 6)
Chronic Wound Care Management and Research     Open Access   (Followers: 4)
Chronobiology International     Hybrid Journal   (Followers: 3)
ChronoPhysiology and Therapy     Open Access  
Chulalongkorn Medical Bulletin     Open Access  
Chulalongkorn Medical Journal     Open Access  
Ciencia e Innovación en Salud     Open Access  
Ciencia e Investigación Medico Estudiantil Latinoamericana     Open Access  
Ciencias Clínicas     Open Access  

  First | 1 2 3 4 5 6 7 8 | Last

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Biophysics Reports
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2364-3439 - ISSN (Online) 2364-3420
Published by Springer-Verlag Homepage  [2570 journals]
  • A Review on Anaglyph 3D Image and Video Watermarking

    • Abstract: Thanks to the rapid growth of internet and the advanced development of 3D technology, 3D images and videos are proliferated over the networks. However, this causes several insecurity problems, and protecting this type of media has become a main challenge for many researchers. 3D watermarking is considered as an efficient solution for 3D data protection. In fact, it consists in embedding a secret key into a 3D content to protect it and in trying to extract it after any attack applied on marked 3D data. Anaglyph is the most popular and economical method among different 3D visualization methods. For this reason, it has become used for many 3D applications. Hence, 3D anaglyph watermarking presents an important research area, and several techniques have been proposed in order to protect this type of media. In this survey paper, the existing anaglyph 3D images and videos watermarking techniques are discussed. This discussion shows that the anaglyph video watermarking field is still not mature and new techniques should be proposed to improve the invisibility/robustness trade-off. In addition, based on the study of anaglyph generation methods, it is concluded that signature can be embedded during the generation stage. Graphical
      PubDate: 2019-03-22
       
  • LGSA: Hybrid Task Scheduling in Multi Objective Functionality in Cloud
           Computing Environment

    • Abstract: Abstract Cloud computing turns to be a big shift from the conventional perception of the IT resources. It is a transpiring computing technology that is increasingly stabling itself as the promising future of distributed on-demand computing. The processes comprised in it are the ones that act as a vital backbone and which strengthen the entire stream of cloud computing as a whole. In specific, Task scheduling is the one such phenomena that enhances the cloud computing in terms of performance. Hence task scheduling that is considered as a predominant one amidst others is what this paper comprises all about. Maximizing the profit via assigning the whole task to the virtual machine is what the problem of scheduling deals with. Although there prevails many more ways to resolve this problem, this paper explores one such solution that consumes lesser number of resources, having lower cost and much importantly consuming lesser energy. By making a profound research regarding this approach of scheduling so as to represent the multi-objective function, both lion optimization algorithm and gravitational search algorithm are hybridized. In spite of having certain drawbacks which could be avoided although, the brighter side relies the merits of making use of both lion search and gravitational search algorithm. There could be many means of measurement for computing the performance of the algorithm. The different algorithms that aid to depict the comparable study encompasses gravitational search algorithm, genetic algorithm and lion, particle swarm optimization. The experimental results serve as the evident for depicting the bitterness of our proposed algorithm compared to the prevailing approaches. As an unexplored path may seem trivial but is effective so does the betterment of our lion approach.
      PubDate: 2019-03-15
       
  • Nonparametric Statistical and Clustering Based RGB-D Dense Visual Odometry
           in a Dynamic Environment

    • Abstract: Abstract The robustness of dense-visual-odometry is still a challenging problem if moving objects appear in the scene. In this paper, we propose a form of dense-visual-odometry to handle a highly dynamic environment by using RGB-D data. Firstly, to find dynamic objects, we propose a multi-frame based residual computing model, which takes a far time difference frame into consideration to achieve the temporal consistency motion segmentation. Then the proposed method combines a scene clustering model and a nonparametric statistical model to obtain weighted cluster-wise residuals, as the weight describes how importantly a cluster residual is considered. Afterward, the motion segmentation labeling and clusters’ weights are added to the energy function optimization of dense-visual-odometry to reduce the influence of moving objects. Finally, the experimental results demonstrate that the proposed method has better performance than the state-of-the-art methods on many challenging sequences from a benchmark dataset, especially on highly dynamic sequences.
      PubDate: 2019-03-07
       
  • Indoor Moving Target 3D-Tracking Algorithm Based on Multi-structure Loss
           Model

    • Abstract: Abstract Because of the influence of obstacles, random noise, signal multipath propagation, and the moving state of moving target, the traditional indoor tracking algorithms have larger error rate in localization accuracy and path optimization. In order to solve these problems, an indoor moving target 3D-tracking algorithm based on wireless sensor networks multi-structure loss model is proposed. In the phase of loss model establishment, this paper presents a multi-structure path loss model. In the phase of localization, this paper proposes a localization algorithm based on regional division. In the phase of tracking, the centroid of the intersection space is used to replace the coordinate which has larger error, and then get on filtering. The simulation results show that the proposed algorithm has high localization accuracy in the case of complicated indoor structure and larger interference. Moreover, the degree of fitting between the tracking path and the real path is high.
      PubDate: 2019-02-25
       
  • Numerical Simulation of Effect of Magnetizer on Magnetic Field of
           Induction Melting Furnace

    • Abstract: Abstract In an induction melting furnace, magnetizers are placed outside the coil region regularly, which prevents leakage of magnetic flux and, therefore, increases the induction melting efficiency of the furnace. In the present paper, the effects of the geometric and structural parameters of magnetizers on the magnetic flux intensity distributed in the material region of an induction melting furnace are investigated. A method for determining resistivity and relative permeability of lamination material of magnetizers in harmonic magnetic field simulation is established. The results indicate that magnetizer height has the strongest influence on the magnetic field distribution formed at the induction coil end. A skin effect and a vector vortex due to magnetic induction were formed at the left and the right sides of the magnetizers, respectively, while a non-magnetized zone was formed in the middle part of the coil. The leakage of the magnetic field at the coil end could be reduced by using an L-type magnetizer. The increased ratio along the circumferential direction of magnetizer improved the magnetic flux intensity in the material field located in the magnetizer gaps, while at the same ratio, increasing the number of magnetizers helped significantly in terms of improving magnetic flux intensity.
      PubDate: 2019-02-15
       
  • Optical Asymmetric Cryptosystem Based on Kronecker Product, Hybrid Phase
           Mask and Optical Vortex Phase Masks in the Phase Truncated Hybrid
           Transform Domain

    • Abstract: Abstract This research work proposes a novel asymmetric scheme by utilizing the hybrid phase truncated fractional Fourier and Gyrator transform with the secure enhancement by adding Kronecker product as a key. In this cryptosystem, the encryption keys constitute Hybrid Phase Mask along with the Optical Vortex Phase Mask and Kronecker product as the other keys. The Hybrid Phase Mask is formed by the combination of a secondary image and random phase mask. The phase truncated parts during encryption process are reserved as decryption keys with the inverse Kronecker product. The proposed method comprises of more obscure keys for upgraded security and to defend different attacks. In support of the technique proposed, the results under the effect of various attacks are presented. The efficiency and robustness of the presented cryptosystem has been examined and demonstrated by simulation in MATLAB (R2014a) with different performance parameters.
      PubDate: 2019-02-13
       
  • A New CT Based Method for Post-operative Motion Analysis of Pelvic
           Fractures

    • Abstract: Abstract Conventional X-ray is commonly used for pelvic fracture follow-ups, but has a precision of only ± 5 mm. Implantation of tantalum beads together with RSA has shown high precision but not applicable in clinical practice. CT scan has been shown a suitable substitute for RSA to follow the metal markers. We aimed to assess whether implantation of metal markers could be avoided using CT scan and merging of bone surface anatomy. A human cadaveric pelvis marked with 0.8 mm tantalum beads was fixed over the symphysis and the right SI-joint. Left hemi-pelvis was subsequently distracted using plastic spacers. Sequential CT exams was conducted and data were analyzed using Sectra® (Sectra AB), CTMA package. Examinations were repeated after 2 weeks. Bone registration showed better precision than registration based on tantalum beads. However, only the difference in angular changes was statistically significant (p = 0.008). The confidence interval of the repeatability was ± 0.5 mm for translation and ± 0.5° for rotation. This new non-invasive technique showed good precision and repeatability and might be a future option in clinical practice for post-operative follow-ups of patients with pelvic fractures.
      PubDate: 2019-01-29
       
  • Image Based Steganography to Facilitate Improving Counting-Based Secret
           Sharing

    • Abstract: Abstract The secret sharing scheme is a security tool that provides reliability and robustness for multi-user authentication systems. This work focuses on improving the security and efficiency of counting-based secret sharing by remodeling its phases. The research presents refining the shares generation phase as well as proposing different secret reconstruction models based on new shares distribution method. This work addressed solving published defects in the original counting-based secret sharing scheme providing optimized efficient methodology. The research further proposed utilizing steganography for practicality purposes. We adopted image-based steganography to hide generated shares preserving the improved security of the scheme enhancing the humanized remembrance usability. The study compared several applicable steganography methods for hiding shares analyzing their distortion, security, and capacity. This facilitating work of image-based steganography with the improved counting-based secret sharing is showing promising results opening research direction for future attractive contributions to follow-on.
      PubDate: 2019-01-18
       
  • Fabric Defect Detection Adopting Combined GLCM, Gabor Wavelet Features and
           Random Decision Forest

    • 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
       
  • Encryption of 3D Point Cloud Using Chaotic Cat Mapping

    • 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
       
  • IoT Based Framework: Mathematical Modelling and Analysis of Dust Impact on
           Solar Panels

    • Abstract: 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
       
  • A Novel n-Rightmost Bit Replacement Image Steganography Technique

    • Abstract: 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
       
  • Energy-Efficient Target Tracking Algorithm for WSNs

    • Abstract: 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
       
  • Hybrid Multi-level Regularizations with Sparse Representation for Single
           Depth Map Super-Resolution

    • 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
       
  • Research on 3D Simulation of Fabricated Building Structure Based on BIM

    • Abstract: 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
       
  • Optimal Design of the Floating Body of the Device of Interception and
           Diversion for Oil Pollution Based on AQWA and MOGA

    • 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
       
  • Evaluation of Supervised Learning Algorithms Based on Speech Features as
           Predictors to the Diagnosis of Mild to Moderate Intellectual Disability

    • Abstract: 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
       
  • Research on Virtual Reconstruction Technology of Tujia Brocade Handcrafts

    • 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
       
  • Non-linear Cryptosystem for Image Encryption Using Radial Hilbert Mask in
           Fractional Fourier Transform Domain

    • Abstract: 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
       
  • Feature Matching Improvement through Merging Features for Remote Sensing
           Imagery

    • Abstract: 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
       
 
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