Search

One of the most pressing problems in the industry at the moment is figuring out how to make wireless sensor networks (WSN) more reliable and extend their lifespan. The processes of selection and the development of clusters are incredibly significant; however, carrying them out is challenging and time-consuming despite the significance of the tasks. In the most recent study, researchers began their hunt by selecting a particular cluster head to use as a basis for their investigation. On the other hand, the model that was suggested utilizes evolutionary cluster head selection as one of its components. This contributes to the acceleration of computing, the improvement of selection precision, and the prevention of the selection of duplicate nodes. When the results of the simulation of the suggested model are compared to the results of simulations using other methods and techniques, we find that our method is both more accurate and more efficient. This was discovered when the results of the simulation of the proposed model were compared to the results of simulations using other approaches and techniques. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) has developed as one of the most promising technologies for the future. This has been achieved by advances in technology to avail small, inexpensive, and smart sensors, which result in cost effective and easily deployable WSNs. Clustering technique is used in communication protocols, so that considerable amount of energy has been conserved while transmitting the data to the cluster head rather than directly to the far away sink. In some applications, the sensors will be triggered to send data when the sensed data exceed the threshold value. In these circumstances, limited number of sensor nodes gets activated and sends the data and remaining nodes are under idle mode. Hence energy consumption is more in these activated regions, which leads to death of sensors nodes. It is concentrated on these activated sensors and find the change in the ratio between the active nodes and alive nodes to calculate the optimal cluster number for each round. The optimum number of clusters is calculated so that the balanced clusters are created. Extensive analysis has been made with e isting protocols, and found that the proposed methodology out performs the existing protocol in terms of networks life time and throughput. [ABSTRACT FROM AUTHOR]

Indexing and query processing is an emerging research field in spatio - temporal data. Most of the real-time applications such as location based services, fleet management, traffic prediction and radio frequency identification and sensor networks are based on spatiotemporal indexing and query processing. All the indexing and query processing applications is any one of the forms, such as spatio index access and supporting queries or spatio-temporal indexing method and support query or temporal dimension, while in spatial data it is considered as the second priority. In this paper, give the survey of the various uncertain indexing and query processing techniques. Most of the existing survey works on spatio-temporal are based on indexing methods and query processing, but presented separately. Both the indexing and querying are related, hence state - of - art of both the indexing and query processing techniques are considered together. This paper gives the details of spatio-temporal data classification, various types of indexing methods, query processing, application areas and research direction of spatio-temporal indexing and query processing. [ABSTRACT FROM AUTHOR]

The aim of Image fusion is to combine the information from number of images of the same scene from different images with focus on different objects. The result of image is more informative and of better quality often the entropy content of the resultant image is poor due to improper local fusing. In this paper a comparative study and modified spatial domain approach is presented by fixing the contrast values of pixel in between the Average -minimum, and Average-Maximum to get better fusion capabilities. Experimental results demonstrates that the few of the proposed techniques outperform the existing techniques in terms of SNR and PSNR. [ABSTRACT FROM AUTHOR]

The objective of Image fusion is to combine the information from number of images of the same scene from different sensors or the images with focus on different objects. The result of image fusion is an image which is more informative and of better quality. In this paper a detailed survey of Select Maximum /Minimum and principal component analysis for spatial domain image fusion techniques is done. On the basis of the survey an improved spatial domain fusion technique is proposed. The proposed spatial domain technique output performs as the state of the art spatial domain techniques. [ABSTRACT FROM AUTHOR]

A new watermarking approach based on affine Legendre moment invariants (ALMIs) and local characteristic regions (LCRs) which allows watermark detection and extraction under affine transformation attacks is presented in this paper. It is a non-blind watermarking scheme. Original image color image is converted into HSV color space and divided into four parts. LCR is constructed and a set of affine invariants are derived on LCRs based on Legendre moments for each part. These invariants can be used for estimating the affine transform coefficients on the LCRs. ALMIs are used for watermark embedding, detection and extraction as they provide synchronization and invariant feature which is necessary for a robust watermarking scheme. The proposed scheme shows resistance to geometric distortion, cropping, filtering, compression, and additive noise than the existing ALMI based scheme [Alghoniemy, M. and Tewfik, A. H. [2004] "Geometric invariance in image watermarking," IEEE Trans. Image Process 13(2), 145-153] and affine geometric moment invariant (AGMI) based scheme [Seo, J. S. and Yoo, C. D. [2006] "Image watermarking based on invariant regions of scale-space representation," IEEE Trans. Signal Process. 54(4), 1537-1549]. [ABSTRACT FROM AUTHOR]

Data mining methods are used to mine voluminous data to find useful information from data. The data that is to be mined may have a large number of dimensions, so the mining process will take a lot of time. In general, the computation time is an exponential function of the number of dimensions. It is in this context that we use dimensionality reduction techniques to speed up the decision-making process. Dimensionality reduction techniques can be categorized as Feature Selection and Feature Extraction Techniques. In this paper we compare the two categories of dimensionality reduction techniques. Feature selection has been implemented using the Information Gain and Goodman-Kruskal measure. Principal Component Analysis has been used for Feature Extraction. In order to compare the accuracy of the methods, we have also implemented a classifier using back-propagation neural network. In general, it is found that feature extraction methods are more accurate than feature selection methods in the framework of credit risk analysis. [ABSTRACT FROM AUTHOR]

In this paper, Principal Component Analysis is used for feature extraction, and a statistical learning based Support Vector Machine is designed for functional classification of clinical data. Appendicitis data collected from BHEL Hospital, Trichy is taken and classified under three classes. Feature extraction transforms the data in the high-dimensional space to a space of fewer dimensions. The classification is done by constructing an optimal hyperplane that separates the members from the nonmembers of the class. For linearly nonseparable data, Kernel functions are used to map data to a higher dimensional space and there the optimal hyperplane is found. This paper works with different SVMs based on radial basis and polynomial kernels, and their performances are compared. [ABSTRACT FROM AUTHOR]

Watermarking is a potential method for the protection of ownership rights on digital images. A robust, invisible, non-blind watermarking scheme in the wavelet domain is proposed in this paper. The watermark is embedded in the mid frequency band after performing a single level wavelet decomposition using Discrete Wavelet Transform (DWT). The coefficients are grouped randomly prior to watermarking. The watermarked image is tested for various attacks including filtering and geometric attacks. The novelty of the proposed approach is that it provides better resistance to collusion attack also when compared with existing spatial domain approach. The appropriate mid frequency band for embedding the watermark is tested and the HL band proves to be the best. [ABSTRACT FROM AUTHOR]

Digital watermarks have been embedded invisibly in digital media to protect copyrights of legal owners. In this paper two new robust digital color image watermarking schemes using fan beam projections are proposed and their imperceptibility, capacity and robustness are analyzed. The approach FBWLC adds a binary watermark to both the luminance and chrominance content of a color image whereas FBWC adds the watermark to the chrominance content of the color image and is based on Fan Beam Transform that takes multiple projections of the image from different angles. It is observed that FBWC scheme is robust to almost all the attacks and FBWLC scheme is more robust and guarantees zero bit error rate (BER) to most of the attacks on color images namely compression, filtering, blurring and sharpening and is compared with an existing approach based on Spatio Chromatic Discrete Fourier Transform (SCDFT). Also, when compared with other works in color image watermarking, these approaches embed a huge amount of data thereby increasing the watermarking capacity while preserving image quality by subjective evaluation. [ABSTRACT FROM AUTHOR]

Since its advent, the use of digital camera in mobile phones is getting more popular, where information retrieval based on visual appearance of an object is very useful when specific parameters for the object are not known. Though it is well-liked, it needs energy aware algorithms to carry out the various tasks such as segmentation and feature extraction. In this paper, a new energy aware fuzzy color segmentation algorithm is proposed and which has been applied for face segmentation in criminal identification using mobile devices. The criminals in the application are in three classes. They are New Criminal (NC), Suspected Criminal (SC) and Confirmed Criminal (CC). It is basically a mobile image-based content search engine that takes photographs of criminals as image queries and finds their relevant contents by matching them to the similar contents in the criminal databases. The energy aware fuzzy color segmentation is used to obtain the most significant parts of an image — facial regions of the persons and which are used in building image-based queries to the databases. Content search methodology in the application is also improved through the fuzzy modeling to make the application more flexible and simpler. Through the experiment conducted, it has been found that the proposed color segmentation algorithm is more robust and it reduces the computational time in searching process by minimizing the number of false cases. It could detect the faces in the images where the other known algorithms have failed to detect. [ABSTRACT FROM AUTHOR]

Introduction: Children with cerebral palsy (CP) have a higher incidence of respiratory dysfunction than healthy children. Virtual reality breathing therapy is an assistive technology that is becoming popular in the rehabilitation of children with CP., Methods: This experimental study included a total of 32 children with spastic diplegic CP who were divided into two groups: the virtual reality breathing training (VRBT) group and the incentive spirometry (IST) group. Individuals classified as levels I to III on the gross motor function classification system (GMFCS) were recruited using the simple random sampling method., Result: The results of comparing the values of forced vital capacity (FVC), forced expiratory volume at one second (FEV1), and the ratio of FVC/FEV1 showed a significant difference between groups. A significant difference was found in the VRBT group compared to the IST group, except for the peak expiratory flow (PEF) values, which showed a nonsignificant difference between the groups., Conclusion: There were significant differences in FVC and FEV1 between the VRBT and IST groups. It has been concluded that VRBT has additional benefits in improving pulmonary functions., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, S et al.)

Today, Coronavirus disease (COVID-19) which is believed to be transmitted from bats to humans where the people of Wuhan city, China exposed to the wet animal market is an important international public health anxiety (Xiong et al., 2020). Although, several measures were undertaken to treat the diseases by various medical advancements and by a variety of treatment procedures, still the mortality is higher. Hence, social distancing has been implemented to control the current outburst of this pandemic which spreads through human to human transmission. As a consequence, there is a need to completely understand the route of invasions of the virus into the humans and the target receptors besides the other factors leading to the disease. Several vaccines and drugs have been developed with its own pros and cons. Many are still under the various phase of R&D and clinical trials. Here we highlight the possible entry molecules, pathogenesis, symptomatology, probable cure and the recently developed vaccines for the existing pandemic due to the COVID-19., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Inspite of various health warnings from Government and health organizations, Calcium carbide (CaC 2 ) is still the most commonly and widely used artificial fruit ripener, probably due to its easy availability, low cost and convenience of usage. Assessment of the hazardous effects of the CaC 2 applications for fruit ripening has been a matter of interest since long. Several in vivo studies have reported the toxicological outcomes such as histopathological changes in lungs and kidneys, haematological and immunological responses, upon exposure with CaC 2 . However, a well-controlled study investigating the effects of CaC 2 under in-vitro setup was lacking. Hence, this study has been conducted to explore the toxicity associated cellular events in L929 cells exposed with varying concentrations of CaC 2 (0.00312-0.2 μg/μl) for 24 h exposure time. A 23.14% reduction in cell viability was observed at the highest dose of CaC 2 . A similar trend in cellular stress levels at 0.2 μg/μl dose was observed in terms of rounded cellular morphology and decreased adherence as compared to the control. Furthermore, Annexin V FITC/PI staining and subsequent confocal imaging revealed a similar trend of CaC 2 induced apoptosis in a dose dependent manner. A gradual elevation of intracellular ROS has also been observed up to 0.025 μg/μl dose. Thus, the study concludes that short term CaC 2 exposure may increase the cellular oxidative stress and disturb the redox balance of the cell which then undergoes apoptosis. The study concludes that the exposure of CaC 2 can be associated with severe diseases and suggests to stop the uses of CaC 2 as fruit ripening agent.