In digital systems design, the high-speed adders play an essential role in modules like adders, multipliers, division, etc. to obtain the response in quickly. In digital signal processor and computer datapath circuits, carry look-ahead adder (CLA), carry save adder (CSA), carry select adder (CSeA) and carry skip adder are the mostly used fast adders to improve the performance of the system. This work mainly focuses on fault-tolerant carry save adder using hardware redundancy configurations for the betterment of reliability at the cost of the area. The popular methods like dual (DMR) and triple modular redundancy (TMR) are implemented to detect an error and tolerate single event upset (SEU) error respectively. To tolerate multiple errors, for example, two, three and four errors, the 5-modular (quintuple), 7-modular (septuple), and 9-modular (nonuple) redundancy configurations are used respectively. For experimental results, the implementation of a simple addition of four 4-bit numbers is considered on Altera FPGA EP4CE115F29C7 device using Quartus II synthesis software tool. Simulation results reveal that for example in nonuple MR, CSA using CSeA final stage obtain higher performance (45.7 MHz) with moderate power dissipation as 173.36 mW and at the cost of more LEs (216).

Abstract: Background: Nowadays, image forgery is a major issue for digital images when used in surveillance purposes, as evidence in court and crime investigation. In spite of this image forgery, yet no one system exists to accomplish the image tampering detection with high. Aim / Objective: to improve the trustworthiness to assess the digital images in the field of blind image forensics, this work has been focused Copy-Move based image Forgery Detection (CMFD) and classification using Improved Relevance Vector Machine (IRVM). Methodology Initially, the input images are divided into overlapping blocks. Then, Biorthogonal Wavelet Transform with Singular Value Decomposition (BWT-SVD) is applied to extract the feature vector from the blocks. After that, the feature vectors are sorted in lexicographically and the duplicate vectors are identified by similarity between two successive vectors. To decide the similarity of vectors, Minkowski distance and Threshold value is used. Finally, the forgergy detected and classified as authentic image and forged image by IRVM and it will increase the accuracy of process. Results: the performance of proposed scheme evaluated by using CoMoFoD database which is collected from internet and the simulation results shows that the proposed IRVM scheme attained high performance with high accuracy rate of 92.22%, sensitivity rate of 88.4%, specificity rate of 97.6%, F-measure rate of 92.24%, G-mean rate of 92.31%, precision rate of 96.87% and recall rate of 88.4% compared than existing CMFD based Support Vector Machine (SVM) classifier and Hybridization of Hidden Markov Model (HMM) and SVM Classifier in MATLAB environment.

Abstract:\n\n Retinal images provide early signs of diabetic retinopathy, glaucoma, and hypertension. These signs can be investigated based on micro aneurysms or smaller vessels. These studies require accurate tracing of retinal vessel structure from fundus images in an automated manner. However, the existing threshold based segmentation encounters great difficulties such as the detected edges are consisted of discrete pixels and may be incomplete or discontinuous and computationally expensive. To solve above problem, Hierarchical Cat Swarm behaviour based Optimization scheme (HCSO) with Mean Shift Clustering (MSC) algorithm is proposed in this paper. In diagnosis, the vessel angles and lengths are changed particularly in junctions and it’s detected by using vessel segmentation. Also the bifurcations and crossings are disconnected and the vessel paths are interrupted in retinal image. So, the proposed system focused these kinds of junction problems. Initially, the input image is pre-processed using top hat filtering to enhance the accurate vessel extraction. Then, the geometric structure based features are extracted by using morphological scheme. Here, the junction problem is analyzed through a connectivity kernel. The experimental result shows the proposed work has efficient and effective vessel segmentation and can be useful for image-aided diagnosis systems and further applications.

Increase in Electric power demand and green energy concepts made the Electric power sector to integrate renewable energy sources. This situation provokes Thermal power producers (TPP) to influence the market during the unavailability of renewable energy resources. Therefore an intelligent bidding strategy is framed by the TPP to maximize their benefit by utilizing the security constraint violations and wind power uncertainty. The intelligent strategic bidding model of TPP is proposed in this paper. It is modelled as a two level optimization problem. It is considered as an oligopoly market and the Cournot quantity model is applied to the problem. The power producers benefit function is a highly non concave function resulting in many local maxima. As a result, a more global soft computing optimization technique, using Particle Swarm Optimization (PSO), is applied to determine the intelligent optimal bidding parameter for TPP. The modified IEEE 30 bus system is used as test system. The results show that how the TPP can influence the wind integrated electric power market. This model of analysis helps an independent system operator to take wise decisions to run the market in an unbiased manner.

This article is dedicated to the issues of determining the basic concepts of principles for naming / renaming in city toponymy and systematization. The urbanonymy phenomenon is described as a very important mechanism operating the linguocultural and linguo-social system of a particular language. Since they as a system represent the language image as language symbols for distinguishing between intracity objects and perform a certain function of a formed society against the background of space and time. The modern linguistic science contains a great variety of classifications the purpose of which is to systemize names and to determine various approaches to studying them, and to identify the general concept. Many classifications remain disputable and contradictory due to a great variety of onomastic phenomena and their various parameters. This article is aimed at, on one hand, showing an important mechanism of the naming principle, the influence of urbanonyms on city image development (with the city of Astana as an example), and, on the other hand, describing and analyzing them for representation of linguistic and cultural knowledge of the ethnos.

Blood is a bodily fluid that comprehends ample statistics about the health conditions of the subject. Due to the easiness and low-cost of the procedure, it is used as the diagnostic measure for many diseases. Leucocytes are the important components of the blood and hence studied for many serious, contiguous and life-threatening diseases. However, leukocytes are generally classified in laboratories by manual analysis of microscopic images. It is a meticulous and subjective task for pathologists. Human-factors like stress, fatigue and lack of competency can affect the process. Manual examination of blood samples under light microscope can prone to errors. Automated analysis of microscopic data can increase the reliability and throughput of pathologists. This paper reviews the state of the art work in the leucocyte identification and classification.This paper summarizes the current state-of-the-art methods for leucocyte identification and counting. Leucocyte segmentation can be served as the preliminary step in many automated microscopic diagnosis. It also presents the basic structural and textural appearance of the leucocytes which may help in automated analysis. It also covers different stages required for computer-based analysis of blood smear. It analyses the state of the art techniques for various steps of leucocyte identification and classification. This research also provide a list of public datasets for the said research. This research can be used as the beacon house for novice researcher of the field. It provides the in-depth analysis of the current research for leucocyte identification. It also highlights the research gaps and future research directions.

To evaluate the antioxidant activity of Korean wine waste extract, we examined its effect on genomic DNA oxidation and glutathione (GSH) production in HT-1080 cells. Both acetone+methylene chloride (A+M) and methanol (MeOH) extracts, as well as 85% aq. MeOH and n-butanol (n-BuOH) fractions significantly inhibited oxidative DNA damage (p<0.05). GSH levels were significantly increased in both A+M and MeOH extracts (p<0.05). Treatment of cells with fractions of 85% aq. MeOH, n-BuOH and Water significantly increased GSH levels at concentrations of 0.1 mg/mL (p<0.05). The 85% aq. MeOH and n-BuOH fractions showed the highest antioxidant effects, and thus, they may contain valuable active compounds.