Anatomical Aspect of Snayu; Ayurveda and Modern Perspectives

In Ayurveda, ligaments described as Snayu while tendon described as Kandra. Anatomically the muscle, ligament and tendon represent extra-articular apparatus. Snayu as structure of human body posses close relation to the Sandhi. Snayu as bunches of fibres helps to maintain body posture and impart weight wearing capacity. Acharya Sushruta referred working of Snayu as like binding plates of boats that allows boat to bear the weight. Snayu itself mean to bind, it helps to bind joints together and its fibrous nature provides flexibility. As anatomical structure Snayu having physiological importance but also suffered by pathological problems. There are some diseases described in Ayurveda related to the impairment of Snayu possessing symptoms of pain, stiffness and swelling, etc. Snayu Sharira needs to be understood in details to explore its physiological, anatomical and pathological aspects. Present article explain Ayurveda and modern view on Snayu Sharira

A study of growth of private hospital

There were so many private hospitals, charitable hospitals, government hospitals are working in India as well as other countries. Amazing facilities, best services are offered to the patients.  But patient’s demand is also increasing day by day and also it is reasonable. This research paper tries to focus on the expectations of the patient in nowadays. From this research paper hospitals must want to pay full attention on the demands and expectations of the patients and hospitals should try to fulfill all demands of the patient

Attracting Foreign Direct Investment in Bangladesh

This article seeks to depict the needs of Foreign Direct Investment (FDI) in Bangladesh along with the required determinants of congenial investment environments. In terms of the identified determinants of FDI, this study delineates the competitive and inductive factors other FDI recipient countries have in comparison to that of Bangladesh. The study also identifies the determinants of FDI that Bangladesh have. Reasons of why Bangladesh could not attract enough FDI have also been sought. The feasible attractive measures required in attracting the much-needed investment in the competitive FDI market have also been shown. In doing this, international competitors of FDI have been traced to locate the position of Bangladesh. Secondary published data from governments and other significant agencies have been comprehensively studied to get the required data in completing the study

Metallographic Image Fusion

Image processing plays important role in manufacturing, aerospace, biomedical fields. To determine the classification of metallic sample, edge structure and images without blur are required. Instead of finding the noise kernel blur section of images can be removed by using multiple images fusion. There are different methods used for image fusions like average method, maxima, wavelet transform. For image fusion discrete wavelet transform is used. Image fusion improves the quality of image, data content. In this paper three images are used to fuse together. This images having standard size of 640x480 pixels. Image fusion improves the quality so that edge structure can be determined. According to edge structure the classification is done using ASTME standards

Comparison of Texture Features Used for Classification of Life Stages of Malaria Parasite

Malaria is a vector borne disease widely occurring at equatorial region. Even after decades of campaigning of malaria control, still today it is high mortality causing disease due to improper and late diagnosis. To prevent number of people getting affected by malaria, the diagnosis should be in early stage and accurate. This paper presents an automatic method for diagnosis of malaria parasite in the blood images. Image processing techniques are used for diagnosis of malaria parasite and to detect their stages. The diagnosis of parasite stages is done using features like statistical features and textural features of malaria parasite in blood images. This paper gives a comparison of the textural based features individually used and used in group together. The comparison is made by considering the accuracy, sensitivity, and specificity of the features for the same images in database

Interoperability Benefits and Challenges in Smart City Services: Blockchain as a Solution

The widespread usage of smart devices with various city-centric services speeds up and improves civic life, in contrast to growing privacy and security concerns. Security issues are exacerbated when e-government service providers trade their services within a centralised framework. Due to security concerns, city-centric centralised services are being converted to blockchain-based systems, which is a very time-consuming and challenging process. The interoperability of these blockchain-based systems is also more challenging due to protocol variances, an excessive amount of local transactions that raise scalability and rapidly occupy memory. In this paper, we have proposed a framework for interoperability across various blockchain-based smart city services. It also summarises how independent service providers might continue self-service choices (i.e., local transactions) without overloading the blockchain network and other organisations. A simulated interoperability network is used to show the network’s effectiveness. The experimental outcomes show the scalability and memory optimization of the blockchain network

Prediction of RNA Secondary Structure Using Butterfly Optimization Algorithm

Ribonucleic acid (RNA) structure is vital to its ability to function within the cell. The ability to predict RNA structure is essential to implementing new medications and understanding genetic illnesses. It is also important in synthetic and computational biology. All these functions are directly related to its secondary structure. Also prediction of RNA secondary structure process is the most significant step to determining the tertiary structure of RNA. On account of this, prediction of secondary structure of RNA is the crying topic in bioinformatics. In this research, we present the swarm-based metaheuristic Butterfly Optimization Algorithm (BOA) method for predicting the secondary structure of RNA. The main feather of the BOA is that it can conduct both local and global search simultaneously. According to the problem perspective, we have redesigned the operators of BOA to perform global and local search operations in different ways. We have followed a thermodynamic model for the selection of the stable secondary structure with minimum Gibbs free energy. Predicting the minimum free energy value we also developed an “Optimize” function to search the new optimize structure. This function increases the prediction efficiency, creating new stable structure and also decreases the time complexity of global searching procedure. We have used a public dataset to perform the prediction operation. To accuse our prediction efficiency, we have compared our outcomes to existing popular algorithms. The result shows that the proposed approach can predict secondary RNA structure better than other state-of-the-art algorithms

Outlier Based Fraud Detection System

Data mining has the vital task of Outlier detection which aims to detect an outlier from given datasets. The analysis or detection of outlier data is referred to as Outlier Mining. In Data mining, outlier detection is the identification of unusual or distant data records that might be require further investigation or analysis. This paper provides the data driven methods for various fraud detection systems based on literature review, fraudulent activities or cases and comparative research. Outlier detection is the technique which discovers such type of data from the given data set. Several techniques of outlier detection have been introduced which requires input parameter from the user. The goal of this proposed work is to partition the input data set into the number of clusters using K-NN algorithm. Then the clusters are given as an input to the outlier detection methods namely cluster based outlier algorithm and Local Outlier Factor Algorithm. The Performance evaluation of this algorithm confirms that our approach of finding local outliers can be practically implemented

Investigating superior performance by configuring bimetallic electrodes on fabric triboelectric nanogenerators (F-TENGs) for IoT enabled touch sensor applications

Fabric Triboelectric Nanogenerators (F-TENGs) are increasingly becoming more significant in wearable monitoring and beyond. These devices offer autonomous energy generation and sensing capabilities, by replacing conventional batteries in flexible wearables. Despite the substantial effort, however, achieving high output with optimal stability, durability, comfort, and washability poses substantial challenges, so we have yet to see any practical commercial uses of these materials. This study focuses on output and investigates the impacts of mono and bimetallic composite fabric electrode configurations on the output performance of F-TENGs. Our findings showcase the superiority of bimetallic configurations, particularly those incorporating Copper (Cu) with Nickel (Ni), over monometallic (Cu only) electrodes. These configurations demonstrate remarkable results, exhibiting a maximum instantaneous voltage, current, and power density of ∼ 199 V (a twofold increase compared to monometallic configurations), ∼22 μA (a threefold increase compared to monometallic configurations), and 2992 mW/m², respectively. Notably, these bimetallic configurations also exhibit exceptional flexibility, shape adaptability, structural integrity, washability, and mechanical stability. Furthermore, the integration of passive component-based power management circuits significantly enhances the performance capabilities of the F-TENGs, highlighting the essential role of power management circuits and electrode selection in optimizing F-TENGs. In addition, we have developed a complete IoT-enabled touch sensor system using CuNi-BEF EcoFlex layered F-TENGs for precise detection of soft and hard touches. This advanced system enhances robotic functionality, enabling nuanced touch understanding essential for precision tasks and fostering more intuitive human-machine interactions