Susceptibility Gene Prediction in Hereditary Disease Retinoblastoma

Nowadays Bioinformatics, proteomics and Genomics are the most intriguing sciences to understand the human genome and diseases. Several hereditary genetic diseases like Retinoblastoma involve a sequence of complex interactions between multiple biological processes. With this paper, genetic similarities were found within a selected group of patient\u27s DNA sequences through the use of signal processing tools. DNA, RNA and protein sequences have similarities in structure and function of the gene with their location. In this paper, we introduce a novel method using scoring matrix and wavelet windowing, for the integrative gene prediction. The proposed methods not only integrate multiple genomic data but can be used to predict gene location, gene mutation and genetic disorder from the multi-block genomic data. The performance was assessed by simulation

Removing Water Droplets In Medical Images Using Textured Spectral Analysis

Some disease in human body is caused by accumulation of water molecules at particular place in an organ or entering of unwanted toxic foreign bodies. This may be in large or in negligible amounts. Many methods like CT, MRI can detect these abnormalities if present in appreciable amount. But if present in small amount, human vision on these scanned images cannot detect them. The visual appearance of moving water droplet is very complex. Each water droplet refracts and reflects both scene radiance and atmospheric illumination toward an observer. Water droplets are randomly distributed in space and move at high velocities. Thus, water droplets produce spatial and temporal intensity fluctuations in videos. Modelling, analysing and detecting these unwanted water molecules may benefit avoiding the negligence of presence of disease. In this paper, the proposed system that detect water molecules in the images of affected organ like lungs automatically .The crux idea is to exploit textural properties of droplets or fluid. To perpetrate this idea, we are aiming to model these droplets by laws of physical science and reveal this through block processing of image pixels. For partially occluded image portions, information of the image may be used to be applied in transform like DCT, blending functions and retrieve it. For fully occluded image, image completion techniques can be used. By using this we can detect the droplets even if they are in micron size

Hybrid Framework on Automatic Detection and Recognition of Traffic Display board Signs

Automatically identifying traffic signs is a challenging and time-consuming process. As the academic community pays more attention to traditional algorithms for vision-based detection, tracking, and classification, three main criteria drive the investigation, they are detection, tracking, and classification. It is capable of performing detection and identification operations to minimize traffic accidents and move towards autonomous cars. A novel method proposed in this paper is based on moment invariants and neural networks for performing detection and recognition with classification, and it also includes automatic detection and identification of traffic signs and traffic board text that uses colour segmentation. Aside from the proposed structure, it is also required to identify the potential graphic road marking with text. This research article contains two algorithms, which are used to accurately classify the board text. The detection through image segmentation and recognition can be done by using the CNN algorithm. Finally, the classification is performed by the SVM framework. Therefore, the proposed framework will be very accurate and reliable with high efficiency, which has been proven in many big dataset applications. The proposed algorithm is tested with various datasets and provided good identification rate compared to the traditional algorithm.</jats:p

Ethereum and IOTA based Battery Management System with Internet of Vehicles

The era of Electric Vehicles (EVs) has influenced the very make and manufacture of vehicles resulting in low pollution and advanced battery life. On the other hand, the internet of things has also expanded allowing a number of devices to stay connected using the internet. Massive drawbacks faced by EVs today are the limitation in battery swapping and charging stations and limitation in the range of batteries used. This proposed paper aims to efficiently manage the best battery system apart from building the essential infrastructure. In some cases battery swapping option is also provided through other EV drivers or at registered stations. Hence a complete database of the EV network is required so that it is possible to swap and charge batteries successfully. An EV management using two blockchains as a data layer and network of the application is implemented in this work. The first step involves the development of a blockchain framework using Ethereum and the next step entails a direct acyclic graph. When integrated, these two methodologies prove to be an efficient platform that offers a viable solution for battery management in Electric Vehicles.</jats:p

Developing Dijik-Primbert Algorithm for Finding Unpredictable Paths over Time-Varying Networks

Abstract Cooperation among multiple unmanned vehicles is an intensely challenging topic from a theoretical and practical standpoint, with far reaching indications in scientific and commercial mission scenarios. The difficulty of time coordination for a rapid of multirotor UAVs includes predefined spatial paths according to mission necessities. With the solution proposed, cooperative control is accomplished in the presence of time-varying communication networks, as well as stringent temporal constraints, such as concurrent arrival at the desired final locations. The proposed explanation solves the time-coordination problem under the acceptance that the trajectory-generation and the path-following algorithms meeting convinced cohesion conditions are given. Communication is processed in unpredictable paths by the use of path following and directed communication graph. Dijik-Primbert algorithm for finding the shortest collision free paths is used to avoid and detect collision/congestion in unpredictable paths. Without collision detection, it doesn&apos;t seem agreeable to have collision avoidance because there wouldn&apos;t be everything to avoid. Dijikloyd algorithm is used for finding shortest paths in a weighted directed graph with positive and negative edges. Primloyd algorithm is used for finding shortest paths in a weighted undirected graph for conquering the complexity in matrix coding. In case of congestion or collision then the whole network is learned about it to all the communicators. Hence, communication is taken place in an unpredictable path in a secured manner. Keyword

Construction of LWCNN Framework and its Application to Pedestrian Detection with Segmentation Process

To solve the challenges in traffic object identification, fuzzification, and simplification in a real traffic environment, it is highly required to develop an automatic detection and classification technique for roads, automobiles, and pedestrians with multiple traffic objects inside the same framework. The proposed method has been evaluated on a database with complicated poses, motions, backgrounds, and lighting conditions for an urban scenario where pedestrians are not obstructed. The suggested CNN classifier has an FPR of less than that of the SVM classifier. Confirming the significance of automatically optimized features, the SVM classifier's accuracy is equal to that of the CNN. The proposed framework is integrated with the additional adaptive segmentation method to identify pedestrians more precisely than the conventional techniques. Additionally, the proposed lightweight feature mapping leads to faster calculation times and it has also been verified and tabulated in the results and discussion section.</jats:p

Review on Data Securing Techniques for Internet of Medical Things

In recent days Internet of Things (IOT) has grown up dramatically. It has wide range of applications. One of its applications is Health care system. IOT helps in managing and optimizing of healthcare system. Though it helps in all ways it also brings security problem in account. There is lot of privacy issues aroused due to IOT. In some cases it leads to risk the patient’s life. To overcome this issue we need an architecture named Internet of Medical Things (IOMT). In this paper we have discussed the problems faced by healthcare system and the authentication approaches used by Internet of Medical Things. Machine learning approaches are used to improvise the system performance.</jats:p

Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain

Multimedia data in various forms is now readily available because of the widespread usage of Internet technology. Unauthorized individuals abuse multimedia material, for which they should not have access to, by disseminating it over several web pages, to defraud the original copyright owners. Numerous patient records have been compromised during the surge in COVID-19 incidents. Adding a watermark to any medical or defense documents is recommended since it protects the integrity of the information. This proposed work is recognized as a new unique method since an innovative technique is being implemented. The resilience of the watermarked picture is quite crucial in the context of steganography. As a result, the emphasis of this research study is on the resilience of watermarked picture methods. Moreover, the two-stage authentication for watermarking is built with key generation in the section on robust improvement. The Fast Fourier transform (FFT) is used in the entire execution process of the suggested framework in order to make computing more straightforward. With the Singular Value Decomposition (SVD) accumulation of processes, the overall suggested architecture becomes more resilient and efficient. A numerous quality metrics are utilized to find out how well the created technique is performing in terms of evaluation. In addition, several signal processing attacks are used to assess the effectiveness of the watermarking strategy.</jats:p