MAC layer based cross-layer solutions for VANET routing: A review

Nigam, Ujjwal,Silakari, Sanjay International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.spc12

Vehicular Ad hoc Networks (VANET's) are gaining popularity in research community with every passing year due to the key role they play in Intelligent Transportation System. Their primary objective is to provide safety, but their potential to offer a variety of user-oriented services makes them more attractive. The biggest challenge in providing all these services is the inherent characteristics of VANET itself such as highly dynamic topology due to which maintaining continuous communication among vehicles is extremely difficult. Here comes the importance of routing solutions which traditionally are designed using strict layered architecture but fail to address stringent QoS requirements. The paradigm of cross-layer design for routing has shown remarkable performance improvements. This paper aims to highlight routing challenges in VANET, limitations of single-layer solutions and presents a survey of cross-layer routing solutions that utilize the information from the MAC layer to improve routing performance in VANET.

MAC layer based cross-layer solutions for VANET routing: A review

Nigam, Ujjwal,Silakari, Sanjay International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.12

Vehicular Ad hoc Networks (VANET's) are gaining popularity in research community with every passing year due to the key role they play in Intelligent Transportation System. Their primary objective is to provide safety, but their potential to offer a variety of user-oriented services makes them more attractive. The biggest challenge in providing all these services is the inherent characteristics of VANET itself such as highly dynamic topology due to which maintaining continuous communication among vehicles is extremely difficult. Here comes the importance of routing solutions which traditionally are designed using strict layered architecture but fail to address stringent QoS requirements. The paradigm of cross-layer design for routing has shown remarkable performance improvements. This paper aims to highlight routing challenges in VANET, limitations of single-layer solutions and presents a survey of cross-layer routing solutions that utilize the information from the MAC layer to improve routing performance in VANET.

Utility of Parametric Curves in Image Processing Applications

Manish Dixit,Sanjay Silakari 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.7

Image Processing is dealing with images containing lots of points. By Interpolation of these points to form different curves are taken under consideration in this paper. The curve modification and fitting in image processing can use Bezier Curve applications in various ways and by modifying these curves better result are generated. Bezier curve and its applications have vast scope for research in image processing like curve fitting algorithm, pattern recognition and computer aided geometric design. Application of Bezier curve are widely implemented in face detection, smile detection, hand writing and digit recognition which give wide view of Bezier curves. In this paper we go through various concepts and its application which can be used in image processing for providing extra edge in this field.

Synthesis and pharmacological evaluation of polyfunctional benzimidazole-NSAID chimeric molecules combining antiinflammatory, immunomodulatory and antioxidant activities

Yogita Bansal,Om Silakari 대한약학회 2014 Archives of Pharmacal Research Vol.37 No.11

Polyfunctional compounds comprise a novelclass of therapeutic agents for treatment of multifactorialdiseases. The present study reports a series of benzimidazole—non-steroidal anti-inflammatory drugs (NSAIDs)conjugates (1–10) as novel polyfunctional compoundssynthesized in the presence of orthophosphoric acid. Thecompounds were evaluated for anti-inflammatory (carageenan-induced paw edema model), immunomodulatory(direct haemagglutination test and carbon clearance indexmodels), antioxidant (in vitro and in vivo) and for ulcerogeniceffects. Each of the compound has retained the antiinflammatoryactivity of the corresponding parent NSAIDwhile exhibiting significantly reduced gastric ulcers. Additionally, the compounds are found to possess potentimmunostimulatory and antioxidant activities. The compound8 was maximally potent (antibody titre value358.4 ± 140.21, carbon clearance index 0.053 ± 0.002and antioxidant EC50 value 0.03 ± 0.006). These compounds,exhibiting such multiple pharmacological activities,can be taken as lead for the development of potentdrugs for the treatment of chronic multifactorial diseasesinvolving inflammation, immune system modulation andoxidative stress such as cancers. The Lipinski’s parameterssuggested the compounds to be bear drug like properties.

Cyber Attack Detection System based on Improved Support Vector Machine

Shailendra Singh,Sanjay Silakari 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.9

This paper presents a novel cyber attack classification approach using improved Support Vector Machine (iSVM) by modifying Gaussian kernel. The Support Vector Machine (SVM) is based on machine learning technique known to perform well at various pattern recognition tasks; such as image classification, text categorization and handwritten character recognition. The cyber attack detection is basically a pattern classification problem, in which classification of normal pattern is done from the abnormal pattern (attack). Although, traditional SVM is better classifier in terms of fast training, scalable and generalization capability. Performance of traditional SVM is enhanced in this work by modifying Gaussian kernel to enlarge the spatial resolution around the margin by a conformal mapping, so that the separability between attack classes is increased. It is based on the Riemannian geometrical structure induced by the kernel function. In the proposed method, class specific Cyber Attack Detection System which combines feature reduction technique and improved support vector machine classifier. This technique has two phases, in the first phase we reduced the redundant features of the original KDDCUP2009 dataset by Generalized Discriminant Analysis (GDA). In the second phase we used improved Support Vector Machine (iSVM) classifier to classify the reduced dataset obtained from first phase. Result shows that iSVM gives 100% detection accuracy for Normal and Denial of Service (DOS) classes and comparable to false alarm rate, training, and testing times.

Face Recognition Using Approximated Bezier Curve and Supervised Learning Approach

Manish Dixit,Sanjay Silakari 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.4

Bezier curve are very strong for variety of application. Specifically in image processing it applies to object recognition, face recognition, and human gait recognition. It also works on fingerprint and other biometric system recognition. This paper presents a work to recognize digital images of human frontal faces using the approximated Bezier curve and an intelligent process of learning using neural network. The main structural features of faces like eye, eyebrows, nose, lips, and Face boundaries are extracted and using minimum of these features face is recognized efficiently.

Automation of Segmentation of MRI Images in the Presence of Intensity Inhomogeneity by the Application of Probabilistic Neural Network

Manish Dixit,Amit Singh Chauhan,Sanjay Silakari 보안공학연구지원센터 2015 International Journal of Bio-Science and Bio-Techn Vol.7 No.4

This paper presents a different approach by employing probabilistic neural network (PNN) with level set method for segmentation of intensity inhomogeneous magnetic resonance images (MRI). The input image is classified by PNN, and initialise the image with initial zero level set contours. A cascade approach is used in which after processing image by PNN, the output of PNN is fed into Level Set Method (LSM) Algorithm. The LSM is usedto perform the segmentation and to estimate bias field.

An Exhaustive Survey on Nature Inspired Optimization Algorithms

Manish Dixit,Nikita Upadhyay,Sanjay Silakari 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.4

Human being are greatly inspired by nature. Nature has the ability to solve very complex problems in its own distinctive way. The problems around us are becoming more and more complex in the real time and at the same instance our mother nature is guiding us to solve these natural problems. Nature gives some of the logical and effective ways to find solution to these problems. Nature acts as an optimizer for solving the complex problems. In this paper, the algorithms which are discussed imitate the processes running in nature. And due to this these process are named as “Nature Inspired Algorithms”. The algorithms inspired from human body and its working and the algorithms inspired from the working of groups of social agents like ants, bees, and insects are the two classes of solving such Problems. This emerging new era is highly unexplored young for the research. This paper proposes the high scope for the development of new, better and efficient techniques and application in this area.