BPAODV : Black Hole Prevention Using Trust Adhoc on Demand Distance Vector Routing Protocol

Ekta Gupta,Akhilesh Tiwari 보안공학연구지원센터 2014 International Journal of Future Generation Communi Vol.7 No.6

Now-a-days, wireless networks are playing vital role for facilitating communication between different entities for different purposes. In case of wireless networks, security aspect has now becomes a very major concern and most of the current researches are focusing in the same direction. This paper addresses the important problems relating to Black hole attack in adhoc network. During the research, a new and robust routing mechanism has been developed. Firstly, on the basis of Trust value and Credential value detection and prevention of Black hole attack has been performed. For assessing the performance of developed routing mechanism, experimentation has been done using NS2 simulator. Comparisons have been performed with AODV, Black hole AODV and results are as per the expectations.

A Rough Set Based Classification Model for the Generation of Decision Rules

Vinod Rampure,Akhilesh Tiwari 보안공학연구지원센터 2014 International Journal of Database Theory and Appli Vol.7 No.5

This paper introduces a very important classification aspect for the analysis of huge amount of data stored in databases and other repositories. Numerous classification models are available in the literature, to predict the class of objects whose class level is unknown. Literature reveals that most of the available models are not capable in handling imperfect data. In view of this, present paper proposes a new rough set based classification model to derive the classification (IF-THEN) rules. Furthermore, developed model has been applied to handle bank-loan applications database as either safe, unsafe or risky. However, proposed model can also be used for the analysis of data from other domains.

Demographic Risk Factors, Affected Anatomical Sites and Clinicopathological Profile for Oral Squamous Cell Carcinoma in a North Indian Population

Krishna, Akhilesh,Singh, R.K.,Singh, Shraddha,Verma, Pratima,Pal, U.S.,Tiwari, Sunita Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.16

Background: Oral cancer is a common form of cancer in India, particularly among men. About 95% are squamous cell carcinomas. Tobacco along with alcohol are regarded as the major risk factors. Objectives: (i) To determine associations of oral squamous cell carcinoma (OSCC) with respect to gender, age group, socioeconomic status and risk habits; (ii) To observe the distribution of affected oral anatomical sites and clinico-pathological profile in OSCC patients. Materials and Methods: This is an unmatched case-control study during period January 2012 to December 2013. Total of 471 confirmed OSCC patients and 556 control subjects were enrolled. Data on socio-demography, risk habits with duration and medical history were recorded. Results: There were significant associations between OSCC with middle age (41-50years; unadjusted OR=1.63, 95%CI=1.05-2.52, p=0.02) (51-60 years; unadjusted OR=1.79, 95%CI=1.15-2.79, p=0.009) and male subjects (unadjusted OR=2.49, 95%CI=1.89-3.27, p=0.0001). Cases with both habits of tobacco chewing and smoking were at a higher risk for OSCC than tobacco chewing alone (unadjusted OR=0.52, 95%CI=0.38-0.72, p=0.0001), duration of risk habits also emerged as a responsible factor for the development of carcinoma. The majority of patients were presented in well-differentiated carcinomas (39.9%). Prevalence of advance stages (TNM stage III, IV) was 23.4% and 18.3% respectively. The buccal mucosa was the most common (35.5%) affected oral site. Conclusions: In most Asian countries, especially India, there is an important need to initiate the national level public awareness programs to control and prevent oral cancer by screening for early diagnosis and support a tobacco free environment.

A Rough Set Based Feature Selection on KDD CUP 99 Data Set

Vinod Rampure,Akhilesh Tiwari 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.1

In the present era as internet is growing with exponential pace, computer security has become a critical issue. In recent times data mining and machine learning have been researched extensively for intrusion detection with the aim of improving the accuracy of detection classifier. KDD CUP’ 99 Data set is the most widely used dataset in research domain. Selecting important feature on the basis of rough set based feature selection approach have lead to a simplification of the problem, faster and more accurate detection rates. In this paper, we presented an efficient approach for detecting relevant features from the KDD CUP’99 Data set.

Genetic Based Hesitation Information Mining for Profitability Management

Prateek Shrivastava,Akhilesh Tiwari 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.6

Traditional Association Rule Mining has been extensively used to discover interesting rules or relationships between items in large databases but it has limitations that it solely deals with the items or products that are sold but avoids the items that are nearly sold. These nearly sold things carry hesitation data since customers are indecisive to shop for them. In this paper, with the help of vague set theory, we describe that item’s hesitation information is precious knowledge for the design of profitable selling strategies. This work proposed Genetic Algorithm based on evolution principles that has found its strong base in mining or maximize the rules for the items that customers mostly hesitate to purchase or has a high percentage of hesitation because of some reasons like price of an item, quality of an item, etc. Fitness function, crossover, and mutation are the main parameters involved in Genetic Algorithm which we used in our work. This work describes that if the reason of giving up the items is identified and resolved, we can easily remove this hesitation status of a customer and considering newly evolved rules as the interesting ones for boosting the sales of the item.

Exploring the Utility of Vague Concept for Uncertainty and Hesitation Management

Arun Kumar Singh,Akhilesh Tiwari 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12

In the realistic situation, there are many areas which contain imprecisely specified data. This imprecise data indicates the presence of vagueness, incompleteness and uncertainty which causes the problem during important decision-making task. The present paper focuses on the problem of mining important inference from supermarket basket data (in the presence of vagueness). The paper specifically studies the usefulness of vague set theory for the exploration of hesitation information and vague association rules. The hesitation information of an item plays a vital role in making selling strategies for the exhilaration of business. For this purpose, the vague set concept can be used as an important tool which can assist in the identification of hesitated item. The vague set theory with its two membership function provides more intuitive way to interact with the vague situation that causes the hesitation for any item. The effectiveness of the hesitated pattern and rule provide advanced decision-making capabilities that transform ‘almost sold’ items to ‘sold items’.

Rough Set and Genetic based Model for Extracting Weighted Association Rules

Shrikant Brajesh Sagar,Akhilesh Tiwari 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11

A novel approach for the efficient weighted association rule mining proposed in this present paper. The proposed approach reducts the transactional dataset (weighted) by utilizing the power of Rough Set theory. Furthermore, proposed approach acquires the benefit for weighted measures (w-support, w-confidence) for obtaining the most profitable weighted frequent itemsets and the Genetic Algorithm for the extracting the desired set of optimized weighted association rules. Experimental analysis of proposed approach has been done and observed that the approach works well and will be helpful in situation when there is a requirement for the consideration of extracting the best weighted association rules in decision-making process.

Metagenomics Analysis of Thrombus Samples Retrieved from Mechanical Thrombectomy

Vajpeyee Atulabh,Chauhan Puneet Singh,Pandey Swapnil,Tiwari Shivam,Yadav Lokendra Bahadur,Shroti Akhilesh Kumar,Vajpeyee Manisha 대한신경중재치료의학회 2021 Neurointervention Vol.16 No.1

Purpose: The purpose of this study was to assess the microbiota in middle cerebral artery thrombi retrieved in mechanical thrombectomy arising out of symptomatic carotid plaque within 6 hours of acute ischemic stroke. Thrombi were subjected to next-generation sequencing for a bacterial signature to determine their role in atherosclerosis.Materials and Methods: We included 4 human middle cerebral artery thrombus samples (all patients were male). The median age for the patients was 51±13.6 years. Patients enrolled in the study from Pacific Medical University and Hospital underwent mechanical thrombectomy in the stroke window period. All patients underwent brain magnetic resonance angiography (MRA) and circle of Willis and neck vessel MRA along with the standard stroke workup to establish stroke etiology. Only patients with symptomatic carotid stenosis and tandem lesions with ipsilateral middle cerebral artery occlusion were included in the study. Thrombus samples were collected, stored at –80 degrees, and subjected to metagenomics analysis.Results: Of the 4 patients undergoing thrombectomy for diagnosis with ischemic stroke, all thrombi recovered for bacterial DNA in qPCR were positive. More than 27 bacteria were present in the 4 thrombus samples. The majority of bacteria were <i>Lactobacillus, Stenotrophomonas, Pseudomonas, Staphylococcus</i>, and <i>Finegoldia</i>.Conclusion: Genesis of symptomatic atherosclerotic carotid plaque leading to thromboembolism could be either due to direct mechanisms like acidification and local inflammation of plaque milieu with lactobacillus, biofilm dispersion leading to inflammation like with pseudomonas fluorescence, or enterococci or indirect mechanisms like Toll 2 like signaling by gut microbiota.