A New Privacy Approach using Graph-EMD

CH.M.H.Saibaba,V. Uday Kumar,K. Praveenkumar,Debnath Bhattacharyya 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.7

Privacy is the word which can listen everywhere in the data mining for data preserving. It should be provided the security to the data in many ways. Privacy should be provided to the sensitive data and micro data. Hence more number of existing techniques has been introduced to provide sensitive data. Many third party service providers are showing interest to release the data which is collected for research purpose. Existing systems like k-anonymity, l-diversity and t-closeness are already existed but they can’t provide better privacy measures. Each existing method carries different types of problems. The t-closeness is the more flexible privacy model called (n,t)-closeness will provide the better privacy and usage. Proposed Closeness measures require Probability distribution that is assessed using Earth Mover’s Distance (EMD) measurement. In this paper, the graph based algorithm graph-EMD. Compare with tree-EMD, graph EMD performs more flexible. The number of unknown variables is reduced to O (N) from O (N2) of the original EMD. In this paper, with Graph-EMD is implemented and show the performance and efficiency.

An Association Rule hiding Algorithm for Privacy Preserving Data Mining

K. Srinivasa Rao,Venkata Naresh Mandhala,Debnath Bhattacharyya,Tai-hoon Kim 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.10

Privacy preserving data mining is a research area concerned with the privacy driven from personally identifiable information when considered for data mining. This paper addresses the privacy problem by considering the privacy and algorithmic requirements simultaneously. The objective of this paper is to implement an association rule hiding algorithm for privacy preserving data mining which would be efficient in providing confidentiality and improve the performance at the time when the database stores and retrieves huge amount of data. This paper compares the performance of proposed algorithm with the two existing algorithms namely ISL and DSR.

Spectrally resolved phase-shifting interference microscopy: technique based on optical coherence tomography for profiling a transparent film on a patterned substrate

Debnath, Sanjit K.,Kim, Seung-Woo,Kothiyal, Mahendra P.,Hariharan, Parameswaran The Optical Society 2010 Applied optics Vol.49 No.34

<P>Spectrally resolved white-light phase-shifting interference microscopy has been used for measurements of the thickness profile of a transparent thin-film layer deposited upon a patterned structure exhibiting steps and discontinuities. We describe a simple technique, using an approach based on spectrally resolved optical coherence tomography, that makes it possible to obtain directly a thickness profile along a line by inverse Fourier transformation of the complex spectral interference function.</P>

Interbody Fusion in Low Grade Lumbar Spondylolsithesis: Clinical Outcome Does Not Correalte with Slip Reduction and Neural Foraminal Dimension

Ujjwal K. Debnath,Atanu Chatterjee,Jeffrey R. McConnell,Deepak K. Jha,Tapas Chakraburtty 대한척추외과학회 2016 Asian Spine Journal Vol.10 No.2

Study Design: Prospective nonrandomized study. Purpose: To find a possible correlation between clinical outcome and extent of lumbar spondylolisthesis reduction. Overview of Literature: There is no consensus in the literature concerning whether a beneficial effect of reduction on outcome can be expected following reduction and surgical fusion for low grade lumbar spondylolisthesis. Methods: Forty six patients with a mean age of 37.5 years (age, 17–48 years) with isthmic spondylolisthesis underwent interbody fusion with cages with posterior instrumentation (TLIF). Clinical outcome was measured using visual analogue score (VAS) and Oswestry disability index (ODI). Foraminal dimensions and disc heights were measured in standard digital radiographs. These were analyzed at baseline and 1 year after surgery and changes were compared. Radiographic fusion was judged with computed tomography scans at 1 year. Results: Ninety percent of the patients had good or very good clinical results with fusion and instrumentation. Baseline and one-year postoperative mean VAS score was 6.33 (range, 5–8) and 0.76 (range, 0–3), respectively (p =0.004). Baseline and one-year postoperative, mean ODI score was 48 (range, 32–62) and 10 (range, 6–16), respectively (p <0.001). A mean spondylolisthesis slip of 32.1% was reduced to 6.7% at 1 year. Average anterior disc height, posterior disc height, vertical foraminal dimension), and foraminal) diameter improved from 9.8 to 11.7 mm (p =0.005), 4.5 to 5.8 mm (p =0.004), 11.3 to 12.6 mm (p =0.002), and 18.6 to 20.0 mm (p <0.001), respectively. The fusion rate was 75% with TLIF. There is no significant correlation between the improvements of ODI scores and the extent of slip reduction. Conclusions: Neural decompression and interbody fusion can significantly improve pain and disability but the clinical outcome does not correlate with radiological improvement in the neural foraminal dimension.

A Comparative Analysis on Contingence Structured Data Methodologies

Kavita K. Beldar,M. D. Gayakwad,Debnath Bhattacharyya,Tai-hoon Kim 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.5

Heterogeneous structured datas give rise to different kind of information caliber issues regarding real-world structured datas. Identical records also a one major issue. Strategy to eliminate identical records results in unsureness to select among true uniform records. Available methods based on expert observation and destructive decisions do not proved effective solution to such problems. This project solves these issues of identical records elimination will solve by de-duplication procedure as data accessing tasks with unsure outcomes. This project implements method to overcome unsureness of identical records that tightly conceal the proper instances of input and gives effective results for identical record.

Review on the Usage of Deep Learning Models in Multi-modal Sentiment Analysis

Naga Durga Saile K,Venkatramaphanikumar S,Venkata Krishna Kishore K,Debnath Bhattacharyya 대한전자공학회 2020 IEIE Transactions on Smart Processing & Computing Vol.9 No.6

In recent years, Sentiment Analysis is reshaping the business operations of many organizations by monitoring their brand reputation on social media and acquiring insights from customer"s feedback. Sentiment Analysis is one of the classification tools that identifies and extracts the subjective information of a product. This subjective information can be stated in different ways, such as feedback, discussions, blogs, podcasts, and video logs. This type of information generated by the empowered customers is known as user-generated content, which is traditionally in the form of words. The analysis was performed on a huge number of words using Natural Language Processing (NLP), which is a Unimodal Sentiment Analysis. With the rapid growth in the usage of the Internet, social media turned out to be a platform to share the thoughts of the individuals. This caused researchers to migrate from the traditional Unimodal analysis to Multimodal Sentiment Analysis, which includes video, audio, and images. This approach leverages the use of emotion and content and helps identify the scope and polarity of an individual’s sentiment. With the latest deep learning algorithms, Multimodal Sentiment Analysis can solve the problem of sarcasm identification. Multi-Modal Sentiment Analysis generates more accurate results compared to Uni Modal Sentiment Analysis. Therefore, this study aimed to define Sentiment Analysis and review the approaches and techniques in Sentiment Analysis from conventional Unimodal to Multimodal. In addition, this paper discusses a Multimodal Sentiment Analysis architecture using a transformers attention net.

Morpho-Physiological Parameters Associated with Iron Deficiency Chlorosis Resistance and Their Effect on Yield and Its Related Traits in Groundnut

Ishwar H. Boodi,Santosh K. Pattanashetti,Basavaraj D. Biradar,Gopalakrishna K. Naidu,Virupakshi P. Chimmad,Anand Kanatti,Manoj K. Debnath 한국작물학회 2016 Journal of crop science and biotechnology Vol.19 No.2

Iron deficiency chlorosis (IDC) causes a significant reduction in yield of groundnut grown in calcareous and alkaline soils in India. The main aim of the study was to assess genotypic differences for morpho-physiological parameters associated with IDC resistance across different stages and their effect on yield and its related traits. The factorial pot experiment was comprised of two major factors, i) soil-Fe status [normal-Fe, deficit-Fe], and ii) genotypes [five] with differential IDC response, constituting 10 treatments. They were assessed for five morpho-physiological parameters associated with IDC resistance across five crop growth stages and also yield and its related traits. Associations between these traits were also estimated. Under deficit-Fe conditions, IDC resistant genotypes recorded significantly lower visual chlorosis rating (VCR), higher SPAD values, active Fe, chlorophyll content, peroxidase activity, and high yield compared to susceptible ones. Between normal- to deficit-Fe soils, resistant compared to susceptible genotypes showed no change in VCR scores; a lower reduction in SPAD, chlorophyll, active Fe, peroxidase activity, and pod yield. Under deficit-Fe conditions, high yield among resistant genotypes could be attributed to higher seed weight, number of pods and haulm yield, while contrasting reduction in main stem height and number of primaries. The results indicate that for initial large-scale screening of groundnut genotypes for IDC resistance, SPAD values are most ideal while active Fe could be utilized for confirmation of identified lines.

Spectrally Resolved Phase Shifting Interferometry for Film Thickness and Surface Profiling

산짓 데브나스(S. K. Debnath),유준호(J. You),김승우(S-W. Kim) 한국정밀공학회 2008 한국정밀공학회 학술발표대회 논문집 Vol.2008 No.11월

Numerical investigation of detonation combustion wave propagation in pulse detonation combustor with nozzle

Debnath, Pinku,Pandey, K.M. Techno-Press 2020 Advances in aircraft and spacecraft science Vol.7 No.3

The exhaust nozzle serves back pressure of Pulse detonation combustor, so combustion chamber gets sufficient pressure for propulsion. In this context recent researches are focused on influence of nozzle effect on single cycle detonation wave propagation and propulsion performance of PDE. The effects of various nozzles like convergent-divergent nozzle, convergent nozzle, divergent nozzle and without nozzle at exit section of detonation tubes were computationally investigated to seek the desired propulsion performance. Further the effect of divergent nozzle length and half angle on detonation wave structure was analyzed. The simulations have been done using Ansys 14 Fluent platform. The LES turbulence model was used to simulate the combustion wave reacting flows in combustor with standard wall function. From these numerical simulations among four acquaint nozzles the highest thrust augmentation could be attained in divergent nozzle geometry and detonation wave propagation velocity eventually reaches to 1830 m/s, which is near about C-J velocity. Smaller the divergent nozzle half angle has a significant effect on faster detonation wave propagation.

Key Aggregate Based Homomorphic Encryption for Efficient Authentication for Secure Cloud Storage

K Ruth Ramya,D Naga Malleswari,Ch Radhika Rani,Debnath Bhattacharyya,Hye-jin Kim 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.11

Now a day’s data out sourcing is the main focusing term in real time cloud computing applications. Secure data outsourcing is another real time intellectual concept in cloud computing applications for proceeding efficient data transmission. Conventionally Attribute Based Encryption (ABE) performs efficient data security of data outsourcing in cloud. It performs effective data security based on attributes of uploaded data for storage. Attributes are key terms for converting plain file data to Meta (cipher) file, so every time attribute extraction is complexity in data storage in cloud for efficient security analysis. We describe new public cryptographic system which effects fixed size for efficient delegation of decryptions for cipher-texts. So in this paper we propose to KAE (Key Aggregate Encryption) for efficient data security for providing. The novelty is one can aggregate any set of secret keys and make them as complete with single key with power of all the keys been aggregated. We provide security analysis as a development in real time cloud applications for processing access control data delivery between users present in cloud. Our experimental results show efficient security with access control policies in data storage in cloud.