Jain S.K.,SDMCET |
Pellenq R.J.-M.,Massachusetts Institute of Technology |
Pellenq R.J.-M.,Aix - Marseille University |
Gubbins K.E.,North Carolina State University |
Peng X.,Beijing University of Chemical Technology
Langmuir | Year: 2017
Realistic molecular models of silica-templated CMK-1, CMK-3, and CMK-5 carbon materials have been developed by using carbon rods and carbon pipes that were obtained by adsorbing carbon in a model MCM-41 pore. The interactions between the carbon atoms with the silica matrix were described using the PN-Traz potential, and the interaction between the carbon atoms was calculated by the reactive empirical bond order (REBO) potential. Carbon rods and pipes with different thicknesses were obtained by changing the silica-carbon interaction strength, the temperature, and the chemical potential of carbon vapor adsorption. These equilibrium structures were further used to obtain the atomic models of CMK-1, CMK-3, and CMK-5 materials using the same symmetry as found in TEM pictures. These models are further refined and made more realistic by adding interconnections between the carbon rods and carbon pipes. We calculated the geometric pore size distribution of the different models of CMK-5 and found that the presence of interconnections results in some new features in the pore size distribution. Argon adsorption properties were investigated using GCMC simulations to characterize these materials at 77 K. We found that the presence of interconnection results greatly improves the agreement with available experimental data by shifting the capillary condensation to lower pressures. Adding interconnections also induces smoother adsorption/condensation isotherms, and desorption/evaporation curves show a sharp jump. These features reflex the complexity of the nanovoids in CMKs in terms of their pore morphology and topology. © 2017 American Chemical Society.
Desai P.,BVBCET |
Pujari J.,SDMCET |
Proceedings - 2016 2nd International Conference on Cognitive Computing and Information Processing, CCIP 2016 | Year: 2016
Digital era has produced large volume of images which created many challenges in computer science field to store, retrieve and manage images efficiently and effectively. Many techniques and algorithms have been proposed by different researcher to implement Content Based Image Retrieval (CBIR) systems. This paper discusses performance of different CBIR systems implemented using combined features colour, texture and shape as a prominent feature based on wavelet transform. Choice of the feature extraction technique used in image retrieval determines performance of CBIR systems. In this paper evaluation of performance of three CBIR systems based on wavelet decomposition using threshold, wavelet decomposition using morphology operators and wavelet decomposition using Local Binary Patterns (LBP) is done. Also the performance of these methods is compared with the existing methods SIMPLIcity and FIRM. Average precision is used to compare the performance of the implemented systems. Results indicate that performance of CBIR systems using wavelet decomposition give better results than simplicity and FIRM, also wavelet decomposition with Local Binary Patterns (LBP) exhibit better retrieval efficiency compared to wavelet decomposition using threshold and morphological operators. Theses CBIR systems have been tested on bench mark Wang's image database. Precision versus Recall graphs for each system shows the performance of respective systems. © 2016 IEEE.
International Conference on Advanced Computing and Communication Technologies, ACCT | Year: 2013
This paper discusses the various methods used to analyze the texture property of an image. Texture analysis is broadly classified into three categories: Pixel based, local feature based and Region based. Pixel based method uses grey level co occurrence matrices, difference histogram and energy measures and Local Binary Patterns(LBP) Local feature based method uses edges of local features and generalization of co occurrence matrices. Region based method uses region growing and topographic models. © 2013 IEEE.
Pujari J.D.,S.D.M.C.E.T. |
Yakkundimath R.,K.L.E.I.T. |
Byadgi A.S.,University of Agricultural science
Procedia Computer Science | Year: 2015
This paper presents a study on the image processing techniques used to identify and classify fungal disease symptoms affected on different agriculture/horticulture crops. Computers have been used to mechanization, automation, and to develop decision support system for taking strategic decision on the agricultural production and protection research. The plant disease diagnosis is limited by the human visual capabilities because most of the first symptoms are microscopic. As plant health monitoring is still carried out by humans due to the visual nature of the plant monitoring task, computer vision techniques seem to be well adapted. One of the areas considered here is the processing of images of disease affected agriculture/horticulture crops. The quantity and quality of plant products gets reduced by plant diseases. The goal is to detect, to identify, and to accurately quantify the first symptoms of diseases. Plant diseases are caused by bacteria, fungi, virus, nematodes, etc., of which fungi is the main disease causing organism. Focus has been done on the early detection of fungal disease based on the symptoms. © 2015 The Authors.
Rodd S.F.,Gogte Institute of Technology |
Kulkarni U.P.,SDMCET |
Yardi A.R.,Walchand College
Evolving Systems | Year: 2013
A recent trend in database performance tuning is towards self tuning for some of the important benefits like efficient use of resources, improved performance and low cost of ownership that the auto-tuning offers. Most modern database management systems (DBMS) have introduced several dynamically tunable parameters that enable the implementation of self tuning systems. An appropriate mix of various tuning parameters results in significant performance enhancement either in terms of response time of the queries or the overall throughput. The choice and extent of tuning of the available tuning parameters must be based on the impact of these parameters on the performance and also on the amount and type of workload the DBMS is subjected to. The tedious task of manual tuning and also non-availability of expert database administrators (DBAs), it is desirable to have a self tuning database system that not only relieves the DBA of the tedious task of manual tuning, but it also eliminates the need for an expert DBA. Thus, it reduces the total cost of ownership of the entire software system. A self tuning system also adapts well to the dynamic workload changes and also user loads during peak hours ensuring acceptable application response times. In this paper, a novel technique that combines learning ability of the artificial neural network and the ability of the fuzzy system to deal with imprecise inputs are employed to estimate the extent of tuning required. Furthermore, the estimated values are moderated based on knowledgebase built using experimental findings. The experimental results show significant performance improvement as compared to built in self tuning feature of the DBMS. © 2013 Springer-Verlag Berlin Heidelberg.
Biradar S.R.,SDMCET |
Jain G.,University of Rajasthan
Advances in Intelligent Systems and Computing | Year: 2015
With the evolution of wireless sensor network, the interests in their application have increased considerably. The architecture of the system differs with the application requirement and characteristics. Now days there are number of applications in which hierarchal based networks are highly in demand and key concept of such network is clustering. Some of the most wellknown hierarchical routing protocols like LEACH, SEP, TEEN, APTEEN and HEED are discussed in brief. These different conventional protocols have diverse strategies to select their cluster head but still have some limitations. Based on the limitations of these conventional models, a new approach has been proposed on the basis of ranks and weights assignment based protocol known as RWBP. This approach considers not only residual energy but also node’s degree and distance of nodes with base station. The node which has higher weight will be chosen as a cluster head. The objective of this approach is to have balance distribution of clusters, enhance lifetime and better efficiency than traditional protocols. The same approach is also applied for multi hop clustering i.e. multi hop RWBP in which the sensing field is divided into more number of areas and the area which lie farther from the base station is sending indirectly via intermediate cluster heads to the base station. The simulations are done in MATLAB with the network size 100x100 meters. The results of the proposed approach are resulting in better lifetime and stability region as compared to LEACH and SEP. © Springer International Publishing Switzerland 2015.
Bhagwat T.N.,SDMCET |
Shetty A.,National Institute of Technology Karnataka |
Catena | Year: 2011
Geomorphological characteristics can be treated as signatures of hydrological responses. Geomorphologic instantaneous unit hydrograph (GIUH) is of utmost use in planning watershed management programs on a broad scale in absence of hydrologic data. Fifth order basins from different agroclimatic zones in the Varada River basin were selected to understand the spatial variation in drainage characteristics. These sub-basins show significant differences in their morphometric properties such as basin area, drainage density, bifurcation ratio, circularity ratio, constant of channel maintenance etc. These differences reflect variation in the hydrological process and geomorphologic instantaneous unit hydrograph (GIUH) of different sub-basins and can be used to understand watershed management aspects. Fifth order sub-basin in the Southern Transition agroclimatic zone is potential for artificial recharge programs. Sub-basins in the Hilly non-forest zone on the north are ideal for surface water storage like tank development program while Forested Hilly zone on the north are environmentally sensitive and prone to erosion. © 2011 Elsevier B.V.
Danti V.N.,SDMCET |
Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 | Year: 2014
Face detection is primarily used for identity. Human face detection is the basic approach in applications such as human computer interface, video surveillance and is a prima facie for face recognition. This paper presents a method of detecting human faces irrespective of different ethnicities. Firstly skin and non skin regions are separated using a skin color model and focus on skin regions to detect faces. Our method uses heuristic approach to detect skin regions over the entire image. Experimental results shows that the proposed method detects faces among various facial expressions in color, different face orientations and various ethnic background and demonstrate successful face detection over the FERET benchmark database and acquired images. GUI based method is implemented which includes features such as detection of faces using webcam and count the number of faces detected. © 2014 IEEE.
Hemadri V.B.,SDMCET |
Communications in Computer and Information Science | Year: 2013
Use of technology in building human comforts and automation is growing fast, particularly in automobile industry. Safety of human being is the major concern in vehicle automation. Statistics shows that 20% of all the traffic accidents are due to diminished vigilance level of driver and hence use of technology in detecting drowsiness and alerting driver is of prime importance. In this paper, method for detection of drowsiness based on multidimensional facial features like eyelid movements and yawning is proposed. The geometrical features of mouth and eyelid movement are processed, in parallel to detect drowsiness. Harr classifiers are used to detect eyes and mouth region. Only the position of lower lip is selected to check for drowsiness as during yawn only lower lip is moved due to downward movement of lower jaw and position of the upper lip is fixed. Processing is done only on one of the eye to analyze attributes of eyelid movement in drowsiness, thus increasing the speed and reducing the false detection. Experimental results show that the algorithm can achieve a 80% performance for drowsiness detection under varying lighting conditions. © 2013 Springer-Verlag Berlin Heidelberg.
Nandibewoor A.,SDMCET |
Nandibewoor A.,Bharathiar University |
Adiver P.,SDMCET |
Hegadi R.,University of Solapur
Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 | Year: 2015
One of the emerging technologies that can be used to study the rate of vegetation is hyper spectral remote sensing. Hyper spectral satellite image of Western part of Indiana is adopted for our study. This data was further used to calculate different spectral indices. The study on spectral indices which show some significant changes with variation in Vegetation are presented in this paper. These spectral indices are used to monitor the vegetation. The spectral indices that are used are NDVI (normalized differential Vegetation index), SRPI (simple Ratio pigment index), red edge (Clrededge) and SG (VI green). All these spectral indices stated above showed significant changes with change in rate of chlorophyll and nitrogen Concentration. In the graph plotted for different wavelengths verses the reflectance values showed different Curves for change in the area. From this study it can be inferred that the hyper spectral data can also be used to find area containing dense forest, farm lands and bare land. Hence Satellite images can give lot of information that needs to be explored. © 2014 IEEE.