Homogenization is a process of achieving homogeneity through out a product by particle size modification. it is characterized into three major categories:-ultrasonic pressure homogenization, pressure homogenization mechanical homogenizer. Application of homogenization are diverse in food industry, chemical industry, pharmaceutical and chemical industry. Most important use of homogenization process in food industry is in milk homogenization. Selection criteria of homogenizers depends on particular application.

[1] www.wikipedia.com
[2] www.horiba.com
[3] http://www.nirosoavi.com/industries-applications/food-dairy-applications-homogenization.asp
[4] http://www.foodscience.uoguelph.ca/dairyedu/homogenization.html
[5] http://www.nirosoavi.com/industries-applications/homogenization-cosmetic-pharma-biotech.asp

Artificial Intelligence is both the intelligence of machine, electronics and the branch of Computer which aim to create it. AI has produced many significant and impressive products even at this early stage in its development. Although no one can predict the future in details, it is clear that computers with human-level intelligence would have a huge impact on our everyday lives and on the future course of civilization. Robot simply acts as an active agent whose environment is the physical world the active part rules out rocks, the artificial part rules out pure software agents or soft bots, whose environment consists of computer, file systems, database and networks. In this paper, the concepts of surgical robots, how robotically assisted brain surgery performed and their benefits are discussed. The first generations of surgical robots are already being installed in a number of operating rooms around the world. Compared with traditional surgery, the Robotically-assisted brain surgery is very useful.

 

Keywords: - Artificial Intelligence, Blood Brain Barrier, Computed Tomography, Gold Plated Electrode, Magnetic Resonance Imaging, Neural Networks, Diathermy.

[1] Natarajan P, Krishnan's, Natasha Sandeep Kenkre, Shraiya Nancy, Bhuvanesh Pratap Singh, "Tumor Detection using threshold operation in MRI Brain Images" , IEEE International Conference on Computational Intelligence and Computing Research, 2012.
[2] Prachi Gadpayleand, P.S. Mahajani, "Detection and Classification of Brain Tumor in MRI Images International Journal of Emerging Trends in Electrical and Electronics, IJETEE – ISSN: 2320-9569, Vol. 5, Issue. 1, July-2013.
[3] Mohd Fauzi Othman, Mohd Ariffanan, Mohd Basri, "Probabilistic Neural Network for Brain Tumor Classification", IEEE International Conference on Intelligent Systems, Modeling and Simulation, 2011.
[4] Stuart J.Russell and Peter Norvig, "Artificial Intelligence a Modern Approach", Pearson Education Series in Artificial Intelligence (2003)., 91(1a):106–15. (1985).
[5] T.J. Cartwright, Dr.Monisha E.Michlen, Dr.Juan Crestanello, sowmiya Createectomy, roboticwhipple surgery, Procedures University at Chicago, 1999-2002

This paper is devoted on impact of post harvest losses at stages of operations. The data balances of food supplied were analyzed and quantified to indicate poor processing and storage facilities in the study Zone Post harvest losses significantly endanger the livelihood of stakeholders and farmers across the value chain by reducing valuable income and profitability. Research has shown that reduction of just one percent in post harvest losses can lead a gain of 40 million USD annually.Government investment will lead to huge reduction in post harvest and increase income levels of actors across various agricultural value chain. Over the past half a century in developing countries with the exception of Ganye, Adamawa State-Nigeria had seen labor saving post harvest system engineering, adopted at unprecedented levels. Post harvest activities in the zone had created power bottle around threshing/shelling of maize, cowpea and groundnut but with adoption of post harvest machines, it had helped and enhance low unit cost with economic impact of 40 percent in the study. Information revealed from the study that farmers sale 20 percent of their grain due to problem of storage facilities. The general grain losses and waste responded by 52 percent of famers is 15-20 percent in the study zone. Quality of grain after post harvest operation with photo type machines is recorded fairly good.

 

Keyword: - Post harvest, lossess, grain, machines storage structures

[1] Skulskeya; L.v; Shirokova T.j (2010) Losses of agricultural products and productive resources in the Russian Federation, studies on Russian Economic Development November 2010,volume 21 issue 6, pp616-629
[2] Razak Owolabi, (2011) Post harvest losses in Nigeria"s Agriculture.New Agency of Nigeria NAN feature vol 5 No 171 2011 August.
[3] Jimoh Babatude (2013) Post harvest losses Arica losses food value at $4billion annually Nigeria Vanguard February 11,2013.
[4] Ahmed .D.A. (2013) Post harvest losses; making Nigerians farmers poorer 21 November 2013, Hits 530 post harvest losses.
[5] Patrick .I. (2013) Nigeria records over 40 percent post harvest losses sustainable food security in Nigeria (SUFOS) 19 November 2013.

The present study is a modest attempt to analyze the socio-economic impact of bank deposits. Deposit mobilization is an integral part of banking activity. Mobilization of savings through intensive deposit collection has been regarded as the major task of banking in India today. Acceptance of deposits is the primary function of Commercial Banks. As such deposit mobilization is one of the basic innovations in current Indian Banking activity. In this paper, an attempt is made to analyze the socio-economic impact of deposit mobilization. Three different types of deposits namely, term deposits, current deposit and savings deposit is considered for the study. The data required for the study has been collected from Union Bank of India Annual Reports. The data, thus collected have been properly classified and analyzed with the help of simple statistical parameters like Average, Indices etc and also the accounting technique i.e. Ratio Analysis. The results shows that, there has been a remarkable growth in mobilization of all kinds of deposits in Union Bank of India.

 

KEY WORDS: - Deposit Mobilization, Socio - Economic Impact.

[1] S. Venkateshan "An Empirical Approach to Deposit Mobilization of Commercial Banks in Tamil Nadu", IOSR Journal of Business and Management (IOSR-JBM) Vol. 4, Issue 2 September - October, 2012.
[2] V. S. Pai "Trends in the Indian Banking Industry: Analyses of Inter-Regional Trends in Deposits and Credits", The Icfaian Journal of Management Research January, 2006.
[3] Gagan Bihari Sahu and D. Rajasekhar "Urban Bias in the Flow of Funds and Deposit Mobilization: Evidence from Karnataka, India", Working paper No. 3 Centre for Social Studies, Veer Narmad South Gujarat University Campus Udhna - Magdalla, SURAT, Gujrat State, September, 2005.
[4] Dr. B. Ramchandra Reddy and Dr. Yuvaraja Reddy "Financial Performance of SBI: An Analysis", Journal of Banking Finance May, 2005.
[5] Avneet Kaur "An empirical study on the performance evaluation of public sector Banks in India", International Journal of Marketing, Financial Services and Management Research Vol. 1 Issue 11, November, 2012

The nonlinear absorption and refraction indices for 2,3-Diaminopyridine solution were measured using open-and closed- aperture z-scan techniques, with continuous wave (cw) irradiation. Furthermore, diffraction rings pattern as a result of nonlinear refraction was observed. The effect of concentration, wavelength and laser intensity on the nonlinear absorption, nonlinear refraction and diffraction rings are studied experimentally. It is found that the nonlinear refraction and absorption indexes in order of 10-8 cm2/W and10-3 cm/W, respectively. We suggested an opportunity to form a new nonlinear-optical media for nonlinear optical application.

 

Keywords: - nonlinear refractive index, nonlinear materials, Z-scan, self- diffraction.

[1] K. Jamshidi-Ghaleh, S. Salmani, M. Hossain Majles Ara , Nonlinear responses and optical limiting behavior of fast green FCF dye under a low power CW He–Ne laser irradiation, Optics Communications, 271(2) , 2007, 551-554.

[2] M. D. Zidan, A. W. Allaf, Z. Ajji and A. Allahham, Optical limiting behavior of Sudan III dye doped polymer, Optics and Laser Technology 42( 3), 2010, 531-533.
[3] S. J. Mathews, S. Chaitanya Kumar, L. Giribabu and S. Venugopal Rao, Large third-order optical nonlinearity and optical limiting in symmetric and unsymmetrical phthalocyanines studied using Z-scan Optics Commu. 280(1), 2007, 206-212.
[4] Z. Fryad Henari and C. Seamus, Non-linear optical properties and all optical switching of Congo red in solution ,Optik 123(8), 2012, 711-714.
[5] P. N. Prasad and D. J. Williams, Introduction to Nonlinear Optical Effects in Organic Molecules and Polymers,Wiley, NewYork,1991.

The Rice milling is the process that helps in removal of hulls and bran's from paddy grains to produce polished rice. Rice is rich in genetic diversity with thousands of varieties grown throughout the world. Rice has been one of man's most important foods. Today, this unique grain helps sustain two-thirds of the world's population. It is life for thousands of millions of people. It is deeply embedded in the cultural heritage of their societies. About four-fifths of the world's rice are produced by small-scale farmers and are consumed locally.Milling is the process wherein the rice grain is transformed into a form suitable for human consumption, therefore, has to be done with utmost care to prevent breakage of the kernel and improve the recovery.the present paper lucidly explains ricce milling process and its importance

[1] http://www.rice-trade.com/milling.html

[2] b/index.php/rice-millingwww.knowledgebank.irri.org/rk

[3] b/index.php/rice-millingwww.knowledgebank.irri.org/rk

[4] http://www.knowledgebank.irri.org/rkb/index.php/rice-milling/commercial-rice-milling-systems/husking

[5] http://www.knowledgebank.irri.org/rkb/index.php/rice-milling/commercial-rice-milling-systems/paddy-pre-cleaner

In areas such as computer vision and image processing, image segmentation has been and still is a relevant research area due to its wide spread usage and application. The traditional segmentation technique which is used in gray-scale mathematical morphology is watershed transform. Region Growing is an approach to image segmentation in which neighbouring pixels are examined and added to a region class if no edges are detected. This process is iterated for each boundary pixel in the region. In this paper, we made enhancements in watershed algorithm and region growing algorithm for image and color segmentation. The new enhanced algorithm is implemented in MATLAB and results are compared with the existing technique in the form of visualization and on the basis of Liu's F- factor values.

 

Keywords: - Color Segmentation, Image Segmentation, Watershed, Liu's F- factor, region growing

[1] Amanpreet Kaur Bhogal et al," Color Image Segmentation Based On Color And Texture properties", INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 8, Issue No. 2, 152 – 156

[2] D.Sasirekha et al," Enhanced Techniques for PDF Image Segmentation and Text Extraction", (IJCSIS) International Journal of Computer Science and Information Security, Vol. 10, No. 9, September 2012

[3] Slawo Wesolkowski and Paul Fieguth," Color Image Segmentation Using Vector Angle-Based Region Growing"

[4] Mr. Salem Saleh Al-amri et al," IMAGE SEGMENTATION BY USING EDGE DETECTION", International Journal on Computer Science and Engineering Vol. 02, No. 03, 2010, 804-807

[5] Om Prakash Verma et al," A Simple Single Seeded Region Growing Algorithm for Color Image Segmentation using Adaptive Thresholding", 2011 International Conference on Communication Systems and Network Technologies

This paper concentrates on the identification of Multiple Input Multiple Output (MIMO) system by means of a hybrid-learning rule, which combines the back propagation and the Least Mean Squared (LMS) to identify parameters. We construct a neuro fuzzy model structure, and generate the membership function from the measured data. The MIMO system model is represented as a set of coupled input-output MISO models of the Takagi- Sugeno type. Neuro fuzzy model of the system structure is incorporated easily in the structure of the model. The simulation is used to implement a MIMO spacecraft system using Matlab for moment_yaw, moment_pitch, and moment_roll as input, and velocity in inertial axis as output. Experimental results are given to show the effectiveness of this Adaptive Neuro Fuzzy System (ANFIS) model. This paper attempts to present a neural inverse control design framework for a class of nonlinear multiple-input multiple-output (MIMO) system with uncertainties. This research effort is motivated by the following considerations: (a) An appropriate reference model that accurately represents the desired system dynamics is usually assumed to exist and to be available, and yet in reality this is not the case often times; (b) In real world applications, there are many cases where controls are constrained within a physically allowable range, which presents another layer of difficulties to directly apply the reference model based inverse control; (c) It is difficult to consider optimal control even for the reference model as in general the analytic solution to the optimal control problem is not available. The simulation study has been focused on the identification of Multiple Input, Single Output (MISO) non-linear complex systems.

 

Index Terms: - Real Time workshop, Neuro Fuzzy Controllers, Adaptive Neuro Fuzzy Inference System (ANFIS)

[1] Ruiyun Qi, Limeng Zhu and Bin Jiang," Fault-Tolerant Reconfigurable Control For MIMO Systems Using OnLine Fuzzy Identification ", International Journal of Innovative Computing, Information and Control ICIC International 2013 ISSN 1349-4198Volume 9, Number 10, October 2013 pp. 3915–3928

[2] Wuhan, Hubei, China, " Modelling, Identification & Control (ICMIC)", 2012 Proceedings of International Conference on June 2012 ,467 - 471 .
[3] A. Gegov, "Multilayer fuzzy control of multivariable systems by active decomposition". Int. Journal of intelligent systems, 12, 1997.
[4] Xiao-Jun Zeng, Madan G. Singh," Fuzzy Bounded Least Squares Method for Systems Identification" March 31 - April 02, 1996, University of Manchester Institute of Science and Technology
[5] Carmona, P. Castro, J.L. Zurita, J.M. "FRIWE: Fuzzy Rule Identification With Exceptions", IEEE Transactions on Fuzzy Systems, Publication Date: Feb. 2004 on page(s): 140- 151Volume: 12, Issue