This emulation supports online condition monitoring to monitor and diagnosis of electrical equipment in real time. Abstract: Hydrological cycle is inherent of climate processes with lot of interactions thereby making the system to be complex. The modeling of hydrological cycle to simulate the water resource has been well researched for more than a decade. In the recent past the studies are initiated to capture the influence of climate parameters on the hydrological cycle. One of the major inferences from the above is that,influence of climate parameters in arid and semiarid climatic region is not very significant.
To understand the generalized behavior stated by the research community on arid regions, in this research paper we explored the inflow database of stanely reservoir, Tamilnadu. A modeling framework has been developed that predicts the reservoir inflow considering the future climatic scenarios. Keywords: hydrological cycle, reservoir inflow, prediction, climate variables. Abstract: Steel framed buildings are flexible, ductile and light weight compared to that of reinforced concrete buildings.
Intense research had been conducted in the last decades regardingthe fatigue and ductility behaviour of structural steel beam. Prismatic beams are the beams with uniform cross-section in the entire span of the beam. Non-prismatic beams are used to increase the efficiency of the beam, by increasing the strength per unit mass than that of prismatic beam. In this study, the load-deformation, stress-strain analysis, the fatigue and ductile behaviour of non-prismatic steel beams with hunched and tapered ends was compared with prismatic beam for different loading condition.
The beams were subjected to static loading conditions during analysis. Keywords: Prismatic beam, non-prismatic beam, stress-strain analysis, static loading, fatigue and ductile behavior. Abstract: Fuzzy Sliding model control FSMC has been suggested to control hydraulic actuated nonlinear active suspension using full car model. The development of efficient classical controller for active suspension has been difficult due to complex nature of full car mathematical model, nonlinear effect in suspension and unpredictable behaviour of hydraulic actuator.
The sliding mode controller SMC has an ability to handle uncertain parameter, nonlinearity and complex mathematical model of dynamic system. Chattering phenomenon remains to be the only obstacle for nonlinear sliding mode controller which can be eliminated by integrating fuzzy logic with sliding mode control.
In this work, fuzzy sliding mode controller proposed for hydraulic actuated nonlinear active suspension to handle nonlinearity, uncertainty in parameter variation and chattering effect. The simulation is carried out using Seven degree of freedom based full car model to measure body displacement, acceleration, roll and pitch angle of vehicle. The response of full car model confirms the feasibility of fuzzy sliding mode controller for hydraulic actuated active suspension.
Keywords: Fuzzy sliding mode control, Vibration control, Active suspension, Actuator dynamics. Abstract: The continuous increase in population and the urbanization resulted in over exploitation of natural resources which directly affects the land use pattern and use of water.
ABB Measurement & Analytics - instrumentation and analyzer technology
A study was framed to assess the changes in the land and water resources management in the Udumalpet taluk region during The changes in land use pattern, growth and reduction in surface water body area in the region was analysed using ArcGIS 9. The land use pattern analysis results showed that the cultivable land and build-up land level increased during the study period , and a trend of decrease in water holding structures and uncultivable land area. The growth of area with buildings was The area of surface water bodies at the urban and rural areas were declined by 7. The portable water demand forecast analysis showed that the portable water requirement in would be 2.
Keywords: Land use pattern change, land cover change, Urbanization, portable water requirement.
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Abstract: The expanded living spaces in provincial and urban territory require great quality water dissemination administration framework. In this way, there is a basic prerequisite to outline a programmed water supply framework to accomplish rise to measure of water conveyance to every one of the natural surroundings. Internet of things, another idea is employed as a part of the planned framework for programmed water circulation and fault identification. The key idea of this paper is to plan a cost proficient framework to accomplish better water supply by regular supervising and furthermore controlling it from a central server to eliminate problems in the supply of water to the habitats.
The proposed design utilizes an Arduino as minicomputer, water flow sensor, and solenoid valves. Arduino is utilized to control the valve and flow meter. The purchase of water should be possible by utilizing cayenne application in which the requisite of water for any of the habitats can be fixed. It depends on the Wiz net W Ethernet chip datasheet. The proposed design takes care of the issue of overflow, over utilization, acquiring of water and makes an appropriate distribution.
Abstract: Homotopy analysis method is attempted to evaluate the hypothalamo- pituitary - adrenocortical mathematical model. The effects of hypothalamo- pituitary adrenocortical,corticotrophin releasing hormone, denocorticotropin, are discussed in this work. Keywords: hypothalamo- pituitary -adrenocortical, corticotrophin, adenocorticotropin. Abstract: Homotopy perturbation method is attempted to evaluate the cross-diffusion forest boundary dynamics.
The effects of exothermic and endothermic parameters are are discussed. Keywords: Homotopy perturbation method, forest boundary dynamics. Abstract: he core objective of the work is to propose a distributed environment based lazy learning Associative Classification AC. Associative Classification is a hybrid version of data mining tasks which integrated both Association Rule Mining ARM and Classification technique to construct accurate classifier. Unfortunately, the AC used for learning these classifier are less popular in real time for building application due to its higher computation time complexity and memory constraints in large volume of datasets.
To overcome such downsides, we proposed a distributed and parallel computing for lazy learning associative classification for accelerating algorithm performance by projecting the testing instances with large training datasets. In this work, we have implemented MapReduce based algorithms which reduce the computation by eliminates the need of constructing generalized classifier. It also well handled rare rules and generated institutive rules. The proposed algorithm may be suitable in area such as network intrusion detection, fraud detection, crowd analysis, rare disease prediction and crime analysis.
Our algorithm has been compared with well known existing algorithms in relations of precision and running time. The experiments result has strengthened the proposed algorithm well handle the rare rules in distributed environment and is making better performance even the size of the datasets is huge. Abstract: Modern techniques such as predictive analytics have gained a lot of research attraction these days.
In the competitive world, it is important for a business people to predict the pulse of customer to shine. With predictive analytics, it is possible to see what a customer will buy next.
Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals
The goal is to increase the profit earned by a company. In this paper, various hypothesis tests have been conducted for analysing the purchases of a customer. Initially, the purchases have been analysed by grouping the purchases gender wise and by analysing what group of people buy more products. It also finds out which group prefers for promotion codes and discounts and for what type of products they preferred more.
In which store, the sales of products are more and in which state, the sales are maximum. Based on this, techniques for improving the sales of a product is suggested. Abstract: In India, the number of people applying for the loans gets increased for various reasons in recent years. The bank employees are not able to analyse or predict whether the customer can payback the amount or not good customer or bad customer for the given interest rate.
The aim of this paper is to find the nature of the client applying for the personal loan. An exploratory data analysis technique is used to deal with this problem. The result of the analysis shows that short term loans are preferred by majority of the clients and the clients majorly apply loans for debt consolidation. Abstract: Heart disease is frightening the people around the world and in some countries it is the number one disease which leads to death.
Biomedical research efforts help to prevent and treat heart disease in a better way. Handling large amount of data is often very tedious with traditional methods which lead into problems, particularly in high level of complexity and vagueness factors. Mining frequent patterns from large databases has emerged as an important area in data mining research and knowledge discovery community; this also contributes so much to health care domain. This heart prediction system helps to predict heart related problems at an early stage.
The proposed system predicts heart related issues of a person based on questions and the answers given to the prediction system. To have better results in minimum time duration an Enhanced Apriori algorithm was introduced which is an improvement of Apriori algorithm.
The experimental results proved that the proposed approach performs faster and memory efficient with more number of patterns. Abstract: In recent times, teaching and learning methods have a direct impact on students' learning experiences. Blended learning is a combination of face-to-face and online delivery methods which influences students' perceptions on the learning environments to a great extent. Learning analytics is a growing trend at all levels of education. Relevant data has been collected from undergraduate and postgraduate students who are exposed to a blended learning environment while learning programming subjects.
Learning analytics has been applied on the collected data.
It can be inferred from the results that the blended learning approach is more beneficial for students who are skilled in using certain computer programs and applications. The study results also provide new insights into the student preferences for learning in such knowledge sharing collaborative environments. Keywords: Blended learning, Learning analytics, Collaboration, Knowledge sharing. In highways the road safety and travel comfort are accomplished through vehicle-to-vehicle and vehicle-to-roadside unit communications.
A major issue in safety application is to diffuse emergency message to all the other vehicles immediately without redundancy. There are number of works have been proposed to disseminate the emergency message, but those works suffer from delay and bandwidth consumption due to redundancy. This paper considers vehicle-to-vehicle communication for emergency message diffusion without the assistance of roadside units.