In current years, because of financial growth, number of cars on the roads has increased. It’s not an easy task to find parking space today. Parking vehicle problem causes waste of time and fuel consumption. Intelligent Parking is the solution to this problem where the driver gets an alert about unoccupied parking which saves the drivers time and increases the efficiency of fuel for automobiles. With the enhancement in modernization, parking has also end up a completely serious difficulty. This paper describes the various Parking techniques with the usage of sensor networks. When so ever a vehicle is placed into a parking slot, its information will be shared with the parking management sensors. Applications of wi-fi sensor networks have made the arena a smooth place to live.

An issue of finding parking space is a serious concern in some locations, especially shopping complexes, hospitals, buildings, malls and other premises requires large parking space for vehicles. The parking scenario becomes worst on special occasions like festivals, fiesta and weekends. The conventional developed techniques using installation of sensors in parking zone for parking vehicles becomes costly. Therefore, a reliable method is required that works for long time to manage traffic congestion that occurs while searching for parking space. In this paper, a novel method is proposed for parking vehicles using metaheuristic approaches. The developed approach provides consistent results considering two parameters, parking efficiency and parking space search time. The parking efficiency is improved and parking space search time is reduced using the Firefly Algorithm (FA) and Feed Forward Back Propagation Neural Network (NN) approach.

Vehicular Ad-hoc Network (VANET) aims at transmitting crucial information regarding road and network traffic conditions and other information pertaining to the network on timely basis. It thrives to enhance the present protection standards and efficiency of the network. The fundamental use of vehicular ad-hoc networks is in relation with traffic conditions and other applications related to road safety. This paper describes essential utility of vehicular ad-hoc networks associated with traffic conditions and road safety. Whenever the emergency messages need to be sent to the vehicles, it is of prime importance that vehicles are connected all the times. If the connectivity is not given importance, then the main objective of disseminating the important information to vehicles is not achieved.

Management of Vehicle Parking is one of the most critical issues in Wireless Sensor Network. Handling the parking of vehicles is manual almost everywhere and require lots of efforts to manage a vehicle parking. The hassle of parking cars causes wastage of time and also consumes fuel. This paper introduces the concept of Artificial Intelligence within the parking enhancement. This paper provides a glimpse of future aspects of vehicle parking management, utilizing Artificial Intelligence. The evaluation of proposed structure is based on the Space Utilization Factor and Delay for parking.

This paper aims to find out the functionality and mechanism and procedure of various brainwaves produced in a human and how non-invasive EEGs are used to read electrical activity that takes place inside our brain. This information can be further used for EEG signal classification for real time neuro marketing applications. In this paper we are going to compare the efficiency of the results of using various algorithms required for signal classification. All this is done by making use of the tool EEGLAB which is implemented in MATLAB. EEGLAB version 14.1.1 was used for the same. The dataset used was the default dataset provided by EEGLAB. Various documentations provided by Swartz Center for Computational Neuroscience were read and the directions to use the tool were followed as per the documentation provided by them.

The Economic Meltdown was general economic decline observed in world markets around the end of the first decade of 21st century. Around the world stock markets had fallen, large financial institutions had collapsed or been bought out, and governments even the wealthiest nations have had to come up with rescue packages to bail out their financial systems. Current statistics demonstrates with the purpose of practically all the globe economies had been stirred by the recession though the large industrialized economies may have reached bottom and are now commencing towards resurgence. Banking Industry of India is inherently strong, operationally assorted and demonstrates competence and flexibility besides being sensitive to India's economic aims of developing a market oriented, industrious and viable economy. The amount of banking assets in India totalled US$ 1.8 trillion in FY 13 and is estimated to touch US$ 28.5 trillion in FY 25. Bank deposits have grown at a compound annual growth rate (CAGR) of 21.2 per cent over FY 06–13. In FY 13, total deposits were US$ 1, 274.3 billion. The revenue of Indian banks increased from US$ 11.8 billion to US$ 46.9 billion over the period 2001–2010. Profit after tax also arrived at US$ 12 billion from US$ 1.4 billion in this period. In the era of globalization, it would be rather idealistic to ascertain any industry in desolation, unaffected by the changes in the larger economic scenario. Financial crisis and economic recessions may likely curtail demand for banking services and the supply of quality banking services. The present paper will focus on the impact of economic meltdown on Indian banking industry, the underlying opportunities for the future growth and will also try to analyze some practical solutions to the problem.

In the fast moving world and changing scenario of market (Business) there is need for improving and updating at every point of time, in order to obtain maximum and exact output companies need detailed data to work on hence this paper involves researching on increasing the efficiency so as to obtain better and exact prediction for the product to be used. The SAS System of software provides a wide variety of tools for analyzing market research data. Everything from simple summary analysis to advanced statistical and graphical techniques is available. Users holding different levels of expertise in both software and market research methodologies benefit from these tools. This project briefly discusses some of the methods available in the SAS System and will examine a case study of a current SAS software user, see how they have implemented their market research applications and increase the efficiency in prediction of aspects related to products. SAS ®is widely accepted as the gold standard for determining safety and efficacy for clinical trials, and it provides the primary mechanism for preparing data for traditional clinical research analysis activities. However, most SAS users in the biopharmaceutical industry are unaware of the broad range of SAS analytics that are widely applied in other industries. This paper discusses and describes how SAS business and advanced analytics can be used to design Better trials, forecast patient-based activities, and optimize other operational processes. Applying business and advanced analytics to clinical trial operations represents a new and improved approach to reducing the cost and time associated with managing clinical research projects. As a result, the roles of SAS experts in the biopharmaceutical industry are expanded.

The essential oil of the marigold (Tagetes erecta L) flower petals was obtained from the flower collected from the experimental field of Indian Agricultural Research Institute, New Delhi. Theses flower petals were hydro distilled in a Clevenger apparatus to obtain the yellow coloured essential oil. The oil yield was 0.1% (w/w). This oil was collected and dried in a desiccator over calcium chloride. The dried oil was injected to a GC-MS. There were ten peaks revealed in the GC. The mass spectra of five out of ten compounds could be analyzed. The spectral fragmentation pattern revealed that the volatile constituents of marigold oil are mixture heterogeneous components. The compounds identified from the spectral analysis were as a-sesquiphellandrene (Rt 2.165 M+ 204), b-sesquiphellandrene (Rt 2.561, M+ 204), and 2-methyl-6-(4-methyl cyclo hexadienyl) hept -4-en-2-ol (Rt 3.701, M+ 216), myristoleic acid (Rt 3.986 M+ 226) and trieicosane (Rt 7.882, M+ 324). Structure of few other compounds could not be confirmed from the mass spectra.