Analysis and Prediction of Bangalore Traffic South Road Accidents

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cut costs or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Traffic accidents cause enormous losses for a country and plenty of national assets drain away every year due to it. The rapid proliferation of Global Position Service (GPS) devices and mounting number of traffic monitoring systems employed by municipalities have opened the door for advanced traffic control and personalized route planning. But the complexity of traffic accident analysis has brought many difficulties to traffic management and decision-making. Most state of the art traffic management and information systems focus on data analysis and very little has been done in the sense of prediction. This paper provides details about how road accidents and traffic data can be analysed and used to predict the probability of an accident to occur. To start with, the analysis has been done on the Bangalore city traffic considering five traffic stations of the south region of the city – Basavanagudi, Kumaraswamy layout, Banashankari, Jayanagar and Chamarajapet

Influence of textile effluent on the Reaction, Structure and Properties of

The transformation of industrial wastes into useful products attracts more researches to work upon for sustainable of natural resources. In this paper, industrial wastes such as treated textile effluent and fly ash were used in the preparation of plain cement concrete with the intention of reducing the environmental pollution caused by these materials. The partially treated textile effluent was used as mixing water and fly ash was used as 30% partial replacement by weight of cement in concrete. The textile effluents were collected after anaerobic treatment and tertiary treatment from textile industry. Class F Fly ash was collected from Mettur thermal power plant. The physical and chemical properties of treated textile effluent were studied. The control concrete was prepared with potable water available in the laboratory. Experimental test was performed for compressive strength of concrete at 28 days. The powdered concrete samples were examined through infrared spectroscopy, X-ray diffraction and scanning electron microscopy to study the microstructure of concrete. The compressive strength test results revealed that anaerobic effluent water (AAE) concrete accomplished higher compressive strength than control concrete. This was also in affirmation with microscopic analysis in which the formations of hydration products were well established when compared to control concrete

The effect of over exposure of Ultraviolet-B radiation on the physiological characteristics of Aeschynomene aspera L.

The impacts of UV-B radiation (280-/320 nm) increasing in recent decades due todepletion of the ozone layer in the stratosphere. UV-B radiation intensity alters plant ecosystems by reducing their productivity. Penetration of ultraviolet radiation variesamong the different plant species and reflect their sensitivity. The effects of UV- Bradiation was studied in Aeschynomene aspera L. belongs to the family Fabaceae. UV-Bsignificantly decreased the photosynthetic pigments as well as growth characteristics ofthe plant. Phenolic compound was increased but total sugars content were reduced inexposed leaf tissue. Protein content was initially decreased but increased on the 9th day ofUV-B treatment

Outage Probability of Multiple-Input Single-Output (MISO) Systems with Delayed Feedback

We investigate the effect of feedback delay on the outage probability of multiple-input single-output (MISO) fading channels. Channel state information at the transmitter (CSIT) is a delayed version of the channel state information available at the receiver (CSIR). We consider two cases of CSIR: (a) perfect CSIR and (b) CSI estimated at the receiver using training symbols. With perfect CSIR, under a short-term power constraint, we determine: (a) the outage probability for beamforming with imperfect CSIT (BF-IC) analytically, and (b) the optimal spatial power allocation (OSPA) scheme that minimizes outage numerically. Results show that, for delayed CSIT, BF-IC is close to optimal for low SNR and uniform spatial power allocation (USPA) is close to optimal at high SNR. Similarly, under a long-term power constraint, we show that BF-IC is close to optimal for low SNR and USPA is close to optimal at high SNR. With imperfect CSIR, we obtain an upper bound on the outage probability with USPA and BF-IC. Results show that the loss in performance due to imperfection in CSIR is not significant, if the training power is chosen appropriately.Comment: Submitted to IEEE Transactions on Communications Jan 2007, Revised Jun 2007, Revised Nov 200

Impacts of ultraviolet-B radiation on Antioxidant defense system in Aeschynomene aspera L.

Sunlight contains a small amount of short wavelength ultraviolet (UV) lightir radiation, which is harmful to life on planet earth. Penetration of ultraviolet radiationvaries among different plant species and may reflect their sensitivity. The selected plant was exposed to UVBradiation for 9 days and determined the changes

Face Recognition Using Neural Networks

Face recognition from the images is challenging due to the wide variability of face appearances and the complexity of the image background. This paper proposes a novel approach for recognizing the human faces. The recognition is done by comparing the characteristics of the new face to that of known individuals. It has Face localization part, where mouth end point and eyeballs will be obtained. In feature Extraction, Distance between eyeballs and mouth end point will be calculated. The recognition is performed by Neural Network (NN) using Back Propagation Networks (BPN) and Radial Basis Function (RBF) networks. The recognition performance of the proposed method is tabulated based on the experiments performed on a number of images

Antiseptic treatment for human foot wounds using piper betel extract finished bamboo/cotton fabrics

In this study, the extracts of Piper betel leaves have been obtained and finished on to the natural and regenerated bamboo/cotton knitted fabrics. The finished fabrics are assessed for the antibacterial activity against the selected pathogens Staphylococcus sp., Bacillus sp., Klebsiella sp., Pseudomonas sp., and Proteus sp., which are commonly present in the human foot wounds. The obtained results are compared with the untreated fabrics and also with the fabric samples treated with two antibiotics, viz Cefixime and Levofloxacin which are commonly used for the treatment of the foot wounds. The herbal extract treated fabrics show good antibacterial activity against the pathogens, which makes them to have an antiseptic property. To enhance the wash durability of the finished samples the herbal extracts are microencapsulated and their wash durability is assessed using the standard methods