Simulation of a gas blasted liquid sheet on GPU architecture

Atomization of liquid fuel from injector in gas turbine combustors is commonly achieved by means of coflowing gas stream. A study of the re presentative example of this scenario is presented in this paper. An in - house finite volume method based code is developed for this purpose. Volume of fluid (VOF) method is used for capturing the interface. Geometric multigrid method is employed for solvin g the pressure poisson equation and it is parallelized on Graphics processing unit ( GPU ) architecture to meet the computational demand required . The solver is validated for standard benchmark test cases. The solver is applied to study the effect of gas to liquid velocity ratio on primary atomization of liquid sheet

Experimental evaluation of select servers and firewalls under denial of service security attacks

Internet security requires newer prevention mechanisms to be implemented on web-servers and routers. Firewall/Intrusion Prevention mechanisms (IPS) can be deployed on host servers or routers as an added line of defense against Internet attacks. In this thesis, we evaluate performance of security mechanisms provided by these devices against Distributed Denial of Service (DDoS) attacks. The host based firewalls on Windows servers-2003 and 2008 were evaluated. In this thesis, we also evaluated Juniper Networks Netscreen-5GT firewall/IPS, and Cisco ASA-5510/IPS that are used in protecting web-servers against DDoS attacks. It was found that the host based firewalls and protection mechanisms on the windows servers were not capable of defending against the DDoS attacks. Our performance evaluation showed the computing resource of the servers to be completely exhausted under these attacks. The evaluation of firewalls and IPS under different loads of attack had varying performance in supporting the number of web connections

WIFI BASED INDOOR POSITIONING - A MACHINE LEARNING APPROACH

Navigation has become much easier these days mainly due to advancement in satellite technology. The current navigation systems provide better positioning accuracy but are limited to outdoors. When it comes to the indoor spaces such as airports, shopping malls, hospitals or office buildings, to name a few, it will be challenging to get good positioning accuracy with satellite signals due to thick walls and roofs as obstacles. This gap led to a whole new area of research in the field of indoor positioning. Many researches have been conducting experiments on different technologies and successful outcomes have beenseen. Each technology providing indoor positioning capability has its own limitations. In this thesis, different radio frequency (RF) and non-radio frequency (Non-RF) technologies are discussed but focus is set on Wi-Fi for indoor positioning. A demo indoor positioning app is developed for the Technobothnia building at the University of Vaasa premises. This building is already equipped with Wi-Fi infrastructure. A floor plan of the building, radio maps and a fingerprinting database with Wi-Fi signal strength measurements is created with help of tools from HERE technology. The app provides real-time positioning and routing as a future visitor tool. With the exceeding amounts of available data, one of the highly popular fields is applying Machine Learning (ML) to data. It can be applied in many disciplines from medicine to space. In ML, algorithms learn from the data and make predictions. Due to the significant growth in various sensor technologies and computational power, large amounts of data can be stored and processed. Here, the ML approach is also taken to the indoor positioning challenge. An open-source Wi-Fi fingerprinting dataset is obtained from Tampere University and ML algorithms are applied on it for performing indoor positioning. Algorithms are trained with received signal strength (RSS) values with their respective reference coordinates and the user location can be predicted. The thesis provides a performance analysis of different algorithms suitable for future mobile implementations

Master of Science

thesisMillions of tons of generated glass are wasted each year and being added to landfills where it takes one million years to decompose. For companies that collect and recycle used glass, contamination from brown or multicolored-glass is more difficult to recycle than the clear glass form. Even among the collected glass, the less-demanded combined colored-glass is still often dumped into landfills. One alternate way to reduce the volume of waste materials being added to landfills is by using waste glass as a supplementary cementitious material (SCM). This alternative may also help in sustainability of the concrete industry by reducing the amount of cement needed in concrete, and thus reducing the amount of carbon emissions produced due to cement production. One challenge to using this waste glass in concrete is that sand-size glass or cullet when added to concrete will cause a cracking-causing expansive reaction referred to as "alkali-silica reaction" (ASR). However, glass also contains a significant amount of silica, which is a main component in many other supplementary cementitious materials that can improve the strength and durability of concrete. It is hypothesized that a finer particle size of the waste glass will drive the reactivity of the silica from the glass to occur earlier in concrete hydration rather than at the later ages when the detrimental reaction in concrete could occur. This research focuses on determining the quantity and particle size at which waste glass powder can be effective in mortar against ASR. The probability of alkali-silica reaction is tested for mortar samples corresponding to ASTM C1567. Additional testing to verify the effect of the glass powder as a SCM on the compressive strength will be measured for mortar using ASTM C109/C109M. A separate common supplementary cementitious material called fly ash was also blended with the glass to examine whether it could provide beneficial combined effects on ASR and strength. It was found that the crushed mixed-colored glass, collected glass dust, or fly ash, when added alone or in combination, but equating to 40% replacement of cement was found to reduce the ASR expansion to the acceptable limits. However, at 10-40% waste glass dust percent replacements of cement, the 7-day compressive strength dropped by 68 to 42% compared to a mortar without any SCMs. The research also found that glass powder collected from the vacuum dust system at a crushing plant acts more effectively to reduce the effects of ASR as compared to the additionally crushed glass powder

Pricing and Equilibrium Analysis of Network Market Systems

Markets have been the most successful method of identifying value of goods and services. Both large and small scale markets have gradually been moving into the Internet domain, with increasingly large numbers of diverse participants. In this dissertation, we consider several problems pertaining to equilibria in networked marketplaces under different application scenarios and market sizes. We approach the question of pricing and market design from two perspectives. On the one hand, we desire to understand how self-interested market participants would set prices and respond to prices resulting in certain allocations. On the other hand, we wish to evaluate how best to allocate resources so as to attain efficient equilibria. There might be a gap between these viewpoints, and characterizing this gap is desirable. Our technical approaches follow the number of market participants, and the nature of trades happening in the market. In our first problem, we consider a market of providing communication services at the level of providing Internet transit. Here, the transit Internet Service Provider (ISP) must determine billing volumes and set prices for its customers who are _rms that are content providers, sinks, or subsidiary ISPs. Demand from these customers is variable, and they have different impacts on the resources that the transit ISP needs to provision. Using measured data from several networks, we design a fair and flexible billing scheme that correctly identifies the impact of each customer on the amount of provisioning needed. While the customer set in the first problem is finite, many marketplaces deal with a very large number of agents that each have ephemeral lifetimes. Here, agents arrive, participate in the market for some time, and then vanish. We consider two such markets in such a regime. The first is one of apps on mobile devices that compete against each other for cellular data service, while the second is on service marketplaces wherein many providers compete with each other for jobs that consider both prices and provider reputations while making choices between them. Our goal is to show that a Mean Field Game can be used to accurately approximate these systems, determine how prices are set, and characterize the nature of equilibria in such markets. Finally, we consider efficiency metrics in large scale resource sharing networks in which bilateral exchange of resources is the norm. In particular, we consider peer-to-peer (P2P) file sharing under which peers obtain chunks of a file from each other. Here, contrary to the intuition that chunks must be shared whenever one peer has one of value to another, we show that a measure of suppression is needed to utilize resources efficiently. In particular, we propose a simple and stable algorithm entitled Mode suppression that attains near optimal file sharing times by disallowing the sharing of the most frequent chunks in the system

Success Stories in National Innovations on Climate Resilient Agriculture

Not AvailableIn recent years, climate change pertains to significant rise in the frequency of extreme weather events affecting the productivity of crops. Another climate change feature significantly influencing agro eco systems in the change in seasonal rainfall patterns. Enhancing resilience of agriculture to climate risk is of immense importance for protecting livelihoods of farmers. Rainfed agriculture in India accounts for about 60 per cent of the net cultivated area which supports 40 per cent human and 60 per cent livestock population. The contribution from agricultural sector towards GDP is very crucial as 65 – 70 per cent of the population is mainly dependent on agriculture for their livelihood. The Agricultural growth in dryland areas is determined by the bio-physical and socioeconomic factors and their interactions. Rainfed agriculture is diverse and risk prone mainly depending on rainfall. Location specific technologies are essential to attain sustainability in agriculture in these areas. The All India Co-ordinated Research Project for Dryland Agriculture (AICRPDA) main centre, Ananthapuramu was started in 1971 and has carried out commendable research work on dryland agriculture for the past four and half decades. This project has been carrying out location specific adaptive research on rain water management, soil and water conservation, crops and cropping system, farming system crop improvement, energy management, integrated nutrient management and alternate land use systems. This publication contains the essence of important technologies developed for profitable rainfed farming including improved crop varieties, soil test based fertilizer application through integrated nutrient management, insitu and exsitu water conservation methods like rain water harvesting, farm ponds, crops and cropping system, seed to seed mechanization in groundnut, contingency plans for climate exigencies and farming systems approach for enhancing health and income. I compliment Dr. B. Sahadeva Reddy, Chief Scientist, all other scientists and staff involved in bringing out this publication entitled “Success Stories in National Innovations on Climate Resilient Agriculture”. I am sure that this publication would form a valuable source of scientific information for scientists, extension workers, stake holders/farmers and all others engaged in the development of dryland agriculture to improve productivity in rainfed agriculture and enhance the livelihood security of farming.Not Availabl

Determination of Low-Level sulfur compounds in Natural gas and Petrochemicals by Gas Chromatography and Pulsed flamed photometric Detector

The natural gas and petrochemical industries are just some areas in which the analysis of sulfur containing compounds in process streams is a critical quality control step. Not being able to right away detect and accurately assess or quantify these compounds can lead to contaminated products, damaged equipment, poisoned catalysts and process downtime. This article presents a fast, reliable and robust method for the determination of individual volatile sulfur containing compounds in gaseous fuels by gas chromatography coupled with pulsed flame photometric detection

Synovial chondromatosis: a rare cause of knee pain and swelling

Synovial chondromatosis (SC) is a rare, benign, metaplastic, monoarticular disorder of synovial membrane and bursae of large joints. It commonly affects the large joints such as the knee, hips, wrist, ankle and shoulder. Here we report a case of SC of right knee in a 60-year-old female presenting with chief complaints of pain, swelling, restriction of movement in right knee since 1 year after a fall at home. X-ray of right knee revealed multiple calcified loose bodies. The final diagnosis was established by correlating radiologic findings with the histopathology of the excised specimen. Patient was successfully treated by open partial synovectomy of knee using anterior approach in a single step procedure

Ranking of Search Engines in View of Information Explosion

Deals with collection of number of records published on Web, on 23 Main Classes of Colon Classification from 1st January to 31st March 2014 on daily basis, using 5 Search Engines – Google, Lycos, Microsoft, Rediff and Yahoo. Ranking of 5 Search Engines, 23 Main Classes, and the months of January, February and March 2014 has been carried-out, based on number of records they retrieved during the period of study. DOI: 10.17762/ijritcc2321-8169.150518

LWT based encrypted payload steganography

Steganography is used in covert communication for transportation of secrete information. In this paper we propose LWT based Encrypted Payload Steganography (LEPS). The payload is segmented into two parts say block 1 and block 2. The LWT is applied on block 2 to generate four sub bands. Payload block 1 is retained in the spatial domain itself. The values of approximation band coefficients of block 2 and spatial domain intensity values of block 1 are compressed. The LWT is applied on cover image to generate wavelet sub bands and considered only diagonal sub bands (XD). The XD band is decomposed into three parts. The key values are embedded into first part of XD band. The compressed payload is embedded in second and third blocks of XD adaptively. The payload can be retrieved at the destination by adapting reverse process of embedding. It is observed that the values of PSNR and capacity are better in the case of proposed algorithm compared to existing algorithm