Keyword Search in Social Networks

People often tend to ask their friends whenever they want some information related to topics like events, restaurants, or movies as majority of the search engines do not yield the desired results which people are seeking [1]. At present, majority of the current Open Source search engines like those based on Nutch also do not yield desired or expected results. Popular search engine, Google recently incorporated the feature of providing information from your social circle but only limited to Google Plus in your search results. On the other hand, micro blogging site Twitter has emerged as a vital source of information with more than 140 million active users [2] and nearly 250 million new tweets every day [2]. People also like to see more results from the blogs or news websites they follow and generally subscribe to their Really Simple Syndicate(RSS) [3] feed service to get the data and have to use RSS reader to find them. A web search engine which can provide results from user’s social network content along with the indexed web results would be a great deal of help for people interested in results from their social circle. This project’s goal is to include results from your Social Networks (Twitter, RSS feeds) in Yioop! search results by using feeds database created from your Twitter account and RSS feeds you follow

On Characterization and Optimization of Engineering Surfaces

Swedish manufacturing industry in collaboration with academia is exploring innovative ways to manufacture eco-efficient and resource efficient products. Consequently, improving manufacturing efficiency and quality has become the priority for the manufacturing sector to remain competitive in a sustainable way. To achieve this, control and optimization of manufacturing process and product’s performance are necessary. This has led to increase in demand for functional surfaces, which are engineering surfaces tailored to different applications. With new advancements in manufacturing and surface metrology, investigations are steadily progressing towards re-defining quality and meeting dynamic customer demands. In this thesis, surfaces produced by different manufacturing systems are investigated, and methods are proposed to improve specification and optimization.The definition and interpretation of surface roughness vary across the manufacturing industry and academia. It is well known that surface characterization helps to understand the manufacturing process and its influence on surface functional properties such as wear, friction, adhesivity, wettability, fluid retention and aesthetic properties such as gloss. Manufactured surfaces consist of features that are relevant and features that are not of interest. To be able to produce the intended function, it is important to identify and quantify the features of relevance. Use of surface texture parameters helps in quantifying these surface features with respect to type, region, spacing and distribution. Currently, surface parameters Ra or Sa that represent average roughness are widely used in the industry, but they may not provide adequate information on the surface. In this thesis, a general methodology, based on the standard surface parameters and statistical approach, is proposed to improve the specification for surface roughness and identify the combination of significant surface texture parameters that best describe the surface and extract valuable surface information.Surface topography generated by additive, subtractive and formative processes is investigated with the developed research approach. The roughness profile parameters and areal surface parameters defined in ISO, along with power spectral density and scale sensitive fractal analysis, are used for surface characterization and analysis. In this thesis, the application of regression statistics to identify the set of significant surface parameters that improve the specification for surface roughness is shown. These surface parameters are used to discriminate between the surfaces produced by multiple process variables at multiple levels. By analyzing the influence of process variables on the surface topography, the research methodology helps to understand the underlying physical phenomenon and enhance the domain-specific knowledge with respect to surface topography. Subsequently, it helps to interpret processing conditions for process and surface function optimization.The research methods employed in this study are valid and applicable for different manufacturing processes. This thesis can support the guidelines for manufacturing industry focusing on process and functional optimization through surface analysis. With increase in use of machine learning and artificial intelligence in automation, methodologies such as the one proposed in this thesis are vital in exploring and extracting new possibilities in functional surfaces

On Deterministic feature-based Surface Analysis

Manufacturing sector is continuously identifying opportunities to streamline production, reduce waste and improve manufacturing efficiency without compromising product quality. Continuous improvement has been the primary objective to produce acceptable quality products and meet dynamic customer demands by using advanced techniques and methods. Considering the current demands from society on improving the efficiency with sustainable goals, there is considerable interest from researchers and industry to explore the potential, to optimize- and customize manufactured surfaces, as one way of improving the performance of products and processes.Every manufacturing process generate surfaces which beholds certain signature features. Engineered surfaces consist of both, features that are of interest and features that are irrelevant. These features imparted on the manufactured part vary depending on the process, materials, tooling and manufacturing process variables. Characterization and analysis of deterministic features represented by significant surface parameters helps the understanding of the process and its influence on surface functional properties such as wettability, fluid retention, friction, wear and aesthetic properties such as gloss, matte. In this thesis, a general methodology with a statistical approach is proposed to extract the robust surface parameters that provides deterministic and valuable information on manufactured surfaces.Surface features produced by turning, injection molding and Fused Deposition Modeling (FDM) are characterized by roughness profile parameters and areal surface parameters defined by ISO standards. Multiple regression statistics is used to resolve surfaces produced with multiple process variables and multiple levels. In addition, other statistical methods used to capture the relevant surface parameters for analysis are also discussed in this thesis. The selected significant parameters discriminate between the samples produced by different process variables and helps to identify the influence of each process variable. The discussed statistical approach provides valuable information on the surface function and further helps to interpret the surfaces for process optimization.The research methods used in this study are found to be valid and applicable for different manufacturing processes and can be used to support guidelines for the manufacturing industry focusing on process optimization through surface analysis. With recent advancement in manufacturing technologies such as additive manufacturing, new methodologies like the statistical one used in this thesis is essential to explore new and future possibilities related to surface engineering

I’m not the person I used to be: The self and autobiographical memories of immoral actions

People maintain a positive identity in at least two ways: They evaluate themselves more favorably than other people, and they judge themselves to be better now than they were in the past. Both strategies rely on autobiographical memories. The authors investigate the role of autobiographical memories of lying and emotional harm in maintaining a positive identity. For memories of lying to or emotionally harming others, participants judge their own actions as less morally wrong and less negative than those in which other people lied to or emotionally harmed them. Furthermore, people judge those actions that happened further in the past to be more morally wrong than those that happened more recently. Finally, for periods of the past when they believed that they were very different people than they are now, participants judge their actions to be more morally wrong and more negative than those actions from periods of their pasts when they believed that they were very similar to who they are now. The authors discuss these findings in relation to theories about the function of autobiographical memory and moral cognition in constructing and perceiving the self over time

Commanding an Indoor Robot with Gaze Using Eye Tracking Glasses and Motion Capture Camera

For a robot to navigate any environment, it should have a perception of its position. This is achieved by robots ability to create a virtual map of the environment or by its ability to keep track of its position using global positioning system. With theavailability of motion tracking systems, it is possible to have an independent system which can keep track of the robot. This thesis tries to use Eye tracking glasses in conjunction with Motion tracking system to command and guide a TurtleBot around a predefined 3D space. This is achieved with the help of Robotic system toolbox present in MatLab which helps in communicating with Robot Operating System (ROS) installed in TurtleBot, Eye tracking glasses use Virtual reality peripheral network to connect with Matlab and Motive. Matlab scripts are used to retrieve data of gaze direction from Eye tracking glasses and calculate the final position desired by the user. The distance and orientation of final position is calculated with respect to the present position of the Robot. It is oriented and moved towards the final position while being tracked using motion tracking system. This thesis managed to establish a system for communication between Eye tracking glasses, Motion tracking system and Turtlebot. Which is reliable and easy to setup

Self Assembly of Modular Robots with Finite Number of Modules Using Graph Grammar

We wish to design decentralized algorithms for self-assembly of robotic modules that have 100% yield even if the number of available building blocks is limited, and specically when the number of available building blocks is identical to the number of blocks required by the structure. In contrast to self-assembly at the nano and micro scales where abundant building blocks are available, modular robotic systems need to self-assemble from a limited number of modules. In particular, when self-assembly is used for reconguration, it is desirable that the new conformation includes all of the available modules. We propose a suite of algorithms that (1) generate a reversible graph grammar, i.e., generates rules for a desired structure that allow the structure not only to assemble, but also to disassemble, and (2) have a set of structures that are growing in parallel converge to a single structure using broadcast communication. We show that by omitting a reversal rule for the last attached module, self-assembly eventually completes, and that communication can drastically speed up this process. We verify our results by running simulations on Matlab and Player/Stage 2D simulato

A cross sectional study to assess the prevalence of microalbuminuria in patients with type 2 diabetes mellitus

Background: Microalbuminuria is an earliest marker of overt diabetic nephropathy, hence monitoring microalbuminuria in patients with diabetes mellites helps to predict and prevent overt diabetic nephropathy. This cross-sectional study was done to find out the prevalence of microalbuminuria in 200 patients with diabetes mellitus attending medicine OPD of Basaweshwara medical college hospital (BMCH), Chitradurga.Methods: 200 patients with Diabetes mellitus visiting the medicine OPD of BMCH, Chitradurga were considered for the study. Patients history and physical examination findings like duration of diabetes, hypertension, smoking and BMI were considered. Relevant blood investigations like fasting blood sugar, glycated haemoglobin (HbA1c), serum cholesterol and creatinine were done. Microalbuminuria was assessed using dipstick kits in an early morning urine samples.Results: The prevalence of normoalbuminuria was 71% and microalbuminuria was 29%. The prevalence of microalbuminuria increased with the increase in duration of diabetes.Conclusions: Prevalence of microalbuminuria among the patients with diabetes depends upon risk factors like blood pressure control, duration of diabetes, fasting blood sugar and HbA1c. Early identification of high risk patients and the subsequent initiation of renal and cardiovascular protective agents helps to reduce the burden of diabetic kidney disease.

Encapsulating Wall Materials for Micro-/Nanocapsules

Wall materials play a vital role in the development of micro-/nanocapsules to protect the bioactive compounds against external factors. The encapsulation process and the type of polymers exert a direct impact on the development of bioactive micro-/nanocapsules, which greatly reflect in encapsulation efficiency, solubility, stability, surface permeability, and release profile of desired bioactive compounds. Among the polymers, biodegradable polymeric materials have been the focus for various applications in food, pharmaceutical, and cosmetic industries. Thus, this chapter focuses on different encapsulation techniques and the importance of biodegradable polymers employed as wall materials for developing stable and safe micro-/nanocapsules. Among the natural polymers, protein- and polysaccharide-based polymers are widely used. Similarly, the most commonly used synthetic polymers are polycaprolactone, poly(lactic-co-glycolic acid), and polyethylene glycol. Synthetic polymers have been classified based on their exogenous and endogenous responsive natures. At the end, we have also discussed on the applications of biodegradable polymers employed in the development of micro-/nanocapsules. To compile this chapter and to provide adequate information to the readers, we have explored various sources, such as reviews, research articles, books, and book chapters including Google sites