Near Optimal Channel Assignment for Interference Mitigation in Wireless Mesh Networks

In multi-radio multi-channel (MRMC) WMNs, interference alleviation is affected through several network design techniques e.g., channel assignment (CA), link scheduling, routing etc., intelligent CA schemes being the most effective tool for interference mitigation. CA in WMNs is an NP-Hard problem, and makes optimality a desired yet elusive goal in real-time deployments which are characterized by fast transmission and switching times and minimal end-to-end latency. The trade-off between optimal performance and minimal response times is often achieved through CA schemes that employ heuristics to propose efficient solutions. WMN configuration and physical layout are also crucial factors which decide network performance, and it has been demonstrated in numerous research works that rectangular/square grid WMNs outperform random or unplanned WMN deployments in terms of network capacity, latency, and network resilience. In this work, we propose a smart heuristic approach to devise a near-optimal CA algorithm for grid WMNs (NOCAG). We demonstrate the efficacy of NOCAG by evaluating its performance against the minimal-interference CA generated through a rudimentary brute-force technique (BFCA), for the same WMN configuration. We assess its ability to mitigate interference both, theoretically (through interference estimation metrics) and experimentally (by running rigorous simulations in NS-3). We demonstrate that the performance of NOCAG is almost as good as the BFCA, at a minimal computational overhead of O(n) compared to the exponential of BFCA

Novel hybrid generative adversarial network for synthesizing image from sketch

In the area of sketch-based image retrieval process, there is a potential difference between retrieving the match images from defined dataset and constructing the synthesized image. The former process is quite easier while the latter process requires more faster, accurate, and intellectual decision making by the processor. After reviewing open-end research problems from existing approaches, the proposed scheme introduces a computational framework of hybrid generative adversarial network (GAN) as a solution to address the identified research problem. The model takes the input of query image which is processed by generator module running 3 different deep learning modes of ResNet, MobileNet, and U-Net. The discriminator module processes the input of real images as well as output from generator. With a novel interactive communication between generator and discriminator, the proposed model offers optimal retrieval performance along with an inclusion of optimizer. The study outcome shows significant performance improvement

Essays in empirical finance

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2008.Includes bibliographical references.The first chapter in my thesis investigates the association between selected hedge fund characteristics and persistence in performance over time. Analyzing TASS data from 1996-2006, I observe a positive correlation between persistence in good performance and fund size, as well as age. Furthermore, I find that more illiquid investment strategies exhibit significantly stronger persistence in good performance, both in the short and long run, even after controlling for illiquidity risk. These results indicate that higher fund size, age, and exposure to illiquidity are reflective of superior managerial skill. Finally, I note that funds with higher incentive fees display greater persistence in both good and bad (post-fee) performance in the long run. These findings are consistent with a scenario in which incentive fees are raised by both skilled and unskilled, (but lucky), fund managers in response to good past performance. Therefore, my analysis suggests that incentive fees for hedge funds may be endogenously determined. The second chapter tests a simple explanation for momentum profits: systematic out performance arises because certain stocks have persistently strong fundamentals which are not fully valued by the market. We find that "winner" portfolios have higher book-to-market ratios than "loser" portfolios, and the economic and statistical significance of momentum profits is markedly reduced when calculated above value benchmarks. A large component of the returns to relative strength portfolios may thus stem from such portfolios overweighting high value stocks, suggesting a close relation between the value and momentum anomalies. The final chapter develops a measure of international financial contagion using a semi structural approach.(cont.) In particular, we work with a multi-country dynamic equilibrium setting, placing a constraint on portfolio volatility. The tightening of this constraint is a channel through which shocks are propagated globally in our model. We then derive a measure of the tightness of the constraint, or 'contagion', using cross-equation restrictions. We finally evaluate our measure of international contagion with regards to its predictability on global asset price co-movement, as well as on news about the recent sub-prime crisis. We find evidence that our contagion estimator is a strong measure of the sub-prime crisis in this regard.by Pavithra Kamakshi Kumar.Ph.D

A simplified and novel technique to retrieve color images from hand-drawn sketch by human

With the increasing adoption of human-computer interaction, there is a growing trend of extracting the image through hand-drawn sketches by humans to find out correlated objects from the storage unit. A review of the existing system shows the dominant use of sophisticated and complex mechanisms where the focus is more on accuracy and less on system efficiency. Hence, this proposed system introduces a simplified extraction of the related image using an attribution clustering process and a cost-effective training scheme. The proposed method uses K-means clustering and bag-of-attributes to extract essential information from the sketch. The proposed system also introduces a unique indexing scheme that makes the retrieval process faster and results in retrieving the highest-ranked images. Implemented in MATLAB, the study outcome shows the proposed system offers better accuracy and processing time than the existing feature extraction technique

INCIDENTAL DETECTION OF CARCINOMA IN SITU IN FIBROADENOMA OF BREAST IN A YOUNG WOMAN: A RARE FINDING

Fibroadenoma is the most common benign tumor of the breast in young females. Breast cancer arising within a fibroadenoma is a rare phenomenon. The incidence of carcinoma within a fibroadenoma is reported to be between 0.1% and 0.3% in a screened population, with a peak age of occurrence between the 4th and 5th decade. We present a case of 29-year-old female with ductal carcinoma in situ in a background of fibroadenoma. There is a low percentage of fibroadenomas harboring carcinoma; however, all breast lumps should be seriously managed; extirpation and histological examination is recommended

Methods and Approaches for Employability Skill Generation in Higher Educational Institutions.

The vision of any higher education institution is an extension of opportunity to all aspirants of education and expansion across all realms of knowledge. Keeping in line with this vision, institutions of higher education should ideally offer the opportunity to take any course to eligible aspirant in any stream of study that it offers. The vision also encompasses a self-reliant society where all people are educated and productively engaged, with the objective of creating academically empowered and ready-for-the-job professionals in diverse fields. To realize this curriculum should provide for building employability skills among students. It is widely agreed that curriculum per se and real job performance do not match and there is need to incorporate skill supplements to boost employability. This paper attempts to outline the measures undertaken to create employment preparedness among students at Srinivas Institute of Management Studies (SIMS), Mangalore

Smart Attendance Monitoring System Using Face Registering

Face recognition is one of the main branches of biometric verification as the face is the identity of an individual and it is utilized by many organizations to mark attendance of employees. Currently student attendance is recorded physically in the classroom by calling their unique ids, which utilizes more time and it is tedious to verify and identify each student if the number of students increases beyond normal range and it is tough to cross verify whether the authenticated students are actually responding. This project demonstrates a technique for attendance monitoring with facial recognition method by using two different algorithms one will be the existing algorithm such as Principal Component Analysis (PCA) algorithm and the other one is proposed by us which is Unconstrained FACE REGISTERING ALGORITHM. This method will automatically record the attendance of the scholars who are present in the classroom and it will also maintain a login and logout time of students and faculties and administration can easily access all the data of the students. However, it is difficult to estimate the outcome of facial recognition as most of the systems currently present have low detection rate and takes 20-100 images of a person for better identification. In this project attendance is marked by continuous observation which helps the system to improve and it also eliminates few features which affects the performance of the system that are different poses, light effects, partial occlusion etc. which helps the system to achieve better accuracy. This method will save approx 15-20 min of valuable class time and can be used to interact or clear doubts with teachers

ALTERATIONS OF LIPID PROFILE LEVELS IN 7,12-DIMETHYLBENZ(A)ANTHRACENE INDUCED ULCERATIVE COLITIS RAT MODEL

Objective: Ulcerative colitis is a type of inflammatory bowel disease is a chronic gastrointestinal disorder characterized by intestinal inflammation and mucosal tissue damage. We examined the lipid profile levels in murine model of 7,12 Dimethylbenz(a)anthracene induced ulcerative colitis.Methods: Serum was separated from whole blood and was used to determine the lipid profile such as total cholesterol (TC), phospholipids (PL), triglycerides (TG), free fatty acids, high density lipoprotein (HDL-C) and low density lipoprotein (HDL-C).Results: Ulcerative colitis rats exhibit low level of low density lipoprotein cholesterol and total cholesterol. No significant difference was observed in high density lipoprotein and triglycerides and significant difference was observed in phospholipids and free fatty acid serum levels. This communication highlights the lipid profile that occurs in ulcerative colitis.Conclusion: This study, thus, provides valuable information about the disturbances in the lipids and lipoproteins occur in ulcerative colitis.Keywords: Ulcerative colitis, 7,12-Dimethylbenz(a)anthracene, Lipoprotein, Low-density lipoprotein, Phospholipids

Development of Zn-SiC composite coatings: Electrochemical corrosion studies

The Zn-SiC composite coatings were fabricated by using sulphate plating bath dispersed with 1, 2 and 3 g L-1 of 64.28 nm SiC nanoparticles. Appreciable influence on morphology and microstructure was observed in scanning electron microscopy, X-ray diffraction spectroscopy and texture co-efficient calculations for SiC incorporated zinc coatings. The electrochemical corrosion behavior of zinc and Zn-SiC composite coatings was studied by potentiodynamic polarization and electrochemical impedance analysis. Significant reduction in corrosion current and corrosion rate with increased charge transfer resistance was noticed for composite coatings. The SiC incorporated zinc coatings shown improved micro-hardness property to pure zinc coating. The properties of Zn-SiC composite coatings were compared with that of pure zinc coating