Prediction of Severity of Diabetes Mellitus using Fuzzy Cognitive Maps

The objective to develop this research paper is concerned with a system which helps diagnose the severity of diabetes. The disease named diabetes mellitus makes the body unable to handle sugar so it causes thirst, frequency of urination, tiredness and many other symptoms. The diabetes mellitus describes a metabolic disorder characterized by chronic hyperglycemia with disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion, insulin action, or both. It can be caused by number of factors like pancreatic dysfunction, obesity, hereditary, stress, drugs, alcohol etc. It includes long term damage, dysfunction and failure of various organs. The effects of diabetes mellitus include long term damage and failure of various organs. Diabetes mellitus may present with characteristic symptoms such as thirst, polyuria, blurring of vision, and weight loss. This Paper is implemented on soft computing technique, namely Fuzzy Cognitive Maps (FCM) to find out the presence or absence of diabetes mellitus based on the input of sign/symptoms recorded at three fuzzy levels developed by the domain experts. The large amount of data and information that needs to be handled and integrated requires specific methodologies and tools. The FCM based decision support system was developed with a view to help medical and nursing personnel to assess patient status assist in making a diagnosis. The software tool was tested on 50 cases, showing results with an accuracy of 96%. The analysis of experimental results of different applicants checks the correctness and consistency of decision Support system for correct decision making. Keywords: Fuzzy Logic, FCM, Diabetes Mellitus, Prediction, Symptoms

Surgically assisted medical management of interstitial ectopic pregnancy

An interesting case of interstitial ectopic pregnancy in a primigravida managed by surgically assisted medical management with intracardiac instillation of KCl and methotrexate. It was diagnosed based on transvaginal and transabdominal ultrasound and procedure was done as USG guided under local anaesthesia in OPD by transabdominal route and immediate disappearance of foetal cardiac activity was noted on Doppler. She was followed up with serial sβ-hCG and TVS. She had no post procedure complication and was discharged on day 2 of procedure.

Calpain 2 proteolysis regulates glioblastoma cell invasion

Glioblastoma is the most malignant primary brain tumor with the average patients surviving only one year after diagnosis, even with aggressive therapy. The formation of numerous micro-tumors dispersed into the brain due to rapid invasion of tumor cells, presents the primary challenge to the surgical removal of tumors and limits the effectiveness of current treatments. This dissertation presents studies aimed at understanding the molecular mechanisms regulating invasion of human glioblastoma cells. Transplantation of human glioblastoma cells in the zebrafish brain showed that the knockdown of calpain 2, a calcium-activated protease, resulted in a three fold decrease in the tumor cell invasion. The result was further verified in the organotypic mouse brain slices where the knockdown cells demonstrated 2-fold decrease in the area of dispersal compared to control cells. Our data show that calpain 2 plays a role in the process of tumor cell angiogenesis. Glioblastoma cells were transplanted into the brain of zebrafish expressing GFP in the blood vessels and we observed that 23% of animals injected with control tumor cells demonstrated angiogenesis. In contrast, only 9% of fish that received calpain 2 knockdown cells showed the formation of new vessels. Consistent to the reports from human glioblastoma patients and rodent models, we did not observe metastasis of transplanted cells outside of the brain in the zebrafish, supporting for the use of zebrafish as an important model for glioblastoma cell invasion studies. These results provide evidence that calpain 2 protease activity is required for the dispersal of glioblastoma cells in the brain microenvironment. To determine the mechanism of calpain 2 regulation of tumor cell invasion, proteolysis of filamin by calpain 2 was studied. Filamin is an important actin cross-linking protein which develops orthogonal actin networks in the periphery of the cell. In this study, we show that the expression of filamin inhibits glioblastoma cell invasion. Hence, knocking down filamin expression by 80% resulted in 220% increase in the invasion of glioblastoma cells through Matrigel extracellular matrix. The regulated proteolysis of filamin is a potential mechanism to facilitate the cyclic turnover of actin orthogonal networks which is required for glioblastoma cell invasion. In this study, we identified a novel mechanism that the PI3 kinase activity regulates the cleavage of filamin by calpain 2 in glioblastoma cells. Binding of a membrane phospholipid phosphatidylinositol (3,4,5) triphosphate [PtdIns (3,4,5)-P₃] to filamin induces its proteolysis by calpain 2 after the amino acid lysine 268, removing the actin binding domain which in-turn abolishes the actin binding ability of filamin.Keywords: Zebrafish, Invasion, Calpain, Filamin, Glioblastom

Embedded Platform For Online Signature Verification

in my project the proposed system is used for verifying the signature of particular person with help of embedded plat form on mobile devices. This paper studies online signature verification on PC interface-based mobile devices. A simple and effective method for signature verification is developed. An online signature is represented with a discriminative feature vector derived from attributes of several histograms that can be computed in linear time. The resulting signature template is compact and requires constant space. The algorithm used in this project is SVM (support vector machine). The signatures are acquired using a digitizing tablet which captures both dynamic and spatial information of the writing. After preprocessing the signature, several features are extracted. The authenticity of a writer is determined by comparing an input signature to a stored reference set (template) consisting of three signatures. The similarity between an input signature and the reference set is computed using string matching and the similarity value is compared to a threshold. Several approaches for obtaining the optimal threshold value from the reference set are investigated. The results demonstrate the problem of within-user variation of signatures across multiple signatures and the effectiveness of cross session training strategies to alleviate these problems

`

617-625Bacterial wilt caused by Ralstonia solanacearum is the most devastating disease of tomato resulting in huge yield loss in commercial growing pockets of Himachal Pradesh, India. Cold tolerant strains of this pathogen evolved in the recent past, particularly pathotype IIB, are responsible for causing bacterial wilt in cold and temperate regions. High temperature and humidity favours the incidence of disease. Resistant genotypes have been developed at various research centers, located within the country and abroad but these genotypes were not found suitable for growing in Himachal Pradesh as these are lacking in one or other characteristics. Therefore, 18 bacterial wilt resistant F4 progenies of tomato were evaluated along with two bacterial wilt resistant checks to identify the most promising progenies on the basis of nature and extent of genetic variability and heritability coupled with genetic gain. To ascertain the variability source structure, computation of principal component analysis (PCA) was also done. Estimates for phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV), heritability and genetic gain were found to be high for average fruit weight, total fruits per plant, marketable fruits per plant, marketable yield per plant, gross yield per plant and lycopene content that indicates the presence of sufficient variability ensuring ample scope for improvement through selection. High heritability allied with high genetic gain suggested the presence of additive gene action and thereby these traits could be considered as reliable indices for selection. For PCA studies, eigenvalues were calculated for 16 morphological traits and the results revealed that the initial eight traits exhibited more than 0.5 eigenvalues and above 95 per cent of genetic variability. Hence, these traits can be considered for effective selection of developing elite bacterial wilt resistant lines in tomato

Trion resonance in polariton-electron scattering

Strong interactions between charges and light-matter coupled quasiparticles offer an intriguing prospect with applications from optoelectronics to light-induced superconductivity. Here, we investigate how the interactions between electrons and exciton-polaritons in a two-dimensional semiconductor microcavity can be resonantly enhanced due to a strong coupling to a trion, i.e., an electron-exciton bound state. We develop a microscopic theory that uses a strongly screened interaction between charges to enable the summation of all possible diagrams in the polariton-electron scattering process. The position and magnitude of the resonance is found to vary depending on the values of the light-matter coupling and detuning, thus indicating a large degree of tunability. We furthermore derive an analytic approximation of the interaction strength based on universal lowenergy scattering theory. This is found to match extremely well with our full calculation, indicating that the trion resonance is near universal, depending more on the strength of the light-matter coupling relative to the trion binding energy rather than on the details of the electronic interactions. Thus, we expect the trion resonance in polariton-electron scattering to appear in a broad range of microcavity systems with few semiconductor layers, such as doped monolayer MoSe2 where such resonances have recently been observed experimentally [Sidler et al., Nature Physics 13, 255 (2017)].Comment: 13 pages and 8 figure

A DYNAMIC ECHO STRATEGY TO KEEP AN EYE ON DRIVING

In this project we're using LPC2148 is primary controller. It is associated with ARM7 architecture. GSM modem is linked to controller through serial interface. IR sensor, alcohol sensor (MQ3), Heartbeat sensors are linked to controller through digital I/O lines. Motor also associated with H-bridge or relay. Assume motor as engine. To begin engine user needs to send SMS from mobile. Accidents mainly occur because of driver negligence. The primary aim would be to provide awareness and safety mechanism for that driver. Primary reason of the accident is a result of drinking and abnormal pulse rate of driving person. Additionally for this thievery recognition, home security system and person level identification is decided. The primary utilization of human level identification technique is to recognize the individual within the vehicle. Passive infrared sensor can be used this detects a person’s level. Within this paper alcohol recognition and heartbeat monitoring system, person level identification system, accident alert, thievery recognition and mobile free auto reply technique is accustomed to avoid any sort of accident. Their simulation output is observed by LABVIEW or MATLAB and also the hardware module is acquired.  Password authentication, calls divert method, pulse level mechanism is processed. Both ways can be used to rectify the negligence from the driver and immediate intimation strategy is produced by utilization of GSM technology. Hardware module for hybrid driver safety product is acquired with three methods namely alcohol recognition, heartbeat monitoring system, person level identification method, eye blink sensor and thievery identification

RewardProfiler: A Reward Based Design Space Profiler on DVFS Enabled MPSoCs

Resource mapping on a heterogeneous multi-processor system-on-chip (MPSoC) imposes enormous challenges such as identifying important design points for appropriate resource mapping for improved efficiency or performance, time consumption of exploring all the important design points for each profiled applications, etc. Moreover, incorporating a profiler into integrated development environments (IDEs) in order to achieve more detailed and accurate profiling information? on the application being targeted during runtime such that improved efficiency or performance while executing the application is achieved, the runtime resource management decision to achieve such improved "reward" has to be utilized in a certain way. In this paper, we propose a hybrid approach of resource mapping technique on DVFS enabled MPSoC, which is suitable for IDE integration due to the reduced design points in our methodology resulting in significant reduction in profiling time. We coined our approach as "RewardProfiler" (a Reward based design space Profiler), which is well capable of reducing the design space exploration without losing most of the important design points based on our heuristic approach. In our strategy, an application has to be mapped onto the available resources in such a way so that the "reward" obtained can be maximized. Our approach can also be utilized to maximize multiple "rewards" (Multivariate Reward Maximization) while executing an application. Implementation of our RewardProfiler on the Exynos 5422 MPSoC reveals the efficacy of our proposed approach under various experimental test cases and has a potential of saving 170× more time in profiling for our chosen MPSoC compared to the state-of-the-art methodologies

MAT-CNN-SOPC: Motionless Analysis of Traffic Using Convolutional Neural Networks on System-On-a-Programmable-Chip

Intelligent Transportation Systems (ITS) have become an important pillar in modern 'smart city' framework which demands intelligent involvement of machines. Traffic load recognition can be categorized as an important and challenging issue for such systems. Recently, Convolutional Neural Network (CNN) models have drawn considerable amount of interest in many areas such as weather classification, human rights violation detection through images, due to its accurate prediction capabilities. This work tackles real-life traffic load recognition problem on System-On-a-Programmable-Chip (SOPC) platform and coin it as MAT-CNN-SOPC, which uses an intelligent retraining mechanism of the CNN with known environments. The proposed methodology is capable of enhancing the efficacy of the approach by 2.44x in comparison to the state-of-art and proven through experimental analysis. We have also introduced a mathematical equation, which is capable of quantifying the suitability of using different CNN models over the other for a particular application based implementation

Treatment opportunities with Fernandoa adenophylla and recent novel approaches for natural medicinal phytochemicals as a drug delivery system

Fernandoa adenophylla (FA, Heterophragma adenophyllum) is a plant, cultivated throughout Africa and Southeast Asia. It contains potent phytochemicals such as novel naphthoquinones, their derivatives (peshwaraquinone, dilapachone, adenophyllone, indadone, and lapachol), and triterpenoids [ursolic acid (UA), β-sitosterol (BS), α-amyrin, and oleanolic acid (OA)] that have been assessed and reported to show potential pharmacological activities. The crude extract obtained from the plant has been investigated for certain pharmacological activities such as antibacterial, antifungal, anti-tubercular (TB), antihypertensive, and leishmanicidal activity. A novel drug delivery systems (NDDS) is the latest technique that combines innovative development, formulations, new technology, and methodologies for the safe delivery of pharmaceutical substances in the body. The present study reports the possible treatment opportunities of FA and recent possible novel drug delivery approaches for the natural medicinal phytochemicals