Decision support method for the selection of OMSs

With the increasing demand for highly complex, integrated and application-domain-specific systems engineering environments (SEEs) more or less specialized components of the SEEs are developed. An important component is the database management system (DBMS). As conventional DBMSs are not useful to fulfill the requirements on highly complex, persistent data structures, specialized DBMSs, namely object management systems (OMS), have been developed. An advantage of OMSs is that they further enhance the integration not only of data but also of processes. Currently several specialized OMSs with significantly different properties such as the data model, architecture and performance are available. As it is very difficult for an SEE developer to select the most appropriate OMS, we propose a decision support method which enables an SEE developer to identify his requirements and to compare the evaluation results of different OMSs. Additionally we present a practical experiment where we have applied the decision support method for comparing different OMSs. Experiences of the investigation are presented briefly

Complexity Measures for Normal and Epileptic EEG Signals using ApEn, SampEn and SEN

There are numerous applications of EEG signal processing such as monitoring alertness, coma, and brain death, controlling an aesthesia, investigating epilepsy and locating seizure origin, testing epilepsy drug effects, monitoring the brain development, and investigating mental disorders; where data size is too long and requires long time to observe the data by clinician or neurologist. EEG signal processing techniques can be used effectively in such applications. The configuration of the signal waveform may contain valuable and useful information about the different state of the brain since biological signal is highly random in both time and frequency domain. Thus computerized analysis is necessary. Being a non-stationary signal, suitable analysis is essential for EEG to differentiate the normal EEG and epileptic seizures. The importance of entropy based features to recognize the normal EEGs, and ictal as well as interictal epileptic seizures. Three features, such as, Approximate entropy, Sample entropy, and Spectral entropy are used to take out the quantitative entropy features from the given EEG time series data of various time frames of 0.88s, and 1s .Average value of entropies for epileptic time series is less than non epileptic time series

A Decision Support Method for the Selection of Object Management Systems

With the increasing demand for highly complex, integrated and application domain specific systems engineering environments (SEEs) more or less specialized components of the SEEs are developed. An important component is the database management system (DBMS). It is generally accepted that conventional DBMSs are not useful to fulfill the requirements on highly complex, persistent data structures. Rather specialized DBMSs, namely object management systems (OMS), have been developed for fulfilling the enhanced requirements. An advantage of OMSs is that they further enhance the integration not only of data but also of processes. Currently several specialized OMSs with significantly different properties such as the data model, architecture and performance are available. Thus it is very difficult for an SEE developer to select the most appropriate OMS for his SEE. In this paper we have proposed a decision support method which enables an SEE developer to identify his requirements and to compare the evaluation results of different OMSs. Additionally we present a practical experiment where we have applied the decision support method for comparing different OMSs. Experiences of the investigation are presented briefly

Lossy To Lossless Medical Image Coding Using Joint Bit Scanning Method

A new algorithm for progressive medical image coding is presented. On the 8-bit gray scale image, lifting based integer wavelet transform (IWT) are applied to get the three level multi-resolution Integer wavelet transformed image. Then, it is encoded using block based partitioning scheme to exploit the energy clustering in frequency and in space. Whenever a pixel is found significant, pixel value is completely transmitted using vertical bit scanning and then proceeds again with block based coding. Experiments are carried on MRI images to prove the effectiveness of the proposed algorithm. The results shows a significant improvement in terms of distortion measured as peak signal to noise ratio (PSNR) and Correlation Coefficient (CoC)  for a given bit rate compared to the existing state of the art embedded image coding methods

Simulation of Thin Film Thermocouple for High Temperature Measurement Applicable to Missiles

Thermocouples have been extensively used for the measurement of temperature since the advent of seebeck effect. Numerous sensors have been developed for temperature measurement, yet measurement of high temperature flowing fluid has been a challenging task. For the measurement of static temperature the measuring device should travel with the fluid at the same speed without disturbing the flow, which is quite unrealistic. So indirect determination of static temperature of flowing fluid is done by using thermocouple exposed into the flowing fluid. Other sensors available for high temperature measurement may lead to problems like resistance in the flow path of fluid which changes the structural dynamics. Thin film thermocouple (TFTC) based on W-W26Re for super high temperature measurement has been investigated which can be used in missiles for surface temperature measurement of nozzle and rocket interior surface. TFTC does not cause disruption in the flow path with maintaining structural integrity. The W-W26Re thermocouple offers advantage of higher seebeck coefficient at high temperature i.e. above 750 K, and usability in vacuum, inert and hydrogen atmosphere. Zirconia Fiber has been proposed as insulation protection material over thermocouple. Modelling and simulation of the TFTC for the temperature range 300 K - 2900 K has been presented. FEA model using PDE has been presented to implement heat equation, current balance  quation, Gauss theorem and Neumann boundary condition. The expected voltage production on exposed temperature gradient has been studied

Beiträge zur molekularen Charakterisierung der unterschiedlichen Formen der männlichen Sterilität bei Allium schoenoprasum L

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A Testbed for Simulation-based Analysis of Forwarding Plane

A Testbed for Simulation-based Analysis of Forwarding Plane - Faras Mohan Dewal Master of Applied Science (Electrical and Computer Engineering) Concordia University, Montreal QC, 2016 This thesis presents a testbed capable of generating scalable realistic network traffic on a standalone machine. The functionality of the proposed testbed is to model a scalable network of client and server instances and generate network traffic to perform simulation based-analysis of forwarding plane designs. The testbed enables the designer to successfully conduct experiments on the design under test using realistic traffic profiles and assess the performance for multiple use cases. The proposed testbed defines simulation models for client and server nodes. The testbed modeling has been abstracted to three different levels. First, a base node design allows us to instantiate and manage multiple instances within the node. Second, a transmission protocol is implemented to enable data transfer between client and server instances. The final stage is the Internet application modeling stage. Our experiments show that we are able to reliably generate network traffic for up to 400 client and server instances on a standalone machine

Ossifying fibroma of nasal cavity: A rare case report

Ossifying fibroma (OF) is considered a rare benign fibro-osseous lesion that occurs most commonly in female patients. It mainly involves the mandibular and maxillary bones, although in rare cases, it may develop within the nasal cavity. Here, we present a rare case report of OF of the nasal cavity in a 30-year-old female. OF is usually diagnosed by histopathological examination and treated by enucleation. However, larger lesions require radical resection

Allelic Selection of Amplicons in Glioblastoma Revealed by Combining Somatic and Germline Analysis

Cancer is a disease driven by a combination of inherited risk alleles coupled with the acquisition of somatic mutations, including amplification and deletion of genomic DNA. Potential relationships between the inherited and somatic aspects of the disease have only rarely been examined on a genome-wide level. Applying a novel integrative analysis of SNP and copy number measurements, we queried the tumor and normal-tissue genomes of 178 glioblastoma patients from the Cancer Genome Atlas project for preferentially amplified alleles, under the hypothesis that oncogenic germline variants will be selectively amplified in the tumor environment. Selected alleles are revealed by allelic imbalance in amplification across samples. This general approach is based on genetic principles and provides a method for identifying important tumor-related alleles. We find that SNP alleles that are most significantly overrepresented in amplicons tend to occur in genes involved with regulation of kinase and transferase activity, and many of these genes are known contributors to gliomagenesis. The analysis also implicates variants in synapse genes. By incorporating gene expression data, we demonstrate synergy between preferential allelic amplification and expression in DOCK4 and EGFR. Our results support the notion that combining germline and tumor genetic data can identify regions relevant to cancer biology

Inclusion of Electrochemically Active Guests by Novel Oxacalixarene Hosts

We demonstrate for the first time the utility of oxacalixarenes as hosts and investigate the forces that influence the thermodynamics of binding