Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.
MR Images Classification of Alzheimer's Disease Based on Deep Belief
Network Method
Alzheimer’s Disease
Magnetic Resonance Imaging
Deep Belief Network
Gray Level
Co-occurrence Matrix
Publication Date
Sun Jan 01 2012
Journal Name
Evidence-based Complementary And Alternative Medicine
Gelam Honey Inhibits the Production of Proinflammatory, Mediators NO,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:msub><mml:mrow><mml:mtext>PGE</mml:mtext></mml:mrow><mml:mtext>2</mml:mtext></mml:msub></mml:mrow></mml:math>, TNF-<b><i>α</i></b>, and IL-6 in Carrageenan-Induced Acute Paw Edema in Rats
Natural honey is well known for its therapeutic value and has been used in traditional medicine of different cultures throughout the world. The aim of this study was to investigate the anti-inflammatory effect of Malaysian Gelam honey in inflammation-induced rats. Paw edema was induced by a subplantar injection of 1% carrageenan into the rat right hind paw. Rats were treated with the nonsteroidal anti-inflammatory drug (NSAID) Indomethacin (10 mg/kg, p.o.) or Gelam honey at different doses (1 or 2 g/kg, p.o.). The increase in footpad thickness was considered to be edema, which was measured using a dial caliper. Plasma and paw tissue were collected to analyze the production of inflammatory mediators, such as NO, PGE2
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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
Today the trend is to perform software development work via distributed geographical area among team
individual or even as an organization. However
due to the global market and international presence of many companies
there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space
time and organizational boundaries via information and communication technologies. A global virtual team relies on communication
collaboration
and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study
we investigated factors that affect global virtual teams’ performance
factors considered include cultural differences
language problems
time-zone differences
team size
technical problems
lack of trust
lack of sufficient training
and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand
team size is the lowest level of effect on global virtual teams’ performance. © 2005 - 2016 JATIT & LLS. All rights reserved.
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