Studying the Behaviour of Model of Mirror Neuron System in Case of Autism

Several experiment done by the researchers conducted that autism is caused by the dysfunctional mirror neuron system and the dysfunctions of mirror neuron system is proportional to the symptom severity of autism. In the present work those experiments were studied as well as studying a model of mirror neuron system called MNS2 developed by a research group. This research examined the behavior of the model in case of autism and compared the result with those studies conducting dysfunctions of mirror neuron system in autism. To perform this, a neural network employing the model was developed which recognized the three types of grasping (faster, normal and slower). The network was implemented with back propagation through time learning algorithm. The whole grasping process was divided into 30 time steps and different hand and object states at each time step was used as the input of the network. Normally the network successfully recognized all of the three types of grasps. The network required more times as the number of inactive neurons increased. And in case of maximum inactive neurons of the mirror neuron system the network became unable to recognize the types of grasp. As the time to recognize the types of grasp is proportional to the number of inactive neurons, the experiment result supports the hypothesis that dysfunctions of MNS is proportional to the symptom severity of autism

CHARACTERIZATION OF REFORMER TUBE CREEP DAMAGE BY ULTRASONIC ATTENUATION PATTERN AND MICROSTRUCTURAL CHANGES

Creep damage is a critical degradation mechanism in reformer tubes which experienced prolonged service periods at elevated temperature. Thus, continuous monitoring of creep is vital in ensuring plant integrity. Since creep damage relates to the changes in microstructure, characterization of creep using common ultrasonic attenuation and metallography techniques can be used. This project utilized the attenuation of ultrasonic wave in different tube samples and changes within the microstructure in characterizing the level of creep damage. The study was based on a failed reformer HK-40 catalyst tube by which the tube was cross-sectioned to the thickness corresponding to exposed temperature calculated based on heat transfer formulation. The sample was characterized in terms of ultrasonic wave attenuation, metallography and micro hardness. Results had shown that tube sample which had been exposed to higher temperature produced higher attenuation of ultrasonic wave, significant increase in carbide formation and hardness value while revealing a decrease in grain size than the sample exposed to lower temperature. Based on the results, it is clear that tube sample which had been exposed to higher temperature exhibits the characteristic of creep damage in tertiary stage, while the tube sample exposed to lower temperature are proved to be in secondary stage. In conclusion, creep damage can be evaluated based on ultrasonic wave attenuation and microstructural analysis

Iron deficiency anemia as a risk factor for simple febrile seizures

To determine the association of iron deficiency anemia with simple febrile seizures in children presenting in a tertiary care hospital

A Modified Deficit Weighted Round Robin traffic Scheduling Algorithm for GPON Networks

In this paper, we propose the modified deficit weighted round robin (MDWRR) traffic scheduling algorithm for Gigabit Passive Optical Network (GPON), which guarantees the real-time priority traffic. The proposed scheduling algorithm is a variation of the deficit weighted round robin (DWRR) algorithm and it assures the highest priority traffic transmission with minimization of delay. WRR algorithm to be aware of bandwidth and improves the fairness. But for certain traffic types, fairness is not the desired behavior. To achieve predictable service for sensitive, real-time traffic, a priority level for scheduling needs to be introduced. By enabling strict priority, or by offering several priority levels and using DWRR scheduling between queues with the same priority levels, service assurance with regards to delay and loss protection can be achieved for demanding traffic types, such as voice and real-time broadcasting. By offering several priority levels and using DWRR scheduling between queues with the same priority levels, service assurance with regards to delay and loss protection can be achieved for demanding traffic types, such as voice and real-time broadcasting

Interactive Virtual Reality Video Walkthrough

This research aims to builds a prototype that has Interactive Video and QuickTime Virtual Reality (QTVR) features into one program. Adobe Flash software has been used as the platform to develop this prototype because end user only needs to download small size of runtime file to play and interact with the program. Other than that, usability testing have been done on the prototype by using System Usability Scale (SUS) to test the prototype usability so that it is easier to use and closely fill user needs and requirements. As conclusions, this research successfully combines features of Interactive Video and QTVR in one prototype in Adobe Flash and successfully finished doing the usability testing

Detection of Intestinal Bleeding in Wireless Capsule Endoscopy using Machine Learning Techniques

Gastrointestinal (GI) bleeding is very common in humans, which may lead to fatal consequences. GI bleeding can usually be identified using a flexible wired endoscope. In 2001, a newer diagnostic tool, wireless capsule endoscopy (WCE) was introduced. It is a swallow-able capsule-shaped device with a camera that captures thousands of color images and wirelessly sends those back to a data recorder. After that, the physicians analyze those images in order to identify any GI abnormalities. But it takes a longer screening time which may increase the danger of the patients in emergency cases. It is therefore necessary to use a real-time detection tool to identify bleeding in the GI tract. Each material has its own spectral ‘signature’ which shows distinct characteristics in specific wavelength of light [33]. Therefore, by evaluating the optical characteristics, the presence of blood can be detected. In the study, three main hardware designs were presented: one using a two-wavelength based optical sensor and others using two six-wavelength based spectral sensors with AS7262 and AS7263 chips respectively to determine the optical characteristics of the blood and non-blood samples. The goal of the research is to develop a machine learning model to differentiate blood samples (BS) and non-blood samples (NBS) by exploring their optical properties. In this experiment, 10 levels of crystallized bovine hemoglobin solutions were used as BS and 5 food colors (red, yellow, orange, tan and pink) with different concentrations totaling 25 non-blood samples were used as NBS. These blood and non-blood samples were also combined with pig’s intestine to mimic in-vivo experimental environment. The collected samples were completely separated into training and testing data. Different spectral features are analyzed to obtain the optical information about the samples. Based on the performance on the selected most significant features of the spectral wavelengths, k-nearest neighbors algorithm (k-NN) is finally chosen for the automated bleeding detection. The proposed k-NN classifier model has been able to distinguish the BS and NBS with an accuracy of 91.54% using two wavelengths features and around 89% using three combined wavelengths features in the visible and near-infrared spectral regions. The research also indicates that it is possible to deploy tiny optical detectors to detect GI bleeding in a WCE system which could eliminate the need of time-consuming image post-processing steps

Procyclical Monetary Policy and Governance

Weak governance adversely affects firm’s net worth and consequently the value of its collateral. This negative impact on the collateral reduces the external credit available for importing inputs constraining potential output. As a result, a stronger procyclical monetary policy stance is adopted for protecting the exchange rate and hence arresting the degradation in the collateral constraint.Collateral Constraints; Governance; Monetary Policy

A Comparative Study of Personality Dynamics of Family and Non-Family Entrepreneurs and their Impact on Organizational Effectiveness

The current research focuses on the exploration of the big five personality traits model and its impact on organizational effectiveness in the restaurant industry entrepreneurs of Lahore, Pakistan. The personality traits of different entrepreneurs working in family and non-family owned enterprises are analyzed along with their effectiveness. Data collection mode was survey and data was collected through structured questionnaire. Purposive non-probability sampling technique was used for sample selection. Questionnaire was responded by 110 entrepreneurs (55 family entrepreneurs and 55 non-family entrepreneurs) of restaurant industry. The research findings reveal that all of the personality items have a positive correlation with the organizational effectiveness except neuroticism, yet these personality traits have variable impact on the effectiveness of restaurants. For family entrepreneurs, the traits of extrovert, neuroticism, openness to experience and agreeableness have significant impact on the effectiveness of restaurants whereas for non-family restaurants only conscientiousness trait has a significant impact on restaurants’ effectiveness. Keywords: family entrepreneurs, non-family entrepreneurs, conscientiousness, extrovert, neuroticism, openness to experience, agreeableness, organizational effectiveness.