Search results for: Fuad Noman
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 46

Search results for: Fuad Noman

46 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning

Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

Procedia PDF Downloads 351
45 Some Results on Generalized Janowski Type Functions

Authors: Fuad Al Sarari

Abstract:

The purpose of the present paper is to study subclasses of analytic functions which generalize the classes of Janowski functions introduced by Polatoglu. We study certain convolution conditions. This leads to a study of the sufficient condition and the neighborhood results related to the functions in the class S (T; H; F ): and a study of new subclasses of analytic functions that are defined using notions of the generalized Janowski classes and -symmetrical functions. In the quotient of analytical representations of starlikeness and convexity with respect to symmetric points, certain inherent properties are pointed out.

Keywords: convolution conditions, subordination, Janowski functions, starlike functions, convex functions

Procedia PDF Downloads 41
44 Brainwave Classification for Brain Balancing Index (BBI) via 3D EEG Model Using k-NN Technique

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

Procedia PDF Downloads 451
43 Use of Fractal Geometry in Machine Learning

Authors: Fuad M. Alkoot

Abstract:

The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

Procedia PDF Downloads 179
42 A Double PWM Source Inverter Technique with Reduced Leakage Current for Application on Standalone Systems

Authors: Md.Noman Habib Khan, M. S. Tajul Islam, T. S. Gunawan, M. Hasanuzzaman

Abstract:

The photovoltaic (PV) panel with no galvanic isolation system is well-known technique in the world which is effective and deliver power with enhanced efficiency. The PV generation presented here is for stand-alone system installed in remote areas when as the resulting power gets connected to electronic load installation instead of being tied to the grid. Though very small, even then transformer-less topology is shown to be with leakage in pico-ampere range. By using PWM technique PWM, leakage current in different situations is shown. The results that are demonstrated in this paper show how the pico-ampere current is reduced to femto-ampere through use of inductors and capacitors of suitable values of inductor and capacitors with the load.

Keywords: photovoltaic (PV) panel, duty cycle, pulse duration modulation (PDM), leakage current

Procedia PDF Downloads 508
41 Characterization of 3D-MRP for Analyzing of Brain Balancing Index (BBI) Pattern

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analysed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).

Keywords: power spectral density, 3D EEG model, brain balancing, mean relative power, different mean relative power

Procedia PDF Downloads 445
40 Biodegradation of Cellulosic Materials by Marine Fungi Isolated from South Corniche of Jeddah, Saudi Arabia

Authors: Fuad Ameen, Mohamed Moslem, Sarfaraz Hadi

Abstract:

Twenty-eight fungal isolates belonging to 12 genera were derived from debris, sediment and water samples collected from Avicennia marina stands 25km south of Jeddah city on the Red Sea coast of Saudi Arabia. Eight of these isolates were found to be able to grow in association cellulosic waste materials under in vitro conditions in the absence of any carbon source. Isolates were further tested for their potential to degrade paper and clothes wastes by co-cultivation under aeration on a rotary shaker. These fungi accumulated significantly higher biomass, produced ligninolytic and cellulase enzymes, and liberated larger volumes of CO2. These observations indicated that the selected isolates were able to break down and consume the waste materials.

Keywords: biodegradation, enzyme activity, waste materials, mangrove

Procedia PDF Downloads 525
39 A Multi-Objective Evolutionary Algorithm of Neural Network for Medical Diseases Problems

Authors: Sultan Noman Qasem

Abstract:

This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

Procedia PDF Downloads 531
38 Micro Grids, Solution to Power Off-Grid Areas in Pakistan

Authors: M. Naveed Iqbal, Sheza Fatima, Noman Shabbir

Abstract:

In the presence of energy crisis in Pakistan, off-grid remote areas are not on priority list. The use of new large scale coal fired power plants will also make this situation worst. Therefore, the greatest challenge in our society is to explore new ways to power off grid remote areas with renewable energy sources. It is time for a sustainable energy policy which puts consumers, the environment, human health, and peace first. The renewable energy is one of the biggest growing sectors of the energy industry. Therefore, the large scale use of micro grid is thus described here with modeling, simulation, planning and operating of the micro grid. The goal of this research paper is to go into detail of a library of major components of micro grid. The introduction will go through the detail view of micro grid definition. Then, the simulation of Micro Grid in MATLAB/ Simulink including the Photo Voltaic Cell will be described with the detailed modeling. The simulation with the design and modeling will be introduced too.

Keywords: micro grids, distribution generation, PV, off-grid operations

Procedia PDF Downloads 275
37 Identity Verification Using k-NN Classifiers and Autistic Genetic Data

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 223
36 Performance Analysis of Routing Protocols for WLAN Based Wireless Sensor Networks (WSNs)

Authors: Noman Shabbir, Roheel Nawaz, Muhammad N. Iqbal, Junaid Zafar

Abstract:

This paper focuses on the performance evaluation of routing protocols in WLAN based Wireless Sensor Networks (WSNs). A comparative analysis of routing protocols such as Ad-hoc On-demand Distance Vector Routing System (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR) is been made against different network parameters like network load, end to end delay and throughput in small, medium and large-scale sensor network scenarios to identify the best performing protocol. Simulation results indicate that OLSR gives minimum network load in all three scenarios while AODV gives the best throughput in small scale network but in medium and large scale networks, DSR is better. In terms of delay, OLSR is more efficient in small and medium scale network while AODV is slightly better in large networks.

Keywords: WLAN, WSN, AODV, DSR, OLSR

Procedia PDF Downloads 400
35 Influencers of E-Learning Readiness among Palestinian Secondary School Teachers: An Explorative Study

Authors: Fuad A. A. Trayek, Tunku Badariah Tunku Ahmad, Mohamad Sahari Nordin, Mohammed AM Dwikat

Abstract:

This paper reports on the results of an exploratory factor analysis procedure applied on the e-learning readiness data obtained from a survey of four hundred and seventy-nine (N = 479) teachers from secondary schools in Nablus, Palestine. The data were drawn from a 23-item Likert questionnaire measuring e-learning readiness based on Chapnick's conception of the construct. Principal axis factoring (PAF) with Promax rotation applied on the data extracted four distinct factors supporting four of Chapnick's e-learning readiness dimensions, namely technological readiness, psychological readiness, infrastructure readiness and equipment readiness. Together these four dimensions explained 56% of the variance. These findings provide further support for the construct validity of the items and for the existence of these four factors that measure e-learning readiness.

Keywords: e-learning, e-learning readiness, technological readiness, psychological readiness, principal axis factoring

Procedia PDF Downloads 356
34 Indigenous Patch Clamp Technique: Design of Highly Sensitive Amplifier Circuit for Measuring and Monitoring of Real Time Ultra Low Ionic Current through Cellular Gates

Authors: Moez ul Hassan, Bushra Noman, Sarmad Hameed, Shahab Mehmood, Asma Bashir

Abstract:

The importance of Noble prize winning “Patch Clamp Technique” is well documented. However, Patch Clamp Technique is very expensive and hence hinders research in developing countries. In this paper, detection, processing and recording of ultra low current from induced cells by using transimpedence amplifier is described. The sensitivity of the proposed amplifier is in the range of femto amperes (fA). Capacitive-feedback is used with active load to obtain a 20MΩ transimpedance gain. The challenging task in designing includes achieving adequate performance in gain, noise immunity and stability. The circuit designed by the authors was able to measure current in the rangeof 300fA to 100pA. Adequate performance shown by the amplifier with different input current and outcome result was found to be within the acceptable error range. Results were recorded using LabVIEW 8.5®for further research.

Keywords: drug discovery, ionic current, operational amplifier, patch clamp

Procedia PDF Downloads 488
33 Development of Mobile EEF Learning System (MEEFLS) for Mobile Learning Implementation in Kolej Poly-Tech MARA (KPTM)

Authors: M. E. Marwan, A. R. Madar, N. Fuad

Abstract:

Mobile learning (m-learning) is a new method in teaching and learning process which combines technology of mobile device with learning materials. It can enhance student's engagement in learning activities and facilitate them to access the learning materials at anytime and anywhere. In Kolej Poly-Tech Mara (KPTM), this method is seen as an important effort in teaching practice and to improve student learning performance. The aim of this paper is to discuss the development of m-learning application called Mobile EEF Learning System (MEEFLS) to be implemented for Electric and Electronic Fundamentals course using Flash, XML (Extensible Markup Language) and J2ME (Java 2 micro edition). System Development Life Cycle (SDLC) was used as an application development approach. It has three modules in this application such as notes or course material, exercises and video. MEELFS development is seen as a tool or a pilot test for m-learning in KPTM.

Keywords: flash, mobile device, mobile learning, teaching and learning, SDLC, XML

Procedia PDF Downloads 495
32 The Methodology of Flip Chip Using Astro Place and Route Tool

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, Md Hanif Md Nasir

Abstract:

This paper will discuss flip chip methodology, in which I/O pads, standard cells, macros and bump cells array are placed in the floorplan, then routed using Astro place and route tool. Final DRC and LVS checking is done using Calibre verification tool. The design vehicle to run this methodology is an OpenRISC design targeted to Silterra 0.18 micrometer technology with 6 metal layers for routing. Astro has extensive support for flip chip placement and routing. Astro tool commands for flip chip are straightforward approach like the conventional standard wire bond packaging. However since we do not have flip chip commands in our Astro tool, no LEF file for bump cell and no LEF file for flip chip I/O pad, we create our own methodology to prepare for future flip chip tapeout. 

Keywords: methodology, flip chip, bump cell, LEF, astro, calibre, SCHEME, TCL

Procedia PDF Downloads 451
31 Using Classifiers to Predict Student Outcome at Higher Institute of Telecommunication

Authors: Fuad M. Alkoot

Abstract:

We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

Procedia PDF Downloads 248
30 Enhancement of Learning Style in Kolej Poly-Tech MARA (KPTM) via Mobile EEF Learning System (MEEFLS)

Authors: M. E. Marwan, A. R. Madar, N. Fuad

Abstract:

Mobile communication provides access to the outside world without borders everywhere and at any time. The learning method that related to mobile communication technology is known as mobile learning (M-learning). It is a method that communicates learning materials with mobile device technology. The purpose of this method is to increase the interest in learning among students and assist them in obtaining learning materials at Kolej Poly-Tech MARA (KPTM) in order to improve the student’s performance in their study and to encourage educators to diversify the teaching practices. This paper discusses the student’s awareness for enhancement of learning style using mobile technologies and their readiness to apply the elements of mobile learning in learning to improve performance and interest in learning among students. An application called Mobile EEF Learning System (MEEFLS) has been developed as a tool to be used as a pilot test in KPTM.

Keywords: awareness, mobile learning, MEEFLS, teaching and learning, readiness

Procedia PDF Downloads 352
29 HPPDFIM-HD: Transaction Distortion and Connected Perturbation Approach for Hierarchical Privacy Preserving Distributed Frequent Itemset Mining over Horizontally-Partitioned Dataset

Authors: Fuad Ali Mohammed Al-Yarimi

Abstract:

Many algorithms have been proposed to provide privacy preserving in data mining. These protocols are based on two main approaches named as: the perturbation approach and the Cryptographic approach. The first one is based on perturbation of the valuable information while the second one uses cryptographic techniques. The perturbation approach is much more efficient with reduced accuracy while the cryptographic approach can provide solutions with perfect accuracy. However, the cryptographic approach is a much slower method and requires considerable computation and communication overhead. In this paper, a new scalable protocol is proposed which combines the advantages of the perturbation and distortion along with cryptographic approach to perform privacy preserving in distributed frequent itemset mining on horizontally distributed data. Both the privacy and performance characteristics of the proposed protocol are studied empirically.

Keywords: anonymity data, data mining, distributed frequent itemset mining, gaussian perturbation, perturbation approach, privacy preserving data mining

Procedia PDF Downloads 475
28 Physical Verification Flow on Multiple Foundries

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Muhammad Al Baqir Zinal Abidin, Md Hanif Md Nasir

Abstract:

This paper will discuss how we optimize our physical verification flow in our IC Design Department having various rule decks from multiple foundries. Our ultimate goal is to achieve faster time to tape-out and avoid schedule delay. Currently the physical verification runtimes and memory usage have drastically increased with the increasing number of design rules, design complexity and the size of the chips to be verified. To manage design violations, we use a number of solutions to reduce the amount of violations needed to be checked by physical verification engineers. The most important functions in physical verifications are DRC (design rule check), LVS (layout vs. schematic) and XRC (extraction). Since we have a multiple number of foundries for our design tape-outs, we need a flow that improve the overall turnaround time and ease of use of the physical verification process. The demand for fast turnaround time is even more critical since the physical design is the last stage before sending the layout to the foundries.

Keywords: physical verification, DRC, LVS, XRC, flow, foundry, runset

Procedia PDF Downloads 626
27 Microarray Gene Expression Data Dimensionality Reduction Using PCA

Authors: Fuad M. Alkoot

Abstract:

Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

Procedia PDF Downloads 526
26 Negative Pressure Waves in Hydraulic Systems

Authors: Fuad H. Veliev

Abstract:

Negative pressure phenomenon appears in many thermodynamic, geophysical and biophysical processes in the Nature and technological systems. For more than 100 years of the laboratory researches beginning from F. M. Donny’s tests, the great values of negative pressure have been achieved. But this phenomenon has not been practically applied, being only a nice lab toy due to the special demands for the purity and homogeneity of the liquids for its appearance. The possibility of creation of direct wave of negative pressure in real heterogeneous liquid systems was confirmed experimentally under the certain kinetic and hydraulic conditions. The negative pressure can be considered as the factor of both useful and destroying energies. The new approach to generation of the negative pressure waves in impure, unclean fluids has allowed the creation of principally new energy saving technologies and installations to increase the effectiveness and efficiency of different production processes. It was proved that the negative pressure is one of the main factors causing hard troubles in some technological and natural processes. Received results emphasize the necessity to take into account the role of the negative pressure as an energy factor in evaluation of many transient thermohydrodynamic processes in the Nature and production systems.

Keywords: liquid systems, negative pressure, temperature, wave, metastable state

Procedia PDF Downloads 384
25 The Integration and Automation of EDA Tools in an Integrated Circuit Design Environment

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, M. Hanif M. Nasir

Abstract:

This paper will discuss how EDA tools are integrated and automated in an Integrated Circuit Design Environment. Some of the problems face in our current environment is that users need to configure manually on the library paths, start-up files and project directories. Certain manual processes that happen between the users and applications can be automated but they must be transparent to the users. For example, the users can run the applications directly after login without knowing the library paths and start-up files locations. The solution to these problems is to automate the processes using standard configuration files which will benefit the users and EDA support. This paper will discuss how the implementation is done to automate the process using scripting languages such as Perl, Tcl, Scheme and Shell Script. These scripting tools are great assets for design engineers to build a robust and powerful design flow and this technique is widely used to integrate all the tools together.

Keywords: EDA tools, Integrated Circuits, scripting, integration, automation

Procedia PDF Downloads 289
24 An Improved Data Aided Channel Estimation Technique Using Genetic Algorithm for Massive Multi-Input Multiple-Output

Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin

Abstract:

With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.

Keywords: channel estimation, LMMSE, LS, MIMO, MMSE

Procedia PDF Downloads 161
23 Community-based Mapping as a Planning Tool; Examples from Pakistan

Authors: Noman Ahmed, Fariha Tahseen

Abstract:

Since several decades, unplanned urbanization and rapid growth of informal settlements have evolved and increased in size and number. Large cities such as Karachi have been impacted with sprawl and rising share of unplanned settlements where poor communities reside. Threats of eviction, deteriorating law and order situation, lack of essential amenities and infrastructure, extortion and bullying from local and non-local musclemen and feeble response of government agencies towards their development needs are some predicaments. Non-governmental organizations (NGOs) have caused important interventions in such locations. Appraisal of the community-based mapping as a tool in supporting the development work in less privileged areas in Karachi has been the objective of this research. The Orangi Pilot Project (OPP), under the leadership of its slain director Perween Rahman had a significant role to play in developing and extending this approach in low income locations in Karachi and beyond. The paper investigates the application of mapping in the process of peri urban land invasion causing rapid transformation of traditional settlements in Karachi. Mixed methodology components comprising literature review, archival research, and unstructured interviews with key informants and case studies have been used.

Keywords: squatters (katchi abadis), land grabbing, community empowerment, housing rights, mapping, infrastructure development

Procedia PDF Downloads 287
22 Managing the Cognitive Load of Medical Students during Anatomy Lecture

Authors: Siti Nurma Hanim Hadie, Asma’ Hassan, Zul Izhar Ismail, Ahmad Fuad Abdul Rahim, Mohd. Zarawi Mat Nor, Hairul Nizam Ismail

Abstract:

Anatomy is a medical subject, which contributes to high cognitive load during learning. Despite its complexity, anatomy remains as the most important basic sciences subject with high clinical relevancy. Although anatomy knowledge is required for safe practice, many medical students graduated without having sufficient knowledge. In fact, anatomy knowledge among the medical graduates was reported to be declining and this had led to various medico-legal problems. Applying cognitive load theory (CLT) in anatomy teaching particularly lecture would be able to address this issue since anatomy information is often perceived as cognitively challenging material. CLT identifies three types of loads which are intrinsic, extraneous and germane loads, which combine to form the total cognitive load. CLT describe that learning can only occur when the total cognitive load does not exceed human working memory capacity. Hence, managing these three types of loads with the aim of optimizing the working memory capacity would be beneficial to the students in learning anatomy and retaining the knowledge for future application.

Keywords: cognitive load theory, intrinsic load, extraneous load, germane load

Procedia PDF Downloads 430
21 Suitability Number of Coarse-Grained Soils and Relationships among Fineness Modulus, Density and Strength Parameters

Authors: Khandaker Fariha Ahmed, Md. Noman Munshi, Tarin Sultana, Md. Zoynul Abedin

Abstract:

Suitability number (SN) is perhaps one of the most important parameters of coarse-grained soil in assessing its appropriateness to use as a backfill in retaining structures, sand compaction pile, Vibro compaction, and other similar foundation and ground improvement works. Though determined in an empirical manner, it is imperative to study SN to understand its relation with other aggregate properties like fineness modulus (FM), and strength and density properties of sandy soil. The present paper reports the findings of the study on the examination of the properties of sandy soil, as mentioned. Random numbers were generated to obtain the percent fineness on various sieve sizes, and fineness modulus and suitability numbers were predicted. Sand samples were collected from the field, and test samples were prepared to determine maximum density, minimum density and shear strength parameter φ against particular fineness modulus and corresponding suitability number Five samples of SN value of excellent (0-10) and three samples of SN value fair (20-30) were taken and relevant tests were done. The data obtained from the laboratory tests were statistically analyzed. Results show that with the increase of SN, the value of FM decreases. Within the SN value rated as excellent (0-10), there is a decreasing trend of φ for a higher value of SN. It is found that SN is dependent on various combinations of grain size properties like D10, D30, and D20, D50. Strong linear relationships were obtained between SN and FM (R²=.0.93) and between SN value and φ (R²=.94). Correlation equations are proposed to define relationships among SN, φ, and FM.

Keywords: density, fineness modulus, shear strength parameter, suitability number

Procedia PDF Downloads 81
20 Analyzing Factors Impacting COVID-19 Vaccination Rates

Authors: Dongseok Cho, Mitchell Driedger, Sera Han, Noman Khan, Mohammed Elmorsy, Mohamad El-Hajj

Abstract:

Since the approval of the COVID-19 vaccine in late 2020, vaccination rates have varied around the globe. Access to a vaccine supply, mandated vaccination policy, and vaccine hesitancy contribute to these rates. This study used COVID-19 vaccination data from Our World in Data and the Multilateral Leaders Task Force on COVID-19 to create two COVID-19 vaccination indices. The first index is the Vaccine Utilization Index (VUI), which measures how effectively each country has utilized its vaccine supply to doubly vaccinate its population. The second index is the Vaccination Acceleration Index (VAI), which evaluates how efficiently each country vaccinated its population within its first 150 days. Pearson correlations were created between these indices and country indicators obtained from the World Bank. The results of these correlations identify countries with stronger health indicators, such as lower mortality rates, lower age dependency ratios, and higher rates of immunization to other diseases, displaying higher VUI and VAI scores than countries with lesser values. VAI scores are also positively correlated to Governance and Economic indicators, such as regulatory quality, control of corruption, and GDP per capita. As represented by the VUI, proper utilization of the COVID-19 vaccine supply by country is observed in countries that display excellence in health practices. A country’s motivation to accelerate its vaccination rates within the first 150 days of vaccinating, as represented by the VAI, was largely a product of the governing body’s effectiveness and economic status, as well as overall excellence in health practises.

Keywords: data mining, Pearson correlation, COVID-19, vaccination rates and hesitancy

Procedia PDF Downloads 83
19 Attitude and Perception of Multiple Sclerosis Patients toward Exercise

Authors: Ali Fuad Ashour

Abstract:

Introduction: Contrary to the common belief that physical training for multiple sclerosis (MS) patients might exacerbate fatigue and provoke other symptoms of the illness, it is now widely accepted that exercise can be actually beneficial in terms of activities of daily living, reduced fatigue, and improved quality of life. The aim of this study was to assess the attitude of MS patients toward exercise. Methodology: 112 MS patients who were recruited from the local community participated in this study. We utilised a self-developed questionnaire targeting attitudes and perceptions of MS patients towards physical exercise. The questionnaire was piloted and tested for validity and reliability. Results: Before being diagnosed with MS, 49.9% of our MS patients’ respondents used to engage in different types of physical activities and sports, namely aerobics/walking (35.3%), stretching exercise (18.7%), and strengthening exercise (11.4%). After being diagnosed with MS, 40.8% of our sample showed determination to remain physically active. The interest in sports activities was consistent after the diagnoses with MS and included aerobics/walking (33.8%), stretching exercise (22.6%), and strengthening exercise (19.7%). Discussion: The Kuwaiti respondents thought that lack of encouragement was the main reason for them not exercise. Aptly put, if they try to exercise, they will be discouraged by the loved ones lest the worse happens. On the other side, British patients are generally aware of the benefits of physical and mental health-promoting activities; they can seek help from a wide range of professionals and are more actively involved in the management of their condition. It is therefore important that the benefits of physical activity are promoted among MS patients, and that attitude towards MS and MS patients is changed through education.

Keywords: perception, multiple sclerosis, exercise, physical training

Procedia PDF Downloads 125
18 Vermicomposting Amended With Microorganisms and Biochar: Phytopathogen Resistant Seedbeds for Vegetables and Heavy Metal Polluted Waste Treatment

Authors: Fuad Ameen, Ali A. Al-Homaidan

Abstract:

Biochar can be used in numerous biotechnological applications due to its properties to adsorb beneficial nutrients and harmful pollutants. Objectives: We aimed to treat heavy metal polluted organic wastes using vermicomposting process and produce a fertilizer that can be used in agriculture. We improved the process by adding biochar as well as microbial inoculum and biomass into household waste or sewage sludge before vermicomposting. The earthworm Eisenia fetida used in vermicomposting was included to accumulate heavy metals, biochar to adsorb heavy metals, and the microalga Navicula sp. or the mangrove fungus Acrophialophora sp. to promote plant growth in the final product used as a seedbed for Solanaceae vegetables. We carried out vermicomposting treatments to see the effect of different amendments. Final compost quality was analyzed for maturity. The earthworms were studied for their vitality, heavy metal accumulation, and metallothionein protein content to verify their role in the process. The compost was used as a seedbed for vegetables that were inoculated with a phytopathogen Pythium sp. known to cause root rot and destroy seeds. Compost as seedbed promoted plant growth and reduced disease symptoms in leaves. In the treatment where E. fetida, 6% biochar, and Navicula sp. had been added, 90% of the seeds germinated, while less than 20% germinated in the control treatment. The experimental plants had acquired resistance against Pythium sp. The metagenomic profile of microbial communities will be reported.

Keywords: organic wastes, vermicomposting process, biochar, mangrove fungus

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17 Artificial Intelligence Based Online Monitoring System for Cardiac Patient

Authors: Syed Qasim Gilani, Muhammad Umair, Muhammad Noman, Syed Bilawal Shah, Aqib Abbasi, Muhammad Waheed

Abstract:

Cardiovascular Diseases(CVD's) are the major cause of death in the world. The main reason for these deaths is the unavailability of first aid for heart failure. In many cases, patients die before reaching the hospital. We in this paper are presenting innovative online health service for Cardiac Patients. The proposed online health system has two ends. Users through device developed by us can communicate with their doctor through a mobile application. This interface provides them with first aid.Also by using this service, they have an easy interface with their doctors for attaining medical advice. According to the proposed system, we developed a device called Cardiac Care. Cardiac Care is a portable device which a patient can use at their home for monitoring heart condition. When a patient checks his/her heart condition, Electrocardiogram (ECG), Blood Pressure(BP), Temperature are sent to the central database. The severity of patients condition is checked using Artificial Intelligence Algorithm at the database. If the patient is suffering from the minor problem, our algorithm will suggest a prescription for patients. But if patient's condition is severe, patients record is sent to doctor through the mobile Android application. Doctor after reviewing patients condition suggests next step. If a doctor identifies the patient condition as critical, then the message is sent to the central database for sending an ambulance for the patient. Ambulance starts moving towards patient for bringing him/her to hospital. We have implemented this model at prototype level. This model will be life-saving for millions of people around the globe. According to this proposed model patients will be in contact with their doctors all the time.

Keywords: cardiovascular disease, classification, electrocardiogram, blood pressure

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