Artificial Intelligence Techniques applied to Biomedical Patterns

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Ignition Delay Correlation for a Direct Injection Diesel Engine Fuelled with Automotive Diesel and Water Diesel Emulsion

Most of ignition delay correlations studies have been developed in a constant volume bombs which cannot capture the dynamic variation in pressure and temperature during the ignition delay as in real engines. Watson, Assanis et. al. and Hardenberg and Hase correlations have been developed based on experimental data of diesel engines. However, they showed limited predictive ability of ignition delay when compared to experimental results. The objective of the study was to investigate the dependency of ignition delay time on engine brake power. An experimental investigation of the effect of automotive diesel and water diesel emulsion fuels on ignition delay under steady state conditions of a direct injection diesel engine was conducted. A four cylinder, direct injection naturally aspirated diesel engine was used in this experiment over a wide range of engine speeds and two engine loads. The ignition delay experimental data were compared with predictions of Assanis et. al. and Watson ignition delay correlations. The results of the experimental investigation were then used to develop a new ignition delay correlation. The newly developed ignition delay correlation has shown a better agreement with the experimental data than Assanis et. al. and Watson when using automotive diesel and water diesel emulsion fuels especially at low to medium engine speeds at both loads. In addition, the second derivative of cylinder pressure which is the most widely used method in determining the start of combustion was investigated.

An Improved Resource Discovery Approach Using P2P Model for Condor: A Grid Middleware

Resource Discovery in Grids is critical for efficient resource allocation and management. Heterogeneous nature and dynamic availability of resources make resource discovery a challenging task. As numbers of nodes are increasing from tens to thousands, scalability is essentially desired. Peer-to-Peer (P2P) techniques, on the other hand, provide effective implementation of scalable services and applications. In this paper we propose a model for resource discovery in Condor Middleware by using the four axis framework defined in P2P approach. The proposed model enhances Condor to incorporate functionality of a P2P system, thus aim to make Condor more scalable, flexible, reliable and robust.

A Short Form of the Taiwan Health Literacy Scale (THLS) for Chinese-Speaking Adults

The Taiwan Health Literacy Scale (THLS) was developed to cope with the need of measuring heath literacy of Chinese-speaking adults in Taiwan. Although the scale was proven having good reliability and validity, it was not popularly adopted by the practitioners due to the length, and the time required completing. Based on the THLS, this research further invited healthcare professionals to review the original scale for a possible shorten work. Under the logic of THLS, the research adopted an analytic hierarchy process technique to consolidate the healthcare experts- assessments to shorten the original scale. There are fifteen items out of the original 66 items were identified having higher loadings. Confirmed by the experts and passed a pilot test with 40 undergraduate students, a short form of THLS is then introduced. This research then used 839 samples from the major cities of the Hua-lien county in the eastern part of Taiwan to test the reliability and validity of this new scale. The reliability of the scale is high and acceptable. The current scale is also highly correlated with the original, of which provide evidence for the validity of the scale.

Throughput Analysis over Power Line Communication Channel in an Electric Noisy Scenario

Powerline Communications –PLC– as an alternative method for broadband networking, has the advantage of transmitting over channels already used for electrical distribution or even transmission. But these channels have been not designed with usual wired channels requirements for broadband applications such as stable impedance or known attenuation, and the network have to reject noises caused by electrical appliances that share the same channel. Noise control standards are difficult to complain or simply do not exist on Latin-American environments. This paper analyzes PLC throughput for home connectivity by probing noisy channel scenarios in a PLC network and the statistical results are shown.

Generalized Predictive Control of Batch Polymerization Reactor

This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.

Development of a Microsensor to Minimize Post Cataract Surgery Complications

This paper presents design and characterization of a microaccelerometer designated for integration into cataract surgical probe to detect hardness of different eye tissues during cataract surgery. Soft posterior lens capsule of eye can be easily damaged in comparison with hard opaque lens since the surgeon can not see directly behind cutting needle during the surgery. Presence of microsensor helps the surgeon to avoid rupturing posterior lens capsule which if occurs leads to severe complications such as glaucoma, infection, or even blindness. The microsensor having overall dimensions of 480 μm x 395 μm is able to deliver significant capacitance variations during encountered vibration situations which makes it capable to distinguish between different types of tissue. Integration of electronic components on chip ensures high level of reliability and noise immunity while minimizes space and power requirements. Physical characteristics and results on performance testing, proves integration of microsensor as an effective tool to aid the surgeon during this procedure.

MHD Falkner-Skan Boundary Layer Flow with Internal Heat Generation or Absorption

This paper examines the forced convection flow of incompressible, electrically conducting viscous fluid past a sharp wedge in the presence of heat generation or absorption with an applied magnetic field. The system of partial differential equations governing Falkner - Skan wedge flow and heat transfer is first transformed into a system of ordinary differential equations using similarity transformations which is later solved using an implicit finite - difference scheme, along with quasilinearization technique. Numerical computations are performed for air (Pr = 0.7) and displayed graphically to illustrate the influence of pertinent physical parameters on local skin friction and heat transfer coefficients and, also on, velocity and temperature fields. It is observed that the magnetic field increases both the coefficients of skin friction and heat transfer. The effect of heat generation or absorption is found to be very significant on heat transfer, but its effect on the skin friction is negligible. Indeed, the occurrence of overshoot is noticed in the temperature profiles during heat generation process, causing the reversal in the direction of heat transfer.

Talent in Autism: Cognitive Style based on Weak Central Coherence and Special Sensory Characteristics in State of Kuwait: Case Study

The study aimed to identify the nature of autistic talent, the manifestations of their weak central coherence, and their sensory characteristics. The case study consisted of four talented autistic males. Two of them in drawing, one in clay formation and one in jigsaw puzzle. Tools of data collection were Group Embedded Figures Test, Block Design Test, Sensory Profile Checklist Revised, Interview forms and direct observation. Results indicated that talent among autistics emerges in limited domain and being extraordinary for each case. Also overlapping construction properties. Indeed, they show three perceptual aspects of weak central coherence: The weak in visual spatial-constructional coherence, the weak in perceptual coherence and the weak in verbal – semantic coherence. Moreover, the majority of the study cases used the three strategies of weak central coherence (segmentation, obliqueness and rotation). As for the sensory characteristics, all study cases have numbers of that characteristics that especially emerges in the visual system.

Incidence of Chronic Disease and Lipid Profile in Veteran Rugby Athletes

Recently, the health of retired National Football League players, particularly lineman has been investigated. A number of studies have reported increased cardiometabolic risk, premature cardiovascular disease and incidence of type 2 diabetes. Rugby union players have somatotypes very similar to National Football League players which suggests that rugby players may have similar health risks. The International Golden Oldies World Rugby Festival (GORF) provided a unique opportunity to investigate the demographics of veteran rugby players. METHODOLOGIES: A cross-sectional, observational study was completed using an online web-based questionnaire that consisted of medical history and physiological measures. Data analysis was completed using a one sample t-test (50yrs) and Chi-square test. RESULTS: A total of 216 veteran rugby competitors (response rate = 6.8%) representing 10 countries, aged 35-72 yrs (mean 51.2, S.D. ±8.0), participated in the online survey. As a group, the incidence of current smokers was low at 8.8% (avg 72.4 cigs/wk) whilst the percentage consuming alcohol was high (93.1% (avg 11.2 drinks/wk). Competitors reported the following top six chronic diseases/disorders; hypertension (18.6%), arthritis (OA/RA, 11.5%), asthma (9.3%), hyperlipidemia (8.2%), diabetes (all types, 7.5%) and gout (6%), there were significant differences between groups with regard to cancer (all types) and migraines. When compared to the Australian general population (Australian Bureau of Statistics data, n=18,000), GORF competitors had a significantly lower incidence of anxiety (p

Reutilization of Organic and Peat Soils by Deep Cement Mixing

Limited infrastructure development on peats and organic soils is a serious geotechnical issues common to many countries of the world especially Malaysia which distributed 1.5 mill ha of those problematic soil. These soils have high water content and organic content which exhibit different mechanical properties and may also change chemically and biologically with time. Constructing structures on peaty ground involves the risk of ground failure and extreme settlement. Nowdays, much efforts need to be done in making peatlands usable for construction due to increased landuse. Deep mixing method employing cement as binders, is generally used as measure again peaty/ organic ground failure problem. Where the technique is widely adopted because it can improved ground considerably in a short period of time. An understanding of geotechnical properties as shear strength, stiffness and compressibility behavior of these soils was requires before continues construction on it. Therefore, 1- 1.5 meter peat soil sample from states of Johor and an organic soil from Melaka, Malaysia were investigated. Cement were added to the soil in the pre-mixing stage with water cement ratio at range 3.5,7,14,140 for peats and 5,10,30 for organic soils, essentially to modify the original soil textures and properties. The mixtures which in slurry form will pour to polyvinyl chloride (pvc) tube and cured at room temperature 250C for 7,14 and 28 days. Laboratory experiments were conducted including unconfined compressive strength and bender element , to monitor the improved strength and stiffness of the 'stabilised mixed soils'. In between, scanning electron miscroscopic (SEM) were observations to investigate changes in microstructures of stabilised soils and to evaluated hardening effect of a peat and organic soils stabilised cement. This preliminary effort indicated that pre-mixing peat and organic soils contributes in gaining soil strength while help the engineers to establish a new method for those problematic ground improvement in further practical and long term applications.

An Alternative Method for Generating Almost Infinite Sequence of Gaussian Variables

Most of the well known methods for generating Gaussian variables require at least one standard uniform distributed value, for each Gaussian variable generated. The length of the random number generator therefore, limits the number of independent Gaussian distributed variables that can be generated meanwhile the statistical solution of complex systems requires a large number of random numbers for their statistical analysis. We propose an alternative simple method of generating almost infinite number of Gaussian distributed variables using a limited number of standard uniform distributed random numbers.

Intellectual Capital Research through Corporate Social Responsibility: (Re) Constructing the Agenda

The business strategy of any company wanting to be competitive on the market should be designed around the concept of intangibles, with an increasingly decisive role in knowledge transfer of the biggest corporations. Advancing the research in these areas, this study integrates the two approaches, emphasizing the relationships between the components of intellectual capital and corporate social responsibility. The three dimensions of intellectual capital in terms of sustainability requirements are debated. The paper introduces the concept of sustainable intellectual capital and debates it within an assessment model designed on the base of key performance indicators. The results refer to the assessment of possible ways for including the information on intellectual capital and corporate responsibility within the corporate strategy. The conclusions enhance the need for companies to be ready to support the integration of this type of information the knowledge transfer process, in order to develop competitive advantage on the market.

A Novel Zero Voltage Transition Synchronous Buck Converter for Portable Application

This paper proposes a zero-voltage transition (ZVT) PWM synchronous buck converter, which is designed to operate at low output voltage and high efficiency typically required for portable systems. To make the DC-DC converter efficient at lower voltage, synchronous converter is an obvious choice because of lower conduction loss in the diode. The high-side MOSFET is dominated by the switching losses and it is eliminated by the soft switching technique. Additionally, the resonant auxiliary circuit designed is also devoid of the switching losses. The suggested procedure ensures an efficient converter. Theoretical analysis, computer simulation, and experimental results are presented to explain the proposed schemes.

A Study on Early Prediction of Fault Proneness in Software Modules using Genetic Algorithm

Fault-proneness of a software module is the probability that the module contains faults. To predict faultproneness of modules different techniques have been proposed which includes statistical methods, machine learning techniques, neural network techniques and clustering techniques. The aim of proposed study is to explore whether metrics available in the early lifecycle (i.e. requirement metrics), metrics available in the late lifecycle (i.e. code metrics) and metrics available in the early lifecycle (i.e. requirement metrics) combined with metrics available in the late lifecycle (i.e. code metrics) can be used to identify fault prone modules using Genetic Algorithm technique. This approach has been tested with real time defect C Programming language datasets of NASA software projects. The results show that the fusion of requirement and code metric is the best prediction model for detecting the faults as compared with commonly used code based model.

Analytical Modelling of Average Bond Stress within the Anchorage of Tensile Reinforcing Bars in Reinforced Concrete Members

A reliable estimate of the average bond stress within the anchorage of steel reinforcing bars in tension is critically important for the design of reinforced concrete member. This paper describes part of a recently completed experimental research program in the Centre for Infrastructure Engineering and Safety (CIES) at the University of New South Wales, Sydney, Australia aimed at assessing the effects of different factors on the anchorage requirements of modern high strength steel reinforcing bars. The study found that an increase in the anchorage length and bar diameter generally leads to a reduction of the average ultimate bond stress. By the extension of a well established analytical model of bond and anchorage, it is shown here that the differences in the average ultimate bond stress for different anchorage lengths is associated with the variable degree of plastic deformation in the tensile zone of the concrete surrounding the bar.

The Best Efficiency Point of the Performance of Solar Cell Panel System for Pumping Water at Various Lifting Heads Using 100 W Motor- Pump Unit

This study was carried out experimentally and analytically about the performance of solar cell panel system for operating the pump coupled by dc-motor. The solar cell panel with total area 1.9848 m2 consists of three modules of 80 Wp each. The small centrifugal pump powered by dc-motor is operated to lift water from 1m to 7m heads in sequence and gives the amount of water pumped over the whole day from 08.00 to 16.00 h are 11988, 10851, 8874, 7695, 5760, 3600, 2340 L/d respectively. The hourly global solar radiation during the day is an average of 506 W/m2. This study also presents the I-V characteristics of the panel at global radiations 200, 400, 600, 800 and 1000 W/m2 matched with the operation of the pump at the above lifting heads. It proves that the only solar radiations 800 and 1000 W/m2 could provide lifting head from 1m to 7m. The analysis shows the best efficiency point of the performance of solar cell panel system occurs at the pumping head 2.89 m.

Local Perspectives on Climate Change Mitigation and Sustainability of Clean Development Mechanism (CDM) Project: A Case Study in Thailand

Global climate change has become the preeminent threat to human security in the 21st century. From mitigation perspective, this study aims to evaluate the performance of biogas renewable project under clean development mechanism activities (namely Korat-Waste-to-Energy) in Thailand and to assess local perceptions towards the significance of climate change mitigation and sustainability of such project in their community. Questionnaire was developed based on the national sustainable development criteria and was distributed among systematically selected households within project boundaries (n=260). Majority of the respondents strongly agreed with the reduction of odor problems (81%) and air pollution (76%). However, they were unsure about greenhouse gas reduction from such project and ignorant about the key issues of climate change. A lesson learned suggested that there is a need to further investigate the possible socio-psychological barriers may significantly shape public perception and understandings of climate change in the local context.

Employee Motivation Factors That Affect Job Performance of Suan Sunandha Rajabhat University Employee

The purpose of this research is to study motivation factors and also to study factors relation to job performance to compare motivation factors under the personal factor classification such as gender, age, income, educational level, marital status, and working duration; and to study the relationship between Motivation Factors and Job Performance with job satisfactions. The sample groups utilized in this research were 400 Suan Sunandha Rajabhat University employees. This research is a quantitative research using questionnaires as research instrument. The statistics applied for data analysis including percentage, mean, and standard deviation. In addition, the difference analysis was conducted by t value computing, one-way analysis of variance and Pearson’s correlation coefficient computing. The findings of the study results were as follows the findings showed that the aspects of job promotion and salary were at the moderate levels. Additionally, the findings also showed that the motivations that affected the revenue branch chiefs’ job performance were job security, job accomplishment, policy and management, job promotion, and interpersonal relation.

Relative Radiometric Correction of Cloudy Multitemporal Satellite Imagery

Repeated observation of a given area over time yields potential for many forms of change detection analysis. These repeated observations are confounded in terms of radiometric consistency due to changes in sensor calibration over time, differences in illumination, observation angles and variation in atmospheric effects. This paper demonstrates applicability of an empirical relative radiometric normalization method to a set of multitemporal cloudy images acquired by Resourcesat1 LISS III sensor. Objective of this study is to detect and remove cloud cover and normalize an image radiometrically. Cloud detection is achieved by using Average Brightness Threshold (ABT) algorithm. The detected cloud is removed and replaced with data from another images of the same area. After cloud removal, the proposed normalization method is applied to reduce the radiometric influence caused by non surface factors. This process identifies landscape elements whose reflectance values are nearly constant over time, i.e. the subset of non-changing pixels are identified using frequency based correlation technique. The quality of radiometric normalization is statistically assessed by R2 value and mean square error (MSE) between each pair of analogous band.