The Data Mining usage in Production System Management

The paper gives the pilot results of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. The simulation models of manufacturing systems have been developed to obtain the necessary data about production. The authors have developed the way of storing data obtained from the simulation models in the data warehouse. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The new knowledge has been applied to production management system. Gained knowledge has been tested on simulation models of the production system. An important benefit of the project has been proposal of the new methodology. This methodology is focused on data mining from the databases that store operational data about the production process.

Numerical Investigation of Flow Patterns and Thermal Comfort in Air-Conditioned Lecture Rooms

The present paper was concerned primarily with the analysis, simulation of the air flow and thermal patterns in a lecture room. The paper is devoted to numerically investigate the influence of location and number of ventilation and air conditioning supply and extracts openings on air flow properties in a lecture room. The work focuses on air flow patterns, thermal behaviour in lecture room where large number of students. The effectiveness of an air flow system is commonly assessed by the successful removal of sensible and latent loads from occupants with additional of attaining air pollutant at a prescribed level to attain the human thermal comfort conditions and to improve the indoor air quality; this is the main target during the present paper. The study is carried out using computational fluid dynamics (CFD) simulation techniques as embedded in the commercially available CFD code (FLUENT 6.2). The CFD modelling techniques solved the continuity, momentum and energy conservation equations in addition to standard k – ε model equations for turbulence closure. Throughout the investigations, numerical validation is carried out by way of comparisons of numerical and experimental results. Good agreement is found among both predictions.

A Visual Educational Modeling Language to Help Teachers in Learning Scenario Design

The success of an e-learning system is highly dependent on the quality of its educational content and how effective, complete, and simple the design tool can be for teachers. Educational modeling languages (EMLs) are proposed as design languages intended to teachers for modeling diverse teaching-learning experiences, independently of the pedagogical approach and in different contexts. However, most existing EMLs are criticized for being too abstract and too complex to be understood and manipulated by teachers. In this paper, we present a visual EML that simplifies the process of designing learning scenarios for teachers with no programming background. Based on the conceptual framework of the activity theory, our resulting visual EML focuses on using Domainspecific modeling techniques to provide a pedagogical level of abstraction in the design process.

Roundabout Optimal Entry and Circulating Flow Induced by Road Hump

Roundabout work on the principle of circulation and entry flows, where the maximum entry flow rates depend largely on circulating flow bearing in mind that entry flows must give away to circulating flows. Where an existing roundabout has a road hump installed at the entry arm, it can be hypothesized that the kinematics of vehicles may prevent the entry arm from achieving optimum performance. Road humps are traffic calming devices placed across road width solely as speed reduction mechanism. They are the preferred traffic calming option in Malaysia and often used on single and dual carriageway local routes. The speed limit on local routes is 30mph (50 km/hr). Road humps in their various forms achieved the biggest mean speed reduction (based on a mean speed before traffic calming of 30mph) of up to 10mph or 16 km/hr according to the UK Department of Transport. The underlying aim of reduced speed should be to achieve a 'safe' distribution of speeds which reflects the function of the road and the impacts on the local community. Constraining safe distribution of speeds may lead to poor drivers timing and delayed reflex reaction that can probably cause accident. Previous studies on road hump impact have focused mainly on speed reduction, traffic volume, noise and vibrations, discomfort and delay from the use of road humps. The paper is aimed at optimal entry and circulating flow induced by road humps. Results show that roundabout entry and circulating flow perform better in circumstances where there is no road hump at entrance.

Modeling of Fluid Flow in 2D Triangular, Sinusoidal, and Square Corrugated Channels

The main focus of the work was concerned with hydrodynamic and thermal analysis of the plate heat exchanger channel with corrugation patterns suggested to be triangular, sinusoidal, and square corrugation. This study was to numerically model and validate the triangular corrugated channel with dimensions/parameters taken from open literature, and then model/analyze both sinusoidal, and square corrugated channel referred to the triangular model. Initially, 2D modeling with local extensive analysis for triangular corrugated channel was carried out. By that, all local pressure drop, wall shear stress, friction factor, static temperature, heat flux, Nusselt number, and surface heat coefficient, were analyzed to interpret the hydrodynamic and thermal phenomena occurred in the flow. Furthermore, in order to facilitate confidence in this model, a comparison between the values predicted, and experimental results taken from literature for almost the same case, was done. Moreover, a holistic numerical study for sinusoidal and square channels together with global comparisons with triangular corrugation under the same condition, were handled. Later, a comparison between electric, and fluid cooling through varying the boundary condition was achieved. The constant wall temperature and constant wall heat flux boundary conditions were employed, and the different resulted Nusselt numbers as a consequence were justified. The results obtained can be used to come up with an optimal design, a 'compromise' between heat transfer and pressure drop.

Enhancing Cache Performance Based on Improved Average Access Time

A high performance computer includes a fast processor and millions bytes of memory. During the data processing, huge amount of information are shuffled between the memory and processor. Because of its small size and its effectiveness speed, cache has become a common feature of high performance computers. Enhancing cache performance proved to be essential in the speed up of cache-based computers. Most enhancement approaches can be classified as either software based or hardware controlled. The performance of the cache is quantified in terms of hit ratio or miss ratio. In this paper, we are optimizing the cache performance based on enhancing the cache hit ratio. The optimum cache performance is obtained by focusing on the cache hardware modification in the way to make a quick rejection to the missed line's tags from the hit-or miss comparison stage, and thus a low hit time for the wanted line in the cache is achieved. In the proposed technique which we called Even- Odd Tabulation (EOT), the cache lines come from the main memory into cache are classified in two types; even line's tags and odd line's tags depending on their Least Significant Bit (LSB). This division is exploited by EOT technique to reject the miss match line's tags in very low time compared to the time spent by the main comparator in the cache, giving an optimum hitting time for the wanted cache line. The high performance of EOT technique against the familiar mapping technique FAM is shown in the simulated results.

Promoting Mental and Spiritual Health among Postpartum Mothers to Extend Breastfeeding Period

The purpose of this study was to study postpartum breastfeeding mothers to determine the impact their psychosocial and spiritual dimensions play in promoting full-term (6 month duration) breastfeeding of their infants. Purposive and snowball sampling methods were used to identify and recruit the study's participants. A total of 23 postpartum mothers, who were breastfeeding within 6 weeks after giving birth, participated in this study. In-depth interviews combined with observations, participant focus groups, and ethnographic records were used for data collection. The Data were then analyzed using content analysis and typology. The results of this study illustrated that postpartum mothers experienced fear and worry that they would lack support from their spouse, family and peers, and that their infant would not get enough milk It was found that the main barrier mothers faced in breastfeeding to full-term was the difficulty of continuing to breastfeed when returning to work. 81.82% of the primiparous mothers and 91.67% of the non-primiparous mothers were able to breastfeed for the desired full-term of 6 months. Factors found to be related to breastfeeding for six months included 1) belief and faith in breastfeeding, 2) support from spouse and family members, 3) counseling from public health nurses and friends. The sample also provided evidence that religious principles such as tolerance, effort, love, and compassion to their infant, and positive thinking, were used in solving their physical, mental and spiritual problems.

Image Segmentation Based on Graph Theoretical Approach to Improve the Quality of Image Segmentation

Graph based image segmentation techniques are considered to be one of the most efficient segmentation techniques which are mainly used as time & space efficient methods for real time applications. How ever, there is need to focus on improving the quality of segmented images obtained from the earlier graph based methods. This paper proposes an improvement to the graph based image segmentation methods already described in the literature. We contribute to the existing method by proposing the use of a weighted Euclidean distance to calculate the edge weight which is the key element in building the graph. We also propose a slight modification of the segmentation method already described in the literature, which results in selection of more prominent edges in the graph. The experimental results show the improvement in the segmentation quality as compared to the methods that already exist, with a slight compromise in efficiency.

Computing Center Conditions for Non-analytic Vector Fields with Constant Angular Speed

We investigate the planar quasi-septic non-analytic systems which have a center-focus equilibrium at the origin and whose angular speed is constant. The system could be changed into an analytic system by two transformations, with the help of computer algebra system MATHEMATICA, the conditions of uniform isochronous center are obtained.

Cost and Productivity Experiences of Pakistan with Aggregate Learning Curve

The principal focus of this study is on the measurement and analysis of labor learnings in Pakistan. The study at the aggregate economy level focus on the labor productivity movements and at large-scale manufacturing level focus on the cost structure, with isolating the contribution of the learning curve. The analysis of S-shaped curve suggests that learnings are only below one half of aggregate learning curve and other half shows the retardation in learning, hence retardation in productivity movements. The study implies the existence of learning economies in term of cost reduction that is input cost per unit produced decreases by 0.51 percent every time the cumulative production output doubles.

Testing Database of Information System using Conceptual Modeling

This paper focuses on testing database of existing information system. At the beginning we describe the basic problems of implemented databases, such as data redundancy, poor design of database logical structure or inappropriate data types in columns of database tables. These problems are often the result of incorrect understanding of the primary requirements for a database of an information system. Then we propose an algorithm to compare the conceptual model created from vague requirements for a database with a conceptual model reconstructed from implemented database. An algorithm also suggests steps leading to optimization of implemented database. The proposed algorithm is verified by an implemented prototype. The paper also describes a fuzzy system which works with the vague requirements for a database of an information system, procedure for creating conceptual from vague requirements and an algorithm for reconstructing a conceptual model from implemented database.

Engagement Strategies for Stakeholder Management in New Technology Development in the Fertilizer Industry – A Conceptual Framework

Communication is becoming a significant tool to engage stakeholders since half of the century ago. In the recent years, there has been rapid growth of new technology developments. In tandem with such developments, there has been growing emphasis in communication strategies and management especially in determining the level of influence and management strategies among the said stakeholders on particular field. This paper presents a research conceptual framework focusing on stakeholder theories, communication and management strategies to be implied on the engagement of stakeholders of new technology developments of fertilizer industry in Malaysia. Framework espoused in this paper will provide insights into the various stakeholder theories and engagement strategies from different principal necessary for a successful introduction of new technology development in the above stated industry. The proposed framework has theoretical significance in filling the gap of the body of knowledge in the implementation of communication strategies in Malaysian fertilizer industry.

A Study of DSRC Radio Testbed under Heavy Channel Load

Dedicated Short Range Communication (DSRC) is a key enabling technology for the next generation of communication-based safety applications. One of the important problems for DSRC deployment is maintaining high performance under heavy channel load. Many studies focus on congestion control mechanisms for simulating hundreds of physical radios deployed on vehicles. The U.S. department of transportation-s (DOT) Intelligent Transportation Systems (ITS) division has a plan to chosen prototype on-board devices capable of transmitting basic “Here I am" safety messages to other vehicles. The devices will be used in an IntelliDrive safety pilot deployment of up to 3,000 vehicles. It is hard to log the information of 3,000 vehicles. In this paper we present the designs and issues related to the DSRC Radio Testbed under heavy channel load. The details not only include the architecture of DSRC Radio Testbed, but also describe how the Radio Interfere System is used to help for emulating the congestion radio environment.

Transportation and Physical Development around Kumasi, Ghana

This research explores the links between physical development and transportation infrastructure around Kumasi, Ghana. It utilizes census data as well as fieldwork and interviews carried out during July and December 2005. The results suggest that there is a weak association between transportation investments and physical development, and that recent housing has generally occurred in poorly accessible locations. Road investments have generally followed physical expansion rather than the reverse. Hence policies designed to manage the fast growth now occurring around Ghanaian cities should not focus exclusively on improving transportation infrastructure but also strengthening the underlying the traditional land management structures and the official land administrative institutions that operate within those structures.

Air Conditioning Energy Saving by Rooftop Greenery System in Subtropical Climate in Australia

The benefits of rooftop greenery systems (such as energy savings, reduction of greenhouse gas emission for mitigating climate change and maintaining sustainable development, indoor temperature control etc.) in buildings are well recognized, however there remains very little research conducted for quantifying the benefits in subtropical climates such as in Australia. This study mainly focuses on measuring/determining temperature profile and air conditioning energy savings by implementing rooftop greenery systems in subtropical Central Queensland in Australia. An experimental set-up was installed at Rockhampton campus of Central Queensland University, where two standard shipping containers (6m x 2.4m x 2.4m) were converted into small offices, one with green roof and one without. These were used for temperature, humidity and energy consumption data collection. The study found that an energy savings of up to 11.70% and temperature difference of up to 4°C can be achieved in March in subtropical Central Queensland climate in Australia. It is expected that more energy can be saved in peak summer days (December/February) as temperature difference between green roof and non-green roof is higher in December- February.

User Pattern Learning Algorithm based MDSS(Medical Decision Support System) Framework under Ubiquitous

In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Organizational Culture and Innovation Adoption/Generation: A Proposed Model for Architectural Firms

Organizational culture fosters innovation, and innovation is the main engine to be sustained within the uncertainty market. Like other countries, the construction industry significantly contributes to the economy, society and technology of Malaysia, yet, innovation is still considered slow compared to other industries such as manufacturing. Given the important role of an architect as the key player and the contributor of new ideas in the construction industry, there is a call to identify the issue and improve the current situation by focusing on the architectural firms. In addition, the existing studies tend to focus only on a few dimensions of organizational culture and very few studies consider whether innovation is being generated or adopted. Hence, the present research tends to fill in the gap by identifying the organizational cultures that foster or hinder innovation generation and/or innovation adoption, and propose a model of organizational culture and innovation generation and/or adoption.

RRNS-Convolutional Concatenated Code for OFDM based Wireless Communication with Direct Analog-to-Residue Converter

The modern telecommunication industry demands higher capacity networks with high data rate. Orthogonal frequency division multiplexing (OFDM) is a promising technique for high data rate wireless communications at reasonable complexity in wireless channels. OFDM has been adopted for many types of wireless systems like wireless local area networks such as IEEE 802.11a, and digital audio/video broadcasting (DAB/DVB). The proposed research focuses on a concatenated coding scheme that improve the performance of OFDM based wireless communications. It uses a Redundant Residue Number System (RRNS) code as the outer code and a convolutional code as the inner code. Here, a direct conversion of analog signal to residue domain is done to reduce the conversion complexity using sigma-delta based parallel analog-to-residue converter. The bit error rate (BER) performances of the proposed system under different channel conditions are investigated. These include the effect of additive white Gaussian noise (AWGN), multipath delay spread, peak power clipping and frame start synchronization error. The simulation results show that the proposed RRNS-Convolutional concatenated coding (RCCC) scheme provides significant improvement in the system performance by exploiting the inherent properties of RRNS.

Advanced Neural Network Learning Applied to Pulping Modeling

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Extracting Single Trial Visual Evoked Potentials using Selective Eigen-Rate Principal Components

In single trial analysis, when using Principal Component Analysis (PCA) to extract Visual Evoked Potential (VEP) signals, the selection of principal components (PCs) is an important issue. We propose a new method here that selects only the appropriate PCs. We denote the method as selective eigen-rate (SER). In the method, the VEP is reconstructed based on the rate of the eigen-values of the PCs. When this technique is applied on emulated VEP signals added with background electroencephalogram (EEG), with a focus on extracting the evoked P3 parameter, it is found to be feasible. The improvement in signal to noise ratio (SNR) is superior to two other existing methods of PC selection: Kaiser (KSR) and Residual Power (RP). Though another PC selection method, Spectral Power Ratio (SPR) gives a comparable SNR with high noise factors (i.e. EEGs), SER give more impressive results in such cases. Next, we applied SER method to real VEP signals to analyse the P3 responses for matched and non-matched stimuli. The P3 parameters extracted through our proposed SER method showed higher P3 response for matched stimulus, which confirms to the existing neuroscience knowledge. Single trial PCA using KSR and RP methods failed to indicate any difference for the stimuli.