Enabling Factors towards Safety Improvement for Industrialised Building System (IBS)

The utilisation of Industrial Building System (IBS) in construction industry will lead to a safe site condition since minimum numbers of workers are required to be on-site, timely material delivery, systematic component storage, reduction of construction material and waste. These matters are being promoted in the Construction Industry Master Plan (CIMP 2006-2015). However, the enabling factors of IBS that will foster a safer working environment are indefinite; on that basis a research has been conducted. The purpose of this paper is to discuss and identify the relevant factors towards safety improvement for IBS. A quantitative research by way of questionnaire surveys have been conducted to 314 construction companies. The target group was Grade 5 to Grade 7 contractors registered with Construction Industry Development Board (CIDB) which specialise in IBS. The findings disclosed seven factors linked to the safety improvement of IBS construction site in Malaysia. The factors were historical, economic, psychological, technical, procedural, organisational and the environmental factors. From the findings, a psychological factor ranked as the highest and most crucial factor contributing to safer IBS construction site. The psychological factor included the self-awareness and influences from workmates behaviour. Followed by organisational factors, where project management style will encourage the safety efforts. From the procedural factors, it was also found that training was one of the significant factors to improve safety culture of IBS construction site. Another important finding that formed as a part of the environmental factor was storage of IBS components, in which proper planning of the layout would able to contribute to a safer site condition. To conclude, in order to improve safety of IBS construction site, a welltrained and skilled workers are required for IBS projects, thus proper training is permissible and should be emphasised.

Intelligent System for Breast Cancer Prognosis using Multiwavelet Packets and Neural Network

This paper presents an approach for early breast cancer diagnostic by employing combination of artificial neural networks (ANN) and multiwaveletpacket based subband image decomposition. The microcalcifications correspond to high-frequency components of the image spectrum, detection of microcalcifications is achieved by decomposing the mammograms into different frequency subbands,, reconstructing the mammograms from the subbands containing only high frequencies. For this approach we employed different types of multiwaveletpacket. We used the result as an input of neural network for classification. The proposed methodology is tested using the Nijmegen and the Mammographic Image Analysis Society (MIAS) mammographic databases and images collected from local hospitals. Results are presented as the receiver operating characteristic (ROC) performance and are quantified by the area under the ROC curve.

A New Image Encryption Approach using Combinational Permutation Techniques

This paper proposes a new approach for image encryption using a combination of different permutation techniques. The main idea behind the present work is that an image can be viewed as an arrangement of bits, pixels and blocks. The intelligible information present in an image is due to the correlations among the bits, pixels and blocks in a given arrangement. This perceivable information can be reduced by decreasing the correlation among the bits, pixels and blocks using certain permutation techniques. This paper presents an approach for a random combination of the aforementioned permutations for image encryption. From the results, it is observed that the permutation of bits is effective in significantly reducing the correlation thereby decreasing the perceptual information, whereas the permutation of pixels and blocks are good at producing higher level security compared to bit permutation. A random combination method employing all the three techniques thus is observed to be useful for tactical security applications, where protection is needed only against a casual observer.

A Family Cars- Life Cycle Cost (LCC)-Oriented Hybrid Modelling Approach Combining ANN and CBR

Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.

Online Learning: Custom Design to Promote Learning for Multiple Disciplines

Today-s Wi Fi generation utilize the latest technology in their daily lives. Instructors at National University, the second largest non profit private institution of higher learning in California, are incorporating these new tools to modify their Online class formats to better accommodate these new skills in their distance education delivery modes. The University provides accelerated learning in a one-course per month format both Onsite and Online. Since there has been such a significant increase in Online classes over the past three years, and it is expected to grow even more over the over the next five years, Instructors cannot afford to maintain the status quo and not take advantage of these new options. It is at the discretion of the instructors which accessory they use and how comfortable and familiar they are with the technology. This paper explores the effects and summarizes students- comments of some of these new technological options which have been recently provided in order to make students- online learning experience more exciting and meaningful.

The Effect of Buckwheat (Fagopyrum esculentum Moench) Groats Addition to the Lard Diet on Antioxidant Parameters of Plasma and Selected Tissues in Wistar Rats

Recent studies demonstrated that high-fat diet increases oxidative stress in plasma and in a variety of tissues. Many researchers have been looking for natural products, which can reverse the effect of high fat diet. Recently, buckwheat is becoming common ingredient in functional food because of it properties. In study on buckwheat, it is known that, this plant plays roles as anti-oxidative, anti-inflammatory and anti-hypertensive. Nevertheless still little is known about buckwheat groats. The aim of this study was to investigate the effects of addition of buckwheat groats to the fat diet (30% lard), on some antioxidant and oxidant stress parameters in plasma and selected tissues in Wistar rats. The experiment was carried out with three months old male Wistar rats ca. 250g of body weight fed for 5 weeks with either a high-fat (30% of lard) diet or control diet, with or without addition of buckwheat groats. In plasma biochemistry and the activities of the antioxidant enzymes were measured selected tissues: glutathione peroxidase (GPX), catalase (CAT) and the levels of total and reduced glutathione (GSH), free thiol groups (pSH), antioxidant potential of plasma (FRAP) and oxidant stress indices - proteins carbonyl groups (CO) and malonyldialdehyde concentration (MDA). Activity of catalase (CAT) in plasma of rats was significantly increased in buckwheat groats groups and activity of GPx3 in plasma of rats was decreased in buckwheat groups as compared to control group. The reduced glutathione (GSH) in plasma of rats was significantly increased and protein CO was significantly decreased in buckwheat groups as compared to controls. The lowered concentration of GSH was found in serum of rats fed buckwheat groats addition but it accompanied in 7-fold increase in reduced-to-oxidized glutatione ratio, significant increase in HDL and decrease in nonHDL concentration. Conclusions: Buckwheat groats indicate a beneficial effect in inhibiting protein and lipid peroxidation in rats and improved lipid profile. These results suggest that buckwheat groats exert a significant antioxidant potential and may be used as normal food constituent to ameliorate the oxidant-induced damage in organism. 

Effect of Low Frequency Memory on High Power 12W LDMOS Transistors Intermodulation Distortion

The increasing demand for higher data rates in wireless communication systems has led to the more effective and efficient use of all allocated frequency bands. In order to use the whole bandwidth at maximum efficiency, one needs to have RF power amplifiers with a higher linear level and memory-less performance. This is considered to be a major challenge to circuit designers. In this thesis the linearity and memory are studied and examined via the behavior of the intermodulation distortion (IMD). A major source of the in-band distortion can be shown to be influenced by the out-of-band impedances presented at either the input or the output of the device, especially those impedances terminated the low frequency (IF) components. Thus, in order to regulate the in-band distortion, the out of-band distortion must be controllable. These investigations are performed on a 12W LDMOS device characterised at 2.1 GHz within a purpose built, high-power measurement system.

Multiple Organ Manifestation in Neonatal Lupus Erythematous (Report of Two Cases)

Neonatal lupus erythematous (NLE) is a rare disease marked by clinical characteristic and specific maternal autoantibody. Many cutaneous, cardiac, liver, and hematological manifestations could happen with affect of one organ or multiple. In this case, both babies were premature, low birth weight (LBW), small for gestational age (SGA) and born through caesarean section from a systemic lupus erythematous (SLE) mother. In the first case, we found a baby girl with dyspnea and grunting. Chest X ray showed respiratory distress syndrome (RDS) great I and echocardiography showed small atrial septal defect (ASD) and ventricular septal defect (VSD). She also developed anemia, thrombocytopenia, elevated C-reactive protein, hypoalbuminemia, increasing coagulation factors, hyperbilirubinemia, and positive blood culture of Klebsiella pneumonia. Anti-Ro/SSA and Anti-nRNP/sm were positive. Intravenous fluid, antibiotic, transfusion of blood, thrombocyte concentrate, and fresh frozen plasma were given. The second baby, male presented with necrotic tissue on the left ear and skin rashes, erythematous macula, athropic scarring, hyperpigmentation on all of his body with various size and facial haemorrhage. He also suffered from thrombocytopenia, mild elevated transaminase enzyme, hyperbilirubinemia, anti-Ro/SSA was positive. Intravenous fluid, methyprednisolone, intravenous immunoglobulin (IVIG), blood, and thrombocyte concentrate transfution were given. Two cases of neonatal lupus erythematous had been presented. Diagnosis based on clinical presentation and maternal auto antibody on neonate. Organ involvement in NLE can occur as single or multiple manifestations.

A New Approach for Predicting and Optimizing Weld Bead Geometry in GMAW

Gas Metal Arc Welding (GMAW) processes is an important joining process widely used in metal fabrication industries. This paper addresses modeling and optimization of this technique using a set of experimental data and regression analysis. The set of experimental data has been used to assess the influence of GMAW process parameters in weld bead geometry. The process variables considered here include voltage (V); wire feed rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate distance (D). The process output characteristics include weld bead height, width and penetration. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the GMAW process parameters. The objective is to determine a suitable set of process parameters that can produce desired bead geometry, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.

Hotel Design and Energy Consumption

A hotel mainly uses its energy on water heating, space heating, refrigeration, space cooling, cooking, lighting and other building services. A number of 4-5 stars hotels in Auckland city are selected for this study. Comparing with the energy used for others, the energy used for the internal space thermal control (e.g. internal space heating) is more closely related to the hotel building itself. This study not only investigates relationship between annual energy (and winter energy) consumptions and building design data but also relationships between winter extra energy consumption and building design data. This study is to identify the major design factors that significantly impact hotel energy consumption for improving the future hotel design for energy efficient.

Utilizing Adaptive Software to Enhance Information Management

The task of strategic information technology management is to focus on adapting technology to ensure competitiveness. A key factor for success in this sector is awareness and readiness to deploy new technologies and exploit the services they offer. Recently, the need for more flexible and dynamic user interfaces (UIs) has been recognized, especially in mobile applications. An ongoing research project (MOP), initiated by TUT in Finland, is looking at how mobile device UIs can be adapted for different needs and contexts. It focuses on examining the possibilities to develop adapter software for solving the challenges related to the UI and its flexibility in mobile devices. This approach has great potential for enhancing information transfer in mobile devices, and consequently for improving information management. The technology presented here could be one of the key emerging technologies in the information technology sector in relation to mobile devices and telecommunications.

Low Power and Less Area Architecture for Integer Motion Estimation

Full search block matching algorithm is widely used for hardware implementation of motion estimators in video compression algorithms. In this paper we are proposing a new architecture, which consists of a 2D parallel processing unit and a 1D unit both working in parallel. The proposed architecture reduces both data access power and computational power which are the main causes of power consumption in integer motion estimation. It also completes the operations with nearly the same number of clock cycles as compared to a 2D systolic array architecture. In this work sum of absolute difference (SAD)-the most repeated operation in block matching, is calculated in two steps. The first step is to calculate the SAD for alternate rows by a 2D parallel unit. If the SAD calculated by the parallel unit is less than the stored minimum SAD, the SAD of the remaining rows is calculated by the 1D unit. Early termination, which stops avoidable computations has been achieved with the help of alternate rows method proposed in this paper and by finding a low initial SAD value based on motion vector prediction. Data reuse has been applied to the reference blocks in the same search area which significantly reduced the memory access.

Implementation of Security Algorithms for u-Health Monitoring System

Data security in u-Health system can be an important issue because wireless network is vulnerable to hacking. However, it is not easy to implement a proper security algorithm in an embedded u-health monitoring because of hardware constraints such as low performance, power consumption and limited memory size and etc. To secure data that contain personal and biosignal information, we implemented several security algorithms such as Blowfish, data encryption standard (DES), advanced encryption standard (AES) and Rivest Cipher 4 (RC4) for our u-Health monitoring system and the results were successful. Under the same experimental conditions, we compared these algorithms. RC4 had the fastest execution time. Memory usage was the most efficient for DES. However, considering performance and safety capability, however, we concluded that AES was the most appropriate algorithm for a personal u-Health monitoring system.

Experimental Study of Adsorption Properties of Acid and Thermal Treated Bentonite from Tehran (Iran)

The Iranian bentonite was first characterized by Scanning Electron Microscopy (SEM), Inductively Coupled Plasma mass spectrometry (ICP-MS), X-ray fluorescence (XRF), X-ray Diffraction (XRD) and BET. The bentonite was then treated thermally between 150°C-250°C at 15min, 45min and 90min and also was activated chemically with different concentration of sulphuric acid (3N, 5N and 10N). Although the results of thermal activated-bentonite didn-t show any considerable changes in specific surface area and Cation Exchange Capacity (CEC), but the results of chemical treated bentonite demonstrated that such properties have been improved by acid activation process.

Comparison between Skyhook and Minimax Control Strategies for Semi-active Suspension System

This paper describes the development, modeling, and testing of skyhook and MiniMax control strategies of semi-active suspension. The control performances are investigated using Matlab/Simulink [1], with a two-degree-of-freedom quarter car semiactive suspension system model. The comparison and evaluation of control result are made using software-in-the-loop simulation (SILS) method. This paper also outlines the development of a hardware-inthe- loop simulation (HILS) system. The simulation results show that skyhook strategy can significantly reduce the resonant peak of body and provide improvement in vehicle ride comfort. Otherwise, MiniMax strategy can be employed to effectively improve drive safety of vehicle by influencing wheel load. The two strategies can be switched to control semi-active suspension system to fulfill different requirement of vehicle in different stages.

Metaheuristic Algorithms for Decoding Binary Linear Codes

This paper introduces two decoders for binary linear codes based on Metaheuristics. The first one uses a genetic algorithm and the second is based on a combination genetic algorithm with a feed forward neural network. The decoder based on the genetic algorithms (DAG) applied to BCH and convolutional codes give good performances compared to Chase-2 and Viterbi algorithm respectively and reach the performances of the OSD-3 for some Residue Quadratic (RQ) codes. This algorithm is less complex for linear block codes of large block length; furthermore their performances can be improved by tuning the decoder-s parameters, in particular the number of individuals by population and the number of generations. In the second algorithm, the search space, in contrast to DAG which was limited to the code word space, now covers the whole binary vector space. It tries to elude a great number of coding operations by using a neural network. This reduces greatly the complexity of the decoder while maintaining comparable performances.

Numerical Simulations of Cross-Flow around Four Square Cylinders in an In-Line Rectangular Configuration

A two-dimensional numerical simulation of crossflow around four cylinders in an in-line rectangular configuration is studied by using the lattice Boltzmann method (LBM). Special attention is paid to the effect of the spacing between the cylinders. The Reynolds number ( Re ) is chosen to be e 100 R = and the spacing ratio L / D is set at 0.5, 1.5, 2.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 and 10.0. Results show that, as in the case of four cylinders in an inline rectangular configuration , flow fields show four different features depending on the spacing (single square cylinder, stable shielding flow, wiggling shielding flow and a vortex shedding flow) are observed in this study. The effects of spacing ratio on physical quantities such as mean drag coefficient, Strouhal number and rootmean- square value of the drag and lift coefficients are also presented. There is more than one shedding frequency at small spacing ratios. The mean drag coefficients for downstream cylinders are less than that of the single cylinder for all spacing ratios. The present results using the LBM are compared with some existing experimental data and numerical studies. The comparison shows that the LBM can capture the characteristics of the bluff body flow reasonably well and is a good tool for bluff body flow studies.

Independent Design of Multi-loop PI/PID Controllers for Multi-delay Processes

The interactions between input/output variables are a very common phenomenon encountered in the design of multi-loop controllers for interacting multivariable processes, which can be a serious obstacle for achieving a good overall performance of multiloop control system. To overcome this impediment, the decomposed dynamic interaction analysis is proposed by decomposing the multiloop control system into a set of n independent SISO systems with the corresponding effective open-loop transfer function (EOTF) within the dynamic interactions embedded explicitly. For each EOTF, the reduced model is independently formulated by using the proposed reduction design strategy, and then the paired multi-loop proportional-integral-derivative (PID) controller is derived quite simply and straightforwardly by using internal model control (IMC) theory. This design method can easily be implemented for various industrial processes because of its effectiveness. Several case studies are considered to demonstrate the superior of the proposed method.

Methods for Better Assessment of Fatigue and Deterioration in Bridges and Other Steel or Concrete Constructions

Large metal and concrete structures suffer by various kinds of deterioration, and accurate prediction of the remaining life is important. This paper informs about two methods for its assessment. One method, suitable for steel bridges and other constructions exposed to fatigue, monitors the loads and damage accumulation using information systems for the operation and the finite element model of the construction. In addition to the operation load, the dead weight of the construction and thermal stresses can be included into the model. The second method is suitable for concrete bridges and other structures, which suffer by carbonatation and other degradation processes, driven by diffusion. The diffusion constant, important for the prediction of future development, can be determined from the depth-profile of pH, obtained by pH measurement at various depths. Comparison with measurements on real objects illustrates the suitability of both methods.

Analysis of a Population of Diabetic Patients Databases with Classifiers

Data mining can be called as a technique to extract information from data. It is the process of obtaining hidden information and then turning it into qualified knowledge by statistical and artificial intelligence technique. One of its application areas is medical area to form decision support systems for diagnosis just by inventing meaningful information from given medical data. In this study a decision support system for diagnosis of illness that make use of data mining and three different artificial intelligence classifier algorithms namely Multilayer Perceptron, Naive Bayes Classifier and J.48. Pima Indian dataset of UCI Machine Learning Repository was used. This dataset includes urinary and blood test results of 768 patients. These test results consist of 8 different feature vectors. Obtained classifying results were compared with the previous studies. The suggestions for future studies were presented.