Utilizing Dredged Sediment for Enhancing Growth of Eelgrass in Artificially Prepared Substrates

Dredged sediment (DS) was utilized as source of silt-clay and organic matter in artificially prepared eelgrass substrates with mountain sand (MS) as the sand media. Addition of DS showed improved growth of eelgrass in the mixed substrates. Increase in added DS up to 15% silt-clay showed increased shoot growth but additional DS in 20% silt-clay mixture didn-t result to further increase in eelgrass growth. Improved root establishment were also found for plants in pots with added DS as shown by the increased resistance to uprooting, increased number of rhizome nodes and longer roots. Results demonstrated that addition of DS may be beneficial to eelgrass up to a certain extent only and too much of it might be harmful to eelgrass plants.

AC Signals Estimation from Irregular Samples

The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.

Hydrogenation of Acetic Acid on Alumina-Supported Pt-Sn Catalysts

Three alumina-supported Pt-Sn catalysts have been prepared by means of co-impregnation and characterized by XRD and N2 adsorption. The influence of catalyst composition and reaction conditions on the conversion and selectivity were investigated in the hydrogenation of acetic acid in an isothermal integral fixed bed reactor. The experiments were performed on the temperature interval 468-548 K, liquid hourly space velocity (LHSV) of 0.3-0.7h-1, pressures between 1.0 and 5.0Mpa. A good compromise of 0.75%Pt-1.5%Sn can act as an optimized acetic acid hydrogenation catalyst, and the conversion and selectivity can be tuned through the variation of reaction conditions.

Fast and Accurate Reservoir Modeling: Genetic Algorithm versus DIRECT Method

In this paper, two very different optimization algorithms, Genetic and DIRECT algorithms, are used to history match a bottomhole pressure response for a reservoir with wellbore storage and skin with the best possible analytical model. No initial guesses are available for reservoir parameters. The results show that the matching process is much faster and more accurate for DIRECT method in comparison with Genetic algorithm. It is furthermore concluded that the DIRECT algorithm does not need any initial guesses, whereas Genetic algorithm needs to be tuned according to initial guesses.

M-Learning the Next Generation of Education in Cyberspace

The technology usages of high speed Internet leads to establish and start new era of online education. With the advancement of the information technology and communication systems new opportunities have been created. This leads universities to have various online education channels to meet the demand of different learners- needs. One of these channels is M-learning, which can be used to improve the online education environment. With using such mobile technology in learning both students and instructors can easily access educational courses anytime from anywhere. The paper first presents literature about mobile learning and to what extent this approach can be utilized to enhance the overall learning system. It provides a comparison between mobile learning and traditional elearning showing the wide array of benefits of the new generation of technology. The possible challenges and potential advantages of Mlearning in the online education system are also discussed.

Tidal Flow Patterns Near A Coastal Headland

Experimental investigations were carried out in the Manchester Tidal flow Facility (MTF) to study the flow patterns in the region around and adjacent to a hypothetical headland in tidal (oscillatory) ambient flow. The Planar laser-induced fluorescence (PLIF) technique was used for visualization, with fluorescent dye released at specific points around the headland perimeter and in its adjacent recirculation zone. The flow patterns can be generalized into the acceleration, stable flow and deceleration stages for each halfcycle, with small variations according to location, which are more distinct for low Keulegan-Carpenter number (KC) cases. Flow patterns in the mixing region are unstable and complex, especially in the recirculation zone. The flow patterns are in agreement with previous visualizations, and support previous results in steady ambient flow. It is suggested that the headland lee could be a viable location for siting of pollutant outfalls.

High Impedance Faults Detection Technique Based on Wavelet Transform

The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.

Application of Phase Change Materials (PCMs) in Maintaining Comfort Temperature inside an Automobile

This paper presents the modeling results of an innovative system for the temperature control in the interior compartment of a stationary automobile facing the solar energy from the sun. A very thin layer of PCM inside a pouch placed in the ceiling of the car in which the heating energy is absorbed and release with melting and solidification of phase change materials. As a result the temperature of the car interior is maintained in the comfort condition. The amount of required PCM has been calculated to be about 755 g. The PCM-temperature controlling system is simple and has a potential to be implemented as a practical solution to prevent undesirable heating of the automobile-s cabin.

Use of Magnetic Nanoparticles in Cancer Detection with MRI

Magnetic Nanoparticles (MNPs) have great potential to overcome many of the shortcomings of the present diagnostic and therapeutic approaches used in cancer diagnosis and treatment. This Literature review discusses the use of Magnetic Nanoparticles focusing mainly on Iron oxide based MNPs in cancer imaging using MRI.

Atomic Force Microscopy (AFM)Topographical Surface Characterization of Multilayer-Coated and Uncoated Carbide Inserts

In recent years, scanning probe atomic force microscopy SPM AFM has gained acceptance over a wide spectrum of research and science applications. Most fields focuses on physical, chemical, biological while less attention is devoted to manufacturing and machining aspects. The purpose of the current study is to assess the possible implementation of the SPM AFM features and its NanoScope software in general machining applications with special attention to the tribological aspects of cutting tool. The surface morphology of coated and uncoated as-received carbide inserts is examined, analyzed, and characterized through the determination of the appropriate scanning setting, the suitable data type imaging techniques and the most representative data analysis parameters using the MultiMode SPM AFM in contact mode. The NanoScope operating software is used to capture realtime three data types images: “Height", “Deflection" and “Friction". Three scan sizes are independently performed: 2, 6, and 12 μm with a 2.5 μm vertical range (Z). Offline mode analysis includes the determination of three functional topographical parameters: surface “Roughness", power spectral density “PSD" and “Section". The 12 μm scan size in association with “Height" imaging is found efficient to capture every tiny features and tribological aspects of the examined surface. Also, “Friction" analysis is found to produce a comprehensive explanation about the lateral characteristics of the scanned surface. Configuration of many surface defects and drawbacks has been precisely detected and analyzed.

Behavioral Analysis of Team Members in Virtual Organization based on Trust Dimension and Learning

Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

Quadratic Pulse Inversion Ultrasonic Imaging(QPI): A Two-Step Procedure for Optimization of Contrast Sensitivity and Specificity

We have previously introduced an ultrasonic imaging approach that combines harmonic-sensitive pulse sequences with a post-beamforming quadratic kernel derived from a second-order Volterra filter (SOVF). This approach is designed to produce images with high sensitivity to nonlinear oscillations from microbubble ultrasound contrast agents (UCA) while maintaining high levels of noise rejection. In this paper, a two-step algorithm for computing the coefficients of the quadratic kernel leading to reduction of tissue component introduced by motion, maximizing the noise rejection and increases the specificity while optimizing the sensitivity to the UCA is presented. In the first step, quadratic kernels from individual singular modes of the PI data matrix are compared in terms of their ability of maximize the contrast to tissue ratio (CTR). In the second step, quadratic kernels resulting in the highest CTR values are convolved. The imaging results indicate that a signal processing approach to this clinical challenge is feasible.

A Multilingual Virtual Simulated Patient Framework for Training Primary Health Care Students

This paper describes the Multilingual Virtual Simulated Patient framework. It has been created to train the social skills and testing the knowledge of primary health care medical students. The framework generates conversational agents which perform in serveral languages as virtual simulated patients that help to improve the communication and diagnosis skills of the students complementing their training process.

Design, Fabrication and Performance Evaluation of Mobile Engine-Driven Pneumatic Paddy Collector

A simple mobile engine-driven pneumatic paddy collector made of locally available materials using local manufacturing technology was designed, fabricated, and tested for collecting and bagging of paddy dried on concrete pavement. The pneumatic paddy collector had the following major components: radial flat bladed type centrifugal fan, power transmission system, bagging area, frame and the conveyance system. Results showed significant differences on the collecting capacity, noise level, and fuel consumption when rotational speed of the air mover shaft was varied. Other parameters such as collecting efficiency, air velocity, augmented cracked grain percentage, and germination rate were not significantly affected by varying rotational speed of the air mover shaft. The pneumatic paddy collector had a collecting efficiency of 99.33 % with a collecting capacity of 2685.00 kg/h at maximum rotational speed of centrifugal fan shaft of about 4200 rpm. The machine entailed an investment cost of P 62,829.25. The break-even weight of paddy was 510,606.75 kg/yr at a collecting cost of 0.11 P/kg of paddy. Utilizing the machine for 400 hours per year generated an income of P 23,887.73. The projected time needed to recover cost of the machine based on 2685 kg/h collecting capacity was 2.63 year.

Sustained Competitive Advantage: Strategic HRM Initiatives and Consequences in Indian Context

In the past few decades, researchers have witnessed a paradigm shift in Human Resource Management-from individual performance to organizational outcomes with the role of Human resource (HR) managers becoming increasingly significant to the organization. In such a context, it is important to examine HR practices from a strategic perspective on the sustained competitive advantage (SCA) of the organizations. The present study explores how Indian organisations look at their human resources strategically when faced with competitive environment. Also, it explores strategic initiatives being taken to manage human resources within the organisations and how these initiatives promote SCA in terms of enhancing the overall customer-centric delivery of goods and services.

Designing Ontology-Based Knowledge Integration for Preprocessing of Medical Data in Enhancing a Machine Learning System for Coding Assignment of a Multi-Label Medical Text

This paper discusses the designing of knowledge integration of clinical information extracted from distributed medical ontologies in order to ameliorate a machine learning-based multilabel coding assignment system. The proposed approach is implemented using a decision tree technique of the machine learning on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding that the use of medical ontologies improves the overall system performance.

Possibilistic Clustering Technique-Based Traffic Light Control for Handling Emergency Vehicle

A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good managementof the crossroad. In this paper, we develop a new approach based onthe technique of clustering and the graphical possibilistic fusionmodeling. So, the proposed model is elaborated in three phases. Thefirst one consists to decompose the environment into clusters,following by the fusion intra and inter clusters processes. Finally, wewill show some experimental results by simulation that proves theefficiency of our proposed approach.KeywordsTraffic light, Wireless sensor network, Controller,Possibilistic network/Bayesain network.

The Contribution of Growth Rate to the Pathogenicity of Candida spp.

Fungal infections are becoming more common and the range of susceptible individuals has expanded. While Candida albicans remains the most common infective species, other Candida spp. are becoming increasingly significant. In a range of large-scale studies of candidaemia between 1999 and 2006, about 52% of 9717 cases involved C. albicans, about 30% involved either C. glabrata or C. parapsilosis and less than 15% involved C. tropicalis, C. krusei or C. guilliermondii. However, the probability of mortality within 30 days of infection with a particular species was at least 40% for C. tropicalis, C. albicans, C. glabrata and C. krusei and only 22% for C. parapsilopsis. Clinical isolates of Candida spp. grew at rates ranging from 1.65 h-1 to 4.9 h-1. Three species (C. krusei, C. albicans and C. glabrata) had relatively high growth rates (μm > 4 h-1), C. tropicalis and C. dubliniensis grew moderately quickly (Ôëê 3 h-1) and C. parapsilosis and C. guilliermondii grew slowly (< 2 h-1). Based on these data, the log of the odds of mortality within 30 days of diagnosis was linearly related to μm. From this the underlying probability of mortality is 0.13 (95% CI: 0.10-0.17) and it increases by about 0.09 ± 0.02 for each unit increase in μm. Given that the overall crude mortality is about 0.36, the growth of Candida spp. approximately doubles the rate, consistent with the results of larger case-matched studies of candidaemia.

Lateral and Longitudinal Vibration of a Rotating Flexible Beam Coupled with Torsional Vibration of a Flexible Shaft

In this study, rotating flexible shaft-disk system having flexible beams is considered as a dynamic system. After neglecting nonlinear terms, torsional vibration of the shaft-disk system and lateral and longitudinal vibration of the flexible beam are still coupled through the motor speed. The system has three natural frequencies; the flexible shaft-disk system torsional natural frequency, the flexible beam lateral and longitudinal natural frequencies. Eigenvalue calculations show that while the shaft speed changes, torsional natural frequency of the shaft-disk system and the beam longitudinal natural frequency are not changing but the beam lateral natural frequency changes. Beam lateral natural frequency stays the same as the nonrotating beam lateral natural frequency ωb until the motor speed ωm is equal to ωb. After then ωb increases and remains equal to the motor speed ωm until the motor speed is equal to the shaft-disk system natural frequency ωT. Then the beam lateral natural frequency ωb becomes equal to the natural frequency ωT and stays same while the motor speed ωm is increased. Modal amplitudes and phase angles of the vibrations are also plotted against the motor speed ωm.

An Efficient MIPv6 Return Routability Scheme Based on Geometric Computing

IETF defines mobility support in IPv6, i.e. MIPv6, to allow nodes to remain reachable while moving around in the IPv6 internet. When a node moves and visits a foreign network, it is still reachable through the indirect packet forwarding from its home network. This triangular routing feature provides node mobility but increases the communication latency between nodes. This deficiency can be overcome by using a Binding Update (BU) scheme, which let nodes keep up-to-date IP addresses and communicate with each other through direct IP routing. To further protect the security of BU, a Return Routability (RR) procedure was developed. However, it has been found that RR procedure is vulnerable to many attacks. In this paper, we will propose a lightweight RR procedure based on geometric computing. In consideration of the inherent limitation of computing resources in mobile node, the proposed scheme is developed to minimize the cost of computations and to eliminate the overhead of state maintenance during binding updates. Compared with other CGA-based BU schemes, our scheme is more efficient and doesn-t need nonce tables in nodes.