Application of Pulse Doubling in Star-Connected Autotransformer Based 12-Pulse AC-DC Converter for Power Quality Improvement

This paper presents a pulse doubling technique in a 12-pulse ac-dc converter which supplies direct torque controlled motor drives (DTCIMD-s) in order to have better power quality conditions at the point of common coupling. The proposed technique increases the number of rectification pulses without significant changes in the installations and yields in harmonic reduction in both ac and dc sides. The 12-pulse rectified output voltage is accomplished via two paralleled six-pulse ac-dc converters each of them consisting of three-phase diode bridge rectifier. An autotransformer is designed to supply the rectifiers. The design procedure of magnetics is in a way such that makes it suitable for retrofit applications where a six-pulse diode bridge rectifier is being utilized. Independent operation of paralleled diode-bridge rectifiers, i.e. dc-ripple re-injection methodology, requires a Zero Sequence Blocking Transformer (ZSBT). Finally, a tapped interphase reactor is connected at the output of ZSBT to double the pulse numbers of output voltage up to 24 pulses. The aforementioned structure improves power quality criteria at ac mains and makes them consistent with the IEEE-519 standard requirements for varying loads. Furthermore, near unity power factor is obtained for a wide range of DTCIMD operation. A comparison is made between 6- pulse, 12-pulse, and proposed converters from view point of power quality indices. Results show that input current total harmonic distortion (THD) is less than 5% for the proposed topology at various loads.

Explanatory of Relationship between Learning Motivation and Learning Performance

In this paper, the relationship between learning motivation and learning performance is explored by using exchange theory. The relationship is concluded that external performance can raise learning motivation and then increase learning performance. The internal performance should be not completely neglected and the external performance should be not attached important excessively. The parents need self-study and must be also reeducated. The existing education must be improved in raise of internal performance. The incorrect learning thinking will mislead the students, parents, and educators of next generation, when the students obtain good learning performance in the learning environment with excess stimulants. Over operation of external performance will result abnormal learning thinking and violating learning goal. Learning is not only to obtain performance. Learning quality and learning performance will be limited as without learning motivation. The best learning motivation is, the best learning performance is. The learning for reward is not good for learning performance. Strategies of promoting life-long learning are including the encouraging for learner, establishment of good interaction learning environment, and the advertisement of the merit and the importance of life-long learning, which can let the learner with the correct learning motivation.

Nonlinear Seismic Dynamic Response of Continuous Curved Highway Viaducts with Different Bearing Supports

The results show that the bridge equipped with seismic isolation bearing system shows a high amount of energy dissipation. The purpose of the present study is to analyze the overall performance of continuous curved highway viaducts with different bearing supports, with an emphasis on the effectiveness of seismic isolation based on lead rubber bearing and hedge reaction force bearing system consisted of friction sliding bearing and rubber bearing. The bridge seismic performance has been evaluated on six different cases with six bearing models. The effects of the different arrangement of bearing on the deck superstructure displacements, the seismic damage at the bottom of the piers, movement track at the pier-s top and the total and strain energies absorbed by the structure are evaluated. In conclusion, the results provide sufficient evidence of the effectiveness on the use of seismic isolation on steel curved highway bridges.

Studying the Environmental Effects of using Biogas Energy in Iran

Presently and in line with the United Nations (EPA), human thinking system has shifted towards clean fuels so as to maintain a cleaner environment and to save our planet earth. One of the most successful studies in order to achieve new energies includes the use of animal wastes and their organic residues, and the result of these researches has been represented in the form of very simple and cheap methods called biogas technology. Biogas technology has developed a lot in the recent decades; its reason is the high cost of fossil fuels and the greater attention of countries to the environmental pollutions due to the consumption of this kind of fuels. IRAN is ready for the optimized application of renewable energies, having much enriched resources of this kind of energies; so a special place could be considered for it when making programs. The purpose of biogas technology is the recovery of energy and finally the protection of the environment, which is much appropriate for the third world farmers with respect to their technical abilities and economic potentials. Studies show that the production and consumption of biogas is appropriate and economic in IRAN, because of the high amount of waste in the agriculture sector, the significant amount of animal and human excrement production, the great volume of garbage produced and the most important the specific social, climatic and agricultural conditions in IRAN, in order to proceed towards the reduction of pollution due to the use of fossil fuels.

Business Process Orientation: Case of Croatia

Because of the increasing business pressures, companies must be adaptable and flexible in order to withstand them. Inadequate business processes and low level of business process orientation, that in its core accentuates business processes as opposed to business functions and focuses on process performance and customer satisfaction, hider the ability to adapt to changing environment. It has been shown in previous studies that the companies which have reached higher business process maturity level consistently outperform those that have not reached them. The aim of this paper is to provide a basic understanding of business process orientation concept and business process maturity model. Besides that the paper presents the state of business process orientation in Croatia that has been captured with a study conducted in 2013. Based on the results some practical implications and guidelines for managers are given.

Factors Influencing Rote Learner's Intention to Use WBL: Developing Country Study

Previous researches found that conventional WBL is effective for meaningful learner, because rote learner learn by repeating without thinking or trying to understand. It is impossible to have full benefit from conventional WBL. Understanding of rote learner-s intention and what influences it becomes important. Poorly designed user interface will discourage rote learner-s cultivation and intention to use WBL. Thus, user interface design is an important factor especially when WBL is used as comprehensive replacement of conventional teaching. This research proposes the influencing factors that can enhance learner-s intention to use the system. The enhanced TAM is used for evaluating the proposed factors. The research result points out that factors influencing rote learner-s intention are Perceived Usefulness of Homepage Content Structure, Perceived User Friendly Interface, Perceived Hedonic Component, and Perceived (homepage) Visual Attractiveness.

Verification of the Simultaneous Local Extraction Method of Base and Thermal Resistance of Bipolar Transistors

In this paper an extensive verification of the extraction method (published earlier) that consistently accounts for self-heating and Early effect to accurately extract both base and thermal resistance of bipolar junction transistors is presented. The method verification is demonstrated on advanced RF SiGe HBTs were the extracted results for the thermal resistance are compared with those from another published method that ignores the effect of Early effect on internal base-emitter voltage and the extracted results of the base resistance are compared with those determined from noise measurements. A self-consistency of our method in the extracted base resistance and thermal resistance using compact model simulation results is also carried out in order to study the level of accuracy of the method.

Humor Roles of Females in a Product Color Matrix

Healthcare providers sometimes use the power of humor as a treatment and therapy for buffering mental health or easing mental disorders because humor can provide relief from distress and conflict. Humor is also very suitable for advertising because of similar benefits. This study carefully examines humor's widespread use in advertising and identifies relationships among humor mechanisms, female depictions, and product types. The purpose is to conceptualize how humor theories can be used not only to successfully define a product as fitting within one of four color categories of the product color matrix, but also to identify compelling contemporary female depictions through humor in ads. The results can offer an idealization for marketing managers and consumers to help them understand how female role depictions can be effectively used with humor in ads. The four propositions developed herein are derived from related literature, through the identification of marketing strategy formulations that achieve product memory enhancement by adopting humor mechanisms properly matched with female role depictions.

Smart Sustainable Cities: An Integrated Planning Approach towards Sustainable Urban Energy Systems, India

Cities denote instantaneously a challenge and an opportunity for climate change policy. Cities are the place where most energy services are needed because urbanization is closely linked to high population densities and concentration of economic activities and production (Urban energy demand). Consequently, it is critical to explain about the role of cities within the world-s energy systems and its correlation with the climate change issue. With more than half of the world-s population already living in urban areas, and that percentage expected to rise to 75 per cent by 2050, it is clear that the path to sustainable development must pass through cities. Cities expanding in size and population pose increased challenges to the environment, of which energy is part as a natural resource, and to the quality of life. Nowadays, most cities have already understood the importance of sustainability, both at their local scale as in terms of their contribution to sustainability at higher geographical scales. It requires the perception of a city as a complex and dynamic ecosystem, an open system, or cluster of systems, where the energy as well as the other natural resources is transformed to satisfy the needs of the different urban activities. In fact, buildings and transportation generally represent most of cities direct energy demand, i.e., between 60 per cent and 80 per cent of the overall consumption. Buildings, both residential and services are usually influenced by the local physical and social conditions. In terms of transport, the energy demand is also strongly linked with the specific characteristics of a city (urban mobility).The concept of a “smart city" builds on statistics as seven key axes of a city-s success in moving towards common platform (brain nerve)of sustainable urban energy systems. With the aforesaid knowledge, the authors have suggested a frame work to role of cities, as energy actors for smart city management. The authors have discusses the potential elements needed for energy in smart cities and also identified potential energy actions and relevant barriers. Furthermore, three levels of city smartness in cities actions to overcome market /institutional failures with a local approach are distinguished. The authors have made an attempt to conceive and implement concepts of city smartness by adopting the city or local government as nerve center through an integrated planning approach. Finally, concluding with recommendations for the organization of the Smart Sustainable Cities for positive changes of urban India.

Improving Air Temperature Prediction with Artificial Neural Networks

The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.

Ionanofluids as Novel Fluids for Advanced Heat Transfer Applications

Ionanofluids are a new and innovative class of heat transfer fluids which exhibit fascinating thermophysical properties compared to their base ionic liquids. This paper deals with the findings of thermal conductivity and specific heat capacity of ionanofluids as a function of a temperature and concentration of nanotubes. Simulation results using ionanofluids as coolants in heat exchanger are also used to access their feasibility and performance in heat transfer devices. Results on thermal conductivity and heat capacity of ionanofluids as well as the estimation of heat transfer areas for ionanofluids and ionic liquids in a model shell and tube heat exchanger reveal that ionanofluids possess superior thermal conductivity and heat capacity and require considerably less heat transfer areas as compared to those of their base ionic liquids. This novel class of fluids shows great potential for advanced heat transfer applications.

Decoupled Scheduling in Meta Environment

Grid scheduling is the process of mapping grid jobs to resources over multiple administrative domains. Traditionally, application-level schedulers have been tightly integrated with the application itself and were not easily applied to other applications. This design is generic that decouples the scheduler core (the search procedure) from the application-specific (e.g. application performance models) and platform-specific (e.g. collection of resource information) components used by the search procedure. In this decoupled approach the application details are not revealed completely to broker, but customer will give the application to resource provider for execution. In a decoupled approach, apart from scheduling, the resource selection can be performed independently in order to achieve scalability.

Development of Manufacturing Simulation Model for Semiconductor Fabrication

This research presents the development of simulation modeling for WIP management in semiconductor fabrication. Manufacturing simulation modeling is needed for productivity optimization analysis due to the complex process flows involved more than 35 percent re-entrance processing steps more than 15 times at same equipment. Furthermore, semiconductor fabrication required to produce high product mixed with total processing steps varies from 300 to 800 steps and cycle time between 30 to 70 days. Besides the complexity, expansive wafer cost that potentially impact the company profits margin once miss due date is another motivation to explore options to experiment any analysis using simulation modeling. In this paper, the simulation model is developed using existing commercial software platform AutoSched AP, with customized integration with Manufacturing Execution Systems (MES) and Advanced Productivity Family (APF) for data collections used to configure the model parameters and data source. Model parameters such as processing steps cycle time, equipment performance, handling time, efficiency of operator are collected through this customization. Once the parameters are validated, few customizations are made to ensure the prior model is executed. The accuracy for the simulation model is validated with the actual output per day for all equipments. The comparison analysis from result of the simulation model compared to actual for achieved 95 percent accuracy for 30 days. This model later was used to perform various what if analysis to understand impacts on cycle time and overall output. By using this simulation model, complex manufacturing environment like semiconductor fabrication (fab) now have alternative source of validation for any new requirements impact analysis.

Neurogenic Potential of Clitoria ternatea Aqueous Root Extract–A Basis for Enhancing Learning and Memory

The neurogenic potential of many herbal extracts used in Indian medicine is hitherto unknown. Extracts derived from Clitoria ternatea Linn have been used in Indian Ayurvedic system of medicine as an ingredient of “Medhya rasayana", consumed for improving memory and longevity in humans and also in treatment of various neurological disorders. Our earlier experimental studies with oral intubation of Clitoria ternatea aqueous root extract (CTR) had shown significant enhancement of learning and memory in postnatal and young adult Wistar rats. The present study was designed to elucidate the in vitro effects of 200ng/ml of CTR on proliferation, differentiation and growth of anterior subventricular zone neural stem cells (aSVZ NSC-s) derived from prenatal and postnatal rat pups. Results show significant increase in proliferation and growth of neurospheres and increase in the yield of differentiated neurons of aSVZ neural precursor cells (aSVZNPC-s) at 7 days in vitro when treated with 200ng/ml of CTR as compared to age matched control. Results indicate that CTR has growth promoting neurogenic effect on aSVZ neural stem cells and their survival similar to neurotrophic factors like Survivin, Neuregulin 1, FGF-2, BDNF possibly the basis for enhanced learning and memory.

Corporate Social Responsibility and Values in Innovation Management

Corporate social responsibility (CSR) viewpoint have challenged the traditional perception to understand corporations position. Production- and managerial-centred views are expanding towards reference group-centred policies. Consequently, the significance of new kind of knowledge has emerged. In addition to management of the organisation, the idea of CSR emphasises the importance to recognise the value-expectations of operational environment. It is know that management is often well-aware of corporate social responsibilities, but it is less clear how well these high level goals are understood in practical product design and development work. In this study, the apprehension above proved to be real to some degree. While management was very aware of CSR it was less familiar to designers. The outcome shows that it is essential to raise ethical values and issues higher in corporate communication, if it is wished that they materialize also in products.

Enhancing Landfill Gas Production by Methanogenic Sand Layer

Landfill gas, particularly methane is one of the greenhouse gases which contributes to global warming. This paper presents the findings of a study on methane gas production from simulated landfill reactor under saturated conditions. A reactor was constructed to represent a landfill cell of 2.5 m thickness on sandy soil. The reactor was 0.2 m in diameter and 4 m in height. One meter of sand and pebble layer was packed at the bottom of the reactor followed by 2.5 m of solid waste layer and 0.4 m of sand layer as the cover soil. Degradation of waste in the solid waste layer was at acidification stage as indicated by the leachate quality with COD as high as 55,511 mg/L and pH as low as 5.1. However, methanogenic environment was established at the bottom sand layer after one year of operation indicated by pH of 7.2 and methane gas generation. Leachate degradation took place as the leachate moved through the sand layer at an infiltration of rate 0.7 cm/day. This resulted in landfill gas production of 77 mL/day/kg containing 55 to 65% methane. The application of sand layer contributed to the gas production from landfill by an in-situ degradation of leachate in the sand at the bottom of the landfill.

Effects of Mixed Convection and Double Dispersion on Semi Infinite Vertical Plate in Presence of Radiation

In this paper, the effects of radiation, chemical reaction and double dispersion on mixed convection heat and mass transfer along a semi vertical plate are considered. The plate is embedded in a Newtonian fluid saturated non - Darcy (Forchheimer flow model) porous medium. The Forchheimer extension and first order chemical reaction are considered in the flow equations. The governing sets of partial differential equations are nondimensionalized and reduced to a set of ordinary differential equations which are then solved numerically by Fourth order Runge– Kutta method. Numerical results for the detail of the velocity, temperature, and concentration profiles as well as heat transfer rates (Nusselt number) and mass transfer rates (Sherwood number) against various parameters are presented in graphs. The obtained results are checked against previously published work for special cases of the problem and are found to be in good agreement.

Conventional Design and Simulation of an Urban Hybrid Bus

Due to heightened concerns over environmental and economic issues the growing important of air pollution, and the importance of conserving fossil fuel resources in the world, the automotive industry is now forced to produce more fuel efficient, low emission vehicles and new drive system technologies. One of the most promising technologies to receive attention is the hybrid electric vehicle (HEV), which consists of two or more energy sources that supply energy to electric traction motors that in turn drive the wheels. This paper presents the various structures of HEV systems, the basic theoretical knowledge for describing their operation and the general behaviour of the HEV in acceleration, cruise and deceleration phases. The conventional design and sizing of a series HEV is studied. A conventional bus and its series configuration are defined and evaluated using the ADVISOR. In this section the simulation of a standard driving cycle and prediction of its fuel consumption and emissions of the HEV are discussed. Finally the bus performance is investigated to establish whether it can satisfy the performance, fuel consumption and emissions requested. The validity of the simulation has been established by the close conformity between the fuel consumption of the conventional bus reported by the manufacturer to what has achieved from the simulation.

Simulating Dynamics of Thoracolumbar Spine Derived from Life MOD under Haptic Forces

In this paper, the construction of a detailed spine model is presented using the LifeMOD Biomechanics Modeler. The detailed spine model is obtained by refining spine segments in cervical, thoracic and lumbar regions into individual vertebra segments, using bushing elements representing the intervertebral discs, and building various ligamentous soft tissues between vertebrae. In the sagittal plane of the spine, constant force will be applied from the posterior to anterior during simulation to determine dynamic characteristics of the spine. The force magnitude is gradually increased in subsequent simulations. Based on these recorded dynamic properties, graphs of displacement-force relationships will be established in terms of polynomial functions by using the least-squares method and imported into a haptic integrated graphic environment. A thoracolumbar spine model with complex geometry of vertebrae, which is digitized from a resin spine prototype, will be utilized in this environment. By using the haptic technique, surgeons can touch as well as apply forces to the spine model through haptic devices to observe the locomotion of the spine which is computed from the displacement-force relationship graphs. This current study provides a preliminary picture of our ongoing work towards building and simulating bio-fidelity scoliotic spine models in a haptic integrated graphic environment whose dynamic properties are obtained from LifeMOD. These models can be helpful for surgeons to examine kinematic behaviors of scoliotic spines and to propose possible surgical plans before spine correction operations.

A Proposed Performance Prediction Approach for Manufacturing Processes using ANNs

this paper aims to provide an approach to predict the performance of the product produced after multi-stages of manufacturing processes, as well as the assembly. Such approach aims to control and subsequently identify the relationship between the process inputs and outputs so that a process engineer can more accurately predict how the process output shall perform based on the system inputs. The approach is guided by a six-sigma methodology to obtain improved performance. In this paper a case study of the manufacture of a hermetic reciprocating compressor is presented. The application of artificial neural networks (ANNs) technique is introduced to improve performance prediction within this manufacturing environment. The results demonstrate that the approach predicts accurately and effectively.