A Computer Aided Model for Supporting Design Education

Educating effective architect designers is an important goal of architectural education. But what contributes to students- performance, and to critical and creative thinking in architectural design education? Besides teaching architecture students how to understand logical arguments, eliminate the inadequate solutions and focus on the correct ones, it is also crucial to teach students how to focus on exploring ideas and the alternative solutions and seeking for other right answers rather than one. This paper focuses on the enhancing architectural design education and may provide implications for enhancing teaching design.

Electrical Properties of n-CdO/p-Si Heterojunction Diode Fabricated by Sol Gel

n-CdO/p-Si heterojunction diode was fabricated using sol-gel spin coating technique which is a low cost and easily scalable method for preparing of semiconductor films. The structural and morphological properties of CdO film were investigated. The X-ray diffraction (XRD) spectra indicated that the film was of polycrystalline nature. The scanning electron microscopy (SEM) images indicate that the surface morphology CdO film consists of the clusters formed with the coming together of the nanoparticles. The electrical characterization of Au/n-CdO/p–Si/Al heterojunction diode was investigated by current-voltage. The ideality factor of the diode was found to be 3.02 for room temperature. The reverse current of the diode strongly increased with illumination intensity of 100 mWcm-2 and the diode gave a maximum open circuit voltage Voc of 0.04 V and short-circuits current Isc of 9.92×10-9 A.

Integration of Fixed and Variable Speed Wind Generator Dynamics with Multimachine AC Systems

The impact of fixed speed squirrel cage type as well as variable speed doubly fed induction generators (DFIG) on dynamic performance of a multimachine power system has been investigated. Detailed models of the various components have been presented and the integration of asynchronous and synchronous generators has been carried out through a rotor angle based transform. Simulation studies carried out considering the conventional dynamic model of squirrel cage asynchronous generators show that integration, as such, could degrade to the AC system performance transiently. This article proposes a frequency or power controller which can effectively control the transients and restore normal operation of fixed speed induction generator quickly. Comparison of simulation results between classical cage and doubly-fed induction generators indicate that the doubly fed induction machine is more adaptable to multimachine AC system. Frequency controller installed in the DFIG system can also improve its transient profile.

Effect of Periodically Use of Garlic (Allium sativum) Powder on Performance and Carcass Characteristics in Broiler Chickens

A feeding trial was conducted to investigate the effect of periodically use of garlic on performance and carcass characteristics in broiler chickens. 240 1-day-old Ross broiler chicks randomly allocated into the 10 dietary treatments (A, B, C, D, E, F, G, H, I and J) for 6 wk. Treatment A or control group, received basal diet (based on standards of Ross management guidelines) without supplementation of garlic powder while B, C and D dietary treatments were basal diet supplemented with 0.5, 1 and 3% garlic powder, respectively for the whole time of experiment (6 weeks). Birds in group E, F and G were fed control diet supplemented with 0.5, 1 and 3% garlic powder, respectively just in their starter diet (0- 21d). Birds in three other treatments (H, I and J) received control diet for the first 21 days and 0.5, 1 and 3% of garlic powder was added to their finisher diets, respectively. 1 and 3% supplemented groups in finisher period had better performance as compared with other groups. Since present study conducted in optimum and antiseptic conditions, it seems that better or more responses could be expected in performance if the raising conditions would not be healthy.

Advanced Gronwall-Bellman-Type Integral Inequalities and Their Applications

In this paper, some new nonlinear generalized Gronwall-Bellman-Type integral inequalities with mixed time delays are established. These inequalities can be used as handy tools to research stability problems of delayed differential and integral dynamic systems. As applications, based on these new established inequalities, some p-stable results of a integro-differential equation are also given. Two numerical examples are presented to illustrate the validity of the main results.

The Application of Real Options to Capital Budgeting

Real options theory suggests that managerial flexibility embedded within irreversible investments can account for a significant value in project valuation. Although the argument has become the dominant focus of capital investment theory over decades, yet recent survey literature in capital budgeting indicates that corporate practitioners still do not explicitly apply real options in investment decisions. In this paper, we explore how real options decision criteria can be transformed into equivalent capital budgeting criteria under the consideration of uncertainty, assuming that underlying stochastic process follows a geometric Brownian motion (GBM), a mixed diffusion-jump (MX), or a mean-reverting process (MR). These equivalent valuation techniques can be readily decomposed into conventional investment rules and “option impacts", the latter of which describe the impacts on optimal investment rules with the option value considered. Based on numerical analysis and Monte Carlo simulation, three major findings are derived. First, it is shown that real options could be successfully integrated into the mindset of conventional capital budgeting. Second, the inclusion of option impacts tends to delay investment. It is indicated that the delay effect is the most significant under a GBM process and the least significant under a MR process. Third, it is optimal to adopt the new capital budgeting criteria in investment decision-making and adopting a suboptimal investment rule without considering real options could lead to a substantial loss in value.

Application of ESA in the CAVE Mode Authentication

This paper proposes the authentication method using ESA algorithm instead of using CAVE algorithm in the CDMA mobile communication systems including IS-95 and CDMA2000 1x. And, we analyze to apply ESA mechanism on behalf of CAVE mechanism without the change of message format and air interface in the existing CDMA systems. If ESA algorithm can be used as the substitution of CAVE algorithm, security strength of authentication algorithm is intensified without protocol change. An algorithm replacement proposed in this paper is not to change an authentication mechanism, but to configure input of ESA algorithm and to produce output. Therefore, our proposal can be the compatible to the existing systems.

Evaluating Alternative Fuel Vehicles from Technical, Environmental and Economic Perspectives: Case of Light-Duty Vehicles in Iran

This paper presents an environmental and technoeconomic evaluation of light duty vehicles in Iran. A comprehensive well-to-wheel (WTW) analysis is applied to compare different automotive fuel chains, conventional internal combustion engines and innovative vehicle powertrains. The study examines the competitiveness of 15 various pathways in terms of energy efficiencies, GHG emissions, and levelized cost of different energy carriers. The results indicate that electric vehicles including battery electric vehicles (BEV), fuel cell vehicles (FCV) and plug-in hybrid electric vehicles (PHEV) increase the WTW energy efficiency by 54%, 51% and 46%, respectively, compared to common internal combustion engines powered by gasoline. On the other hand, greenhouse gas (GHG) emissions per kilometer of FCV and BEV would be 48% lower than that of gasoline engines. It is concluded that BEV has the lowest total cost of energy consumption and external cost of emission, followed by internal combustion engines (ICE) fueled by CNG. Conventional internal combustion engines fueled by gasoline, on the other hand, would have the highest costs.

Multi-Scale Gabor Feature Based Eye Localization

Eye localization is necessary for face recognition and related application areas. Most of eye localization algorithms reported so far still need to be improved about precision and computational time for successful applications. In this paper, we propose an eye location method based on multi-scale Gabor feature vectors, which is more robust with respect to initial points. The eye localization based on Gabor feature vectors first needs to constructs an Eye Model Bunch for each eye (left or right eye) which consists of n Gabor jets and average eye coordinates of each eyes obtained from n model face images, and then tries to localize eyes in an incoming face image by utilizing the fact that the true eye coordinates is most likely to be very close to the position where the Gabor jet will have the best Gabor jet similarity matching with a Gabor jet in the Eye Model Bunch. Similar ideas have been already proposed in such as EBGM (Elastic Bunch Graph Matching). However, the method used in EBGM is known to be not robust with respect to initial values and may need extensive search range for achieving the required performance, but extensive search ranges will cause much more computational burden. In this paper, we propose a multi-scale approach with a little increased computational burden where one first tries to localize eyes based on Gabor feature vectors in a coarse face image obtained from down sampling of the original face image, and then localize eyes based on Gabor feature vectors in the original resolution face image by using the eye coordinates localized in the coarse scaled image as initial points. Several experiments and comparisons with other eye localization methods reported in the other papers show the efficiency of our proposed method.

Design of an Intelligent Location Identification Scheme Based On LANDMARC and BPNs

Radio frequency identification (RFID) applications have grown rapidly in many industries, especially in indoor location identification. The advantage of using received signal strength indicator (RSSI) values as an indoor location measurement method is a cost-effective approach without installing extra hardware. Because the accuracy of many positioning schemes using RSSI values is limited by interference factors and the environment, thus it is challenging to use RFID location techniques based on integrating positioning algorithm design. This study proposes the location estimation approach and analyzes a scheme relying on RSSI values to minimize location errors. In addition, this paper examines different factors that affect location accuracy by integrating the backpropagation neural network (BPN) with the LANDMARC algorithm in a training phase and an online phase. First, the training phase computes coordinates obtained from the LANDMARC algorithm, which uses RSSI values and the real coordinates of reference tags as training data for constructing an appropriate BPN architecture and training length. Second, in the online phase, the LANDMARC algorithm calculates the coordinates of tracking tags, which are then used as BPN inputs to obtain location estimates. The results show that the proposed scheme can estimate locations more accurately compared to LANDMARC without extra devices.

Molecular Analysis of Somaclonal Variation in Tissue Culture Derived Bananas Using MSAP and SSR Markers

The project was undertaken to determine the effects of modified tissue culture protocols e.g. age of culture and hormone levels (2,4-D) in generating somaclonal variation. Moreover, the utility of molecular markers (SSR and MSAP) in sorting off types/somaclones were investigated. Results show that somaclonal variation is in effect due to prolonged subculture and high 2,4-D concentration. The resultant variation was observed to be due to high level of methylation events specifically cytosine methylation either at the internal or external cytosine and was identified by methylation sensitive amplification polymorphism (MSAP).Simple sequence repeats (SSR) on the other hand, was able to associate a marker to a trait of interest. These therefore, show that molecular markers can be an important tool in sorting out variation/mutants at an early stage.

Carbon Accumulation in Winter Wheat under Different Growing Intensity and Climate Change

World population growth drives food demand, promotes intensification of agriculture, development of new production technologies and varieties more suitable for regional nature conditions. Climate change can affect the length of growing period, biomass and carbon accumulation in winter wheat. The increasing mean air temperature resulting from climate change can reduce the length of growth period of cereals, and without adequate adjustments in growing technologies or varieties, can reduce biomass and carbon accumulation. Deeper understanding and effective measures for monitoring and management of cereal growth process are needed for adaptation to changing climate and technological conditions.

Students- uses of Wiki in Teacher Education: A Statistical Analysis

Wikis are considered to be part of Web 2.0 technologies that potentially support collaborative learning and writing. Wikis provide opportunities for multiple users to work on the same document simultaneously. Most wikis have also a page for written group discussion. Nevertheless, wikis may be used in different ways depending on the pedagogy being used, and the constraints imposed by the course design. This work explores students- uses of wiki in teacher education. The analysis is based on a taxonomy for classifying students- activities and actions carried out on the wiki. The article also discusses the implications for using wikis as collaborative writing tools in teacher education.

Environmental Performance of the United States Energy Sector: A DEA Model with Non-Discretionary Factors and Perfect Object

It is suggested to evaluate environmental performance of energy sector using Data Envelopment Analysis with nondiscretionary factors (DEA-ND) with relative indicators as inputs and outputs. The latter allows for comparison of the objects essentially different in size. Inclusion of non-discretionary factors serves separation of the indicators that are beyond the control of the objects. A virtual perfect object comprised of maximal outputs and minimal inputs was added to the group of actual ones. In this setting, explicit solution of the DEA-ND problem was obtained. Energy sector of the United States was analyzed using suggested approach for the period of 1980 – 2006 with expected values of economic indicators for 2030 used for forming the perfect object. It was obtained that environmental performance has been increasing steadily for the period from 7.7% through 50.0% but still remains well below the prospected level

A Security Model of Voice Eavesdropping Protection over Digital Networks

The purpose of this research is to develop a security model for voice eavesdropping protection over digital networks. The proposed model provides an encryption scheme and a personal secret key exchange between communicating parties, a so-called voice data transformation system, resulting in a real-privacy conversation. The operation of this system comprises two main steps as follows: The first one is the personal secret key exchange for using the keys in the data encryption process during conversation. The key owner could freely make his/her choice in key selection, so it is recommended that one should exchange a different key for a different conversational party, and record the key for each case into the memory provided in the client device. The next step is to set and record another personal option of encryption, either taking all frames or just partial frames, so-called the figure of 1:M. Using different personal secret keys and different sets of 1:M to different parties without the intervention of the service operator, would result in posing quite a big problem for any eavesdroppers who attempt to discover the key used during the conversation, especially in a short period of time. Thus, it is quite safe and effective to protect the case of voice eavesdropping. The results of the implementation indicate that the system can perform its function accurately as designed. In this regard, the proposed system is suitable for effective use in voice eavesdropping protection over digital networks, without any requirements to change presently existing network systems, mobile phone network and VoIP, for instance.

Lower Order Harmonics Minimisation in CHB Inverter Using GA and Decomposition by WT

Nowadays Multilevel inverters are widely using in various applications. Modulation strategy at fundamental switching frequency like, SHEPWM is prominent technique to eliminate lower order of harmonics with less switching losses and better harmonic profile. The equations which are formed by SHE are highly nonlinear transcendental in nature, there may exist single, multiple or even no solutions for a particular MI. However, some loads such as electrical drives, it is required to operate in whole range of MI. In order to solve SHE equations for whole range of MI, intelligent techniques are well suited to solve equations so as to produce lest %THDV. Hence, this paper uses Continuous genetic algorithm for minimising harmonics. This paper also presents wavelet based analysis of harmonics. The developed algorithm is simulated and %THD from FFT analysis and Wavelet analysis are compared. MATLAB programming environment and SIMULINK models are used whenever necessary.

A Study of the Relationship of PSI and LMX to Service Providers' CS in Hospitality Industry

The purpose of the current study is to gain insight into the relative role of professional self-image (PSI) for service providers among leader-member exchange (LMX), career success. Lack of studies demonstrated that PSI of service providers affect on their CS. So, it is necessary to, according to service providers- perspective, explore the relationship among LMX and CS in hospitality industry. The result of the current study can suggest strategic directions for hospitality practitioners in terms of constructing LMX relationship, so as to make service providers realize and build their PSI, and to promote their CS. Implications of these findings for hospitality implementations as well as future research directions are subsequently discussed.

User Acceptance of Educational Games: A Revised Unified Theory of Acceptance and Use of Technology (UTAUT)

Educational games (EG) seem to have lots of potential due to digital games popularity and preferences of our younger generations of learners. However, most studies focus on game design and its effectiveness while little has been known about the factors that can affect users to accept or to reject EG for their learning. User acceptance research try to understand the determinants of information systems (IS) adoption among users by investigating both systems factors and users factors. Upon the lack of knowledge on acceptance factors for educational games, we seek to understand the issue. This study proposed a model of acceptance factors based on Unified Theory of Acceptance and Use of Technology (UTAUT). We use original model (performance expectancy, effort expectancy and social influence) together with two new determinants (learning opportunities and enjoyment). We will also investigate the effect of gender and gaming experience that moderate the proposed factors.

A Hybrid Approach to Fault Detection and Diagnosis in a Diesel Fuel Hydrotreatment Process

It is estimated that the total cost of abnormal conditions to US process industries is around $20 billion dollars in annual losses. The hydrotreatment (HDT) of diesel fuel in petroleum refineries is a conversion process that leads to high profitable economical returns. However, this is a difficult process to control because it is operated continuously, with high hydrogen pressures and it is also subject to disturbances in feed properties and catalyst performance. So, the automatic detection of fault and diagnosis plays an important role in this context. In this work, a hybrid approach based on neural networks together with a pos-processing classification algorithm is used to detect faults in a simulated HDT unit. Nine classes (8 faults and the normal operation) were correctly classified using the proposed approach in a maximum time of 5 minutes, based on on-line data process measurements.

Consumer Adoption - Risk Factor of Mobile Banking Services

Mobile banking services present a unique growth opportunity for mobile operators in emerging markets, and have already made good progress in bringing financial services to the previously unbanked populations of many developing countries. The potential is amazing, but what about the risks? In the complex process of establishing a mobile banking business model, many kinds of risks and factors need to be monitored and well-managed. Risk identification is the first stage of risk management. Correct risk identification ensures risk management effectiveness. Keeping the risks low makes it possible to use the full potential of mobile banking and carry out the planned business strategy. The focus should be on adoption of consumers which is the main risk factor of mobile banking services.