Abstract: Unlike general-purpose processors, digital signal
processors (DSP processors) are strongly application-dependent. To
meet the needs for diverse applications, a wide variety of DSP
processors based on different architectures ranging from the
traditional to VLIW have been introduced to the market over the
years. The functionality, performance, and cost of these processors
vary over a wide range. In order to select a processor that meets the
design criteria for an application, processor performance is usually
the major concern for digital signal processing (DSP) application
developers. Performance data are also essential for the designers of
DSP processors to improve their design. Consequently, several DSP
performance benchmarks have been proposed over the past decade or
so. However, none of these benchmarks seem to have included recent
new DSP applications.
In this paper, we use a new benchmark that we recently developed
to compare the performance of popular DSP processors from Texas
Instruments and StarCore. The new benchmark is based on the
Selectable Mode Vocoder (SMV), a speech-coding program from the
recent third generation (3G) wireless voice applications. All
benchmark kernels are compiled by the compilers of the respective
DSP processors and run on their simulators. Weighted arithmetic
mean of clock cycles and arithmetic mean of code size are used to
compare the performance of five DSP processors.
In addition, we studied how the performance of a processor is
affected by code structure, features of processor architecture and
optimization of compiler. The extensive experimental data gathered,
analyzed, and presented in this paper should be helpful for DSP
processor and compiler designers to meet their specific design goals.
Abstract: The purpose of this study was to survey the effect of
organizational communication system on the conflict in physical
education offices of Isfahan province. The research methodology of
this research was a descriptive study. All employees working in
physical education offices of Isfahan province were included in the
sample for this study (N= 236). Researcher made questionnaire and
demographic questionnaire were used as investigation instruments.
Based on the result of chi square test, there is significant difference
between organizational communication system and interpersonal
conflict. The most of participants evaluate communication in an
informal way and pointed out that the communication channels were
not open. Based on the result of binomial test, interpersonal conflict
exists in physical education offices of Isfahan.
Abstract: Artemia is one of the most conspicuous invertebrates
associated with aquaculture. It can be considered as a model
organism, offering numerous advantages for comprehensive and
multidisciplinary studies using morphologic or molecular methods.
Since DNA extraction is an important step of any molecular
experiment, a new and a rapid method of DNA extraction from adult
Artemia was described in this study. Besides, the efficiency of this
technique was compared with two widely used alternative techniques,
namely Chelex® 100 resin and SDS-chloroform methods. Data
analysis revealed that the new method is the easiest and the most cost
effective method among the other methods which allows a quick and
efficient extraction of DNA from the adult animal.
Abstract: Security is an interesting and significance issue for
popular virtual platforms, such as virtualization cluster and cloud
platforms. Virtualization is the powerful technology for cloud
computing services, there are a lot of benefits by using virtual machine
tools which be called hypervisors, such as it can quickly deploy all
kinds of virtual Operating Systems in single platform, able to control
all virtual system resources effectively, cost down for system platform
deployment, ability of customization, high elasticity and high
reliability. However, some important security problems need to take
care and resolved in virtual platforms that include terrible viruses, evil
programs, illegal operations and intrusion behavior. In this paper, we
present useful Intrusion Detection Mechanism (IDM) software that not
only can auto to analyze all system-s operations with the accounting
journal database, but also is able to monitor the system-s state for
virtual platforms.
Abstract: The present research was focused to investigate the
role of investment in the course of economic growth with reference to
Pakistan. The study analyzed the role of the public and private
investment and impact of the political and macroeconomic
uncertainty on economic growth of Pakistan by using the vector
autoregressive approach (VAR). In long-run both public and private
investment showed a positive impact on economic growth but the
growth was largely driven by private investment as compared to
public investment. Government consumption expenditure, economic
uncertainty and political instability hampered the economic growth of
Pakistan. In short-run the private investment positively influences the
growth but there was negative and insignificant effect of the public
investment and government consumption expenditure on the growth.
There was a positive relationship found between economic
uncertainty (proxy for inflation) and GDP in short run.
Abstract: 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.
Abstract: 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.
Abstract: 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.
Abstract: 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.
Abstract: 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.
Abstract: Attempts to add fibre and polyphenols (PPs) into
popular beverages present challenges related to the properties of
finished products such as smoothies. Consumer acceptability,
viscosity and phenolic composition of smoothies containing high
levels of fruit fibre (2.5-7.5 g per 300 mL serve) and PPs (250-750
mg per 300 mL serve) were examined. The changes in total
extractable PP, vitamin C content, and colour of selected smoothies
over a storage stability trial (4°C, 14 days) were compared. A set of
acidic aqueous model beverages were prepared to further examine
the effect of two different heat treatments on the stability and
extractability of PPs. Results show that overall consumer
acceptability of high fibre and PP smoothies was low, with average
hedonic scores ranging from 3.9 to 6.4 (on a 1-9 scale). Flavour,
texture and overall acceptability decreased as fibre and polyphenol
contents increased, with fibre content exerting a stronger effect.
Higher fibre content resulted in greater viscosity, with an elevated PP
content increasing viscosity only slightly. The presence of fibre also
aided the stability and extractability of PPs after heating. A reduction
of extractable PPs, vitamin C content and colour intensity of
smoothies was observed after a 14-day storage period at 4°C. Two
heat treatments (75°C for 45 min or 85°C for 1 min) that are
normally used for beverage production, did not cause significant
reduction of total extracted PPs. It is clear that high levels of added
fibre and PPs greatly influence the consumer appeal of smoothies,
suggesting the need to develop novel formulation and processing
methods if a satisfactory functional beverage is to be developed
incorporating these ingredients.
Abstract: 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.
Abstract: Quantitative characterization of nonlinear directional
couplings between stochastic oscillators from data is considered. We
suggest coupling characteristics readily interpreted from a physical
viewpoint and their estimators. An expression for a statistical
significance level is derived analytically that allows reliable coupling
detection from a relatively short time series. Performance of the
technique is demonstrated in numerical experiments.
Abstract: Identifying and classifying intersections according to
severity is very important for implementation of safety related
counter measures and effective models are needed to compare and
assess the severity. Highway safety organizations have considered
intersection safety among their priorities. In spite of significant
advances in highways safety, the large numbers of crashes with high
severities still occur in the highways. Investigation of influential
factors on crashes enables engineers to carry out calculations in order
to reduce crash severity. Previous studies lacked a model capable of
simultaneous illustration of the influence of human factors, road,
vehicle, weather conditions and traffic features including traffic
volume and flow speed on the crash severity. Thus, this paper is
aimed at developing the models to illustrate the simultaneous
influence of these variables on the crash severity in urban highways.
The models represented in this study have been developed using
binary Logit Models. SPSS software has been used to calibrate the
models. It must be mentioned that backward regression method in
SPSS was used to identify the significant variables in the model.
Consider to obtained results it can be concluded that the main
factor in increasing of crash severity in urban highways are driver
age, movement with reverse gear, technical defect of the vehicle,
vehicle collision with motorcycle and bicycle, bridge, frontal impact
collisions, frontal-lateral collisions and multi-vehicle crashes in
urban highways which always increase the crash severity in urban
highways.
Abstract: Soil erosion is the most serious problem faced at
global and local level. So planning of soil conservation measures has
become prominent agenda in the view of water basin managers. To
plan for the soil conservation measures, the information on soil
erosion is essential. Universal Soil Loss Equation (USLE), Revised
Universal Soil Loss Equation 1 (RUSLE1or RUSLE) and Modified
Universal Soil Loss Equation (MUSLE), RUSLE 1.06, RUSLE1.06c,
RUSLE2 are most widely used conventional erosion estimation
methods. The essential drawbacks of USLE, RUSLE1 equations are
that they are based on average annual values of its parameters and so
their applicability to small temporal scale is questionable. Also these
equations do not estimate runoff generated soil erosion. So
applicability of these equations to estimate runoff generated soil
erosion is questionable. Data used in formation of USLE, RUSLE1
equations was plot data so its applicability at greater spatial scale
needs some scale correction factors to be induced. On the other hand
MUSLE is unsuitable for predicting sediment yield of small and large
events. Although the new revised forms of USLE like RUSLE 1.06,
RUSLE1.06c and RUSLE2 were land use independent and they have
almost cleared all the drawbacks in earlier versions like USLE and
RUSLE1, they are based on the regional data of specific area and
their applicability to other areas having different climate, soil, land
use is questionable. These conventional equations are applicable for
sheet and rill erosion and unable to predict gully erosion and spatial
pattern of rills. So the research was focused on development of nonconventional
(other than conventional) methods of soil erosion
estimation. When these non-conventional methods are combined with
GIS and RS, gives spatial distribution of soil erosion. In the present
paper the review of literature on non- conventional methods of soil
erosion estimation supported by GIS and RS is presented.
Abstract: In this paper the authors propose and verify an approach to control heat flow in machine tool components. Thermal deformations are a main aspect that affects the accuracy of machining. Due to goals of energy efficiency, thermal basic loads should be reduced. This leads to inhomogeneous and time variant temperature profiles. To counteract these negative consequences, material with high melting enthalpy is used as a method for thermal stabilization. The increased thermal capacity slows down the transient thermal behavior. To account for the delayed thermal equilibrium, a control mechanism for thermal flow is introduced. By varying a gap in a heat flow path the thermal resistance of an assembly can be controlled. This mechanism is evaluated in two experimental setups. First to validate the ability to control the thermal resistance and second to prove the possibility of a self-sufficient option based on the selfsensing abilities of thermal shape memory alloys.
Abstract: Direct and indirect somatic embryogenesis (SE) from
petiole and leaf explants of Scaevola aemula R. Br. cv. 'Purple
Fanfare' was achieved. High frequency of somatic embryos was
obtained directly from petiole and leaf explants using an inductive
plant growth regulator signal thidiazuron (TDZ). Petiole explants
were more responsive to SE than leaves. Plants derived from somatic
embryos of petiole explants germinated more readily into plants. SE
occurred more efficiently in half-strength Murashige and Skoog
(MS) medium than in full-strength MS medium. Non-embryogenic
callus induced by 2, 4-dichlorophenoxyacetic acid was used to
investigate the feasibility of obtaining SE with TDZ as a secondary
inductive plant growth regulator (PGR) signal. Non-embryogenic
callus of S. aemula was able to convert into an “embryogenic
competent mode" with PGR signal. Protocol developed for induction
of direct and indirect somatic embryogenesis in S. aemula can
improve the large scale propagation system of the plant in future.
Abstract: 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.
Abstract: 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.
Abstract: In this paper, we propose a high capacity image hiding
technology based on pixel prediction and the difference of modified histogram. This approach is used the pixel prediction and the
difference of modified histogram to calculate the best embedding point.
This approach can improve the predictive accuracy and increase the pixel difference to advance the hiding capacity. We also use the
histogram modification to prevent the overflow and underflow. Experimental results demonstrate that our proposed method within the
same average hiding capacity can still keep high quality of image and low distortion