Abstract: For scores of years now, several microfinance
organizations, non governmental organizations and other welfare
organizations have, with a view to aiding the progress of
communities rooted in poverty have been focusing on creating
microentrepreneurs, besides taking several other measures. In recent
times, business corporations have joined forces to combat poverty by
taking up microenterprise development. Hindustan Unilever Limited
(HUL), the Indian subsidiary of Unilever Limited exemplifies this
through its Project Shakti. The company through the Project creates
rural women entrepreneurs by making them direct to home sales
distributors of its products in villages that have thus far been ignored
by multinational corporations. The members participating in Project
Shakti are largely self help group members. The paper focuses on
assessing the impact made by the company on the members engaged
in Project Shakti. The analysis involves use of quantitative methods
to study the effect of Project Shakti on those self help group
members engaged in Project Shakti and those not engaged with
Project Shakti. Path analysis has been used to study the impact made
on those members engaged in Project Shakti. Significant differences
were observed on fronts of entrepreneurial development, economic
empowerment and social empowerment between members associated
with Project Shakti and those not associated with Project Shakti.
Path analysis demonstrated that involvement in Project Shakti led to
entrepreneurial development resulting in economic empowerment
that in turn led to social empowerment and that these three elements
independently induced a feeling of privilege in the women for being
associated with the Project.
Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: One promising way to achieve low temperature
combustion regime is the use of a large amount of cooled EGR. In
this paper, the effect of injection timing on low temperature
combustion process and emissions were investigated via three
dimensional computational fluid dynamics (CFD) procedures in a DI
diesel engine using high EGR rates. The results show when
increasing EGR from low levels to levels corresponding to reduced
temperature combustion, soot emission after first increasing, is
decreased beyond 40% EGR and get the lowest value at 58% EGR
rate. Soot and NOx emissions are simultaneously decreased at
advanced injection timing before 20.5 ºCA BTDC in conjunction
with 58% cooled EGR rate in compared to baseline case.
Abstract: Although current competitive challenges induced by today-s digital economy place their main emphasis on organizational knowledge, customer knowledge has been overlooked. On the other hand, the business community has finally begun to realize the important role customer knowledge can play in the organizational boundaries of the corporate arena. As a result, there is an emerging market for the tools and utilities whose objective is to provide the intelligence for knowledge sharing between the businesses and their customers. In this paper, we present a conceptual model of customer knowledge management by identifying and analyzing the existing tools in the market. The focus will be upon the emerging British dotcom industry whose customer based B2C behavior has been an influential part of the knowledge based intelligence tools in existence today.
Abstract: the elastic scattering of protons, deuterons and 3He on 6Li at different incident energies have been analyzed in the framework of the optical model using ECIS88 as well as SPI GENOA codes. The potential parameters were extracted in the phenomenological treatment of measured by us angular distributions and literature data. A good agreement between theoretical and experimental differential cross sections was obtained in whole angular range. Parameters for real part of potential have been also calculated microscopically with singleand double-folding model for the p and d, 3He scattering, respectively, using DFPOT code. For best agreement with experiment the normalization factor N for the potential depth is obtained in the range of 0.7-0.9.
Abstract: This paper proposes a novel multi-format stream grid
architecture for real-time image monitoring system. The system, based
on a three-tier architecture, includes stream receiving unit, stream
processor unit, and presentation unit. It is a distributed computing and
a loose coupling architecture. The benefit is the amount of required
servers can be adjusted depending on the loading of the image
monitoring system. The stream receive unit supports multi capture
source devices and multi-format stream compress encoder. Stream
processor unit includes three modules; they are stream clipping
module, image processing module and image management module.
Presentation unit can display image data on several different platforms.
We verified the proposed grid architecture with an actual test of image
monitoring. We used a fast image matching method with the
adjustable parameters for different monitoring situations. Background
subtraction method is also implemented in the system. Experimental
results showed that the proposed architecture is robust, adaptive, and
powerful in the image monitoring system.
Abstract: Many studies have emphasized the importance of
resistive exercise to maintain a healthy human body, particular in
prevention of weakening of physical strength. Recently, some studies
advocated that an application of vibration as a supplementary means in
a regular training was effective in encouraging physical strength. Aim
of the current study was, therefore, to identify if an application of
vibration in a resistive exercise was effective in encouraging physical
strength as that in a regular training. A 3-dimensional virtual lower
extremity model for a healthy male and virtual leg-press model were
generated and synchronized. Dynamic leg-press exercises on a slide
machine with/without extra load and on a footboard with vibration as
well as on a slide machine with extra load were analyzed. The results
of the current indicated that the application of the vibration on the
dynamic leg-press exercise might be not greatly effective in
encouraging physical strength, compared with the dynamic leg press
exercise with extra load. It was, however, thought that the application
of the vibration might be helpful to elderly individuals because the
reduced maximum muscle strength appeared by the effect of the
vibration may avoid a muscular spasm, which can be driven from a
high muscle strength sometimes produced during the leg-press
exercise with extra load.
Abstract: Crude oil blending is an important unit operation in
petroleum refining industry. A good model for the blending system is
beneficial for supervision operation, prediction of the export
petroleum quality and realizing model-based optimal control. Since
the blending cannot follow the ideal mixing rule in practice, we
propose a static neural network to approximate the blending
properties. By the dead-zone approach, we propose a new robust
learning algorithm and give theoretical analysis. Real data of crude
oil blending is applied to illustrate the neuro modeling approach.
Abstract: Near-infrared (NIR) spectroscopy is a widely used
method for material identification for laboratory and industrial applications.
While standard spectrometers only allow measurements at
one sampling point at a time, NIR Spectral Imaging techniques can
measure, in real-time, both the size and shape of an object as well as
identify the material the object is made of. The online classification
and sorting of recovered paper with NIR Spectral Imaging (SI)
is used with success in the paper recycling industry throughout
Europe. Recently, the globalisation of the recycling material streams
caused that water-based flexographic-printed newspapers mainly from
UK and Italy appear also in central Europe. These flexo-printed
newspapers are not sufficiently de-inkable with the standard de-inking
process originally developed for offset-printed paper. This de-inking
process removes the ink from recovered paper and is the fundamental
processing step to produce high-quality paper from recovered paper.
Thus, the flexo-printed newspapers are a growing problem for the
recycling industry as they reduce the quality of the produced paper
if their amount exceeds a certain limit within the recovered paper
material.
This paper presents the results of a research project for the
development of an automated entry inspection system for recovered
paper that was jointly conducted by CTR AG (Austria) and PTS
Papiertechnische Stiftung (Germany). Within the project an NIR
SI prototype for the identification of flexo-printed newspaper has
been developed. The prototype can identify and sort out flexoprinted
newspapers in real-time and achieves a detection accuracy
for flexo-printed newspaper of over 95%. NIR SI, the technology the
prototype is based on, allows the development of inspection systems
for incoming goods in a paper production facility as well as industrial
sorting systems for recovered paper in the recycling industry in the
near future.
Abstract: In this paper we propose a class of second derivative multistep methods for solving some well-known classes of Lane- Emden type equations which are nonlinear ordinary differential equations on the semi-infinite domain. These methods, which have good stability and accuracy properties, are useful in deal with stiff ODEs. We show superiority of these methods by applying them on the some famous Lane-Emden type equations.
Abstract: Short message integrated distributed monitoring systems (SM-DMS) are growing rapidly in wireless communication applications in various areas, such as electromagnetic field (EMF) management, wastewater monitoring, and air pollution supervision, etc. However, delay in short messages often makes the data embedded in SM-DMS transmit unreliably. Moreover, there are few regulations dealing with this problem in SMS transmission protocols. In this study, based on the analysis of the command and data requirements in the SM-DMS, we developed a processing model for the control center to solve the delay problem in data transmission. Three components of the model: the data transmission protocol, the receiving buffer pool method, and the timer mechanism were described in detail. Discussions on adjusting the threshold parameter in the timer mechanism were presented for the adaptive performance during the runtime of the SM-DMS. This model optimized the data transmission reliability in SM-DMS, and provided a supplement to the data transmission reliability protocols at the application level.
Abstract: Many electronic voting systems, classified mainly as homomorphic cryptography based, mix-net based and blind signature based, appear after the eighties when zero knowledge proofs were introduced. The common ground for all these three systems is that none of them works without real time cryptologic calculations that should be held on a server. As far as known, the agent-based approach has not been used in a secure electronic voting system. In this study, an agent-based electronic voting schema, which does not contain real time calculations on the server side, is proposed. Conventional cryptologic methods are used in the proposed schema and some of the requirements of an electronic voting system are constructed within the schema. The schema seems quite secure if the used cryptologic methods and agents are secure. In this paper, proposed schema will be explained and compared with already known electronic voting systems.
Abstract: Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.
Abstract: Particulate reinforced metal matrix composites
(MMCs) are potential materials for various applications due to their
advantageous of physical and mechanical properties. This paper
presents a study on the performance of stir cast Al2O3 SiC reinforced
metal matrix composite materials. The results indicate that the
composite materials exhibit improved physical and mechanical
properties, such as, low coefficient of thermal expansion, high
ultimate tensile strength, high impact strength, and hardness. It has
been found that with the increase of weight percentage of
reinforcement particles in the aluminium metal matrix, the new
material exhibits lower wear rate against abrasive wearing. Being
extremely lighter than the conventional gray cast iron material, the
Al-Al2O3 and Al-SiC composites could be potential green materials
for applications in the automobile industry, for instance, in making
car disc brake rotors.
Abstract: This paper presents an efficient algorithm for
optimization of radial distribution systems by a network
reconfiguration to balance feeder loads and eliminate overload
conditions. The system load-balancing index is used to determine the
loading conditions of the system and maximum system loading
capacity. The index value has to be minimum in the optimal network
reconfiguration of load balancing. A method based on Tabu search
algorithm, The Tabu search algorithm is employed to search for the
optimal network reconfiguration. The basic idea behind the search is
a move from a current solution to its neighborhood by effectively
utilizing a memory to provide an efficient search for optimality. It
presents low computational effort and is able to find good quality
configurations. Simulation results for a radial 69-bus system with
distributed generations and capacitors placement. The study results
show that the optimal on/off patterns of the switches can be identified
to give the best network reconfiguration involving balancing of
feeder loads while respecting all the constraints.
Abstract: Ecological ponds can be a good teaching tool for
science teachers, but they must be built and maintained properly to
provide students with a safe and suitable learning environment.
Hence, many schools do not have the ability to build an ecological
pond. This study used virtual reality technology to develop a webbased
virtual ecological pond. Supported by situated learning theory
and the instructional design of “Aquatic Life" learning unit,
elementary school students can actively explore in the virtual
ecological pond to observe aquatic animals and plants and learn
about the concept of ecological conservation. A teaching experiment
was conducted to investigate the learning effectiveness and
practicability of this instructional design, and the results showed that
students improved a great deal in learning about aquatic life. They
found the virtual ecological pond interesting, easy to operate and
helpful to understanding the aquatic ecological system. Therefore, it
is useful in elementary science education.
Abstract: A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance. Therefore, in this paper, we introduce a new approach aimed to solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that 2PO outperform the original algorithms in terms of query processing cost and view maintenance cost.
Abstract: In a pilot plant scale of a fluidized bed reactor, a
reduction reaction of sodium sulfate by natural gas has been
investigated. Natural gas is applied in this study as a reductant. Feed
density, feed mass flow rate, natural gas and air flow rate
(independent parameters)and temperature of bed and CO
concentration in inlet and outlet of reactor (dependent parameters)
were monitored and recorded at steady state. The residence time was
adjusted close to value of traditional reaction [1]. An artificial neural
network (ANN) was established to study dependency of yield and
carbon gradient on operating parameters. Resultant 97% accuracy of
applied ANN is a good prove that natural gas can be used as a
reducing agent. Predicted ANN model for relation between other
sources carbon gradient (accuracy 74%) indicates there is not a
meaningful relation between other sources carbon variation and
reduction process which means carbon in granule does not have
significant effect on the reaction yield.
Abstract: This paper describes the pipeline architecture of
high-speed modified Booth multipliers. The proposed multiplier
circuits are based on the modified Booth algorithm and the pipeline
technique which are the most widely used to accelerate the
multiplication speed. In order to implement the optimally pipelined
multipliers, many kinds of experiments have been conducted. The
speed of the multipliers is greatly improved by properly deciding the
number of pipeline stages and the positions for the pipeline registers to
be inserted. We described the proposed modified Booth multiplier
circuits in Verilog HDL and synthesized the gate-level circuits using
0.13um standard cell library. The resultant multiplier circuits show
better performance than others. Since the proposed multipliers operate
at GHz ranges, they can be used in the systems requiring very high
performance.
Abstract: A new estimator for evolutionary spectrum (ES) based
on short time Fourier transform (STFT) and modified group delay
function (MGDF) by signal decomposition (SD) is proposed. The
STFT due to its built-in averaging, suppresses the cross terms and the
MGDF preserves the frequency resolution of the rectangular window
with the reduction in the Gibbs ripple. The present work overcomes
the magnitude distortion observed in multi-component non-stationary
signals with STFT and MGDF estimation of ES using SD. The SD is
achieved either through discrete cosine transform based harmonic
wavelet transform (DCTHWT) or perfect reconstruction filter banks
(PRFB). The MGDF also improves the signal to noise ratio by
removing associated noise. The performance of the present method is
illustrated for cross chirp and frequency shift keying (FSK) signals,
which indicates that its performance is better than STFT-MGDF
(STFT-GD) alone. Further its noise immunity is better than STFT.
The SD based methods, however cannot bring out the frequency
transition path from band to band clearly, as there will be gap in the
contour plot at the transition. The PRFB based STFT-SD shows good
performance than DCTHWT decomposition method for STFT-GD.