Abstract: This paper contributes to our knowledge about buyerseller
relations by identifying barriers and conflict situations
associated with maintaining and developing durable business
relationships by small companies. The contribution of prior studies
with regard to negative aspects of marketing relationships is
presented in the first section. The international research results are
discussed with regard to the existing conceptualizations and main
research implications identified at the end.
Abstract: Inflammatory bowel disease (IBD) is a chronic
relapsing-remitting condition that afflicts millions of people
throughout the world and impairs their daily functions and quality of
life. Treatment of IBD depends largely on 5-aminosalicylic acid (5-
ASA) and corticosteroids. The present study aimed to clarify the
effects of 5-aminosalicylic acid, budesonide and currcumin on 90
male albino rats against trinitrobenzene sulfonic acid (TNB) induced
colitis. TNB was injected intrarectally to 50 rats. The other 40 rats
served as control groups. Both 5-ASA (in a dose of 120 mg/kg) and
budesonide (in a dose of 0.1 mg/kg) were administered daily for one
week whereas currcumin was injected intraperitonially (in a dose of
30 mg/kg daily) for 14 days after injection of either TNB in the
colitis rats (group B) or saline in control groups (group A). The study
included estimation of macroscopic score index, histological
examination of H&E stained sections of the colonic tissue,
biochemical estimation of myeloperoxidase (MPO), nitric oxide
(NO), and caspase-3 levels, in addition to studying the effect of tested
drugs on colonic motility. It was found that budesonide and curcumin
improved mucosal healing, reduced both NO production and caspase-
3 level. They had the best impact on the disturbed colonic motility in
TNBS-model of colitis.
Abstract: The decision of information technology (IT) outsourcing requires close attention to the evaluation of supplier selection process because the selection decision involves conflicting multiple criteria and is replete with complex decision making problems. Selecting the most appropriate suppliers is considered an important strategic decision that may impact the performance of outsourcing engagements. The objective of this paper is to aid decision makers to evaluate and assess possible IT outsourcing suppliers. An axiomatic design based fuzzy group decision making is adopted to evaluate supplier alternatives. Finally, a case study is given to demonstrate the potential of the methodology. KeywordsIT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic.
Abstract: Working memory (WM) can be defined as the system
which actively holds information in the mind to do tasks in spite of
the distraction. Contrary, short-term memory (STM) is a system that
represents the capacity for the active storing of information without
distraction. There has been accumulating evidence that these types of
memory are related to higher cognition (HC). The aim of this study
was to verify the relationship between HC and memory (visual STM
and WM, auditory STM and WM). 59 primary school children were
tested by intelligence test, mathematical tasks (HC) and memory
subtests. We have shown that visual but not auditory memory is a
significant predictor of higher cognition. The relevance of these
results are discussed.
Abstract: The aim of the study is to investigate a number of characteristics of Corporate Social Responsibility (CSR) indicators that should be adopted by CSR assessment methodologies. For the purpose of this paper, a survey among the Greek companies that belong to FTSE 20 in Athens Exchange (FTSE/Athex-20) has been conducted, as these companies are expected to pioneer in the field of CSR. The results show consensus as regards the characteristics of indicators such as the need for the adoption of general and specific sector indicators, financial and non-financial indicators, the origin and the weight rate. However, the results are contradictory concerning the appropriate number of indicators for the assessment of CSR and the unit of measurement. Finally, the company-s sector is a more important dimension of CSR than the size and the country where the company operates. The purpose of this paper is to standardize the main characteristics of CSR indicators.
Abstract: An incentive for performance, as one subsystem of a
new performance management system, has been implemented in the
Thai public sector since 2004. This research investigates the
development of organizational justice in the incentive allocation by
comparing the roles of distributive and procedural justice on national
personnel-s attitudinal outcomes (incentive satisfaction and job
performance) between 2 periods, i.e. 2006 and 2008. The data were
collected via self-administered questionnaires completed by national
government officers and employees. They were stratified using multistage
sampling with 2,600 usable samples or 72.0% response rate in
2006, and 1,969 usable samples or 59.3% in 2008. The findings are:
(1) There is no difference in means between the two periods relating
to distributive justice, procedural justice, incentive satisfaction and
job performance. (2) Distributive justice and procedural justice
played more important roles in predicting incentive satisfaction and
job performance in 2008 than in 2006.
Abstract: In order to enhance the aircraft survivability, the
infrared signatures emitted by hot engine parts should be determined
exactly. For its reduction it is necessary for the rear fuselage
temperature to be decreased. In this study, numerical modeling of flow
fields and heat transfer characteristics of an aircraft nozzle is
performed and its temperature distribution along each component wall
is predicted. The radiation shield is expected to reduce the skin
temperature of rear fuselage. The effect of material characteristic of
radiation shield on the heat transfer is also investigated. Through this
numerical analysis, design parameters related to the susceptibility of
aircraft are examined.
Abstract: BEAMnrc was used to calculate the spectrum and
HVL for X-ray Beam during low energy X-ray radiation using tube model: SRO 33/100 /ROT 350 Philips. The results of BEAMnrc
simulation and measurements were compared to the IPEM report
number 78 and SpekCalc software. Three energies 127, 103 and 84
Kv were used. In these simulation a tungsten anode with 1.2 mm for
Be window were used as source. HVLs were calculated from
BEAMnrc spectrum with air Kerma method for four different filters.
For BEAMnrc one billion particles were used as original particles for
all simulations. The results show that for 127 kV, there was
maximum 5.2 % difference between BEAMnrc and Measurements
and minimum was 0.7% .the maximum 9.1% difference between
BEAMnrc and IPEM and minimum was 2.3% .The maximum
difference was 3.2% between BEAMnrc and SpekCal and minimum
was 2.8%. The result show BEAMnrc was able to satisfactory predict
the quantities of Low energy Beam as well as high energy X-ray
radiation.
Abstract: Friction Stir Welding is a solid state welding technique which can be used to produce sound welds between similar and dissimilar materials. Dissimilar welds which include welds between the different series of aluminium alloys, aluminium to magnesium, steel and titanium has been successfully produced by many researchers. This review covers the work conducted in the above mentioned materials and further concludes by showing the need to fully understand the FSW process in order to expand the latter industrially.
Abstract: When considering the development of constitutive
equations describing the behavior of materials under cyclic plastic
strains, different kinds of formulations can be adopted. The primary
intention of this study is to develop computer programming of
plasticity models to accurately predict the life of engineering
components. For this purpose, the energy or cyclic strain is computed
in multi-surface plasticity models in non-proportional loading and to
present their procedures and codes results.
Abstract: With the advent of new technologies, factors related to
mental health in e-workspaces are taken into consideration more than
ever. Studies have revealed that one of the factors affecting the
productivity of employees in an organization is occupational stress.
Another influential factor is quality of work life which is important in
the improvement of work environment conditions and organizational
efficiency. In order to uncover the quality of work life level and to
investigate the impact of occupational stress on quality of work life
among information technology employees in Iran, a cross-sectional
study design was applied and data were gathered using a
questionnaire validated by a group of experts. The results of the study
showed that information technology staffs have average level of both
occupational stress and quality of work life. Furthermore, it was
found that occupational stress has a negative impact on quality of
work life. In addition, the same results were observed for role
ambiguity, role conflict, role under-load, work-pace, work
repetitiveness and tension toward quality of work life. No significant
relation was found between role overload and quality of work life.
Finally, directions for future research are proposed and discussed.
Abstract: The objective of this paper is to investigate a new
approach based on the idea of pictograms for food portion size. This
approach adopts the model of the United States Pharmacopeia- Drug
Information (USP-DI). The representation of each food portion size
composed of three parts: frame, the connotation of dietary portion
sizes and layout. To investigate users- comprehension based on this
approach, two experiments were conducted, included 122 Taiwanese
people, 60 male and 62 female with ages between 16 and 64 (divided
into age groups of 16-30, 31-45 and 46-64). In Experiment 1, the mean
correcting rate of the understanding level of food items is 48.54%
(S.D.= 95.08) and the mean response time 2.89sec (S.D.=2.14). The
difference on the correct rates for different age groups is significant
(P*=0.00
Abstract: This paper proposes a novel hybrid algorithm for feature selection based on a binary ant colony and SVM. The final subset selection is attained through the elimination of the features that produce noise or, are strictly correlated with other already selected features. Our algorithm can improve classification accuracy with a small and appropriate feature subset. Proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through a real Rotary Cement kiln dataset. The results show that our algorithm outperforms existing algorithms.
Abstract: Chikungunya virus (CHICKV) is an arboviruses belonging to family Tagoviridae and is transmitted to human through by mosquito (Aedes aegypti and Aedes albopictus) bite. A large outbreak of chikungunya has been reported in India between 2006 and 2007, along with several other countries from South-East Asia and for the first time in Europe. It was for the first time that the CHICKV outbreak has been reported with mortality from Reunion Island and increased mortality from Asian countries. CHICKV affects all age groups, and currently there are no specific drugs or vaccine to cure the disease. The need of antiviral agents for the treatment of CHICKV infection and the success of virtual screening against many therapeutically valuable targets led us to carry out the structure based drug design against Chikungunya nSP2 protease (PDB: 3TRK). Highthroughput virtual screening of publicly available databases, ZINC12 and BindingDB, has been carried out using the Openeye tools and Schrodinger LLC software packages. Openeye Filter program has been used to filter the database and the filtered outputs were docked using HTVS protocol implemented in GLIDE package of Schrodinger LLC. The top HITS were further used for enriching the similar molecules from the database through vROCS; a shape based screening protocol implemented in Openeye. The approach adopted has provided different scaffolds as HITS against CHICKV protease. Three scaffolds: Indole, Pyrazole and Sulphone derivatives were selected based on the docking score and synthetic feasibility. Derivatives of Pyrazole were synthesized and submitted for antiviral screening against CHICKV.
Abstract: Fault-proneness of a software module is the
probability that the module contains faults. A correlation exists
between the fault-proneness of the software and the measurable
attributes of the code (i.e. the static metrics) and of the testing (i.e.
the dynamic metrics). Early detection of fault-prone software
components enables verification experts to concentrate their time and
resources on the problem areas of the software system under
development. This paper introduces Genetic Algorithm based
software fault prediction models with Object-Oriented metrics. The
contribution of this paper is that it has used Metric values of JEdit
open source software for generation of the rules for the classification
of software modules in the categories of Faulty and non faulty
modules and thereafter empirically validation is performed. The
results shows that Genetic algorithm approach can be used for
finding the fault proneness in object oriented software components.
Abstract: Until recently, researchers have developed various
tools and methodologies for effective clinical decision-making.
Among those decisions, chest pain diseases have been one of
important diagnostic issues especially in an emergency department. To
improve the ability of physicians in diagnosis, many researchers have
developed diagnosis intelligence by using machine learning and data
mining. However, most of the conventional methodologies have been
generally based on a single classifier for disease classification and
prediction, which shows moderate performance. This study utilizes an
ensemble strategy to combine multiple different classifiers to help
physicians diagnose chest pain diseases more accurately than ever.
Specifically the ensemble strategy is applied by using the integration
of decision trees, neural networks, and support vector machines. The
ensemble models are applied to real-world emergency data. This study
shows that the performance of the ensemble models is superior to each
of single classifiers.
Abstract: This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
Abstract: Internal combustion engines rejects 30-40% of the
energy supplied by fuel to the environment through exhaust gas. thus, there is a possibility for further significant improvement of efficiency with the utilization of exhaust gas energy and its conversion to mechanical energy or electrical energy. The Thermo-Electric
Generator (TEG) will be located in the exhaust system and will make use of an energy flow between the warmer exhaust gas and the external environment. Predict to th optimum position of temperature
distribution and the performance of TEG through numerical analysis.
The experimental results obtained show that the power output significantly increases with the temperature difference between cold
and hot sides of a thermoelectric generator.
Abstract: In sport, human resources management gives special
attention to method of applying volunteers, their maintenance, and
participation of volunteers with each other and management
approaches for better operation of events celebrants. The recognition
of volunteers- characteristics and motives is important to notice,
because it makes the basis of their participation and commitment at
sport environment. The motivation and commitment of 281
volunteers were assessed using the organizational commitment scale,
motivation scale and personal characteristics questionnaire.The
descriptive results showed that; 64% of volunteers were women with
age average 21/24 years old. They were physical education student,
single (71/9%), without occupation (53%) and with average of 5
years sport experience. Their most important motivation was career
factor and the most important commitment factor was normative
factor. The results of examining the hypothesized showed that; age,
sport experience and education are effective in the amount of
volunteers- commitment. And the motive factors such as career,
material, purposive and protective factors also have the power to
predict the amount of sports volunteers- commitment value.
Therefore it is recommended to provide possible opportunities for
volunteers and carrying out appropriate instructional courses by
events executive managers.
Abstract: Purpose: To explore the use of Curvelet transform to
extract texture features of pulmonary nodules in CT image and support
vector machine to establish prediction model of small solitary
pulmonary nodules in order to promote the ratio of detection and
diagnosis of early-stage lung cancer. Methods: 2461 benign or
malignant small solitary pulmonary nodules in CT image from 129
patients were collected. Fourteen Curvelet transform textural features
were as parameters to establish support vector machine prediction
model. Results: Compared with other methods, using 252 texture
features as parameters to establish prediction model is more proper.
And the classification consistency, sensitivity and specificity for the
model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based
on texture features extracted from Curvelet transform, support vector
machine prediction model is sensitive to lung cancer, which can
promote the rate of diagnosis for early-stage lung cancer to some
extent.