Abstract: Given the limited research on Small and Mediumsized
Enterprises’ (SMEs) contribution to Corporate Social
Responsibility (CSR) and even scarcer research on Swiss SMEs, this
paper helps to fill these gaps by enabling the identification of supranational
SME parameters. Thus, the paper investigates the current
state of SME practices in Switzerland and across 15 other countries.
Combining the degree to which SMEs demonstrate an explicit (or
business case) approach or see CSR as an implicit moral activity with
the assessment of their attributes for “variety of capitalism” defines
the framework of this comparative analysis. To outline Swiss small
business CSR patterns in particular, 40 SME owner-managers were
interviewed. A secondary data analysis of studies from different
countries laid groundwork for this comparative overview of small
business CSR. The paper identifies Swiss small business CSR as
driven by norms, values, and by the aspiration to contribute to
society, thus, as an implicit part of the day-to-day business. Similar to
most Central European, Mediterranean, Nordic, and Asian countries,
explicit CSR is still very rare in Swiss SMEs. Astonishingly, also
British and American SMEs follow this pattern in spite of their strong
and distinctly liberal market economies. Though other findings show
that nationality matters this research concludes that SME culture and
an informal CSR agenda are strongly formative and superseding even
forces of market economies, nationally cultural patterns, and
language. Hence, classifications of countries by their market system,
as found in the comparative capitalism literature, do not match the
CSR practices in SMEs as they do not mirror the peculiarities of their
business. This raises questions on the universality and
generalisability of unmediated, explicit management concepts,
especially in the context of small firms.
Abstract: STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to real-world data
Abstract: In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.
Abstract: Nowadays, cloud environments are becoming a need for companies, this new technology gives the opportunities to access to the data anywhere and anytime. It also provides an optimized and secured access to the resources and gives more security for the data which is stored in the platform. However, some companies do not trust Cloud providers, they think that providers can access and modify some confidential data such as bank accounts. Many works have been done in this context, they conclude that encryption methods realized by providers ensure the confidentiality, but, they forgot that Cloud providers can decrypt the confidential resources. The best solution here is to apply some operations on the data before sending them to the provider Cloud in the objective to make them unreadable. The principal idea is to allow user how it can protect his data with his own methods. In this paper, we are going to demonstrate our approach and prove that is more efficient in term of execution time than some existing methods. This work aims at enhancing the quality of service of providers and ensuring the trust of the customers.
Abstract: High resolution images are always desired as they contain the more information and they can better represent the original data. So, to convert the low resolution image into high resolution interpolation is done. The quality of such high resolution image depends on the interpolation function and is assessed in terms of sharpness of image. This paper focuses on Wavelet based Interpolation Techniques in which an input image is divided into subbands. Each subband is processed separately and finally combined the processed subbandsto get the super resolution image.
Abstract: Obesity and osteoporosis are the two diseases whose
increasing prevalence and high impact on the global morbidity and
mortality, during the two recent decades, have gained a status of
major health threats worldwide. Obesity purports to affect the bone
metabolism through complex mechanisms. Debated data on the
connection between the bone mineral density and fracture prevalence
in the obese patients are widely presented in literature. There is
evidence that the correlation of weight and fracture risk is sitespecific.
This study is aimed at determining the connection between
the bone mineral density (BMD) and trabecular bone score (TBS)
parameters in Ukrainian women suffering from obesity. We
examined 1025 40-89-year-old women, divided them into the groups
according to their body mass index: Group A included 360 women
with obesity whose BMI was ≥30 kg/m2, and Group B – 665 women
with no obesity and BMI of
Abstract: Supply chains are the backbone of trade and
commerce. Their logistics use different transport corridors on regular
basis for operational purpose. The international supply chain
transport corridors include different infrastructure elements (e.g.
weighbridge, package handling equipments, border clearance
authorities, and so on). This paper presents the use of multi-agent
systems (MAS) to model and simulate some aspects of transportation
corridors, and in particular the area of weighbridge resource
optimization for operational profit. An underlying multi-agent model
provides a means of modeling the relationships among stakeholders
in order to enable coordination in a transport corridor environment.
Simulations of the costs of container unloading, reloading, and
waiting time for queuing up tracks have been carried out using data
sets. Results of the simulation provide the potential guidance in
making decisions about optimal service resource allocation in a trade
corridor.
Abstract: Aim of this research study is to investigate and
establish the characteristics of brain dominances (BD) and multiple
intelligences (MI). This experimentation has been conducted for the
sample size of 552 undergraduate computer-engineering students. In
addition, mathematical formulation has been established to exhibit
the relation between thinking and intelligence, and its correlation has
been analyzed. Correlation analysis has been statistically measured
using Pearson’s coefficient. Analysis of the results proves that there
is a strong relational existence between thinking and intelligence.
This research is carried to improve the didactic methods in
engineering learning and also to improve e-learning strategies.
Abstract: The main objective of this study was to assess the
annual concentration and seasonal variation of benzo(a)pyrene (BaP)
associated with PM10 in an urban site of Győr and in a rural site of
Sarród in the sampling period of 2008–2012. A total of 280 PM10
aerosol samples were collected in each sampling site and analyzed for
BaP by gas chromatography method. The BaP concentrations ranged
from undetected to 8 ng/m3 with the mean value of 1.01 ng/m3 in the
sampling site of Győr, and from undetected to 4.07 ng/m3 with the
mean value of 0.52 ng/m3 in the sampling site of Sarród, respectively.
Relatively higher concentrations of BaP were detected in samples
collected in both sampling sites in the heating seasons compared with
non-heating periods. The annual mean BaP concentrations were
comparable with the published data of different other Hungarian
sites.
Abstract: In present study, it was aimed to determine potential
agricultural lands (PALs) in Gokceada (Imroz) Island of Canakkale
province, Turkey. Seven-band Landsat 8 OLI images acquired on
July 12 and August 13, 2013, and their 14-band combination image
were used to identify current Land Use Land Cover (LULC) status.
Principal Component Analysis (PCA) was applied to three Landsat
datasets in order to reduce the correlation between the bands. A total
of six Original and PCA images were classified using supervised
classification method to obtain the LULC maps including 6 main
classes (“Forest”, “Agriculture”, “Water Surface”, “Residential Area-
Bare Soil”, “Reforestation” and “Other”). Accuracy assessment was
performed by checking the accuracy of 120 randomized points for
each LULC maps. The best overall accuracy and Kappa statistic
values (90.83%, 0.8791% respectively) were found for PCA images
which were generated from 14-bands combined images called 3-
B/JA.
Digital Elevation Model (DEM) with 15 m spatial resolution
(ASTER) was used to consider topographical characteristics. Soil
properties were obtained by digitizing 1:25000 scaled soil maps of
Rural Services Directorate General. Potential Agricultural Lands
(PALs) were determined using Geographic information Systems
(GIS). Procedure was applied considering that “Other” class of
LULC map may be used for agricultural purposes in the future
properties. Overlaying analysis was conducted using Slope (S), Land
Use Capability Class (LUCC), Other Soil Properties (OSP) and Land
Use Capability Sub-Class (SUBC) properties.
A total of 901.62 ha areas within “Other” class (15798.2 ha) of
LULC map were determined as PALs. These lands were ranked as
“Very Suitable”, “Suitable”, “Moderate Suitable” and “Low
Suitable”. It was determined that the 8.03 ha were classified as “Very
Suitable” while 18.59 ha as suitable and 11.44 ha as “Moderate
Suitable” for PALs. In addition, 756.56 ha were found to be “Low
Suitable”. The results obtained from this preliminary study can serve
as basis for further studies.
Abstract: To construct the lumped spring-mass model
considering the occupants for the offset frontal crash, the SISAME
software and the NHTSA test data were used. The data on 56 kph 40%
offset frontal vehicle to deformable barrier crash test of a MY2007
Mazda 6 4-door sedan were obtained from NHTSA test database. The
overall behaviors of B-pillar and engine of simulation models agreed
very well with the test data. The trends of accelerations at the driver
and passenger head were similar but big differences in peak values.
The differences of peak values caused the large errors of the HIC36
and 3 ms chest g’s. To predict well the behaviors of dummies, the
spring-mass model for the offset frontal crash needs to be improved.
Abstract: Designing cost-efficient, secure network protocols for
Wireless Sensor Networks (WSNs) is a challenging problem because
sensors are resource-limited wireless devices. Security services such
as authentication and improved pairwise key establishment are
critical to high efficient networks with sensor nodes. For sensor
nodes to correspond securely with each other efficiently, usage of
cryptographic techniques is necessary. In this paper, two key
predistribution schemes that enable a mobile sink to establish a
secure data-communication link, on the fly, with any sensor nodes.
The intermediate nodes along the path to the sink are able to verify
the authenticity and integrity of the incoming packets using a
predicted value of the key generated by the sender’s essential power.
The proposed schemes are based on the pairwise key with the mobile
sink, our analytical results clearly show that our schemes perform
better in terms of network resilience to node capture than existing
schemes if used in wireless sensor networks with mobile sinks.
Abstract: This paper presents an approach for the classification of
an unstructured format description for identification of file formats.
The main contribution of this work is the employment of data mining
techniques to support file format selection with just the unstructured
text description that comprises the most important format features for
a particular organisation. Subsequently, the file format indentification
method employs file format classifier and associated configurations to
support digital preservation experts with an estimation of required file
format. Our goal is to make use of a format specification knowledge
base aggregated from a different Web sources in order to select file
format for a particular institution. Using the naive Bayes method,
the decision support system recommends to an expert, the file format
for his institution. The proposed methods facilitate the selection of
file format and the quality of a digital preservation process. The
presented approach is meant to facilitate decision making for the
preservation of digital content in libraries and archives using domain
expert knowledge and specifications of file formats. To facilitate
decision-making, the aggregated information about the file formats is
presented as a file format vocabulary that comprises most common
terms that are characteristic for all researched formats. The goal is to
suggest a particular file format based on this vocabulary for analysis
by an expert. The sample file format calculation and the calculation
results including probabilities are presented in the evaluation section.
Abstract: The aim of this investigation is to elaborate nearinfrared
methods for testing and recognition of chemical components
and quality in “Pannon wheat” allied (i.e. true to variety or variety
identified) milling fractions as well as to develop spectroscopic
methods following the milling processes and evaluate the stability of
the milling technology by different types of milling products and
according to sampling times, respectively. These wheat categories
produced under industrial conditions where samples were collected
versus sampling time and maximum or minimum yields. The changes
of the main chemical components (such as starch, protein, lipid) and
physical properties of fractions (particle size) were analysed by
dispersive spectrophotometers using visible (VIS) and near-infrared
(NIR) regions of the electromagnetic radiation. Close correlation
were obtained between the data of spectroscopic measurement
techniques processed by various chemometric methods (e.g. principal
component analysis [PCA], cluster analysis [CA]) and operation
condition of milling technology. It is obvious that NIR methods are
able to detect the deviation of the yield parameters and differences of
the sampling times by a wide variety of fractions, respectively. NIR
technology can be used in the sensitive monitoring of milling
technology.
Abstract: By the evolvement in technology, the way of
expressing opinions switched direction to the digital world. The
domain of politics, as one of the hottest topics of opinion mining
research, merged together with the behavior analysis for affiliation
determination in texts, which constitutes the subject of this paper.
This study aims to classify the text in news/blogs either as
Republican or Democrat with the minimum number of features. As
an initial set, 68 features which 64 were constituted by Linguistic
Inquiry and Word Count (LIWC) features were tested against 14
benchmark classification algorithms. In the later experiments, the
dimensions of the feature vector reduced based on the 7 feature
selection algorithms. The results show that the “Decision Tree”,
“Rule Induction” and “M5 Rule” classifiers when used with “SVM”
and “IGR” feature selection algorithms performed the best up to
82.5% accuracy on a given dataset. Further tests on a single feature
and the linguistic based feature sets showed the similar results. The
feature “Function”, as an aggregate feature of the linguistic category,
was found as the most differentiating feature among the 68 features
with the accuracy of 81% in classifying articles either as Republican
or Democrat.
Abstract: Submerged arc welding is a very complex process. It
is a very efficient and high performance welding process. In this
present study an attempt have been done to reduce the welding
distortion by increased amount of oxide flux through TiO2 in
submerged arc welding process. Care has been taken to avoid the
excessiveness of the adding agent for attainment of significant
results. Data Envelopment Analysis (DEA) based BAT algorithm is
used for the parametric optimization purpose in which DEA is used
to convert multi response parameters into a single response
parameter. The present study also helps to know the effectiveness of
the addition of TiO2 in active flux during submerged arc welding
process.
Abstract: In this study, the experiments were carried out to
determine the best coolant for the quenching process among waterbased
silica, alumina, titania and copper oxide nanofluids (0.1 vol%).
A sphere made up off brass material was used in the experiments.
When the spherical test specimen was heated at high temperatures, it
was suddenly immersed into the nanofluids. All experiments were
carried out at saturated conditions and under atmospheric pressure.
After the experiments, the cooling curves were obtained by using the
temperature-time data of the specimen. The experimental results
showed that the cooling performance of test specimen depended on
the type of nanofluids. The silica nanoparticles enhanced the
performance of boiling heat transfer and it is the best coolant for the
quenching among other nanoparticles.
Abstract: As technology-based service industries grow
drastically worldwide; companies are recognizing the importance of
market preoccupancy and have made an effort to capture a large
market to gain the upper hand. To this end, a focus on patents can be
used to determine the properties of a technology, as well as to capture
advantages in technical skills, in comparison with the firm’s
competitors. However, technology-based services largely depend not
only on their technological value but also their economic value, due
to the recognized worth that is passed to a plurality of users. Thus, it
is important to determine whether there are any competitors in the
target areas and what services they provide in any field. Despite this
importance, little effort has been made to systematically benchmark
competitors in order to identify business opportunities. Thus, this
study aims to not only identify each position of technology-centered
service companies in complex market dynamics, but also to discover
new business opportunities. For this, we try to consider both
technology and market environments simultaneously by utilizing
patent data as a representative proxy for technology and trademark
dates as an index for a firm’s target goods and services. Theoretically,
this is one of the earliest attempts to combine patent data and
trademark data to analyze corporate strategies. In practice, the
research results are expected to be used as a decision criterion to
diagnose the economic value that companies can obtain by entering
the market, as well as the technological value to be passed onto their
customers. Thus, the proposed approach can be useful to support
effective technology and business strategies in a firm.
Abstract: Any signal transmitted over a channel is corrupted by noise and interference. A host of channel coding techniques has been proposed to alleviate the effect of such noise and interference. Among these Turbo codes are recommended, because of increased capacity at higher transmission rates and superior performance over convolutional codes. The multimedia elements which are associated with ample amount of data are best protected by Turbo codes. Turbo decoder employs Maximum A-posteriori Probability (MAP) and Soft Output Viterbi Decoding (SOVA) algorithms. Conventional Turbo coded systems employ Equal Error Protection (EEP) in which the protection of all the data in an information message is uniform. Some applications involve Unequal Error Protection (UEP) in which the level of protection is higher for important information bits than that of other bits. In this work, enhancement to the traditional Log MAP decoding algorithm is being done by using optimized scaling factors for both the decoders. The error correcting performance in presence of UEP in Additive White Gaussian Noise channel (AWGN) and Rayleigh fading are analyzed for the transmission of image with Discrete Cosine Transform (DCT) as source coding technique. This paper compares the performance of log MAP, Modified log MAP (MlogMAP) and Enhanced log MAP (ElogMAP) algorithms used for image transmission. The MlogMAP algorithm is found to be best for lower Eb/N0 values but for higher Eb/N0 ElogMAP performs better with optimized scaling factors. The performance comparison of AWGN with fading channel indicates the robustness of the proposed algorithm. According to the performance of three different message classes, class3 would be more protected than other two classes. From the performance analysis, it is observed that ElogMAP algorithm with UEP is best for transmission of an image compared to Log MAP and MlogMAP decoding algorithms.
Abstract: A sensory network consists of multiple detection
locations called sensor nodes, each of which is tiny, featherweight
and portable. A single path routing protocols in wireless sensor
network can lead to holes in the network, since only the nodes
present in the single path is used for the data transmission. Apart
from the advantages like reduced computation, complexity and
resource utilization, there are some drawbacks like throughput,
increased traffic load and delay in data delivery. Therefore, multipath
routing protocols are preferred for WSN. Distributing the traffic
among multiple paths increases the network lifetime. We propose a
scheme, for the data to be transmitted through a dominant path to
save energy. In order to obtain a high delivery ratio, a basic route
reconstruction protocol is utilized to reconstruct the path whenever a
failure is detected. A basic reconstruction routing (BRR) algorithm is
proposed, in which a node can leap over path failure by using the
already existing routing information from its neighbourhood while
the composed data is transmitted from the source to the sink. In order
to save the energy and attain high data delivery ratio, data is
transmitted along a multiple path, which is achieved by BRR
algorithm whenever a failure is detected. Further, the analysis of
how the proposed protocol overcomes the drawback of the existing
protocols is presented. The performance of our protocol is compared
to AOMDV and energy efficient node-disjoint multipath routing
protocol (EENDMRP). The system is implemented using NS-2.34.
The simulation results show that the proposed protocol has high
delivery ratio with low energy consumption.