Abstract: Today, wine quality is only evaluated by wine experts with their own different personal tastes, even if they may agree on some common features. So producers do not have any unbiased way to independently assess the quality of their products. A tool is here proposed to evaluate wine quality by an objective ranking based upon the variables entering wine elaboration, and analysed through principal component analysis (PCA) method. Actual climatic data are compared by measuring the relative distance between each considered wine, out of which the general ranking is performed.
Abstract: This paper discusses the intake of combining multi-criteria
decision analysis (MCDA) with OLAP systems, to generate
an integrated analysis process dealing with complex multi-criteria
decision-making situations. In this context, a multi-agent modeling is
presented for decision support systems by combining multi-criteria
decision analysis (MCDA) with OLAP systems. The proposed
modeling which consists in performing the multi-agent system
(MAS) architecture, procedure and protocol of the negotiation model
is elaborated as a decision support tool for complex decision-making
environments. Our objective is to take advantage from the multi-agent
system which distributes resources and computational
capabilities across interconnected agents, and provide a problem
modeling in terms of autonomous interacting component-agents.
Thus, the identification and evaluation of criteria as well as the
evaluation and ranking of alternatives in a decision support situation
will be performed by organizing tasks and user preferences between
different agents in order to reach the right decision. At the end, an
illustrative example is conducted to demonstrate the function and
effectiveness of our MAS modeling.
Abstract: Energy has a prominent role for development of
nations. Countries which have energy resources also have strategic
power in the international trade of energy since it is essential for all
stages of production in the economy. Thus, it is important for
countries to analyze the weaknesses and strength of the system. On
the other side, international trade is one of the fields that are analyzed
as a complex network via network analysis. Complex network is one
of the tools to analyze complex systems with heterogeneous agents
and interaction between them. A complex network consists of nodes
and the interactions between these nodes. Total properties which
emerge as a result of these interactions are distinct from the sum of
small parts (more or less) in complex systems. Thus, standard
approaches to international trade are superficial to analyze these
systems. Network analysis provides a new approach to analyze
international trade as a network. In this network, countries constitute
nodes and trade relations (export or import) constitute edges. It
becomes possible to analyze international trade network in terms of
high degree indicators which are specific to complex networks such
as connectivity, clustering, assortativity/disassortativity, centrality,
etc. In this analysis, international trade of crude oil and coal which
are types of fossil fuel has been analyzed from 2005 to 2014 via
network analysis. First, it has been analyzed in terms of some
topological parameters such as density, transitivity, clustering etc.
Afterwards, fitness to Pareto distribution has been analyzed via
Kolmogorov-Smirnov test. Finally, weighted HITS algorithm has
been applied to the data as a centrality measure to determine the real
prominence of countries in these trade networks. Weighted HITS
algorithm is a strong tool to analyze the network by ranking countries
with regards to prominence of their trade partners. We have
calculated both an export centrality and an import centrality by
applying w-HITS algorithm to the data. As a result, impacts of the
trading countries have been presented in terms of high-degree
indicators.
Abstract: Environmental concerns about the scarcity of marine
resources are critical driving forces for firms aiming to prepare their
supply chains for sustainability. Building on previous work, this
paper highlights the implementation of good practices geared towards
sustainable operations in the seafood department, which were
pursued in an exploratory retailer case. Outcomes of the adopted
environmentally and socially acceptable fish retailing strategies,
ranged from traceability, to self-certification and eco-labelling. The
consequences for business were, as follows: stronger collaboration
and trust across the chain of custody, improvement of sponsors’
image and of consumers’ loyalty and, progress in the Greenpeace
retailers’ evaluation ranking.
Abstract: Noninvasive diagnostics of diseases via breath
analysis has attracted considerable scientific and clinical interest for
many years and become more and more promising with the rapid
advancements in nanotechnology and biotechnology. The volatile
organic compounds (VOCs) in exhaled breath, which are mainly
blood borne, particularly provide highly valuable information about
individuals’ physiological and pathophysiological conditions.
Additionally, breath analysis is noninvasive, real-time, painless, and
agreeable to patients. We have developed a wireless sensor array
based on single-stranded DNA (ssDNA)-functionalized single-walled
carbon nanotubes (SWNT) for the detection of a number of
physiological indicators in breath. Seven DNA sequences were used
to functionalize SWNT sensors to detect trace amount of methanol,
benzene, dimethyl sulfide, hydrogen sulfide, acetone, and ethanol,
which are indicators of heavy smoking, excessive drinking, and
diseases such as lung cancer, breast cancer, and diabetes. Our test
results indicated that DNA functionalized SWNT sensors exhibit
great selectivity, sensitivity, and repeatability; and different
molecules can be distinguished through pattern recognition enabled
by this sensor array. Furthermore, the experimental sensing results
are consistent with the Molecular Dynamics simulated ssDNAmolecular
target interaction rankings. Thus, the DNA-SWNT sensor
array has great potential to be applied in chemical or biomolecular
detection for the noninvasive diagnostics of diseases and personal
health monitoring.
Abstract: This paper is meant to analyze the ranking of
University of Malaysia Terengganu, UMT’s website in the World
Wide Web. There are only few researches have been done on
comparing the ranking of universities’ websites so this research will
be able to determine whether the existing UMT’s website is serving
its purpose which is to introduce UMT to the world. The ranking is
based on hub and authority values which are accordance to the
structure of the website. These values are computed using two websearching
algorithms, HITS and SALSA. Three other universities’
websites are used as the benchmarks which are UM, Harvard and
Stanford. The result is clearly showing that more work has to be done
on the existing UMT’s website where important pages according to
the benchmarks, do not exist in UMT’s pages. The ranking of UMT’s
website will act as a guideline for the web-developer to develop a
more efficient website.
Abstract: This paper develops a multiple channel assignment
model, which allows to take advantage of spectrum opportunities in
cognitive radio networks in the most efficient way. The developed
scheme allows making several assignments of available and
frequency adjacent channel, which require a bigger bandwidth, under
an equality environment. The hybrid assignment model it is made by
two algorithms, one that makes the ranking and selects available
frequency channels and the other one in charge of establishing the
Max-Min Fairness for not restrict the spectrum opportunities for all
the other secondary users, who also claim to make transmissions.
Measurements made were done for average bandwidth, average
delay, as well as fairness computation for several channel
assignments. Reached results were evaluated with experimental
spectrum occupational data from captured GSM frequency band. The
developed model shows evidence of improvement in spectrum
opportunity use and a wider average transmission bandwidth for each
secondary user, maintaining equality criteria in channel assignment.
Abstract: Erosion and abrasion are wear mechanisms reducing
the lifetime of machine elements like valves, pump and pipe systems.
Both wear mechanisms are acting at the same time, causing a
“Synergy” effect, which leads to a rapid damage of the surface.
Different parameters are effective on erosive abrasive wear rate. In
this study effect of particle impact angle on wear rate and wear
mechanism of ductile and brittle materials was investigated. A new
slurry pot was designed for experimental investigation. As abrasive
particle, silica sand was used. Particle size was ranking between 200-
500 μm. All tests were carried out in a sand-water mixture of 20%
concentration for four hours. Impact velocities of the particles were
4.76 m/s. As ductile material steel St 37 with Vickers Hardness
Number (VHN) of 245 and quenched St 37 with 510 VHN was used
as brittle material. After wear tests, morphology of the eroded
surfaces were investigated for better understanding of the wear
mechanisms acting at different impact angles by using Scanning
Electron Microscope. The results indicated that wear rate of ductile
material was higher than brittle material. Maximum wear rate was
observed by ductile material at a particle impact angle of 300 and
decreased further by an increase in attack angle. Maximum wear rate
by brittle materials was by impact angle of 450 and decreased further
up to 900. Ploughing was the dominant wear mechanism by ductile
material. Microcracks on the surface were detected by ductile
materials, which are nucleation centers for crater formation. Number
of craters decreased and depth of craters increased by ductile
materials by attack angle higher than 300. Deformation wear
mechanism was observed by brittle materials. Number and depth of
pits decreased by brittle materials by impact angles higher than 450.
At the end it is concluded that wear rate could not be directly related
to impact angle of particles due to the different reaction of ductile and
brittle materials.
Abstract: This paper investigates the benefits of deliberately
unbalancing both operation time means (MTs) and unreliability
(failure and repair rates) for non-automated production lines. The
lines were simulated with various line lengths, buffer capacities,
degrees of imbalance and patterns of MT and unreliability imbalance.
Data on two performance measures, namely throughput (TR) and
average buffer level (ABL) were gathered, analyzed and compared to
a balanced line counterpart. A number of conclusions were made
with respect to the ranking of configurations, as well as to the
relationships among the independent design parameters and the
dependent variables. It was found that the best configurations are a
balanced line arrangement and a monotone decreasing MT order,
coupled with either a decreasing or a bowl unreliability configuration,
with the first generally resulting in a reduced TR and the second
leading to a lower ABL than those of a balanced line.
Abstract: Due to the rapid increase of Internet, web opinion
sources dynamically emerge which is useful for both potential
customers and product manufacturers for prediction and decision
purposes. These are the user generated contents written in natural
languages and are unstructured-free-texts scheme. Therefore, opinion
mining techniques become popular to automatically process customer
reviews for extracting product features and user opinions expressed
over them. Since customer reviews may contain both opinionated and
factual sentences, a supervised machine learning technique applies
for subjectivity classification to improve the mining performance. In
this paper, we dedicate our work is the task of opinion
summarization. Therefore, product feature and opinion extraction is
critical to opinion summarization, because its effectiveness
significantly affects the identification of semantic relationships. The
polarity and numeric score of all the features are determined by
Senti-WordNet Lexicon. The problem of opinion summarization
refers how to relate the opinion words with respect to a certain
feature. Probabilistic based model of supervised learning will
improve the result that is more flexible and effective.
Abstract: Image search engines rely on the surrounding textual
keywords for the retrieval of images. It is a tedious work for the
search engines like Google and Bing to interpret the user’s search
intention and to provide the desired results. The recent researches
also state that the Google image search engines do not work well on
all the images. Consequently, this leads to the emergence of efficient
image retrieval technique, which interprets the user’s search intention
and shows the desired results. In order to accomplish this task, an
efficient image re-ranking framework is required. Sequentially, to
provide best image retrieval, the new image re-ranking framework is
experimented in this paper. The implemented new image re-ranking
framework provides best image retrieval from the image dataset by
making use of re-ranking of retrieved images that is based on the
user’s desired images. This is experimented in two sections. One is
offline section and other is online section. In offline section, the reranking
framework studies differently (reference classes or Semantic
Spaces) for diverse user query keywords. The semantic signatures get
generated by combining the textual and visual features of the images.
In the online section, images are re-ranked by comparing the
semantic signatures that are obtained from the reference classes with
the user specified image query keywords. This re-ranking
methodology will increases the retrieval image efficiency and the
result will be effective to the user.
Abstract: To date, one of the few comprehensive indicators for
the measurement of food security is the Global Food Security Index
(GFSI). This index is a dynamic quantitative and qualitative
benchmarking model, constructed from 28 unique indicators, that
measures drivers of food security across both developing and
developed countries. Whereas the GFSI has been calculated across a
set of 109 countries, in this paper we aim to present and compare, for
the Middle East and North Africa (MENA), 1) the Food Security
Index scores achieved and 2) the data available on affordability,
availability, and quality of food. The data for this work was taken
from the latest available report published by the creators of the GFSI,
which in turn used information from national and international
statistical sources. MENA countries rank from place 17/109 (Israel,
although with resent political turmoil this is likely to have changed)
to place 91/109 (Yemen) with household expenditure spent in food
ranging from 15.5% (Israel) to 60% (Egypt). Lower spending on food
as a share of household consumption in most countries and better
food safety net programs in the MENA have contributed to a notable
increase in food affordability. The region has also, however,
experienced a decline in food availability, owing to more limited
food supplies and higher volatility of agricultural production. In
terms of food quality and safety the MENA has the top ranking
country (Israel). The most frequent challenges faced by the countries
of the MENA include public expenditure on agricultural research and
development as well as volatility of agricultural production. Food
security is a complex phenomenon that interacts with many other
indicators of a country’s wellbeing; in the MENA it is slowly but
markedly improving.
Abstract: There is decagram of strategic decisions of operations
and production/service management (POSM) within operational
research (OR) which must collate, namely: design, inventory, quality,
location, process and capacity, layout, scheduling, maintain ace, and
supply chain. This paper presents an architectural configuration
conceptual framework of a decagram of sets decisions in a form of
mathematical complete graph and abelian graph.
Mathematically, a complete graph is undirected (UDG), and
directed (DG) a relationship where every pair of vertices is
connected, collated, confluent, and holomorphic.
There has not been any study conducted which, however,
prioritizes the holomorphic sets which of POMS within OR field of
study. The study utilizes OR structured technique known as The
Analytic Hierarchy Process (AHP) analysis for organizing, sorting
and prioritizing(ranking) the sets within the decagram of POMS
according to their attribution (propensity), and provides an analysis
how the prioritization has real-world application within the 21st
century.
Abstract: Search engine plays an important role in internet, to
retrieve the relevant documents among the huge number of web
pages. However, it retrieves more number of documents, which are
all relevant to your search topics. To retrieve the most meaningful
documents related to search topics, ranking algorithm is used in
information retrieval technique. One of the issues in data miming is
ranking the retrieved document. In information retrieval the ranking
is one of the practical problems. This paper includes various Page
Ranking algorithms, page segmentation algorithms and compares
those algorithms used for Information Retrieval. Diverse Page Rank
based algorithms like Page Rank (PR), Weighted Page Rank (WPR),
Weight Page Content Rank (WPCR), Hyperlink Induced Topic
Selection (HITS), Distance Rank, Eigen Rumor, Distance Rank Time
Rank, Tag Rank, Relational Based Page Rank and Query Dependent
Ranking algorithms are discussed and compared.
Abstract: In this study, we develop a performance evaluation
model based on a multi-attribute utility approach aiming at reaching
the sustainable banking (SB) status. This model is built accounting
for various banks’ stakeholders in a win-win paradigm. In addition, it
offers the opportunity for adopting a global measure of performance
as an indication of a bank’s sustainability degree. This measure is
referred to as banking sustainability performance index (BSPI). This
index may constitute a basis for ranking banks. Moreover, it may
constitute a bridge between the assessment types of financial and
extra-financial rating agencies. A real application is performed on
three French banks.
Abstract: In Capitalism all economic activity rests upon a set of
core institutional foundations, main from which are privately owned
capital assets and profit. How these core institutional foundations are
working in former soviet countries, in particular in Travel and
Tourism Industry of Georgia?
The role of Travel and Tourism as a key pillar of economic growth
is being increasingly recognized by governments in all regions of the
world. For the last few years Georgia succeeded in the World Bank
and IFC “Doing Business” rankings. Despite of that, during decades
totally different statistical data of the tourism sector were provided by
the different State bodies; economic parameters were published few,
or not published at all.
The frequency and extent of property rights violation in Georgia
has repeatedly been the subject of concern for the last decade. Total
value of abrogated by the former Georgian Government private
property is estimated approximately in US$4-5 billion.
Thus, if economic profitability is unknown and property rights are
not protected – that means that the main institutional foundations of
capitalism in Georgia, are not working properly yet, that cause
management problems at all levels of the national Travel and
Tourism industry of Georgia.
Abstract: This work proposes a fuzzy methodology to support
the investment decisions. While choosing among competitive
investment projects, the methodology makes ranking of projects
using the new aggregation OWA operator – AsPOWA, presented in
the environment of possibility uncertainty. For numerical evaluation
of the weighting vector associated with the AsPOWA operator the
mathematical programming problem is constructed. On the basis of
the AsPOWA operator the projects’ group ranking maximum criteria
is constructed. The methodology also allows making the most
profitable investments into several of the project using the method
developed by the authors for discrete possibilistic bicriteria problems.
The article provides an example of the investment decision-making
that explains the work of the proposed methodology.
Abstract: The work proposes a decision support methodology
for the credit risk minimization in selection of investment projects.
The methodology provides two stages of projects’ evaluation.
Preliminary selection of projects with minor credit risks is made
using the Expertons Method. The second stage makes ranking of
chosen projects using the Possibilistic Discrimination Analysis
Method. The latter is a new modification of a well-known Method of
Fuzzy Discrimination Analysis.
Abstract: Recently there has been a dramatic proliferation in
the number of social networking sites (SNSs) users; however, little
is published about what motivates college students to use SNSs in
education. The main goal of this research is to explore the college
students’ motives for using SNSs in education. A conceptual
framework has therefore been developed to identify the main
factors that influence/motivate students to use social networking
sites for learning purposes. To achieve the research objectives a
quantitative method was used to collect data. A questionnaire has
been distributed amongst college students. The results reveal that
social influence, perceived enjoyment, institute regulation,
perceived usefulness, ranking up-lift, attractiveness,
communication tools, free of charge, sharing material and course
nature all play an important role in the motivation of college
students to use SNSs for learning purposes.
Abstract: During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances and cost performances in the supply chain.