Abstract: One of research issues in social network analysis is to
evaluate the position/importance of users in social networks. As the
information diffusion in social network is evolving, it seems difficult
to evaluate the importance of users using traditional approaches. In
this paper, we propose an evaluation approach for user importance
with fractal view in social networks. In this approach, the global importance
(Fractal Importance) and the local importance (Topological
Importance) of nodes are considered. The basic idea is that the bigger
the product of fractal importance and topological importance of a
node is, the more important of the node is. We devise the algorithm
called TFRank corresponding to the proposed approach. Finally, we
evaluate TFRank by experiments. Experimental results demonstrate
our TFRank has the high correlations with PageRank algorithm
and potential ranking algorithm, and it shows the effectiveness and
advantages of our approach.
Abstract: In this paper, an improved technique for contingency
ranking using artificial neural network (ANN) is presented. The
proposed approach is based on multi-layer perceptrons trained by
backpropagation to contingency analysis. Severity indices in dynamic
stability assessment are presented. These indices are based on the
concept of coherency and three dot products of the system variables.
It is well known that some indices work better than others for a
particular power system. This paper along with test results using
several different systems, demonstrates that combination of indices
with ANN provides better ranking than a single index. The presented
results are obtained through the use of power system simulation
(PSS/E) and MATLAB 6.5 software.
Abstract: The lifelong learning is a crucial element in the
modernization of European education and training systems. The most
important actors in the development process of the lifelong learning
are the trainers, whose professional characteristics need new
competences and skills in the current labour market. The main
objective of this paper is to establish an importance ranking of the
new competences, capabilities and skills that the lifelong learning
Spanish trainers must possess nowadays. A wide study of secondary
sources has allowed the design of a questionnaire that organizes the
trainer-s skills and competences. The e-Delphi method is used for
realizing a creative, individual and anonymous evaluation by experts
on the importance ranking that presents the criteria, sub-criteria and
indicators of the e-Delphi questionnaire. Twenty Spanish experts in
the lifelong learning have participated in two rounds of the e-
DELPHI method. In the first round, the analysis of the experts-
evaluation has allowed to establish the ranking of the most
importance criteria, sub-criteria and indicators and to eliminate the
least valued. The minimum level necessary to reach the consensus
among experts has been achieved in the second round.
Abstract: A dent is a gross distortion of the pipe cross-section.
Dent depth is defined as the maximum reduction in the diameter of
the pipe compared to the original diameter. Pipeline dent finite
element (FE) simulation and theoretical analysis are conducted in this
paper to develop an understanding of the geometric characteristics
and strain distribution in the pressurized dented pipe. Based on the
results, the magnitude of the denting force increases significantly
with increasing the internal pressure, and the maximum
circumferential and longitudinal strains increase by increasing the
internal pressure and the dent depth. The results can be used for
characterizing dents and ranking their risks to the integrity of a
pipeline.
Abstract: Term Extraction, a key data preparation step in Text
Mining, extracts the terms, i.e. relevant collocation of words,
attached to specific concepts (e.g. genetic-algorithms and decisiontrees
are terms associated to the concept “Machine Learning" ). In
this paper, the task of extracting interesting collocations is achieved
through a supervised learning algorithm, exploiting a few
collocations manually labelled as interesting/not interesting. From
these examples, the ROGER algorithm learns a numerical function,
inducing some ranking on the collocations. This ranking is optimized
using genetic algorithms, maximizing the trade-off between the false
positive and true positive rates (Area Under the ROC curve). This
approach uses a particular representation for the word collocations,
namely the vector of values corresponding to the standard statistical
interestingness measures attached to this collocation. As this
representation is general (over corpora and natural languages),
generality tests were performed by experimenting the ranking
function learned from an English corpus in Biology, onto a French
corpus of Curriculum Vitae, and vice versa, showing a good
robustness of the approaches compared to the state-of-the-art Support
Vector Machine (SVM).
Abstract: In this paper, a benchmarking framework is presented
for the performance assessment of irrigations systems. Firstly, a data
envelopment analysis (DEA) is applied to measure the technical
efficiency of irrigation systems. This method, based on linear
programming, aims to determine a consistent efficiency ranking of
irrigation systems in which known inputs, such as water volume
supplied and total irrigated area, and a given output corresponding to
the total value of irrigation production are taken into account
simultaneously. Secondly, in order to examine the irrigation
efficiency in more detail, a cross – system comparison is elaborated
using a performance indicators set selected by IWMI. The above
methodologies were applied in Thessaloniki plain, located in
Northern Greece while the results of the application are presented and
discussed. The conjunctive use of DEA and performance indicators
seems to be a very useful tool for efficiency assessment and
identification of best practices in irrigation systems management.
Abstract: In this study, the Taguchi method was used to optimize the effect of HALO structure or halo implant variations on threshold voltage (VTH) and leakage current (ILeak) in 45nm p-type Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) device. Besides halo implant dose, the other process parameters which used were Source/Drain (S/D) implant dose, oxide growth temperature and silicide anneal temperature. This work was done using TCAD simulator, consisting of a process simulator, ATHENA and device simulator, ATLAS. These two simulators were combined with Taguchi method to aid in design and optimize the process parameters. In this research, the most effective process parameters with respect to VTH and ILeak are halo implant dose (40%) and S/D implant dose (52%) respectively. Whereas the second ranking factor affecting VTH and ILeak are oxide growth temperature (32%) and halo implant dose (34%) respectively. The results show that after optimizations approaches is -0.157V at ILeak=0.195mA/μm.
Abstract: Saudi Arabia in recent years has seen drastic increase
in traffic related crashes. With population of over 29 million, Saudi
Arabia is considered as a fast growing and emerging economy. The
rapid population increase and economic growth has resulted in rapid
expansion of transportation infrastructure, which has led to increase
in road crashes. Saudi Ministry of Interior reported more than 7,000
people killed and 68,000 injured in 2011 ranking Saudi Arabia to be
one of the worst worldwide in traffic safety. The traffic safety issues
in the country also result in distress to road users and cause and
economic loss exceeding 3.7 billion Euros annually. Keeping this in
view, the researchers in Saudi Arabia are investigating ways to
improve traffic safety conditions in the country. This paper presents a
multilevel approach to collect traffic safety related data required to do
traffic safety studies in the region. Two highway corridors including
King Fahd Highway 39 kilometre and Gulf Cooperation Council
Highway 42 kilometre long connecting the cities of Dammam and
Khobar were selected as a study area. Traffic data collected included
traffic counts, crash data, travel time data, and speed data. The
collected data was analysed using geographic information system to
evaluate any correlation. Further research is needed to investigate the
effectiveness of traffic safety related data when collected in a
concerted effort.
Abstract: The aim of this paper is to adopt a compromise ratio (CR) methodology for fuzzy multi-attribute single-expert decision making proble. In this paper, the rating of each alternative has been described by linguistic terms, which can be expressed as triangular fuzzy numbers. The compromise ratio method for fuzzy multi-attribute single expert decision making has been considered here by taking the ranking index based on the concept that the chosen alternative should be as close as possible to the ideal solution and as far away as possible from the negative-ideal solution simultaneously. From logical point of view, the distance between two triangular fuzzy numbers also is a fuzzy number, not a crisp value. Therefore a fuzzy distance measure, which is itself a fuzzy number, has been used here to calculate the difference between two triangular fuzzy numbers. Now in this paper, with the help of this fuzzy distance measure, it has been shown that the compromise ratio is a fuzzy number and this eases the problem of the decision maker to take the decision. The computation principle and the procedure of the compromise ratio method have been described in detail in this paper. A comparative analysis of the compromise ratio method previously proposed [1] and the newly adopted method have been illustrated with two numerical examples.
Abstract: The traditional Failure Mode and Effects Analysis
(FMEA) uses Risk Priority Number (RPN) to evaluate the risk level
of a component or process. The RPN index is determined by
calculating the product of severity, occurrence and detection indexes.
The most critically debated disadvantage of this approach is that
various sets of these three indexes may produce an identical value of
RPN. This research paper seeks to address the drawbacks in
traditional FMEA and to propose a new approach to overcome these
shortcomings. The Risk Priority Code (RPC) is used to prioritize
failure modes, when two or more failure modes have the same RPN.
A new method is proposed to prioritize failure modes, when there is a
disagreement in ranking scale for severity, occurrence and detection.
An Analysis of Variance (ANOVA) is used to compare means of
RPN values. SPSS (Statistical Package for the Social Sciences)
statistical analysis package is used to analyze the data. The results
presented are based on two case studies. It is found that the proposed
new methodology/approach resolves the limitations of traditional
FMEA approach.
Abstract: This paper applies fuzzy set theory to evaluate the
service quality of online auction. Service quality is a composition of
various criteria. Among them many intangible attributes are difficult
to measure. This characteristic introduces the obstacles for respondent
in replying to the survey. So as to overcome this problem, we
invite fuzzy set theory into the measurement of performance. By
using AHP in obtaining criteria and TOPSIS in ranking, we found
the most concerned dimension of service quality is Transaction
Safety Mechanism and the least is Charge Item. Regarding to the
most concerned attributes are information security, accuracy and
information.
Abstract: Islamic banking is one the most blossoming doctrine in
economic system of the world. The Fast growing awareness about
Islamic financial system has brought strong feeling to Muslims to
confront the western interest-based economic cycle. The Islamic
economic system is emerging as a reliable alternative to the interest
based system. This study is proposed to ascertain the motivational
factors encouraging people to go for Islamic banking in Pakistan.
These pulsing factors are determined by generation of hypothesis that
there are certain factors which are urging people to opt Islamic
banking system and to see the differences in their ranking by applying
Friedman test. These factors include: Economically derived factors
such as stability of Islamic banks in crisis, profit and loss sharing
doctrine and equity sharing etc. This study also highlights the
religiously derived factors such as interest free banking, Shariah
tenets and supervisory of Islamic Shariah board and sociopsychological
factors.
Abstract: Achieving success is a highly critical issue for the
companies to survive in a competitive business environment. The
construction industry is also an area where there is strong
competition due to a large number of construction contractors. There
have been many factors such as qualified employees, quality
workmanship and financial management that can lead to company
success in the construction industry. The aim of this study was to
investigate the critical factors leading to construction company
success. Within this context, a survey was carried out among 40
Turkish construction companies which are located in the Northwest
region of Turkey. In this survey, top-level managers and owners of
the companies were interviewed. The interviews took place over a
five month period between January and May 2007. Finally, the
ranking of the critical success factors has been determined by using
the Simple Multi Attribute Rating Technique (SMART). Based on
the results, business management, financial conditions and
owner/manager characteristics were determined as the most
important factors to company success.
Abstract: Structural Integrity Management (SIM) is
important for the protection of offshore crew, environment, business assets and company and industry reputation. API RP 2A contained guidelines for assessment of existing platforms mostly for the Gulf
of Mexico (GOM). ISO 19902 SIM framework also does not
specifically cater for Malaysia. There are about 200 platforms in
Malaysia with 90 exceeding their design life. The Petronas Carigali
Sdn Bhd (PCSB) uses the Asset Integrity Management System and
the very subjective Risk based Inspection Program for these
platforms. Petronas currently doesn-t have a standalone Petronas
Technical Standard PTS-SIM. This study proposes a recommended
practice for the SIM process for offshore structures in Malaysia,
including studies by API and ISO and local elements such as the
number of platforms, types of facilities, age and risk ranking. Case
study on SMG-A platform in Sabah shows missing or scattered
platform data and a gap in inspection history. It is to undergo a level
3 underwater inspection in year 2015.
Abstract: The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.
Abstract: Statistical selection procedures are used to select the
best simulated system from a finite set of alternatives. In this paper,
we present a procedure that can be used to select the best system
when the number of alternatives is large. The proposed procedure
consists a combination between Ranking and Selection, and Ordinal
Optimization procedures. In order to improve the performance of Ordinal
Optimization, Optimal Computing Budget Allocation technique
is used to determine the best simulation lengths for all simulation
systems and to reduce the total computation time. We also argue
the effect of increment in simulation samples for the combined
procedure. The results of numerical illustration show clearly the effect
of increment in simulation samples on the proposed combination of
selection procedure.
Abstract: This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.
Abstract: Although so far, many methods for ranking fuzzy numbers
have been discussed broadly, most of them contained some shortcomings,
such as requirement of complicated calculations, inconsistency
with human intuition and indiscrimination. The motivation of
this study is to develop a model for ranking fuzzy numbers based
on the lexicographical ordering which provides decision-makers with
a simple and efficient algorithm to generate an ordering founded on
a precedence. The main emphasis here is put on the ease of use
and reliability. The effectiveness of the proposed method is finally
demonstrated by including a comprehensive comparing different
ranking methods with the present one.
Abstract: Automatic keyphrase extraction is useful in efficiently
locating specific documents in online databases. While several
techniques have been introduced over the years, improvement on
accuracy rate is minimal. This research examines attribute scores for
author-supplied keyphrases to better understand how the scores affect
the accuracy rate of automatic keyphrase extraction. Five attributes
are chosen for examination: Term Frequency, First Occurrence, Last
Occurrence, Phrase Position in Sentences, and Term Cohesion
Degree. The results show that First Occurrence is the most reliable
attribute. Term Frequency, Last Occurrence and Term Cohesion
Degree display a wide range of variation but are still usable with
suggested tweaks. Only Phrase Position in Sentences shows a totally
unpredictable pattern. The results imply that the commonly used
ranking approach which directly extracts top ranked potential phrases
from candidate keyphrase list as the keyphrases may not be reliable.
Abstract: This article proposes a novel Pareto-based multiobjective
meta-heuristic algorithm named non-dominated ranking
genetic algorithm (NRGA) to solve multi-facility location-allocation
problem. In NRGA, a fitness value representing rank is assigned to
each individual of the population. Moreover, two features ranked
based roulette wheel selection including select the fronts and choose
solutions from the fronts, are utilized. The proposed solving
methodology is validated using several examples taken from the
specialized literature. The performance of our approach shows that
NRGA algorithm is able to generate true and well distributed Pareto
optimal solutions.