Abstract: The school / university orientation interests a broad and
often badly informed public. Technically, it is an important
multicriterion decision problem, which supposes the combination of
much academic professional and/or lawful knowledge, which in turn
justifies software resorting to the techniques of Artificial Intelligence.
CORUS is an expert system of the "Conseil et ORientation
Universitaire et Scolaire", based on a knowledge representation
language (KRL) with rules and objects, called/ known as Ibn Rochd.
CORUS was developed thanks to DéGSE, a workshop of cognitive
engineering which supports this LRC. CORUS works out many
acceptable solutions for the case considered, and retains the most
satisfactory among them. Several versions of CORUS have extended
its services gradually.
Abstract: Contour filter strips planted with perennial vegetation
can be used to improve surface and ground water quality by reducing
pollutant, such as NO3-N, and sediment outflow from cropland to a
river or lake. Meanwhile, the filter strips of perennial grass with biofuel
potentials also have economic benefits of producing ethanol. In
this study, The Soil and Water Assessment Tool (SWAT) model was
applied to the Walnut Creek Watershed to examine the effectiveness
of contour strips in reducing NO3-N outflows from crop fields to the
river or lake. Required input data include watershed topography,
slope, soil type, land-use, management practices in the watershed and
climate parameters (precipitation, maximum/minimum air
temperature, solar radiation, wind speed and relative humidity).
Numerical experiments were conducted to identify potential
subbasins in the watershed that have high water quality impact, and
to examine the effects of strip size and location on NO3-N reduction
in the subbasins under various meteorological conditions (dry,
average and wet). Variable sizes of contour strips (10%, 20%, 30%
and 50%, respectively, of a subbasin area) planted with perennial
switchgrass were selected for simulating the effects of strip size and
location on stream water quality. Simulation results showed that a
filter strip having 10%-50% of the subbasin area could lead to 55%-
90% NO3-N reduction in the subbasin during an average rainfall
year. Strips occupying 10-20% of the subbasin area were found to be
more efficient in reducing NO3-N when placed along the contour
than that when placed along the river. The results of this study can
assist in cost-benefit analysis and decision-making in best water
resources management practices for environmental protection.
Abstract: Knowledge management is a process taking any steps
that needed to get the most out of available knowledge resources.
KM involved several steps; capturing the knowledge discovering
new knowledge, sharing the knowledge and applied the knowledge in
the decision making process. In applying the knowledge, it is not
necessary for the individual that use the knowledge to comprehend it
as long as the available knowledge is used in guiding the decision
making and actions. When an expert is called and he provides stepby-
step procedure on how to solve the problems to the caller, the
expert is transferring the knowledge or giving direction to the caller.
And the caller is 'applying' the knowledge by following the
instructions given by the expert. An appropriate mechanism is
needed to ensure effective knowledge transfer which in this case is
by telephone or email. The problem with email and telephone is that
the knowledge is not fully circulated and disseminated to all users. In
this paper, with related experience of local university Help Desk, it is
proposed the usage of Information Technology (IT)to effectively
support the knowledge transfer in the organization. The issues
covered include the existing knowledge, the related works, the
methodology used in defining the knowledge management
requirements as well the overview of the prototype.
Abstract: In this study, we explore the use of information for inventory decision in the healthcare organization (HO). We consider the scenario when the HO can make use of the information collected from some correlated products to enhance its inventory planning. Motivated by our real world observations that HOs adopt RFID and bar-coding system for information collection purpose, we examine the effectiveness of these systems for inventory planning with Bayesian information updating. We derive the optimal ordering decision and study the issue of Pareto improvement in the supply chain. Our analysis demonstrates that RFID system will outperform the bar-coding system when the RFID system installation cost and the tag cost reduce to a level that is comparable with that of the barcoding system. We also show how an appropriately set wholesale pricing contract can achieve Pareto improvement in the HO supply chain.
Abstract: It is well known that Logistic Regression is the gold
standard method for predicting clinical outcome, especially
predicting risk of mortality. In this paper, the Decision Tree method
has been proposed to solve specific problems that commonly use
Logistic Regression as a solution. The Biochemistry and
Haematology Outcome Model (BHOM) dataset obtained from
Portsmouth NHS Hospital from 1 January to 31 December 2001 was
divided into four subsets. One subset of training data was used to
generate a model, and the model obtained was then applied to three
testing datasets. The performance of each model from both methods
was then compared using calibration (the χ2 test or chi-test) and
discrimination (area under ROC curve or c-index). The experiment
presented that both methods have reasonable results in the case of the
c-index. However, in some cases the calibration value (χ2) obtained
quite a high result. After conducting experiments and investigating
the advantages and disadvantages of each method, we can conclude
that Decision Trees can be seen as a worthy alternative to Logistic
Regression in the area of Data Mining.
Abstract: As new challenges emerge in power electrical
workplace safety, it is the responsibility of the systems designer to
seek out new approaches and solutions that address them. Design
decisions made today will impact cost, safety and serviceability of
the installed systems for 40 or 50 years during the useful life for the
owner. Studies have shown that this cost is an order of magnitude of
7 to 10 times the installed cost of the power distribution equipment.
This paper reviews some aspects of earthing system design in power
substation surrounded by residential houses. The electrical potential
rise and split factors are discussed and a few recommendations are
provided to achieve a safety voltage in the area beyond the boundary
of the substation.
Abstract: Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.
Abstract: Continuation of an active call is one of the most important quality measurements in the cellular systems. Handoff process enables a cellular system to provide such a facility by transferring an active call from one cell to another. Different approaches are proposed and applied in order to achieve better handoff service. The principal parameters used to evaluate handoff techniques are: forced termination probability and call blocking probability. The mechanisms such as guard channels and queuing handoff calls decrease the forced termination probability while increasing the call blocking probability. In this paper we present an overview about the issues related to handoff initiation and decision and discuss about different types of handoff techniques available in the literature.
Abstract: This paper presents Cost per Equivalent Wafer Out, which we find useful in wafer fab operational cost monitoring and controlling. It removes the loading and product mix effect in the cost variance analysis. The operation heads, therefore, could immediately focus on identifying areas for cost improvement. Without this, they would have to measure the impact of the loading variance and product mix variance between actual and budgeted prior to make any decision on cost improvement. Cost per Equivalent Wafer Out, thereby, increases efficiency in wafer fab operational cost monitoring and controlling.
Abstract: In today-s global and competitive market,
manufacturing companies are working hard towards improving their
production system performance. Most companies develop production
systems that can help in cost reduction. Manufacturing systems
consist of different elements including production methods,
machines, processes, control and information systems. Human issues
are an important part of manufacturing systems, yet most companies
do not pay sufficient attention to them. In this paper, a workforce
planning (WP) model is presented. A non-linear programming model
is developed in order to minimize the hiring, firing, training and
overtime costs. The purpose is to determine the number of workers
for each worker type, the number of workers trained, and the number
of overtime hours. Moreover, a decision support system (DSS) based
on the proposed model is introduced using the Excel-Lingo software
interfacing feature. This model will help to improve the interaction
between the workers, managers and the technical systems in
manufacturing.
Abstract: A novel path planning approach is presented to solve
optimal path in stochastic, time-varying networks under priori traffic
information. Most existing studies make use of dynamic programming
to find optimal path. However, those methods are proved to
be unable to obtain global optimal value, moreover, how to design
efficient algorithms is also another challenge.
This paper employs a decision theoretic framework for defining
optimal path: for a given source S and destination D in urban transit
network, we seek an S - D path of lowest expected travel time
where its link travel times are discrete random variables. To solve
deficiency caused by the methods of dynamic programming, such as
curse of dimensionality and violation of optimal principle, an integer
programming model is built to realize assignment of discrete travel
time variables to arcs. Simultaneously, pruning techniques are also
applied to reduce computation complexity in the algorithm. The final
experiments show the feasibility of the novel approach.
Abstract: Intellectual capital reporting becomes critical at
universities, mainly due to the fact that knowledge is the main output
as well as input in these institutions. In addition, universities have
continuous external demands for greater information and
transparency about the use of public funds, and are increasingly
provided with greater autonomy regarding their organization,
management, and budget allocation. This situation requires new
management and reporting systems. The purpose of the present study
is to provide a model for intellectual capital report in Spanish
universities. To this end, a questionnaire was sent to every member of
the Social Councils of Spanish public universities in order to identify
which intangible elements university stakeholders demand most. Our
proposal for an intellectual capital report aims to act as a guide to
help the Spanish universities on the road to the presentation of
information on intellectual capital which can assist stakeholders to
make the right decisions.
Abstract: The aim of this study is to determine the effect of
strategic management implementations on the institutionalization
levels. In this regard a field study has been made over 31 stone quarry
enterprises in cement producing sector in Konya by using survey
method. In this study, institutionalization levels of the enterprises
have been evaluated regarding three dimensions: professionalization,
management approach, participation in decisions and delegation of
authority. According to the results of the survey, there is a highly
positive and statistically significant relationship between the strategic
management implementations and institutionalization levels of the
enterprises. Additionally,-considering the results of regression
analysis made for establishing the relationship between strategic
management and institutionalization levels- it has been determined
that strategic management implementations of the enterprises can be
used as a variable to explain the institutionalization levels of them,
and also strategic management implementations of the enterprises
increase the institutionalization levels of them.
Abstract: We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.
Abstract: For the last decade, statistics show traumatic brain
injury (TBI) is a growing concern in our legal system. In an effort to
obtain data regarding the influence of neuropsychological expert
witness testimony in a criminal case, this study tested three
hypotheses. H1: The majority of jurors will vote not guilty, due to
mild head injury. H2: The jurors will give more credence to the
testimony of the neuropsychologist rather than the psychiatrist. H3:
The jurors will be more lenient in their sentencing, given the
testimony of the neuropsychologist-s testimony. The criterion for
inclusion in the study as a participant is identical to those used for
inclusion in the eligibility for jury duty in the United States. A chisquared
test was performed to analyze the data for the three
hypotheses. The results supported all of the hypotheses; however
statistical significance was seen in H1 and H2 only.
Abstract: In this study we tried to replicate the unconscious
thought advantage (UTA), which states that complex decisions are
better handled by unconscious thinking. We designed an experiment
in e-prime using similar material as the original study (choosing
between four different apartments, each described by 12 attributes).
A total of 73 participants (52 women (71.2%); 18 to 62 age:
M=24.63; SD=8.7) took part in the experiment. We did not replicate
the results suggested by UTT. However, from the present study we
cannot conclude whether this was the case of flaws in the theory or
flaws in our experiment and we discuss several ways in which the
issue of UTA could be examined further.
Abstract: Selection of a project among a set of possible
alternatives is a difficult task that the decision maker (DM) has to
face. In this paper, by using a fuzzy TOPSIS technique we propose a
new method for a project selection problem. After reviewing four
common methods of comparing investment alternatives (net present
value, rate of return, benefit cost analysis and payback period) we
use them as criteria in a TOPSIS technique. First we calculate the
weight of each criterion by a pairwise comparison and then we utilize
the improved TOPSIS assessment for the project selection.
Abstract: An original DEA model is to evaluate each DMU
optimistically, but the interval DEA Model proposed in this paper
has been formulated to obtain an efficiency interval consisting of
Evaluations from both the optimistic and the pessimistic view points.
DMUs are improved so that their lower bounds become so large as to
attain the maximum Value one. The points obtained by this method
are called ideal points. Ideal PPS is calculated by ideal of efficiency
DMUs. The purpose of this paper is to rank DMUs by this ideal PPS.
Finally we extend the efficiency interval of a DMU under variable
RTS technology.