Abstract: Diagnosis can be achieved by building a model of a
certain organ under surveillance and comparing it with the real time
physiological measurements taken from the patient. This paper deals
with the presentation of the benefits of using Data Mining techniques
in the computer-aided diagnosis (CAD), focusing on the cancer
detection, in order to help doctors to make optimal decisions quickly
and accurately. In the field of the noninvasive diagnosis techniques,
the endoscopic ultrasound elastography (EUSE) is a recent elasticity
imaging technique, allowing characterizing the difference between
malignant and benign tumors. Digitalizing and summarizing the main
EUSE sample movies features in a vector form concern with the use
of the exploratory data analysis (EDA). Neural networks are then
trained on the corresponding EUSE sample movies vector input in
such a way that these intelligent systems are able to offer a very
precise and objective diagnosis, discriminating between benign and
malignant tumors. A concrete application of these Data Mining
techniques illustrates the suitability and the reliability of this
methodology in CAD.
Abstract: The need in cognitive radio system for a simple, fast, and independent technique to sense the spectrum occupancy has led to the energy detection approach. Energy detector is known by its dependency on noise variation in the system which is one of its major drawbacks. In this paper, we are aiming to improve its performance by utilizing a weighted collaborative spectrum sensing, it is similar to the collaborative spectrum sensing methods introduced previously in the literature. These weighting methods give more improvement for collaborative spectrum sensing as compared to no weighting case. There is two method proposed in this paper: the first one depends on the channel status between each sensor and the primary user while the second depends on the value of the energy measured in each sensor.
Abstract: This paper proposes a new optimization techniques
for the optimization a gas processing plant uncertain feed and
product flows. The problem is first formulated using a continuous
linear deterministic approach. Subsequently, the single and joint
chance constraint models for steady state process with timedependent
uncertainties have been developed. The solution approach
is based on converting the probabilistic problems into their
equivalent deterministic form and solved at different confidence
levels Case study for a real plant operation has been used to
effectively implement the proposed model. The optimization results
indicate that prior decision has to be made for in-operating plant
under uncertain feed and product flows by satisfying all the
constraints at 95% confidence level for single chance constrained and
85% confidence level for joint chance constrained optimizations
cases.
Abstract: This paper proposes a novel solution for optimizing
the size and communication overhead of a distributed multiagent
system without compromising the performance. The proposed approach
addresses the challenges of scalability especially when the
multiagent system is large. A modified spectral clustering technique
is used to partition a large network into logically related clusters.
Agents are assigned to monitor dedicated clusters rather than monitor
each device or node. The proposed scalable multiagent system is
implemented using JADE (Java Agent Development Environment)
for a large power system. The performance of the proposed topologyindependent
decentralized multiagent system and the scalable multiagent
system is compared by comprehensively simulating different
fault scenarios. The time taken for reconfiguration, the overall computational
complexity, and the communication overhead incurred are
computed. The results of these simulations show that the proposed
scalable multiagent system uses fewer agents efficiently, makes faster
decisions to reconfigure when a fault occurs, and incurs significantly
less communication overhead.
Abstract: One of the main processes of supply chain
management is supplier selection process which its accurate
implementation can dramatically increase company competitiveness.
In presented article model developed based on the features of
second tiers suppliers and four scenarios are predicted in order to
help the decision maker (DM) in making up his/her mind. In addition
two tiers of suppliers have been considered as a chain of suppliers.
Then the proposed approach is solved by a method combined of
concepts of fuzzy set theory (FST) and linear programming (LP)
which has been nourished by real data extracted from an engineering
design and supplying parts company. At the end results reveal the
high importance of considering second tier suppliers features as
criteria for selecting the best supplier.
Abstract: Business rules and data warehouse are concepts and
technologies that impact a wide variety of organizational tasks. In
general, each area has evolved independently, impacting application
development and decision-making. Generating knowledge from data
warehouse is a complex process. This paper outlines an approach to
ease import of information and knowledge from a data warehouse
star schema through an inference class of business rules. The paper
utilizes the Oracle database for illustrating the working of the
concepts. The star schema structure and the business rules are stored
within a relational database. The approach is explained through a
prototype in Oracle-s PL/SQL Server Pages.
Abstract: Communication is an important factor and a prop in
directing corporate activities efficiently, in ensuring the flow of
knowledge which is necessary for the continuity of the institution, in
creating a common language in the institution, in transferring
corporate culture and ultimately in corporate success. The idea of
transmitting the knowledge among the workers in a healthy manner
has revived knowledge communication. Knowledge communication
can be defined as the act of mutual creation and communication of
intuitions, assessments, experiences and capabilities, as long as
maintained effectively, can provide advantages such as corporate
continuity, access to corporate objectives and making true
administrative decisions. Although the benefits of the knowledge
communication to corporations are known, and the necessary worth
and care is given, some hardships may arise which makes it difficult
or even block it. In this article, difficulties that prevent knowledge
communication will be discussed and solutions will be proposed.
Abstract: Majority of Business Software Systems (BSS)
Development and Enhancement Projects (D&EP) fail to meet criteria
of their effectiveness, what leads to the considerable financial losses.
One of the fundamental reasons for such projects- exceptionally low
success rate are improperly derived estimates for their costs and time.
In the case of BSS D&EP these attributes are determined by the work
effort, meanwhile reliable and objective effort estimation still appears
to be a great challenge to the software engineering. Thus this paper is
aimed at presenting the most important synthetic conclusions coming
from the author-s own studies concerning the main factors of
effective BSS D&EP work effort estimation. Thanks to the rational
investment decisions made on the basis of reliable and objective
criteria it is possible to reduce losses caused not only by abandoned
projects but also by large scale of overrunning the time and costs of
BSS D&EP execution.
Abstract: This paper presents an integrated knowledge-based
approach to multi-scale modeling of aquatic systems, with a view to
enhancing predictive power and aiding environmental management
and policy-making. The basic phases of this approach have been
exemplified in the case of a bay in Saronicos Gulf (Attiki, Greece).
The results showed a significant problem with rising phytoplankton
blooms linked to excessive microbial growth, arisen mostly due to
increased nitrogen inflows; therefore, the nitrification/denitrification
processes of the benthic and water column sub-systems have
provided the quality variables to be monitored for assessing
environmental status. It is thereby demonstrated that the proposed
approach facilitates modeling choices and implementation option
decisions, while it provides substantial support for knowledge and
experience capitalization in long-term water management.
Abstract: In this paper we will develop further the sequential life test approach presented in a previous article by [1] using an underlying two parameter Inverse Weibull sampling distribution. The location parameter or minimum life will be considered equal to zero. Once again we will provide rules for making one of the three possible decisions as each observation becomes available; that is: accept the null hypothesis H0; reject the null hypothesis H0; or obtain additional information by making another observation. The product being analyzed is a new electronic component. There is little information available about the possible values the parameters of the corresponding Inverse Weibull underlying sampling distribution could have.To estimate the shape and the scale parameters of the underlying Inverse Weibull model we will use a maximum likelihood approach for censored failure data. A new example will further develop the proposed sequential life testing approach.
Abstract: This paper considers a multi criteria cell formation
problem in Cellular Manufacturing System (CMS). Minimizing the
number of voids and exceptional elements in cells simultaneously are
two proposed objective functions. This problem is an Np-hard
problem according to the literature, and therefore, we can-t find the
optimal solution by an exact method. In this paper we developed two
ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant
System (MMAS), based on Data Envelopment Analysis (DEA). Both
of them try to find the efficient solutions based on efficiency concept
in DEA. Each artificial ant is considered as a Decision Making Unit
(DMU). For each DMU we considered two inputs, the values of
objective functions, and one output, the value of one for all of them.
In order to evaluate performance of proposed methods we provided
an experimental design with some empirical problem in three
different sizes, small, medium and large. We defined three different
criteria that show which algorithm has the best performance.
Abstract: Sustainability in rural production system can only be achieved if it can suitably satisfy the local requirement as well as the outside demand with the changing time. With the increased pressure from the food sector in a globalised world, the agrarian economy
needs to re-organise its cultivable land system to be compatible with new management practices as well as the multiple needs of various stakeholders and the changing resource scenario. An attempt has been made to transform this problem into a multi-objective decisionmaking problem considering various objectives, resource constraints and conditional constraints. An interactive fuzzy multi-objective
programming approach has been used for such a purpose taking a
case study in Indian context to demonstrate the validity of the method.
Abstract: All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.
Abstract: Risk response planning is of importance for software project risk management (SPRM). In CMMI, risk management was in the third capability maturity level, which provides a framework for software project risk identification, assessment, risk planning, risk control. However, the CMMI-based SPRM currently lacks quantitative supporting tools, especially during the process of implementing software project risk planning. In this paper, an economic optimization model for selecting risk reduction actions in the phase of software project risk response planning is presented. Furthermore, an example taken from a Chinese software industry is illustrated to verify the application of this method. The research provides a risk decision method for project risk managers that can be used in the implementation of CMMI-based SPRM.
Abstract: In this paper we present high performance
dynamically allocated multi-queue (DAMQ) buffer schemes for fault
tolerance systems on chip applications that require an interconnection
network. Two virtual channels shared the same buffer space. Fault
tolerant mechanisms for interconnection networks are becoming a
critical design issue for large massively parallel computers. It is also
important to high performance SoCs as the system complexity keeps
increasing rapidly. On the message switching layer, we make
improvement to boost system performance when there are faults
involved in the components communication. The proposed scheme is
when a node or a physical channel is deemed as faulty, the previous
hop node will terminate the buffer occupancy of messages destined
to the failed link. The buffer usage decisions are made at switching
layer without interactions with higher abstract layer, thus buffer
space will be released to messages destined to other healthy nodes
quickly. Therefore, the buffer space will be efficiently used in case
fault occurs at some nodes.
Abstract: Owing the fact that optimization of business process
is a crucial requirement to navigate, survive and even thrive in
today-s volatile business environment, this paper presents a
framework for selecting a best-fit optimization package for solving
complex business problems. Complexity level of the problem and/or
using incorrect optimization software can lead to biased solutions of
the optimization problem. Accordingly, the proposed framework
identifies a number of relevant factors (e.g. decision variables,
objective functions, and modeling approach) to be considered during
the evaluation and selection process. Application domain, problem
specifications, and available accredited optimization approaches are
also to be regarded. A recommendation of one or two optimization
software is the output of the framework which is believed to provide
the best results of the underlying problem. In addition to a set of
guidelines and recommendations on how managers can conduct an
effective optimization exercise is discussed.
Abstract: Network-Centric Air Defense Missile Systems
(NCADMS) represents the superior development of the air defense
missile systems and has been regarded as one of the major research
issues in military domain at present. Due to lack of knowledge and
experience on NCADMS, modeling and simulation becomes an effective
approach to perform operational analysis, compared with
those equation based ones. However, the complex dynamic interactions
among entities and flexible architectures of NCADMS put forward
new requirements and challenges to the simulation framework
and models. ABS (Agent-Based Simulations) explicitly addresses
modeling behaviors of heterogeneous individuals. Agents have capability
to sense and understand things, make decisions, and act on the
environment. They can also cooperate with others dynamically to
perform the tasks assigned to them. ABS proves an effective approach
to explore the new operational characteristics emerging in
NCADMS. In this paper, based on the analysis of network-centric
architecture and new cooperative engagement strategies for
NCADMS, an agent-based simulation framework by expanding the
simulation framework in the so-called System Effectiveness Analysis
Simulation (SEAS) was designed. The simulation framework specifies
components, relationships and interactions between them, the
structure and behavior rules of an agent in NCADMS. Based on scenario
simulations, information and decision superiority and operational
advantages in NCADMS were analyzed; meanwhile some
suggestions were provided for its future development.
Abstract: A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Abstract: In this work the opportunity of construction of the
qualifiers for face-recognition systems based on conjugation criteria
is investigated. The linkage between the bipartite conjugation, the
conjugation with a subspace and the conjugation with the null-space
is shown. The unified solving rule is investigated. It makes the
decision on the rating of face to a class considering the linkage
between conjugation values. The described recognition method can
be successfully applied to the distributed systems of video control
and video observation.
Abstract: Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.