Abstract: Many-core GPUs provide high computing ability and
substantial bandwidth; however, optimizing irregular applications
like SpMV on GPUs becomes a difficult but meaningful task. In this
paper, we propose a novel method to improve the performance of
SpMV on GPUs. A new storage format called HYB-R is proposed to
exploit GPU architecture more efficiently. The COO portion of the
matrix is partitioned recursively into a ELL portion and a COO
portion in the process of creating HYB-R format to ensure that there
are as many non-zeros as possible in ELL format. The method of
partitioning the matrix is an important problem for HYB-R kernel, so
we also try to tune the parameters to partition the matrix for higher
performance. Experimental results show that our method can get
better performance than the fastest kernel (HYB) in NVIDIA-s
SpMV library with as high as 17% speedup.
Abstract: In this paper a class of analog algorithms based on the
concept of Cellular Neural Network (CNN) is applied in some
processing operations of some important medical images, namely
retina images, for detecting various symptoms connected with
diabetic retinopathy. Some specific processing tasks like
morphological operations, linear filtering and thresholding are
proposed, the corresponding template values are given and
simulations on real retina images are provided.
Abstract: The Programmable Logic Controller (PLC) plays a
vital role in automation and process control. Grafcet is used for
representing the control logic, and traditional programming
languages are used for describing the pure algorithms. Grafcet is used
for dividing the process to be automated in elementary sequences that
can be easily implemented. Each sequence represent a step that has
associated actions programmed using textual or graphical languages
after case. The programming task is simplified by using a set of
subroutines that are used in several steps. The paper presents an
example of implementation for a punching machine for sheets and
plates. The use the graphical languages the programming of a
complex sequential process is a necessary solution. The state of
Grafcet can be used for debugging and malfunction determination.
The use of the method combined with a set of knowledge acquisition
for process application reduces the downtime of the machine and
improve the productivity.
Abstract: In the era of great competition, understanding and satisfying
customers- requirements are the critical tasks for a company
to make a profits. Customer relationship management (CRM) thus
becomes an important business issue at present. With the help of
the data mining techniques, the manager can explore and analyze
from a large quantity of data to discover meaningful patterns and
rules. Among all methods, well-known association rule is most
commonly seen. This paper is based on Apriori algorithm and uses
genetic algorithms combining a data mining method to discover fuzzy
classification rules. The mined results can be applied in CRM to
help decision marker make correct business decisions for marketing
strategies.
Abstract: The concept of flexible manufacturing is highly
appealing in gaining a competitive edge in the market by quickly
adapting to the changing customer needs. Scheduling jobs on flexible
manufacturing systems (FMSs) is a challenging task of managing the
available flexibility on the shop floor to react to the dynamics of the
environment in real-time. In this paper, an agent-oriented scheduling
framework that can be integrated with a real or a simulated FMS is
proposed. This framework works in stochastic environments with a
dynamic model of job arrival. It supports a hierarchical cooperative
scheduling that builds on the available flexibility of the shop floor.
Testing the framework on a model of a real FMS showed the
capability of the proposed approach to overcome the drawbacks of
the conventional approaches and maintain a near optimal solution
despite the dynamics of the operational environment.
Abstract: Work Breakdown Structure (WBS) is one of the
most vital planning processes of the project management since it
is considered to be the fundamental of other processes like
scheduling, controlling, assigning responsibilities, etc. In fact
WBS or activity list is the heart of a project and omission of a
simple task can lead to an irrecoverable result. There are some
tools in order to generate a project WBS. One of the most
powerful tools is mind mapping which is the basis of this article.
Mind map is a method for thinking together and helps a project
manager to stimulate the mind of project team members to
generate project WBS. Here we try to generate a WBS of a
sample project involving with the building construction using the
aid of mind map and the artificial intelligence (AI) programming
language. Since mind map structure can not represent data in a
computerized way, we convert it to a semantic network which can
be used by the computer and then extract the final WBS from the
semantic network by the prolog programming language. This
method will result a comprehensive WBS and decrease the
probability of omitting project tasks.
Abstract: Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.
Abstract: This paper investigates the control of a bouncing
ball using Model Predictive Control. Bouncing ball is a benchmark
problem for various rhythmic tasks such as juggling, walking,
hopping and running. Humans develop intentions which may be
perceived as our reference trajectory and tries to track it. The
human brain optimizes the control effort needed to track its
reference; this forms the central theme for control of bouncing ball
in our investigations.
Abstract: In this paper, we present the recently implemented approach allowing dynamics systems to plan its actions, taking into account the environment perception changes, and to control their execution when uncertainty and incomplete knowledge are the major characteristics of the situated environment [1],[2],[3],[4]. The control distributed architecture has three modules and the approach is related to hierarchical planning: the plan produced by the planner is further refined at the control layer that in turn supervises its execution by a functional level. We propose a new intelligent distributed architecture constituted by: Multi-Agent subsystem of the sensor, of the interpretation and representation of environment [9], of the dynamic localization and of the action. We tested this distributed architecture with dynamic system in the known environment. The autonomous for Rotor Mini Rotorcraft task is described by the primitive actions. The distributed controlbased on multi-agent system is in charge of achieving each task in the best possible way taking into account the context and sensory feedback.
Abstract: Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.
Abstract: Extracting and elaborating software requirements and
transforming them into viable software architecture are still an
intricate task. This paper defines a solution architecture which is
based on the blurred amalgamation of problem space and solution
space. The dependencies between domain constraints, requirements
and architecture and their importance are described that are to be
considered collectively while evolving from problem space to
solution space. This paper proposes a revised version of Twin Peaks
Model named Win Peaks Model that reconciles software
requirements and architecture in more consistent and adaptable
manner. Further the conflict between stakeholders- win-requirements
is resolved by proposed Voting methodology that is simple
adaptation of win-win requirements negotiation model and QARCC.
Abstract: Faced with social and health system capacity
constraints and rising and changing demand for welfare services,
governments and welfare providers are increasingly relying on
innovation to help support and enhance services. However, the
evidence reported by several studies indicates that the realization of
that potential is not an easy task. Innovations can be deemed
inherently complex to implement and operate, because many of them
involve a combination of technological and organizational renewal
within an environment featuring a diversity of stakeholders. Many
public welfare service innovations are markedly systemic in their
nature, which means that they emerge from, and must address, the
complex interplay between political, administrative, technological,
institutional and legal issues. This paper suggests that stakeholders
dealing with systemic innovation in welfare services must deal with
ambiguous and incomplete information in circumstances of
uncertainty. Employing a literature review methodology and case
study, this paper identifies, categorizes and discusses different
aspects of the uncertainty of systemic innovation in public welfare
services, and argues that uncertainty can be classified into eight
categories: technological uncertainty, market uncertainty,
regulatory/institutional uncertainty, social/political uncertainty,
acceptance/legitimacy uncertainty, managerial uncertainty, timing
uncertainty and consequence uncertainty.
Abstract: The complexity of today-s software systems makes
collaborative development necessary to accomplish tasks.
Frameworks are necessary to allow developers perform their tasks
independently yet collaboratively. Similarity detection is one of the
major issues to consider when developing such frameworks. It allows
developers to mine existing repositories when developing their own
views of a software artifact, and it is necessary for identifying the
correspondences between the views to allow merging them and
checking their consistency. Due to the importance of the
requirements specification stage in software development, this paper
proposes a framework for collaborative development of Object-
Oriented formal specifications along with a similarity detection
approach to support the creation, merging and consistency checking
of specifications. The paper also explores the impact of using
additional concepts on improving the matching results. Finally, the
proposed approach is empirically evaluated.
Abstract: With the enormous growth on the web, users get easily
lost in the rich hyper structure. Thus developing user friendly and
automated tools for providing relevant information without any
redundant links to the users to cater to their needs is the primary task
for the website owners. Most of the existing web mining algorithms
have concentrated on finding frequent patterns while neglecting the
less frequent one that are likely to contain the outlying data such as
noise, irrelevant and redundant data. This paper proposes new
algorithm for mining the web content by detecting the redundant
links from the web documents using set theoretical(classical
mathematics) such as subset, union, intersection etc,. Then the
redundant links is removed from the original web content to get the
required information by the user..
Abstract: The use of machine vision to inspect the outcome of
surgical tasks is investigated, with the aim of incorporating this
approach in robotic surgery systems. Machine vision is a non-contact
form of inspection i.e. no part of the vision system is in direct contact
with the patient, and is therefore well suited for surgery where
sterility is an important consideration,. As a proof-of-concept, three
primary surgical tasks for a common neurosurgical procedure were
inspected using machine vision. Experiments were performed on
cadaveric pig heads to simulate the two possible outcomes i.e.
satisfactory or unsatisfactory, for tasks involved in making a burr
hole, namely incision, retraction, and drilling. We identify low level
image features to distinguish the two outcomes, as well as report on
results that validate our proposed approach. The potential of using
machine vision in a surgical environment, and the challenges that
must be addressed, are identified and discussed.
Abstract: This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.
Abstract: This paper mathematically analyses the varying
magnitude of production loss, which may occur due to idle time (inprocess
waiting time and traveling time) on a linear walking worker
assembly line. Within this flexible and reconfigurable assembly
system, each worker travels down the line carrying out each
assembly task at each station; and each worker accomplishes the
assembly of a unit from start to finish and then travels back to the
first station to start the assembly of a new product. This strategy of
system design attempts to combine the flexibility of the U-shaped
moving worker assembly cell with the efficiency of the conventional
fixed worker assembly line. The paper aims to evaluate the effect of
idle time that may offset the labor efficiency of each walking worker
providing an insight into the mechanism of such a flexible and
reconfigurable assembly system.
Abstract: It is necessary to incorporate technological advances
achieved in the field of engineering into dentistry in order to enhance
the process of diagnosis, treatment planning and enable the doctors to
render better treatment to their patients. To achieve this ultimate goal
long distance collaborations are often necessary. This paper discusses
the various collaborative tools and their applications to solve a few
burning problems confronted by the dentists. Customization is often
the solution to most of the problems. But rapid designing,
development and cost effective manufacturing is a difficult task to
achieve. This problem can be solved using the technique of digital
manufacturing. Cases from 6 major branches of dentistry have been
discussed and possible solutions with the help of state of art
technology using rapid digital manufacturing have been proposed in
the present paper. The paper also entails the usage of existing tools in
collaborative and digital manufacturing area.
Abstract: There are multiple reasons to expect that detecting the
word order errors in a text will be a difficult problem, and detection
rates reported in the literature are in fact low. Although grammatical
rules constructed by computer linguists improve the performance of
grammar checker in word order diagnosis, the repairing task is still
very difficult. This paper presents an approach for repairing word
order errors in English text by reordering words in a sentence and
choosing the version that maximizes the number of trigram hits
according to a language model. The novelty of this method concerns
the use of an efficient confusion matrix technique for reordering the
words. The comparative advantage of this method is that works with
a large set of words, and avoids the laborious and costly process of
collecting word order errors for creating error patterns.
Abstract: This paper presents a recognition system for isolated
words like robot commands. It’s carried out by Time Delay Neural
Networks; TDNN. To teleoperate a robot for specific tasks as turn,
close, etc… In industrial environment and taking into account the
noise coming from the machine. The choice of TDNN is based on its
generalization in terms of accuracy, in more it acts as a filter that
allows the passage of certain desirable frequency characteristics of
speech; the goal is to determine the parameters of this filter for
making an adaptable system to the variability of speech signal and to
noise especially, for this the back propagation technique was used in
learning phase. The approach was applied on commands pronounced
in two languages separately: The French and Arabic. The results for
two test bases of 300 spoken words for each one are 87%, 97.6% in
neutral environment and 77.67%, 92.67% when the white Gaussian
noisy was added with a SNR of 35 dB.