Abstract: An appropriate project delivery system (PDS) is crucial
to the success of a construction projects. Case-based Reasoning (CBR)
is a useful support for PDS selection. However, the traditional CBR
approach represents cases as attribute-value vectors without taking
relations among attributes into consideration, and could not calculate
the similarity when the structures of cases are not strictly same.
Therefore, this paper solves this problem by adopting the Relational
Case-based Reasoning (RCBR) approach for PDS selection,
considering both the structural similarity and feature similarity. To
develop the feature terms of the construction projects, the criteria and
factors governing PDS selection process are first identified. Then
feature terms for the construction projects are developed. Finally, the
mechanism of similarity calculation and a case study indicate how
RCBR works for PDS selection. The adoption of RCBR in PDS
selection expands the scope of application of traditional CBR method
and improves the accuracy of the PDS selection system.
Abstract: This paper examines the use of mechanical aerator for
oxidation-ditch process. The rotor, which controls the aeration, is the
main component of the aeration process. Therefore, the objective of
this study is to find out the variations in overall oxygen transfer
coefficient (KLa) and aeration efficiency (AE) for different
configurations of aerator by varying the parameters viz. speed of
aerator, depth of immersion, blade tip angles so as to yield higher
values of KLa and AE. Six different configurations of aerator were
developed and fabricated in the laboratory and were tested for abovementioned
parameters. The curved blade rotor (CBR) emerged as a
potential aerator with blade tip angle of 47°.
The mathematical models are developed for predicting the
behaviour of CBR w.r.t kLa and power. In laboratory studies, the
optimum value of KLa and AE were observed to be 10.33 h-1 and
2.269 kg O2/ kWh.
Abstract: The paper aims to specify and build a system, a learning support in radiology-senology (breast radiology) dedicated to help assist junior radiologists-senologists in their radiologysenology- related activity based on experience of expert radiologistssenologists. This system is named SAFRS (i.e. system supporting the training of radiologists-senologists). It is based on the exploitation of radiologic-senologic images (primarily mammograms but also echographic images or MRI) and their related clinical files. The aim of such a system is to help breast cancer screening in education. In order to acquire this expert radiologist-senologist knowledge, we have used the CBR (case-based reasoning) approach. The SAFRS system will promote the evolution of teaching in radiology-senology by offering the “junior radiologist" trainees an advanced pedagogical product. It will permit a strengthening of knowledge together with a very elaborate presentation of results. At last, the know-how will derive from all these factors.
Abstract: Design for cost (DFC) is a method that reduces life
cycle cost (LCC) from the angle of designers. Multiple domain
features mapping (MDFM) methodology was given in DFC. Using
MDFM, we can use design features to estimate the LCC. From the
angle of DFC, the design features of family cars were obtained, such
as all dimensions, engine power and emission volume. At the
conceptual design stage, cars- LCC were estimated using back
propagation (BP) artificial neural networks (ANN) method and
case-based reasoning (CBR). Hamming space was used to measure the
similarity among cases in CBR method. Levenberg-Marquardt (LM)
algorithm and genetic algorithm (GA) were used in ANN. The
differences of LCC estimation model between CBR and artificial
neural networks (ANN) were provided. ANN and CBR separately
each method has its shortcomings. By combining ANN and CBR
improved results accuracy was obtained. Firstly, using ANN selected
some design features that affect LCC. Then using LCC estimation
results of ANN could raise the accuracy of LCC estimation in CBR
method. Thirdly, using ANN estimate LCC errors and correct errors in
CBR-s estimation results if the accuracy is not enough accurate.
Finally, economically family cars and sport utility vehicle (SUV) was
given as LCC estimation cases using this hybrid approach combining
ANN and CBR.
Abstract: Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.
Abstract: Currently, there are many local area industrial networks
that can give guaranteed bandwidth to synchronous traffic, particularly
providing CBR channels (Constant Bit Rate), which allow
improved bandwidth management. Some of such networks operate
over Ethernet, delivering channels with enough capacity, specially
with compressors, to integrate multimedia traffic in industrial monitoring
and image processing applications with many sources. In
these industrial environments where a low latency is an essential
requirement, JPEG is an adequate compressing technique but it
generates VBR traffic (Variable Bit Rate). Transmitting VBR traffic
in CBR channels is inefficient and current solutions to this problem
significantly increase the latency or further degrade the quality. In
this paper an R(q) model is used which allows on-line calculation of
the JPEG quantification factor. We obtained increased quality, a lower
requirement for the CBR channel with reduced number of discarded
frames along with better use of the channel bandwidth.
Abstract: This paper presents an integrated case based and rule
based reasoning method for car faulty diagnosis. The reasoning
method is done through extracting the past cases from the Proton
Service Center while comparing with the preset rules to deduce a
diagnosis/solution to a car service case. New cases will be stored to
the knowledge base. The test cases examples illustrate the
effectiveness of the proposed integrated reasoning. It has proven
accuracy of similar reasoning if carried out by a service advisor from
the service center.
Abstract: Nowadays, quick technological changes force companies
to develop innovative products in an increasingly competitive
environment. Therefore, how to enhance the time of new product
development is very important. This design problem often lacks
the exact formula for getting it, and highly depends upon human
designers- past experiences. For these reasons, in this work, a Casebased
reasoning (CBR) system to assist in new product development
is proposed. When a case is recovered from the case base, the system
will take into account not only the attribute-s specific value and
how important it is. It will also take into account if the attribute
has a positive influence over the product development. Hence the
manufacturing time will be improved. This information will be
introduced as a new concept called “adaptability". An application to
this method for hearing instrument new design illustrates the proposed
approach.
Abstract: Case based reasoning (CBR) methodology presents a foundation for a new technology of building intelligent computeraided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. This paper discusses the CBR methodology, the research issues and technical aspects of implementing intelligent medical diagnoses systems. Successful applications in cancer and heart diseases developed by Medical Informatics Research Group at Ain Shams University are also discussed.
Abstract: Exploring an autistic child in Elementary school is a
difficult task that must be fully thought out and the teachers should
be aware of the many challenges they face raising their child
especially the behavioral problems of autistic children. Hence there
arises a need for developing Artificial intelligence (AI)
Contemporary Techniques to help diagnosis to discover autistic
people.
In this research, we suggest designing architecture of expert
system that combine Cognitive Maps (CM) with Case Based
Reasoning technique (CBR) in order to reduce time and costs of
traditional diagnosis process for the early detection to discover
autistic children. The teacher is supposed to enter child's information
for analyzing by CM module. Then, the reasoning processor would
translate the output into a case to be solved a current problem by
CBR module. We will implement a prototype for the model as a
proof of concept using java and MYSQL.
This will be provided a new hybrid approach that will achieve new
synergies and improve problem solving capabilities in AI. And we
will predict that will reduce time, costs, the number of human errors
and make expertise available to more people who want who want to
serve autistic children and their families.
Abstract: A laboratory study on the influence of compactive
effort on expansive black cotton specimens treated with up to 8%
ordinary Portland cement (OPC) admixed with up to 8% bagasse ash
(BA) by dry weight of soil and compacted using the energies of the
standard Proctor (SP), West African Standard (WAS) or
“intermediate” and modified Proctor (MP) were undertaken. The
expansive black cotton soil was classified as A-7-6 (16) or CL using
the American Association of Highway and Transportation Officials
(AASHTO) and Unified Soil Classification System (USCS),
respectively. The 7day unconfined compressive strength (UCS)
values of the natural soil for SP, WAS and MP compactive efforts are
286, 401 and 515kN/m2 respectively, while peak values of 1019,
1328 and 1420kN/m2 recorded at 8% OPC/ 6% BA, 8% OPC/ 2% BA
and 6% OPC/ 4% BA treatments, respectively were less than the
UCS value of 1710kN/m2 conventionally used as criterion for
adequate cement stabilization. The soaked California bearing ratio
(CBR) values of the OPC/BA stabilized soil increased with higher
energy level from 2, 4 and 10% for the natural soil to Peak values of
55, 18 and 8% were recorded at 8% OPC/4% BA 8% OPC/2% BA
and 8% OPC/4% BA, treatments when SP, WAS and MP compactive
effort were used, respectively. The durability of specimens was
determined by immersion in water. Soils treatment at 8% OPC/ 4%
BA blend gave a value of 50% resistance to loss in strength value
which is acceptable because of the harsh test condition of 7 days
soaking period specimens were subjected instead of the 4 days
soaking period that specified a minimum resistance to loss in strength
of 80%. Finally An optimal blend of is 8% OPC/ 4% BA is
recommended for treatment of expansive black cotton soil for use as
a sub-base material.
Abstract: Mobile Ad hoc Network (MANET) is a wireless ad hoc self-configuring network of mobile routers (and associated hosts) connected by wireless links, the union of which forms an arbitrary topology, cause of the random mobility of the nodes. In this paper, an attempt has been made to compare these three protocols DSDV, AODV and DSR on the performance basis under different traffic protocols namely CBR and TCP in a large network. The simulation tool is NS2, the scenarios are made to see the effect of pause times. The results presented in this paper clearly indicate that the different protocols behave differently under different pause times. Also, the results show the main characteristics of different traffic protocols operating on MANETs and thus select the best protocol on each scenario.
Abstract: Case-Based Reasoning (CBR) is one of machine
learning algorithms for problem solving and learning that caught a lot
of attention over the last few years. In general, CBR is composed of
four main phases: retrieve the most similar case or cases, reuse the
case to solve the problem, revise or adapt the proposed solution, and
retain the learned cases before returning them to the case base for
learning purpose. Unfortunately, in many cases, this retain process
causes the uncontrolled case base growth. The problem affects
competence and performance of CBR systems. This paper proposes
competence-based maintenance method based on deletion policy
strategy for CBR. There are three main steps in this method. Step 1,
formulate problems. Step 2, determine coverage and reachability set
based on coverage value. Step 3, reduce case base size. The results
obtained show that this proposed method performs better than the
existing methods currently discussed in literature.
Abstract: This paper provides a flexible way of controlling
Variable-Bit-Rate (VBR) of compressed digital video, applicable to
the new H264 video compression standard. The entire video
sequence is assessed in advance and the quantisation level is then set
such that bit rate (and thus the frame rate) remains within
predetermined limits compatible with the bandwidth of the
transmission system and the capabilities of the remote end, while at
the same time providing constant quality similar to VBR encoding.
A process for avoiding buffer starvation by selectively eliminating
frames from the encoded output at times when the frame rate is slow
(large number of bits per frame) will be also described. Finally, the
problem of buffer overflow will be solved by selectively eliminating
frames from the received input to the decoder. The decoder detects
the omission of the frames and resynchronizes the transmission by
monitoring time stamps and repeating frames if necessary.
Abstract: Available Bit Rate Service (ABR) is the lower priority
service and the better service for the transmission of data. On wireline
ATM networks ABR source is always getting the feedback from
switches about increase or decrease of bandwidth according to the
changing network conditions and minimum bandwidth is guaranteed.
In wireless networks guaranteeing the minimum bandwidth is really a
challenging task as the source is always in mobile and traveling from
one cell to another cell. Re establishment of virtual circuits from start
to end every time causes the delay in transmission. In our proposed
solution we proposed the mechanism to provide more available
bandwidth to the ABR source by re-usage of part of old Virtual
Channels and establishing the new ones. We want the ABR source to
transmit the data continuously (non-stop) inorderto avoid the delay.
In worst case scenario at least minimum bandwidth is to be allocated.
In order to keep the data flow continuously, priority is given to the
handoff ABR call against new ABR call.
Abstract: The Mobile Ad-hoc Network (MANET) is a collection of self-configuring and rapidly deployed mobile nodes (routers) without any central infrastructure. Routing is one of the potential issues. Many routing protocols are reported but it is difficult to decide which one is best in all scenarios. In this paper on demand routing protocols DSR and DYMO based on IEEE 802.11 DCF MAC protocol are examined and characteristic summary of these routing protocols is presented. Their performance is analyzed and compared on performance measuring metrics throughput, dropped packets due to non availability of routes, duplicate RREQ generated for route discovery and normalized routing load by varying CBR data traffic load using QualNet 5.0.2 network simulator.
Abstract: Online learning with Intelligent Tutoring System (ITS) is becoming very popular where the system models the student-s learning behavior and presents to the student the learning material (content, questions-answers, assignments) accordingly. In today-s distributed computing environment, the tutoring system can take advantage of networking to utilize the model for a student for students from other similar groups. In the present paper we present a methodology where using Case Based Reasoning (CBR), ITS provides student modeling for online learning in a distributed environment with the help of agents. The paper describes the approach, the architecture, and the agent characteristics for such system. This concept can be deployed to develop ITS where the tutor can author and the students can learn locally whereas the ITS can model the students- learning globally in a distributed environment. The advantage of such an approach is that both the learning material (domain knowledge) and student model can be globally distributed thus enhancing the efficiency of ITS with reducing the bandwidth requirement and complexity of the system.
Abstract: Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.
Abstract: Soil stabilization has been widely used to improve
soil strength and durability or to prevent erosion and dust generation.
Generally to reduce problems of clayey soils in engineering work and
to stabilize these soils additional materials are used. The most
common materials are lime, fly ash and cement. Using this materials,
although improve soil property , but in some cases due to financial
problems and the need to use special equipment are limited .One of
the best methods for stabilization clayey soils is neutralization the
clay particles. For this purpose we can use ion exchange materials.
Ion exchange solution like CBR plus can be used for soil
stabilization. One of the most important things in using CBR plus is
determination the amount of this solution for various soils with
different properties. In this study a laboratory experiment is conduct
to evaluate the ion exchange capacity of three soils with various
plasticity index (PI) to determine amount or required CBR plus
solution for soil stabilization.
Abstract: Typically thermal power plants are located near to
surface coal mines that produce huge amount of fly ash as a waste
byproduct. Disposal of fly ash causes significant economic and
environmental problems. Now-a-days, research is going on for bulk
utilization of fly ash. In order to increase its percentage utilization, an
investigation was carried out to evaluate its potential for haul road
construction. This paper presents the laboratory California bearing
ratio (CBR) tests and evaluates the effect of lime on CBR behavior of
fly ash - mine overburden mixes. Tests were performed with different
percentages of lime (2%, 3%, 6%, and 9%). The results show that the
increase in bearing ratio of fly ash-overburden mixes was achieved
by lime treatment. Scanning electron microscopy (SEM) analyses
were conducted on 28 days cured specimens. The SEM study showed
that the bearing ratio development is related to the microstructural
development.