Abstract: This study was conducted to investigate the optimum
levels of glutamine (Gln) supplementation in broiler diets. A total of
32 one-day-old male chicks with initial body weight 41.5 g were
segregated into 4 groups (8 chicks per group) and subsequently
distributed to individual cages. Feed and water were provided ad
libitum for 21 days. Four dietary treatments were as follows: control
and supplemented Gln at 1, 2 and 3%, respectively. The results found
that the addition Gln had no negative effects on dry matter, organic
matter, ash digestibility or nitrogen retention. Birds fed with 1% Gln
had significantly higher villi wide and villi height : crypt depth ratio
in duodenum than the control chicks and 2 and 3% Gln chicks. It is
suggested that the addition of Gln at 1% indicated a beneficial effect
on improving small intestinal morphology, in addition Gln may
stimulate immune organ development of broiler chickens.
Abstract: A rare phenomenon of SDS-induced activation of a latent protease activity associated with the purified silkworm excretory red fluorescent protein (SE-RFP) was noticed. SE-RFP aliquots incubated with SDS for different time intervals indicated that the protein undergoes an obligatory breakdown into a number of subunits which exhibit autoproteolytic (acting upon themselves) and/or heteroproteolytic (acting on other proteins) activities. A strong serine protease activity of SE-RFP subunits on Bombyx mori nucleopolyhedrovirus (BmNPV) polyhedral protein was detected by zymography technique. A complete inhibition of BmNPV infection to silkworms was observed by the oral administration assay of the SE-RFP. Here, it is proposed that the SE-RFP prevents the initial infection of BmNPV to silkworms by obliterating the polyhedral protein. This is the first report on a silkworm red fluorescent protein that exhibits a protease activity on exposure to SDS. The present studies would help in understanding the antiviral mechanism of silkworm red fluorescent proteins.
Abstract: This paper presents a software quality support tool, a
Java source code evaluator and a code profiler based on
computational intelligence techniques. It is Java prototype software
developed by AI Group [1] from the Research Laboratories at
Universidad de Palermo: an Intelligent Java Analyzer (in Spanish:
Analizador Java Inteligente, AJI). It represents a new approach to
evaluate and identify inaccurate source code usage and transitively,
the software product itself.
The aim of this project is to provide the software development
industry with a new tool to increase software quality by extending
the value of source code metrics through computational intelligence.
Abstract: Frauds in insurance industry are one of the major
sources of operational risk of insurance companies and constitute a
significant portion of their losses. Every reasonable company on the
market aims for improving their processes of uncovering frauds and
invests their resources to reduce them. This article is addressing fraud
management area from the view of extension of existing Business
Intelligence solution. We describe the frame of such solution and
would like to share with readers all benefits brought to insurance
companies by adopting this approach in their fight against insurance
frauds.
Abstract: This paper proposes a new model to support user
queries on postgraduate research information at Universiti Tenaga
Nasional. The ontology to be developed will contribute towards
shareable and reusable domain knowledge that makes knowledge
assets intelligently accessible to both people and software. This work
adapts a methodology for ontology development based on the
framework proposed by Uschold and King. The concepts and
relations in this domain are represented in a class diagram using the
Protégé software. The ontology will be used to support a menudriven
query system for assisting students in searching for
information related to postgraduate research at the university.
Abstract: Fuel cells have become one of the major areas of
research in the academia and the industry. The goal of most fish
farmers is to maximize production and profits while holding labor
and management efforts to the minimum. Risk of fish kills, disease
outbreaks, poor water quality in most pond culture operations,
aeration offers the most immediate and practical solution to water
quality problems encountered at higher stocking and feeding rates.
Many units of aeration system are electrical units so using a
continuous, high reliability, affordable, and environmentally friendly
power sources is necessary. Aeration of water by using PEM fuel cell
power is not only a new application of the renewable energy, but
also, it provides an affordable method to promote biodiversity in
stagnant ponds and lakes. This paper presents a new design and
control of PEM fuel cell powered a diffused air aeration system for a
shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence
(AI) techniques control is used to control the fuel cell output power
by control input gases flow rate. Moreover the mathematical
modeling and simulation of PEM fuel cell is introduced. A
comparison study is applied between the performance of fuzzy logic
control (FLC) and neural network control (NNC). The results show
the effectiveness of NNC over FLC.
Abstract: This work presents the design of an expert system that aims in the procurement of patient medial background and in the search for suitable skin test selections. Skin testing is the tool used most widely to diagnose allergies. The language of expert systems CLIPS is used as a tool of designing. Finally, we present the evaluation of the proposed expert system which was achieved with the import of certain medical cases and the system produced with suitable successful skin tests.
Abstract: This article addresses the procedures to validate the Arabic version of Multiple Intelligence Development Assessment Scale (MIDAS). The content validity was examined based on the experts- judgments on the MIDAS-s items in the Arabic version. The content of eleven items in the Arabic version of MIDAS was modified to match the Arabic context. Then a translation from original English version of MIDAS into Arabic language was performed. The reliability of the Arabic MIDAS was calculated based on test and retest method and found to be 0.85 for the overall MIDAS and for the different subscales ranging between 0.78 - 0.87. The examination of construct validity for the overall Arabic MIDAS and its subscales was established by using Winsteps program version 6 based on Rasch model in order to fit the items into the Arabic context. The findings indicated that, the eight subscales in Arabic version of MIDAS scale have a unidimensionality, and the total number of kept items in the overall scale is 108 items.
Abstract: This study include the effect of strain and storage
period and their interaction on some quantitative and qualitative traits
and percentages of the egg components in the eggs collected at the
start of production (at age 24 weeks). Eggs were divided into three
storage periods (1, 7 and 14) days under refrigerator temperature (5-
7)0C. Fifty seven eggs obtained randomly from each strain including
Isa Brown and Lohman White. General Linear Model within
SAS programme was used to analyze the collected data
and correlations between the studied traits were calculated for each
strain.Average egg weight (EW), Haugh Unit (HU), yolk index (YI),
yolk % (HP), albumin % (AP) and yolk to albumin ratio (YAR) was
56.629 gm, 87.968 %, 0.493, 22.13%, 67.74% and 32.76
respectively. Egg produced from ISA Brown surpassed those
produced by Lohman White significantly (P
Abstract: Fuzzy logic approach is used in this study to predict
the tractive performance in terms of traction force, and motion
resistance for an intelligent air cushion track vehicle while it operates
in the swamp peat. The system is effective to control the intelligent
air –cushion system with measuring the vehicle traction force (TF),
motion resistance (MR), cushion clearance height (CH) and cushion
pressure (CP). Sinkage measuring sensor, magnetic switch, pressure
sensor, micro controller, control valves and battery are incorporated
with the Fuzzy logic system (FLS) to investigate experimentally the
TF, MR, CH, and CP. In this study, a comparison for tractive
performance of an intelligent air cushion track vehicle has been
performed with the results obtained from the predicted values of FLS
and experimental actual values. The mean relative error of actual and
predicted values from the FLS model on traction force, and total
motion resistance are found as 5.58 %, and 6.78 % respectively. For
all parameters, the relative error of predicted values are found to be
less than the acceptable limits. The goodness of fit of the prediction
values from the FLS model on TF, and MR are found as 0.90, and
0.98 respectively.
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents in legacy e-learning environments. It introduces the design and development of a scalable
and interoperable integration platform supporting various assessment agents for e-learning environments. The agents are implemented in
order to provide intelligent assessment services to computational intelligent techniques such as Bayesian Networks and Genetic
Algorithms. The utilization of new and emerging technologies like web services allows integrating the provided services to any web
based legacy e-learning environment.
Abstract: This paper presents a general trainable framework
for fast and robust upright human face and non-human object
detection and verification in static images. To enhance the
performance of the detection process, the technique we develop is
based on the combination of fast neural network (FNN) and
classical neural network (CNN). In FNN, a useful correlation is
exploited to sustain high level of detection accuracy between input
image and the weight of the hidden neurons. This is to enable the
use of Fourier transform that significantly speed up the time
detection. The combination of CNN is responsible to verify the
face region. A bootstrap algorithm is used to collect non human
object, which adds the false detection to the training process of the
human and non-human object. Experimental results on test images
with both simple and complex background demonstrate that the
proposed method has obtained high detection rate and low false
positive rate in detecting both human face and non-human object.
Abstract: Coloured Petri net (CPN) has been widely adopted in various areas in Computer Science, including protocol specification, performance evaluation, distributed systems and coordination in multi-agent systems. It provides a graphical representation of a system and has a strong mathematical foundation for proving various properties. This paper proposes a novel representation of a coloured Petri net using an extension of logic programming called abductive logic programming (ALP), which is purely based on classical logic. Under such a representation, an implementation of a CPN could be directly obtained, in which every inference step could be treated as a kind of equivalence preserved transformation. We would describe how to implement a CPN under such a representation using common meta-programming techniques in Prolog. We call our framework CPN-LP and illustrate its applications in modeling an intelligent agent.
Abstract: Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.
Abstract: As a result of the high cost of housing, the increasing population is forced to live in substandard housing and unhealthy conditions giving rise to poor residential neighborhoods. The paper examines the causes and characteristics of poor residential neighborhood. The paper finds the problems that have influence poor neighborhoods to; poverty, growth of informal sector and housing shortage. The paper asserts that poor residential neighborhoods have adverse effects on the people.
The secondary data was obtained from books, journals and seminar papers while primary data relating to building and environmental quality from structured questionnaire administered on sample of 500 household heads, from sampling frame of 5000 housing units.
The study reveals that majority of the respondents are poor and employed in informal sector. The paper suggests urban renewal and slum upgrading programs as methods in dealing with the situation and an improvement in the socio-economic circumstances of the inhabitants.
Abstract: A logic model for analyzing complex systems- stability
is very useful to many areas of sciences. In the real world, we are
enlightened from some natural phenomena such as “biosphere", “food
chain", “ecological balance" etc. By research and practice, and taking
advantage of the orthogonality and symmetry defined by the theory of
multilateral matrices, we put forward a logic analysis model of
stability of complex systems with three relations, and prove it by
means of mathematics. This logic model is usually successful in
analyzing stability of a complex system. The structure of the logic
model is not only clear and simple, but also can be easily used to
research and solve many stability problems of complex systems. As an
application, some examples are given.
Abstract: Flexible manufacturing system is a system that is able to respond to changed conditions. In general, this flexibility is divided into two key categories and several subcategories. The first category is the so called machine flexibility which enables to make various products by the given machinery. The second category is routing flexibility enabling to execute the same operation by various machines. Flexible manufacturing systems usually consist of three main parts: CNC machine tools, transport system and control system. A higher level of flexible manufacturing systems is represented by the so called intelligent manufacturing systems.
Abstract: In this paper, the deformation modes of a compact impact absorption member subjected to axial compression are investigated using finite element method and experiments. A multiple combination compact impact absorption member, referred to as a 'compress-expand member', is proposed to substitute the conventional thin-walled circular tube. This study found that the proposed compact impact absorption member has stable load increase characteristics and a wider range of high load efficiency (Pave/Pmax) than the thin-walled circular tube. Moreover, the proposed compact impact absorption member can absorb larger loads in a smaller radius than the thin-walled cylindrical tube, as it can maintain its stable deformation in increased wall thicknesses.
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: A greenhouse experiment was conducted to investigate the effects of different types of nutrients induced salinity on the growth, membrane permeability, nitrate reductase activity, proline content and macronutrient concentrations of tomato plants. The plants were subjected to six different treatments: 1 (control) containing basic solution, 2 basic solution+40mM of NaCl, 3 basic solution+40 mM of KNO3, 4 basic solution+20 mM of Ca(NO3)2.4H2O, 5 basic solution+20 mM of Mg(NO3)2.6H2O and 6 basic solution+20 mM of KNO3+5 mM of Ca(NO3)2.4H2O+5 mM of Mg(NO3)2.6H2O. Membrane permeability was increased significantly only with addition of NaCl, and then decreased to its lower level with addition of Ca(NO3)2.4H2O and Mg(NO3)2.6H2O. Proline accumulation were followed the same trend of results when they had been exposed to NaCl salinity. Nitrate reductase activity (NRA) was significantly affected by addition of different types of nutrient induced salinity.