Abstract: This paper reviews the major contributions to the Motion Planning (MP) field throughout a 35-year period, from classic approaches to heuristic algorithms. Due to the NP-Hardness of the MP problem, heuristic methods have outperformed the classic approaches and have gained wide popularity. After surveying around 1400 papers in the field, the amount of existing works for each method is identified and classified. Especially, the history and applications of numerous heuristic methods in MP is investigated. The paper concludes with comparative tables and graphs demonstrating the frequency of each MP method's application, and so can be used as a guideline for MP researchers.
Abstract: The concept of housing affordability is a contested
issue, but a pressing and widespread problem for many countries.
Simple ratio measures based on housing expenditure and income are
habitually used to defined and assess housing affordability. However,
conceptualising and measuring affordability in this manner focuses
only on financial attributes and fails to deal with wider issues such as
housing quality, location and access to services and facilities.
The research is based on the notion that the housing affordability
problem encompasses more than the financial costs of housing and a
households ability to meet such costs and must address larger issues
such as social and environmental sustainability and the welfare of
households. Therefore, the need arises for a broad and more
encompassing set of attributes by which housing affordability can be
assessed. This paper presents a system of criteria by which the
affordability of different housing locations could be assessed in a
comprehensive and sustainable manner. Moreover, the paper explores
the way in which such criteria could be measured.
Abstract: This paper describes the modeling and simulation of an
underwater robot glider used in the shallow-water environment. We
followed the Equations of motion derived by [2] and simplified
dynamic Equations of motion of an underwater glider according to our
underwater glider. A simulation code is built and operated in the
MATLAB Simulink environment so that we can make improvements
to our testing glider design. It may be also used to validate a robot
glider design.
Abstract: Landfill gas, particularly methane is one of the
greenhouse gases which contributes to global warming. This paper presents the findings of a study on methane gas production from
simulated landfill reactor under saturated conditions. A reactor was constructed to represent a landfill cell of 2.5 m thickness on sandy
soil. The reactor was 0.2 m in diameter and 4 m in height. One meter of sand and pebble layer was packed at the bottom of the reactor
followed by 2.5 m of solid waste layer and 0.4 m of sand layer as the cover soil. Degradation of waste in the solid waste layer was at
acidification stage as indicated by the leachate quality with COD as
high as 55,511 mg/L and pH as low as 5.1. However, methanogenic
environment was established at the bottom sand layer after one year of operation indicated by pH of 7.2 and methane gas generation.
Leachate degradation took place as the leachate moved through the
sand layer at an infiltration of rate 0.7 cm/day. This resulted in landfill gas production of 77 mL/day/kg containing 55 to 65% methane. The application of sand layer contributed to the gas
production from landfill by an in-situ degradation of leachate in the
sand at the bottom of the landfill.
Abstract: “Dengue" is an African word meaning “bone
breaking" because it causes severe joint and muscle pain that feels
like bones are breaking. It is an infectious disease mainly transmitted
by female mosquito, Aedes aegypti, and causes four serotypes of
dengue viruses. In recent years, a dramatic increase in the dengue
fever confirmed cases around the equator-s belt has been reported.
Several conventional indices have been designed so far to monitor the
transmitting vector populations known as House Index (HI),
Container Index (CI), Breteau Index (BI). However, none of them
describes the adult mosquito population size which is important to
direct and guide comprehensive control strategy operations since
number of infected people has a direct relationship with the vector
density. Therefore, it is crucial to know the population size of the
transmitting vector in order to design a suitable and effective control
program. In this context, a study is carried out to report a new
statistical index, ABURAS Index, using Poisson distribution based
on the collection of vector population in Jeddah Governorate, Saudi Arabia.
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents and evolutionary
computation techniques in legacy e-learning environments. It
introduces the design and development of a scalable and
interoperable integration platform supporting:
I) various assessment agents for e-learning environments,
II) a specific resource retrieval agent for the provision of
additional information from Internet sources matching the
needs and profile of the specific user and
III) a genetic algorithm designed to extract efficient information
(classifying rules) based on the students- answering input
data.
The agents are implemented in order to provide intelligent
assessment services based on computational intelligence techniques
such as Bayesian Networks and Genetic Algorithms.
The proposed Genetic Algorithm (GA) is used in order to extract
efficient information (classifying rules) based on the students-
answering input data. The idea of using a GA in order to fulfil this
difficult task came from the fact that GAs have been widely used in
applications including classification of unknown data.
The utilization of new and emerging technologies like web
services allows integrating the provided services to any web based
legacy e-learning environment.
Abstract: Power system state estimation is the process of
calculating a reliable estimate of the power system state vector
composed of bus voltages' angles and magnitudes from telemetered
measurements on the system. This estimate of the state vector
provides the description of the system necessary for the operation
and security monitoring. Many methods are described in the
literature for solving the state estimation problem, the most important
of which are the classical weighted least squares method and the nondeterministic
genetic based method; however both showed
drawbacks. In this paper a modified version of the genetic
algorithm power system state estimation is introduced, Sensitivity of
the proposed algorithm to genetic operators is discussed, the
algorithm is applied to case studies and finally it is compared with
the classical weighted least squares method formulation.
Abstract: Due to heightened concerns over environmental and economic issues the growing important of air pollution, and the importance of conserving fossil fuel resources in the world, the automotive industry is now forced to produce more fuel efficient, low emission vehicles and new drive system technologies. One of the most promising technologies to receive attention is the hybrid electric vehicle (HEV), which consists of two or more energy sources that supply energy to electric traction motors that in turn drive the wheels. This paper presents the various structures of HEV systems, the basic theoretical knowledge for describing their operation and the general behaviour of the HEV in acceleration, cruise and deceleration phases. The conventional design and sizing of a series HEV is studied. A conventional bus and its series configuration are defined and evaluated using the ADVISOR. In this section the simulation of a standard driving cycle and prediction of its fuel consumption and emissions of the HEV are discussed. Finally the bus performance is investigated to establish whether it can satisfy the performance, fuel consumption and emissions requested. The validity of the simulation has been established by the close conformity between the fuel consumption of the conventional bus reported by the manufacturer to what has achieved from the simulation.
Abstract: Scene interpretation systems need to match (often ambiguous)
low-level input data to concepts from a high-level ontology.
In many domains, these decisions are uncertain and benefit greatly
from proper context. This paper demonstrates the use of decision
trees for estimating class probabilities for regions described by feature
vectors, and shows how context can be introduced in order to improve
the matching performance.
Abstract: In this study, the Scots pine (Pinus sylvestris L.) C
needles (i.e. the current-year-needles) were used as bioindicators in
determining the aerial distribution pattern of sulphur emissions
around industrial point sources at Kemi, Northern Finland. The
average sulphur concentration in the C needles was 897 mg/kg
(d.w.), with a standard deviation of 118 mg/kg (d.w.) and range 740 –
1350 mg/kg (d.w.). According to results in this study, Scots pine
needles (Pinus sylvestris L.) appear to be an ideal bioindicators for
identifying atmospheric sulphur pollution derived from industrial
plants and can complement the information provided by plant
mapping studies around industrial plants.
Abstract: Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.
Abstract: A two dimensional numerical simulation has been
performed for incompressible and compressible fluid flow through
microchannels in slip flow regime. The Navier-Stokes equations have
been solved in conjunction with Maxwell slip conditions for
modeling flow field associated with slip flow regime. The wall
roughness is simulated with triangular microelements distributed on
wall surfaces to study the effects of roughness on fluid flow. Various
Mach and Knudsen numbers are used to investigate the effects of
rarefaction as well as compressibility. It is found that rarefaction has
more significant effect on flow field in microchannels with higher
relative roughness. It is also found that compressibility has more
significant effects on Poiseuille number when relative roughness
increases. In addition, similar to incompressible models the increase
in average fRe is more significant at low Knudsen number flows but
the increase of Poiseuille number duo to relative roughness is sharper
for compressible models. The numerical results have also validated
with some available theoretical and experimental relations and good
agreements have been seen.
Abstract: The logistical requirements placed on industrial manufacturing companies are steadily increasing. In order to meet those requirements, a consistent and efficient concept is necessary for production control. Set up properly, production control offers considerable potential with respect to achieving the logistical targets. As experience with the many production control methods already in existence and their compatibility is, however, often inadequate, this article describes a systematic approach to the configuration of production control based on the Lödding model. This model enables production control to be set up individually to suit a company and the requirements. It therefore permits today-s demands regarding logistical performance to be met.
Abstract: Today, Genetic Algorithm has been used to solve
wide range of optimization problems. Some researches conduct on
applying Genetic Algorithm to text classification, summarization
and information retrieval system in text mining process. This
researches show a better performance due to the nature of Genetic
Algorithm. In this paper a new algorithm for using Genetic
Algorithm in concept weighting and topic identification, based on
concept standard deviation will be explored.
Abstract: Texture information plays increasingly an important
role in remotely sensed imagery classification and many pattern
recognition applications. However, the selection of relevant textural
features to improve this classification accuracy is not a straightforward
task. This work investigates the effectiveness of two Mutual
Information Feature Selector (MIFS) algorithms to select salient
textural features that contain highly discriminatory information for
multispectral imagery classification. The input candidate features are
extracted from a SPOT High Resolution Visible(HRV) image using
Wavelet Transform (WT) at levels (l = 1,2).
The experimental results show that the selected textural features
according to MIFS algorithms make the largest contribution to
improve the classification accuracy than classical approaches such
as Principal Components Analysis (PCA) and Linear Discriminant
Analysis (LDA).
Abstract: The study of proteomics reached unexpected levels of
interest, as a direct consequence of its discovered influence over some
complex biological phenomena, such as problematic diseases like
cancer. This paper presents the latest authors- achievements regarding
the analysis of the networks of proteins (interactome networks), by
computing more efficiently the betweenness centrality measure. The
paper introduces the concept of betweenness centrality, and then
describes how betweenness computation can help the interactome net-
work analysis. Current sequential implementations for the between-
ness computation do not perform satisfactory in terms of execution
times. The paper-s main contribution is centered towards introducing
a speedup technique for the betweenness computation, based on
modified shortest path algorithms for sparse graphs. Three optimized
generic algorithms for betweenness computation are described and
implemented, and their performance tested against real biological
data, which is part of the IntAct dataset.
Abstract: 28 healthy adult Maradi bucks were used to evaluate
sperm production and sperm storage capacity in the breed. Daily
sperm production (DSP) averaged 0.55±0.05x109, while the daily
sperm production/g (DSP/g) was 1.37±0.12 x107. Gonadal sperm
reserve was 1.99±0.18 x109, while the caput, upper corpus and lower
corpus averaged 0.58±0.04 x109, 0.36±0.02 x109 and 0.33±0.08 x109
respectively. The proximal cauda, mid cauda, distal cauda and ductus
deferens had values of 0.68±0.10 x109, 1.23±0.16 x109,1.87±0.
x109and 0.17±0.05 x109 respectively. The relative contributions of
the respective epididymal sections and ductus deferens to the total
extragonadal sperm reserves were, 11.11%, 6.89%, 6.32%, 13.03%,
23.56%, 35.82% and 3.26% respectively. Gonadal sperm reserves
were significantly higher (p0.05) to
mid cauda and distal cauda epididymal reserves.
Abstract: The aim of this retrospective study was to evaluate the
parameters of dental implants such as patient gender, number of
implant, failed implant before prosthetic restorations and failed
implant after implantation and failed implant after prosthetic
restorations. 135 male and 99 female patients, total 234 implant
patients which have been treated with 450 implant between 2005-
2009 years in GATA Haydarpasa Training Hospital Dental Service.
Twelve implants were failed before prosthetic restorations. Four
implant were failed after fixed prosthetic restorations. Cumulative
survival rate after prostheses were 97.56 % during 6 years period.
Abstract: The composite materials were prepared by sawdust, cassava starch and natural rubber latex (NR). The mixtures of 15%w/v gelatinized cassava starch and 15%w/v PVOH were used as the binder of these composite materials. The concentrated rubber latex was added to the mixtures. They were mixed rigorously to the treated sawdust in the ratio of 70:30 until achive uniform dispersion. The batters were subjected to the hot compression moulding at the temperature of 160°C and 3,000 psi pressure for 5 min. The experimental results showed that the mechanical properties of composite materials, which contained the gelatinized cassava starch and PVOH in the ratio of 2:1, 20% NR latex by weight of the dry starch and treated sawdust with 5%NaOH or 1% BPO, were the best. It contributed the maximal compression strength (341.10 + 26.11 N), puncture resistance (8.79 + 0.98 N/mm2) and flexural strength (3.99 + 0.72N/mm2). It is also found that the physicochemical and mechanical properties of composites strongly depends on the interface quality of sawdust, cassava starch and NR latex.
Abstract: This paper describes part of a project about Learningby-
Modeling (LbM). Studying complex systems is increasingly
important in teaching and learning many science domains. Many
features of complex systems make it difficult for students to develop
deep understanding. Previous research indicates that involvement
with modeling scientific phenomena and complex systems can play a
powerful role in science learning. Some researchers argue with this
view indicating that models and modeling do not contribute to
understanding complexity concepts, since these increases the
cognitive load on students. This study will investigate the effect of
different modes of involvement in exploring scientific phenomena
using computer simulation tools, on students- mental model from the
perspective of structure, behavior and function. Quantitative and
qualitative methods are used to report about 121 freshmen students
that engaged in participatory simulations about complex phenomena,
showing emergent, self-organized and decentralized patterns. Results
show that LbM plays a major role in students' concept formation
about complexity concepts.