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: The present work faces the problem of automatic enumeration and recognition of an unknown and time-varying number of environmental sound sources while using a single microphone. The assumption that is made is that the sound recorded is a realization of sound sources belonging to a group of audio classes which is known a-priori. We describe two variations of the same principle which is to calculate the distance between the current unknown audio frame and all possible combinations of the classes that are assumed to span the soundscene. We concentrate on categorizing environmental sound sources, such as birds, insects etc. in the task of monitoring the biodiversity of a specific habitat.
Abstract: In wireless sensor network (WSN) the use of mobile
sink has been attracting more attention in recent times. Mobile sinks
are more effective means of balancing load, reducing hotspot
problem and elongating network lifetime. The sensor nodes in WSN
have limited power supply, computational capability and storage and
therefore for continuous data delivery reliability becomes high
priority in these networks. In this paper, we propose a Reliable
Energy-efficient Data Dissemination (REDD) scheme for WSNs with
multiple mobile sinks. In this strategy, sink first determines the
location of source and then directly communicates with the source
using geographical forwarding. Every forwarding node (FN) creates a
local zone comprising some sensor nodes that can act as
representative of FN when it fails. Analytical and simulation study
reveals significant improvement in energy conservation and reliable
data delivery in comparison to existing schemes.
Abstract: Prolonged immobilization leads to significant
weakness and atrophy of the skeletal muscle and can also impair the
recovery of muscle strength following injury. Therefore, it is
important to minimize the period under immobilization and accelerate
the return to normal activity. This study examined the effects of heat
treatment and rest-inserted exercise on the muscle activity of the lower
limb during knee flexion/extension. Twelve healthy subjects were
assigned to 4 groups that included: (1) heat treatment + rest-inserted
exercise; (2) heat + continuous exercise; (3) no heat + rest-inserted
exercise; and (4) no heat + continuous exercise. Heat treatment was
applied for 15 mins prior to exercise. Continuous exercise groups
performed knee flexion/extension at 0.5 Hz for 300 cycles without rest
whereas rest-inserted exercise groups performed the same exercise but
with 2 mins rest inserted every 60 cycles of continuous exercise.
Changes in the rectus femoris and hamstring muscle activities were
assessed at 0, 1, and 2 weeks of treatment by measuring the
electromyography signals of isokinetic maximum voluntary
contraction. Significant increases in both the rectus femoris and
hamstring muscles were observed after 2 weeks of treatment only
when both heat treatment and rest-inserted exercise were performed.
These results suggest that combination of various treatment techniques,
such as heat treatment and rest-inserted exercise, may expedite the
recovery of muscle strength following immobilization.
Abstract: Recently, the improvements in processing performance
of a computer and in high speed communication of an optical fiber
have been achieved, so that the amount of data which are processed
by a computer and flowed on a network has been increasing greatly.
However, in a client-server system, since the server receives and
processes the amount of data from the clients through the network, a
load on the server is increasing. Thus, there are needed to introduce
a server with high processing ability and to have a line with high
bandwidth. In this paper, concerning to P2P networks to resolve the
load on a specific server, a criterion called an Indexed-Priority Metric
is proposed and its performance is evaluated. The proposed metric is
to allocate some files to each node. As a result, the load on a specific
server can distribute them to each node equally well. A P2P file
sharing system using the proposed metric is implemented. Simulation
results show that the proposed metric can make it distribute files on
the specific server.
Abstract: Thermo-chemical treatment (TCT) such as pyrolysis
is getting recognized as a valid route for (i) materials and valuable
products and petrochemicals recovery; (ii) waste recycling; and (iii)
elemental characterization. Pyrolysis is also receiving renewed
attention for its operational, economical and environmental
advantages. In this study, samples of polyethylene terephthalate
(PET) and polystyrene (PS) were pyrolysed in a microthermobalance
reactor (using a thermogravimetric-TGA setup). Both
polymers were prepared and conditioned prior to experimentation.
The main objective was to determine the kinetic parameters of the
depolymerization reactions that occur within the thermal degradation
process. Overall kinetic rate constants (ko) and activation energies
(Eo) were determined using the general kinetics theory (GKT)
method previously used by a number of authors. Fitted correlations
were found and validated using the GKT, errors were within ± 5%.
This study represents a fundamental step to pave the way towards the
development of scaling relationship for the investigation of larger
scale reactors relevant to industry.
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: A spanning tree of a connected graph is a tree which
consists the set of vertices and some or perhaps all of the edges from
the connected graph. In this paper, a model for spanning tree
transformation of connected graphs into single-row networks, namely
Spanning Tree of Connected Graph Modeling (STCGM) will be
introduced. Path-Growing Tree-Forming algorithm applied with
Vertex-Prioritized is contained in the model to produce the spanning
tree from the connected graph. Paths are produced by Path-Growing
and they are combined into a spanning tree by Tree-Forming. The
spanning tree that is produced from the connected graph is then
transformed into single-row network using Tree Sequence Modeling
(TSM). Finally, the single-row routing problem is solved using a
method called Enhanced Simulated Annealing for Single-Row
Routing (ESSR).
Abstract: This paper deals with under actuator dynamic systems such as spring-mass-damper system when the number of control variable is less than the number of state variable. In order to apply optimal control, the controllability must be checked. There are many objective functions to be selected as the goal of the optimal control such as minimum energy, maximum energy and minimum jerk. As the objective function is the first priority, if one like to have the second goal to be applied; however, it could not fit in the objective function format and also avoiding the vector cost for the objective, this paper will illustrate the problem of under actuator dynamic systems with the easiest to deal with comparing between minimum energy and minimum jerk.
Abstract: The analysis of electromagnetic environment using
deterministic mathematical models is characterized by the
impossibility of analyzing a large number of interacting network
stations with a priori unknown parameters, and this is characteristic,
for example, of mobile wireless communication networks. One of the
tasks of the tools used in designing, planning and optimization of
mobile wireless network is to carry out simulation of electromagnetic
environment based on mathematical modelling methods, including
computer experiment, and to estimate its effect on radio
communication devices. This paper proposes the development of a
statistical model of electromagnetic environment of a mobile
wireless communication network by describing the parameters and
factors affecting it including the propagation channel and their
statistical models.
Abstract: This paper proposes an analytical method for the
dynamics of generating firms- alliance networks along with business
phases. Dynamics in network developments have previously been
discussed in the research areas of organizational strategy rather than in
the areas of regional cluster, where the static properties of the
networks are often discussed. The analytical method introduces the
concept of business phases into innovation processes and uses
relationships called prior experiences; this idea was developed in
organizational strategy to investigate the state of networks from the
viewpoints of tradeoffs between link stabilization and node
exploration. This paper also discusses the results of the analytical
method using five cases of the network developments of firms. The
idea of Embeddedness helps interpret the backgrounds of the
analytical results. The analytical method is useful for policymakers of
regional clusters to establish concrete evaluation targets and a
viewpoint for comparisons of policy programs.
Abstract: Bandwidth allocation in wired network is less complex
and to allocate bandwidth in wireless networks is complex and
challenging, due to the mobility of source end system.This paper
proposes a new approach to bandwidth allocation to higher and lower
priority mobile nodes.In our proposal bandwidth allocation to new
mobile node is based on bandwidth utilization of existing mobile
nodes.The first section of the paper focuses on introduction to
bandwidth allocation in wireless networks and presents the existing
solutions available for allocation of bandwidth. The second section
proposes the new solution for the bandwidth allocation to higher and
lower priority nodes. Finally this paper ends with the analytical
evaluation of the proposed solution.
Abstract: Requirements are critical to system validation as they guide all subsequent stages of systems development. Inadequately specified requirements generate systems that require major revisions or cause system failure entirely. Use Cases have become the main vehicle for requirements capture in many current Object Oriented (OO) development methodologies, and a means for developers to communicate with different stakeholders. In this paper we present the results of a laboratory experiment that explored whether different types of use case format are equally effective in facilitating high knowledge user-s understanding. Results showed that the provision of diagrams along with the textual use case descriptions significantly improved user comprehension of system requirements in both familiar and unfamiliar application domains. However, when comparing groups that received models of textual description accompanied with diagrams of different level of details (simple and detailed) we found no significant difference in performance.
Abstract: Housing is a basic human right. The provision of new
house shall be free from any defects, even for the defects that people
do normally considered as 'cosmetic defects'. This paper studies
about the building defects of newly completed house of 72 unit of
double-storey terraced located in Bangi, Selangor. The building
survey implemented using protocol 1 (visual inspection). As for new
house, the survey work is very stringent in determining the defects
condition and priority. Survey and reporting procedure is carried out
based on CSP1 Matrix that involved scoring system, photographs and
plan tagging. The analysis is done using Statistical Package for Social
Sciences (SPSS). The finding reveals that there are 2119 defects
recorded in 72 terraced houses. The cumulative score obtained was
27644 while the overall rating is 13.05. These results indicate that the
construction quality of the newly terraced houses is low and not up to
an acceptable standard as the new house should be.
Abstract: Medical image data hiding has strict constrains such
as high imperceptibility, high capacity and high robustness.
Achieving these three requirements simultaneously is highly
cumbersome. Some works have been reported in the literature on
data hiding, watermarking and stegnography which are suitable for
telemedicine applications. None is reliable in all aspects. Electronic
Patient Report (EPR) data hiding for telemedicine demand it blind
and reversible. This paper proposes a novel approach to blind
reversible data hiding based on integer wavelet transform.
Experimental results shows that this scheme outperforms the prior
arts in terms of zero BER (Bit Error Rate), higher PSNR (Peak Signal
to Noise Ratio), and large EPR data embedding capacity with
WPSNR (Weighted Peak Signal to Noise Ratio) around 53 dB,
compared with the existing reversible data hiding schemes.
Abstract: The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.
Abstract: This study considers priorities of primary goals to increase policy efficiency of Green ICT. Recently several studies have been published that address how IT is linked to climate change. However, most of the previous studies are limited to Green ICT industrial statute and policy directions. This paper present Green ICT
policy making processes systematically. As a result of the analysis of
Korean Green ICT policy, the following emerged as important to accomplish for Green ICT policy: eco-friendliness, technology evolution, economic efficiency, energy efficiency, and stable supply
of energy. This is an initial study analyzing Green ICT policy, which provides an academic framework that can be used a guideline to
establish Green ICT policy.
Abstract: The uses of road map in daily activities are numerous
but it is a hassle to construct and update a road map whenever there
are changes. In Universiti Malaysia Sarawak, research on Automatic
Road Extraction (ARE) was explored to solve the difficulties in
updating road map. The research started with using Satellite Image
(SI), or in short, the ARE-SI project. A Hybrid Simple Colour Space
Segmentation & Edge Detection (Hybrid SCSS-EDGE) algorithm
was developed to extract roads automatically from satellite-taken
images. In order to extract the road network accurately, the satellite
image must be analyzed prior to the extraction process. The
characteristics of these elements are analyzed and consequently the
relationships among them are determined. In this study, the road
regions are extracted based on colour space elements and edge details
of roads. Besides, edge detection method is applied to further filter
out the non-road regions. The extracted road regions are validated by
using a segmentation method. These results are valuable for building
road map and detecting the changes of the existing road database.
The proposed Hybrid Simple Colour Space Segmentation and Edge
Detection (Hybrid SCSS-EDGE) algorithm can perform the tasks
fully automatic, where the user only needs to input a high-resolution
satellite image and wait for the result. Moreover, this system can
work on complex road network and generate the extraction result in
seconds.
Abstract: The work reported in this paper is motivated by the fact that there is a need to apply autonomic computing concepts to parallel computing systems. Advancing on prior work based on intelligent cores [36], a swarm-array computing approach, this paper focuses on 'Intelligent agents' another swarm-array computing approach in which the task to be executed on a parallel computing core is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and is seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed swarm-array computing approach is validated on a multi-agent simulator.
Abstract: This paper presents a novel approach to finding a
priori interesting regions in mammograms. In order to delineate those
regions of interest (ROI-s) in mammograms, which appear to be
prominent, a topographic representation called the iso-level contour
map consisting of iso-level contours at multiple intensity levels and
region segmentation based-thresholding have been proposed. The
simulation results indicate that the computed boundary gives the
detection rate of 99.5% accuracy.