Abstract: This paper addresses a stock-cutting problem with rotation of items and without the guillotine cutting constraint. In order to solve the large-scale problem effectively and efficiently, we propose a simple but fast heuristic algorithm. It is shown that this heuristic outperforms the latest published algorithms for large-scale problem instances.
Abstract: Producing companies aspire to high delivery
availability despite appearing disruptions. To ensure high delivery
availability safety stocksare required. Howeversafety stock leads to
additional capital commitment and compensates disruptions instead
of solving the reasons.The intention is to increase the stability in
production by configuring the production planning and control
systematically. Thus the safety stock can be reduced. The largest
proportion of inventory in producing companies is caused by batch
inventory, schedule deviations and variability of demand rates.These
reasons for high inventory levels can be reduced by configuring the
production planning and control specifically. Hence the inventory
level can be reduced. This is enabled by synchronizing the lot size
straightening the demand as well as optimizing the releasing order,
sequencing and capacity control.
Abstract: In this paper, mathematical models for permutation flow shop scheduling and job shop scheduling problems are proposed. The first problem is based on a mixed integer programming model. As the problem is NP-complete, this model can only be used for smaller instances where an optimal solution can be computed. For large instances, another model is proposed which is suitable for solving the problem by stochastic heuristic methods. For the job shop scheduling problem, a mathematical model and its main representation schemes are presented.
Abstract: In managing healthcare logistics, cost is not the only
factor to be considered. The level of items- criticality used in patient
care services plays an important role as well. A stock-out incident of
a high critical item could threaten a patient's life. In this paper, the
DMAIC (Define-Measure-Analyze-Improve-Control) methodology is
used to drive improvement projects based on customer driven critical
to quality characteristics at a Jordanian hospital. This paper shows
how the application of Six Sigma improves the performance of the
case hospital logistics system by reducing the number of stock-out
incidents.
Abstract: In 2011, Debiao et al. pointed out that S-3PAKE protocol proposed by Lu and Cao for password-authenticated key exchange in the three-party setting is vulnerable to an off-line dictionary attack. Then, they proposed some countermeasures to eliminate the security vulnerability of the S-3PAKE. Nevertheless, this paper points out their enhanced S-3PAKE protocol is still vulnerable to undetectable on-line dictionary attacks unlike their claim.
Abstract: Proteins or genes that have similar sequences are likely to perform the same function. One of the most widely used techniques for sequence comparison is sequence alignment. Sequence alignment allows mismatches and insertion/deletion, which represents biological mutations. Sequence alignment is usually performed only on two sequences. Multiple sequence alignment, is a natural extension of two-sequence alignment. In multiple sequence alignment, the emphasis is to find optimal alignment for a group of sequences. Several applicable techniques were observed in this research, from traditional method such as dynamic programming to the extend of widely used stochastic optimization method such as Genetic Algorithms (GAs) and Simulated Annealing. A framework with combination of Genetic Algorithm and Simulated Annealing is presented to solve Multiple Sequence Alignment problem. The Genetic Algorithm phase will try to find new region of solution while Simulated Annealing can be considered as an alignment improver for any near optimal solution produced by GAs.
Abstract: Speckled images arise when coherent microwave,
optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar
systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted
by speckle noise is complicated by the nature of the noise and is not
as straightforward as detection and estimation in additive noise. In
this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The
motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this
context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series
of Laguerre weighted exponential functions, resulting in a doubly
stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form.
It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an
exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.
Abstract: Wireless sensor networks (WSN) consists of many
sensor nodes that are placed on unattended environments such as
military sites in order to collect important information.
Implementing a secure protocol that can prevent forwarding forged
data and modifying content of aggregated data and has low delay
and overhead of communication, computing and storage is very
important. This paper presents a new protocol for concealed data
aggregation (CDA). In this protocol, the network is divided to
virtual cells, nodes within each cell produce a shared key to send
and receive of concealed data with each other. Considering to data
aggregation in each cell is locally and implementing a secure
authentication mechanism, data aggregation delay is very low and
producing false data in the network by malicious nodes is not
possible. To evaluate the performance of our proposed protocol, we
have presented computational models that show the performance
and low overhead in our protocol.
Abstract: Knowledge-based e-mail systems focus on
incorporating knowledge management approach in order to enhance
the traditional e-mail systems. In this paper, we present a knowledgebased
e-mail system called KS-Mail where people do not only send
and receive e-mail conventionally but are also able to create a sense
of knowledge flow. We introduce semantic processing on the e-mail
contents by automatically assigning categories and providing links to
semantically related e-mails. This is done to enrich the knowledge
value of each e-mail as well as to ease the organization of the e-mails
and their contents. At the application level, we have also built
components like the service manager, evaluation engine and search
engine to handle the e-mail processes efficiently by providing the
means to share and reuse knowledge. For this purpose, we present the
KS-Mail architecture, and elaborate on the details of the e-mail
server and the application server. We present the ontology mapping
technique used to achieve the e-mail content-s categorization as well
as the protocols that we have developed to handle the transactions in
the e-mail system. Finally, we discuss further on the implementation
of the modules presented in the KS-Mail architecture.
Abstract: This paper presents a comparative study of Ant Colony and Genetic Algorithms for VLSI circuit bi-partitioning. Ant colony optimization is an optimization method based on behaviour of social insects [27] whereas Genetic algorithm is an evolutionary optimization technique based on Darwinian Theory of natural evolution and its concept of survival of the fittest [19]. Both the methods are stochastic in nature and have been successfully applied to solve many Non Polynomial hard problems. Results obtained show that Genetic algorithms out perform Ant Colony optimization technique when tested on the VLSI circuit bi-partitioning problem.
Abstract: Mobile adhoc network (MANET) is a collection of
mobile devices which form a communication network with no preexisting
wiring or infrastructure. Multiple routing protocols have
been developed for MANETs. As MANETs gain popularity, their
need to support real time applications is growing as well. Such
applications have stringent quality of service (QoS) requirements
such as throughput, end-to-end delay, and energy. Due to dynamic
topology and bandwidth constraint supporting QoS is a challenging
task. QoS aware routing is an important building block for QoS
support. The primary goal of the QoS aware protocol is to determine
the path from source to destination that satisfies the QoS
requirements. This paper proposes a new energy and delay aware
protocol called energy and delay aware TORA (EDTORA) based on
extension of Temporally Ordered Routing Protocol (TORA).Energy
and delay verifications of query packet have been done in each node.
Simulation results show that the proposed protocol has a higher
performance than TORA in terms of network lifetime, packet
delivery ratio and end-to-end delay.
Abstract: The psychological well-being of a family is a subjective matter for evaluation, all the more when it involves the element of religions, whether Islam, Christianity, Buddhism or Hinduism. Each of these religions emphasises similar values and morals on family psychological well-being. This comparative study is specifically to determine the role of religion on family psychological well-being in Pekan district, Pahang, Malaysia. The study adopts a quantitative and qualitative mixed method design and considers a total of 412 samples of parents and children for the quantitative study, and 21 samples for the qualitative study. The quantitative study uses simple random sampling, whereas the qualitative sampling is purposive. The instrument for quantitative study is Ryff’s Psychological Well-being Scale and the qualitative study involves the construction of a guidelines protocol for in-depth interviews of respondents. The quantitative study uses the SPSS version .19 with One Way Anova, and the qualitative analysis is manual based on transcripts with specific codes and themes. The results show nonsignificance, that is, no significant difference among religions in all family psychological well-being constructs in the comparison of Islam, Christianity, Buddhism and Hinduism, thereby accepting a null hypothesis and rejecting an alternative hypothesis. The qualitative study supports the quantitative study, that is, all 21 respondents explain that no difference exists in psychological wellbeing in the comparison of teachings in all the religious mentioned. These implications may be used as guidelines for government and non-government bodies in considering religion as an important element in family psychological well-being in the long run.
Abstract: This paper presents the automated methods employed
for extracting craniofacial landmarks in white light images as part of
a registration framework designed to support three neurosurgical
procedures. The intraoperative space is characterised by white light
stereo imaging while the preoperative plan is performed on CT scans.
The registration aims at aligning these two modalities to provide a
calibrated environment to enable image-guided solutions. The
neurosurgical procedures can then be carried out by mapping the
entry and target points from CT space onto the patient-s space. The
registration basis adopted consists of natural landmarks (eye corner
and ear tragus). A 5mm accuracy is deemed sufficient for these three
procedures and the validity of the selected registration basis in
achieving this accuracy has been assessed by simulation studies. The
registration protocol is briefly described, followed by a presentation
of the automated techniques developed for the extraction of the
craniofacial features and results obtained from tests on the AR and
FERET databases. Since the three targeted neurosurgical procedures
are routinely used for head injury management, the effect of
bruised/swollen faces on the automated algorithms is assessed. A
user-interactive method is proposed to deal with such unpredictable
circumstances.
Abstract: This article combines two techniques: data
envelopment analysis (DEA) and Factor analysis (FA) to data
reduction in decision making units (DMU). Data envelopment
analysis (DEA), a popular linear programming technique is useful to
rate comparatively operational efficiency of decision making units
(DMU) based on their deterministic (not necessarily stochastic)
input–output data and factor analysis techniques, have been proposed
as data reduction and classification technique, which can be applied
in data envelopment analysis (DEA) technique for reduction input –
output data. Numerical results reveal that the new approach shows a
good consistency in ranking with DEA.
Abstract: Mobile ad hoc network is a collection of mobile
nodes communicating through wireless channels without any
existing network infrastructure or centralized administration.
Because of the limited transmission range of wireless network
interfaces, multiple "hops" may be needed to exchange data
across the network. Consequently, many routing algorithms
have come into existence to satisfy the needs of
communications in such networks. Researchers have
conducted many simulations comparing the performance of
these routing protocols under various conditions and
constraints. One question that arises is whether speed of nodes
affects the relative performance of routing protocols being
studied. This paper addresses the question by simulating two
routing protocols AODV and DSDV. Protocols were
simulated using the ns-2 and were compared in terms of
packet delivery fraction, normalized routing load and average
delay, while varying number of nodes, and speed.
Abstract: This study explored the relationship between
psychological traits, demographics and financial behavioral biases for
individual investors in Taiwan stock market. By using questionnaire
survey method conducted in 2010, there are 554 valid convenient
samples collected to examine the determinants of three types of
behavioral biases. Based on literature review, two hypothesized
models are constructed and further used to evaluate the effects of big
five personality traits and demographic variables on investment biases
through Structural Equation Model (SEM) analysis. The results
showed that investment biases of individual investors are significantly
related to four personality traits as well as some demographics.
Abstract: The antioxidant capability of beverage blends made from cocoa, zobo and ginger with standard antioxidant assay procedures was investigated. The DPPH (2,2-diphenyl-1- picrylhydrazyl) scavenging capacity ranged from 21.2-25.8% in comparison with GSH of 37.1%. The ferric reducing ability was highest in the zobo drink and lowest in ginger. The superoxide scavenging capacity was also highest in the zobo drink followed by the drink with alkalized cocoa. The metal chelating power decreased as the level of zobo in the blends decreases. The chelating power of zobo and ginger were significantly lower than the natural and alkalized cocoa. The 100% zobo drink inhibited linoleic acid till the fifth day while natural and alkalized cocoa as well as the blend with 50% alkalized cocoa inhibited linoleic acid greatly till the sixth day. The finding describes the potential health benefit of the phytochemical antioxidants of cocoa:zobo:ginger beverage blends.
Abstract: In this paper a combination approach of two heuristic-based algorithms: genetic algorithm and tabu search is proposed. It has been developed to obtain the least cost based on the split-pipe design of looped water distribution network. The proposed combination algorithm has been applied to solve the three well-known water distribution networks taken from the literature. The development of the combination of these two heuristic-based algorithms for optimization is aimed at enhancing their strengths and compensating their weaknesses. Tabu search is rather systematic and deterministic that uses adaptive memory in search process, while genetic algorithm is probabilistic and stochastic optimization technique in which the solution space is explored by generating candidate solutions. Split-pipe design may not be realistic in practice but in optimization purpose, optimal solutions are always achieved with split-pipe design. The solutions obtained in this study have proved that the least cost solutions obtained from the split-pipe design are always better than those obtained from the single pipe design. The results obtained from the combination approach show its ability and effectiveness to solve combinatorial optimization problems. The solutions obtained are very satisfactory and high quality in which the solutions of two networks are found to be the lowest-cost solutions yet presented in the literature. The concept of combination approach proposed in this study is expected to contribute some useful benefits in diverse problems.
Abstract: The paper is concerned with the existence of solution
of nonlinear second order neutral stochastic differential inclusions
with infinite delay in a Hilbert Space. Sufficient conditions for the
existence are obtained by using a fixed point theorem for condensing
maps.
Abstract: In this work, a characterization and modeling of
packet loss of a Voice over Internet Protocol (VoIP) communication
is developed. The distributions of the number of consecutive received
and lost packets (namely gap and burst) are modeled from the
transition probabilities of two-state and four-state model.
Measurements show that both models describe adequately the burst
distribution, but the decay of gap distribution for non-homogeneous
losses is better fit by the four-state model. The respective
probabilities of transition between states for each model were
estimated with a proposed algorithm from a set of monitored VoIP
calls in order to obtain representative minimum, maximum and
average values for both models.