Abstract: In this study, we are interested in the economic lot
scheduling problem (ELSP) that considers manufacturing of the
serviceable products and remanufacturing of the reworked products. In
this paper, we formulate a mathematical model for the ELSP with
reworks using the basic period approach. In order to solve this
problem, we propose a search algorithm to find the cyclic multiplier ki
of each product that can be cyclically produced for every ki basic
periods. This research also uses two heuristics to search for the optimal
production sequence of all lots and the optimal time length of the basic
period so as to minimize the average total cost. This research uses a
numerical example to show the effectiveness of our approach.
Abstract: Least Development Countries (LDC) like
Bangladesh, whose 25% revenue earning is achieved from Textile
export, requires producing less defective textile for minimizing
production cost and time. Inspection processes done on these
industries are mostly manual and time consuming. To reduce error
on identifying fabric defects requires more automotive and
accurate inspection process. Considering this lacking, this research
implements a Textile Defect Recognizer which uses computer
vision methodology with the combination of multi-layer neural
networks to identify four classifications of textile defects. The
recognizer, suitable for LDC countries, identifies the fabric defects
within economical cost and produces less error prone inspection
system in real time. In order to generate input set for the neural
network, primarily the recognizer captures digital fabric images by
image acquisition device and converts the RGB images into binary
images by restoration process and local threshold techniques.
Later, the output of the processed image, the area of the faulty
portion, the number of objects of the image and the sharp factor of
the image, are feed backed as an input layer to the neural network
which uses back propagation algorithm to compute the weighted
factors and generates the desired classifications of defects as an
output.
Abstract: Given a large sparse signal, great wishes are to
reconstruct the signal precisely and accurately from lease number of
measurements as possible as it could. Although this seems possible
by theory, the difficulty is in built an algorithm to perform the
accuracy and efficiency of reconstructing. This paper proposes a new
proved method to reconstruct sparse signal depend on using new
method called Least Support Matching Pursuit (LS-OMP) merge it
with the theory of Partial Knowing Support (PSK) given new method
called Partially Knowing of Least Support Orthogonal Matching
Pursuit (PKLS-OMP).
The new methods depend on the greedy algorithm to compute the
support which depends on the number of iterations. So to make it
faster, the PKLS-OMP adds the idea of partial knowing support of its
algorithm. It shows the efficiency, simplicity, and accuracy to get
back the original signal if the sampling matrix satisfies the Restricted
Isometry Property (RIP).
Simulation results also show that it outperforms many algorithms
especially for compressible signals.
Abstract: This work presents the first results from the long-term experiment, which is focused on the impact of intensive rainfall and long period of drought on microbial activities in soil. Fifteen lysimeters were prepared in the area of our interest. This area is a protection zone of underground source of drinking water. These lysimeters were filed with topsoil and subsoil collected in this area and divided into two groups. These groups differ in fertilization and amount of water received during the growing season. Amount of microbial biomass and leaching of mineral nitrogen and phosphates were chosen as main indicators of microbial activities in soil. Content of mineral nitrogen and phosphates was measured in soil solution, which was collected from each lysimeters. Amount of microbial biomass was determined in soil samples that were taken from the lysimeters before and after the long period of drought and intensive rainfall.
Abstract: In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
Abstract: Nonspecific protein adsorption generally occurs on
any solid surfaces and usually has adverse consequences. Adsorption
of proteins onto a solid surface is believed to be the initial and
controlling step in biofouling. Surfaces modified with end-tethered
poly(ethylene glycol) (PEG) have been shown to be protein-resistant
to some degree. In this study, the adsorption of β-casein and
lysozyme was performed on 6 different types of surfaces where PEG
was tethered onto stainless steel by polyethylene imine (PEI) through
either OH or NHS end groups. Protein adsorption was also performed
on the bare stainless steel surface as a control. The adsorption was
conducted at 23 °C and pH 7.2. In situ QCM-D was used to
determine PEG adsorption kinetics, plateau PEG chain densities,
protein adsorption kinetics and plateau protein adsorbed quantities.
PEG grafting density was the highest for a NHS coupled chain,
around 0.5 chains / nm2. Interestingly, lysozyme which has smaller
size than β-casein, appeared to adsorb much less mass than that of β-
casein. Overall, the surface with high PEG grafting density exhibited
a good protein rejection.
Abstract: The paper applies a discourse analytical approach to investigate important concepts influencing the infrastructure planning process in the region of Scania in southern Sweden. Two discourses, one concerning regional development and one concerning sustainability are identified, discussed and contrasted. It is argued that the perceptions of problems and their suggested solutions related to transportation are based on specific ideas, in turn dependent on the importance given to certain concepts, such as regional enlargement, Scania as a transit region, the national environmental quality goals and regional attractiveness. These concepts, their underlying meaning structures and their relevance for the infrastructure planning process are analyzed. The handling of conflicting interests in the planning process, and the possible implications this may have is also discussed. The results indicate that the regional development discourse is dominant and although the solutions to the problems caused by transport are framed in similar ways in the two discourses a harmonization between conflicting goals is proving difficult to achieve.
Abstract: Due to new distributed database applications such as
huge deductive database systems, the search complexity is constantly
increasing and we need better algorithms to speedup traditional
relational database queries. An optimal dynamic programming
method for such high dimensional queries has the big disadvantage of
its exponential order and thus we are interested in semi-optimal but
faster approaches. In this work we present a multi-agent based
mechanism to meet this demand and also compare the result with
some commonly used query optimization algorithms.
Abstract: Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.
Abstract: There is limited evidence from various countries
about the possible impact of various criteria to be used to determine
the scope of the IFRS for SMEs issued in 2009 and, research is
needed in this area. We provide evidence from Romania, an
emerging economy member of the European Union. The aim of this
paper is to analyze in a local setting if size is a relevant factor for
deciding between local and global standards for SMEs. Our results
indicate that size is a moderate indicator of the existence of possible
users interested in financial statements and that there is a difference
between the scopes of the standard determined on various criteria..
Also, we suggest that the international exposure is quite reduced in
the case of SMEs, but is sufficient to suggest that at least some SMEs
would benefit from international comparability of financial
statements
Abstract: The study of soil for agriculture purposes has
remained the main focus of research since the beginning of civilization as humans- food related requirements remained closely linked with the soil. The study of soil has generated an interest
among the researchers for very similar other reasons including transmission, reflection and refraction of signals for deploying
wireless underground sensor networks or for the monitoring of objects on (or in ) soil in the form of better understanding of soil
electromagnetic characteristics properties. The moisture content has
been very instrumental in such studies as it decides on the resistance of the soil, and hence the attenuation on signals traveling through soil
or the attenuation the signals may suffer upon their impact on soil. This work is related testing and characterizing a measurement circuit
meant for the detection of moisture level content in soil.
Abstract: Nowadays the construction industry is growing specially among developing counties. Iran also has a critical role in these industries in terms of workers disorders. Work-related musculoskeletal disorders (WMSDs) assign 7% of the whole diseases in the society, which make some limitations. One of the main factors, which are ended to WMSDs, is awkward posture. Steel bar bending is considered as one of the prominent performance among construction workers. In this case study we conducted to find the major tasks of bar benders and the most important related risk factors. This study was carried out among twenty workers (18-45 years) as our volunteer samples in some construction sites with less than 6 floors in two regions of Tehran municipality. The data was gathered through in depth observation, interview and questionnaire. Also postural analysis was done by OWAS. In another part of study we used NMQ for gathering some data about psychosocial effects of work related disorders. Our findings show that 64% of workers were not aware of work risks, also about 59% of workers had troubles in their wrists, hands, and especially among workers who worked in steel bar bending. In 46% cases low back pain were prevalence. Considering with gathered data and results, awkward postures and long term tasks and its duration are known as the main risk factors in WMSDs among construction workers, so work-rest schedule and also tools design should be considered to make an ergonomic condition for the mentioned workers.
Abstract: This paper presents a study of laminar to turbulent transition on a profile specifically designed for wind turbine blades, the DU91-W2-250, which belongs to a class of wind turbine dedicated airfoils, developed by Delft University of Technology. A comparison between the experimental behavior of the airfoil studied at Delft wind tunnel and the numerical predictions of the commercial CFD solver ANSYS FLUENT® has been performed. The prediction capabilities of the Spalart-Allmaras turbulence model and of the γ-θ Transitional model have been tested. A sensitivity analysis of the numerical results to the spatial domain discretization has also been performed using four different computational grids, which have been created using the mesher GAMBIT®. The comparison between experimental measurements and CFD results have allowed to determine the importance of the numerical prediction of the laminar to turbulent transition, in order not to overestimate airfoil friction drag due to a fully turbulent-regime flow computation.
Abstract: In many applications there is a broad variety of
information relevant to a focal “object" of interest, and the fusion of such heterogeneous data types is desirable for classification and
categorization. While these various data types can sometimes be treated as orthogonal (such as the hull number, superstructure color,
and speed of an oil tanker), there are instances where the inference and the correlation between quantities can provide improved fusion
capabilities (such as the height, weight, and gender of a person). A
service-oriented architecture has been designed and prototyped to
support the fusion of information for such “object-centric" situations.
It is modular, scalable, and flexible, and designed to support new data sources, fusion algorithms, and computational resources without affecting existing services. The architecture is designed to simplify
the incorporation of legacy systems, support exact and probabilistic entity disambiguation, recognize and utilize multiple types of
uncertainties, and minimize network bandwidth requirements.
Abstract: This research gathered local wisdom towards career building of people in Kamchanoad Community, Baan Muang sub-district, Baan Dung district, Udon Thani province. Data was collected through in-depth interviews with village headmen, community board, teachers, monks, Kamchanoad forest managers and revered elderly aged over 60 years old. All of these 30 interviewees have resided in Kamchanoad Community for more than 40. Descriptive data analysis result revealed that the most prominent local wisdom of Kamchanoad community is their beliefs and religion. Most people in the community have strongly maintained local tradition, the festival of appeasing Chao Pu Sri Suttho on the middle of the 6th month of Thai lunar calendar which falls on the same day with Vesak Day. 100 percent of the people in this community are Buddhist. They believe that Naga, an entity or being, taking the form of a serpent, named “Sri Suttho” lives in Kamchanoad forest. The local people worship the serpent and ask for blessings. Another local wisdom of this community is Sinh fabric weaving.
Abstract: The growing interest on national heritage
preservation has led to intensive efforts on digital documentation of
cultural heritage knowledge. Encapsulated within this effort is the
focus on ontology development that will help facilitate the
organization and retrieval of the knowledge. Ontologies surrounding
cultural heritage domain are related to archives, museum and library
information such as archaeology, artifacts, paintings, etc. The growth
in number and size of ontologies indicates the well acceptance of its
semantic enrichment in many emerging applications. Nowadays,
there are many heritage information systems available for access.
Among others is community-based e-museum designed to support the
digital cultural heritage preservation. This work extends previous
effort of developing the Traditional Malay Textile (TMT) Knowledge
Model where the model is designed with the intention of auxiliary
mapping with CIDOC CRM. Due to its internal constraints, the
model needs to be transformed in advance. This paper addresses the
issue by reviewing the previous harmonization works with CIDOC
CRM as exemplars in refining the facets in the model particularly
involving TMT-Artifact class. The result is an extensible model
which could lead to a common view for automated mapping with
CIDOC CRM. Hence, it promotes integration and exchange of
textile information especially batik-related between communities in
e-museum applications.
Abstract: In elliptic curve theory, number of rational points on
elliptic curves and determination of these points is a fairly important
problem. Let p be a prime and Fp be a finite field and k ∈ Fp. It
is well known that which points the curve y2 = x3 + kx has and
the number of rational points of on Fp. Consider the circle family
x2 + y2 = r2. It can be interesting to determine common points of
these two curve families and to find the number of these common
points. In this work we study this problem.
Abstract: The rapid development of the BlackBerry games industry and its development goals were not just for entertainment, but also used for educational of students interactively. Unfortunately the development of adaptive educational games on BlackBerry in Indonesian language that interesting and entertaining for learning process is very limited. This paper shows the research of development of novel adaptive educational games for students who can adjust the difficulty level of games based on the ability of the user, so that it can motivate students to continue to play these games. We propose a method where these games can adjust the level of difficulty, based on the assessment of the results of previous problems using neural networks with three inputs in the form of percentage correct, the speed of answer and interest mode of games (animation / lessons) and 1 output. The experimental results are presented and show the adaptive games are running well on mobile devices based on BlackBerry platform
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: Suppose KY and KX are large sets of observed and
reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori
information only on few signals, p N, from KX but performs better than the known filters based on a priori information on every
reference signal from KX? It is shown that the positive answer is
achievable under quite unrestrictive assumptions. The device behind
the proposed method is based on a special extension of the piecewise
linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from
the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.