Abstract: This paper presents three models which enable the
customisation of Universal Description, Discovery and Integration
(UDDI) query results, based on some pre-defined and/or real-time
changing parameters. These proposed models detail the requirements,
design and techniques which make ranking of Web service discovery
results from a service registry possible. Our contribution is two fold:
First, we present an extension to the UDDI inquiry capabilities. This
enables a private UDDI registry owner to customise or rank the query
results, based on its business requirements. Second, our proposal
utilises existing technologies and standards which require minimal
changes to existing UDDI interfaces or its data structures. We believe
these models will serve as valuable reference for enhancing the
service discovery methods within a private UDDI registry
environment.
Abstract: This paper discusses the theory behind the existence of an idealistic model for business network governance and uses a clarifying case-study, containing governance structures and processes within a business network framework. The case study from a German pharmaceutical industry company complements existing literature by providing a comprehensive explanation of the relations between supply chains and business networks, and also between supply chain management and business network governance. Supply chains and supply chain management are only one side of the interorganizational relationships and ensure short-term performance, while real-world governance structures are needed for ensuring the long-term existence of a supply chain. Within this context, a comprehensive model for business governance is presented. An interesting finding from the case study is that multiple business network governance systems co-exist within the evaluated supply chain.
Abstract: Seaweed farming is emerging as a viable alternative
activity in the Indonesian fisheries sector. This paper aims to
investigate people-s perceptions of seaweed farming, to analyze its
social and economic impacts and to identify the problems and
obstacles hindering its continued development. Structured and
semi-structured questionnaires were prepared to obtain qualitative
data, and interviews were conducted with fishermen who also plant
seaweed. The findings showed that fishermen in the Laikang Bay were
enthusiastic about cultivating seaweeds and that seaweed plays a major
role in supporting the household economy of fishermen. However,
current seaweed drying technologies cannot support increased
seaweed production on a farm or plot, especially in the rainy season.
Additionally, variable monsoon seasons and long marketing channels
are still major constraints on the development of the industry. Finally,
capture fisheries, the primary economic livelihood of fishermen of
older generations, is being slowly replaced by seaweed farming.
Abstract: Knowledge Discovery of Databases (KDD) is the
process of extracting previously unknown but useful and significant
information from large massive volume of databases. Data Mining is
a stage in the entire process of KDD which applies an algorithm to
extract interesting patterns. Usually, such algorithms generate huge
volume of patterns. These patterns have to be evaluated by using
interestingness measures to reflect the user requirements.
Interestingness is defined in different ways, (i) Objective measures
(ii) Subjective measures. Objective measures such as support and
confidence extract meaningful patterns based on the structure of the
patterns, while subjective measures such as unexpectedness and
novelty reflect the user perspective. In this report, we try to brief the
more widely spread and successful subjective measures and propose
a new subjective measure of interestingness, i.e. shocking.
Abstract: LDPC codes could be used in magnetic storage devices because of their better decoding performance compared to other error correction codes. However, their hardware implementation results in large and complex decoders. This one of the main obstacles the decoders to be incorporated in magnetic storage devices. We construct small high girth and rate 2 columnweight codes from cage graphs. Though these codes have low performance compared to higher column weight codes, they are easier to implement. The ease of implementation makes them more suitable for applications such as magnetic recording. Cages are the smallest known regular distance graphs, which give us the smallest known column-weight 2 codes given the size, girth and rate of the code.
Abstract: Abstract— The paper presents a preliminary study on modeling and estimation of basic wind speed ( extreme wind gusts ) for the consideration of vulnerability and design of building in Ayeyarwady Region. The establishment of appropriate design wind speeds is a critical step towards the calculation of design wind loads for structures. In this paper the extreme value analysis of this prediction work is based on the anemometer data (1970-2009) maintained by the department of meteorology and hydrology of Pathein. Statistical and probabilistic approaches are used to derive formulas for estimating 3-second gusts from recorded data (10-minute sustained mean wind speeds).
Abstract: A feed-forward, back-propagation Artificial Neural
Network (ANN) model has been used to forecast the occurrences of
wastewater overflows in a combined sewerage reticulation system.
This approach was tested to evaluate its applicability as a method
alternative to the common practice of developing a complete
conceptual, mathematical hydrological-hydraulic model for the
sewerage system to enable such forecasts. The ANN approach
obviates the need for a-priori understanding and representation of the
underlying hydrological hydraulic phenomena in mathematical terms
but enables learning the characteristics of a sewer overflow from the
historical data.
The performance of the standard feed-forward, back-propagation
of error algorithm was enhanced by a modified data normalizing
technique that enabled the ANN model to extrapolate into the
territory that was unseen by the training data. The algorithm and the
data normalizing method are presented along with the ANN model
output results that indicate a good accuracy in the forecasted sewer
overflow rates. However, it was revealed that the accurate
forecasting of the overflow rates are heavily dependent on the
availability of a real-time flow monitoring at the overflow structure
to provide antecedent flow rate data. The ability of the ANN to
forecast the overflow rates without the antecedent flow rates (as is
the case with traditional conceptual reticulation models) was found to
be quite poor.
Abstract: The evolution of technology and construction techniques has enabled the upgrading of transport networks. In particular, the high-speed rail networks allow convoys to peak at above 300 km/h. These structures, however, often significantly impact the surrounding environment. Among the effects of greater importance are the ones provoked by the soundwave connected to train transit. The wave propagation affects the quality of life in areas surrounding the tracks, often for several hundred metres. There are substantial damages to properties (buildings and land), in terms of market depreciation. The present study, integrating expertise in acoustics, computering and evaluation fields, outlines a useful model to select project paths so as to minimize the noise impact and reduce the causes of possible litigation. It also facilitates the rational selection of initiatives to contain the environmental damage to the already existing railway tracks. The research is developed with reference to the Italian regulatory framework (usually more stringent than European and international standards) and refers to a case study concerning the high speed network in Italy.
Abstract: In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the
kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental treestructure
algorithm. Then, by using this method, we obtained 3
distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes
prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes prediction horizon are presented.
At the end, we detect these faults in validation data. The data collected from White Saveh Cement Company is used for in this study.
Abstract: Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting patterns according to some measures, from databases. It is of vital importance to define good measures of interestingness that would allow the system to discover only the useful patterns. Measures of interestingness are divided into objective and subjective measures. Objective measures are those that depend only on the structure of a pattern and which can be quantified by using statistical methods. While, subjective measures depend only on the subjectivity and understandability of the user who examine the patterns. These subjective measures are further divided into actionable, unexpected and novel. The key issues that faces data mining community is how to make actions on the basis of discovered knowledge. For a pattern to be actionable, the user subjectivity is captured by providing his/her background knowledge about domain. Here, we consider the actionability of the discovered knowledge as a measure of interestingness and raise important issues which need to be addressed to discover actionable knowledge.
Abstract: In this paper, we first introduce the model of games on augmenting systems with a coalition structure, which can be seen as an extension of games on augmenting systems. The core of games on augmenting systems with a coalition structure is defined, and an equivalent form is discussed. Meantime, the Shapley function for this type of games is given, and two axiomatic systems of the given Shapley function are researched. When the given games are quasi convex, the relationship between the core and the Shapley function is discussed, which does coincide as in classical case. Finally, a numerical example is given.
Abstract: The systematic manipulations of shapes and sizes of
inorganic compounds greatly benefit the various application fields
including optics, magnetic, electronics, catalysis and medicine.
However shape control has been much more difficult to achieve.
Hence exploration of novel method for the preparation of differently
shaped nanoparticles is challenging research area. II-VI group of
semiconductor cadmium sulphide (CdS) nanostructure with different
morphologies (such as, acicular like, mesoporous, spherical shapes)
and of crystallite sizes vary from 11 to 16 nm were successfully
synthesized by chemical aqueous precipitation of Cd2+ ions with
homogeneously released S2- ions from decomposition of cadmium
sulphate (CdSO4) and thioacetamide (CH3CSNH2) by annealing at
different radiations (microwave, ultrasonic and sunlight) with matter
and systematic research has been done for various factors affecting
the controlled growth rate of CdS nanoparticles. The obtained
nanomaterials have been characterized by X-ray Diffraction (XRD),
Fourier Transform Infrared Spectroscopy (FTIR),
Thermogravometric (DSC-TGA) analysis and Scanning Electron
Microscopy (SEM). The result indicates that on increasing the
reaction time particle size increases but on increasing the molar ratios
grain size decreases.
Abstract: Primary studies are being carried out in Turkey for
expanding information and communication technologies (ICT) aided instruction activities. Subject of the present study is to identify
whether those studies achieved their goals in the application. Information technologies (IT) formative teachers in the primary
schools, and academicians in the faculties of education were interviewed to investigate the process and results of implementing
computer-aided instruction methods whose basis is strengthened in theory. Analysis of the results gained from two separate surveys
demonstrated that capability of the teachers in elementary education institutions for carrying into effect computer-aided instruction and
technical infrastructure has not been established for computer-aided instruction practices yet. Prospective teachers must be well-equipped in ICT to duly fulfill requirements of modern education and also
must be self-confident. Finally, scope and intensity of the courses given in connection with teaching of the ICT in faculties of education needs to be revised.
Abstract: This study was conducted published to investigate
there liability of the equation pressure-impulse (PI) reinforced
concrete column inprevious studies. Equation involves three different
levels of damage criteria known as D =0. 2, D =0. 5 and D =0. 8.The
damage criteria known as a minor when 0-0.2, 0.2-0.5is known as
moderate damage, high damage known as 0.5-0.8, and 0.8-1 of the
structure is considered a failure. In this study, two types of reliability
analyzes conducted. First, using pressure-impulse equation with
different parameters. The parameters involved are the concrete
strength, depth, width, and height column, the ratio of longitudinal
reinforcement and transverse reinforcement ratio. In the first analysis
of the reliability of this new equation is derived to improve the
previous equations. The second reliability analysis involves three
types of columns used to derive the PI curve diagram using the
derived equation to compare with the equation derived from other
researchers and graph minimum standoff versus weapon yield
Federal Emergency Management Agency (FEMA). The results
showed that the derived equation is more accurate with FEMA
standards than previous researchers.
Abstract: The Internet has become an indispensable part of our lives. Witnessing recent web-based mass collaboration, e.g. Wikipedia, people are questioning whether the Internet has made fundamental changes to the society or whether it is merely a hyperbolic fad. It has long been assumed that collective action for a certain goal yields the problem of free-riding, due to its non-exclusive and non-rival characteristics. Then, thanks to recent technological advances, the on-line space experienced the following changes that enabled it to produce public goods: 1) decrease in the cost of production or coordination 2) externality from networked structure 3) production function which integrates both self-interest and altruism. However, this research doubts the homogeneity of on-line mass collaboration and argues that a more sophisticated and systematical approach is required. The alternative that we suggest is to connect the characteristics of the goal to the motivation. Despite various approaches, previous literature fails to recognize that motivation can be structurally restricted by the characteristic of the goal. First we draw a typology of on-line mass collaboration with 'the extent of expected beneficiary' and 'the existence of externality', and then we examine each combination of motivation using Benkler-s framework. Finally, we explore and connect such typology with its possible dominant participating motivation.
Abstract: Numerous concrete structures projects are currently running in Libya as part of a US$50 billion government funding. The
quality of concrete used in 20 different construction projects were assessed based mainly on the concrete compressive strength achieved. The projects are scattered all over the country and are at
various levels of completeness. For most of these projects, the
concrete compressive strength was obtained from test results of a
150mm standard cube mold. Statistical analysis of collected concrete
compressive strengths reveals that the data in general followed a
normal distribution pattern. The study covers comparison and assessment of concrete quality aspects such as: quality control, strength range, data standard deviation, data scatter, and ratio of minimum strength to design strength. Site quality control for these projects ranged from very good to poor according to ACI214 criteria [1]. The ranges (Rg) of the strength (max. strength – min. strength) divided by average strength are from (34% to 160%). Data scatter is
measured as the range (Rg) divided by standard deviation () and is
found to be (1.82 to 11.04), indicating that the range is ±3σ.
International construction companies working in Libya follow
different assessment criteria for concrete compressive strength in lieu
of national unified procedure. The study reveals that assessments of
concrete quality conducted by these construction companies usually
meet their adopted (internal) standards, but sometimes fail to meet
internationally known standard requirements. The assessment of
concrete presented in this paper is based on ACI, British standards
and proposed Libyan concrete strength assessment criteria.
Abstract: In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.
Abstract: Multi-loop (De-centralized) Proportional-Integral-
Derivative (PID) controllers have been used extensively in process
industries due to their simple structure for control of multivariable
processes. The objective of this work is to design multiple-model
adaptive multi-loop PID strategy (Multiple Model Adaptive-PID)
and neural network based multi-loop PID strategy (Neural Net
Adaptive-PID) for the control of multivariable system. The first
method combines the output of multiple linear PID controllers,
each describing process dynamics at a specific level of operation.
The global output is an interpolation of the individual multi-loop
PID controller outputs weighted based on the current value of the
measured process variable. In the second method, neural network
is used to calculate the PID controller parameters based on the
scheduling variable that corresponds to major shift in the process
dynamics. The proposed control schemes are simple in structure with
less computational complexity. The effectiveness of the proposed
control schemes have been demonstrated on the CSTR process,
which exhibits dynamic non-linearity.
Abstract: TiO2/MgO composite films were prepared by coating
the magnesium acetate solution in the pores of mesoporous TiO2
films using a dip coating method. Concentrations of magnesium
acetate solution were varied in a range of 1x10-4 – 1x10-1 M. The
TiO2/MgO composite films were characterized by scanning electron
microscopy (SEM), transmission electron microscropy (TEM),
electrochemical impedance spectroscopy(EIS) , transient voltage
decay and I-V test. The TiO2 films and TiO2/MgO composite films
were immersed in a 0.3 mM N719 dye solution. The Dye-sensitized
solar cells with the TiO2/MgO/N719 structure showed an optimal
concentration of magnesium acetate solution of 1x10-3 M resulting in
the MgO film estimated thickness of 0.0963 nm and giving the
maximum efficiency of 4.85%. The improved efficiency of dyesensitized
solar cell was due to the magnesium oxide film as the wide
band gap coating decays the electron back transfer to the triiodide
electrolyte and reduce charge recombination.
Abstract: Perhaps no single issue has been cited as either the root
cause and / or the greatest challenge to the restructured power system then the lack of adequate reliable transmission. Probabilistic transmission planning has become increasingly necessary and important in recent
years. The transmission planning analysis carried out by the authors,
spans a 10-year horizon, taking into consideration a value of 2 % load
increase / year at each consumer. Taking into consideration this increased
load, a probabilistic power flow was carried out, all the system components
being regarded from probabilistic point of view. Several contingencies
have been generated, for assessing the security of the power system. The results have been analyzed and several important conclusions were pointed. The objective is to achieve a network that works without limit violations for all (or most of) scenario realizations. The case study is represented by the IEEE 14 buses test power system.