Abstract: This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.
Abstract: A pilot project was carried out in 2007 by the senior
students of Cyprus International University, aiming to minimize the
total cost of waste collection in Northern Cyprus. Many developed
and developing countries have cut their transportation costs – which
lies between 30-40% – down at a rate of 40% percent, by
implementing network models for their route assignments.
Accordingly, a network model was implemented at Göçmenköy
district, to optimize and standardize waste collection works. The
work environment of the employees were also redesigned to provide
maximum ergonomy and to increase productivity, efficiency and
safety. Following the collection of the required data including waste
densities, lengths of roads and population, a model was constructed
to allocate the optimal route assignment for the waste collection
trucks at Göçmenköy district.
Abstract: Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.
Abstract: Two-phase frictional pressure drop data were
obtained for condensation of carbon dioxide in single horizontal
micro tube of inner diameter ranged from 0.6 mm up to 1.6 mm over
mass flow rates from 2.5*10-5 to 17*10-5 kg/s and vapor qualities
from 0.0 to 1.0. The inlet condensing pressure is changed from 33.5
to 45 bars. The saturation temperature ranged from -1.5 oC up to 10
oC. These data have then been compared against three (two-phase)
frictional pressure drop prediction methods. The first method is by
Muller-Steinhagen and Heck (Muller-Steinhagen H, Heck K. A
simple friction pressure drop correlation for two-phase flow in pipes.
Chem. Eng. Process 1986;20:297–308) and that by Gronnerud R.
Investigation of liquid hold-up, flow-resistance and heat transfer in
circulation type evaporators, part IV: two-phase flow resistance in
boiling refrigerants, Annexe 1972. Then the method used by
FriedelL. Improved friction pressures drop in horizontal and vertical
two-phase pipe flow. European Two-Phase Flow Group Meeting,
Paper E2; 1979 June, Ispra, Italy. The methods are used by M.B Ould
Didi et al (2001) “Prediction of two-phase pressure gradients of
refrigerant in horizontal tubes". Int.J.of Refrigeration 25(2002) 935-
947. The best available method for annular flow was that of Muller-
Steinhagen and Heck. It was observed that the peak in the two-phase
frictional pressure gradient is at high vapor qualities.
Abstract: The Neuro-Fuzzy hybridization scheme has become
of research interest in pattern classification over the past decade. The
present paper proposes a novel Modified Adaptive Fuzzy Inference
Engine (MAFIE) for pattern classification. A modified Apriori
algorithm technique is utilized to reduce a minimal set of decision
rules based on input output data sets. A TSK type fuzzy inference
system is constructed by the automatic generation of membership
functions and rules by the fuzzy c-means clustering and Apriori
algorithm technique, respectively. The generated adaptive fuzzy
inference engine is adjusted by the least-squares fit and a conjugate
gradient descent algorithm towards better performance with a
minimal set of rules. The proposed MAFIE is able to reduce the
number of rules which increases exponentially when more input
variables are involved. The performance of the proposed MAFIE is
compared with other existing applications of pattern classification
schemes using Fisher-s Iris and Wisconsin breast cancer data sets and
shown to be very competitive.
Abstract: This paper explores the scalability issues associated
with solving the Named Entity Recognition (NER) problem using
Support Vector Machines (SVM) and high-dimensional features. The
performance results of a set of experiments conducted using binary
and multi-class SVM with increasing training data sizes are
examined. The NER domain chosen for these experiments is the
biomedical publications domain, especially selected due to its
importance and inherent challenges. A simple machine learning
approach is used that eliminates prior language knowledge such as
part-of-speech or noun phrase tagging thereby allowing for its
applicability across languages. No domain-specific knowledge is
included. The accuracy measures achieved are comparable to those
obtained using more complex approaches, which constitutes a
motivation to investigate ways to improve the scalability of multiclass
SVM in order to make the solution more practical and useable.
Improving training time of multi-class SVM would make support
vector machines a more viable and practical machine learning
solution for real-world problems with large datasets. An initial
prototype results in great improvement of the training time at the
expense of memory requirements.
Abstract: Data warehousing success is not high enough. User
dissatisfaction and failure to adhere to time frames and budgets are
too common. Most traditional information systems practices are
rooted in hard systems thinking. Today, the great systems thinkers
are forgotten by information systems developers. A data warehouse
is still a system and it is worth investigating whether systems
thinkers such as Churchman can enhance our practices today. This
paper investigates data warehouse development practices from a
systems thinking perspective. An empirical investigation is done in
order to understand the everyday practices of data warehousing
professionals from a systems perspective. The paper presents a
model for the application of Churchman-s systems approach in data
warehouse development.
Abstract: Dynamic location referencing method is an important technology to shield map differences. These method references objects of the road network by utilizing condensed selection of its real-world geographic properties stored in a digital map database, which overcomes the defections existing in pre-coded location referencing methods. The high attributes completeness requirements and complicated reference point selection algorithm are the main problems of recent researches. Therefore, a dynamic location referencing algorithm combining intersection points selected at the extremities compulsively and road link points selected according to link partition principle was proposed. An experimental system based on this theory was implemented. The tests using Beijing digital map database showed satisfied results and thus verified the feasibility and practicability of this method.
Abstract: There have been many variations of technologies that helped educators in teaching & learning. From the past research it is evident that Information Technology significantly increases student participation and interactivity in the classrooms. This research started with a aim to find whether adoption of Wi-Fi environment by Malaysian Higher Educational Institutions (HEI) can benefit students and staff equally. The study was carried out in HEI-s of Klang Valley, Malaysia and the data is gathered through paper based surveys. A sample size of 237 units were randomly selected from 5 higher educational institutions in the Klang Valley using the Stratified Random sampling method and from the analysis of the data, it was found that the implementation of wireless technologies in HEIs have created lot of opportunities and also challenges.
Abstract: This work has been conducted to study on comfort level of drivers of suspended cabin tractor semitrailer. Some drivers suffer from low back pain caused by vibration. The practical significance of applying suspended cabin type of tractor semi trailer was tested at different road conditions, different speed as well as different load conditions for comfortable driver seat interface (x, y, z ) and the process parameters have been prioritized using Taguchi-s L27 orthogonal array. Genetic Algorithm (GA) is used to optimize the human comfort vibration of suspended cabin tractor semitrailer drivers. The practical significance of applying GA to human comfort to reaction of suspended cabin tractor semitrailer has been validated by means of computing the deviation between predicted and experimentally obtained human comfort to vibration. The optimized acceleration data indicate a little uncomfortable ride for suspended cabin tractor semitrailer.
Abstract: This paper presents a new approach for the protection
of Thyristor-Controlled Series Compensator (TCSC) line using
Support Vector Machine (SVM). One SVM is trained for fault
classification and another for section identification. This method use
three phase current measurement that results in better speed and
accuracy than other SVM based methods which used single phase
current measurement. This makes it suitable for real-time protection.
The method was tested on 10,000 data instances with a very wide
variation in system conditions such as compensation level, source
impedance, location of fault, fault inception angle, load angle at
source bus and fault resistance. The proposed method requires only
local current measurement.
Abstract: This paper deals with the status of solid waste pollution in touristic spots of North coastal Andhra Pradesh. Case studies of Eco tourism, cultural tourism and pilgrim tourism are elaborately discussed and the study is based on both primary and secondary data. Data collection includes field collection of solid waste, semi structured interviews and observation of tourists. Results indicate generation of 72% Non biodegradable material in Eco touristic places like RK beach Visakhapatnam, Araku Valley. Pydithalli Jathra is a famous cultural touristic attraction and more than one lakh people converge here. The solid waste at this spot includes 20% coconut shells, 50% plastic bottles and covers, 20% Banana peelings and remaining are food materials. Radhasapthami is the most important festival celebrated at famous sun temple Arasavalli of Srikakulam. Here solid waste includes 50% water bottles, plastic covers, 10% papers, 10% hair, 30% left out food material and Banana peelings.
Abstract: In a chirp spread spectrum (CSS) system, the overlap
technique is used for increasing bit rate. More overlaps can offer
higher data throughput; however, they may cause more intersymbol
interference (ISI) at the same time, resulting in serious bit error
rate (BER) performance degradation. In this paper, we perform the
BER analysis and derive a closed form BER expression for the
overlap-based CSS system. The derived BER expression includes
the number of overlaps as a parameter, and thus, would be very
useful in determining the number of overlaps for a specified BER.
The numerical results demonstrate that the BER derived in a closed
form closely agrees with the simulated BER.
Abstract: With the demand of mobility by users, wireless
technologies have become the hotspot developing arena. Internet
Engineering Task Force (IETF) working group has developed Mobile
IP to support node mobility. The concept of node mobility indicates
that in spite of the movement of the node, it is still connected to the
internet and all the data transactions are preserved. It provides
location-independent access to Internet. After the incorporation of
host mobility, network mobility has undergone intense research.
There are several intricacies faced in the real world implementation
of network mobility significantly the problem of nested networks and
their consequences. This article is concerned regarding a problem of
nested network called pinball route problem and proposes a solution
to eliminate the above problem. The proposed mechanism is
implemented using NS2 simulation tool and it is found that the
proposed mechanism efficiently reduces the overload caused by the
pinball route problem.
Abstract: A Decision Support System/Expert System for stock
portfolio selection presented where at first step, both technical and
fundamental data used to estimate technical and fundamental return
and risk (1st phase); Then, the estimated values are aggregated with
the investor preferences (2nd phase) to produce convenient stock
portfolio.
In the 1st phase, there are two expert systems, each of which is
responsible for technical or fundamental estimation. In the technical
expert system, for each stock, twenty seven candidates are identified
and with using rough sets-based clustering method (RC) the effective
variables have been selected. Next, for each stock two fuzzy rulebases
are developed with fuzzy C-Mean method and Takai-Sugeno-
Kang (TSK) approach; one for return estimation and the other for
risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation
method. In parallel, for fundamental expert systems,
fuzzy rule-bases have been identified in the form of “IF-THEN" rules
through brainstorming with the stock market experts and the input
data have been derived from financial statements; as a result two
fuzzy rule-bases have been generated for all the stocks, one for return
and the other for risk.
In the 2nd phase, user preferences represented by four criteria and
are obtained by questionnaire. Using an expert system, four estimated
values of return and risk have been aggregated with the respective
values of user preference. At last, a fuzzy rule base having four rules,
treats these values and produce a ranking score for each stock which
will lead to a satisfactory portfolio for the user.
The stocks of six manufacturing companies and the period of
2003-2006 selected for data gathering.
Abstract: Over recent years, the number of building integrated photovoltaic (BIPV) installations for home systems have been increasing in Malaysia. The paper concerns an analysis - as part of current Research and Development (R&D) efforts - to integrate photovoltaics as an architectural feature of a detached house in the new satellite township of Putrajaya, Malaysia. The analysis was undertaken using calculation and simulation tools to optimize performance of BIPV home system. In this study, a the simulation analysis was undertaken for selected bungalow units based on a long term recorded weather data for city of Kuala Lumpur. The simulation and calculation was done with consideration of a PV panels' tilt and direction, shading effect and economical considerations. A simulation of the performance of a grid connected BIPV house in Kuala Lumpur was undertaken. This case study uses a 60 PV modules with power output of 2.7 kW giving an average of PV electricity output is 255 kWh/month..
Abstract: The critical period for weed control (CPWC) is the period in the crop growth cycle during which weeds must be controlled to prevent unacceptable yield losses. Field studies were conducted in 2005 and 2006 in the University of Birjand at the south east of Iran to determine CPWC of corn using a randomized complete block design with 14 treatments and four replications. The treatments consisted of two different periods of weed interference, a critical weed-free period and a critical time of weed removal, were imposed at V3, V6, V9, V12, V15, and R1 (based on phonological stages of corn development) with a weedy check and a weed-free check. The CPWC was determined with the use of 2.5, 5, 10, 15 and 20% acceptable yield loss levels by non-linear Regression method and fitting Logistic and Gompertz nonlinear equations to relative yield data. The CPWC of corn was from 5- to 15-leaf stage (19-55 DAE) to prevent yield losses of 5%. This period to prevent yield losses of 2.5, 10 and 20% was 4- to 17-leaf stage (14-59 DAE), 6- to 12-leaf stage (25-47 DAE) and 8- to 9-leaf stage (31-36 DAE) respectively. The height and leaf area index of corn were significantly decreased by weed competition in both weed free and weed infested treatments (P
Abstract: The RANS method with Saffman-s turbulence model
was employed to solve the time-dependent turbulent Navier-Stokes
and energy equations for oscillating pipe flows. The method of
partial sums of the Fourier series is used to analyze the harmonic
velocity and temperature results. The complete structures of the
oscillating pipe flows and the averaged Nusselt numbers on the tube
wall are provided by numerical simulation over wide ranges of ReA
and ReR. Present numerical code is validated by comparing the
laminar flow results to analytic solutions and turbulence flow results
to published experimental data at lower and higher Reynolds
numbers respectively. The effects of ReA and ReR on the velocity,
temperature and Nusselt number distributions have been di scussed.
The enhancement of the heat transfer due to oscillating flows has
also been presented. By the way of analyzing the overall Nusselt
number over wide ranges of the Reynolds number Re and Keulegan-
Carpenter number KC, the optimal ratio of the tube diameter over
the oscillation amplitude is obtained based on the existence of a
nearly constant optimal KC number. The potential application of the
present results in sea water cooling has also been discussed.
Abstract: The flow field over a flat roof model building has been numerically investigated in order to determine threedimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data. Wind tunnel measurements and numerical predictions have been compared for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions. The proposed calculations have allowed the development of a preliminary procedure to be used as guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a three-dimensional roof architecture dominated by flow separation.
Abstract: The winding hot-spot temperature is one of the most
critical parameters that affect the useful life of the power
transformers. The winding hot-spot temperature can be calculated as
function of the top-oil temperature that can estimated by using the
ambient temperature and transformer loading measured data. This
paper proposes the estimation of the top-oil temperature by using a
method based on Least Squares Support Vector Machines approach.
The estimated top-oil temperature is compared with measured data of
a power transformer in operation. The results are also compared with
methods based on the IEEE Standard C57.91-1995/2000 and
Artificial Neural Networks. It is shown that the Least Squares
Support Vector Machines approach presents better performance than
the methods based in the IEEE Standard C57.91-1995/2000 and
artificial neural networks.