Abstract: Seasonal variability of nutrients concentration in the Baltic Sea using the 3D ecosystem numerical model 3D-CEMBS has been investigated. Additionally this study shows horizontal and vertical distribution of nutrients in the Baltic Sea. Model domain is an extended Baltic Sea area divided into 600x640 horizontal grid cells. Aside from standard hydrodynamic parameters 3D-CEMBS produces modeled ecological variables such as: three types of phytoplankton, two detrital classes, dissolved oxygen and the nutrients (nitrate, ammonium, phosphate and silicate). The presented model allows prediction of parameters that describe distribution of nutrients concentration and phytoplankton biomass. 3D-CEMBS can be used to study the effect of different hydrodynamic and biogeochemical processes on distributions of these variables in a larger scale.
Abstract: In this paper, Land Marks for Unique Addressing( LMUA) algorithm is develped to generate unique ID for each and every node which leads to the formation of overlapping/Non overlapping clusters based on unique ID. To overcome the draw back of the developed LMUA algorithm, the concept of clustering is introduced. Based on the clustering concept a Land Marks for Unique Addressing and Clustering(LMUAC) Algorithm is developed to construct strictly non-overlapping clusters and classify those nodes in to Cluster Heads, Member Nodes, Gate way nodes and generating the Hierarchical code for the cluster heads to operate in the level one hierarchy for wireless communication switching. The expansion of the existing network can be performed or not without modifying the cost of adding the clusterhead is shown. The developed algorithm shows one way of efficiently constructing the
Abstract: The identification and classification of weeds are of
major technical and economical importance in the agricultural
industry. To automate these activities, like in shape, color and
texture, weed control system is feasible. The goal of this paper is to
build a real-time, machine vision weed control system that can detect
weed locations. In order to accomplish this objective, a real-time
robotic system is developed to identify and locate outdoor plants
using machine vision technology and pattern recognition. The
algorithm is developed to classify images into broad and narrow class
for real-time selective herbicide application. The developed
algorithm has been tested on weeds at various locations, which have
shown that the algorithm to be very effectiveness in weed
identification. Further the results show a very reliable performance
on weeds under varying field conditions. The analysis of the results
shows over 90 percent classification accuracy over 140 sample
images (broad and narrow) with 70 samples from each category of
weeds.
Abstract: Distributed denial-of-service (DDoS) attacks pose a
serious threat to network security. There have been a lot of
methodologies and tools devised to detect DDoS attacks and reduce
the damage they cause. Still, most of the methods cannot
simultaneously achieve (1) efficient detection with a small number of
false alarms and (2) real-time transfer of packets. Here, we introduce
a method for proactive detection of DDoS attacks, by classifying the
network status, to be utilized in the detection stage of the proposed
anti-DDoS framework. Initially, we analyse the DDoS architecture
and obtain details of its phases. Then, we investigate the procedures
of DDoS attacks and select variables based on these features. Finally,
we apply the k-nearest neighbour (k-NN) method to classify the
network status into each phase of DDoS attack. The simulation result
showed that each phase of the attack scenario is classified well and
we could detect DDoS attack in the early stage.
Abstract: In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.
Abstract: The globe Sustainability has become the subject of international attention, the key reason is that global climate change. Climate and disasters around the abnormal frequency multiplier, the global temperature of the catastrophe and disaster continue to occur throughout the world, as well as countries around the world. Currently there are many important international conferences and policy, it is a "global environmental sustainability " and "living human health " as the goal of development, including the APEC 2007 meeting to "climate Clean Energy" as the theme Sydney Declaration, 2008 World Economic Forum's "Carbon - promote Cool Earth energy efficiency improvement project", the EU proposed "Green Idea" program, the Japanese annual policy, "low-carbon society, sustainable eco-city environment (Eco City) "And from 2009 to 2010 to promote the "Eco-Point" to promote green energy and carbon reduction products .And the 2010 World Climate Change Conference (COP16 United Nations Climate Change Conference Copenhagen), the world has been the subject of Negative conservative "Environmental Protection ", "save energy consumption, " into a positive response to the "Sustainable " and" LOHAS", while Taiwan has actively put forward eco-cities, green building, green building materials and other related environmental response Measures, especially green building construction environment that is the basis of factors, the most widely used application level, and direct contact with human health and the key to sustainable planet. "Sustainable development "is a necessary condition for continuation of the Earth, "healthy and comfortable" is a necessary condition for the continuation of life, and improve the "quality" is a necessary condition for economic development, balance between the three is "to enhance the efficiency of ", According to the World Business Council for Sustainable Development (WBCSD) for the "environmental efficiency "(Eco-Efficiency) proposed: " the achievement of environmental efficiency, the price to be competitive in the provision of goods or services to meet people's needs, improve living Quality at the same time, the goods or services throughout the life cycle. Its impact on the environment and natural resource utilization and gradually reduced to the extent the Earth can load. "whichever is the economy "Economic" and " Ecologic". The research into the methodology to obtain the Taiwan Green Building Material Labeling product as the scope of the study, by investigating and weight analysis to explore green building environmental load (Ln) factor and the Green Building Quality (Qn) factor to Establish green building environmental efficiency assessment model (GBM Eco-Efficiency). And building materials for healthy green label products for priority assessment object, the object is set in the material evidence for the direct response to the environmental load from the floor class-based, explicit feedback correction to the Green Building environmental efficiency assessment model, "efficiency " as a starting point to achieve balance between human "health "and Earth "sustainable development of win-win strategy. The study is expected to reach 1.To establish green building materials and the quality of environmental impact assessment system, 2. To establish value of GBM Eco-Efficiency model, 3. To establish the GBM Eco-Efficiency model for application of green building material feedback mechanisms.
Abstract: This paper takes the actual scene of Aletheia
University campus – the Class 2 national monument, the first
educational institute in northern Taiwan as an example, to present a
3D virtual navigation system which supports user positioning and
pre-download mechanism. The proposed system was designed based
on the principle of Voronoi Diagra) to divide the virtual scenes and
its multimedia information, which combining outdoor GPS
positioning and the indoor RFID location detecting function. When
users carry mobile equipments such as notebook computer, UMPC,
EeePC...etc., walking around the actual scenes of indoor and outdoor
areas of campus, this system can automatically detect the moving
path of users and pre-download the needed data so that users will
have a smooth and seamless navigation without waiting.
Abstract: Fractional Fourier Transform is a powerful tool,
which is a generalization of the classical Fourier Transform. This
paper provides a mathematical relation relating the span in Fractional
Fourier domain with the amplitude and phase functions of the signal,
which is further used to study the variation of quality factor with
different values of the transform order. It is seen that with the
increase in the number of transients in the signal, the deviation of
average Fractional Fourier span from the frequency bandwidth
increases. Also, with the increase in the transient nature of the signal,
the optimum value of transform order can be estimated based on the
quality factor variation, and this value is found to be very close to
that for which one can obtain the most compact representation. With
the entire mathematical analysis and experimentation, we consolidate
the fact that Fractional Fourier Transform gives more optimal
representations for a number of transform orders than Fourier
transform.
Abstract: 17α-ethinylestradiol (EE2) is a recalcitrant micropollutant which is found in small amounts in municipal wastewater. But these small amounts still adversely affect for the reproductive function of aquatic organisms. Evidence in the past suggested that full-scale WWTPs equipped with nitrification process enhanced the removal of EE2 in the municipal wastewater. EE2 has been proven to be able to be transformed by ammonia oxidizing bacteria (AOB) via co-metabolism. This research aims to clarify the EE2 degradation pattern by different consortium of ammonia oxidizing microorganism (AOM) including AOA (ammonia oxidizing archaea) and investigate contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM. The result showed that AOA or AOB of N. oligotropha cluster in enriched nitrifying activated sludge (NAS) from 2mM and 5mM, commonly found in municipal WWTPs, could degrade EE2 in wastewater via co-metabolism. Moreover, the investigation of the contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM demonstrated that the new synthesized AMO enzyme may perform ammonia oxidation rather than the existing AMO enzyme or the existing AMO enzyme may has a small amount to oxidize ammonia.
Abstract: Mobile Picture Puzzle is a mobile game application where the player use existing images stored in the mobile phone to create a puzzle to be played. This traditional picture puzzle is not so challenging once the player is familiar with the game. The objective of the developed mobile game application is to have a similar mobile game application that can provide the player with more challenging gaming experience. The developed mobile game application is also a mobile picture puzzle game application to create a puzzle to be played but instead of just using existing images that are stored, the personalised capability allows the player to use the built-in camera phone to capture an image and use the newly captured image to create the puzzle. The development of the mobile game application uses Symbian Operating System (OS), Mobile Media API (Application Programming Interface), Record Management System (RMS) storage and TiledLayer class from Game API.
Abstract: Many digital signal processing, techniques have been used to automatically distinguish protein coding regions (exons) from non-coding regions (introns) in DNA sequences. In this work, we have characterized these sequences according to their nonlinear dynamical features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our model to a number of real sequences encoded into a time series using EIIP sequence indicators. In order to discriminate between coding and non coding DNA regions, the phase space trajectory was first reconstructed for coding and non-coding regions. Nonlinear dynamical features are extracted from those regions and used to investigate a difference between them. Our results indicate that the nonlinear dynamical characteristics have yielded significant differences between coding (CR) and non-coding regions (NCR) in DNA sequences. Finally, the classifier is tested on real genes where coding and non-coding regions are well known.
Abstract: The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.
Abstract: A new approach for protection of power transformer is
presented using a time-frequency transform known as Wavelet transform.
Different operating conditions such as inrush, Normal, load,
External fault and internal fault current are sampled and processed
to obtain wavelet coefficients. Different Operating conditions provide
variation in wavelet coefficients. Features like energy and Standard
deviation are calculated using Parsevals theorem. These features
are used as inputs to PNN (Probabilistic neural network) for fault
classification. The proposed algorithm provides more accurate results
even in the presence of noise inputs and accurately identifies inrush
and fault currents. Overall classification accuracy of the proposed
method is found to be 96.45%. Simulation of the fault (with and
without noise) was done using MATLAB AND SIMULINK software
taking 2 cycles of data window (40 m sec) containing 800 samples.
The algorithm was evaluated by using 10 % Gaussian white noise.
Abstract: Telemedicine is brought to life by contemporary changes of our world and summarizes the entire range of services that are at the crossroad of traditional healthcare and information technology. It is believed that eHealth can help in solving critical issues of rising costs, care for ageing and housebound population, staff shortage. It is a feasible tool to provide routine as well as specialized health service as it has the potential to improve both the access to and the standard of care. eHealth is no more an optional choice. It has already made quite a way but it still remains a fantastic challenge for the future requiring cooperation and coordination at all possible levels. The strategic objectives of this paper are: 1. To start with an attempt to clarify the mass of terms used nowadays; 2. To answer the question “Who needs eHealth"; 3. To focus on the necessity of bridging telemedicine and medical (health) informatics as well as on the dual relationship between them; as well as 4. To underline the need of networking in understanding, developing and implementing eHealth.
Abstract: A laboratory study on the influence of compactive
effort on expansive black cotton specimens treated with up to 8%
ordinary Portland cement (OPC) admixed with up to 8% bagasse ash
(BA) by dry weight of soil and compacted using the energies of the
standard Proctor (SP), West African Standard (WAS) or
“intermediate” and modified Proctor (MP) were undertaken. The
expansive black cotton soil was classified as A-7-6 (16) or CL using
the American Association of Highway and Transportation Officials
(AASHTO) and Unified Soil Classification System (USCS),
respectively. The 7day unconfined compressive strength (UCS)
values of the natural soil for SP, WAS and MP compactive efforts are
286, 401 and 515kN/m2 respectively, while peak values of 1019,
1328 and 1420kN/m2 recorded at 8% OPC/ 6% BA, 8% OPC/ 2% BA
and 6% OPC/ 4% BA treatments, respectively were less than the
UCS value of 1710kN/m2 conventionally used as criterion for
adequate cement stabilization. The soaked California bearing ratio
(CBR) values of the OPC/BA stabilized soil increased with higher
energy level from 2, 4 and 10% for the natural soil to Peak values of
55, 18 and 8% were recorded at 8% OPC/4% BA 8% OPC/2% BA
and 8% OPC/4% BA, treatments when SP, WAS and MP compactive
effort were used, respectively. The durability of specimens was
determined by immersion in water. Soils treatment at 8% OPC/ 4%
BA blend gave a value of 50% resistance to loss in strength value
which is acceptable because of the harsh test condition of 7 days
soaking period specimens were subjected instead of the 4 days
soaking period that specified a minimum resistance to loss in strength
of 80%. Finally An optimal blend of is 8% OPC/ 4% BA is
recommended for treatment of expansive black cotton soil for use as
a sub-base material.
Abstract: Rapid growth of distance learning resulted in
importance to conduct research on students- satisfaction with distance
learning because differences in students- satisfaction might influence
educational opportunities for learning in a relevant Web-based
environment. In line with this, this paper deals with satisfaction of
students with distance module at Faculty of organizational sciences
(FOS) in Serbia as well as some factors affecting differences in their
satisfaction . We have conducted a research on a population of 68
first-year students of distance learning studies at FOS. Using
statistical techniques, we have found out that there is no significant
difference in students- satisfaction with distance learning module
between men and women. In the same way, we also concluded that
there is a difference in satisfaction with distance learning module
regarding to student-s perception of opportunity to gain knowledge as
the classic students.
Abstract: Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.
Abstract: To overcome the product overload of Internet
shoppers, we introduce a semantic recommendation procedure which
is more efficient when applied to Internet shopping malls. The
suggested procedure recommends the semantic products to the
customers and is originally based on Web usage mining, product
classification, association rule mining, and frequently purchasing.
We applied the procedure to the data set of MovieLens Company for
performance evaluation, and some experimental results are provided.
The experimental results have shown superior performance in
terms of coverage and precision.
Abstract: Implicit equations play a crucial role in Engineering.
Based on this importance, several techniques have been applied to
solve this particular class of equations. When it comes to practical
applications, in general, iterative procedures are taken into account.
On the other hand, with the improvement of computers, other
numerical methods have been developed to provide a more
straightforward methodology of solution. Analytical exact approaches
seem to have been continuously neglected due to the difficulty
inherent in their application; notwithstanding, they are indispensable
to validate numerical routines. Lagrange-s Inversion Theorem is a
simple mathematical tool which has proved to be widely applicable to
engineering problems. In short, it provides the solution to implicit
equations by means of an infinite series. To show the validity of this
method, the tree-parameter infiltration equation is, for the first time,
analytically and exactly solved. After manipulating these series,
closed-form solutions are presented as H-functions.
Abstract: Facial recognition and expression analysis is rapidly
becoming an area of intense interest in computer science and humancomputer
interaction design communities. The most expressive way
humans display emotions is through facial expressions. In this paper
skin and non-skin pixels were separated. Face regions were extracted
from the detected skin regions. Facial expressions are analyzed from
facial images by applying Gabor wavelet transform (GWT) and
Discrete Cosine Transform (DCT) on face images. Radial Basis
Function (RBF) Network is used to identify the person and to classify
the facial expressions. Our method reliably works even with faces,
which carry heavy expressions.