Abstract: The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.
Abstract: Intelligent Transportation System integrates various modern advanced technologies into the ground transportation system, and it will be the goal of urban transport system in the future because of its comprehensive effects. However, it also brings some problems, such as project performance assessment, fairness of benefiting groups, fund management, which are directly related to its operation and implementation. Wuhan has difficulties in organizing transportation because of its nature feature (river and lake), therefore, calling Service of Taxi plays an important role in transportation. This paper researches on calling Service of Taxi in Wuhan, based on quantitative and qualitative analysis. It analyzes its operations management systematically, including business model, finance, usage analysis and users evaluation. As for business model, it is that the government leads the operation at the initial stage, and the third part dominates the operation at the mature stage, which not only eases the pressure of the third part and benefits the spread of the calling service at the initial stage, but also alleviates financial pressure of government and improve the efficiency of the operation at the mature stage. As for finance, it draws that this service will bring heavy financial burden of equipments, but it will be alleviated in the future because of its spread. As for usage analysis, through data comparison, this service can bring some benefits for taxi drivers, and time and spatial distribution of usage have certain features. As for user evaluation, it analyzes using group and the reason why choosing it. At last, according to the analysis above, the paper puts forward the potentials, limitations, and future development strategies for it.
Abstract: The future of business intelligence (BI) is to integrate
intelligence into operational systems that works in real-time
analyzing small chunks of data based on requirements on continuous
basis. This is moving away from traditional approach of doing
analysis on ad-hoc basis or sporadically in passive and off-line mode
analyzing huge amount data. Various AI techniques such as expert
systems, case-based reasoning, neural-networks play important role
in building business intelligent systems. Since BI involves various
tasks and models various types of problems, hybrid intelligent
techniques can be better choice. Intelligent systems accessible
through web services make it easier to integrate them into existing
operational systems to add intelligence in every business processes.
These can be built to be invoked in modular and distributed way to
work in real time. Functionality of such systems can be extended to
get external inputs compatible with formats like RSS. In this paper,
we describe a framework that use effective combinations of these
techniques, accessible through web services and work in real-time.
We have successfully developed various prototype systems and done
few commercial deployments in the area of personalization and
recommendation on mobile and websites.
Abstract: Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and Real- Coded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters. The performance of the designed supplementary TCSC-based damping controller is tested on a weakly connected power system with different disturbances and loading conditions with parameter variations. Simulation results are presented and compared with a conventional power system stabilizer and also with the TCSC-based supplementary controller when the controller parameters are not optimized to show the effectiveness and robustness of the proposed approach over a wide range of loading conditions and disturbances.
Abstract: Essential hypertension (HTN) usually clusters with other cardiovascular risk factors such as age, overweight, diabetes, insulin resistance and dyslipidemia. The target organ damage (TOD) such as left ventricular hypertrophy, microalbuminuria (MA), acute coronary syndrome (ACS), stroke and cognitive dysfunction takes place early in course of hypertension. Though the prevalence of hypertension is high in India, the relationship between microalbuminuria and target organ damage in hypertension is not well studied. This study aim at detecting MA in essential hypertension and its relation to severity of HTN, duration of HTN, body mass index (BMI), age and TOD such as HTN retinopathy and acute coronary syndrome The present study was done in 100 patients of essential hypertension non diabetics admitted to B.L.D.E.University-s Sri B.M.Patil Medical College, Bijapur, from October 2008 to April 2011. The patients underwent detailed history and clinical examination. Early morning 5 ml of urine sample was collected & MA was estimated by immunoturbidometry method. The relationship of MA with the duration & severity of HTN, BMI, age, sex and TOD's like hypertensive retinopathy, ACS was assessed by univariate analysis. The prevalence of MA in this study was found to be 63 %. In that 42% were male & 21% were female. In this study a significant association between MA and the duration of hypertension (p = 0.036) & (OR =0.438). Longer the duration of hypertension, more possibility of microalbumin in urine. Also there was a significant association between severity of hypertension and MA (p=0.045) and (OR=0.093). MA was positive in 50 (79.4%) patients out of 63, whose blood pressure was >160/100 mm Hg. In this study a significant association between MA and the grades of hypertensive retinopathy (p =0.011) and acute coronary syndrome (p = 0.041) (OR =2.805). Gender and BMI did not pose high risk for MA in this study.The prevalence of MA in essential hypertension is high in this part of the community and MA will increase the risk of developing target organ damage.Early screening of patients with essential hypertension for MA and aggressive management of positive cases might reduce the burden of chronic kidney diseases and cardiovascular diseases in the community.
Abstract: Recently, web services to access from many type devices
are often used. We have developed the shortest path planning
system called "Bus-Net" in Tottori prefecture as a web application
to sustain the public transport. And it used the same user interface
for both devices. To support both devices, the interface cannot use
JavaScript and so on.
Thus, we developed the method that use individual user interface
for each device type to improve its convenience. To be concrete,
we defined formats of condition input to the path planning system
and result output from it and separate the system into the request
processing part and user interface parts that depend on device types.
By this method, we have also developed special device for Bus-Net
named "Intelligent-Bus-Stop".
Abstract: This paper features the modeling and design of a
Robust Decentralized Fast Output Sampling (RDFOS) Feedback
control technique for the active vibration control of a smart flexible
multimodel Euler-Bernoulli cantilever beams for a multivariable
(MIMO) case by retaining the first 6 vibratory modes. The beam
structure is modeled in state space form using the concept of
piezoelectric theory, the Euler-Bernoulli beam theory and the Finite
Element Method (FEM) technique by dividing the beam into 4 finite
elements and placing the piezoelectric sensor / actuator at two finite
element locations (positions 2 and 4) as collocated pairs, i.e., as
surface mounted sensor / actuator, thus giving rise to a multivariable
model of the smart structure plant with two inputs and two outputs.
Five such multivariable models are obtained by varying the
dimensions (aspect ratios) of the aluminium beam. Using model
order reduction technique, the reduced order model of the higher
order system is obtained based on dominant Eigen value retention
and the Davison technique. RDFOS feedback controllers are
designed for the above 5 multivariable-multimodel plant. The closed
loop responses with the RDFOS feedback gain and the magnitudes of
the control input are obtained and the performance of the proposed
multimodel smart structure system is evaluated for vibration control.
Abstract: This study was carried out to reveal the bacterial composition of aerosol in the studied abattoirs. Bacteria isolated were characterized according to microbiological standards. Factors such as temperature and distance were considered as variable in this study. The isolation was carried out at different temperatures such as 27oC, 31oC and 29oC and at various distances of 100meters and 200meters away from the slaughter sites. Result obtained showed that strains of Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Lactobacillus alimentarius and Micrococcus sp. were identified. The total viable counts showed that more microorganisms were present in the morning while the least viable count of 388cfu was recorded in the evening period of this study. This study also showed that more microbial loads were recorded the further the distance is to the slaughter site. Conclusively, the array of bacteria isolated suggests that abattoir sites may be a potential source of pathogenic organisms to commuters if located within residential environment.
Abstract: This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.
Abstract: Indian subcontinent has a plethora of traditional
medicine systems that provide promising solutions to lifestyle
disorders in an 'all natural way'. Spices and oilseeds hold
prominence in Indian cuisine hence the focus of the current study
was to evaluate the bioactive molecules from Linum usitatissinum
(LU), Lepidium sativum (LS), Nigella sativa (NS) and Guizotia
abyssinica (GA) seeds. The seeds were characterized for functional
lipids like omega-3 fatty acid, antioxidant capacity, phenolic
compounds, dietary fiber and anti-nutritional factors. Analysis of the
seeds revealed LU and LS to be a rich source of α-linolenic acid
(41.85 ± 0.33%, 26.71 ± 0.63%), an omega 3 fatty acid (using
GCMS). While studying antioxidant potential NS seeds demonstrated
highest antioxidant ability (61.68 ± 0.21 TEAC/ 100 gm DW) due to
the presence of phenolics and terpenes as assayed by the Mass
spectral analysis. When screened for anti-nutritional factor
cyanogenic glycoside, LS seeds showed content as high as 1674 ± 54
mg HCN / kg. GA is a probable good source of a stable vegetable oil
(SFA: PUFA 1:2.3). The seeds showed diversified bioactive profile
and hence further studies to use different bio molecules in tandem for
the development of a possible 'nutraceutical cocktail' have been
initiated..
Abstract: The most common domestic birds live in Turkey are: crows (Corvus corone), pigeons (Columba livia), sparrows (Passer domesticus), starlings (Sturnus vulgaris) and blackbirds (Turdus merula). These birds give damage to the agricultural areas and make dirty the human life areas. In order to send away these birds, some different materials and methods such as chemicals, treatments, colored lights, flash and audible scarers are used. It is possible to see many studies about chemical methods in the literatures. However there is not enough works regarding audible bird scarers are reported in the literature. Therefore, a solar powered bird scarer was designed, manufactured and tested in this experimental investigation. Firstly, to understand the sensitive level of these domestic birds against to the audible scarer, many series preliminary studies were conducted. These studies showed that crows are the most resistant against to the audible bird scarer when compared with pigeons, sparrows, starlings and blackbirds. Therefore the solar powered audible bird scarer was tested on crows. The scarer was tested about one month during April- May, 2007. 18 different common known predators- sounds (voices or calls) of domestic birds from Falcon (Falco eleonorae), Falcon (Buteo lagopus), Eagle (Aquila chrysaetos), Montagu-s harrier (Circus pygargus) and Owl (Glaucidium passerinum) were selected for test of the scarer. It was seen from the results that the reaction of the birds was changed depending on the predators- sound type, camouflage of the scarer, sound quality and volume, loudspeaker play and pause periods in one application. In addition, it was also seen that the sound from Falcon (Buteo lagopus) was most effective on crows and the scarer was enough efficient.
Abstract: Radio Frequency Identification (RFID) system is
looked upon as one of the top ten important technologies in the 20th
century and find its applications in many fields such as car industry.
The intelligent cars are one important part of this industry and always
try to find new and satisfied intelligent cars. The purpose of this
paper is to introduce an intelligent car with the based of RFID. By
storing the moving control commands such as turn right, turn left,
speed up and speed down etc. into the RFID tags beforehand and
sticking the tags on the tracks Car can read the moving control
commands from the tags and accomplish the proper actions.
Abstract: A new approach is adopted in this paper based
on Turk and Pentland-s eigenface method. It was found that the
probability density function of the distance between the projection
vector of the input face image and the average projection vector of
the subject in the face database, follows Rayleigh distribution. In
order to decrease the false acceptance rate and increase the
recognition rate, the input face image has been recognized using two
thresholds including the acceptance threshold and the rejection
threshold. We also find out that the value of two thresholds will be
close to each other as number of trials increases. During the training,
in order to reduce the number of trials, the projection vectors for each
subject has been averaged. The recognition experiments using the
proposed algorithm show that the recognition rate achieves to
92.875% whilst the average number of judgment is only 2.56 times.
Abstract: In this paper, we propose a Connect6 solver which
adopts a hybrid approach based on a tree-search algorithm and image
processing techniques. The solver must deal with the complicated
computation and provide high performance in order to make real-time
decisions. The proposed approach enables the solver to be
implemented on a single Spartan-6 XC6SLX45 FPGA produced by
XILINX without using any external devices. The compact
implementation is achieved through image processing techniques to
optimize a tree-search algorithm of the Connect6 game. The tree
search is widely used in computer games and the optimal search brings
the best move in every turn of a computer game. Thus, many
tree-search algorithms such as Minimax algorithm and artificial
intelligence approaches have been widely proposed in this field.
However, there is one fundamental problem in this area; the
computation time increases rapidly in response to the growth of the
game tree. It means the larger the game tree is, the bigger the circuit
size is because of their highly parallel computation characteristics.
Here, this paper aims to reduce the size of a Connect6 game tree using
image processing techniques and its position symmetric property. The
proposed solver is composed of four computational modules: a
two-dimensional checkmate strategy checker, a template matching
module, a skilful-line predictor, and a next-move selector. These
modules work well together in selecting next moves from some
candidates and the total amount of their circuits is small. The details of
the hardware design for an FPGA implementation are described and
the performance of this design is also shown in this paper.
Abstract: On one hand, SNMP (Simple Network Management
Protocol) allows integrating different enterprise elements connected
through Internet into a standardized remote management. On the
other hand, as a consequence of the success of Intelligent Houses
they can be connected through Internet now by means of a residential
gateway according to a common standard called OSGi (Open
Services Gateway initiative). Due to the specifics of OSGi Service
Platforms and their dynamic nature, specific design criterions should
be defined to implement SNMP Agents for OSGi in order to integrate
them into the SNMP remote management. Based on the analysis of
the relation between both standards (SNMP and OSGi), this paper
shows how OSGi Service Platforms can be included into the SNMP
management of a global enterprise, giving implementation details
about an SNMP Agent solution and the definition of a new MIB
(Management Information Base) for managing OSGi platforms that
takes into account the specifics and dynamic nature of OSGi.
Abstract: In this paper a new fast simplification method is
presented. Such method realizes Karnough map with large
number of variables. In order to accelerate the operation of the
proposed method, a new approach for fast detection of group
of ones is presented. Such approach implemented in the
frequency domain. The search operation relies on performing
cross correlation in the frequency domain rather than time one.
It is proved mathematically and practically that the number of
computation steps required for the presented method is less
than that needed by conventional cross correlation. Simulation
results using MATLAB confirm the theoretical computations.
Furthermore, a powerful solution for realization of complex
functions is given. The simplified functions are implemented
by using a new desigen for neural networks. Neural networks
are used because they are fault tolerance and as a result they
can recognize signals even with noise or distortion. This is
very useful for logic functions used in data and computer
communications. Moreover, the implemented functions are
realized with minimum amount of components. This is done
by using modular neural nets (MNNs) that divide the input
space into several homogenous regions. Such approach is
applied to implement XOR function, 16 logic functions on one
bit level, and 2-bit digital multiplier. Compared to previous
non- modular designs, a clear reduction in the order of
computations and hardware requirements is achieved.
Abstract: Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.
Abstract: In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.
Abstract: This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.
Abstract: We present a BeeBot, Binus Multi-client Intelligent Telepresence Robot, a custom-build robot system specifically designed for teleconference with multiple person using omni directional actuator. The robot is controlled using a computer networks, so the manager/supervisor can direct the robot to the intended person to start a discussion/inspection. People tracking and autonomous navigation are intelligent features of this robot. We build a web application for controlling the multi-client telepresence robot and open-source teleconference system used. Experimental result presented and we evaluated its performance.