Abstract: In order to answer the general question: “What does a simple agent with a limited life-time require for constructing a useful representation of the environment?" we propose a robot platform including the simplest probabilistic sensory and motor layers. Then we use the platform as a test-bed for evaluation of the navigational capabilities of the robot with different “brains". We claim that a protocognitive behavior is not a consequence of highly sophisticated sensory–motor organs but instead emerges through an increment of the internal complexity and reutilization of the minimal sensory information. We show that the most fundamental robot element, the short-time memory, is essential in obstacle avoidance. However, in the simplest conditions of no obstacles the straightforward memoryless robot is usually superior. We also demonstrate how a low level action planning, involving essentially nonlinear dynamics, provides a considerable gain to the robot performance dynamically changing the robot strategy. Still, however, for very short life time the brainless robot is superior. Accordingly we suggest that small organisms (or agents) with short life-time does not require complex brains and even can benefit from simple brain-like (reflex) structures. To some extend this may mean that controlling blocks of modern robots are too complicated comparative to their life-time and mechanical abilities.
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.
Abstract: Malaysia government had been trying hard in order to
find the most efficient methods in learning. However, it is hard to
actually access and evaluate students whom will then be called an
excellent student. It is because in our realties student who excellent
is only excel in academic. This evaluation becomes a problem
because it not balances in our real life interm of to get an excellent
student in whole area in their involvement of curiculum and cocuriculum.
To overcome this scenario, we designed a module for
Student Idol to evaluate student through three categories which are
academic, co-curiculum and leadership. All the categories have their
own merit point. Using this method, student will be evaluated more
accurate compared to the previously. So, teacher can easily evaluate
their student without having any emotion factor, relation factor and
others. As conclusion this system module will helps the development
of student evaluation more accurate and valid in Student Idol.
Abstract: Since the last two decades, container transportation
system has been faced under increasing development. This fact
shows the importance of container transportation system as a key role
of container terminals to link between sea and land. Therefore, there
is a continuous need for the optimal use of equipment and facilities in
the ports. Regarding the complex structure of container ports, this
paper presents a simulation model that compares tow storage
strategies for storing containers in the yard. For this purpose, we
considered loading and unloading norm as an important criterion to
evaluate the performance of Shahid Rajaee container port. By
analysing the results of the model, it will be shown that using
marshalling yard policy instead of current storage system has a
significant effect on the performance level of the port and can
increase the loading and unloading norm up to 14%.
Abstract: The problems associated with wind predictions of
WAsP model in complex terrain are already the target of several
studies in the last decade. In this paper, the influence of surrounding
orography on accuracy of wind data analysis of a train is
investigated. For the case study, a site with complex surrounding
orography is considered. This site is located in Manjil, one of the
windiest cities of Iran. For having precise evaluation of wind regime
in the site, one-year wind data measurements from two metrological
masts are used. To validate the obtained results from WAsP, the
cross prediction between each mast is performed. The analysis
reveals that WAsP model can estimate the wind speed behavior
accurately. In addition, results show that this software can be used
for predicting the wind regime in flat sites with complex surrounding
orography.
Abstract: Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.
Abstract: As a part of evaluation system for R&D program, the
Korean government has applied feasibility analysis since 2008.
Various professionals put forth a great effort in order to catch up the
high degree of freedom of R&D programs, and make contributions to
evolving the feasibility analysis. We analyze diverse R&D programs
from various viewpoints, such as technology, policy, and Economics,
integrate the separate analysis, and finally arrive at a definite result;
whether a program is feasible or unfeasible. This paper describes the
concept and method of the feasibility analysis as a decision making
tool. The analysis unit and content of each criterion, which are key
elements in a comprehensive decision making structure, are examined
Abstract: The study aimed to investigate the effect of rice types on chewing behaviours (chewing time, number of chews, and portion size) and bolus properties (bolus moisture content, solid loss, and particle size distribution (PSD)) in human subjects. Five cooked rice types including brown rice (BR), white rice (WR), parboiled white rice (PR), high amylose white rice (HR) and waxy white rice (WXR) were chewed by six subjects. The chewing behaviours were recorded and the food boluses were collected during mastication. Rice typeswere found to significantly influence all chewing parameters evaluated. The WXR and BR showed the most pronounced differences compared with other rice types. The initial moisture content of un-chewed WXR was lowest (43.39%) whereas those of other rice types were ranged from 66.86 to 70.33%. The bolus obtained from chewing the WXR contained lowest moisture content (56.43%) whilst its solid loss (22.03%) was not significant different from those of all rice types. In PSD evaluation using Mastersizer S, the diameter of particles measured was ranged between 4 to 3500 μm. The particle size of food bolus from BR, HR, and WXR contained much finer particles than those of WR and PR.
Abstract: Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features.
Abstract: In this paper is to evaluate audio and speech quality
with the help of Digital Audio Watermarking Technique under the
different types of attacks (signal impairments) like Gaussian Noise,
Compression Error and Jittering Effect. Further attacks are
considered as Hostile Environment. Audio and Speech Quality
Evaluation is an important research topic. The traditional way for
speech quality evaluation is using subjective tests. They are reliable,
but very expensive, time consuming, and cannot be used in certain
applications such as online monitoring. Objective models, based on
human perception, were developed to predict the results of subjective
tests. The existing objective methods require either the original
speech or complicated computation model, which makes some
applications of quality evaluation impossible.
Abstract: In order to study the influence of different methods of controlling weeds such as mechanical weeding and mechanical weeder efficiency analysis in mechanical cultivation conditions, in farming year of 2011 an experiment was done in a farm in coupling and development of technology center in Haraz,Iran. The treatments consisted of (I) control treatment: where no weeding was done, (II) use of mechanical weeding without engine and (III) power mechanical weeding. Results showed that experimental treatments had significantly different effects (p=0.05) on yield traits and number of filled grains per panicle, while treatments had the significant effects on grain weight and dry weight of weeds in the first, second and third weeding methods at 1% of confidence level. Treatment (II) had its most significant effect on number of filled grains per panicle and yield performance standpoint, which was 3705.97 kg ha-1 in its highest peak. Treatment (III) was ranked as second influential with 3559.8 kg ha-1. In addition, under (I) treatments, 2364.73 kg ha-1 of yield produced. The minimum dry weights of weeds in all weeding methods were related to the treatment (II), (III) and (I), respectively. The correlation coefficient analysis showed that total yield had a significant positive correlation with the panicle grain yield per plant (r= 0.55*) and the number of grains per panicle-1 (r= 0.57*) and the number of filled grains (r= 0.63*). Total rice yield also had negative correlation of r= -0. 64* with weed dry weight at second weed sampling time (17 DAT). The weed dry weight at third and fourth sampling times (24 and 40 DAT) had negative correlations of -0.65** and r=-0.61* with rice yield, respectively.
Abstract: A Cable-Driven Locomotion Interface provides a low
inertia haptic interface and is used as a way of enabling the user
to walk and interact with virtual surfaces. These surfaces generate
Cartesian wrenches which must be optimized for each motorized
reel in order to reproduce a haptic sensation in both feet. However,
the use of wrench control requires a measure of the cable tensions
applied to the moving platform. The latter measure may be inaccurate
if it is based on sensors located near the reel. Moreover, friction
hysteresis from the reel moving parts needs to be compensated
for with an evaluation of low angular velocity of the motor shaft.
Also, the pose of the platform is not known precisely due to cable
sagging and mechanical deformation. This paper presents a non-ideal
motorized reel design with its corresponding control strategy that
aims at overcoming the aforementioned issues. A transfert function
of the reel based on frequency responses in function of cable tension
and cable length is presented with an optimal adaptative PIDF
controller. Finally, an hybrid position/tension control is discussed with
an analysis of the stability for achieving a complete functionnality of
the haptic platform.
Abstract: This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.
Abstract: This study, focusing on the importance of encouraging
outdoor activities for children, aims to propose and implement a
Web-GIS based outdoor education program for elementary schools,
which will then be evaluated by users. Specifically, for the purpose of
improved outdoor activities in the elementary school education, the
outdoor education program, with chiefly using the Web-GIS that
provides a good information provision and sharing tool, is proposed
and implemented before being evaluated by users. Conclusions of the
study boil down to:
(1) An eight-staged outdoor education program based on the Web-GIS
was proposed for a “second school" of an elementary school that
was then implemented before being evaluated by users (teachers,
instructors, students, and their parents).
(2) The program generally received a good evaluation, while a lot of
students and their parents evaluated negatively for the degree of
discovery and for the degree of interest, respectively, in the
questionnaire survey of students and their parents conducted after
the “second school". The surveys clearly show that an issue to be
solved, from the viewpoint of teachers in particular, is the
establishment of the GIS that will easily represent teaching materials
developed by teachers and of Web-GIS, and improved significance
of the use of GIS and Web-GIS for their widespread.
Abstract: Image registration plays an important role in the
diagnosis of dental pathologies such as dental caries, alveolar bone
loss and periapical lesions etc. This paper presents a new wavelet
based algorithm for registering noisy and poor contrast dental x-rays.
Proposed algorithm has two stages. First stage is a preprocessing
stage, removes the noise from the x-ray images. Gaussian filter has
been used. Second stage is a geometric transformation stage.
Proposed work uses two levels of affine transformation. Wavelet
coefficients are correlated instead of gray values. Algorithm has been
applied on number of pre and post RCT (Root canal treatment)
periapical radiographs. Root Mean Square Error (RMSE) and
Correlation coefficients (CC) are used for quantitative evaluation.
Proposed technique outperforms conventional Multiresolution
strategy based image registration technique and manual registration
technique.
Abstract: Transportation authorities need to provide the services
and facilities that are critical to every country-s well-being and
development. Management of the road network is becoming
increasingly challenging as demands increase and resources are
limited. Public sector institutions are integrating performance
information into budgeting, managing and reporting via
implementing performance measurement systems. In the face of
growing challenges, performance measurement of road networks is
attracting growing interest in many countries. The large scale of
public investments makes the maintenance and development of road
networks an area where such systems are an important assessment
tool. Transportation agencies have been using performance
measurement and modeling as part of pavement and bridge
management systems. Recently the focus has been on extending the
process to applications in road construction and maintenance
systems, operations and safety programs, and administrative
structures and procedures. To eliminate failure and dysfunctional
consequences the importance of obtaining objective data and
implementing evaluation instrument where necessary is presented in
this paper
Abstract: A pilot plant for continuous flow microwave-assisted
chemical reaction combined with microreactors was developed and
water heating tests were conducted for evaluation of the developed
plant. We developed a microwave apparatus having a single
microwave generator that can heat reaction solutions in four reaction
fields simultaneously in order to increase throughput. We also
designed a four-branch waveguide using electromagnetic simulation,
and found that the transmission efficiency at 99%. Finally, we
developed the pilot plant using the developed microwave apparatus
and conducted water heating tests. The temperatures in the respective
reaction fields were controlled within ±1.1 K at 353.2 K. Moreover,
the energy absorption rates by the water were about 90% in the
respective reaction fields, whereas the energy absorption rate was
about 40% when 100 cm3 of water was heated by a commercially
available multimode microwave chemical reactor.
Abstract: Low-carbon economy means the energy conservation and emission reduction. How to measure and evaluate the regional low-carbon economy is an important problem which should be solved immediately. This paper proposed the eco-efficiency ratio based on the ecological efficiency to evaluate the current situation of the low-carbon economy in Jiangsu province and to analyze the efficiency of the low-carbon economy in Jiangsu and other provinces, compared both advantages and disadvantages. And then this paper put forward some advices for the government to formulate the correct development policy of low-carbon economy, to improve the technology innovation capacity and the efficiency of resource allocation.
Abstract: Naive Bayes Nearest Neighbor (NBNN) and its variants, i,e., local NBNN and the NBNN kernels, are local feature-based classifiers that have achieved impressive performance in image classification. By exploiting instance-to-class (I2C) distances (instance means image/video in image/video classification), they avoid quantization errors of local image descriptors in the bag of words (BoW) model. However, the performances of NBNN, local NBNN and the NBNN kernels have not been validated on video analysis. In this paper, we introduce these three classifiers into human action recognition and conduct comprehensive experiments on the benchmark KTH and the realistic HMDB datasets. The results shows that those I2C based classifiers consistently outperform the SVM classifier with the BoW model.