Abstract: This paper examines ethical and social issues which
have proved important when initiating and creating educational spaces within a virtual environment. It focuses on one project, identifying the key decisions made, the barriers to new practice
encountered and the impact these had on the project. It demonstrates
the importance of the 'backstage' ethical and social issues involved in
the creation of a virtual education community and offers conclusions,
and questions, which will inform future research and practice in this
area. These ethical issues are considered using Knobel-s framework
of front-end, in-process and back-end concerns, and include
establishing social practices for the islands, allocating access rights,
considering personal safety and supporting researchers appropriately
within this context.
Abstract: Wireless sensor network has recently emerged as enablers
of several areas. Real applications of WSN are being explored
and some of them are yet to come. While the potential of sensor
networks has been only beginning to be realized, several challenges
still remain. One of them is the experimental evaluation of WSN.
Therefore, deploying and operating a testbed to study the real
behavior of WSN become more and more important. The main
contribution of this work is to analysis the RF link budget behavior
of wireless sensor networks in underground mine gallery.
Abstract: A vast array of biological materials, especially algae have received increasing attention for heavy metal removal. Algae have been proven to be cheaper, more effective for the removal of metallic elements in aqueous solutions. A fresh water algal strain was isolated from Zoo Lake, Johannesburg, South Africa and identified as Desmodesmus sp. This paper investigates the efficacy of Desmodesmus sp.in removing heavy metals contaminating the Wonderfonteinspruit Catchment Area (WCA) water bodies. The biosorption data fitted the pseudo-second order and Langmuir isotherm models. The Langmuir maximum uptakes gave the sequence: Mn2+>Ni2+>Fe2+. The best results for kinetic study was obtained in concentration 120 ppm for Fe3+ and Mn2+, whilst for Ni2+ was at 20 ppm, which is about the same concentrations found in contaminated water in the WCA (Fe3+115 ppm, Mn2+ 121 ppm and Ni2+ 26.5 ppm).
Abstract: Populations of wild boar present in semi-arid of central Iran. We studied features influencing bed site selection by this species in semi-arid central steppe of Iran. Habitat features of the detected bed site were compared with randomly selected by quantifying number of habitat variables in semi- arid area in Iran. The results revealed that the most important influencing factors in bed site selection were vegetation cover, number of Artemisia sieberi, percentage cover and height of Acer cinerascens, percentage cover and height of Amygdalus scoparia. This is the first ecological study of the wild boar in a protected area of the semi desert biome of Iran. Sustainability of wild boar populations in this area dependent to shrubs of Amygdalus scoparia and Acer cinerascens for thermal and camouflage cover.
Abstract: Tracing and locating the geographical location of users (Geolocation) is used extensively in todays Internet. Whenever we, e.g., request a page from google we are - unless there was a specific configuration made - automatically forwarded to the page with the relevant language and amongst others, dependent on our location identified, specific commercials are presented. Especially within the area of Network Security, Geolocation has a significant impact. Because of the way the Internet works, attacks can be executed from almost everywhere. Therefore, for an attribution, knowledge of the origination of an attack - and thus Geolocation - is mandatory in order to be able to trace back an attacker. In addition, Geolocation can also be used very successfully to increase the security of a network during operation (i.e. before an intrusion actually has taken place). Similar to greylisting in emails, Geolocation allows to (i) correlate attacks detected with new connections and (ii) as a consequence to classify traffic a priori as more suspicious (thus particularly allowing to inspect this traffic in more detail). Although numerous techniques for Geolocation are existing, each strategy is subject to certain restrictions. Following the ideas of Endo et al., this publication tries to overcome these shortcomings with a combined solution of different methods to allow improved and optimized Geolocation. Thus, we present our architecture for improved Geolocation, by designing a new algorithm, which combines several Geolocation techniques to increase the accuracy.
Abstract: This paper presents an approach for early breast
cancer diagnostic by employing combination of artificial neural
networks (ANN) and multiwaveletpacket based subband image
decomposition. The microcalcifications correspond to high-frequency
components of the image spectrum, detection of microcalcifications
is achieved by decomposing the mammograms into different
frequency subbands,, reconstructing the mammograms from the
subbands containing only high frequencies. For this approach we
employed different types of multiwaveletpacket. We used the result
as an input of neural network for classification. The proposed
methodology is tested using the Nijmegen and the Mammographic
Image Analysis Society (MIAS) mammographic databases and
images collected from local hospitals. Results are presented as the
receiver operating characteristic (ROC) performance and are
quantified by the area under the ROC curve.
Abstract: This paper presents the application of a signal intensity
independent similarity criterion for rigid and non-rigid body
registration of binary objects. The criterion is defined as the
weighted ratio image of two images. The ratio is computed on a
voxel per voxel basis and weighting is performed by setting the raios
between signal and background voxels to a standard high value. The
mean squared value of the weighted ratio is computed over the union
of the signal areas of the two images and it is minimized using the
Chebyshev polynomial approximation.
Abstract: Neonatal lupus erythematous (NLE) is a rare disease marked by clinical characteristic and specific maternal autoantibody. Many cutaneous, cardiac, liver, and hematological manifestations could happen with affect of one organ or multiple. In this case, both babies were premature, low birth weight (LBW), small for gestational age (SGA) and born through caesarean section from a systemic lupus erythematous (SLE) mother. In the first case, we found a baby girl with dyspnea and grunting. Chest X ray showed respiratory distress syndrome (RDS) great I and echocardiography showed small atrial septal defect (ASD) and ventricular septal defect (VSD). She also developed anemia, thrombocytopenia, elevated C-reactive protein, hypoalbuminemia, increasing coagulation factors, hyperbilirubinemia, and positive blood culture of Klebsiella pneumonia. Anti-Ro/SSA and Anti-nRNP/sm were positive. Intravenous fluid, antibiotic, transfusion of blood, thrombocyte concentrate, and fresh frozen plasma were given. The second baby, male presented with necrotic tissue on the left ear and skin rashes, erythematous macula, athropic scarring, hyperpigmentation on all of his body with various size and facial haemorrhage. He also suffered from thrombocytopenia, mild elevated transaminase enzyme, hyperbilirubinemia, anti-Ro/SSA was positive. Intravenous fluid, methyprednisolone, intravenous immunoglobulin (IVIG), blood, and thrombocyte concentrate transfution were given. Two cases of neonatal lupus erythematous had been presented. Diagnosis based on clinical presentation and maternal auto antibody on neonate. Organ involvement in NLE can occur as single or multiple manifestations.
Abstract: In this paper, a Bayesian Network (BN) based system
is presented for providing clinical decision support to healthcare
practitioners in rural or remote areas of India for young infants or
children up to the age of 5 years. The government is unable to
appoint child specialists in rural areas because of inadequate number
of available pediatricians. It leads to a high Infant Mortality Rate
(IMR). In such a scenario, Intelligent Pediatric System provides a
realistic solution. The prototype of an intelligent system has been
developed that involves a knowledge component called an Intelligent
Pediatric Assistant (IPA); and User Agents (UA) along with their
Graphical User Interfaces (GUI). The GUI of UA provides the
interface to the healthcare practitioner for submitting sign-symptoms
and displaying the expert opinion as suggested by IPA. Depending
upon the observations, the IPA decides the diagnosis and the
treatment plan. The UA and IPA form client-server architecture for
knowledge sharing.
Abstract: Full search block matching algorithm is widely used for hardware implementation of motion estimators in video compression algorithms. In this paper we are proposing a new architecture, which consists of a 2D parallel processing unit and a 1D unit both working in parallel. The proposed architecture reduces both data access power and computational power which are the main causes of power consumption in integer motion estimation. It also completes the operations with nearly the same number of clock cycles as compared to a 2D systolic array architecture. In this work sum of absolute difference (SAD)-the most repeated operation in block matching, is calculated in two steps. The first step is to calculate the SAD for alternate rows by a 2D parallel unit. If the SAD calculated by the parallel unit is less than the stored minimum SAD, the SAD of the remaining rows is calculated by the 1D unit. Early termination, which stops avoidable computations has been achieved with the help of alternate rows method proposed in this paper and by finding a low initial SAD value based on motion vector prediction. Data reuse has been applied to the reference blocks in the same search area which significantly reduced the memory access.
Abstract: The Iranian bentonite was first characterized by
Scanning Electron Microscopy (SEM), Inductively Coupled Plasma
mass spectrometry (ICP-MS), X-ray fluorescence (XRF), X-ray
Diffraction (XRD) and BET. The bentonite was then treated
thermally between 150°C-250°C at 15min, 45min and 90min and
also was activated chemically with different concentration of
sulphuric acid (3N, 5N and 10N). Although the results of thermal
activated-bentonite didn-t show any considerable changes in specific
surface area and Cation Exchange Capacity (CEC), but the results of
chemical treated bentonite demonstrated that such properties have
been improved by acid activation process.
Abstract: Developed tool is one of system tools for easier access to various scientific areas and real time interactive learning between
lecturer and for hearing impaired students. There is no demand for the lecturer to know Sign Language (SL). Instead, the new software
tools will perform the translation of the regular speech into SL, after
which it will be transferred to the student. On the other side, the
questions of the student (in SL) will be translated and transferred to
the lecturer in text or speech. One of those tools is presented tool. It-s
too for developing the correct Speech Visemes as a root of total communication method for hearing impared students.
Abstract: Data mining can be called as a technique to extract
information from data. It is the process of obtaining hidden
information and then turning it into qualified knowledge by statistical
and artificial intelligence technique. One of its application areas is
medical area to form decision support systems for diagnosis just by
inventing meaningful information from given medical data. In this
study a decision support system for diagnosis of illness that make use
of data mining and three different artificial intelligence classifier
algorithms namely Multilayer Perceptron, Naive Bayes Classifier and
J.48. Pima Indian dataset of UCI Machine Learning Repository was
used. This dataset includes urinary and blood test results of 768
patients. These test results consist of 8 different feature vectors.
Obtained classifying results were compared with the previous studies.
The suggestions for future studies were presented.
Abstract: Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.
Abstract: management of medical devices in hospitals includes
the planning of medical equipment acquisition and maintenance. The
presence of critical and non-critical areas together with technological
proliferation render the management of medical devices very
complex. This study creates an easy and objective methodology for
the analysis of medical equipment maintenance, that makes the
management of medical devices more feasible. The study has been
carried out at Florence Hospital Careggi and it aims to help the
clinical engineering department to manage medical equipment by
clarifying the hospital situation through a characterization of the
different areas, technologies and fault typologies.
Abstract: The construction of a civil structure inside a urban
area inevitably modifies the outdoor microclimate at the building
site. Wind speed, wind direction, air pollution, driving rain, radiation
and daylight are some of the main physical aspects that are subjected
to the major changes. The quantitative amount of these modifications
depends on the shape, size and orientation of the building and on its
interaction with the surrounding environment.The flow field over a
flat roof model building has been numerically investigated in order to
determine two-dimensional 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.Several turbulence models and
spatial node distributions have been tested 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 a guidance in
selecting the appropriate grid configuration and corresponding
turbulence model for the prediction of the flow field over a twodimensional
roof architecture dominated by flow separation.
Abstract: The advances in location-based data collection
technologies such as GPS, RFID etc. and the rapid reduction of their
costs provide us with a huge and continuously increasing amount of
data about movement of vehicles, people and goods in an urban area.
This explosive growth of geospatially-referenced data has far
outpaced the planner-s ability to utilize and transform the data into
insightful information thus creating an adverse impact on the return
on the investment made to collect and manage this data. Addressing
this pressing need, we designed and developed DIVAD, a dynamic
and interactive visual analytics dashboard to allow city planners to
explore and analyze city-s transportation data to gain valuable
insights about city-s traffic flow and transportation requirements. We
demonstrate the potential of DIVAD through the use of interactive
choropleth and hexagon binning maps to explore and analyze large
taxi-transportation data of Singapore for different geographic and
time zones.
Abstract: Wireless sensor networks have been used in wide
areas of application and become an attractive area for researchers in
recent years. Because of the limited energy storage capability of
sensor nodes, Energy consumption is one of the most challenging
aspects of these networks and different strategies and protocols deals
with this area. This paper presents general methods for designing low
power wireless sensor network. Different sources of energy
consumptions in these networks are discussed here and techniques for
alleviating the consumption of energy are presented.
Abstract: Modeling and simulation of biochemical reactions is of great interest in the context of system biology. The central dogma of this re-emerging area states that it is system dynamics and organizing principles of complex biological phenomena that give rise to functioning and function of cells. Cell functions, such as growth, division, differentiation and apoptosis are temporal processes, that can be understood if they are treated as dynamic systems. System biology focuses on an understanding of functional activity from a system-wide perspective and, consequently, it is defined by two hey questions: (i) how do the components within a cell interact, so as to bring about its structure and functioning? (ii) How do cells interact, so as to develop and maintain higher levels of organization and functions? In recent years, wet-lab biologists embraced mathematical modeling and simulation as two essential means toward answering the above questions. The credo of dynamics system theory is that the behavior of a biological system is given by the temporal evolution of its state. Our understanding of the time behavior of a biological system can be measured by the extent to which a simulation mimics the real behavior of that system. Deviations of a simulation indicate either limitations or errors in our knowledge. The aim of this paper is to summarize and review the main conceptual frameworks in which models of biochemical networks can be developed. In particular, we review the stochastic molecular modelling approaches, by reporting the principal conceptualizations suggested by A. A. Markov, P. Langevin, A. Fokker, M. Planck, D. T. Gillespie, N. G. van Kampfen, and recently by D. Wilkinson, O. Wolkenhauer, P. S. Jöberg and by the author.
Abstract: This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.