Abstract: This paper describes a platform that faces the main
research areas for e-learning educational contents. Reusability tackles
the possibility to use contents in different courses reducing costs and
exploiting available data from repositories. In our approach the
production of educational material is based on templates to reuse
learning objects. In terms of interoperability the main challenge lays
on reaching the audience through different platforms. E-learning
solution must track social consumption evolution where nowadays
lots of multimedia contents are accessed through the social networks.
Our work faces it by implementing a platform for generation of
multimedia presentations focused on the new paradigm related to
social media. The system produces videos-courses on top of web
standard SMIL (Synchronized Multimedia Integration Language)
ready to be published and shared. Regarding interfaces it is
mandatory to satisfy user needs and ease communication. To
overcome it the platform deploys virtual teachers that provide natural
interfaces while multimodal features remove barriers to pupils with
disabilities.
Abstract: Inventory decisional environment of short life-cycle
products is full of uncertainties arising from randomness and
fuzziness of input parameters like customer demand requiring
modeling under hybrid uncertainty. Prior inventory models
incorporating fuzzy demand have unfortunately ignored stochastic
variation of demand. This paper determines an unambiguous optimal
order quantity from a set of n fuzzy observations in a newsvendor
inventory setting in presence of fuzzy random variable demand
capturing both fuzzy perception and randomness of customer
demand. The stress of this paper is in providing solution procedure
that attains optimality in two steps with demand information
availability in linguistic phrases leading to fuzziness along with
stochastic variation. The first step of solution procedure identifies
and prefers one best fuzzy opinion out of all expert opinions and the
second step determines optimal order quantity from the selected
event that maximizes profit. The model and solution procedure is
illustrated with a numerical example.
Abstract: In this article, the authors reviewed and analyzed the survey materials similarities ornament proto-Turkic and northern Indians. The study examined the materials scientists - geneticists, archaeologists, anthropologists. Numerous studies of scientists from different directions once again prove the relevance of the topic. The authors approached the subject from an artistic side. The study authors have made the appropriate conclusions. This publication is based on the proceedings of the investigation.
Abstract: This paper describes the design and development of pico-hydro generation system using consuming water distributed to houses. Water flow in the domestic pipes has kinetic energy that potential to generate electricity for energy storage purposes in addition to the routine activities such as laundry, cook and bathe. The inherent water pressure and flow inside the pipe from utility-s main tank that used for those usual activities is also used to rotate small scale hydro turbine to drive a generator for electrical power generation. Hence, this project is conducted to develop a small scale hydro generation system using consuming water distributed to houses as an alternative electrical energy source for residential use.
Abstract: In this paper, a TSK-type Neuro-fuzzy Inference
System that combines the features of fuzzy sets and neural networks
has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled
Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate
the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on
Particle Swarm Optimization algorithm (PSO) and Genetic
Algorithm (GA).
Abstract: Cavitation, usually known as a destructive
phenomenon, involves turbulent unsteady two-phase flow. Having
such features, cavitating flows have been turned to a challenging
topic in numerical studies and many researches are being done for
better understanding of bubbly flows and proposing solutions to
reduce its consequent destructive effects. Aeration may be regarded
as an effective protection against cavitation erosion in many
hydraulic structures, like gated tunnels. The paper concerns
numerical simulation of flow in discharge gated tunnel of a dam
using ing RNG k -ε model coupled with the volume of fluid (VOF)
method and the zone which is susceptible of cavitation inception in
the tunnel is predicted. In the second step, a vent is considered in the
mentioned zone for aeration and the numerical simulation is done
again to study the effects of aeration. The results show that aeration
is an impressively useful method to exclude cavitation in mentioned
tunnels.
Abstract: The purpose of this study attempts to emphasize the factors relating to intra-family relationships (order point of view) on violence against the women, For this purpose a survey technique on the sample size amounted 100 women of married of city of Ilam in country of Iran were considered. For measurement of violence against the women , the CTS scaled has been used .violence against the women be measured in four dimension ( emotional violence, psycho violence, physical violence, neglect violence). highest violence was related to emotional violence and after are as follow respectively : physical violence and neglect violence. The results showed that women have experienced the violence more than once during the last year, degree of order in family is high. Explanation result indicated that the order variables in family including collective thinking, empathy and communal co-circumstance have significant effects on violence against the women. Via multiple regression analysis variables of empathy, religious tenet and education of husband had significant effect on violence against women. In other words relationships among family effect on violence in family.
Abstract: This paper presents the application of Intelligent
Techniques to the various duties of Intelligent Condition Monitoring
Systems (ICMS) for Unmanned Aerial Vehicle (UAV) Robots. These
Systems are intended to support these Intelligent Robots in the event
of a Fault occurrence. Neural Networks are used for Diagnosis, whilst
Fuzzy Logic is intended for Prognosis and Remedy. The ultimate
goals of ICMS are to save large losses in financial cost, time and
data.
Abstract: This paper proposes an alternative control mechanism
for an interactive Pan/Tilt/Zoom (PTZ) camera control system.
Instead of using a mouse or a joystick, the proposed mechanism
utilizes a Nintendo Wii remote and infrared (IR) sensor bar. The Wii
remote has buttons that allows the user to control the movement of a
PTZ camera through Bluetooth connectivity. In addition, the Wii
remote has a built-in motion sensor that allows the user to give
control signals to the PTZ camera through pitch and roll movement.
A stationary IR sensor bar, placed at some distance away opposite the
Wii remote, enables the detection of yaw movement. In addition, the
Wii remote-s built-in IR camera has the ability to detect its spatial
position, and thus generates a control signal when the user moves the
Wii remote. Some experiments are carried out and their performances
are compared with an industry-standard PTZ joystick.
Abstract: In this paper, we investigate a class of fuzzy Cohen- Grossberg neural networks with time delays and impulsive effects. By virtue of stochastic analysis, Halanay inequality for stochastic differential equations, we find sufficient conditions for the global exponential square-mean synchronization of the FCGNNs under noise perturbation. In particular, the traditional assumption on the differentiability of the time-varying delays is no longer needed. Finally, a numerical example is given to show the effectiveness of the results in this paper.
Abstract: Antibacterial activity of Plumeria alba (Frangipani)
petals methanolic extracts were evaluated against Escherichia coli,
Proteus vulgaris,Staphylococcus aureus, Klebsiella pneumoniae,
Pseudomonas aeruginosa, Staphylococcus saprophyticus,
Enterococcus faecalis and Serratia marcescens by using disk
diffusion method. Concentration extracts (80 %) showed the highest
inhibition zone towards Escherichia coli (14.3 mm). Frangipani
extract also showed high antibacterial activity against
Staphylococcus saprophyticus, Proteus vulgaris and Serratia
marcescens, but not more than the zones of the positive control used.
Comparison between two broad specrum antibiotics to frangipani
extracts showed that the 80 % concentration extracts produce the
same zone of inhibition as Streptomycin. Frangipani extracts showed
no bacterial activity towards Klebsiella pneumoniae, Pseudomonas
aeruginosa and Enterococcus faecalis. There are differences in the
sensitivity of different bacteria to frangipani extracts, suggesting that
frangipani-s potency varies between these bacteria. The present
results indicate that frangipani showed significant antibacterial
activity especially to Escherichia coli.
Abstract: This paper is an extension of a previous work where a diagonally implicit harmonic balance method was developed and applied to simulate oscillatory motions of pitching airfoil and wing. A more detailed study on the accuracy, convergence, and the efficiency of the method is carried out in the current paperby varying the number of harmonics in the solution approximation. As the main advantage of the method is itsusage for the design optimization of the unsteady problems, its application to more practical case of rotor flow analysis during forward flight is carried out and compared with flight test data and time-accurate computation results.
Abstract: Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.
Abstract: Stormwater wetlands have been mainly designed in an
empirical approach for water quality improvement, with little
quantitative understanding of the internal microbial processes. This
study investigated into heterotrophic bacterial production rate,
heterotrophic bacterial mineralization percentage, and algal biomass
in hypertrophic and eutrophic surface flow stormwater wetlands.
Compared to a nearby wood leachate treatment wetland, the
stormwater wetlands had much higher chlorophyll-a concentrations.
The eutrophic stormwater wetland had improved water quality,
whereas the hypertrophic stormwater wetland had degraded water
quality. Heterotrophic bacterial activities in water were limited in the
stormwater wetlands due to competition of algal growth for nutrients.
The relative contribution of biofilms to the overall heterotrophic
activities was higher in the stormwater wetlands than that in the wood
leachate treatment wetland.
Abstract: This work discusses an innovative methodology for
deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational
relationships. A House of Service Quality (HOSQ) matrix is built to
extract the desired improvement in the service quality characteristics
and to translate them into a hierarchy of important organizational
features. The Mean Square Error (MSE) criterion enables the
pinpointing of the few essential service quality characteristics to be
improved as well as selection of the vital organizational features. The
method was implemented in an engineering supply enterprise and
provides useful information on its vital service dimensions.
Abstract: Narratives are invaluable assets of human lives. Due to
the distinct features of narratives, they are useful for supporting human
reasoning processes. However, many useful narratives become
residuals in organizations or human minds nowadays. Researchers
have contributed effort to investigate and improve narrative generation
processes. This paper attempts to contemplate essential components in
narratives and explore a computational approach to acquire and extract
knowledge to generate narratives. The methodology and significant
benefit for decision support are presented.
Abstract: At present, the tendency to implement the conditionbased
maintenance (CBM), which allows the optimization of the
expenses for equipment monitoring, is more and more evident; also,
the transformer substations with remote monitoring are increasingly
used. This paper reviews all the advantages of the on-line monitoring
and presents an equipment for on-line monitoring of bushings, which
is the own contribution of specialists who are the authors of this
paper. The paper presents a study of the temperature field, using the
finite element method. For carrying out this study, the 3D modelling
of the above mentioned bushing was performed. The analysis study is
done taking into account the extreme thermal stresses, focusing at the
level of the first cooling wing section of the ceramic insulator. This
fact enables to justify the tanδ variation in time, depending on the
transformer loading and the environmental conditions. With a view
to reducing the variation of dielectric losses in bushing insulation, the
use of ferrofuids instead of mineral oils is proposed.
Abstract: The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.
Abstract: A transient heat transfer mathematical model for the
prediction of temperature distribution in the car body during primer
baking has been developed by considering the thermal radiation and
convection in the furnace chamber and transient heat conduction
governing equations in the car framework. The car cockpit is
considered like a structure with six flat plates, four vertical plates
representing the car doors and the rear and front panels. The other
two flat plates are the car roof and floor. The transient heat
conduction in each flat plate is modeled by the lumped capacitance
method. Comparison with the experimental data shows that the heat
transfer model works well for the prediction of thermal behavior of
the car body in the curing furnace, with deviations below 5%.
Abstract: In this paper a data miner based on the learning
automata is proposed and is called LA-miner. The LA-miner extracts
classification rules from data sets automatically. The proposed
algorithm is established based on the function optimization using
learning automata. The experimental results on three benchmarks
indicate that the performance of the proposed LA-miner is
comparable with (sometimes better than) the Ant-miner (a data miner
algorithm based on the Ant Colony optimization algorithm) and CNZ
(a well-known data mining algorithm for classification).