Computational Intelligence Techniques and Agents- Technology in E-learning Environments

In this contribution a newly developed e-learning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Spatial thinking Issues: Towards Rural Sociological Research Agenda in the Third Millennium

Does the spatial perspective provide a common thread for rural sociology? Have rural sociologists succeeded in bringing order to their data using spatial analysis models and techniques? A trial answer to such questions, as touchstones of theoretical and applied sociological studies in rural areas, is the point at issue in the present paper. Spatial analyses have changed the way rural sociologists approach scientific problems. Rural sociology is spatial by nature because much, if not most, of its research topics has a spatial “awareness." However, such spatial awareness is not quite the same as spatial analysis because it is not typically associated with underlying theories and hypotheses about spatial patterns that are designed to be tested for their specific spatial content. This paper presents pressing issues for future research to reintroduce mainstream rural sociology to the concept of space.

Enhanced Performance of Fading Dispersive Channel Using Dynamic Frequency Hopping(DFH)

techniques are examined to overcome the performance degradation caused by the channel dispersion using slow frequency hopping (SFH) with dynamic frequency hopping (DFH) pattern adaptation. In DFH systems, the frequency slots are selected by continuous quality monitoring of all frequencies available in a system and modification of hopping patterns for each individual link based on replacing slots which its signal to interference ratio (SIR) measurement is below a required threshold. Simulation results will show the improvements in BER obtained by DFH in comparison with matched frequency hopping (MFH), random frequency hopping (RFH) and multi-carrier code division multiple access (MC-CDMA) in multipath slowly fading dispersive channels using a generalized bandpass two-path transfer function model, and will show the improvement obtained according to the threshold selection.

Analytical Solution of Time-Harmonic Torsional Vibration of a Cylindrical Cavity in a Half-Space

In this article an isotropic linear elastic half-space with a cylindrical cavity of finite length is considered to be under the effect of a ring shape time-harmonic torsion force applied at an arbitrary depth on the surface of the cavity. The equation of equilibrium has been written in a cylindrical coordinate system. By means of Fourier cosine integral transform, the non-zero displacement component is obtained in the transformed domain. With the aid of the inversion theorem of the Fourier cosine integral transform, the displacement is obtained in the real domain. With the aid of boundary conditions, the involved boundary value problem for the fundamental solution is reduced to a generalized Cauchy singular integral equation. Integral representation of the stress and displacement are obtained, and it is shown that their degenerated form to the static problem coincides with existing solutions in the literature.

Analysis of Driving Conditions and Preferred Media on Diversion

Studies on the distribution of traffic demands have been proceeding by providing traffic information for reducing greenhouse gases and reinforcing the road's competitiveness in the transport section, however, since it is preferentially required the extensive studies on the driver's behavior changing routes and its influence factors, this study has been developed a discriminant model for changing routes considering driving conditions including traffic conditions of roads and driver's preferences for information media. It is divided into three groups depending on driving conditions in group classification with the CART analysis, which is statistically meaningful. And the extent that driving conditions and preferred media affect a route change is examined through a discriminant analysis, and it is developed a discriminant model equation to predict a route change. As a result of building the discriminant model equation, it is shown that driving conditions affect a route change much more, the entire discriminant hit ratio is derived as 64.2%, and this discriminant equation shows high discriminant ability more than a certain degree.

Approximation Incremental Training Algorithm Based on a Changeable Training Set

The quick training algorithms and accurate solution procedure for incremental learning aim at improving the efficiency of training of SVR, whereas there are some disadvantages for them, i.e. the nonconvergence of the formers for changeable training set and the inefficiency of the latter for a massive dataset. In order to handle the problems, a new training algorithm for a changeable training set, named Approximation Incremental Training Algorithm (AITA), was proposed. This paper explored the reason of nonconvergence theoretically and discussed the realization of AITA, and finally demonstrated the benefits of AITA both on precision and efficiency.

Why do Clawback Provisions Affect Financial Reporting Quality? - An Analysis of Trigger Effects

We identify clawback triggers from firms- proxy statements (Form DEF 14A) and use the likelihood of restatements to proxy for financial reporting quality. Based on a sample of 578 U.S. firms that voluntarily adopt clawback provisions during 2003-2009, when restatement-based triggers could be decomposed into two types: fraud and unintentional error, and we do observe the evidence that using fraud triggers is associated with high financial reporting quality. The findings support that fraud triggers can enhance deterrent effect of clawback provision by establishing a viable disincentive against fraud, misconduct, and otherwise harmful acts. These results are robust to controlling for the compensation components, to different sample specifications and to a number of sensitivity.

The Anti-Noise System for Rail Brakes on Hump Yards

The friction between two metal surfaces results in a high frequency noise (squealing) which also occurs during the braking of wagons with rail brakes in the process of shunting at a marshalling yard with a hump. At that point the noise level may exceed 130dB, which is extremely unpleasant for workers and inhabitants. In our research we developed a new composite material which does not change braking properties, is capable of taking extremely high pressure loads, reduces noise and is environmentally friendly. The noise reduction results had been very good and had shown a decrease of the high frequency noise almost completely (by 99%) at its source. With our technology we had also reduced general noise by more than 30dBA.

Deformation Mechanisms at Elevated Temperatures: Influence of Momenta and Energy in the Single Impact Test

Within this work High Temperature Single Impact Studies were performed to evaluate deformation mechanisms at different energy and momentum levels. To show the influence of different microstructures and hardness levels and their response to single impacts four different materials were tested at various temperatures up to 700°C. One carbide reinforced NiCrBSi based Metal Matrix Composite and three different steels were tested. The aim of this work is to determine critical energies for fracture appearance and the materials response at different energy and momenta levels. Critical impact loadings were examined at elevated temperatures to limit operating conditions in impact dominated regimes at elevated temperatures. The investigations on the mechanisms were performed using different means of microscopy at the surface and in metallographic cross sections. Results indicate temperature dependence of the occurrence of cracks in hardphase rich materials, such as Metal Matrix Composites High Speed Steels and the influence of different impact momenta at constant energies on the deformation of different steels.

Wheat Yield Prediction through Agro Meteorological Indices for Ardebil District

Wheat prediction was carried out using different meteorological variables together with agro meteorological indices in Ardebil district for the years 2004-2005 & 2005–2006. On the basis of correlation coefficients, standard error of estimate as well as relative deviation of predicted yield from actual yield using different statistical models, the best subset of agro meteorological indices were selected including daily minimum temperature (Tmin), accumulated difference of maximum & minimum temperatures (TD), growing degree days (GDD), accumulated water vapor pressure deficit (VPD), sunshine hours (SH) & potential evapotranspiration (PET). Yield prediction was done two months in advance before harvesting time which was coincide with commencement of reproductive stage of wheat (5th of June). It revealed that in the final statistical models, 83% of wheat yield variability was accounted for variation in above agro meteorological indices.

A Serial Hierarchical Support Vector Machine and 2D Feature Sets Act for Brain DTI Segmentation

Serial hierarchical support vector machine (SHSVM) is proposed to discriminate three brain tissues which are white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM has novel classification approach by repeating the hierarchical classification on data set iteratively. It used Radial Basis Function (rbf) Kernel with different tuning to obtain accurate results. Also as the second approach, segmentation performed with DAGSVM method. In this article eight univariate features from the raw DTI data are extracted and all the possible 2D feature sets are examined within the segmentation process. SHSVM succeed to obtain DSI values higher than 0.95 accuracy for all the three tissues, which are higher than DAGSVM results.

Conflict, Confusion, Choice: A Phenomenological Approach to Acts of Corruption

Public sector corruption has long-term and damaging effects that are deep and broad. Addressing corruption relies on understanding the drivers that precipitate acts of corruption and developing educational programs that target areas of vulnerability. This paper provides an innovative approach to explore the nature of corruption by drawing on the perceptions and ideas of a group of public servants who have been part of a corruption investigation. The paper examines these reflections through the ideas of Pierre Bourdieu and Alfred Schutz to point to some of the steps that can lead to corrupt activity. The paper demonstrates that phenomenological inquiry is useful in the exploration of corruption and, as a theoretical framework, it highlights that corruption emerges through a combination of conflict, doubt and uncertainty. The paper calls for anti-corruption education programs to be attentive to way in which these conditions can influence the steps into corruption.

Main Elements of Soft Cost in Green Buildings

Green buildings have been commonly cited to be more expensive than conventional buildings. However, limited research has been conducted to clearly identify elements that contribute to this cost differential. The construction cost of buildings can be typically divided into “hard" costs and “soft" cost elements. Using a review analysis of existing literature, the study identified six main elements in green buildings that contribute to the general cost elements that are “soft" in nature. The six elements found are insurance, developer-s experience, design cost, certification, commissioning and energy modeling. Out of the six elements, most literatures have highlighted the increase in design cost for green design as compared to conventional design due to additional architectural and engineering costs, eco-charettes, extra design time, and the further need for a green consultant. The study concluded that these elements of soft cost contribute to the green premium or cost differential of green buildings.

Collaborative Tracking Control of UAV-UGV

This paper suggests a fast and stable Target Tracking system in collaborative control of UAV and UGV. Wi-Fi communication range is limited in collaborative control of UAV and UGV. Thus, to secure a stable communications, UAV and UGV have to be kept within a certain distance from each other. But existing method which uses UAV Vertical Camera to follow the motion of UGV is likely to lose a target with a sudden movement change. Eventually, UGV has disadvantages that it could only move at a low speed and not make any sudden change of direction in order to keep track of the target. Therefore, we suggest utilizing AR Drone UAV front camera to track fast-moving and Omnidirectional Mecanum Wheel UGV.

Rhetorical Communication in the CogSci Discourse Community: The Cognitive Neurosciences (2004) in the Context of Scientific Dissemination

In recent years linguistic research has turned increasing attention to covert/overt strategies to modulate authorial stance and positioning in scientific texts, and to the recipients' response. This study discussed some theoretical implications of the use of rhetoric in scientific communication and analysed qualitative data from the authoritative The Cognitive Neurosciences III (2004) volume. Its genre-identity, status and readability were considered, in the social interactive context of contemporary disciplinary discourses – in their polyphony of traditional and new, emerging genres. Evidence was given of the ways its famous authors negotiate and shape knowledge and research results – explicitly appraising team work and promoting faith in the fast-paced progress of Cognitive Neuroscience, also through experiential metaphors – by presenting a set of examples, ordered according to their dominant rhetorical quality.

A Discrete-Event-Simulation Approach for Logistic Systems with Real Time Resource Routing and VR Integration

Today, transport and logistic systems are often tightly integrated in the production. Lean production and just-in-time delivering create multiple constraints that have to be fulfilled. As transport networks often have evolved over time they are very expensive to change. This paper describes a discrete-event-simulation system which simulates transportation models using real time resource routing and collision avoidance. It allows for the specification of own control algorithms and validation of new strategies. The simulation is integrated into a virtual reality (VR) environment and can be displayed in 3-D to show the progress. Simulation elements can be selected through VR metaphors. All data gathered during the simulation can be presented as a detailed summary afterwards. The included cost-benefit calculation can help to optimize the financial outcome. The operation of this approach is shown by the example of a timber harvest simulation.

Adaptive Naïve Bayesian Anti-Spam Engine

The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.

Salient Points Reduction for Content-Based Image Retrieval

Salient points are frequently used to represent local properties of the image in content-based image retrieval. In this paper, we present a reduction algorithm that extracts the local most salient points such that they not only give a satisfying representation of an image, but also make the image retrieval process efficiently. This algorithm recursively reduces the continuous point set by their corresponding saliency values under a top-down approach. The resulting salient points are evaluated with an image retrieval system using Hausdoff distance. In this experiment, it shows that our method is robust and the extracted salient points provide better retrieval performance comparing with other point detectors.

Marangoni Convection in a Fluid Saturated Porous Layer with a Deformable Free Surface

The stability analysis of Marangoni convection in porous media with a deformable upper free surface is investigated. The linear stability theory and the normal mode analysis are applied and the resulting eigenvalue problem is solved exactly. The Darcy law and the Brinkman model are used to describe the flow in the porous medium heated from below. The effect of the Crispation number, Bond number and the Biot number are analyzed for the stability of the system. It is found that a decrease in the Crispation number and an increase in the Bond number delay the onset of convection in porous media. In addition, the system becomes more stable when the Biot number is increases and the Daeff number is decreases.

Concept for a Multidisciplinary Design Process–An Application on High Lift Systems

Presents a concept for a multidisciplinary process supporting effective task transitions between different technical domains during the architectural design stage. A system configuration challenge is the multifunctional driven increased solution space. As a consequence, more iteration is needed to find a global optimum, i.e. a compromise between involved disciplines without negative impact on development time. Since state of the art standards like ISO 15288 and VDI 2206 do not provide a detailed methodology on multidisciplinary design process, higher uncertainties regarding final specifications arise. This leads to the need of more detailed and standardized concepts or processes which could mitigate risks. The performed work is based on analysis of multidisciplinary interaction, of modeling and simulation techniques. To demonstrate and prove the applicability of the presented concept, it is applied to the design of aircraft high lift systems, in the context of the engineering disciplines kinematics, actuation, monitoring, installation and structure design.