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.

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.

Continual Improvement with Integrated Management System

Management Systems are powerful tools for businesses to manage quality , environmental and occupational health and safety requirements . where once these systems were considered as stand alone control mechanisms , industry is now opting to increase the efficiency of these documented systems through a more integrated approach . System integration offers a significant step forward, where there are similarities between system components , reducing duplication and adminstration costs and increasing efficiency . At first , this paper reviews integrated management system structure and its benefits. The second part of this paper focuses on the one example implementation of such a system at Imam Khomeini Hospital and in final part of the paper will be discuss outcomes of that proccess .

Plasma Density Distribution in Asymmetric Geometry Capacitive Coupled Plasma Discharge System

In this work, we used the single Langmuir probe to measure the plasma density distribution in an geometrically asymmetric capacitive coupled plasma discharge system. Because of the frame structure of powered electrode, the plasma density was not homogeneous in the discharge volume. It was higher under the frame, but lower in the centre. Finite element simulation results showed a good agreement with the experiment results. To increase the electron density in the central volume and improve the homogeneity of the plasma, we added an auxiliary electrode, powered by DC voltage, in the simulation geometry. The simulation results showed that the auxiliary electrode could alter the potential distribution and improve the density homogeneity effectively.

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.

Sample-Weighted Fuzzy Clustering with Regularizations

Although there have been many researches in cluster analysis to consider on feature weights, little effort is made on sample weights. Recently, Yu et al. (2011) considered a probability distribution over a data set to represent its sample weights and then proposed sample-weighted clustering algorithms. In this paper, we give a sample-weighted version of generalized fuzzy clustering regularization (GFCR), called the sample-weighted GFCR (SW-GFCR). Some experiments are considered. These experimental results and comparisons demonstrate that the proposed SW-GFCR is more effective than the most clustering algorithms.

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.

Definition and Implementation of a Simulation Model for the Physical Layer and the Radio Channel in Dedicated Short Range Communication Systems

This paper proposes a vehicle-to-vehicle propagation model implemented with SDL. To estimate the channel characteristics for Inter-Vehicle communication, we first define a predicted propagation pathloss between the moving vehicles under three typical scenarios. A Ray-tracing method is used for the simple gamma model performance.

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.

Determining the Gender of Korean Names for Pronoun Generation

It is an important task in Korean-English machine translation to classify the gender of names correctly. When a sentence is composed of two or more clauses and only one subject is given as a proper noun, it is important to find the gender of the proper noun for correct translation of the sentence. This is because a singular pronoun has a gender in English while it does not in Korean. Thus, in Korean-English machine translation, the gender of a proper noun should be determined. More generally, this task can be expanded into the classification of the general Korean names. This paper proposes a statistical method for this problem. By considering a name as just a sequence of syllables, it is possible to get a statistics for each name from a collection of names. An evaluation of the proposed method yields the improvement in accuracy over the simple looking-up of the collection. While the accuracy of the looking-up method is 64.11%, that of the proposed method is 81.49%. This implies that the proposed method is more plausible for the gender classification of the Korean names.

Synthesis and Characterization of ZnO and Fe3O4 Nanocrystals from Oleat-based Organometallic Compounds

Magnetic and semiconductor nanomaterials exhibit novel magnetic and optical properties owing to their unique size and shape-dependent effects. With shrinking the size down to nanoscale region, various anomalous properties that normally not present in bulk start to dominate. Ability in harnessing of these anomalous properties for the design of various advance electronic devices is strictly dependent on synthetic strategies. Hence, current research has focused on developing a rational synthetic control to produce high quality nanocrystals by using organometallic approach to tune both size and shape of the nanomaterials. In order to elucidate the growth mechanism, transmission electron microscopy was employed as a powerful tool in performing real time-resolved morphologies and structural characterization of magnetic (Fe3O4) and semiconductor (ZnO) nanocrystals. The current synthetic approach is found able to produce nanostructures with well-defined shapes. We have found that oleic acid is an effective capping ligand in preparing oxide-based nanostructures without any agglomerations, even at high temperature. The oleate-based precursors and capping ligands are fatty acid compounds, which are respectively originated from natural palm oil with low toxicity. In comparison with other synthetic approaches in producing nanostructures, current synthetic method offers an effective route to produce oxide-based nanomaterials with well-defined shapes and good monodispersity. The nanocystals are well-separated with each other without any stacking effect. In addition, the as-synthesized nanopellets are stable in terms of chemically and physically if compared to those nanomaterials that are previous reported. Further development and extension of current synthetic strategy are being pursued to combine both of these materials into nanocomposite form that will be used as “smart magnetic nanophotocatalyst" for industry waste water treatment.

The Study of Managing the Personal Consent in the Electronic Healthcare Environment

The Electronic Health Record (EHR) system is very general and we should pay more attention to a patient-s privacy. The patient-s consent is one of the elements when dealing with privacy topics. This study focuses on the creating and managing of patient consent. The integration of the HL7 standards and the IHE BPPC profile provides a base for the creation of patient consent. Establishing the platform offers the patients a way to create, revoke or update their consents. Through this platform, they can manage their consents in an easier manner.

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.