Selection of TBM and geotechnical assessment of a microtunnel in a difficult geological environment: a case of a natural gas pipeline beneath an active landslide (Albania)

Bulletin of Engineering Geology and the Environment - This present paper presents an adopted methodology for Micro Tunnel Boring Machine (TBM) selection, based on the results of a...     

A process model of cyberbullying in adolescence

Cyberbullying is an emerging form of aggression that utilizes information and communication technologies (ICTs). While cyberbullying incidents attract considerable attention, research on the causes and psychosocial predictors of cyberbullying is still limited. The present study used an integrated theoretical model incorporating empathy, moral disengagement, and social cognitions related to cyberbullying. Structured questionnaires were administered to 355 randomly selected adolescents (M = 14.7, SD = 1.20). Linear regression analysis showed that social norms, prototype similarity and situational self-efficacy directly predicted cyberbullying expectations. Multiple mediation modelling indicated that normative influences mediated the effects of moral disengagement and affective empathy on cyberbullying expectations. These findings provide valuable information regarding the effect of both distal and proximal risk factors for cyberbullying in adolescence, highlight the relationship between normative processes and moral self-regulation, and set the basis for related educational and preventive interventions.     

Local difference patterns for drunk person identification

In this work, facial thermal infrared images are employed for intoxicated person discrimination. Specifically, the region of the forehead of the face of the sober and the corresponding intoxicated person is used to test if the employed Local Difference Patterns (LDPs) constitute discriminative features. For an intoxicated person, vessels on the forehead become more active so that the intensity of the pixels in this region is affected accordingly. The LDPs employed ignore orientation of the pixels distribution and give emphasis on the first and second norms of the differences as well as the ordered values of the pixels in the employed kernels. The statistics of the LDPs for the drunk person are different from those of the sober one and accordingly drunkenness can be ascertained by comparing the thermal infrared image of the corresponding sober and intoxicated person. Six from the eight LDPs examined to be used as features for drunk identification were proved successful. Their classification success rate was over 73 and up to 85%. The proposed method can be incorporated into a non-invasive inspection commercial system to be used by the police as a first step for intoxicated person detection. Forty one participants in the experiment have contributed to the creation of the unique sober–drunk database which is available on the web and contains over 4.000 images.     

Effect of water aging on the mechanical properties of flax fiber/bio-based resin composites

Present work investigates the effect of hydrothermal aging of flax fiber-reinforced bio-based epoxy resin laminates on the mechanical and thermomechanical properties of the composites. Three different types of bio-based resins were used. Plates reinforced with eight layers plain weave flax fibers of 150 g/m², manufactured using Resin Transfer Molding (RTM), compression molding or autoclave technique depends on type of the resin. One dimensional Fickian behavior shows a good fitting to the experimental data derived from weight measurements. The water uptake at the equilibrium state in the case of 60 °C temperature was slightly greater than that at 40 °C. The mechanical properties after hydrothermal aging show a significant reduction and do not return to their initial values even after the drying process. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48787.     

Effect of preheating on potato texture

Preheating potatoes at 50 to 80°C has a firming effect on the cooked potato tissue. This effect is particularly pronounced at a preheating temperature of 60 to 70°C followed by cooling. Several theories have been presented in the literature to explain this firming effect: retrogradation of starch, leaching of amylose, stabilization of the middle lamellae and cell walls by the activation of the pectin methylesterase (PME) enzyme, and by the release of calcium from gelatinized starch and the formation of calcium bridges between pectin molecules. Most probably, none of these theories alone can explain the phenomenon and more than one mechanism seems to be involved. Some of these mechanisms seem to be interdependent. As an example, calcium could be considered as a link all the way through release after starch gelatinization to cross‐linking pectin substances in the cell wall and the middle lamellae, which has been demethylated by the PME enzyme. More research and “clear cut” experiments are needed in order to elucidate the role of each mechanism, especially which of them is the main contributor to the process of firming. Most probably, the calcium‐pectin‐PME mechanism plays a secondary role, that is, it only retards the collapse of the tissue structure that would otherwise occur during the final heating without preheating, and it is not the main factor of firmness.     

Data hiding based on image texture classification

In this paper, a new pattern-based fragile, semi-blind, spatial domain data hiding scheme is proposed. The Local Binary Pattern texture classification approach is used, in order to transparently and securely embed secret data into an image. Pixel values are modified in such a way that the texture satisfies the message requirements. The method is thoroughly studied and compared to other techniques in spatial domain in terms of capacity and image quality. The scheme performs well in images with smooth areas and can be used for authentication, tamper proofing, and secret communications.     

OPC-SMS: a wireless gateway to OPC-based data sources

This paper describes OPC-SMS gateway, a platform that integrates IP networks with the Short Message Service (SMS), in order to deliver an integrated service for access to data sources conforming to Object Linking and Embedding for Process Control (OPC) standard specifications, through SMS-enabled mobile devices. The gateway supports pull and push services in order to support both request-based and alarm/scheduled-based notifications, respectively. The proposed architecture is based entirely on the ubiquitous HyperText Transport Protocol (HTTP), Simple Object Access Protocol (SOAP), Extensible Markup Language (XML) protocols, and the Global System for Mobile communication (GSM) network and thus exploits the network infrastructure already in place. The capability of accessing different types of OPC data sources (real-time and historical) by any SMS-enabled device consists of a highly flexible service, supporting mobility and event-based notification. A pilot implementation of our approach has been tested in a large-scale installation for accessing OPC data sources of several automation subsystems in a hospital.     

Input Feature Extraction for Multilayered Perceptrons Using Supervised Principal Component Analysis

A method is proposed for constructing salient features from a set of features that are given as input to a feedforward neural network used for supervised learning. Combinations of the original features are formed that maximize the sensitivity of the network's outputs with respect to variations of its inputs. The method exhibits some similarity to Principal Component Analysis, but also takes into account supervised character of the learning task. It is applied to classification problems leading to improved generalization ability originating from the alleviation of the curse of dimensionality problem.     

Skin color-based video segmentation under time-varying illumination

A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling, and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24 percent is observed in 17 out of 21 test sequences. In all but one case, the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation.