Search results for: dynamic interaction network

Authors: Perumal Kumar, Rajamohan Ganesan

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Addition of milli or micro sized particles to the heat transfer fluid is one of the many techniques employed for improving heat transfer rate. Though this looks simple, this method has practical problems such as high pressure loss, clogging and erosion of the material of construction. These problems can be overcome by using nanofluids, which is a dispersion of nanosized particles in a base fluid. Nanoparticles increase the thermal conductivity of the base fluid manifold which in turn increases the heat transfer rate. Nanoparticles also increase the viscosity of the basefluid resulting in higher pressure drop for the nanofluid compared to the base fluid. So it is imperative that the Reynolds number (Re) and the volume fraction have to be optimum for better thermal hydraulic effectiveness. In this work, the heat transfer enhancement using aluminium oxide nanofluid using low and high volume fraction nanofluids in turbulent pipe flow with constant wall temperature has been studied by computational fluid dynamic modeling of the nanofluid flow adopting the single phase approach. Nanofluid, up till a volume fraction of 1% is found to be an effective heat transfer enhancement technique. The Nusselt number (Nu) and friction factor predictions for the low volume fractions (i.e. 0.02%, 0.1 and 0.5%) agree very well with the experimental values of Sundar and Sharma (2010). While, predictions for the high volume fraction nanofluids (i.e. 1%, 4% and 6%) are found to have reasonable agreement with both experimental and numerical results available in the literature. So the computationally inexpensive single phase approach can be used for heat transfer and pressure drop prediction of new nanofluids.

Keywords: Heat transfer intensification, nanofluid, CFD, friction factor

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Authors: Guillermo Romero-Jiménez, Luis A. Jiménez-Fraustro, Mayolo Salinas-Camacho, Heriberto Avalos-Valenzuela

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A geothermal power plant multiple simulator for operators training is presented. The simulator is designed to be installed in a wireless local area network and has a capacity to train one to six operators simultaneously, each one with an independent simulation session. The sessions must be supervised only by one instructor. The main parts of this multiple simulator are: instructor and operator-s stations. On the instructor station, the instructor controls the simulation sessions, establishes training exercises and supervises each power plant operator in individual way. This station is hosted in a Main Personal Computer (NS) and its main functions are: to set initial conditions, snapshots, malfunctions or faults, monitoring trends, and process and soft-panel diagrams. On the other hand the operators carry out their actions over the power plant simulated on the operator-s stations; each one is also hosted in a PC. The main software of instructor and operator-s stations are executed on the same NS and displayed in PCs through graphical Interactive Process Diagrams (IDP). The geothermal multiple simulator has been installed in the Geothermal Simulation Training Center (GSTC) of the Comisi├│n Federal de Electricidad, (Federal Commission of Electricity, CFE), Mexico, and is being utilized as a part of the training courses for geothermal power plant operators.

Keywords: Geothermal power plant, multiple simulator, training operator.

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Authors: Sara D. Garduño-Diaz, Philippe Y. Garduño-Diaz

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To date, one of the few comprehensive indicators for the measurement of food security is the Global Food Security Index (GFSI). This index is a dynamic quantitative and qualitative benchmarking model, constructed from 28 unique indicators, that measures drivers of food security across both developing and developed countries. Whereas the GFSI has been calculated across a set of 109 countries, in this paper we aim to present and compare, for the Middle East and North Africa (MENA), 1) the Food Security Index scores achieved and 2) the data available on affordability, availability, and quality of food. The data for this work was taken from the latest available report published by the creators of the GFSI, which in turn used information from national and international statistical sources. MENA countries rank from place 17/109 (Israel, although with resent political turmoil this is likely to have changed) to place 91/109 (Yemen) with household expenditure spent in food ranging from 15.5% (Israel) to 60% (Egypt). Lower spending on food as a share of household consumption in most countries and better food safety net programs in the MENA have contributed to a notable increase in food affordability. The region has also, however, experienced a decline in food availability, owing to more limited food supplies and higher volatility of agricultural production. In terms of food quality and safety the MENA has the top ranking country (Israel). The most frequent challenges faced by the countries of the MENA include public expenditure on agricultural research and development as well as volatility of agricultural production. Food security is a complex phenomenon that interacts with many other indicators of a country’s wellbeing; in the MENA it is slowly but markedly improving.

Keywords: Diet, food insecurity, global food security index, nutrition, sustainability.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

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Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: Diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography.

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Authors: Sameh A. S. Alariqi

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Food is widely packaged with plastic materials to prevent microbial contamination and spoilage. Ionizing radiation is widely used to sterilize the food-packaging materials. Sterilization by γ-radiation causes degradation such as embrittlement, stiffening, softening, discoloration, odour generation, and decrease in molecular weight. Many antioxidants can prevent γ-degradation but most of them are toxic. The migration of antioxidants to its environment gives rise to major concerns in case of food packaging plastics. In this attempt, we have aimed to utilize synergistic mixtures of stabilizers which are approved for food-contact applications. Ethylene-propylene-diene terpolymer has been melt-mixed with hindered amine stabilizers (HAS), phenolic antioxidants and organophosphites (hydroperoxide decomposer). Results were discussed by comparing the stabilizing efficiency of mixtures with and without phenol system. Among phenol containing systems where we mostly observed discoloration due to the oxidation of hindered phenol, the combination of secondary HAS, tertiary HAS, organo-phosphite and hindered phenol exhibited improved stabilization efficiency than single or binary additive systems. The mixture of secondary HAS and tertiary HAS, has shown antagonistic effect of stabilization. However, the combination of organo-phosphite with secondary HAS, tertiary HAS and phenol antioxidants have been found to give synergistic even at higher doses of Gamma-irradiation. The effects have been explained through the interaction between the stabilizers. After γ-irradiation, the consumption of oligomeric stabilizer significantly depends on the components of stabilization mixture. The effect of the organo-phosphite antioxidant on the overall stability has been discussed.

Keywords: Ethylene-propylene-diene terpolymer, Synergistic mixtures, Gamma-sterilization and stabilization.

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Authors: Belkacem Selma, Boumediene Selma, Samira Chouraqui, Hanifi Missoum, Tourkia Guerzou

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. Earthquake prediction to prevent the loss of human lives and even property damage is an important factor; that, is why it is crucial to develop techniques for predicting this natural disaster. This study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 104 J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines have been analyzed. The results obtained show that the ANN is able to predict earthquake parameters with  high accuracy; the classification accuracy through neural networks is more than 94%, and the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: Earthquake prediction, artificial intelligence, AI, Artificial Neural Network, ANN, seismic bumps.

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Authors: A. Faro, D. Giordano, F. Maiorana

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Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optimize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is able to automatically suggest a strategy to optimize the number of classes optimization, but also support both tree classifications and semi-lattice organizations of the classes to give to the users the possibility of passing from one class to the ones with which it has some aspects in common. Examples of using tree and semi-lattice classifications are given to illustrate advantages and problems. The tool is applied to classify macroeconomic data that report the most developed countries- import and export. It is possible to classify the countries based on their economic behaviour and use the tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation. Possible interrelationships between the classes and their meaning are also discussed.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, Cluster interpretation.

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Authors: Sunil Patel, Pallab Maji

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To study the effect of adversarial attack environment must be controlled. Autonomous driving includes mainly 5 phases sense, perceive, map, plan, and drive. Autonomous vehicles sense their surrounding with the help of different sensors like cameras, radars, and lidars. Deep learning techniques are considered Blackbox and found to be vulnerable to adversarial attacks. In this research, we study the effect of the various known adversarial attacks with the help of the Unreal Engine-based, high-fidelity, real-time raytraced simulated environment. The goal of this experiment is to find out if adversarial attacks work in moving vehicles and if an unknown network may be targeted. We discovered that the existing Blackbox and Whitebox attacks have varying effects on different traffic signs. We observed that attacks that impair detection in static scenarios do not have the same effect on moving vehicles. It was found that some adversarial attacks with hardly noticeable perturbations entirely blocked the recognition of certain traffic signs. We observed that the daylight condition has a substantial impact on the model's performance by simulating the interplay of light on traffic signs. Our findings have been found to closely resemble outcomes encountered in the real world.

Keywords: Adversarial attack simulation, computer simulation, ray-traced environment, realistic simulation, unreal engine.

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Authors: Amin Kamal Akhnoukh, Lois Zaki Kamel, Magued Mourad Barsoum

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The objective of this research is to mitigate and prevent the alkali silica reactivity (ASR) in highway construction projects. ASR is a deleterious reaction initiated when the silica content of the aggregate reacts with alkali hydroxides in cement in the presence of relatively high moisture content. The ASR results in the formation of an expansive white colored gel-like material which forms the destructive tensile stresses inside hardened concrete. In this research, different types of local aggregates available in the State of Arkansas were mixed and mortar bars were poured according to the ASTM specifications. Mortar bars expansion was measured versus time and aggregates with potential ASR problems were detected. Different types of supplementary cementitious materials (SCMs) were used in remixing mortar bars with highly reactive aggregates. Length changes for remixed bars proved that different types of SCMs can be successfully used in reducing the expansive effect of ASR. SCMs percentage by weight is highly dependent on the SCM type. The result of this study will help avoiding future losses due to ASR cracking in construction project and reduce the maintenance, repair, and replacement budgets required for highways network.

Keywords: Alkali Silica Reaction, Aggregates, Moisture, Cracks, Mortar Bar Test supplementary cementitious materials.

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Authors: Mohammed Sharif, Donald Burn

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Large scale climate signals and their teleconnections can influence hydro-meteorological variables on a local scale. Several extreme flow and timing measures, including high flow and low flow measures, from 62 hydrometric stations in Canada are investigated to detect possible linkages with several large scale climate indices. The streamflow data used in this study are derived from the Canadian Reference Hydrometric Basin Network and are characterized by relatively pristine and stable land-use conditions with a minimum of 40 years of record. A composite analysis approach was used to identify linkages between extreme flow and timing measures and climate indices. The approach involves determining the 10 highest and 10 lowest values of various climate indices from the data record. Extreme flow and timing measures for each station were examined for the years associated with the 10 largest values and the years associated with the 10 smallest values. In each case, a re-sampling approach was applied to determine if the 10 values of extreme flow measures differed significantly from the series mean. Results indicate that several stations are impacted by the large scale climate indices considered in this study. The results allow the determination of any relationship between stations that exhibit a statistically significant trend and stations for which the extreme measures exhibit a linkage with the climate indices.

Keywords: flood analysis, low-flow events, climate change, trend analysis, Canada

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Authors: Omowunmi E. Isafiade, Isaac O. Osunmakinde, Antoine B. Bagula

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Robots- visual perception is a field that is gaining increasing attention from researchers. This is partly due to emerging trends in the commercial availability of 3D scanning systems or devices that produce a high information accuracy level for a variety of applications. In the history of mining, the mortality rate of mine workers has been alarming and robots exhibit a great deal of potentials to tackle safety issues in mines. However, an effective vision system is crucial to safe autonomous navigation in underground terrains. This work investigates robots- perception in underground terrains (mines and tunnels) using statistical region merging (SRM) model. SRM reconstructs the main structural components of an imagery by a simple but effective statistical analysis. An investigation is conducted on different regions of the mine, such as the shaft, stope and gallery, using publicly available mine frames, with a stream of locally captured mine images. An investigation is also conducted on a stream of underground tunnel image frames, using the XBOX Kinect 3D sensors. The Kinect sensors produce streams of red, green and blue (RGB) and depth images of 640 x 480 resolution at 30 frames per second. Integrating the depth information to drivability gives a strong cue to the analysis, which detects 3D results augmenting drivable and non-drivable regions in 2D. The results of the 2D and 3D experiment with different terrains, mines and tunnels, together with the qualitative and quantitative evaluation, reveal that a good drivable region can be detected in dynamic underground terrains.

Keywords: Drivable Region Detection, Kinect Sensor, Robots' Perception, SRM, Underground Terrains.

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Authors: Hariton N. Costin, Iulian Ciocoiu, Tudor Barbu, Cristian Rotariu

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In this paper three different approaches for person verification and identification, i.e. by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). Fingerprint detection was approached by classical minutiae (small graphical patterns) matching through image segmentation by using a structural approach and a neural network as decision block. As to voice / speaker recognition, melodic cepstral and delta delta mel cepstral analysis were used as main methods, in order to construct a supervised speaker-dependent voice recognition system. The final decision (e.g. “accept-reject" for a verification task) is taken by using a majority voting technique applied to the three biometrics. The preliminary results, obtained for medium databases of fingerprints, faces and voice recordings, indicate the feasibility of our study and an overall recognition precision (about 92%) permitting the utilization of our system for a future complex biometric card.

Keywords: Biometry, image processing, pattern recognition, speech analysis.

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: Autonomous vehicle, data recording, remote monitoring, controller area network.

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Authors: Jiří F. Urbánek, David Král

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Small and Middle Enterprises (SME) have a specific mission, characteristics, and behavior in global business competitive environments. They must respect policy, rules, requirements and standards in all their inherent and outer processes of supply - customer chains and networks. Paper aims and purposes are to introduce computational assistance, which enables us the using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It is providing for SMS´s global environment the capability and profit to achieve its commitment regarding the effectiveness of the quality management system in customer requirements meeting and also the continual improvement of the organization’s and SME´s processes overall performance and efficiency, as well as its societal security via continual planning improvement. DYVELOP model´s maps - the Blazons are able mathematically - graphically express the relationships among entities, actors, and processes, including the discovering and modeling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission – added value analysis. The crisis management of SMEs is obliged to use the cycles for successful coping of crisis situations.  Several times cycling of these cases is a necessary condition for the encompassment of the both the emergency event and the mitigation of organization´s damages. Uninterrupted and continuous cycling process is a good indicator and controlling actor of SME continuity and its sustainable development advanced possibilities.

Keywords: Blazons, computational assistance, DYVELOP method, small and middle enterprises.

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Authors: Suman

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In the continuous interaction between the past and the present that historiography is, each time when history gets re/written, a new representation emerges. This new representation is a reflection of the earlier archives and their interpretations, fragmented remembrances of the past, as well as the reactions to the present. Memory, or lack thereof, and stereotyping generally play a major role in this representation. William Dalrymple’s Nine Lives: In Search of the Sacred in Modern India (2009) is one such written account that sets out to narrate the representations of religion and culture of India and contemporary reactions to it. Dalrymple’s nine saints belong to different castes, sects, religions, and regions. By dealing with their religions and expressions of those religions, and through the lived mysticism of these nine individuals, the book engages with some important issues like class, caste and gender in the contexts provided by historical as well as present India. The paper studies the development of religion and accompanied feeling of religiosity in modern as well as historical contexts through a study of these elements in the book. Since, the language used in creation of texts and the literary texts thus produced create a new reality that questions the stereotypes of the past, and in turn often end up creating new stereotypes or stereotypical representations at times, the paper seeks to actively engage with the text in order to identify and study such stereotypes, along with their changing representations. Through a detailed examination of the book, the paper seeks to unravel whether some socio-cultural stereotypes existed earlier, and whether there is development of new stereotypes from Dalrymple’s point of view as an outsider writing on issues that are deeply rooted in the cultural milieu of the country. For this analysis, the paper takes help from the psycho-literary theories of stereotyping and representation.

Keywords: Religion, Representation, Stereotyping, William Dalrymple.

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Authors: Tahseen Al-Shaikhli, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

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A concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. Furthermore, the objectives are to control the coordination problem which mainly depends on offset selection, and to estimate the uniform delay based on the offset choice at each signalized intersection. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show that the derived model minimizes the total uniform delay to almost half compared to conventional models; the mathematical objective function is robust; the algorithm convergence time is fast.

Keywords: Area traffic control, differential evolution, offset variable, sinusoidal periodic function, traffic flow, uniform delay.

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Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: Optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization.

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Authors: J. P. Dubois, H. M. Chiu

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In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.

Keywords: ATM, multiplexing, queueing, telemedicine, VBR.

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Authors: I. Kurashvili, G. Darsavelidze, T. Kimeridze, G. Chubinidze, I. Tabatadze

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At present, a number of modern semiconductor devices based on SiGe alloys have been created in which the latest achievements of high technologies are used. These devices might cause significant changes to networking, computing, and space technology. In the nearest future new materials based on SiGe will be able to restrict the A³B⁵ and Si technologies and firmly establish themselves in medium frequency electronics. Effective realization of these prospects requires the solution of prediction and controlling of structural state and dynamical physical –mechanical properties of new SiGe materials. Based on these circumstances, a complex investigation of structural defects and structural-sensitive dynamic mechanical characteristics of SiGe alloys under different external impacts (deformation, radiation, thermal cycling) acquires great importance. Internal friction (IF) and shear modulus temperature and amplitude dependences of the monocrystalline boron-doped Si_1-xGe_x(x≤0.05) alloys grown by Czochralski technique is studied in initial and ⁶⁰Co gamma-irradiated states. In the initial samples, a set of dislocation origin relaxation processes and accompanying modulus defects are revealed in a temperature interval of 400-800 ⁰C. It is shown that after gamma-irradiation intensity of relaxation internal friction in the vicinity of 280 ⁰C increases and simultaneously activation parameters of high temperature relaxation processes reveal clear rising. It is proposed that these changes of dynamical mechanical characteristics might be caused by a decrease of the dislocation mobility in the Cottrell atmosphere enriched by the radiation defects.

Keywords: Gamma-irradiation, internal friction, shear modulus, SiGe alloys.

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Authors: Ali Hamadi Dicko, Nicolas Tong-Yette, Benjamin Gilles, François Faure, Olivier Palombi

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A novel hybrid model of the lumbar spine, allowing fast static and dynamic simulations of the disc pressure and the spine mobility, is introduced in this work. Our contribution is to combine rigid bodies, deformable finite elements, articular constraints, and springs into a unique model of the spine. Each vertebra is represented by a rigid body controlling a surface mesh to model contacts on the facet joints and the spinous process. The discs are modeled using a heterogeneous tetrahedral finite element model. The facet joints are represented as elastic joints with six degrees of freedom, while the ligaments are modeled using non-linear one-dimensional elastic elements. The challenge we tackle is to make these different models efficiently interact while respecting the principles of Anatomy and Mechanics. The mobility, the intradiscal pressure, the facet joint force and the instantaneous center of rotation of the lumbar spine are validated against the experimental and theoretical results of the literature on flexion, extension, lateral bending as well as axial rotation. Our hybrid model greatly simplifies the modeling task and dramatically accelerates the simulation of pressure within the discs, as well as the evaluation of the range of motion and the instantaneous centers of rotation, without penalizing precision. These results suggest that for some types of biomechanical simulations, simplified models allow far easier modeling and faster simulations compared to usual full-FEM approaches without any loss of accuracy.

Keywords: Hybrid, modeling, fast simulation, lumbar spine.

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Authors: Promise A. Azor, Avievie Igodo, Esabai M. Ase

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The paper merged the return of premium clause and voluntary contributions to investigate retirees’ investment plan in a defined contributory (DC) pension scheme with a portfolio comprising of a risk-free asset and a risky asset whose price process is described by geometric Brownian motion (GBM). The paper considers additional voluntary contributions paid by members, charge on balance by pension fund administrators and the mortality risk of members of the scheme during the accumulation period by introducing return of premium clause. To achieve this, the Weilbull mortality force function is used to establish the mortality rate of members during accumulation phase. Furthermore, an optimization problem from the Hamilton Jacobi Bellman (HJB) equation is obtained using dynamic programming approach. Also, the Legendre transformation method is used to transform the HJB equation which is a nonlinear partial differential equation to a linear partial differential equation and solves the resultant equation for the value function and the optimal distribution plan under logarithm utility function. Finally, numerical simulations of the impact of some important parameters on the optimal distribution plan were obtained and it was observed that the optimal distribution plan is inversely proportional to the initial fund size, predetermined interest rate, additional voluntary contributions, charge on balance and instantaneous volatility.

Keywords: Legendre transform, logarithm utility, optimal distribution plan, return clause of premium, charge on balance, Weibull mortality function.

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Authors: S. M. Abdul Khader, Anurag Ayachit, Raghuvir Pai, K. A. Ahmed, V. R. K. Rao, S. Ganesh Kamath

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The numerical simulation has made tremendous advances in investigating the blood flow phenomenon through elastic arteries. Such study can be useful in demonstrating the disease progression and hemodynamics of cardiovascular diseases such as atherosclerosis. In the present study, patient specific case diagnosed with partially stenosed complete right ICA and normal left carotid bifurcation without any atherosclerotic plaque formation is considered. 3D patient specific carotid bifurcation model is generated based on CT scan data using MIMICS-4.0 and numerical analysis is performed using FSI solver in ANSYS-14.5. The blood flow is assumed to be incompressible, homogenous and Newtonian, while the artery wall is assumed to be linearly elastic. The two-way sequentially coupled transient FSI analysis is performed using FSI solver for three pulse cycles. The hemodynamic parameters such as flow pattern, Wall Shear Stress, pressure contours and arterial wall deformation are studied at the bifurcation and critical zones such as stenosis. The variation in flow behavior is studied throughout the pulse cycle. Also, the simulation results reveal that there is a considerable increase in the flow behavior in stenosed carotid in contrast to the normal carotid bifurcation system. The investigation also demonstrates the disturbed flow pattern especially at the bifurcation and stenosed zone elevating the hemodynamics, particularly during peak systole and later part of the pulse cycle. The results obtained agree well with the clinical observation and demonstrates the potential of patient specific numerical studies in prognosis of disease progression and plaque rupture.

Keywords: Fluid-Structure Interaction, arterial stenosis, Wall Shear Stress, Carotid Artery Bifurcation.

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Authors: S. Farid F. Mojtahedi, Ali Khosravi, Behnaz Naeimian, S. Adel A. Hosseini

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Land subsidence is a gradual settling or sudden sinking of the land surface from changes that take place underground. There are different causes of land subsidence; most notably, ground-water overdraft and severe weather conditions. Subsidence of the land surface due to ground water overdraft is caused by an increase in the intergranular pressure in unconsolidated aquifers, which results in a loss of buoyancy of solid particles in the zone dewatered by the falling water table and accordingly compaction of the aquifer. On the other hand, exploitation of underground water may result in significant changes in degree of saturation of soil layers above the water table, increasing the effective stress in these layers, and considerable soil settlements. This study focuses on estimation of soil moisture at surface using different methods. Specifically, different methods for the estimation of moisture content at the soil surface, as an important term to solve Richard’s equation and estimate soil moisture profile are presented, and their results are discussed through comparison with field measurements obtained from Yanco1 station in south-eastern Australia. Surface soil moisture is not easy to measure at the spatial scale of a catchment. Due to the heterogeneity of soil type, land use, and topography, surface soil moisture may change considerably in space and time.

Keywords: Artificial neural network, empirical method, remote sensing, surface soil moisture, unsaturated soil.

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Authors: A. B. Chehreh, M. Grätzel, M. Klein, J. P. Bergmann, F. Walther

Abstract:

Friction stir welding (FSW) is an advantageous method in the thermal joining processes, featuring the welding of various dissimilar and similar material combinations, joining temperatures below the melting point which prevents irregularities such as pores and hot cracks as well as high strengths mechanical joints near the base material. The FSW process consists of a rotating tool which is made of a shoulder and a probe. The welding process is based on a rotating tool which plunges in the workpiece under axial pressure. As a result, the material is plasticized by frictional heat which leads to a decrease in the flow stress. During the welding procedure, the material is continuously displaced by the tool, creating a firmly bonded weld seam behind the tool. However, the mechanical properties of the weld seam are affected by the design and geometry of the tool. These include in particular microstructural and surface properties which can favor crack initiation. Following investigation compares the dynamic properties of FSW weld seams with conventional and stationary shoulder geometry based on load increase test (LIT). Compared to classical Woehler tests, it is possible to determine the fatigue strength of the specimens after a short amount of time. The investigations were carried out on a robotized welding setup on 2 mm thick EN AW 5754 aluminum alloy sheets. It was shown that an increased tensile and fatigue strength can be achieved by using the stationary shoulder concept. Furthermore, it could be demonstrated that the LIT is a valid method to describe the fatigue behavior of FSW weld seams.

Keywords: Aluminum alloy, fatigue performance, fracture, friction stir welding.

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Authors: V. Santamarina Campos, M. de Miguel Molina, B. de Miguel Molina, M. Á. Carabal Montagud

Abstract:

With this contribution, we want to show a successful example of the application of the Design Thinking methodology, in the European project 'Technology transfer of Remotely Piloted Aircraft Systems (RPAS) for the creative industry'. The use of this methodology has allowed us to design and build a drone, based on the real needs of prospective users. It has demonstrated that this is a powerful tool for generating innovative ideas in the field of robotics, by focusing its effectiveness on understanding and solving real user needs. In this way, with the support of an interdisciplinary team, comprised of creatives, engineers and economists, together with the collaboration of prospective users from three European countries, a non-linear work dynamic has been created. This teamwork has generated a sense of appreciation towards the creative industries, through continuously adaptive, inventive, and playful collaboration and communication, which has facilitated the development of prototypes. These have been designed to enable filming and photography in interior spaces, within 13 sectors of European creative industries: Advertising, Architecture, Fashion, Film, Antiques and Museums, Music, Photography, Televison, Performing Arts, Publishing, Arts and Crafts, Design and Software. Furthermore, it has married the real needs of the creative industries, with what is technologically and commercially viable. As a result, a product of great value has been obtained, which offers new business opportunities for small companies across this sector.

Keywords: Design thinking, design for effectiveness, methodology, active toolkit, storyboards, storytelling, PAR, focus group, innovation, RPAS, indoor drone, robotics, TRL, aerial film, creative industries, end-users.

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Authors: Franco Frattolillo

Abstract:

In the last decade digital watermarking procedures have become increasingly applied to implement the copyright protection of multimedia digital contents distributed on the Internet. To this end, it is worth noting that a lot of watermarking procedures for images and videos proposed in literature are based on spread spectrum techniques. However, some scepticism about the robustness and security of such watermarking procedures has arisen because of some documented attacks which claim to render the inserted watermarks undetectable. On the other hand, web content providers wish to exploit watermarking procedures characterized by flexible and efficient implementations and which can be easily integrated in their existing web services frameworks or platforms. This paper presents how a simple spread spectrum watermarking procedure for MPEG-2 videos can be modified to be exploited in web contexts. To this end, the proposed procedure has been made secure and robust against some well-known and dangerous attacks. Furthermore, its basic scheme has been optimized by making the insertion procedure adaptive with respect to the terminals used to open the videos and the network transactions carried out to deliver them to buyers. Finally, two different implementations of the procedure have been developed: the former is a high performance parallel implementation, whereas the latter is a portable Java and XML based implementation. Thus, the paper demonstrates that a simple spread spectrum watermarking procedure, with limited and appropriate modifications to the embedding scheme, can still represent a valid alternative to many other well-known and more recent watermarking procedures proposed in literature.

Keywords: Copyright protection, digital watermarking, intellectual property protection.

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Authors: Citlali Aguilera Lira, David Lynch Steinicke, Andrea León Garcia

Abstract:

One of the challenges that higher education faces is to find how to approach the sustainability in an inclusive way to the student within all the different academic areas, how to move the sustainable development from the abstract field to the operational field. This research comes from the ecoliteracy and the pedagogical praxis as tools for rebuilding the teaching processes inside of universities. The purpose is to determine and describe which are the factors involved in the process of learning particularly in the Greenhouse-School Siembra UV. In the Greenhouse-School Siembra UV, of the University of Veracruz, are cultivated vegetables, medicinal plants and small cornfields under the usage of eco-technologies such as hydroponics, Wickingbed and Hugelkultur, which main purpose is the saving of space, labor and natural resources, as well as function as agricultural production alternatives in the urban and periurban zones. The sample was formed with students from different academic areas and who are actively involved in the greenhouse, as well as institutes from the University of Veracruz and governmental and nongovernmental departments. This project comes from a pedagogic praxis approach, from filling the needs that the different professional profiles of the university students have. All this with the purpose of generate a pragmatic dialogue with the sustainability. It also comes from the necessity to understand the factors that intervene in the students’ praxis. In this manner is how the students are the fundamental unit in the sphere of sustainability. As a result, it is observed that those University of Veracruz students who are involved in the Greenhouse-school, Siembra UV, have enriched in different levels the sense of urban and periurban agriculture because of the diverse academic approaches they have and the interaction between them. It is concluded that the ecotechnologies act as fundamental tools for ecoliteracy in society, where it is strengthen the nutritional and food security from a sustainable development approach.

Keywords: Farming eco-technologies, food security, multidisciplinary, pedagogical praxis.

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Authors: Reham A. El-mayet, Hesham M. El-Badawy, Salwa H. Elramly

Abstract:

New generation mobile communication networks have the ability of supporting triple play. In order that, Orthogonal Frequency Division Multiplexing (OFDM) access techniques have been chosen to enlarge the system ability for high data rates networks. Many of cross-layer modeling and optimization schemes for Quality of Service (QoS) and capacity of downlink multiuser OFDM system were proposed. In this paper, the Maximum Weighted Capacity (MWC) based resource allocation at the Physical (PHY) layer is used. This resource allocation scheme provides a much better QoS than the previous resource allocation schemes, while maintaining the highest or nearly highest capacity and costing similar complexity. In addition, the Delay Satisfaction (DS) scheduling at the Medium Access Control (MAC) layer, which allows more than one connection to be served in each slot is used. This scheduling technique is more efficient than conventional scheduling to investigate both of the number of users as well as the number of subcarriers against system capacity. The system will be optimized for different operational environments: the outdoor deployment scenarios as well as the indoor deployment scenarios are investigated and also for different channel models. In addition, effective capacity approach [1] is used not only for providing QoS for different mobile users, but also to increase the total wireless network's throughput.

Keywords: Cross-layer, effective capacity, LTE, OFDM, QoS, resource allocation, wireless networks.

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Authors: Y. Al-Mahroqi, I.A. Metwally, A. Al-Hinai, A. Al-Badi

Abstract:

Losses reduction initiatives in distribution systems have been activated due to the increasing cost of supplying electricity, the shortage in fuel with ever-increasing cost to produce more power, and the global warming concerns. These initiatives have been introduced to the utilities in shape of incentives and penalties. Recently, the electricity distribution companies in Oman have been incentivized to reduce the distribution technical and non-technical losses with an equal annual reduction rate for 6 years. In this paper, different techniques for losses reduction in Mazoon Electricity Company (MZEC) are addressed. In this company, high numbers of substation and feeders were found to be non-compliant with the Distribution System Security Standard (DSSS). Therefore, 33 projects have been suggested to bring non-complying 29 substations and 28 feeders to meet the planed criteria and to comply with the DSSS. The largest part of MZEC-s network (South Batinah region) was modeled by ETAP software package. The model has been extended to implement the proposed projects and to examine their effects on losses reduction. Simulation results have shown that the implementation of these projects leads to a significant improvement in voltage profile, and reduction in the active and the reactive power losses. Finally, the economical analysis has revealed that the implementation of the proposed projects in MZEC leads to an annual saving of about US$ 5 million.

Keywords: Losses Reduction, Technical Losses, Non-Technical Losses, Cost Analysis

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