Search results for: 3D smart network composite structures

Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

Procedia PDF Downloads 165

Authors: Heba Gamal Abd Elhaleem Elsayed, Nour F Attia

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The extensive use of textile and textile based materials in various applications including industrial applications are increasing regularly due to their interesting properties which require rapid development in their functions to be adapted to these applications [1-3]. Herein, green, new and renewable smart coating was developed for furniture textile fabrics. Facile and single step method was used for synthesis of green coating based on mandarin peel and chitosan. As, the mandarin peel as fruit waste material was dried, grinded and directly dispersed in chitosan solution producing new green coating composite and then coated on textile fabrics. The mass loadings of green mandarin peel powder was varied on 20-70 wt% and optimized. Thermal stability of coated textile fabrics was enhanced and char yield was improved compared to uncoated one. The charring effect of mandarin peel powder coated samples was significantly enhanced anticipating good flame retardancy effect. The tensile strength of the coated textile fabrics was improved achieved 35% improvement compared to uncoated sample. The interaction between the renewable coating and textile was evaluated. The morphology of uncoated and coated textile fabrics was studied using microscopic technique. Additionally, based on thermal properties of mandarin peel powder it could be promising flame retardant for textile fabrics. This study open new avenues for finishing textile fabrics with enhanced thermal, flame retardancy and mechanical properties with cost-effective and renewable green and effective coating

Keywords: flame retardant , Thermal Properties, Textile Coating , Renewable Textile

Procedia PDF Downloads 141

Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

Procedia PDF Downloads 475

Authors: K. Tomolya, D. Janovszky, A. Sycheva, M. Sveda, A. Roosz

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CuZrAl amorphous alloys have attracted high interest due to unique physical and mechanical properties, which can be enhanced by adding of Ni and Ti elements. It is known that this properties can be enhanced by crystallization of amorphous alloys creating nanocrystallines in the matrix. The present work intends to produce nanosized crystalline parti-cle reinforced amorphous matrix composite powders by crystallization of amorphous powders. As the first step the amorphous powders were synthe-tized by ball-milling of crystalline powders. (Cu49Zr45Al6) 80Ni10Ti10 and (Cu49Zr44Al7) 80Ni10Ti10 (at%) alloys were ball-milled for 12 hours in order to reach the fully amorphous structure. The impact en-ergy of the balls during milling causes the change of the structure in the powders. Scanning electron microscopical (SEM) images shows that the phases mixed first and then changed into a fully amorphous matrix. Furthermore, nanosized particles in the amorphous matrix were crystallized by heat treatment of the amorphous powders that was confirmed by TEM measurement. It was of importance to define the tem-perature when the amorphous phase starts to crystal-lize. Amorphous alloys have a special heating curve and characteristic temperatures, which can be meas-ured by differential scanning calorimetry (DSC). A typical DSC curve of an amorphous alloy exhibits an endothermic event characteristic of the equilibrium glass transition (Tg) and a distinct undercooled liquid region, followed by one or two exothermic events corresponding to crystallization processes (Tp). After measuring the DSC traces of the amorphous powders, the annealing temperatures should be determined between Tx and Tp. In our experiments several temperatures from the annealing temperature range were selected and de-pendency of crystallized nanoparticles fraction on their hardness was investigated.

Keywords: amorphous structure, composite, mechanical milling, powder, scanning electron microscopy (SEM), differential scanning calorimetry (DSC), transmission electronmocroscopy (TEM)

Procedia PDF Downloads 450

Authors: R. Ziaie Moayed, A. Khalili

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Improvement and reinforcement of soils with poor strength and engineering properties for constructing low height structures or structures such as liquid storage tanks, bridge columns, and heavy structures have necessitated applying particular techniques. Stone columns are among the well-known methods applied in such soils. This method provides an economically justified way for improving engineering properties of soft clay and loose sandy soils. Stone column implementation in these soils increases their bearing capacity and reduces the settlement of foundation build on them. In the present study, the finite difference based FLAC3D software was used to investigate the performance and effect of soil reinforcement through stone columns without lining and those with geosynthetic lining with different levels of stiffness in horizontal and vertical modes in clayey soils. The results showed that soil improvement using stone columns with lining in vertical and horizontal modes results in improvement of bearing capacity and foundation settlement.

Keywords: bearing capacity, FLAC3D, geosynthetic, settlement, stone column

Procedia PDF Downloads 172

Authors: Edafe Lucky Okotie, Emmanuel Osawaru Omosigho

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This paper examines the impacts of the introduction of distributed energy generation (DEG) technology into the Nigerian power system as an alternative means of energy generation at distribution ends using Otovwodo 15 MVA, 33/11kV injection substation as a case study. The overall idea is to increase the generated energy in the system, improve the voltage profile and reduce system losses. A photovoltaic-based distributed energy generator (PV-DEG) was considered and was optimally placed in the network using Genetic Algorithm (GA) in Mat. Lab/Simulink environment. The results of simulation obtained shows that the dynamic performance of the network was optimized with DEG-grid integration.

Keywords: distributed energy generation (DEG), genetic algorithm (GA), power quality, total load demand, voltage profile

Procedia PDF Downloads 85

Authors: Doo Byong Bae, Jae Jun Yoo, Il Gyu Park, Choi Seowon, Oh Chang Kook

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There are several wind load provisions to evaluate the wind response on tank structures such as API, Euro-code, etc. the assessment of wind action applying these provisions is made by performing the finite element analysis using both linear bifurcation analysis and geometrically nonlinear analysis. By comparing the pressure patterns obtained from the analysis with the results of wind tunnel test, most appropriate wind load criteria will be recommended.

Keywords: wind load, finite element analysis, linear bifurcation analysis, geometrically nonlinear analysis

Procedia PDF Downloads 637

Authors: Ameen Jameel Alawneh

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A Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts that dynamically form a temporary network without the aid of a system administrator. It has neither fixed infrastructure nor wireless ad hoc sessions. It inherently reaches several nodes with a single transmission, and each node functions as both a host and a router. The network maybe represented as a set of clusters each managed by clusterhead. The cluster size is not fixed and it depends on the movement of nodes. We proposed a clusterhead size algorithm (CHSize). This clustering algorithm can be used by several routing algorithms for ad hoc networks. An elected clusterhead is assigned for communication with all other clusters. Analysis and simulation of the algorithm has been implemented using GloMoSim networks simulator, MATLAB and MAPL11 proved that the proposed algorithm achieves the goals.

Keywords: simulation, MANET, Ad-hoc, cluster head size, linked cluster algorithm, loss and dropped packets

Procedia PDF Downloads 392

Authors: Shadab Shishegar, Sophie Duchesne, Genevieve Pelletier

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Sustainability as one of the key elements of Smart cities, can be realized by employing Real Time Control Strategies for city’s infrastructures. Nowadays Stormwater management systems play an important role in mitigating the impacts of urbanization on natural hydrological cycle. These systems can be managed in such a way that they meet the smart cities standards. In fact, there is a huge potential for sustainable management of urban stormwater and also its adaptability to global challenges like climate change. Hence, a dynamically managed system that can adapt itself to instability of the environmental conditions is desirable. A Global Predictive Real Time Control approach is proposed in this paper to optimize the performance of stormwater management basins in terms of flooding prevention. To do so, a mathematical optimization model is developed then solved using Genetic Algorithm (GA). Results show an improved performance at system-level for the stormwater basins in comparison to static strategy.

Keywords: environmental sustainability, optimization, real time control, storm water management

Procedia PDF Downloads 177

Authors: Yen-Ting Chiu, Chia-Ying Lin, Pei-Hsuan Ho

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New technologies can help solve the problem of labor shortage and the decline of birthrate. Technologies can improve human’s life and reduce the burden on the staff and bring convenience to people. That’s why unmanned retail store X-Store was established in Taiwan to create more valuable services and shopping experiences based on smart retailing. The purpose of this study is to examine the impact of unmanned stores, X-Store, on customers’ behavioral intentions. It uses the Unified theory of acceptance and use of technology (UTAUT) model as a basis and adds a perceived value factor to explain customer willingness to use the X-Store. In addition, the study further divided the sample into gender and age groups to compare behavioral differences between different groups. The study collected 214 valid questionnaires through online questionnaires. Using SPSS as a statistical analysis tool, the results of the study show that effort expectancy, social influence, facilitating conditions, and perceived value have a significant impact on behavioral intention to use X-Store. However, performance expectancy is not significant. This research concludes with managerial implications and suggestions for retail practitioners.

Keywords: perceived value, smart retailing, unmanned store, UTAUT, X-Store

Procedia PDF Downloads 90

Authors: Azhar Equbal, Anoop Kumar Sood, M. Asif Equbal, M. Israr Equbal

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In the present work response surface methodology (RSM) based central composite design (CCD) is used for analyzing the electrical discharge machining (EDM) process. For experimentation, mild steel is selected as work piece and copper is used as electrode. Three machining parameters namely current (I), spark on time (T_on) and spark off time (T_off) are selected as the input variables. The output or response chosen is material removal rate (MRR) which is to be maximized. To reduce the number of runs face centered central composite design (FCCCD) was used. ANOVA was used to determine the significance of parameter and interactions. The suitability of model is tested using Anderson darling (AD) plot. The results conclude that different parameters considered i.e. current, pulse on and pulse off time; all have dominant effect on the MRR. At last, the optimized parameter setting for maximizing MRR is found through main effect plot analysis.

Keywords: EDM, electrode, MRR, RSM, ANOVA

Procedia PDF Downloads 305

Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

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Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

Procedia PDF Downloads 234

Authors: Ari Lindeman, Melina Maunula, Jani Kiviranta, Ronja Pölkki

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The aim of this paper is to build a vision of the utilization of creative industry competences in industrial and services firms connected to Kymenlaakso region, Finland, smart specialization focus areas. Research indicates that creativity and the use of creative industry’s inputs can enhance innovation and competitiveness. Currently creative methods and services are underutilized in regional businesses and the added value they provide is not well grasped. Methodologically, the research adopts a qualitative exploratory approach. Data is collected in multiple ways including a survey, focus groups, and interviews. Theoretically, the paper contributes to the discussion about the use creative industry competences in regional development, and argues for building regional creative economy ecosystems in close co-operation with regional strategies and traditional industries rather than as treating regional creative industry ecosystem initiatives separate from them. The practical contribution of the paper is the creative vision for the use of regional authorities in updating smart specialization strategy as well as boosting industrial and creative & cultural sectors’ competitiveness. The paper also illustrates a research-based model of vision building.

Keywords: business, cooperation, creative economy, regional development, vision

Procedia PDF Downloads 131

Authors: Laaziz El Hassan

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The Service Network Design Problem (SNDP) is a tactical issue in freight transportation firms. The existing formulations of the problem for intermodal rail-road transportation were not always adapted to the intermodality in terms of full asset utilization and modal shift reinforcement. The objective of the article is to propose a model having a more compliant formulation with intermodality, including constraints highlighting the imperatives of asset management, reinforcing modal shift from road to rail and reducing, by the way, road mode CO2 emissions. The model is a fixed charged, path based integer nonlinear program. Its objective is to minimize services total cost while ensuring full assets utilization to satisfy freight demand forecast. The model's main feature is that it gives as output both the train sizes and the services frequencies for a planning period. We solved the program using a commercial solver and discussed the numerical results.

Keywords: intermodal transport network, service network design, model, nonlinear integer program, path-based, service frequencies, modal shift

Procedia PDF Downloads 118

Authors: Angela U. Makolo, Temitayo A. Olagunju

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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.

Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways

Procedia PDF Downloads 545

Authors: Subal Kar, Amitesh Kumar, A. Majumder, S. K. Ghosh, S. Saha, S. S. Sikdar, T. K. Saha

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CRLH (composite right/left-handed) based and SRR (split-ring resonator) based filters have been designed at microwave frequency which can provide better performance compared to conventional edge-coupled band-pass filter designed around the same frequency, 2.45 GHz. Both CRLH and SRR are unit cells used in metamaterial design. The primary aim of designing filters with such structures is to realize size reduction and also to realize novel filter performance. The CRLH based filter has been designed in microstrip transmission line, while the SRR based filter is designed with SRR loading in waveguide. The CRLH based filter designed at 2.45 GHz provides an insertion loss of 1.6 dB with harmonic suppression up to 10 GHz with 67 % size reduction when compared with a conventional edge-coupled band-pass filter designed around the same frequency. One dimensional (1-D) SRR matrix loaded in a waveguide shows the possibility of realizing a stop-band with sharp skirts in the pass-band while a stop-band in the pass-band of normal rectangular waveguide with tailoring of the dimensions of SRR unit cells. Such filters are expected to be very useful for communication systems at microwave frequency.

Keywords: BPF, CRLH, harmonic, metamaterial, SRR and waveguide

Procedia PDF Downloads 427

Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

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Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

Procedia PDF Downloads 113

Authors: J. R. Büttler, T. Pham

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Basic understanding of interfacial mechanisms is of importance for the development of polymer composites. For this purpose, we need techniques to analyze the quality of interphases, their chemical and physical interactions and their strength and fracture resistance. In order to investigate the interfacial phenomena in detail, advanced characterization techniques are favorable. Dynamic mechanical thermal analysis (DMTA) using a rheological system is a sensitive tool. T-peel tests were performed with this system, to investigate the temperature-dependent peel behavior of woven textile composites. A model system was made of polyamide (PA) woven fabric laminated with films of polypropylene (PP) or PP modified by grafting with maleic anhydride (PP-g-MAH). Firstly, control measurements were performed with solely PP matrixes. Polymer melt investigations, as well as the extensional stress, extensional viscosity and extensional relaxation modulus at -10°C, 100 °C and 170 °C, demonstrate similar viscoelastic behavior for films made of PP-g-MAH and its non-modified PP-control. Frequency sweeps have shown that PP-g-MAH has a zero phase viscosity of around 1600 Pa·s and PP-control has a similar zero phase viscosity of 1345 Pa·s. Also, the gelation points are similar at 2.42*104 Pa (118 rad/s) and 2.81*104 Pa (161 rad/s) for PP-control and PP-g-MAH, respectively. Secondly, the textile composite was analyzed. The extensional stress of PA66 fabric laminated with either PP-control or PP-g-MAH at -10 °C, 25 °C and 170 °C for strain rates of 0.001 – 1 s^-1 was investigated. The laminates containing the modified PP need more stress for T-peeling. However, the strengthening effect due to the modification decreases by increasing temperature and at 170 °C, just above the melting temperature of the matrix, the difference disappears. Independent of the matrix used in the textile composite, there is a decrease of extensional stress by increasing temperature. It appears that the more viscous is the matrix, the weaker the laminar adhesion. Possibly, the measurement is influenced by the fact that the laminate becomes stiffer at lower temperatures. Adhesive lap-shear testing at room temperature supports the findings obtained with the T-peel test. Additional analysis of the textile composite at the microscopic level ensures that the fibers are well embedded in the matrix. Atomic force microscopy (AFM) imaging of a cross section of the composite shows no gaps between the fibers and matrix. Measurements of the water contact angle show that the MAH grafted PP is more polar than the virgin-PP, and that suggests a more favorable chemical interaction of PP-g-MAH with PA, compared to the non-modified PP. In fact, this study indicates that T-peel testing by DMTA is a technique to achieve more insights into polymeric textile composites.

Keywords: dynamic mechanical thermal analysis, interphase, polyamide, polypropylene, textile composite

Procedia PDF Downloads 129

Authors: B. S.Akhmetov, S. T. Akhmetova, D. N. Nadeyev, V. Yu. Yegorov, V. V. Smogoonov

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Estimated probabilities of errors of the first and second kind for nonideal biometrics-neural transducers 256 outputs, the construction of nomograms based error probability of 'own' and 'alien' from the mathematical expectation and standard deviation of the normalized measures Hamming.

Keywords: modeling, errors, probability, biometrics, neural network, authentication

Procedia PDF Downloads 482

Authors: Chin-Chia Jane

Abstract:

In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

Procedia PDF Downloads 221

Authors: A. Pietro Rimoldi, B. Anilkumar Gopinath, C. Minimol Korulla

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Coastal engineering structure is conventionally designed for a shorter planning horizon usually 20 years. These structures are subjected to different offshore climatic externalities like waves, tides, tsunamis etc. during the design life period. The probability of occurrence of these different offshore climatic externalities varies. The impact frequently caused by these externalities on the structures is of concern because it has a significant bearing on the capital /operating cost of the project. There can also be repeated short time occurrence of these externalities in the assumed planning horizon which can cause heavy damage to the conventional coastal structure which are mainly made of rock. A replacement of the damaged portion to prevent complete collapse is time consuming and expensive when dealing with hard rock structures. But if coastal structures are made of Geo-synthetic containment systems such replacement is quickly possible in the time period between two successive occurrences. In order to have a better knowledge and to enhance the predictive capacity of these occurrences, this study estimates risk of encounter within the design life period of various externalities based on the concept of exponential distribution. This gives an idea of the frequency of occurrences which in turn gives an indication of whether replacement is necessary and if so at what time interval such replacements have to be effected. To validate this theoretical finding, a pilot project has been taken up in the field so that the impact of the externalities can be studied both for a hard rock and a Geosynthetic tube structure. The paper brings out the salient feature of a case study which pertains to a project in which Geosynthetic tubes have been used for reformation of a seawall adjacent to a conventional rock structure in Alappuzha coast, Kerala, India. The effectiveness of the Geosystem in combatting the impact of the short-term externalities has been brought out.

Keywords: climatic externalities, exponential distribution, geosystems, planning horizon

Procedia PDF Downloads 228

Authors: Z. Zerdoumi, D. Benatia, , D. Chicouche

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This paper investigates the application of artificial neural network to the problem of nonlinear channel equalization. The difficulties caused by channel distortions such as inter symbol interference (ISI) and nonlinearity can overcome by nonlinear equalizers employing neural networks. It has been shown that multilayer perceptron based equalizer outperform significantly linear equalizers. We present a multilayer perceptron based equalizer with decision feedback (MLP-DFE) trained with the back propagation algorithm. The capacity of the MLP-DFE to deal with nonlinear channels is evaluated. From simulation results it can be noted that the MLP based DFE improves significantly the restored signal quality, the steady state mean square error (MSE), and minimum Bit Error Rate (BER), when comparing with its conventional counterpart.

Keywords: Artificial Neural Network, signal restoration, Nonlinear Channel equalization, equalization

Procedia PDF Downloads 497

Authors: Navid Khayat, Babak Mombeni

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This study investigates the retrofitting of schools in Ahvaz City. Three schools, namely, Enghelab, Sherafat, and Golchehreh, in Ahvaz City, are initially examined through Schmidt hammer and ultrasonic tests. Given the tests and controls on the structures of these schools, the methods are presented for their reconstruction. The plan is presented for each school by estimating the cost and generally the feasibility and estimated the duration of project reconstruction. After reconstruction, the mentioned tests are re-performed for rebuilt parts and the results indicate a significant improvement in performance of structure because of reconstruction. According to the results, despite the fact that the use of fiber reinforced polymers (FRP) for structure retrofitting is costly, due to the low executive costs and also other benefits of FRP, it is generally considered as one of the most effective ways of retrofitting. Building the concrete coating on walls is another effective method in retrofitting the buildings. According to this method, a grid of horizontal and vertical bars is installed on the wall and then the concrete is poured on it. The use of concrete coating on the concrete and brick structures leads to the useful results and the experience indicates that the poured concrete filled the joints well and provides the appropriate bonding and adhesion.

Keywords: renovation, retrofitting, masonry structures, concrete coating

Procedia PDF Downloads 454

Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

Procedia PDF Downloads 190

Authors: Yu-Kuei Hsu, Ying-Chu Chen, Yan-Gu Lin

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The hierarchical Cu2S nano structural film is successfully fabricated via an electroplated ZnO nanorod array as a template and subsequently chemical solution process for the growth of Cu2S in the application of surface-enhanced Raman scattering (SERS) detection. The as-grown Cu2S nano structures were thermally treated at temperature of 150-300 oC under nitrogen atmosphere to improve the crystal quality and unexpectedly induce the Cu nano particles on surface of Cu2S. The structure and composition of thermally treated Cu2S nano structures were carefully analyzed by SEM, XRD, XPS, and XAS. Using 4-aminothiophenol (4-ATP) as probing molecules, the SERS experiments showed that the thermally treated Cu2S nano structures exhibit excellent detecting performance, which could be used as active and cost-effective SERS substrate for ultra sensitive detecting. Additionally, this novel hierarchical SERS substrates show good reproducibility and a linear dependence between analyte concentrations and intensities, revealing the advantage of this method for easily scale-up production.

Keywords: cuprous sulfide, copper, nanostructures, surface-enhanced raman scattering

Procedia PDF Downloads 408

Authors: Z. Sakka, I. Assakkaf, T. Al-Yaqoub, J. Parol

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A reliability-based methodology for the analysis assessment and evaluation of reinforced concrete structural elements of concrete structures is presented herein. The results of the reliability analysis and assessment for structural elements are verified by the results obtained from the deterministic methods. The analysis outcomes of reliability-based analysis are compared against the safety limits of the required reliability index β according to international standards and codes. The methodology is based on probabilistic analysis using reliability concepts and statistics of the main random variables that are relevant to the subject matter, and for which they are to be used in the performance-function equation(s) related to the structural elements under study. These methodology techniques can result in reliability index β, which is commonly known as the reliability index or reliability measure value that can be utilized to assess and evaluate the safety, human risk, and functionality of the structural component. Also, these methods can result in revised partial safety factor values for certain target reliability indices that can be used for the purpose of redesigning the reinforced concrete elements of the building and in which they could assist in considering some other remedial actions to improve the safety and functionality of the member.

Keywords: structural reliability, concrete structures, FORM, Monte Carlo simulation

Procedia PDF Downloads 518

Authors: Marija Vitanovа, Igor Gjorgjiev, Viktor Hristovski, Vlado Micov

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Evaluation of stability is very important in the process of definition of optimal structural measures for maintenance of bridge structures and their strengthening. To define optimal measures for their repair and strengthening, it is necessary to evaluate their static and seismic stability. Presented in this paper are methodologies for evaluation of the seismic stability of existing reinforced concrete bridges designed without consideration of seismic effects and checking of structural justification of newly designed bridge structures. All bridges are located in the territory of the Republic of North Macedonia. A total of 26 existing bridges of different structural systems have been analyzed. Visual inspection has been carried out for all bridges, along with the definition of three main damage categories according to which structures have been categorized in respect to the need for their repair and strengthening. Investigations involving testing the quality of the built-in materials have been carried out, and dynamic tests pointing to the dynamic characteristics of the structures have been conducted by use of non-destructive methods of ambient vibration measurements. The conclusions drawn from the performed measurements and tests have been used for the development of accurate mathematical models that have been analyzed for static and dynamic loads. Based on the geometrical characteristics of the cross-sections and the physical characteristics of the built-in materials, interaction diagrams have been constructed. These diagrams along with the obtained section quantities under seismic effects, have been used to obtain the bearing capacity of the cross-sections. The results obtained from the conducted analyses point to the need for the repair of certain structural parts of the bridge structures. They indicate that the stability of the superstructure elements is not critical during a seismic effect, unlike the elements of the sub-structure, whose strengthening is necessary.

Keywords: existing bridges, newly designed bridges, reinforced concrete bridges, stability assessment

Procedia PDF Downloads 101

Authors: L. N. Shubha, M. Kalpana, P. Madhusudana Rao

Abstract:

Polyaniline/gold (PANI/Au) nanocomposite was prepared by in-situ chemical oxidation polymerization method. The synthesis involved the formation of polyaniline-gold nanocomposite, by in-situ redox reaction and the dispersion of gold nano particles throughout the polyaniline matrix. The nanocomposites were characterized by XRD, FTIR, TEM and UV-visible spectroscopy. The characteristic peaks in FTIR and UV-visible spectra confirmed the expected structure of polymer as reported in the literature. Further, transmission electron microscopy (TEM) confirmed the formation of gold nano particles. The crystallite size of 30 nm for nanoAu was supported by the XRD pattern. Further, the A.C. conductivity, dielectric constant (€’(w)) and dielectric loss (€’’(w)) of PANI/Au nano composite was measured using impedance analyzer. The effect of doping on the conductivity was investigated. The antibacterial activity was examined for this nano composite and it was observed that PANI/Au nanocomposite could be used as an antibacterial agent.

Keywords: AC-conductivity, anti-microbial activity, dielectric constant, dielectric loss, polyaniline/gold (PANI/AU) nanocomposite

Procedia PDF Downloads 383

Authors: B. Chikh, L. Moussa, H. Bechtoula, Y. Mehani, A. Zerzour

Abstract:

This study presents a new method, applicable to evaluation and design of structures has been developed and illustrated by comparison with the capacity spectrum method (CSM, ATC-40). This method uses inelastic spectra and gives peak responses consistent with those obtained when using the nonlinear time history analysis. Hereafter, the seismic demands assessment method is called in this paper DSM, Ductility Spectrum Method. It is used to estimate the seismic deformation of Single-Degree-Of-Freedom (SDOF) systems based on DDRS, Ductility Demand Response Spectrum, developed by the author.

Keywords: seismic demand, capacity, inelastic spectra, design and structure

Procedia PDF Downloads 396

Authors: Mustafa Zemin

Abstract:

The increasing popularity of deepfake technology poses a growing threat to information integrity and security. This paper presents a deepfake detection system designed to leverage public blockchain and collective intelligence as solutions to address this issue. Utilizing smart contracts on the Ethereum blockchain ensures secure, decentralized media content verification, creating an auditable and tamper-resistant framework. The approach integrates concepts from electronic voting, allowing a network of participants to assess content authenticity collectively through consensus mechanisms. This decentralized, community-driven model enhances detection accuracy while preventing single points of failure. Experimental analysis demonstrates the system’s robustness, reliability, and scalability in deepfake detection, offering a sustainable approach to combat digital misinformation. The proposed solution advances deepfake detection capabilities and provides a framework for applying blockchain-based collective intelligence to other domains facing similar verification challenges, thereby contributing to the fight against digital misinformation in a secure, trustless environment.

Keywords: deepfake detection, public blockchain, electronic voting, collective intelligence, Ethereum

Procedia PDF Downloads 3