Search results for: network optimization methods

Authors: Serkan Tezgel

Abstract:

Effectively managing threats and power that transcend national boundaries requires a reformulation from the traditional post-modern navy to an adaptive and institutional transnational navy. By analyzing existing soft power concept, post-modern navy, and sea power, this study proposes the transnational navy, founded on the triangle of main attributes of transnational companies, 'Global Competitiveness, Local Responsiveness, Worldwide Learning and Innovation Sharing', a new model which will lead to a positive peace with an institutional network. This transnational model necessitates 'Transnational Navies' to help establish peace with collective and transnational understanding during a transition period 'Reactive Postmodern Navy' has been experiencing. In this regard, it is fairly claimed that a new paradigm shift will revolve around sea power to establish good order at sea with collective and collaborative initiatives and bound to breed new theories and ideas in the forthcoming years. However, there are obstacles to overcome. Postmodern navies, currently shaped by 'Collective Maritime Security' and 'Collective Defense' concepts, can not abandon reactive applications and acts. States deploying postmodern navies to realize their policies on international platforms and seapower structures shaped by the axis of countries’ absolute interests resulted in multipolar alliances and coalitions, but the establishment of the peace. These obstacles can be categorized into three tiers in establishing a unique transnational model navy: Strategic, Organizational and Management challenges. To overcome these obstacles and challenges, postmodern navies should transform into cooperative, collective and independent soft transnational navies with the transnational mentality, global commons, and institutional network. Such an adaptive institution can help the world navigate to a positive peace.

Keywords: postmodern navy, transnational navy, transnational mentality, institutional network

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Authors: Nasibeh Mohammadpour, Ali Rajabzadeh, Adel Azar, Hamid Zargham Borujeni,

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Generally, various industries development depends on their stakeholders and beneficiaries supports. One of the most important stakeholders in tourism industry ( which has become one of the most important lucrative and employment-generating activities at the international level these days) are host communities in tourist destination which are affected and effect on this industry development. Recognizing host community and its segmentations can be important to get their support for future decisions and policy making. In order to identify these segments, in this study, clustering of the residents has been done by using some tools that are designed to encounter human complexities and have ability to model and generalize complex systems without any needs for the initial clusters’ seeds like classic methods. Neural networks can help to meet these expectations. The research have been planned to design neural networks-based mathematical model for clustering the host community effectively according to multi criteria, and identifies differences among segments. In order to achieve this goal, the residents’ segmentation has been done by demographic characteristics, their attitude towards the tourism development, the level of satisfaction and the type of their support in this field. The applied method is self-organized neural networks and the results have compared with K-means. As the results show, the use of Self- Organized Map (SOM) method provides much better results by considering the Cophenetic correlation and between clusters variance coefficients. Based on these criteria, the host community is divided into five sections with unique and distinctive features, which are in the best condition (in comparison other modes) according to Cophenetic correlation coefficient of 0.8769 and between clusters variance of 0.1412.

Keywords: Artificial Nural Network, Clustering , Resident, SOM, Tourism

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Authors: Victoria Molina, Wendy Franco, Sergio Benavides, José M. Troncoso, Ricardo Luna, Jose R. PéRez-Correa

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Emamectin Benzoate (EB) is a crystal antiparasitic that belongs to the avermectin family. It is one of the most common treatments used in Chile to control Caligus rogercresseyi in Atlantic salmon. However, the sea lice acquired resistance to EB when it is exposed at sublethal EB doses. The low solubility rate of EB and its degradation at the acidic pH in the fish digestive tract are the causes of the slow absorption of EB in the intestine. To protect EB from degradation and enhance its absorption, specific microencapsulation technologies must be developed. Amorphous Solid Dispersion techniques such as Spray Drying (SD) and Ionic Gelation (IG) seem adequate for this purpose. Recently, Soluplus® (SOL) has been used to increase the solubility rate of several drugs with similar characteristics than EB. In addition, alginate (ALG) is a widely used polymer in IG for biomedical applications. Regardless of the encapsulation technique, the quality of the obtained microparticles is evaluated with the following responses, yield (Y%), encapsulation efficiency (EE%) and loading capacity (LC%). In addition, it is important to know the percentage of EB released from the microparticles in gastric (GD%) and intestinal (ID%) digestions. In this work, we microencapsulated EB with SOL (EB-SD) and with ALG (EB-IG) using SD and IG, respectively. Quality microencapsulation responses and in vitro gastric and intestinal digestions at pH 3.35 and 7.8, respectively, were obtained. A central composite design was used to find the optimum microencapsulation variables (amount of EB, amount of polymer and feed flow). In each formulation, the behavior of these variables was predicted with statistical models. Then, the response surface methodology was used to find the best combination of the factors that allowed a lower EB release in gastric conditions, while permitting a major release at intestinal digestion. Two approaches were used to determine this. The desirability approach (DA) and multi-objective optimization (MOO) with multi-criteria decision making (MCDM). Both microencapsulation techniques allowed to maintain the integrity of EB in acid pH, given the small amount of EB released in gastric medium, while EB-IG microparticles showed greater EB release at intestinal digestion. For EB-SD, optimal conditions obtained with MOO plus MCDM yielded a good compromise among the microencapsulation responses. In addition, using these conditions, it is possible to reduce microparticles costs due to the reduction of 60% of BE regard the optimal BE proposed by (DA). For EB-GI, the optimization techniques used (DA and MOO) yielded solutions with different advantages and limitations. Applying DA costs can be reduced 21%, while Y, GD and ID showed 9.5%, 84.8% and 2.6% lower values than the best condition. In turn, MOO yielded better microencapsulation responses, but at a higher cost. Overall, EB-SD with operating conditions selected by MOO seems the best option, since a good compromise between costs and encapsulation responses was obtained.

Keywords: microencapsulation, multiple decision-making criteria, multi-objective optimization, Soluplus®

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Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

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Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

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Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

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Authors: Yiwei Huang, Chunyu Zhao, Jingjing Ding

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Electrical Resistivity Tomography has been widely used in the medicine and the geology, such as the imaging of the lung impedance and the analysis of the soil impedance, etc. Linear Back Projection is the core algorithm of Electrical Resistivity Tomography, but the traditional Linear Back Projection can not make full use of the information of the electric field. In this paper, an imaging method of Parallel Electrode Linear Back Projection for Electrical Resistivity Tomography is proposed, which generates the electric field distribution that is not linearly related to the traditional Linear Back Projection, captures the new information and improves the imaging accuracy without increasing the number of electrodes by changing the connection mode of the electrodes. The simulation results show that the accuracy of the image obtained by the inverse operation obtained by the Parallel Electrode Linear Back Projection can be improved by about 20%.

Keywords: electrical resistivity tomography, finite element simulation, image optimization, parallel electrode linear back projection

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Authors: Rishabh Sharma

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The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system

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Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

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Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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Authors: Juha Kettunen

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This study presents a project that tests and adjusts active European learning and teaching methods in Indonesian universities to increase their external impact on enterprises and other organizations; it also assesses the implementation of the Erasmus+ projects funded by the European Union. The project is based on the approach of innovation pedagogy that responds to regional development needs and integrates applied research and development projects into education to create capabilities for students to participate in development work after graduation. The assessment of the Erasmus+ project resulted in many improvements that can be made to achieve higher quality and innovativeness. The results of this study are useful for those who want to improve the applied research and development projects of higher education institutions.

Keywords: higher education, innovations, social network, project management

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Authors: Ahsan Ali, Mayank Ostwal, Nikhil Agarwal

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Abstract—According to a World Bank report, millions of people across the globe still do not have access to improved water services. With uninterrupted growth of cities and urban inhabitants, there is a mounting need to safeguard the sustainable expansion of cities. Efficient functioning of the urban components and high living standards of the residents are needed to be ensured. The water and sanitation network of an urban development is one of its most essential parts of its critical infrastructure. The growth in urban population is leading towards increased water demand, and thus, the local water resources are severely strained. 'Smart water' is referred to water and waste water infrastructure that is able to manage the limited resources and the energy used to transport it. It enables the sustainable consumption of water resources through co-ordinate water management system, by integrating Information Communication Technology (ICT) solutions, intended at maximizing the socioeconomic benefits without compromising the environmental values. This paper presents a case study from a medium sized city in North-western Pakistan. Currently, water is getting contaminated due to the proximity between water and sewer pipelines in the study area, leading to public health issues. Due to unsafe grey water infiltration, the scarce ground water is also getting polluted. This research takes into account the design of smart urban water network by integrating ICT (Information and Communication Technology) with urban water network. The proximity between the existing water supply network and sewage network is analyzed and a design of new water supply system is proposed. Real time mapping of the existing urban utility networks will be projected with the help of GIS applications. The issue of grey water infiltration is addressed by providing sustainable solutions with the help of locally available materials, keeping in mind the economic condition of the area. To deal with the current growth of urban population, it is vital to develop new water resources. Hence, distinctive and cost effective procedures to harness rain water would be suggested as a part of the research study experiment.

Keywords: GIS, smart water, sustainability, urban water management

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Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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Authors: Loong Qing Zhe, Foo Jing Heng

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A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

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Authors: Hong-Ming Chen

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This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

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Authors: Essam Al Daoud

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Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort

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Authors: Ping-Hung Chen, Han-Liang Lin

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Taiwan has formed diverse settlement patterns in different time and space backgrounds. Various socio-network links are created between individuals, families, communities, and societies, and different living cultures are also derived. But rapid urbanization and social structural change have caused the creation of densely-packed assembly housing complexes and made neighborhood community upward developed. This, among others, seemed to have affected neighborhood relationship and also created social problems. To understand the complex relations and socio-spatial structure of the community, it is important to use mixed methods. This research employs the theory of space syntax to analyze the layout and structural indicators of the selected communities in Tainan city. On the other hand, this research does the survey about residents' interactions and the sense of community by questionnaire of the selected communities. Then the mean values of the syntax measures from each community were correlated with the results of the questionnaire using a Pearson correlation to examine how elements in physical design affect the sense of community and neighborhood relationship. In Taiwan, most urban morphology research methods are qualitative study. This paper tries to use space syntax to find out the correlation between the community layout and the neighborhood relationship. The result of this study could be used in future studies or improve the quality of residential communities in Taiwan.

Keywords: community layout, neighborhood relationship, space syntax, mixed-method

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Authors: Vivek Kumar Singh, Tripti Singh

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An ad hoc wireless network consists of mobile networks which creates an underlying architecture for communication without the help of traditional fixed-position routers. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol used for Mobile Ad hoc Network (MANET). Nevertheless, the architecture must maintain communication routes although the hosts are mobile and they have limited transmission range. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks, so that MANET requires different protocols. This paper presents the performance analysis of the routing protocols used various parameter-patterns with Two-ray model.

Keywords: AODV, packet transmission rate, pause time, ZRP, QualNet 6.1

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Authors: Liuhui Zhu, Peng Zeng

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The rural revitalization strategy means to take the country and the city on the same level, and achieve urban-rural integration and comprehensive development of rural areas. Beijing-Tianjin-Hebei rural areas have always been the weak links in the region, with prominently uneven development between urban and rural areas. The rural areas need to join the overall regional synergy. Based on the analysis of the characteristics and problems of rural development in the region from the perspective of production-living-ecology space, the paper proposes the township as the basic unit for rural revitalization according to the overall requirements of the rural revitalization strategy. The basic unit helps to realize resource arrangement, functional organization, and collaborative governance organized by the production-living-ecology spatial network. The paper summarizes the planning strategies for the basic unit. Through spatial cognition and spatial reconstruction, the three space is networked through the base, nodes, and connections to improve the comprehensive value of rural areas and achieve the multiple goals of rural revitalization.

Keywords: rural revitalization, Beijing-Tianjin-Hebei region, township level, production-living-ecology spatial network

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Authors: Ramakrishna Rao Mamidi

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It is essential for Surface Mounted Permanent Magnet (SMPM) generators to determine the performance prediction and analyze the magnet’s air gap flux density wave shape. The flux density wave shape is neither a pure sine wave or square wave nor a combination. This is due to the variation of air gap reluctance between the stator and permanent magnets. The stator slot openings and the number of slots make the wave shape highly complicated. To reduce the complexity of analysis, approximations are made to the wave shape using Fourier analysis. In contrast to the traditional integration method, the Fourier coefficients, an and bn, are obtained by direct search method optimization. The wave shape with optimized coefficients gives a wave shape close to the desired wave shape. Harmonics amplitudes are worked out and compared with initial values. It can be concluded that the direct search method can be used for estimating Fourier coefficients for irregular wave shapes.

Keywords: direct search, flux plot, fourier analysis, permanent magnets

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

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Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: causality, defect causes, social network analysis, association rule mining

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Authors: Reihaneh Ahmadzadeh Ghavidel

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Free radicals such as reactive oxygen species (ROS) have detrimental effects on human health through several mechanisms. On the other hand, antioxidant molecules reduce free radical generation in biologic systems. Synthetic antioxidants, which are used in food industry, have also negative impact on human health. Therefore recognition of natural antioxidants such as anthocyanins can solve these problems simultaneously. Coleus (Solenostemon scutellarioides) with red leaves is a rich source of anthocyanins compounds. In this study we evaluated the effect of time (10, 20 and 30 min) and temperature (40, 50 and 60° C) on optimization of anthocyanin extraction using surface response method. In addition, the study was aimed to determine maximum extraction for anthocyanin from coleus plant using ultrasound method. The results indicated that the optimum conditions for extraction were 39.84 min at 69.25° C. At this point, total compounds were achieved 3.7451 mg 100 ml⁻¹. Furthermore, under optimum conditions, anthocyanin concentration, extraction efficiency, ferric reducing ability, total phenolic compounds and EC50 were registered 3.221931, 6.692765, 223.062, 3355.605 and 2.614045, respectively.

Keywords: anthocyanin, antioxidant, coleus, extraction, sonication

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Authors: Seung Ho Park, Young Su Moon, Nam Ik Cho

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We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods.

Keywords: compression artifact reduction, deblocking, image denoising, image restoration

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Authors: Salman Naseer, Usman Zafar, Iqra Zafar

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This study explores the implication of Vehicular Adhoc Network (VANET) - in the rural and urban scenarios that is one domain of Mobile Adhoc Network (MANET). VANET provides wireless communication between vehicle to vehicle and also roadside units. The Federal Commission Committee of United States of American has been allocated 75 MHz of the spectrum band in the 5.9 GHz frequency range for dedicated short-range communications (DSRC) that are specifically designed to enhance any road safety applications and entertainment/information applications. There are several vehicular related projects viz; California path, car 2 car communication consortium, the ETSI, and IEEE 1609 working group that have already been conducted to improve the overall road safety or traffic management. After the critical literature review, the selection of routing protocols is determined, and its performance was well thought-out in the urban and rural scenarios. Numerous routing protocols for VANET are applied to carry out current research. Its evaluation was conceded with the help of selected protocols through simulation via performance metric i.e. throughput and packet drop. Excel and Google graph API tools are used for plotting the graphs after the simulation results in order to compare the selected routing protocols which result with each other. In addition, the sum of the output from each scenario was computed to undoubtedly present the divergence in results. The findings of the current study present that DSR gives enhanced performance for low packet drop and high throughput as compared to AODV and DSDV in an urban congested area and in rural environments. On the other hand, in low-density area, VANET AODV gives better results as compared to DSR. The worth of the current study may be judged as the information exchanged between vehicles is useful for comfort, safety, and entertainment. Furthermore, the communication system performance depends on the way routing is done in the network and moreover, the routing of the data based on protocols implement in the network. The above-presented results lead to policy implication and develop our understanding of the broader spectrum of VANET.

Keywords: AODV, DSDV, DSR, Adhoc network

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Authors: M. A. Mulatu, L. C. Chang, Y. S. Han

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Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.

Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration

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Authors: Mohamed Mesbah, Bruce Janson

Abstract:

An Interchange is the most important component of freeway and highway facilities. It is working as a connector between the highway’s elements. The main goal of designing interchanges is to provide an acceptable level of service and delay to make vehicles move smoothly when they are entering and exiting the interchange. There are many factors that can have a significant impact on level of service, the main factors are traffic volumes, and type of interchange. This paper will discuss in interchange with roundabout under various values of traffic volumes to determine the level of service of the interchanges that will be studies in this paper and replace the system of interchange from roundabout to traffic signal to make a significant compression between these systems. A secondary goal is to propose improvements for scenarios where the level of service is deemed unacceptable. This will be achieved using Synchro traffic simulation software, which facilitates the simulation and optimization of interchanges to enhance operational efficiency and safety.

Keywords: interchange, roundabout, traffic signal, Synchro, delay, level of service, traffic volumes, vehicles, simulation, optimization, adjustment

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Authors: Phillip Garrad, Saritha Unnikrishnan

Abstract:

The recent popularity of connected and autonomous vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks have been instigated by both researchers or white-coat hackers and cyber-criminals. As Connected Vehicles move towards full autonomy, the impact of these cyber-attacks also grows. The current research details challenges faced in cybersecurity testing of CAV, including access and cost of the representative test setup. Other challenges faced are lack of experts in the field. Possible solutions to how these challenges can be overcome are reviewed and discussed. From these findings, a software simulated CAV network is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects in penetration testing in other industries. There is an attempt to introduce similar AI models to the software simulation. The expectation from this implementation is to see similar improvements in runtime and efficiency for the CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing

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Authors: Fawaz A. Binsarra, Halim Boussabaine

Abstract:

The notion of complexity science has been attracting the interest of researchers and professionals due to the need of enhancing the efficiency of understanding complex systems dynamic and structure of interactions. In addition, complexity analysis has been used as an approach to investigate complex systems that contains a large number of components interacts with each other to accomplish specific outcomes and emerges specific behavior. The design process is considered as a complex action that involves large number interacted components, which are ranked as design tasks, design team, and the components of the design process. Those three main aspects of the building design process consist of several components that interact with each other as a dynamic system with complex information flow. In this paper, the goal is to uncover the complex structure of information interactions in building design process. The Investigating of Royal Institute of British Architects Plan Of Work 2013 information interactions as a case study to uncover the structure and building design process complexity using network analysis software to model the information interaction will significantly enhance the efficiency of the building design process outcomes.

Keywords: complexity, process, building desgin, Riba, design complexity, network, network analysis

Procedia PDF Downloads 525

Authors: Dariush Jafari, S. Mostafa Nowee

Abstract:

In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: thermodynamic modeling, ANN, solubility, ternary electrolyte system

Procedia PDF Downloads 384

Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

Abstract:

The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

Procedia PDF Downloads 415