Search results for: analytic network process
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18932

Search results for: analytic network process

17522 Tomato-Weed Classification by RetinaNet One-Step Neural Network

Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

Abstract:

The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

Procedia PDF Downloads 89
17521 Effects of Compensation on Distribution System Technical Losses

Authors: B. Kekezoglu, C. Kocatepe, O. Arikan, Y. Hacialiefendioglu, G. Ucar

Abstract:

One of the significant problems of energy systems is to supply economic and efficient energy to consumers. Therefore studies has been continued to reduce technical losses in the network. In this paper, the technical losses analyzed for a portion of European side of Istanbul MV distribution network for different compensation scenarios by considering real system and load data and results are presented. Investigated system is modeled with CYME Power Engineering Software and optimal capacity placement has been proposed to minimize losses.

Keywords: distribution system, optimal capacitor placement, reactive power compensation, technical losses

Procedia PDF Downloads 656
17520 Imputation of Urban Movement Patterns Using Big Data

Authors: Eusebio Odiari, Mark Birkin, Susan Grant-Muller, Nicolas Malleson

Abstract:

Big data typically refers to consumer datasets revealing some detailed heterogeneity in human behavior, which if harnessed appropriately, could potentially revolutionize our understanding of the collective phenomena of the physical world. Inadvertent missing values skew these datasets and compromise the validity of the thesis. Here we discuss a conceptually consistent strategy for identifying other relevant datasets to combine with available big data, to plug the gaps and to create a rich requisite comprehensive dataset for subsequent analysis. Specifically, emphasis is on how these methodologies can for the first time enable the construction of more detailed pictures of passenger demand and drivers of mobility on the railways. These methodologies can predict the influence of changes within the network (like a change in time-table or impact of a new station), explain local phenomena outside the network (like rail-heading) and the other impacts of urban morphology. Our analysis also reveals that our new imputation data model provides for more equitable revenue sharing amongst network operators who manage different parts of the integrated UK railways.

Keywords: big-data, micro-simulation, mobility, ticketing-data, commuters, transport, synthetic, population

Procedia PDF Downloads 212
17519 Civic Participation in Context of Political Transformation: Case of Argentina

Authors: Kirill Neverov

Abstract:

In the paper is considered issues of civic participation in context of changing political landscape of Argentina. Last two years, this South American country faced a drastic change of political course. Pro-peronist, left-oriented administration of Christina Fernandez de Kirchner were replaced by right of center Mauricio Macri's one. The study is focused on inclusive policy in conditions of political transformations. We use network analysis to figure out which actors are involved in participation and to describe connections between them. As a resuflt, we plan to receive map of transactions which form inclusive policy in Argentina.

Keywords: civic participation, Argentina, political transformation, network analysis

Procedia PDF Downloads 192
17518 Flowsheet Development, Simulation and Optimization of Carbon-Di-Oxide Removal System at Natural Gas Reserves by Aspen–Hysys Process Simulator

Authors: Mohammad Ruhul Amin, Nusrat Jahan

Abstract:

Natural gas is a cleaner fuel compared to the others. But it needs some treatment before it is in a state to be used. So natural gas purification is an integral part of any process where natural gas is used as raw material or fuel. There are several impurities in natural gas that have to be removed before use. CO2 is one of the major contaminants. In this project we have removed CO2 by amine process by using MEA solution. We have built up the whole amine process for removing CO2 in Aspen Hysys and simulated the process. At the end of simulation we have got very satisfactory results by using MEA solution for the removal of CO2. Simulation result shows that amine absorption process enables to reduce CO2 content from NG by 58%. HYSYS optimizer allowed us to get a perfect optimized plant. After optimization the profit of existing plant is increased by 2.34 %.Simulation and optimization by Aspen-HYSYS simulator makes available us to enormous information which will help us to further research in future.

Keywords: Aspen–Hysys, CO2 removal, flowsheet development, MEA solution, natural gas optimization

Procedia PDF Downloads 480
17517 Smartphones in the (Class) Room in Pandemic and Post-pandemic Times: a Study in an Ecological Perspective

Authors: Junia Braga, Antonio carlos Martins, Marcos Racilan

Abstract:

Drawing on the ecological approach, this paper reports a qualitative study that aims to understand how mobile technologies were integrated during the pandemic in the context of language teaching and the use of these technologies in post-pandemic times. Seventy-six teachers answered a questionnaire about their experiences. The findings show how the network with peers scaffolded this experience and played a crucial role in their appropriation of those technologies. They also suggest that this network may have contributed to the normalisation of digital technology use.

Keywords: ecological perspective, language teaching, mobile technologies, teacher education

Procedia PDF Downloads 86
17516 A Deep Learning Approach to Online Social Network Account Compromisation

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

Abstract:

The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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17515 Notes on Frames in Weighted Hardy Spaces and Generalized Weighted Composition Operators

Authors: Shams Alyusof

Abstract:

This work is to enrich the studies of the frames due to their prominent role in pure mathematics as well as in applied mathematics and many applications in computer science and engineering. Recently, there are remarkable studies of operators that preserve frames on some spaces, and this research could be considered as an extension of such studies. Indeed, this paper is to we characterize weighted composition operators that preserve frames in weighted Hardy spaces on the open unit disk. Moreover, it shows that this characterization does not apply to generalized weighted composition operators on such spaces. Nevertheless, this study could be extended to provide more specific characterizations.

Keywords: frames, generalized weighted composition operators, weighted Hardy spaces, analytic functions

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17514 Training the Hospitality Entrepreneurship on the Account of Constructing Nascent Entrepreneurial Competence

Authors: Ching-Hsu Huang, Yao-Ling Liu

Abstract:

Over the past several decades there has been considerable research on the topics of entrepreneurship education and nascent entrepreneurial competence. The purpose of this study is to explore the nascent entrepreneurial competence within entrepreneurship education via the use of three studies. It will be a three-phrases longitudinal study and the effective plan will combine the qualitative and quantitative mixed research methodology in order to understand the issues of nascent entrepreneurship and entrepreneurial competence in hospitality industry in Taiwan. In study one, the systematic literature reviews and twelve nascent entrepreneurs who graduated from hospitality management department will be conducted simultaneously to construct the nascent entrepreneurial competence indicators. Nine subjects who are from industry, government, and academia will be the decision makers in terms of forming the systematic nascent entrepreneurial competence indicators. The relative importance of indicators to each decision maker will be synthesized and compared using the Analytic Hierarchy Process method. According to the results of study one, this study will develop the teaching module of nascent hospitality entrepreneurship. It will include the objectives, context, content, audiences, assessment, pedagogy and outcomes. Based on the results of the second study, the quasi-experiment will be conducted in third study to explore the influence of nascent hospitality entrepreneurship teaching module on learners’ learning effectiveness. The nascent hospitality entrepreneurship education program and entrepreneurial competence will be promoted all around the hospitality industry and vocational universities. At the end, the implication for designing the nascent hospitality entrepreneurship teaching module and training programs will be suggested for the nascent entrepreneurship education. All of the proposed hypotheses will be examined and major finding, implication, discussion, and recommendations will be provided for the government and education administration in hospitality field.

Keywords: entrepreneurial competence, hospitality entrepreneurship, nascent entrepreneurial, training in hospitality entrepreneurship

Procedia PDF Downloads 225
17513 Exploring the Link between Intangible Capital and Urban Economic Development: The Case of Three UK Core Cities

Authors: Melissa Dickinson

Abstract:

In the context of intense global competitiveness and urban transformations, today’s cities are faced with enormous challenges. There is increasing pressure among cities and regions to respond promptly and efficiently to fierce market progressions, to offer a competitive advantage, higher flexibility, and to be pro-active in creating future markets. Consequently, competition among cities and regions within the dynamics of a worldwide spatial economic system is growing fiercer, amplifying the importance of intangible capital in shaping the competitive and dynamic economic performance of organisations and firms. Accordingly, this study addresses how intangible capital influences urban economic development within an urban environment. Despite substantial research on the economic, and strategic determinants of urban economic development this multidimensional phenomenon remains to be one of the greatest challenges for economic geographers. The research provides a unique contribution, exploring intangible capital through the lenses of entrepreneurial capital and social-network capital. Drawing on business surveys and in-depth interviews with key stakeholders in the case of the three UK Core Cities Birmingham, Bristol and Cardiff. This paper critically considers how entrepreneurial capital and social-network capital is a crucial source of competitiveness and urban economic development. This paper deals with questions concerning the complexity of operationalizing ‘network capital’ in different urban settings and the challenges that reside in characterising its effects. The paper will highlight the role of institutions in facilitating urban economic development. Particular emphasis will be placed on exploring the roles formal and informal institutions have in delivering, supporting and nurturing entrepreneurial capital and social-network capital, to facilitate urban economic development. Discussions will then consider how institutions moderate and contribute to the economic development of urban areas, to provide implications in terms of future policy formulation in the context of large and medium sized cities.

Keywords: urban economic development, network capital, entrepreneurialism, institutions

Procedia PDF Downloads 262
17512 A Fuzzy Multi-Criteria Model for Sustainable Development of Community-Based Tourism through the Homestay Program in Malaysia

Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

Abstract:

Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

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17511 Experimental Investigation on Freeze-Concentration Process Desalting for Highly Saline Brines

Authors: H. Al-Jabli

Abstract:

Using the freeze-melting process for the disposing of high saline brines was the aim of the paper by confirming the performance estimation of the treatment system. A laboratory bench scale freezing technique test unit was designed, constructed, and tested at Doha Research Plant (DRP) in Kuwait. The principal unit operations that have been considered for the laboratory study are: ice crystallization, separation, washing, and melting. The applied process is characterized as “the secondary-refrigerant indirect freezing”, which is utilizing normal freezing concept. The high saline brine was used as definite feed water, i.e. average TDS of 250,000 ppm. Kuwait desalination plants were carried out in the experimental study to measure the performance of the proposed treatment system. Experimental analysis shows that the freeze-melting process is capable of dropping the TDS of the feed water from 249,482 ppm to 56,880 ppm of the freeze-melting process in the two-phase’s course, whereas overall recovery results of the salt passage and salt rejection are 31.11%, 19.05%, and 80.95%, correspondingly. Therefore, the freeze-melting process is encouraging for the proposed application, as it shows on the results, which approves the process capability of reducing a major amount of the dissolved salts of the high saline brine with reasonable sensible recovery. This process might be reasonable with other brine disposal processes.

Keywords: high saline brine, freeze-melting process, ice crystallization, brine disposal process

Procedia PDF Downloads 255
17510 Synthesis and Characterisation of Starch-PVP as Encapsulation Material for Drug Delivery System

Authors: Nungki Rositaningsih, Emil Budianto

Abstract:

Starch has been widely used as an encapsulation material for drug delivery system. However, starch hydrogel is very easily degraded during metabolism in human stomach. Modification of this material is needed to improve the encapsulation process in drug delivery system, especially for gastrointestinal drug. In this research, three modified starch-based hydrogels are synthesized i.e. Crosslinked starch hydrogel, Semi- and Full- Interpenetrating Polymer Network (IPN) starch hydrogel using Poly(N-Vinyl-Pyrrolidone). Non-modified starch hydrogel was also synthesized as a control. All of those samples were compared as biomaterials, floating drug delivery, and their ability in loading drug test. Biomaterial characterizations were swelling test, stereomicroscopy observation, Differential Scanning Calorimetry (DSC), and Fourier Transform Infrared Spectroscopy (FTIR). Buoyancy test and stereomicroscopy scanning were done for floating drug delivery characterizations. Lastly, amoxicillin was used as test drug, and characterized with UV-Vis spectroscopy for loading drug observation. Preliminary observation showed that Full-IPN has the most dense and elastic texture, followed by Semi-IPN, Crosslinked, and Non-modified in the last position. Semi-IPN and Crosslinked starch hydrogel have the most ideal properties and will not be degraded easily during metabolism. Therefore, both hydrogels could be considered as promising candidates for encapsulation material. Further analysis and issues will be discussed in the paper.

Keywords: biomaterial, drug delivery system, interpenetrating polymer network, poly(N-vinyl-pyrrolidone), starch hydrogel

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17509 Control of Photovoltaic System Interfacing Grid

Authors: Zerzouri Nora

Abstract:

In this paper, author presented the generalities of a photovoltaic system study and simulation. Author inserted the DC-DC converter to raise the voltage level and improve the operation of the PV panel by continuing the operating point at maximum power by using the Perturb and Observe technique (P&O). The connection to the network is made by inserting a three-phase voltage inverter allowing synchronization with the network the inverter is controlled by a PWM control. The simulation results allow the author to visualize the operation of the different components of the system, as well as the behavior of the system during the variation of meteorological values.

Keywords: photovoltaic generator PV, boost converter, P&O MPPT, PWM inverter, three phase grid

Procedia PDF Downloads 101
17508 Analysing Causal Effect of London Cycle Superhighways on Traffic Congestion

Authors: Prajamitra Bhuyan

Abstract:

Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

Procedia PDF Downloads 219
17507 DOS and DDOS Attacks

Authors: Amin Hamrahi, Niloofar Moghaddam

Abstract:

Denial of Service is for denial-of-service attack, a type of attack on a network that is designed to bring the network to its knees by flooding it with useless traffic. Denial of Service (DoS) attacks have become a major threat to current computer networks. Many recent DoS attacks were launched via a large number of distributed attacking hosts in the Internet. These attacks are called distributed denial of service (DDoS) attacks. To have a better understanding on DoS attacks, this article provides an overview on existing DoS and DDoS attacks and major defense technologies in the Internet.

Keywords: denial of service, distributed denial of service, traffic, flooding

Procedia PDF Downloads 376
17506 Evaluation of Reliability, Availability and Maintainability for Automotive Manufacturing Process

Authors: Hamzeh Soltanali, Abbas Rohani, A. H. S. Garmabaki, Mohammad Hossein Abbaspour-Fard, Adithya Thaduri

Abstract:

Toward continuous innovation and high complexity of technological systems, the automotive manufacturing industry is also under pressure to implement adequate management strategies regarding availability and productivity. In this context, evaluation of system’s performance by considering reliability, availability and maintainability (RAM) methodologies can constitute for resilient operation, identifying the bottlenecks of manufacturing process and optimization of maintenance actions. In this paper, RAM parameters are evaluated for improving the operational performance of the fluid filling process. To evaluate the RAM factors through the behavior of states defined for such process, a systematic decision framework was developed. The results of RAM analysis revealed that that the improving reliability and maintainability of main bottlenecks for each filling workstation need to be considered as a priority. The results could be useful to improve operational performance and sustainability of production process.

Keywords: automotive, performance, reliability, RAM, fluid filling process

Procedia PDF Downloads 336
17505 Steady State Analysis of Distribution System with Wind Generation Uncertainity

Authors: Zakir Husain, Neem Sagar, Neeraj Gupta

Abstract:

Due to the increased penetration of renewable energy resources in the distribution system, the system is no longer passive in nature. In this paper, a steady state analysis of the distribution system has been done with the inclusion of wind generation. The modeling of wind turbine generator system and wind generator has been made to obtain the average active and the reactive power injection into the system. The study has been conducted on a IEEE-33 bus system with two wind generators. The present research work is useful not only to utilities but also to customers.

Keywords: distributed generation, distribution network, radial network, wind turbine generating system

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17504 Engineering Topology of Construction Ecology in Urban Environments: Suez Canal Economic Zone

Authors: Moustafa Osman Mohammed

Abstract:

Integration sustainability outcomes give attention to construction ecology in the design review of urban environments to comply with Earth’s System that is composed of integral parts of the (i.e., physical, chemical and biological components). Naturally, exchange patterns of industrial ecology have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. When engineering topology is affecting internal and external processes in system networks, it postulated the valence of the first-level spatial outcome (i.e., project compatibility success). These instrumentalities are dependent on relating the second-level outcome (i.e., participant security satisfaction). Construction ecology approach feedback energy from resources flows between biotic and abiotic in the entire Earth’s ecosystems. These spatial outcomes are providing an innovation, as entails a wide range of interactions to state, regulate and feedback “topology” to flow as “interdisciplinary equilibrium” of ecosystems. The interrelation dynamics of ecosystems are performing a process in a certain location within an appropriate time for characterizing their unique structure in “equilibrium patterns”, such as biosphere and collecting a composite structure of many distributed feedback flows. These interdisciplinary systems regulate their dynamics within complex structures. These dynamic mechanisms of the ecosystem regulate physical and chemical properties to enable a gradual and prolonged incremental pattern to develop a stable structure. The engineering topology of construction ecology for integration sustainability outcomes offers an interesting tool for ecologists and engineers in the simulation paradigm as an initial form of development structure within compatible computer software. This approach argues from ecology, resource savings, static load design, financial other pragmatic reasons, while an artistic/architectural perspective, these are not decisive. The paper described an attempt to unify analytic and analogical spatial modeling in developing urban environments as a relational setting, using optimization software and applied as an example of integrated industrial ecology where the construction process is based on a topology optimization approach.

Keywords: construction ecology, industrial ecology, urban topology, environmental planning

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17503 Routing and Energy Efficiency through Data Coupled Clustering in Large Scale Wireless Sensor Networks (WSNs)

Authors: Jainendra Singh, Zaheeruddin

Abstract:

A typical wireless sensor networks (WSNs) consists of several tiny and low-power sensors which use radio frequency to perform distributed sensing tasks. The longevity of wireless sensor networks (WSNs) is a major issue that impacts the application of such networks. While routing protocols are striving to save energy by acting on sensor nodes, recent studies show that network lifetime can be enhanced by further involving sink mobility. A common approach for energy efficiency is partitioning the network into clusters with correlated data, where the representative nodes simply transmit or average measurements inside the cluster. In this paper, we propose an energy- efficient homogenous clustering (EHC) technique. In this technique, the decision of each sensor is based on their residual energy and an estimate of how many of its neighboring cluster heads (CHs) will benefit from it being a CH. We, also explore the routing algorithm in clustered WSNs. We show that the proposed schemes significantly outperform current approaches in terms of packet delay, hop count and energy consumption of WSNs.

Keywords: wireless sensor network, energy efficiency, clustering, routing

Procedia PDF Downloads 248
17502 Using Cyclic Structure to Improve Inference on Network Community Structure

Authors: Behnaz Moradijamei, Michael Higgins

Abstract:

Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

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17501 Optimal Number and Placement of Vertical Links in 3D Network-On-Chip

Authors: Nesrine Toubaline, Djamel Bennouar, Ali Mahdoum

Abstract:

3D technology can lead to a significant reduction in power and average hop-count in Networks on Chip (NoCs). It offers short and fast vertical links which copes with the long wire problem in 2D NoCs. This work proposes heuristic-based method to optimize number and placement of vertical links to achieve specified performance goals. Experiments show that significant improvement can be achieved by using a specific number of vertical interconnect.

Keywords: interconnect optimization, monolithic inter-tier vias, network on chip, system on chip, through silicon vias, three dimensional integration circuits

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17500 An Artificial Neural Network Model Based Study of Seismic Wave

Authors: Hemant Kumar, Nilendu Das

Abstract:

A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesion class, earthquakes, IMD

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17499 Convolutional Neural Networks versus Radiomic Analysis for Classification of Breast Mammogram

Authors: Mehwish Asghar

Abstract:

Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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17498 Classifying Turbomachinery Blade Mode Shapes Using Artificial Neural Networks

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

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17497 A Three-Step Iterative Process for Common Fixed Points of Three Contractive-Like Operators

Authors: Safeer Hussain Khan, H. Fukhar-ud-Din

Abstract:

The concept of quasi-contractive type operators was given by Berinde and extended by Imoru and Olatinwo. They named this new type as contractive-like operators. On the other hand, Xu and Noo introduced a three-step-one-mappings iterative process which can be seen as a generalization of Mann and Ishikawa iterative processes. Approximating common fixed points has its own importance as it has a direct link with minimization problem. Motivated by this, in this paper, we first extend the iterative process of Xu and Noor to the case of three-step-three-mappings and then prove a strong convergence result using contractive-like operators for this iterative process. In general, this generalizes corresponding results using Mann, Ishikawa and Xu-Noor iterative processes with quasi-contractive type operators. It is to be pointed out that our results can also be proved with iterative process involving error terms.

Keywords: contractive-like operator, iterative process, common fixed point, strong convergence

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17496 A Dynamic Neural Network Model for Accurate Detection of Masked Faces

Authors: Oladapo Tolulope Ibitoye

Abstract:

Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

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17495 Requirements Management in Agile

Authors: Ravneet Kaur

Abstract:

The concept of Agile Requirements Engineering and Management is not new. However, the struggle to figure out how traditional Requirements Management Process fits within an Agile framework remains complex. This paper talks about a process that can merge the organization’s traditional Requirements Management Process nicely into the Agile Software Development Process. This process provides Traceability of the Product Backlog to the external documents on one hand and User Stories on the other hand. It also gives sufficient evidence that the system will deliver the right functionality with good quality in the form of various statistics and reports. In the nutshell, by overlaying a process on top of Agile, without disturbing the Agility, we are able to get synergic benefits in terms of productivity, profitability, its reporting, and end to end visibility to all Stakeholders. The framework can be used for just-in-time requirements definition or to build a repository of requirements for future use. The goal is to make sure that the business (specifically, the product owner) can clearly articulate what needs to be built and define what is of high quality. To accomplish this, the requirements cycle follows a Scrum-like process that mirrors the development cycle but stays two to three steps ahead. The goal is to create a process by which requirements can be thoroughly vetted, organized, and communicated in a manner that is iterative, timely, and quality-focused. Agile is quickly becoming the most popular way of developing software because it fosters continuous improvement, time-boxed development cycles, and more quickly delivering value to the end users. That value will be driven to a large extent by the quality and clarity of requirements that feed the software development process. An agile, lean, and timely approach to requirements as the starting point will help to ensure that the process is optimized.

Keywords: requirements management, Agile

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17494 Micromechanics Modeling of 3D Network Smart Orthotropic Structures

Authors: E. M. Hassan, A. L. Kalamkarov

Abstract:

Two micromechanical models for 3D smart composite with embedded periodic or nearly periodic network of generally orthotropic reinforcements and actuators are developed and applied to cubic structures with unidirectional orientation of constituents. Analytical formulas for the effective piezothermoelastic coefficients are derived using the Asymptotic Homogenization Method (AHM). Finite Element Analysis (FEA) is subsequently developed and used to examine the aforementioned periodic 3D network reinforced smart structures. The deformation responses from the FE simulations are used to extract effective coefficients. The results from both techniques are compared. This work considers piezoelectric materials that respond linearly to changes in electric field, electric displacement, mechanical stress and strain and thermal effects. This combination of electric fields and thermo-mechanical response in smart composite structures is characterized by piezoelectric and thermal expansion coefficients. The problem is represented by unit-cell and the models are developed using the AHM and the FEA to determine the effective piezoelectric and thermal expansion coefficients. Each unit cell contains a number of orthotropic inclusions in the form of structural reinforcements and actuators. Using matrix representation of the coupled response of the unit cell, the effective piezoelectric and thermal expansion coefficients are calculated and compared with results of the asymptotic homogenization method. A very good agreement is shown between these two approaches.

Keywords: asymptotic homogenization method, finite element analysis, effective piezothermoelastic coefficients, 3D smart network composite structures

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17493 Research on Strategies of Building a Child Friendly City in Wuhan

Authors: Tianyue Wan

Abstract:

Building a child-friendly city (CFC) contributes to improving the quality of urbanization. It also forms a local system committed to fulfilling children's rights and development. Yet, the work related to CFC is still at the initial stage in China. Therefore, taking Wuhan, the most populous city in central China, as the pilot city would offer some reference for other cities. Based on the analysis of theories and practice examples, this study puts forward the challenges of building a child-friendly city under the particularity of China's national conditions. To handle these challenges, this study uses four methods to collect status data: literature research, site observation, research inquiry, and semantic differential (SD). And it adopts three data analysis methods: case analysis, geographic information system (GIS) analysis, and analytic hierarchy process (AHP) method. Through data analysis, this study identifies the evaluation system and appraises the current situation of Wuhan. According to the status of Wuhan's child-friendly city, this study proposes three strategies: 1) construct the evaluation system; 2) establish a child-friendly space system integrating 'point-line-surface'; 3) build a digitalized service platform. At the same time, this study suggests building a long-term mechanism for children's participation and multi-subject supervision from laws, medical treatment, education, safety protection, social welfare, and other aspects. Finally, some conclusions of strategies about CFC are tried to be drawn to promote the highest quality of life for all citizens in Wuhan.

Keywords: action plan, child friendly city, construction strategy, urban space

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