Search results for: fuzzy network project

Authors: Mohammad Reza Zamanian

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The construction industry has always been recognized as one of the most dangerous available industries, and the statistics of accidents and injuries resulting from it say that the safety category needs more attention and the arrival of up-to-date technologies in this field. Building information modeling (BIM) is one of the relatively new and applicable technologies in Iran, that the necessity of using it is increasingly evident. The main purposes of this research are to evaluate the feasibility of using this technology in the safety sector of construction projects and to evaluate the effectiveness and operationality of its various applications in this sector. These applications were collected and categorized after reviewing past studies and researches then a questionnaire based on Delphi method criteria was presented to 30 experts who were thoroughly familiar with modeling software and safety guidelines. After receiving and exporting the answers to SPSS software, the validity and reliability of the questionnaire were assessed to evaluate the measuring tools. Fuzzy logic is a good way to analyze data because of its flexibility in dealing with ambiguity and uncertainty issues, and the implementation of the Delphi method in the fuzzy environment overcomes the uncertainties in decision making. Therefore, this method was used for data analysis, and the results indicate the usefulness and effectiveness of BIM in projects and improvement of safety status at different stages of construction. Finally, the applications and the sections discussed were ranked in order of priority for efficiency and effectiveness. Safety planning is considered as the most influential part of the safety of BIM among the four sectors discussed, and planning for the installation of protective fences and barriers to prevent falls and site layout planning with a safety approach based on a 3D model are the most important applications of BIM among the 18 applications to improve the safety of construction projects.

Keywords: building information modeling, safety of construction projects, Delphi method, fuzzy logic

Procedia PDF Downloads 155

Authors: Jong Hoon Kim, Hyun-Soo Lee, Moonseo Park, Min Jeong, Inbeom Lee

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Pre-construction is essential in achieving the success of a construction project. Due to the early involvement of project participants in the construction phase, project managers are able to plan ahead and solve issues well in advance leading to the success of the project and the satisfaction of the client. This research utilizes quantitative data derived from construction management projects in order to identify the relationship between pre-construction, construction schedule, and client satisfaction. A total of 65 construction projects and 93 clients were investigated for this research in an attempt to identify (a) the relationship between pre-construction and schedule reduction, and (b) pre-construction and client loyalty. Based on the quantitative analysis, this research was able to establish a negative correlation based on 65 construction projects between pre-construction and project schedule existed. This finding represents that the more pre-construction is performed for a certain project, the overall construction schedule decreased. Then, to determine the relationship between pre-construction and client satisfaction, Net Promoter Score (NPS) of 93 clients from the 65 projects was utilized. Pre-construction and NPS was further analyzed and a positive correlation was found between the two. This infers that clients tend to be more satisfied with projects with higher ratio of pre-construction than those projects with less pre-construction.

Keywords: client loyalty, NPS, pre-construction, schedule reduction

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Authors: N. Borjalilu, P. Rabiei, A. Enjoo

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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

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Authors: Rashid Mahmood, Muhammad Sufyan, Nasir Ahmed

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The MANETs have lessened transportation and decentralized network. There are numerous basis of routing protocols. We derived the MANETs protocol into three major categories like Reactive, Proactive and hybrid. In these protocols, we discussed only some protocols like Distance Sequenced Distance Vector (DSDV), Ad hoc on Demand Distance Vector (AODV) and Dynamic Source Routing (DSR). The AODV and DSR are both reactive type of protocols. On the other hand, DSDV is proactive type protocol here. We compare these routing protocols for network security estimated by network simulator (NS-2). In this dissertation some parameters discussed such as simulation time, packet size, number of node, packet delivery fraction, push time and speed etc. We will construct all these parameters on routing protocols under suitable conditions for network security measures.

Keywords: DSDV, AODV, DSR NS-2, PDF, push time

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Authors: Sagar Ghos, Andrew E. Elaryan, Syed Ashik Ali, Musharraf Zaman, Mohammed Ashiqur Rahman

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Achieving desired density during construction is an important indicator of pavement quality. Insufficient compaction often compromises pavement performance and service life. Intelligent compaction (IC) is an emerging technology for monitoring compaction quality during the construction of asphalt pavements. This paper aims to provide an overview of findings from four case studies in Oklahoma involving the compaction quality of asphalt pavements, namely SE 44th St project (Project 1) and EOC Turnpike project (Project 2), Highway 92 project (Project 3), and 108th Avenue project (Project 4). For this purpose, an IC technology, the intelligent compaction analyzer (ICA), developed at the University of Oklahoma, was used to evaluate compaction quality. Collected data include GPS locations, roller vibrations, roller speed, the direction of movement, and temperature of the asphalt mat. The collected data were analyzed using a widely used software, VETA. The average densities for Projects 1, 2, 3 and 4, were found as 89.8%, 91.50%, 90.7% and 87.5%, respectively. The maximum densities were found as 94.6%, 95.8%, 95.9%, and 89.7% for Projects 1, 2, 3, and 4, respectively. It was observed that the ICA estimated densities correlated well with the field core densities. The ICA results indicated that at least 90% of the asphalt mats were subjected to at least two roller passes. However, the number of passes required to achieve the desired density (94% to 97%) differed from project to project depending on the underlying layer. The results of these case studies show both opportunities and challenges in using IC for monitoring compaction quality during construction in real-time.

Keywords: asphalt pavement construction, density, intelligent compaction, intelligent compaction analyzer, intelligent compaction measure value

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a combination of linguistic variables, fuzzy numbers, and by using defuzzification process. The results show that the designed evaluation method creates suitable mechanism in order to improve the performance of the knowledge-based system.

Keywords: case-based reasoning, fuzzy number, legal decision-support system, linguistic variable, rule-based reasoning, system evaluation

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Emanuele A. Solagna, Ricardo S, Tozetto, Roberto dos S. Rabello

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Nowadays, physical processes are becoming digitized by the evolution of communication, sensing and storage technologies which promote the development of smart cities. The evolution of this technology has generated multiple challenges related to the generation of big data and the active participation of electronic devices in society. Thus, devices can send information that is captured and processed over large areas, but there is no guarantee that all the obtained data amount will be effectively stored and correctly persisted. Because, depending on the technology which is used, there are parameters that has huge influence on the full delivery of information. This article aims to characterize the project, currently under development, of a platform that based on data science will perform a performance and effectiveness evaluation of an industrial network that implements LoRaWAN technology considering its main parameters configuration relating these parameters to the information loss.

Keywords: Internet of Things, LoRa, LoRaWAN, smart cities

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Authors: Ogwueleka Francisca Nonyelum, Jiya Muhammad

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Poor communication between the victims of the burglaries, road and fire accidents and the agencies, and lack of quick emergency response by the agencies is solved through Machine-to-Machine (M2M) communication. A distress caller is expected to make a call through a network to the respective agency for emergency response but due to some challenges, this often becomes arduous and futile. This research puts forth an Internet-based architecture for Machine-to-Machine (M2M) communication to enhance information dissemination in National Public Security Communication System (NPSCS) network. M2M enables the flow of data between machines and machines and ultimately machines and people with information flowing from a machine over a network, and then through a gateway to a system where it is reviewed and acted on. The research findings showed that Internet-based architecture for M2M communication is most suitable for deployment of a public security network which will allow machines to use Internet to talk to each other.

Keywords: machine-to-machine (M2M), internet-based architecture, network, gateway

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Authors: Talha Ali Khan

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This paper presents an adaptive neuro-fuzzy interference system (ANFIS), which is applied to a hybrid stepper motor (HSM) to regulate its speed. The dynamic response of the HSM with the ANFIS controller is studied during the starting process and under different load disturbance. The effectiveness of the proposed controller is compared with that of the conventional PI controller. The proposed method solves the problem of nonlinearities and load changes of the HSM drives. The proposed controller ensures fast and precise dynamic response with an excellent steady state performance. Matlab/Simulink program is used for this dynamic simulation study.

Keywords: stepper motor, hybrid, ANFIS, speed control

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Authors: Germán Díaz Flórez, Carlos Alberto Olvera Olvera, Domingo José Gómez Meléndez, Francisco Eneldo López Monteagudo

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In recent decades, population growth has exerted great pressure on natural resources. Two of the most scarce and difficult to obtain resources, arable land, and water, are closely interrelated, to the satisfaction of the demand for food production. In Mexico, the agricultural sector uses more than 70% of water consumption. Therefore, maximize the efficiency of current production systems is inescapable. It is essential to utilize techniques and tools that will enable us to the significant savings of water, labor and fertilizer. In this study, we present a production module of hydroponic green forage (HGF), which is a viable alternative in the production of livestock feed in the semi-arid and arid zones. The equipment in addition to having a forage production module, has a climate and irrigation control system that operated with photovoltaics. The climate control, irrigation and power management is based on fuzzy control techniques. The fuzzy control provides an accurate method in the design of controllers for nonlinear dynamic physical phenomena such as temperature and humidity, besides other as lighting level, aeration and irrigation control using heuristic information. In this working, firstly refers to the production of the hydroponic green forage, suitable weather conditions and fertigation subsequently presents the design of the production module and the design of the controller. A simulation of the behavior of the production module and the end results of actual operation of the equipment are presented, demonstrating its easy design, flexibility, robustness and low cost that represents this equipment in the primary sector.

Keywords: fuzzy, climate control system, hydroponic green forage, forage production module

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Authors: Praveen Battula

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Any high performance car has the tendency to over steer and Understeer under slippery conditions, An Electronic Stability Control System is needed under these conditions to regulate the steering of the car. It uses Anti-Lock Braking System (ABS) and Traction Control and Wheel Speed Sensor, Steering Angle Sensor, Rotational Speed Sensors to correct the problems. The focus of this paper is to improve the driving dynamics and safety by controlling the forces applied on each wheel. ESC Control the Yaw Stability, traction controls the Roll Stability, where actually the vehicle slip rate and lateral acceleration is controlled. ESC uses differential braking on all four brakes independently to control the vehicle’s motion. A mathematical model is developed in Simulink for the FlexRay based Electronic Stability Control. Vehicle steering is developed using Neuro Fuzzy Logic Controller. 7 Degrees of Freedom Vehicle Model is used as a Plant Model using dSpace autobox. The Performance of the system is assessed using two different road Scenarios, Vehicle Control under standard maneuvering conditions. The entire system is set using Dspace Control Desk. Results are provided by comparison of how a Vehicle with and without Electronic Stability Control which shows an improved performance in control.

Keywords: ESC, flexray, chassis control, steering, neuro fuzzy, vehicle dynamics

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Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

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Authors: Md. Moniruzzaman, Thirayoot Limanond

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Being the most visible indicator, the transport system of a city points out how developed the city is. Dhaka megacity holds a mixed composition of motorized and non-motorized modes of transport and the number of vehicle figure is escalating over times. And this obviously poses associated environmental costs like air pollution, noise etc. which is degrading the quality of life in the city. Eventually sustainable transport or more importantly green transport from environmental point of view has become a prime choice to the transport professionals in order to cope up the crisis. Currently the city authority is planning to execute such sustainable transport systems that could serve the pressing demand of the present and meet the future needs effectively. This study focuses on the selection and evaluation of green transportation systems among potential alternatives on a priority basis. In this paper, Fuzzy TOPSIS - a multi-criteria decision method is presented to find out the most prioritized alternative. In the first step, Twenty-one individual specific criteria for sustainability assessment are selected. In the following step, experts provide linguistic ratings to the potential alternatives with respect to the selected criteria. The approach is used to generate aggregate scores for sustainability assessment and selection of the best alternative. In the third step, a sensitivity analysis is performed to understand the influence of criteria weights on the decision making process. The key strength of fuzzy TOPSIS approach is its practical applicability having a generation of good quality solution even under uncertainty.

Keywords: green transport, multi-criteria decision approach, urban transportation system, sustainability assessment, fuzzy theory, uncertainty

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Authors: Pallavi Bhogaram, Xiaolong Wu, Min He, Onyedikachi Okenwa

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A transportation network is a realization of a spatial network, describing a structure which permits either vehicular movement or flow of some commodity. Examples include road networks, railways, air routes, pipelines, and many more. The transportation network plays a vital role in maintaining the vigor of the nation’s economy. Hence, ensuring the network stays resilient all the time, especially in the face of challenges such as heavy traffic loads and large scale natural disasters, is of utmost importance. In this paper, we used the Neo4j application to develop the graph. Neo4j is the world's leading open-source, NoSQL, a native graph database that implements an ACID-compliant transactional backend to applications. The Southern California network model is developed using the Neo4j application and obtained the most critical and optimal nodes and paths in the network using centrality algorithms. The edge betweenness centrality algorithm calculates the critical or optimal paths using Yen's k-shortest paths algorithm, and the node betweenness centrality algorithm calculates the amount of influence a node has over the network. The preliminary study results confirm that the Neo4j application can be a suitable tool to study the important nodes and the critical paths for the major congested metropolitan area.

Keywords: critical path, transportation network, connectivity reliability, network model, Neo4j application, edge betweenness centrality index

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Authors: Amruta Rout, Golak Bihari Mahanta, Gunji Bala Murali, Bibhuti Bhusan Biswal, B. B. V. L. Deepak

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The use of industrial robots for performing welding operation is one of the chief sign of contemporary welding in these days. The weld joint parameter and weld process parameter modeling is one of the most crucial aspects of robotic welding. As weld process parameters affect the weld joint parameters differently, a multi-objective optimization technique has to be utilized to obtain optimal setting of weld process parameter. In this paper, a hybrid optimization technique, i.e., Principal Component Analysis (PCA) combined with fuzzy logic has been proposed to get optimal setting of weld process parameters like wire feed rate, welding current. Gas flow rate, welding speed and nozzle tip to plate distance. The weld joint parameters considered for optimization are the depth of penetration, yield strength, and ultimate strength. PCA is a very efficient multi-objective technique for converting the correlated and dependent parameters into uncorrelated and independent variables like the weld joint parameters. Also in this approach, no need for checking the correlation among responses as no individual weight has been assigned to responses. Fuzzy Inference Engine can efficiently consider these aspects into an internal hierarchy of it thereby overcoming various limitations of existing optimization approaches. At last Taguchi method is used to get the optimal setting of weld process parameters. Therefore, it has been concluded the hybrid technique has its own advantages which can be used for quality improvement in industrial applications.

Keywords: robotic arc welding, weld process parameters, weld joint parameters, principal component analysis, fuzzy logic, Taguchi method

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Authors: Faribaebrahimi, Mehdi Ghorbani, Mohsen Mohsenisaravi

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Ecosystem management is complex because of natural and human issues. To cope with this complexity water governance is recommended since it involves all stakeholders including people, governmental and non-governmental organization who related to environmental systems. Water governance emphasizes on water co-management through consideration of all the stakeholders in the form of social and organizational network. In this research, to illustrate indicators of water governance in Dorood watershed, in Shemiranat region of Iran, social network analysis had been applied. The results revealed that social cohesion among pastoralists in Dorood is medium because of trust links, while link sustainability is weak to medium. According to the results, some pastoralists have high social power and therefore are key actors in the utilization network, regarding to centrality index and trust links. The results also demonstrated that Agricultural Development Office and (Shemshak-Darbandsar Islamic) Council are key actors in rangeland co-management, based on centrality index in rangeland institutional network at regional scale in Shemiranat district.

Keywords: social network analysis, water governance, organizational network, water co-management

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Authors: Colette Malyack, Pius Egbelu

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Business-to-Customer (B2C) delivery options have improved to meet increased demand in recent years. The change in end users has forced logistics networks to focus on customer service and sentiment that would have previously been the priority of the company or organization of origin. This has led to increased pressure on logistics companies to extend traditional B2B networks into a B2C solution while accommodating additional costs, roadblocks, and customer sentiment; the result has been the creation of the omnichannel delivery network encompassing a number of traditional and modern methods of package delivery. In this paper the many solutions within the omnichannel delivery network are defined and discussed. It can be seen through this analysis that the omnichannel delivery network can be applied to reduce the complexity of package delivery and provide customers with more options. Applied correctly the result is a reduction in cost to the logistics company over time, even with an initial increase in cost to obtain the technology.

Keywords: network planning, last mile delivery, omnichannel delivery network, omnichannel logistics

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Authors: Mehran Dizbadi, Daniyal Safarzadeh, Behrooz Arastoo, Ansgar Brunn

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Rapid and uncontrolled expansion of cities has led to unplanned aerial development. In this way, modeling and predicting the urban growth of a city helps decision-makers. In this study, the aspect of sustainable urban development has been studied for the city of Mashhad. In general, the prediction of urban aerial development is one of the most important topics of modern town management. In this research, using the Cellular Automaton (CA) model developed for geo data of Geographic Information Systems (GIS) and presenting a simple and powerful model, a simulation of complex urban processes has been done.

Keywords: urban modeling, sustainable development, fuzzy cellular automaton, geo-information system

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Authors: Jesus Carretero, Mario Vasile, Guillermo Izquierdo, Javier Garcia-Blas

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Currently, there is a so called ‘identity crisis’ in cybersecurity caused by the substantial security, privacy and usability shortcomings encountered in existing systems for identity management. Federated Identity Management (FIM) could be solution for this crisis, as it is a method that facilitates management of identity processes and policies among collaborating entities without enforcing a global consistency, that is difficult to achieve when there are ID legacy systems. To cope with this problem, the Connecting Europe Facility (CEF) initiative proposed in 2014 a federated solution in anticipation of the adoption of the Regulation (EU) N°910/2014, the so-called eIDAS Regulation. At present, a network of eIDAS Nodes is being deployed at European level to allow that every citizen recognized by a member state is to be recognized within the trust network at European level, enabling the consumption of services in other member states that, until now were not allowed, or whose concession was tedious. This is a very ambitious approach, since it tends to enable cross-border authentication of Member States citizens without the need to unify the authentication method (eID Scheme) of the member state in question. However, this federation is currently managed by member states and it is initially applied only to citizens and public organizations. The goal of this paper is to present the results of a European Project, named eID@Cloud, that focuses on the integration of eID in 5 cloud platforms belonging to authentication service providers of different EU Member States to act as Service Providers (SP) for private entities. We propose an initiative based on a private eID Scheme both for natural and legal persons. The methodology followed in the eID@Cloud project is that each Identity Provider (IdP) is subscribed to an eIDAS Node Connector, requesting for authentication, that is subscribed to an eIDAS Node Proxy Service, issuing authentication assertions. To cope with high loads, load balancing is supported in the eIDAS Node. The eID@Cloud project is still going on, but we already have some important outcomes. First, we have deployed the federation identity nodes and tested it from the security and performance point of view. The pilot prototype has shown the feasibility of deploying this kind of systems, ensuring good performance due to the replication of the eIDAS nodes and the load balance mechanism. Second, our solution avoids the propagation of identity data out of the native domain of the user or entity being identified, which avoids problems well known in cybersecurity due to network interception, man in the middle attack, etc. Last, but not least, this system allows to connect any country or collectivity easily, providing incremental development of the network and avoiding difficult political negotiations to agree on a single authentication format (which would be a major stopper).

Keywords: cybersecurity, identity federation, trust, user authentication

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Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das

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Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.

Keywords: information diffusion, personality and values, social network analysis, twitter mentions network

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Authors: Cristina Costa-Lobo, Sandra Fernandes, Miguel Magalhães, José Dinis-Carvalho, Alfredo Regueiro, Ana Carvalho

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This paper is a report on the findings of the construction and the validation of a questionnaire monetized in a portuguese higher education context with undergraduate students. The Questionnaire for the Evaluation of Entrepreneurship Project Psychopedagogical Practices consists of six scales: Critical appraisal of the project, Developed Learning and Skills, Teamwork, Teacher and Tutor Roles, Evaluation of Student Performance, and Project Effectiveness as a Teaching-Learning Methodology. The proceedings of its construction are analyzed, and the validity and internal consistency analysis are described. Findings indicate good indicators of validity, good fidelity and an interpretable factorial structure.

Keywords: entrepreneurship project, higher education, psychopedagogical practices, teacher and tutor roles

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

Procedia PDF Downloads 287

Authors: Patrick J. Kerpan, Ryan C. Koop, Margaret M. Walker, Chris P. Swan

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The User Datagram Protocol (UDP) multicast is a vital part of data center networking that is being left out of major cloud computing providers' network infrastructure. Enterprise users rely on multicast, and particularly UDP multicast to create and connect vital business operations. For example, UPD makes a variety of business functions possible from simultaneous content media updates, High-Performance Computing (HPC) grids, and video call routing for massive open online courses (MOOCs). Essentially, UDP multicast's technological slight is causing a huge effect on whether companies choose to use (or not to use) public cloud infrastructure as a service (IaaS). Allowing the ‘chatty’ UDP multicast protocol inside a cloud network could have a serious impact on the performance of the cloud as a whole. Cloud IaaS providers solve the issue by disallowing all UDP multicast. But what about enterprise use cases for multicast applications in organizations that want to move to the cloud? To re-allow multicast traffic, enterprises can build a layer 3 - 7 network over the top of a data center, private cloud, or public cloud. An overlay network simply creates a private, sealed network on top of the existing network. Overlays give complete control of the network back to enterprise cloud users the freedom to manage their network beyond the control of the cloud provider’s firewall conditions. The same logic applies if for users who wish to use IPsec or BGP network protocols inside or connected into an overlay network in cloud IaaS.

Keywords: cloud computing, protocols, UDP multicast, virtualization

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Authors: Jirarat Teeravaraprug, Usawadee Inklay

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This paper gave an attempt in prioritizing information technologies that organizations should give concentration. The case study was organizations in the automotive assembly industry in Thailand. Data were first collected to gather all information technologies known and used in the automotive assembly industry in Thailand. Five experts from the industries were surveyed based on the concept of fuzzy DEMATEL. The information technologies were categorized into six groups, which were communication, transaction, planning, organization management, warehouse management, and transportation. The cause groups of information technologies for each group were analysed and presented. Moreover, the relationship between the used and the significant information technologies was given. Discussions based on the used information technologies and the research results are given.

Keywords: information technology, automotive assembly industry, fuzzy DEMATEL

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Authors: Mehrzad Mohabbi Yadollahi, Ramazan Demirboğa, Majid Atashafrazeh

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Geopolymers are highly complex materials which involve many variables which makes modeling its properties very difficult. There is no systematic approach in mix design for Geopolymers. Since the amounts of silica modulus, Na2O content, w/b ratios and curing time have a great influence on the compressive strength an ANFIS (Adaptive neuro fuzzy inference system) method has been established for predicting compressive strength of ground pumice based Geopolymers and the possibilities of ANFIS for predicting the compressive strength has been studied. Consequently, ANFIS can be used for geopolymer compressive strength prediction with acceptable accuracy.

Keywords: geopolymer, ANFIS, compressive strength, mix design

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Authors: N. Ould cherchali, M. S. Boucherit, L. Barazane, A. Morsli

Abstract:

Photovoltaic power is widely used to supply isolated or unpopulated areas (lighting, pumping, etc.). Great advantage is that this source is inexhaustible, it offers great safety in use and it is clean. But the dynamic models used to describe a photovoltaic system are complicated and nonlinear and due to nonlinear I-V and P–V characteristics of photovoltaic generators, a maximum power point tracking technique (MPPT) is required to maximize the output power. In this paper, two online techniques of maximum power point tracking using robust controller for photovoltaic systems are proposed, the first technique use fuzzy logic controller (FLC) and the second use sliding mode controller (SMC) for photovoltaic systems. The two maximum power point tracking controllers receive the partial derivative of power as inputs, and the output is the duty cycle corresponding to maximum power. A Photovoltaic generator with Boost converter is developed using MATLAB/Simulink to verify the preferences of the proposed techniques. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller

Procedia PDF Downloads 533

Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

Abstract:

Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA

Procedia PDF Downloads 538

Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

Abstract:

The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis

Procedia PDF Downloads 306