Search results for: sensor network design

Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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Authors: Takashi Shimizu, Tomoaki Hashimoto

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A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: optimal control, nonlinear systems, state estimation, Kalman filter

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Authors: Umesh Kumar Singh, Chanchala Joshi

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With increasing dependency on IT infrastructure, the main objective of a system administrator is to maintain a stable and secure network, with ensuring that the network is robust enough against malicious network users like attackers and intruders. Security risk management provides a way to manage the growing threats to infrastructures or system. This paper proposes a framework for risk level estimation which uses vulnerability database National Institute of Standards and Technology (NIST) National Vulnerability Database (NVD) and the Common Vulnerability Scoring System (CVSS). The proposed framework measures the frequency of vulnerability exploitation; converges this measured frequency with standard CVSS score and estimates the security risk level which helps in automated and reasonable security management. In this paper equation for the Temporal score calculation with respect to availability of remediation plan is derived and further, frequency of exploitation is calculated with determined temporal score. The frequency of exploitation along with CVSS score is used to calculate the security risk level of the system. The proposed framework uses the CVSS vectors for risk level estimation and measures the security level of specific network environment, which assists system administrator for assessment of security risks and making decision related to mitigation of security risks.

Keywords: CVSS score, risk level, security measurement, vulnerability category

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Haleh Hamidpour

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Since the seismic damageability of structures is controlled by the inelastic deformation capacities of structural elements, seismic design of structure based on force analogy methods is not appropriate. In recent year, the basic approach of design codes have been changed from force-based approach to displacement-based. In this regard, a Direct Displacement-Based Design (DDBD) and a Performance-Based Plastic Design (PBPD) method are proposed. In this study, the efficiency of these two methods on seismic performance of structures is evaluated through a sample 12-story reinforced concrete moment frame. The building is designed separately based on the DDBD and the PBPD methods. Once again the structure is designed by the traditional force analogy method according to the FEMA P695 regulation. Different design method results in different structural elements. Seismic performance of these three structures is evaluated through nonlinear static and nonlinear dynamic analysis. The results show that the displacement-based design methods accommodate the intended performance objectives better than the traditional force analogy method.

Keywords: direct performance-based design, ductility demands, inelastic seismic performance, yield mechanism

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Authors: Niloofar Zebarjad

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This research aims at finding a tool to provide basketball players with real-time audio feedback on their shooting form in free throw shots. Free throws played a pivotal role in taking the lead in fierce competitions. The major problem in performing an accurate free throw seems to be improper training. Since the arm movement during the free throw shot is complex, the coach or the athlete might miss the movement details during practice. Hence, there is a necessity to create a system that measures arm movements' critical characteristics and control for improper kinematics. The proposed setup in this study quantifies arm kinematics and provides real-time feedback as an audio signal consisting of a gyroscope sensor. Spatial shoulder angle data are transmitted in a mobile application in real-time and can be saved and processed for statistical and analysis purposes. The proposed system is easy to use, inexpensive, portable, and real-time applicable. Objectives: This research aims to modify and control the free throw using audio feedback and determine if and to what extent the new setup reduces errors in arm formations during throws and finally assesses the successful throw rate. Methods: One group of elite basketball athletes and two novice athletes (control and study group) participated in this study. Each group contains 5 participants being studied in three separate sessions over a week. Results: Empirical results showed enhancements in the free throw shooting style, shot pocket (SP), and locked position (LP). The mean values of shoulder angle were controlled on 25° and 45° for SP and LP, respectively, recommended by valid FIBA references. Conclusion: Throughout the experiments, the system helped correct and control the shoulder angles toward the targeted pattern of shot pocket (SP) and locked position (LP). According to the desired results for arm motion, adding another sensor to measure and control the elbow angle is recommended.

Keywords: audio-feedback, basketball, free-throw, locked-position, motor-control, shot-pocket

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Authors: Thomas Adi Purnomo Sidhi

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The importance of designing a pregnancy interactive information design for a mobile application is felt in order to assist pregnant women to get an easy access of highly credible pregnancy-related information on which often fail to be fulfilled, while it has been a very critical one. Thus, an observation of needs assessment for designing a pregnancy interactive information system design for a mobile application at iOS becomes current objective study. A comparative study of the top five pregnancy interactive information design available at the Apple Store conducted in order to fulfill it. Whilst, an observation of user experiences included for deeper analyzes. Moreover, a literature study conducted to support the arguments that being provided in the current study. The findings, surprisingly, also reveal the advantages of local wisdom in pregnancy that never been attached to those top five applications before.

Keywords: information system design, interactive design, local wisdom, pregnancy

Procedia PDF Downloads 187

Authors: (Ted) Edward Holmberg, Mahdi Abdelguerfi, Elias Ioup

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This research details a coverage measure for evaluating the effectiveness of observer node placements in a spatial bipartite network. This coverage measure can be used to optimize the configuration of stationary or mobile spatially oriented observer nodes, or a hybrid of the two, over time in order to fully utilize their capabilities. To demonstrate the practical application of this approach, we construct a SpatioTemporal Bipartite Network (STBN) using real-time crime center (RTCC) camera nodes and NOPD calls for service (CFS) event nodes from New Orleans, La (NOLA). We use the coverage measure to identify optimal placements for moving mobile RTCC camera vans to improve coverage of vulnerable areas based on temporal patterns.

Keywords: coverage measure, mobile node dynamics, Monte Carlo simulation, observer nodes, observable nodes, spatiotemporal bipartite knowledge graph, temporal spatial analysis

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Authors: Adkham Paiziev, Fikrat Kerimov

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Near Infrared Spectroscopy (NIRS) is one of the biophotonic techniques which can be used to monitor oxygenation and hemodynamics in a variety of human tissues, including skeletal muscle. In the present work, we are offering tissue oximetry (OxyPrem) to measure hemodynamic parameters of skeletal muscles in rest and exercise. Purpose: - To elaborate the new wireless, portable, noninvasive, wearable NIRS device to measure skeletal muscle oxygenation during exercise. - To test this device on brachioradialis muscle of wrestler volunteers by using combined method of arterial occlusion (AO) and NIRS (AO+NIRS). Methods: Oxyprem NIRS device has been used together with AO test. AO test and Isometric brachioradialis muscle contraction experiments have been performed on one group of wrestler volunteers. ‘Accu- Measure’ caliper (USA) to measure skinfold thickness (SFT) has been used. Results: Elaborated device consists on power supply box, a sensor head and installed ‘Tubis’ software for data acquisition and to compute deoxyhemoglobin ([HHb), oxyhemoglobin ([O2Hb]), tissue oxygenation (StO2) and muscle tissue oxygen consumption (mVO2). Sensor head consists on four light sources with three light emitting diodes with nominal wavelengths of 760 nm, 805 nm, and 870 nm, and two detectors. AO and isometric voluntary forearm muscle contraction (IVFMC) on five healthy male subjects (23,2±0.84 in age, 0.43±0.05cm of SFT ) and four female subjects (22.0±1.0 in age and 0.24±0.04 cm SFT) has been measured. mVO2 for control group has been calculated (-0.65%/sec±0.07) for male and -0.69%/±0.19 for female subjects). Tissue oxygenation index for wrestlers in average about 75% whereas for control group StO2 =63%. Second experiment was connected with quality monitoring muscle activity during IVFMC at 10%,30% and 50% of MVC. It has been shown, that the concentration changes of HbO2 and HHb positively correlated to the contraction intensity. Conclusion: We have presented a portable multi-channel wireless NIRS device for real-time monitoring of muscle activity. The miniaturized NIRS sensor and the usage of wireless communication make the whole device have a compact-size, thus can be used in muscle monitoring.

Keywords: skeletal muscle, oxygenation, instrumentation, near infrared spectroscopy

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Authors: Thulane Paepae, Tumisang Seodigeng

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This paper demonstrates the use of a method of synthesizing process flowsheets using a graphical tool called the GH-plot and in particular, to look at how it can be used to compare the reactions of a combined simultaneous process with regard to their thermodynamics. The technique uses fundamental thermodynamic principles to allow the mass, energy and work balances locate the attainable region for chemical processes in a reactor. This provides guidance on what design decisions would be best suited to developing new processes that are more effective and make lower demands on raw material and energy usage.

Keywords: attainable regions, dimethyl ether, optimal reaction network, GH Space

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Authors: S. Sudhharani

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Energy distribution networks are the main link between the energy industry and consumers and are subject to the most scrutiny and testing of any category. As a result, it is important to monitor energy levels during the distribution phase. Power distribution networks, on the other hand, remain subject to common problems, including voltage breakdown, power outages, harmonics, and capacitor switching, all of which disrupt sinusoidal waveforms and reduce the quality and power of the network. Using power appliances in the form of custom power appliances is one way to deal with energy quality issues. Dynamic Voltage Restorer (DVR), integrated with network and distribution networks, is one of these devices. At the same time, by injecting voltage into the system, it can adjust the voltage amplitude and phase in the network. In the form of injections and three-phase syncing, it is used to compensate for the difficulty of energy quality. This article examines the recent use of DVR for power compensation and provides data on the control of each DVR in distribution networks.

Keywords: dynamic voltage restorer (DVR), power quality, distribution networks, control systems(PWM)

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Authors: P. G. F. Siqueira, N. G. S. Almeida, P. M. A. Stemler, P. R. Cetlin, M. T. P. Aguilar

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The processing of metals through Equal Channel Angular Pressing (ECAP) leads to their remarkable strengthening. The ECAP dies control the amount of strain imposed on the material through its geometry, especially through the angle between the die channels, and thus the microstructural and mechanical properties evolution of the material. The present study describes the design of an ECAP die whose utilization and maintenance are facilitated, and that also controls the eventual undesired flow of the material during processing. The proposed design was validated through numerical simulations procedures using commercial software. The die was manufactured according to the present design and tested. Tests using aluminum alloys also indicated to be suitable for the processing of higher strength alloys.

Keywords: ECAP, mechanical design, numerical methods, SPD

Procedia PDF Downloads 139

Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Bander Alzahrani, Mohammed Alreshoodi

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Information-centric networking (ICN) using architectures such as the Publish-Subscribe Internet Technology (PURSUIT) has been proposed as a new networking model that aims at replacing the current used end-centric networking model of the Internet. This emerged model focuses on what is being exchanged rather than which network entities are exchanging information, which gives the control plane functions such as routing and host location the ability to be specified according to the content items. The forwarding plane of the PURSUIT ICN architecture uses a simple and light mechanism based on Bloom filter technologies to forward the packets. Although this forwarding scheme solve many problems of the today’s Internet such as the growth of the routing table and the scalability issues, it is vulnerable to brute force attacks which are starting point to distributed- denial-of-service (DDoS) attacks. In this work, we design and analyze a novel source-routing and information delivery technique that keeps the simplicity of using Bloom filter-based forwarding while being able to deter different attacks such as denial of service attacks at the ingress of the network. To achieve this, special forwarding nodes called Edge-FW are directly attached to end user nodes and used to perform a security test for malicious injected random packets at the ingress of the path to prevent any possible attack brute force attacks at early stage. In this technique, a core entity of the PURSUIT ICN architecture called topology manager, that is responsible for finding shortest path and creating a forwarding identifiers (FId), uses a cryptographically secure hash function to create a 64-bit hash, h, over the formed FId for authentication purpose to be included in the packet. Our proposal restricts the attacker from injecting packets carrying random FIds with a high amount of filling factor ρ, by optimizing and reducing the maximum allowed filling factor ρm in the network. We optimize the FId to the minimum possible filling factor where ρ ≤ ρm, while it supports longer delivery trees, so the network scalability is not affected by the chosen ρm. With this scheme, the filling factor of any legitimate FId never exceeds the ρm while the filling factor of illegitimate FIds cannot exceed the chosen small value of ρm. Therefore, injecting a packet containing an FId with a large value of filling factor, to achieve higher attack probability, is not possible anymore. The preliminary analysis of this proposal indicates that with the designed scheme, the forwarding function can detect and prevent malicious activities such DDoS attacks at early stage and with very high probability.

Keywords: forwarding identifier, filling factor, information centric network, topology manager

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Authors: He Lingsong, Wang Junfeng, Tan Qiong, Xu Jiang

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The paper describes efforts on reconstruction methods of engineering testing and measurement technology course by applying new techniques and applications. Firstly, flipped classroom was introduced. In-class time was used for in-depth discussions and interactions while theory concept teaching was done by self-study course outside of class. Secondly, two hands-on practices of technique applications, including the program design of MATLAB Signal Analysis and the measurement application of Arduino sensor, have been covered in class. Class was transformed from an instructor-centered teaching process into an active student-centered learning process, consisting of the pre-class massive open online course (MOOC), in-class discussion and after-class practice. The third is to change sole written homework to the research-oriented application practice assignments, so as to enhance the breadth and depth of the course.

Keywords: testing and measurement, flipped classroom, MOOC, research-oriented learning, practice-oriented learning

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Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

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Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Q. J. Yang

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This paper presents a case study of geotechnical design of bridge foundations and approaches in hilly granite formation in northern New South Wales of Australia. Firstly, the geological formation and existing cut slope conditions which have high risks of rock fall will be described. The bridge has three spans to be constructed using balanced cantilever method with a middle span of 150 m. After concept design option engineering, it was decided to change from pile foundation to pad footing with ground anchor system to optimize the bridge foundation design. The geotechnical design parameters were derived after two staged site investigations. The foundation design was carried out to satisfy both serviceability limit state and ultimate limit state during construction and in operation. It was found that the pad footing design was governed by serviceability limit state design loading cases. The design of bridge foundation also considered presence of weak rock layer intrusion and a layer of “no core” to ensure foundation stability. The precast mass concrete block system was considered for the retaining walls for the bridge approaches to resolve the constructability issue over hilly terrain. The design considered the retaining wall block sliding stability, while the overturning and internal stabilities are satisfied.

Keywords: pad footing, Hilly formation, stability, block works

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Wei Zheng, Mao Ji, Zhe Hou, Meng Huang, Bo Qi

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The transformer is the key equipment of the power system. Winding deformation is one of the main transformer defects, and timely and effective detection of the transformer winding deformation can ensure the safe and stable operation of the transformer to the maximum extent. When winding deformation occurs, the size, shape and spatial position of the winding will change, which directly leads to the change of magnetic flux leakage distribution. Therefore, it is promising to study the online detection method of the transformer winding deformation based on magnetic flux leakage characteristics, in which the key step is to study the optimal placement method of magnetic flux leakage sensors inside the transformer. In this paper, a simulation model of the transformer winding deformation is established to obtain the internal magnetic flux leakage distribution of the transformer under normal operation and different winding deformation conditions, and the law of change of magnetic flux leakage distribution due to winding deformation is analyzed. The results show that different winding deformation leads to different characteristics of the magnetic flux leakage distribution. On this basis, an optimized placement of magnetic flux leakage sensors inside the transformer is proposed to provide a basis for the online detection method of transformer winding deformation based on the magnetic flux leakage characteristics.

Keywords: magnetic flux leakage, sensor placement method, transformer, winding deformation

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Authors: Fuyuan Ma, Ying Wang, Xin Wang

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Social networks have become breeding grounds for the rapid spread of rumors and malicious information, posing threats to societal stability and causing significant public harm. Existing research focuses on simulating the spread of information and its impact on users through propagation dynamics and applies methods such as greedy approximation strategies to approximate the optimal control solution at the global scale. However, the greedy strategy at the global scale may fall into locally optimal solutions, and the approximate simulation of information spread may accumulate more errors. Therefore, we propose a multi-scale control model for network group behavior, introducing individual and group scales on top of the greedy strategy’s global scale. At the individual scale, we calculate the propagation influence of nodes based on their structural attributes to alleviate the issue of local optimality. At the group scale, we conduct precise propagation simulations to avoid introducing cumulative errors from approximate calculations without increasing computational costs. Experimental results on three real-world datasets demonstrate the effectiveness of our proposed multi-scale model in controlling network group behavior.

Keywords: influence blocking maximization, competitive linear threshold model, social networks, network group behavior

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Authors: Jesús Antonio Puente Fernández, Luis Javier Garcia Villalba

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New trends on streaming videos such as series or films require a high demand of network resources. This fact results in a huge problem within traditional IP networks due to the rigidity of its architecture. In this way, Software Defined Networks (SDN) is a new concept of network architecture that intends to be more flexible and it simplifies the management in networks with respect to the existing ones. These aspects are possible due to the separation of control plane (controller) and data plane (switches). Taking the advantage of this separated control, it is easy to deploy a monitoring tool independent of device vendors since the existing ones are dependent on the installation of specialized and expensive hardware. In this paper, we propose a framework that optimizes the traffic monitoring in SDN networks that decreases the number of monitoring queries to improve the network traffic and also reduces the overload. The performed experiments (with and without the optimization) using a video streaming delivery between two hosts demonstrate the feasibility of our monitoring proposal.

Keywords: optimization, monitoring, software defined networking, statistics, query

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Authors: M. Sarrab, M. Elbasir

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Most of mobile learning applications currently available are developed for the formal education and learning environment. Those applications are characterized by the improvement of the interaction process between instructors and learners to provide more collaboration and flexibility in the learning process. Despite the long history and large amount of research on Instruction design model and mobile learning there is no complete and well defined set of steps to follow in designing mobile learning applications. Based on this scenario, this paper focuses on identifying instruction design phases considerations and influencing factors in developing mobile learning application. This set of instruction design steps includes analysis, design, development, implementation, evaluation and continuous has been built from a literature study with focus on standards for learning and mobile application software quality and guidelines. The effort is part of an Omani-funded research project investigating the development, adoption and dissemination of mobile learning in Oman.

Keywords: instruction design, mobile learning, mobile application

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Authors: Mohammed S. Alqahtani, Paulo J. Bartolo

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External fixation is a common technique for the treatment and stabilization of bone fractures. Different designs have been proposed by companies and research groups, but all of them present limitations such as high weight, not comfortable to use, and not customized to individual patients. This paper proposes a lightweight customized external fixator, overcoming some of these limitations. External fixators are designed using a set of techniques such as medical imaging, CAD modelling, finite element analysis, and full factorial design of experiments. Key design parameters are discussed, and the optimal set of parameters is used to design the final external fixator. Numerical simulations are used to validate design concepts. Results present an optimal external fixation design with weight reduction of 13% without compromising its stiffness and structural integrity. External fixators are also designed to be additively manufactured, allowing to develop a strategy for personalization.

Keywords: computer-aided design modelling, external fixation, finite element analysis, full factorial, personalization

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Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

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Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

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Authors: S. Vignesh, K. S. Rangasamy

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The paper deals with the device capable of detecting and disabling digital cameras. The system locates the camera and then neutralizes it. Every digital camera has an image sensor known as a CCD, which is retro-reflective and sends light back directly to its original source at the same angle. The device shines infrared LED light, which is invisible to the human eye, at a distance of about 20 feet. It then collects video of these reflections with a camcorder. Then the video of the reflections is transferred to a computer connected to the device, where it is sent through image processing algorithms that pick out infrared light bouncing back. Once the camera is detected, the device would project an invisible infrared laser into the camera's lens, thereby overexposing the photo and rendering it useless. Low levels of infrared laser neutralize digital cameras but are neither a health danger to humans nor a physical damage to cameras. We also discuss the simplified design of the above device that can used in theatres to prevent piracy. The domains being covered here are optics and image processing.

Keywords: CCD, optics, image processing, D3CIP

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Authors: Elizabeth Malebogo Mosepele

Abstract:

Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation.

Keywords: Chi squared, geographic information system, multinomial logistic regression, remote sensing, road side vegetation

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Authors: Walaa Mohammed Metwally

Abstract:

This case study used the action research concept as a tool to integrate the innovation in a learning experience on a design course. The action research was investigated at Prince Sultan University, College of Engineering in the Interior Design and Architecture Department in January 2015, through the Higher Education Academy program. The action research was presented first with the definition of the research, leading to how it was used and how solutions were found. It concluded by showing that once the action research application in interior design and architecture were studied it was an effective tool to improve student’s learning, develop their practice in design courses, and it discussed the negative and positive issues that were encountered.

Keywords: action research, innovation, intervention, learning experience, peer review

Procedia PDF Downloads 339

Authors: Areti Angeliki Veroniki, Sofia Tsokani, Evangelos Paraskevaidis, Dimitris Mavridis

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The plethora of diagnostic test accuracy (DTA) studies has led to the increased use of systematic reviews and meta-analysis of DTA studies. Clinicians and healthcare professionals often consult DTA meta-analyses to make informed decisions regarding the optimum test to choose and use for a given setting. For example, the human papilloma virus (HPV) DNA, mRNA, and cytology can be used for the cervical intraepithelial neoplasia grade 2+ (CIN2+) diagnosis. But which test is the most accurate? Studies directly comparing test accuracy are not always available, and comparisons between multiple tests create a network of DTA studies that can be synthesized through a network meta-analysis of diagnostic tests (DTA-NMA). The aim is to summarize the DTA-NMA methods for at least three index tests presented in the methodological literature. We illustrate the application of the methods using a real data set for the comparative accuracy of HPV DNA, HPV mRNA, and cytology tests for cervical cancer. A search was conducted in PubMed, Web of Science, and Scopus from inception until the end of July 2019 to identify full-text research articles that describe a DTA-NMA method for three or more index tests. Since the joint classification of the results from one index against the results of another index test amongst those with the target condition and amongst those without the target condition are rarely reported in DTA studies, only methods requiring the 2x2 tables of the results of each index test against the reference standard were included. Studies of any design published in English were eligible for inclusion. Relevant unpublished material was also included. Ten relevant studies were finally included to evaluate their methodology. DTA-NMA methods that have been presented in the literature together with their advantages and disadvantages are described. In addition, using 37 studies for cervical cancer obtained from a published Cochrane review as a case study, an application of the identified DTA-NMA methods to determine the most promising test (in terms of sensitivity and specificity) for use as the best screening test to detect CIN2+ is presented. As a conclusion, different approaches for the comparative DTA meta-analysis of multiple tests may conclude to different results and hence may influence decision-making. Acknowledgment: This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Extension of Network Meta-Analysis for the Comparison of Diagnostic Tests ” (MIS 5047640).

Keywords: colposcopy, diagnostic test, HPV, network meta-analysis

Procedia PDF Downloads 139

Authors: Uma U. Uma, Uzoechi Laz

Abstract:

Protection of equipment insulation against lightning over voltages and selection of lightning arrester that will discharge at lower voltage level than the voltage required to breakdown the electrical equipment insulation is examined. The objectives of this paper are to design a computer based model using standard equations for the selection of appropriate lightning arrester with the lowest rated surge arrester that will provide adequate protection of equipment insulation and equally have a satisfactory service life when connected to a specified line voltage in power system network. The effectiveness and non-effectiveness of the earthing system of substation determine arrester properties. MATLAB program with GUI (graphic user interphase) its subprogram is used in the development of the model for the determination of required parameters like voltage rating, impulse spark over voltage, power frequency spark over voltage, discharge current, current rating and protection level of lightning arrester of a specified voltage level of a particular line.

Keywords: lightning arrester, GUIs, MatLab program, computer based model

Procedia PDF Downloads 417