Search results for: traffic noise level

Authors: Amara Rafik, Bougherara Maamar, Belhadj Aissa Mostefa

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Radar data is one of the many data sources used by ATM Air Traffic Management systems. These data come from air navigation radar antennas. These radars intercept signals emitted by the various aircraft crossing the controlled airspace and calculate the position of these aircraft and retransmit their positions to the Air Traffic Management System. For greater reliability, these radars are positioned in such a way as to allow their coverage areas to overlap. An aircraft will therefore be detected by at least one of these radars. However, the position coordinates of the same aircraft and sent by these different radars are not necessarily identical. Therefore, the ATM system must calculate a single position (radar track) which will ultimately be sent to the control position and displayed on the air traffic controller's monitor. There are several techniques for calculating the radar track. Furthermore, the geographical nature of the problem requires the use of a Geographic Information System (GIS), i.e. a geographical database on the one hand and geographical processing. The objective of this work is to propose a GIS for traffic simulation which reconstructs the evolution over time of aircraft positions from a multi-source radar data set and by applying these different techniques.

Keywords: ATM, GIS, radar data, air traffic simulation

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Authors: Chen Niu, Xuesong Zhang, Dejiang Shang, Yongwei Liu

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Fishes can secrete high molecular weight fluid on their body skin to enable their rapid movement in the water. In this work, we employ a hybrid method that combines Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) to investigate the effects of different mucus viscosities and injection velocities on fluctuation pressure in the boundary layer and flow-induced structural vibration noise of a flat plate model. To accurately capture the transient flow distribution on the plate surface, we use Large Eddy Simulation (LES) while the mucus inlet is positioned at a sufficient distance from the model to ensure effective coverage. Mucus injection is modeled using the Volume of Fluid (VOF) method for multiphase flow calculations. The results demonstrate that mucus control of pulsating pressure effectively reduces flow-induced structural vibration noise, providing an approach for controlling flow-induced noise in underwater vehicles.

Keywords: mucus, flow control, noise control, flow-induced noise

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Authors: Raj Kumar Kama, Rajshree Kamat

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Traffic congestion is a serious problem that is to be considered, and it is increasing day-by-day in urban areas that is seriously affecting the urban society. From the study, it is understood that increased urbanization and growth of population are the principal causes of congestion. It has adverse effects on society, economy, environment, and health. This study mainly focussed on studying and understanding the causes of congestion, consequences faced by urban society, and planning solutions to mitigate congestion. Techniques like transit oriented development (TOD) and integrated transport systems are more effective in mitigating traffic congestion.

Keywords: traffic congestion, transit oriented development, integrated transport system, urbanization

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Authors: Ferdi Sönmez, Nihal Yorulmaz

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Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: operator cost, bi-level optimization model, user cost, urban transportation

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Authors: Aswin V. J., Sreeja S., R. Harikumar

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Ship collision is one of the major concerns while navigating in the ocean. In congested sea routes where there are hectic offshore operations, ships are often forced to take close encounter maneuvers. Maritime rules for preventing collision at sea are defined in the International Regulations for Preventing Collision at Sea. Traffic Separation Schemes (TSS) are traffic management route systems ruled by International Maritime Organization (IMO), where the traffic lanes indicate the general direction of traffic flow. The Rule 10 of International Regulations for Preventing Collision at Sea prescribes the conduct of vessels while navigating through TSS. But no quantitative criteria regarding the procedures to detect and evaluate collision risk is specified in International Regulations for Preventing Collision at Sea. Most of the accidents that occur are due to operational errors affected by human factors such as lack of experience and loss of situational awareness. In open waters, the traffic density is less when compared to that in TSS, and hence the vessels can be operated in autopilot mode. A collision avoidance method that uses the possible obstacle trajectories in advance to predict “collision occurrence” and can generate suitable maneuvers for collision avoidance is presented in this paper. The suitable course and propulsion changes that can be used in a TSS considering International Regulations for Preventing Collision at Sea are found out for various obstacle scenarios.

Keywords: collision avoidance, maneuvers, obstacle trajectories, traffic separation scheme

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Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

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The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

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Authors: Richard J. Hanowski, Rebecca L. Hammond

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Very few studies have been conducted to investigate safety issues associated with motorcoach/bus operations. The current study investigates the impact that roadway infrastructure, including locality, roadway grade, traffic flow and traffic density, have on bus safety. A naturalistic driving study was conducted in the U.S.A that involved 43 motorcoaches. Two fleets participated in the study and over 600,000 miles of naturalistic driving data were collected. Sixty-five bus drivers participated in this study; 48 male and 17 female. The average age of the drivers was 49 years. A sophisticated data acquisition system (DAS) was installed on each of the 43 motorcoaches and a variety of kinematic and video data were continuously recorded. The data were analyzed by identifying safety critical events (SCEs), which included crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Additionally, baseline (normative driving) segments were also identified and analyzed for comparison to the SCEs. This presentation highlights the need for bus safety research and the methods used in this data collection effort. With respect to elements of roadway infrastructure, this study highlights the methods used to assess locality, roadway grade, traffic flow, and traffic density. Locality was determined by manual review of the recorded video for each event and baseline and was characterized in terms of open country, residential, business/industrial, church, playground, school, urban, airport, interstate, and other. Roadway grade was similarly determined through video review and characterized in terms of level, grade up, grade down, hillcrest, and dip. The video was also used to make a determination of the traffic flow and traffic density at the time of the event or baseline segment. For traffic flow, video was used to assess which of the following best characterized the event or baseline: not divided (2-way traffic), not divided (center 2-way left turn lane), divided (median or barrier), one-way traffic, or no lanes. In terms of traffic density, level-of-service categories were used: A1, A2, B, C, D, E, and F. Highlighted in this abstract are only a few of the many roadway elements that were coded in this study. Other elements included lighting levels, weather conditions, roadway surface conditions, relation to junction, and roadway alignment. Note that a key component of this study was to assess the impact that driver distraction and fatigue have on bus operations. In this regard, once the roadway elements had been coded, the primary research questions that were addressed were (i) “What environmental condition are associated with driver choice of engagement in tasks?”, and (ii) “what are the odds of being in a SCE while engaging in tasks while encountering these conditions?”. The study may be of interest to researchers and traffic engineers that are interested in the relationship between roadway infrastructure elements and safety events in motorcoach bus operations.

Keywords: bus safety, motorcoach, naturalistic driving, roadway infrastructure

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing as one of the demand management strategies constrains expenditure to network users so that it helps reduction in traffic congestion and environment pollution like air pollution. Despite the development of congestion pricing schemes for traffic in our country, the matters of traditional toll collection, drivers’ waste of time and delay in traffic are still widespread. Electronic toll collection as a part of the intelligent transportation system provides the possibility of collecting tolls without car-stop and traffic disruption. Unlike the satisfying outcomes of using intelligent systems in congestion pricing schemes, implementation costs and technological problems are the barriers in these schemes. In this research first, a variety of electronic pay toll systems and their components are introduced then their functional usage is discussed. In the following, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of intelligent systems are described and the results show that the choice of the best technology depends on the various parameters which, by examining them, it is concluded that in a long-term run and by providing the necessary conditions, DSRC technology as the main system in the schemes and ANPR as a major backup system of the main one can be employed.

Keywords: congestion pricing, electronic toll collection, intelligent systems, technology, traffic

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Authors: N. Hadjigeorgiou, A. C. Tsalikidou, E. Hristoforou, P. P. Sotiriadis

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During the last few decades, the continuously increasing demand for accurate and reliable magnetic measurements has paved the way for the development of different types of magnetic sensing systems as well as different measurement techniques. Sensor sensitivity and linearity, signal-to-noise ratio, measurement range, cross-talk between sensors in multi-sensor applications are only some of the aspects that have been examined in the past. In this paper, a fully analog closed loop system in order to optimize the performance of AMR sensors has been developed. The operation of the proposed system has been tested using a Helmholtz coil calibration setup in order to control both the amplitude and direction of magnetic field in the vicinity of the AMR sensor. Experimental testing indicated that improved linearity of sensor response, as well as low noise levels can be achieved, when the system is employed.

Keywords: AMR sensor, closed loop, memory effects, chopper, linearity improvement, sensitivity improvement, magnetic noise, electronic noise

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Authors: Svea Missfeldt, Rainer Höger

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A number of studies show that aircraft noise around airports negatively affects the reading comprehension of children attending schools in the neighbourhood. Yet little is known about the underlying mechanisms. Explanatory approaches discuss the attention capturing effect of noise sources which occupy mental capacity. Research suggests that attentional capacities are especially demanded when different modalities are involved at the same time. To explore whether aircraft noise affects reading processes in specific manners, students read texts in variable sound conditions while their eye movements were recorded. Besides noise caused by aircraft flyovers, which represent moving sound sources, saccades were also recorded under the condition of white noise, a natural sound setting and silence for comparison. Data showed an increase in regressive saccades when the sound of moving sources was presented. Interestingly, this effect was significantly high when the aircrafts moved in the opposite of the reading direction. Especially the latter result is not compatible with the hypothesis of a general impairment of cognitive processes by noise where the direction of movement should not have an influence. Reading is assumed to be based on two different attentional mechanisms: overt and covert attention, where the latter supports control and pre-planning of eye movements during reading. We believe that covert attention is affected by moving sound sources, resulting in an enhanced number of backwardly directed saccades.

Keywords: aircraft noise, attentional processes, cognition, eye movements, reading saccades

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Authors: C. Temaneh-Nyah

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Electromagnetic compatibility (EMC) is the ability of a Radio Communication Equipment (RCE) to operate with a desired quality of service in a given Electromagnetic Environment (EME) and not to create harmful interference with other RCE. This paper presents an algorithm which improves the simulation speed of estimating EMC of RCE in a complex EME, based on a stage by stage frequency-energy criterion of filtering. This algorithm considers different interference types including: Blocking and intermodulation. It consist of the following steps: simplified energy criterion where filtration is based on comparing the free space interference level to the industrial noise, frequency criterion which checks whether the interfering emissions characteristic overlap with the receiver’s channels characteristic and lastly the detailed energy criterion where the real channel interference level is compared to the noise level. In each of these stages, some interference cases are filtered out by the relevant criteria. This reduces the total number of dual and different combinations of RCE involved in the tedious detailed energy analysis and thus provides an improved simulation speed.

Keywords: electromagnetic compatibility, electromagnetic environment, simulation of communication network

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Authors: Hossein Arfaeinia, Ahmad Jonidi Jafari, Sina Dobaradaran, Sadegh Niazi, Mojtaba Ehsanifar, Amir Zahedi

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Street dust and surface soil samples were collected from very heavy, heavy, medium and low traffic areas and natural site in Tehran, Iran. These samples were analyzed for some physical–chemical features, total and chemical speciation of selected metals and metalloids (Zn, Al, Sr, Pb, Cu, Cr, Cd, Co, Ni, and V) to study the effect of traffic on their mobility and accumulation in the environment. The pH, electrical conductivity (EC), carbonates and organic carbon (OC) values were similar in soil and dust samples from similar traffic areas. The traffic increases EC contents in dust/soil matrixes but has no effect on concentrations of metals and metalloids in soil samples. Rises in metal and metalloids levels with traffic were found in dust samples. Moreover, the traffic increases the percentage of acid soluble fraction and Fe and Mn oxides associated fractions of Pb and Zn. The mobilization of Cu, Zn, Pb, Cr in dust samples was easier than in soil. The speciation of metals and metalloids except Cd is mainly affected by physicochemical features in soil, although total metals and metalloids affected the speciation in dust samples (except chromium and nickel).

Keywords: street dust, surface soil, traffic, metals, metalloids, chemical speciation

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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Authors: Ajish K. Abraham

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Hearing aid is the most fundamental technology employed towards rehabilitation of persons with sensory neural hearing impairment. Hearing in noise is still a matter of major concern for many hearing aid users and thus continues to be a challenging issue for the hearing aid designers. Several techniques are being currently used to enhance the speech at the hearing aid output. Most of these techniques, when implemented, result in reduction of intelligibility of the speech signal. Thus the dissatisfaction of the hearing aid user towards comprehending the desired speech amidst noise is prevailing. Multichannel Wiener Filter is widely implemented in binaural hearing aid technology for noise reduction. In this study, Wiener filter based noise reduction approach is experimented for a single microphone based hearing aid set up. This method checks the status of the input speech signal in each frequency band and then selects the relevant noise reduction procedure. Results showed that the Wiener filter based algorithm is capable of enhancing speech even when the input acoustic signal has a very low Signal to Noise Ratio (SNR). Performance of the algorithm was compared with other similar algorithms on the basis of improvement in intelligibility and SNR of the output, at different SNR levels of the input speech. Wiener filter based algorithm provided significant improvement in SNR and intelligibility compared to other techniques.

Keywords: hearing aid output speech, noise reduction, SNR improvement, Wiener filter, speech enhancement

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Authors: Yuxiao Jiang, Lingjun Meng, Mengyu Zhan, Lichunyi Zhang, Yingxia Yun

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On August 8th of 2015, a serious explosion occurred in Binhai New Area of Tianjin. This explosion led to the suspension of Tianjin-Binhai Light Rail Line 9 which was an important transportation mean connecting the old and new urban areas and the suspension causes inconvenience to commuters traveling from Tianjin to Binhai or Binhai to Tianjin and residents living by Line 9. On this regard, this paper intends to give suggestions on how to develop multi-mode transportation system rapidly and effectively after a disaster and tackle with the problems in terms of transportation infrastructure facilities. The paper proposes the idea of traffic resilience which refers to the city’s ability to restore its transportation system and reduce risks when the transportation system is destroyed by a disaster. By doing questionnaire research, on the spot study and collecting data from the internet, a GIS model is established so as to analyze the alternative traffic means used by different types of residents and study the transportation supply and demand. The result shows that along the Line 9, there is a larger demand for alternative traffic means in the place which is nearer to the downtown area. Also, the distribution of bus stations is more reasonable in the place nearer to downtown area, however, the traffic speed in the area is slower. Based on traffic resilience, the paper raises strategies to develop post-disaster multi-mode transportation system such as establishing traffic management mechanism timely and effectively, building multi-mode traffic networks, improving intelligent traffic systems and so on.

Keywords: traffic resilience, multi-mode transportation system, public traffic, transportation demand

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Authors: M. Sirajul Islam Molla

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Noise pollution has been a continuous and an increasing threat to human health in urban population all over the world. The situation in Bangladesh particularly in major cities has been dangerously aggravating. Despite the government of Bangladesh have laws in its hand to curb the noise pollution the authority’s reluctance in enforcing it, is making the situation worse. We do not see any difference in some other major cities of the South Asian Regional Countries like Delhi and Kathmandu, both of the cities are facing the same situation like Dhaka. With the expansion of technology-based township all over the world, the noise pollution has been an emerging threat to urban health. The information for this review has been derived from websites of GOs, NGOs, peer-reviewed papers, seminars and symposia. The worse situation of noise pollution results in people’s irritation and protest, but in many cases, the protesters are facing the wrath of the polluters. Two such consequences in Bangladesh have resulted in killing the protesters by the polluters – one happened in Dhaka city and the other in a rural town. The law-enforcing agencies proactively do not attempt to impose the law. Noise pollution has been increasing so rapidly that it has become a burden on human health in urban populations. Prolonged exposure to higher noise causes mental stress, sleeplessness, high blood pressure, cardiac failure, respiratory disorder, miscarriage and breaks attention of students to their studies and also irritates their behavior. The noise pollution-caused mortality has also been increasing all over the world. Recommendations from the international conferences such as ICUH should be forwarded to the United Nations. The UN then should pass it on to the concerned countries. The UN should also keenly monitor if the countries have appropriate plan to curb noise pollution to meet the sustainable development goals.

Keywords: decibel, environment, noise, pollution

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Authors: R. Ajgou, S. Sbaa, S. Ghendir, A. Chemsa, A. Taleb-Ahmed

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The speech enhancement algorithm is to improve speech quality. In this paper, we review some speech enhancement methods and we evaluated their performance based on Perceptual Evaluation of Speech Quality scores (PESQ, ITU-T P.862). All method was evaluated in presence of different kind of noise using TIMIT database and NOIZEUS noisy speech corpus.. The noise was taken from the AURORA database and includes suburban train noise, babble, car, exhibition hall, restaurant, street, airport and train station noise. Simulation results showed improved performance of speech enhancement for Tracking of non-stationary noise approach in comparison with various methods in terms of PESQ measure. Moreover, we have evaluated the effects of the speech enhancement technique on Speaker Identification system based on autoregressive (AR) model and Mel-frequency Cepstral coefficients (MFCC).

Keywords: speech enhancement, pesq, speaker recognition, MFCC

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Authors: Reji Thankachan, Varsha PS

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Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

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Authors: Hesham Abdin, Mohamed Zakaria, Talaat Abd-Elmonaem, Alaa El-Din Sayed Hafez

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Kalman filter algorithm is an estimator known as the workhorse of estimation. It has an important application in missile guidance, especially in lack of accurate data of the target due to noise or uncertainty. In this paper, a Kalman filter is used as a tracking filter in a simulated target-interceptor scenario with noise. It estimates the position, velocity, and acceleration of the target in the presence of noise. These estimations are needed for both proportional navigation and differential geometry guidance laws. A Kalman filter has a good performance at low noise, but a large noise causes considerable errors leads to performance degradation. Therefore, a new technique is required to overcome this defect using tuning factors to tune a Kalman filter to adapt increasing of noise. The values of the tuning factors are between 0.8 and 1.2, they have a specific value for the first half of range and a different value for the second half. they are multiplied by the estimated values. These factors have its optimum values and are altered with the change of the target heading. A genetic algorithm updates these selections to increase the maximum effective range which was previously reduced by noise. The results show that the selected factors have other benefits such as decreasing the minimum effective range that was increased earlier due to noise. In addition to, the selected factors decrease the miss distance for all ranges of this direction of the target, and expand the effective range which leads to increase probability of kill.

Keywords: proportional navigation, differential geometry, Kalman filter, genetic algorithm

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

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Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety

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Authors: Sanjai Sureshkumar, Sathish G. Kumar, P. V. V. Sathyanarayana

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For e-gear drivetrain, the transmission error and the resulting variation in mesh stiffness is one of the main source of excitation in High performance Electric Vehicle. These vibrations are transferred through the shaft to the bearings and then to the e-Gear drive housing eventually radiating noise. A parametrical model developed in 1-D system simulation by optimizing the micro and macro geometry along with bearing properties and oil filtration to achieve least transmission error and high contact ratio. Histogram analysis is performed to condense the actual road load data into condensed duty cycle to find the bearing forces. The structural vibration generated by these forces will be simulated in a nonlinear solver obtaining the normal surface velocity of the housing and the results will be carried forward to Acoustic software wherein a virtual environment of the surrounding (actual testing scenario) with accurate microphone position will be maintained to predict the sound pressure level of radiated noise and directivity plot of the e-Gear Drive. Order analysis will be carried out to find the root cause of the vibration and whine noise. Broadband spectrum will be checked to find the rattle noise source. Further, with the available results, the design will be optimized, and the next loop of simulation will be performed to build a best e-Gear Drive on NVH aspect. Structural analysis will be also carried out to check the robustness of the e-Gear Drive.

Keywords: 1-D system simulation, contact ratio, e-Gear, mesh stiffness, micro and macro geometry, transmission error, radiated noise, NVH

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Authors: Fatemeh Sadeghi, Peyman Sheikhzadeh

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Introduction: Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm was recently developed to suppress excessive noise by applying a relative difference penalty. The aim of this study was to investigate the effect of various strengths of noise penalization factor in the BSREM algorithm under different acquisition duration and lesion sizes in order to determine an optimum penalty factor by considering both quantitative and qualitative image evaluation parameters in clinical uses. Materials and Methods: The NEMA IQ phantom and 15 clinical whole-body patients with prostate cancer were evaluated. Phantom and patients were injected withGallium-68 Prostate-Specific Membrane Antigen(68 Ga-PSMA)and scanned on a non-time-of-flight Discovery IQ Positron Emission Tomography/Computed Tomography(PET/CT) scanner with BGO crystals. The data were reconstructed using BSREM with a β-value of 100-500 at an interval of 100. These reconstructions were compared to OSEM as a widely used reconstruction algorithm. Following the standard NEMA measurement procedure, background variability (BV), recovery coefficient (RC), contrast recovery (CR) and residual lung error (LE) from phantom data and signal-to-noise ratio (SNR), signal-to-background ratio (SBR) and tumor SUV from clinical data were measured. Qualitative features of clinical images visually were ranked by one nuclear medicine expert. Results: The β-value acts as a noise suppression factor, so BSREM showed a decreasing image noise with an increasing β-value. BSREM, with a β-value of 400 at a decreased acquisition duration (2 min/ bp), made an approximately equal noise level with OSEM at an increased acquisition duration (5 min/ bp). For the β-value of 400 at 2 min/bp duration, SNR increased by 43.7%, and LE decreased by 62%, compared with OSEM at a 5 min/bp duration. In both phantom and clinical data, an increase in the β-value is translated into a decrease in SUV. The lowest level of SUV and noise were reached with the highest β-value (β=500), resulting in the highest SNR and lowest SBR due to the greater noise reduction than SUV reduction at the highest β-value. In compression of BSREM with different β-values, the relative difference in the quantitative parameters was generally larger for smaller lesions. As the β-value decreased from 500 to 100, the increase in CR was 160.2% for the smallest sphere (10mm) and 12.6% for the largest sphere (37mm), and the trend was similar for SNR (-58.4% and -20.5%, respectively). BSREM visually was ranked more than OSEM in all Qualitative features. Conclusions: The BSREM algorithm using more iteration numbers leads to more quantitative accuracy without excessive noise, which translates into higher overall image quality and lesion detectability. This improvement can be used to shorter acquisition time.

Keywords: BSREM reconstruction, PET/CT imaging, noise penalization, quantification accuracy

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Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

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Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

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Authors: Sanjeet Kumar Singh, Shantanu Bhatacharya

Abstract:

Design of high-efficiency low, frequency (<1000Hz) soundproof window or wall absorber which is transparent to airflow is presented. Due to the massive rise in human population and modernization, environmental noise has significantly risen globally. Prolonged noise exposure can cause severe physiological and psychological symptoms like nausea, headaches, fatigue, and insomnia. There has been continuous growth in building construction and infrastructure like offices, bus stops, and airports due to the urban population. Generally, a ventilated window is used for getting fresh air into the room, but at the same time, unwanted noise comes along. Researchers used traditional approaches like noise barrier mats in front of the window or designed the entire window using sound-absorbing materials. However, this solution is not aesthetically pleasing, and at the same time, it's heavy and not adequate for low-frequency noise shielding. To address this challenge, we design a transparent hexagonal panel based on the Sierpiński fractal triangle, which is aesthetically pleasing and demonstrates a normal incident sound absorption coefficient of more than 0.96 around 700 Hz and transmission loss of around 23 dB while maintaining e air circulation through the triangular cutout. Next, we present a concept of fabrication of large acoustic panels for large-scale applications, which leads to suppressing urban noise pollution.

Keywords: acoustic metamaterials, ventilation, urban noise pollution, noise control

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Authors: Ramesh Chandra Majhi

Abstract:

Saturation flow is a very important input variable for the design of signalized intersections. Saturation flow measurement is well established for homogeneous traffic. However, saturation flow measurement and modeling is a challenging task in heterogeneous characterized by multiple vehicle types and non-lane based movement. Present study focuses on proposing a field procedure for Saturation flow measurement and the effect of typical mixed traffic behavior at the signal as far as non-lane based traffic movement is concerned. Data collected during peak and off-peak hour from five intersections with varying approach width is used for validating the saturation flow model. The insights from the study can be used for modeling saturation flow and delay at signalized intersection in heterogeneous traffic conditions.

Keywords: optimization, passenger car unit, saturation flow, signalized intersection

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Authors: Vittorio Astarita, Giuseppe Guido, Vincenzo Pasquale Giofre, Alessandro Vitale

Abstract:

Traffic microsimulation has been used extensively to evaluate consequences of different traffic planning and control policies in terms of travel time delays, queues, pollutant emissions, and every other common measured performance while at the same time traffic safety has not been considered in common traffic microsimulation packages as a measure of performance for different traffic scenarios. Vehicle conflict techniques that were introduced at intersections in the early traffic researches carried out at the General Motor laboratory in the USA and in the Swedish traffic conflict manual have been applied to vehicles trajectories simulated in microscopic traffic simulators. The concept is that microsimulation can be used as a base for calculating the number of conflicts that will define the safety level of a traffic scenario. This allows engineers to identify unsafe road traffic maneuvers and helps in finding the right countermeasures that can improve safety. Unfortunately, most commonly used indicators do not consider conflicts between single vehicles and roadside obstacles and barriers. A great number of vehicle crashes take place with roadside objects or obstacles. Only some recent proposed indicators have been trying to address this issue. This paper introduces a new procedure based on the simulation of potential crash events for the evaluation of safety levels in microsimulation traffic scenarios, which takes into account also potential crashes with roadside objects and barriers. The procedure can be used to define new conflict indicators. The proposed simulation procedure generates with the random perturbation of vehicle trajectories a set of potential crashes which can be evaluated accurately in terms of DeltaV, the energy of the impact, and/or expected number of injuries or casualties. The procedure can also be applied to real trajectories giving birth to new surrogate safety performance indicators, which can be considered as “simulation-based”. The methodology and a specific safety performance indicator are described and applied to a simulated test traffic scenario. Results indicate that the procedure is able to evaluate safety levels both at the intersection level and in the presence of roadside obstacles. The procedure produces results that are expressed in the same unity of measure for both vehicle to vehicle and vehicle to roadside object conflicts. The total energy for a square meter of all generated crash can be used and is shown on the map, for the test network, after the application of a threshold to evidence the most dangerous points. Without any detailed calibration of the microsimulation model and without any calibration of the parameters of the procedure (standard values have been used), it is possible to identify dangerous points. A preliminary sensitivity analysis has shown that results are not dependent on the different energy thresholds and different parameters of the procedure. This paper introduces a specific new procedure and the implementation in the form of a software package that is able to assess road safety, also considering potential conflicts with roadside objects. Some of the principles that are at the base of this specific model are discussed. The procedure can be applied on common microsimulation packages once vehicle trajectories and the positions of roadside barriers and obstacles are known. The procedure has many calibration parameters and research efforts will have to be devoted to make confrontations with real crash data in order to obtain the best parameters that have the potential of giving an accurate evaluation of the risk of any traffic scenario.

Keywords: road safety, traffic, traffic safety, traffic simulation

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Authors: Keunhong Chae, Seokho Yoon

Abstract:

This paper proposes frequency offset (FO) estimation schemes robust to the non-Gaussian noise for orthogonal frequency division multiplexing (OFDM) systems. A maximum-likelihood (ML) scheme and a low-complexity estimation scheme are proposed by applying the probability density function of the cyclic prefix of OFDM symbols to the ML criterion. From simulation results, it is confirmed that the proposed schemes offer a significant FO estimation performance improvement over the conventional estimation scheme in non-Gaussian noise environments.

Keywords: frequency offset, cyclic prefix, maximum-likelihood, non-Gaussian noise, OFDM

Procedia PDF Downloads 451