Search results for: railway signal

Authors: Alla Levina, Sergey Taranov

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The classical approach to the providing noise immunity and integrity of information that process in computing devices and communication channels is to use linear codes. Linear codes have fast and efficient algorithms of encoding and decoding information, but this codes concentrate their detect and correct abilities in certain error configurations. To protect against any configuration of errors at predetermined probability can robust codes. This is accomplished by the use of perfect nonlinear and almost perfect nonlinear functions to calculate the code redundancy. The paper presents the error-correcting coding scheme using biorthogonal wavelet transform. Wavelet transform applied in various fields of science. Some of the wavelet applications are cleaning of signal from noise, data compression, spectral analysis of the signal components. The article suggests methods for constructing linear codes based on wavelet decomposition. For developed constructions we build generator and check matrix that contain the scaling function coefficients of wavelet. Based on linear wavelet codes we develop robust codes that provide uniform protection against all errors. In article we propose two constructions of robust code. The first class of robust code is based on multiplicative inverse in finite field. In the second robust code construction the redundancy part is a cube of information part. Also, this paper investigates the characteristics of proposed robust and linear codes.

Keywords: robust code, linear code, wavelet decomposition, scaling function, error masking probability

Procedia PDF Downloads 489

Authors: Gopi Kerekere Rangaraju, Madhu Puttegowda

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Natural fibres composites include coir, jute, bagasse, cotton, bamboo, and hemp. Natural fibers come from plants. These fibers contain lingo cellulose in nature. Natural fibers are eco-friendly; lightweight, strong, renewable, cheap, and biodegradable. The natural fibers can be used to reinforce both thermosetting and thermoplastic matrices. Thermosetting resins such as epoxy, polyester, polyurethane, and phenolic are commonly used composites requiring higher performance applications. They provide sufficient mechanical properties, in particular, stiffness and strength at acceptably low-price levels. Recent advances in natural fibers development are genetic engineering. The composites science offers significant opportunities for improved materials from renewable resources with enhanced support for global sustainability. Natural fibers composites are attractive to industry because of their low density and ecological advantages over conventional composites. These composites are gaining importance due to their non-carcinogenic and bio-degradable nature. Natural fibers composites are a very costeffective material, especially in building and construction, packaging, automobile and railway coach interiors, and storage devices. These composites are potential candidates for the replacement of high- cost glass fibers for low load bearing applications. Natural fibers have the advantages of low density, low cost, and biodegradability

Keywords: PMC, basalt, coir, carbon fibers

Procedia PDF Downloads 132

Authors: Ahmed Auda, Manjree Agarwala, Giles Hardya, Yonglin Rena

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Botrytis cinerea is a major pest for many plants. It can attack a wide range of plant parts. It can attack buds, flowers, and leaves, stems, and fruit. However, B. cinerea can be mixed with other diseases that cause the same damage. There are many species of botrytis and more than one different strains of each. Botrytis might infect the foliage of nursery stock stored through winter in damp conditions. There are no known resistant plants. Botrytis must have nutrients or food source before it infests the plant. Nutrients leaking from wounded plant parts or dying tissue like old flower petals give the required nutrients. From this food, the fungus becomes more attackers and invades healthy tissue. Dark to light brown rot forms in the ill tissue. High humidity conditions support the growth of this fungus. However, we suppose that selection pressure can act on the morphological and neurophysiologic filter properties of the receiver and on both the biochemical and the physiological regulation of the signal. Communication is implied when signal and receiver evolves toward more and more specific matching, culminating. In other hand, receivers respond to portions of a body odor bouquet which is released to the environment not as an (intentional) signal but as an unavoidable consequence of metabolic activity or tissue damage. Each year Botrytis species can cause considerable economic losses to plant crops. Even with the application of strict quarantine and control measures, these fungi can still find their way into crops and cause the imposition of onerous restrictions on exports. Blueberry fruit mould caused by a fungal infection usually results in major losses during post-harvest storage. Therefore, the management of infection in early stages of disease development is necessary to minimize losses. The overall purpose of this study will develop sensitive, cheap, quick and robust diagnostic techniques for the detection of B. cinerea in blueberry. The specific aim was designed to investigate the performance of volatile organic compounds (VOCs) in the detection and discrimination of blueberry fruits infected by fungal pathogens with an emphasis on Botrytis in the early storage stage of post-harvest.

Keywords: botrytis cinerea, blueberry, GC/MS, VOCs

Procedia PDF Downloads 241

Authors: Qi Liu, Jiqin Yao, Xiaohu Zhou, Bo Zheng

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The first artificial cell was produced by Thomas Chang in the 1950s when he was trying to make a mimic of red blood cells. Since then, many different types of artificial cells have been constructed from one of the two approaches: a so-called bottom-up approach, which aims to create a cell from scratch, and a top-down approach, in which genes are sequentially knocked out from organisms until only the minimal genome required for sustaining life remains. In this project, bottom-up approach was used to build a new cell-free expression system which mimics artificial cell that capable of protein expression and communicate with each other. The artificial cells constructed from the bottom-up approach are usually lipid vesicles, polymersomes, hydrogels or aqueous droplets containing the nucleic acids and transcription-translation machinery. However, lipid vesicles based artificial cells capable of communication present several issues in the cell communication research: (1) The lipid vesicles normally lose the important functions such as protein expression within a few hours. (2) The lipid membrane allows the permeation of only small molecules and limits the types of molecules that can be sensed and released to the surrounding environment for chemical communication; (3) The lipid vesicles are prone to rupture due to the imbalance of the osmotic pressure. To address these issues, the hydrogel-based artificial cells were constructed in this work. To construct the artificial cell, polyacrylamide hydrogel was functionalized with Acrylate PEG Succinimidyl Carboxymethyl Ester (ACLT-PEG2000-SCM) moiety on the polymer backbone. The proteinaceous factors can then be immobilized on the polymer backbone by the reaction between primary amines of proteins and N-hydroxysuccinimide esters (NHS esters) of ACLT-PEG2000-SCM, the plasmid template and ribosome were encapsulated inside the hydrogel particles. Because the artificial cell could continuously express protein with the supply of nutrients and energy, the artificial cell-artificial cell communication and artificial cell-natural cell communication could be achieved by combining the artificial cell vector with designed plasmids. The plasmids were designed referring to the quorum sensing (QS) system of bacteria, which largely relied on cognate acyl-homoserine lactone (AHL) / transcription pairs. In one communication pair, “sender” is the artificial cell or natural cell that can produce AHL signal molecule by synthesizing the corresponding signal synthase that catalyzed the conversion of S-adenosyl-L-methionine (SAM) into AHL, while the “receiver” is the artificial cell or natural cell that can sense the quorum sensing signaling molecule form “sender” and in turn express the gene of interest. In the experiment, GFP was first immobilized inside the hydrogel particle to prove that the functionalized hydrogel particles could be used for protein binding. After that, the successful communication between artificial cell-artificial cell and artificial cell-natural cell was demonstrated, the successful signal between artificial cell-artificial cell or artificial cell-natural cell could be observed by recording the fluorescence signal increase. The hydrogel-based artificial cell designed in this work can help to study the complex communication system in bacteria, it can also be further developed for therapeutic applications.

Keywords: artificial cell, cell-free system, gene circuit, synthetic biology

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Authors: Sun Zhe, Ruggero Micheletto

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As discussed extensively in many studies, noise in neural networks have an important role in the functioning and time evolution of the system. The mechanism by which noise induce stochastic resonance enhancing and influencing certain operations is not clarified nor is the mechanism of information storage and coding. With the present research we want to study the role of noise, especially focusing on the frequency peaks in a three variable Hindmarsh−Rose Small−World network. We investigated the behaviour of the network to external noises. We demonstrate that a variation of signal to noise ratio of about 10 dB induces an increase in membrane potential signal of about 15%, averaged over the whole network. We also considered the integral of the whole membrane potential as a paradigm of internal noise, the one generated by the brain network. We showed that this internal noise is attenuated with the size of the network or with the number of random connections. By means of Fourier analysis we found that it has distinct peaks of frequencies, moreover, we showed that increasing the size of the network introducing more neurons, reduced the maximum frequencies generated by the network, whereas the increase in the number of random connections (determined by the small-world probability p) led to a trend toward higher frequencies. This study may give clues on how networks utilize noise to alter the collective behaviour of the system in their operations.

Keywords: neural networks, stochastic processes, small-world networks, discrete Fourier analysis

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Authors: Delara Kazempour, Mashallah Abasi Dezfuli, Reza Javidan

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Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform.

Keywords: video compression, contourlet transform, discrete cosine transform, wavelet transform

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Authors: Houmame Benbouali

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This paper introduces the design, analysis, tests and application of a new isolation system used in irregular structure, also briefly introduces the recent research, and development on seismic isolation of civil buildings in China. A very large platform (2 stories RC frame) with plane size 1500m wide and 2000m long was built to cover the city railway communication hub area. About 50 isolation house buildings (9 stories RC frame) with 480,000 M2 were built on the top floor of platform. A new advanced isolation system named Storied-Isolation was used to ensure the seismic safety for this irregular structure with the largest isolation house building area in the world. This new isolation system has been used widely in China. There are over 400 buildings with seismic isolation have been built in China until 2003. This paper will introduce the recent research, and development on seismic isolation of civil buildings in China, including the tendency of application on seismic isolation, different isolation systems, different design level being used, design codes, application status and examples of application. Also the paper makes discussion of some problems on the future development of seismic isolation in China.

Keywords: civil buildings, floor, irregular structure, seismic isolation

Procedia PDF Downloads 328

Authors: Ayad A. Abdulkafi, Shahir F. Nawaf, Mohammed K. Hussein, Ibrahim K. Sileh, Fouad A. Abdulkafi

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Visible light communication (VLC) is a new approach of optical wireless communication proposed to support the congested radio frequency (RF) spectrum. VLC systems are combined with orthogonal frequency division multiplexing (OFDM) to achieve high rate transmission and high spectral efficiency. In this paper, we investigate the Pilot-Assisted Channel Estimation for DC biased Optical OFDM (PACE-DCO-OFDM) systems to reduce the effects of the distortion on the transmitted signal. Least-square (LS) and linear minimum mean-squared error (LMMSE) estimators are implemented in MATLAB/Simulink to enhance the bit-error-rate (BER) of PACE-DCO-OFDM. Results show that DCO-OFDM system based on PACE scheme has achieved better BER performance compared to conventional system without pilot assisted channel estimation. Simulation results show that the proposed PACE-DCO-OFDM based on LMMSE algorithm can more accurately estimate the channel and achieves better BER performance when compared to the LS based PACE-DCO-OFDM and the traditional system without PACE. For the same signal to noise ratio (SNR) of 25 dB, the achieved BER is about 5×10^-4 for LMMSE-PACE and 4.2×10^-3 with LS-PACE while it is about 2×10^-1 for system without PACE scheme.

Keywords: channel estimation, OFDM, pilot-assist, VLC

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Authors: Mario A. Blanco, Nicholas Burkhardt

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An important problem in satellite communication systems which operate in the Ka and EHF frequency bands consists of the overall degradation in link performance of mobile terminals due to various types of degradations in the link/channel, such as fading, blockage of the link to the satellite (especially in urban environments), intentional as well as other types of interference, etc. In this paper, we focus primarily on the interference problem, and we develop a very efficient and cost-effective solution based on the use of fountain codes. We first introduce a satellite communications (SATCOM) terminal uplink interference channel model that is classically used against communication systems that use spread-spectrum waveforms. We then consider the use of fountain codes, with focus on Raptor codes, as our main mitigation technique to combat the degradation in link/receiver performance due to the interference signal. The performance of the receiver is obtained in terms of average probability of bit and message error rate as a function of bit energy-to-noise density ratio, Eb/N0, and other parameters of interest, via a combination of analysis and computer simulations, and we show that the use of fountain codes is extremely effective in overcoming the effects of intentional interference on the performance of the receiver and associated communication links. We then show this technique can be extended to mitigate other types of SATCOM channel degradations, such as those caused by channel fading, shadowing, and hard-blockage of the uplink signal.

Keywords: SATCOM, interference mitigation, fountain codes, turbo codes, cross-layer

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: T. Pedersen, A. Lindfeldt

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The minimum dwell time is an important part of railway timetable planning. Due to its stochastic behaviour, the minimum dwell time should be considered to create resilient timetables. While there has been significant focus on how to determine and estimate dwell times, to our knowledge, little research has been carried out regarding temporal and running direction variations of these. In this paper, we examine how the minimum dwell time varies depending on temporal factors such as the time of day, day of the week and time of the year. We also examine how it is affected by running direction and station type. The minimum dwell time is estimated by means of track occupation data. A method is proposed to ensure that only minimum dwell times and not planned dwell times are acquired from the track occupation data. The results show that on an aggregated level, the average minimum dwell times in both running directions at a station are similar. However, when temporal factors are considered, there are significant variations. The minimum dwell time varies throughout the day with peak hours having the longest dwell times. It is also found that the minimum dwell times are influenced by weekday, and in particular, weekends are found to have lower minimum dwell times than most other days. The findings show that there is a potential to significantly improve timetable planning by taking minimum dwell time variations into account.

Keywords: minimum dwell time, operations quality, timetable planning, track occupation data

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Authors: Viktoriia Malinovska, Iryna Kuklina, Katerina Grabicova, Milos Buric, Pavel Kozak

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Personal care products, including organic UV filters, are considered emerging contaminants and their toxic effects have been a concern for the last decades. Sunscreen compounds continually enter the surface waters via sewage water treatment due to incomplete removal and during human recreational and laundry activities. Despite the environmental occurrence of organic UV filters in the freshwater environment, little is known about their impacts on aquatic biota. In this study, environmentally relevant concentrations of 5-Benzoyl-4-hydroxy-2-methoxybenzenesulfonic acid (BP-4, 2.5 µg/L) and 2-Phenylbenzimidazole-5-sulfonic acid (PBSA, 3 µg/L) were used to evaluate the cardiac and locomotor responses of signal crayfish Pacifastacus leniusculus during a short time period. The effects of these compounds were evident in experimental animals. Specimens exposed to both tested compounds exhibited significantly bigger changes in distance moved and time movement than controls. Significant differences in changes in mean heart rate were detected in both PBSA and BP-4 experimental groups compared to control groups. Such behavioral and physiological alterations demonstrate the ecological effects of selected sunscreen compounds during a short time period. Since the evidence of the impacts of sunscreen compounds is scarce, the knowledge of how organic UV filters influence aquatic organisms is of key importance for future research.

Keywords: aquatic pollutants, behavior, freshwaters, heart rate, invertebrate

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs. This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of cepstrum analysis in detection and diagnosis of the gear condition.

Keywords: cepstrum analysis, fault diagnosis, gearbox, vibration signals

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Robert O. Abolade, Olumide O. Ajayi, Zacheaus K. Adeyemo, Solomon A. Adeniran

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Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.

Keywords: channel quality indicator, fuzzy logic, link adaptation, MIMO, spatial multiplexing, transmit diversity

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Seyed Habib A. Rahmati, Parsa Fallah Sheikhlari, Morteza Musakhani

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This paper studies the structure of financial investment and efficiency on the subway would be created between Hashtgerd and Qazvin in Iran. Regarding ascending rate of transportation between Tehran and Qazvin which directly air pollution, it clearly implies to public transportation requirement between these two cities near Tehran. The railway transportation like subway can help each country to terminate traffic jam which has some advantages such as speed, security, non-pollution, low cost of public transport, etc. This type of transportation needs national infrastructures which require enormous investment. It couldn’t implement without leading and managing funds and investments properly. In order to response 'needs', clear norms or normative targets have to be agreed and obviously it is important to distinguish costs from investment requirements critically. Implementation phase affects investment requirements and financing needs. So recognizing barrier related to investment and the quality of investment (what technologies and services are invested in) is as important as the amounts of investment. Different investment methods have mentioned as follows loan, leasing, equity participation, Line of financing, finance, usance, bay back. Alternatives survey before initiation and analyzing of risk management is one of the most important parts in this project. Observation of similar project cities each country has the own specification to choose investment method.

Keywords: subway project, project investment, project contract, project management

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Authors: Xuyang Song, Jun Yin

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The smart card has been an extremely universal tool in public transit. It collects a large amount of data on buses, urban railway transit, and ferries and provides possibilities for passenger profiling. This paper combines offline analysis of passenger profiling and real-time prediction to propose a method that can accurately predict the destination station in real-time when passengers tag on. Firstly, this article constructs a static database of user travel characteristics after identifying passenger travel patterns based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The dual travel passenger habits are identified: OD travel habits and D station travel habits. Then a rapid real-time prediction algorithm based on Transit Passenger Profiling is proposed, which can predict the destination of in-board passengers. This article combines offline learning with online prediction, providing a technical foundation for real-time passenger flow prediction, monitoring and simulation, and short-term passenger behavior and demand prediction. This technology facilitates the efficient and real-time acquisition of passengers' travel destinations and demand. The last, an actual case was simulated and demonstrated feasibility and efficiency.

Keywords: travel behavior, destination prediction, public transit, passenger profiling

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Authors: Osama Brinji, Wing Kong Chiu, Graham Tew

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Understanding the stability of rail ballast is one of the most important aspects in the railways. An unstable track may cause some issues such as unnecessary vibration and ultimately loss of track quality. The track foundation plays an important role in the stabilization of the railway. The dynamic response of rail ballast in the vicinity of the rail sleeper can affect the stability of the rail track and this has not been studied in detail. A review of literature showed that most of the works focused on the area under the concrete sleeper. Although there are some theories about the shear (longitudinal) effect of the rail ballast, these have not properly been studied and hence are not well understood. The stability of a rail track will depend on the compactness of the ballast in its vicinity. This paper will try to determine the dynamic response of the ballast to identify its resonant behaviour. This preliminary research is one of several studies that examine the vibration response of the granular materials. The main aim is to use this information for future design of sleepers to ensure that any dynamic response of the sleeper will not compromise the state of compactness of the ballast. This paper will report on the dependence of damping and the natural frequency of the ballast as a function of depth and distance from the point of excitation introduced through a concrete block. The concrete block is used to simulate a sleeper and the ballast is simulated with gravel. In spite of these approximations, the results presented in the paper will show an agreement with theories and the assumptions that are used in study the mechanical behaviour of the rail ballast.

Keywords: ballast, dynamic response, sleeper, stability

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Authors: Shivam Dubey, Shivakant Bajpai

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The Kalachuri dynasty of Tripuri was a significant ruling dynasty in central India that held power over a vast region for a longer period compared to renowned dynasties like the Chandellas. Their capital, Tripuri (modern-day Tewar, a small village near Jabalpur), and its surrounding area witnessed significant developments that were later disrupted by the Royal Indian Railways' construction of railway lines. However, remnants of their achievements can still be found scattered in and around Tewar. The Kalachuris made remarkable contributions in the fields of art, architecture, and iconography. The evolution of temple architecture, particularly in Baghelkhand and the Mahakoshal range after the decline of the Gupta Empire, can be attributed to the Kalachuris. There is a notable progression from early temple styles to mature architecture, with numerous examples displaying continuity between the two. One particularly unique temple style features a ground plan resembling a complete Chaitya Hall, while the elevation showcases a circular Grabhagriha with a Mandapa and a conical Shikhara adorned with a series of Gavakshas. This distinctive temple style is among the most exceptional in central India. While several studies have been conducted on the Kalachuris' architecture, there is still a need for further research, as recent discoveries have provided valuable insights into understanding their architectural achievements. This paper aims to explore the development of architecture in this region, incorporating these recent findings.

Keywords: architecture, Kalachuri, art, iconography

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Authors: Nipun Manirajan, Heeralal Gargama, Sushil Guhe, Manoj Prabhakaran

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In railway industry, train sets are designed based on contractual requirements (mission profile), where reliability targets are measured in terms of mean distance between failures (MDBF). However, during the beginning of revenue services, trains do not achieve the designed mission profile distance (mileage) within the timeframe due to infrastructure constraints, scarcity of commuters or other operational challenges thereby not respecting the original design inputs. Since trains do not run sufficiently and do not achieve the designed mileage within the specified time, car builder has a risk of not achieving the contractual MDBF target. This paper proposes a constant failure rate based model to deal with the situations where mileage accumulation is not a part of the design mission profile. The model provides appropriate MDBF target to be demonstrated based on actual accumulated mileage. A case study of rolling stock running in the field is undertaken to analyze the failure data and MDBF target demonstration during low mileage accumulation. The results of case study prove that with the proposed method, reliability targets are achieved under low mileage accumulation.

Keywords: mean distance between failures, mileage-based reliability, reliability target appropriations, rolling stock reliability

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Authors: Zulfajri Basri Hasanuddin

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There is an increasing demand for broadband services in Indonesia. Therefore, the answer is the use of Ka-Band which has some advantages such as wider bandwidth, the higher transmission speeds, and smaller size of antenna in the ground. However, rain attenuation is the primary factor in the degradation of signal at the Kaband. In this paper, the author will determine whether the Ka-band frequency can be implemented in Indonesia which has high intensity of rainfall.

Keywords: Ka-band, link budget, link availability, BER, Eb/No, C/N

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Authors: M. N. Khajavi, S. Nasiri, E. Farokhi, M. R. Bavir

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Alcohol fuels are renewable, have low pollution and have high octane number; therefore, they are important as fuel in internal combustion engines. Percentage detection of these alcoholic fuels with gasoline is a complicated, time consuming, and expensive process. Nowadays, these processes are done in equipped laboratories, based on international standards. The aim of this research is to determine percentage detection of different fuels based on vibration analysis of engine block signals. By doing, so considerable saving in time and cost can be achieved. Five different fuels consisted of pure gasoline (G) as base fuel and combination of this fuel with different percent of ethanol and methanol are prepared. For example, volumetric combination of pure gasoline with 10 percent ethanol is called E10. By this convention, we made M10 (10% methanol plus 90% pure gasoline), E30 (30% ethanol plus 70% pure gasoline), and M30 (30% Methanol plus 70% pure gasoline) were prepared. To simulate real working condition for this experiment, the vehicle was mounted on a chassis dynamometer and run under 1900 rpm and 30 KW load. To measure the engine block vibration, a three axis accelerometer was mounted between cylinder 2 and 3. After acquisition of vibration signal, eight time feature of these signals were used as inputs to an Adaptive Neuro Fuzzy Inference System (ANFIS). The designed ANFIS was trained for classifying these five different fuels. The results show suitable classification ability of the designed ANFIS network with 96.3 percent of correct classification.

Keywords: internal combustion engine, vibration signal, fuel composition, classification, ANFIS

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Authors: Nkemjika Chinenye-Kanu, Mamdud Hossain, Ghazi Droubi

Abstract:

Prediction of multiphase flow induced forces, void fraction and pressure is crucial at both design and operating stages of practical energy and process pipe systems. In this study, transient numerical simulations of upward slug-churn flow through a vertical 90-degree elbow have been conducted. The volume of fluid (VOF) method was used to model the two-phase flows while the K-epsilon Reynolds-Averaged Navier-Stokes (RANS) equations were used to model turbulence in the flows. The simulation results were validated using experimental results. Void fraction signal, peak frequency and maximum magnitude of void fraction fluctuation of the slug-churn flow validation case studies compared well with experimental results. The x and y direction force fluctuation signals at the elbow control volume were obtained by carrying out force balance calculations using the directly extracted time domain signals of flow properties through the control volume in the numerical simulation. The computed force signal compared well with experiment for the slug and churn flow validation case studies. Hence, the present numerical simulation technique was able to predict the behaviours of the one-way flow induced forces and void fraction fluctuations.

Keywords: computational fluid dynamics, flow induced vibration, slug-churn flow, void fraction and force fluctuation

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Authors: Desmond Adair, Kairat Ismailov, Martin Jaeger

Abstract:

Modelling of Timoshenko beams on elastic foundations has been widely used in the analysis of buildings, geotechnical problems, and, railway and aerospace structures. For the elastic foundation, the most widely used models are one-parameter mechanical models or two-parameter models to include continuity and cohesion of typical foundations, with the two-parameter usually considered the better of the two. Knowledge of free vibration characteristics of beams on an elastic foundation is considered necessary for optimal design solutions in many engineering applications, and in this work, the efficient and accurate variational iteration method is developed and used to calculate natural frequencies of a Timoshenko beam on a two-parameter foundation. The variational iteration method is a technique capable of dealing with some linear and non-linear problems in an easy and efficient way. The calculations are compared with those using a finite-element method and other analytical solutions, and it is shown that the results are accurate and are obtained efficiently. It is found that the effect of the presence of the two-parameter foundation is to increase the beam’s natural frequencies and this is thought to be because of the shear-layer stiffness, which has an effect on the elastic stiffness. By setting the two-parameter model’s stiffness parameter to zero, it is possible to obtain a one-parameter foundation model, and so, comparison between the two foundation models is also made.

Keywords: Timoshenko beam, variational iteration method, two-parameter elastic foundation model

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Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

Abstract:

Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

Abstract:

The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: Tokirhusen Iqbalbhai Shaikh, M. V. Shah

Abstract:

With an increase in travel demand and a reduction in travel time, high-speed rail (HSR) has been introduced in India. Simplified 3-D finite element modelling is necessary to predict the stability and deformation characteristics of railway embankments and soil structure interaction behaviour under high-speed design requirements for Indian soil conditions. The objective of this study is to analyse the rigid ballast-less and flexible ballast-based high speed rail track embankments for various critical conditions subjected to them, viz. static condition, moving train condition, sudden brake application, and derailment case, using software. The input parameters for the analysis are soil type, thickness of the relevant strata, unit weight, Young’s modulus, Poisson’s ratio, undrained cohesion, friction angle, dilatancy angle, modulus of subgrade reaction, design speed, and other anticipated, relevant data. Eurocode 1, IRS-004(D), IS 1343, IRS specifications, California high-speed rail technical specifications, and the NHSRCL feasibility report will be followed in this study.

Keywords: soil structure interaction, high speed rail, numerical modelling, PLAXIS3D

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Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

Abstract:

One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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Authors: M. Kharrat, G. Moreau, Z. Aboura

Abstract:

The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

Procedia PDF Downloads 155