Search results for: fully spatial signal processing

Authors: J. Harrison Kurunathan, R. Jayaparvathy

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"Assistive Robotics" is the field that deals with the study of robots that helps in human motion and also empowers human abilities by interfacing the robotic systems to be manipulated by human motion. The proposed model is a robotic arm that works as a haptic interface on the basis on accelerometers and DC motors that will function with respect to the movement of the human muscle. The proposed model would effectively work as a haptic interface that would reduce human effort in the field of defense and rescue. This can be used in very critical conditions like fire accidents to avoid causalities.

Keywords: accelerometers, haptic interface, servo motors, signal processing

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Authors: C. Agrawal, R. Kumar, A. Gupta, B. Chatterjee

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An experimental investigation has been carried out to study the cooling of a hot horizontal Stainless Steel surface of 3 mm thickness, which has 800±10 °C initial temperature. A round water jet of 22 ± 1 °C temperature was injected over the hot surface through straight tube type nozzles of 2.5-4.8 mm diameter and 250 mm length. The experiments were performed for the jet exit to target surface spacing of 4 times of jet diameter and jet Reynolds number of 5000-24000. The effect of change in jet Reynolds number on the surface quenching has been investigated form the stagnation point to 16 mm spatial location.

Keywords: hot-surface, jet impingement, quenching, stagnation point

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Ejay Nsugbe, Andrew Starr, Ian Jennions, Cristobal Ruiz-Carcel

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This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250 microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated.

Keywords: acoustic emissions, particle sizing, process monitoring, signal processing

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally non-stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. the results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

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Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: artificial neural network (ANN), chromatic dispersion (CD), delay-tap sampling (DTS), optical signal-to-noise ratio (OSNR)

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Authors: Lin Li, P. G. R. N. I. Pussella

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When representing spatial data and their attributes on different types of maps, the scale plays a key role in the process of map generalization. The process is consisted with two main operators such as selection and omission. Once some data were selected, they would undergo of several geometrical changing processes such as elimination, simplification, smoothing, exaggeration, displacement, aggregation and size reduction. As a result of these operations at different levels of data, the geometry of the spatial features such as length, sinuosity, orientation, perimeter and area would be altered. This would be worst in the case of preparation of small scale maps, since the cartographer has not enough space to represent all the features on the map. What the GIS users do is when they wanted to analyze a set of spatial data; they retrieve a data set and does the analysis part without considering very important characteristics such as the scale, the purpose of the map and the degree of generalization. Further, the GIS users use and compare different maps with different degrees of generalization. Sometimes, GIS users are going beyond the scale of the source map using zoom in facility and violate the basic cartographic rule 'it is not suitable to create a larger scale map using a smaller scale map'. In the study, the effect of map generalization for GIS analysis would be discussed as the main objective. It was used three digital maps with different scales such as 1:10000, 1:50000 and 1:250000 which were prepared by the Survey Department of Sri Lanka, the National Mapping Agency of Sri Lanka. It was used common features which were on above three maps and an overlay analysis was done by repeating the data with different combinations. Road data, River data and Land use data sets were used for the study. A simple model, to find the best place for a wild life park, was used to identify the effects. The results show remarkable effects on different degrees of generalization processes. It can see that different locations with different geometries were received as the outputs from this analysis. The study suggests that there should be reasonable methods to overcome this effect. It can be recommended that, as a solution, it would be very reasonable to take all the data sets into a common scale and do the analysis part.

Keywords: generalization, GIS, scales, spatial analysis

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Authors: Magdalena Idzikowska, Katarzyna Pająk, Kamil Kowalczyk

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Seafloor topography is a fundamental issue in geological, geophysical, and oceanographic studies. Single-beam or multibeam sonars attached to the hulls of ships are used to emit a hydroacoustic signal from transducers and reproduce the topography of the seabed. This solution provides relevant accuracy and spatial resolution. Bathymetric data from ships surveys provides National Centers for Environmental Information – National Oceanic and Atmospheric Administration. Unfortunately, most of the seabed is still unidentified, as there are still many gaps to be explored between ship survey tracks. Moreover, such measurements are very expensive and time-consuming. The solution is raster bathymetric models shared by The General Bathymetric Chart of the Oceans. The offered products are a compilation of different sets of data - raw or processed. Indirect data for the development of bathymetric models are also measurements of gravity anomalies. Some forms of seafloor relief (e.g. seamounts) increase the force of the Earth's pull, leading to changes in the sea surface. Based on satellite altimetry data, Sea Surface Height and marine gravity anomalies can be estimated, and based on the anomalies, it’s possible to infer the structure of the seabed. The main goal of the work is to create regional bathymetric models and models of the sea surface in the area of the east coast of North America – a region of seamounts and undulating seafloor. The research includes an analysis of the methods and techniques used, an evaluation of the interpolation algorithms used, model thickening, and the creation of grid models. Obtained data are raster bathymetric models in NetCDF format, survey data from multibeam soundings in MB-System format, and satellite altimetry data from Copernicus Marine Environment Monitoring Service. The methodology includes data extraction, processing, mapping, and spatial analysis. Visualization of the obtained results was carried out with Geographic Information System tools. The result is an extension of the state of the knowledge of the quality and usefulness of the data used for seabed and sea surface modeling and knowledge of the accuracy of the generated models. Sea level is averaged over time and space (excluding waves, tides, etc.). Its changes, along with knowledge of the topography of the ocean floor - inform us indirectly about the volume of the entire water ocean. The true shape of the ocean surface is further varied by such phenomena as tides, differences in atmospheric pressure, wind systems, thermal expansion of water, or phases of ocean circulation. Depending on the location of the point, the higher the depth, the lower the trend of sea level change. Studies show that combining data sets, from different sources, with different accuracies can affect the quality of sea surface and seafloor topography models.

Keywords: seafloor, sea surface height, bathymetry, satellite altimetry

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Authors: Jiun-Nan Hou, Tien-Huang Chen, Wei-June Chen

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Dengue viruses (DENVs) are naturally transmitted between humans by mosquito vectors. Mosquito cells usually survive DENV infection, allowing infected mosquitoes to retain an active status for virus transmission. In this study, we found that DENV2 virus infection in mosquito cells causes the unfolded protein response (UPR) that activates the protein kinase RNA-like endoplasmic reticulum kinase (PERK) signal pathway, leading to shutdown of global protein translation in infected cells which was apparently regulated by the PERK signal pathway. According to observation in this study, the PERK signal pathway in DENV2-infected C6/36 cells alleviates ER stress, and reduces initiator and effector caspases, as well as the apoptosis rate via shutdown of cellular proteins. In fact, phosphorylation of eukaryotic initiation factor 2ɑ (eIF2ɑ) by the PERK signal pathway may impair recruitment of ribosomes that bind to the mRNA 5’-cap structure, resulting in an inhibitory effect on canonical cap-dependent cellular protein translation. The resultant pro-survival “byproduct” of infected mosquito cells is undoubtedly advantageous for viral replication. This finding provides insights into elucidating the PERK-mediated modulating web that is actively involved in dynamic protein synthesis, cell survival, and viral replication in mosquito cells.

Keywords: cap-dependent protein translation, dengue virus, endoplasmic reticulum stress, mosquito cells, PERK signal pathway

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Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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Authors: B. Kishore Kumar, Rakesh Pogula, T. Kishore Kumar

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The steepness of an audio signal which is produced by the musical instruments, specifically percussive instruments is the perception of how high tone or low tone which can be considered as a frequency closely related to the fundamental frequency. This paper presents a novel method for silence removal and segmentation of music signals produced by the percussive instruments and the performance of proposed method is studied with the help of MATLAB simulations. This method is based on two simple features, namely the signal energy and the spectral centroid. As long as the feature sequences are extracted, a simple thresholding criterion is applied in order to remove the silence areas in the sound signal. The simulations were carried on various instruments like drum, flute and guitar and results of the proposed method were analyzed.

Keywords: percussive instruments, spectral energy, spectral centroid, silence removal

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Chenchen Liu, Jacques Audran

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Using tablet apps with a certain educational purpose to promote young children’s cognitive development, is quite common now. Developing an educational app on an Ipad like tablet, especially for a young child (age 3-5) requires an optimal level of challenge to continuously attract children’s attention and obtain an educational effect. Adaptive difficulty adjustment, which could dynamically set the difficulty in the challenge according to children’s performance, seems to be a good solution. Since space concept plays an important role in young children’s cognitive development, we made an experimental comparison in a French kindergarten between one group of 23 children using an educational app ‘Debout Ludo’ with adaptive difficulty settings and another group of 20 children using the previous version of ‘Debout Ludo’ with a classic incremental difficulty adjustment. The experiment results of spatial problem solving indicated that a significantly higher learning outcome was acquired by the young children who used the adaptive version of the app.

Keywords: adaptive difficulty, spatial problem solving, tactile tablet, young children

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Authors: Melkamu A. Zeru, Aweke A. Mitiku, Endashaw Amuka

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Background: Under-five mortality is the likelihood that a baby will pass away before turning exactly 5 years old, represented as a percentage per 1,000 live births. Exploring the spatial distribution and identifying the temporal pattern is important to reducing under-five child mortality globally, including in Ethiopia. Thus, this study aimed to identify the risk factors of under-five mortality and the spatiotemporal variation in Ethiopian administrative zones. Method: This study used the 2000-2016 Ethiopian Demographic and Health Survey (EDHS) data, which were collected using a two-stage sampling method. A total of 43,029 (10,873 in 2000, 9,861 in 2005, 11,654 in 2011, and 10,641 in 2016) weighted sample under-five child mortality was used. The space-time dynamic model was employed to account for spatial and time effects in 65 administrative zones in Ethiopia. Results: From the result of a general nesting spatial-temporal dynamic model, there was a significant space-time interaction effect [γ = -0.1444, 95 % CI (-0.6680, -0.1355)] for under-five mortality. The increase in the percentages of mothers illiteracy [𝛽 = 0.4501, 95% CI (0.2442, 0.6559)], not vaccinated[𝛽= 0.7681, 95% CI (0.5683, 0.9678)], unimproved water[𝛽= 0.5801, CI (0.3793, 0.7808)] were increased death rates for under five children while increased percentage of contraceptive use [𝛽= -0.6609, 95% CI (-0.8636, -0.4582)] and ANC visit > 4 times [𝛽= -0.1585, 95% CI(-0.1812, -0.1357)] were contributed to the decreased under-five mortality rate at the zone in Ethiopia. Conclusions: Even though the mortality rate for children under five has decreased over time, still there is still higher in different zones of Ethiopia. There exists spatial and temporal variation in under-five mortality among zones. Therefore, it is very important to consider spatial neighbourhoods and temporal context when aiming to avoid under-five mortality.

Keywords: under-five children mortality, space-time dynamic, spatiotemporal, Ethiopia

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Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

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Authors: Mohamed O. Babana

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In wireless channel multipath is the propagation phenomena where the transmitted signal arrive at the receiver side with many of paths, the signal at these paths arrive with different time delay the results is random signal fading due to intersymbols interference(ISI). This paper deals with identification of orthogonal frequency division multiplexing (OFDM) technology, and how it is used to overcome intersymbol interference due to multipath. Also investigates the effect of Additive White Gaussian Noise Channel (AWGN) on OFDM using multi-level modulation of Phase Shift Keying (PSK), computer simulation to calculate the bit error rate (BER) under AWGN channel is applied. A comparison study is carried out to obtain the Bit Error Rate performance for OFDM to identify the best multi-level modulation of PSK.

Keywords: intersymbol interference(ISI), bit error rate(BER), modulation, multiplexing, simulation

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Authors: Muhammet Dursun Kaya, Hasan Asil

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In recent years, different methods have been proposed to optimize question processing in database. Although different methods have been proposed to optimize the query, but the problem which exists here is that most of these methods destroy the query execution plan after executing the query. This research attempts to solve the above problem by using a combination of methods of communicating with the database (the present questions in the programming code and using store procedures) and making query processing adaptive in database, and proposing a new approach for optimization of query processing by introducing the idea of dynamic store procedures. This research creates dynamic store procedures in the database according to the proposed algorithm. This method has been tested on applied software and results shows a significant improvement in reducing the query processing time and also reducing the workload of DBMS. Other advantages of this algorithm include: making the programming environment a single environment, eliminating the parametric limitations of the stored procedures in the database, making the stored procedures in the database dynamic, etc.

Keywords: relational database, agent, query processing, adaptable, communication with the database

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Authors: Jiayue Yang

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Based on an analysis of China's database of certified disabled persons in 2021, this study reveals several key findings. Firstly, the proportion of certified mentally disabled persons among China's certified disabled population (Certification rate 1) shows a decreasing distribution from the East to the West and from the South to the North. Secondly, the spatial distribution of the number of mentally disabled persons per 1,000 people holding certificates (certification rate 2) shows a relatively scattered pattern, with significant variations observed between cities in the eastern region. However, on an overall scale, a south-north gradient can still be observed, with higher rates in the North and lower rates in the west, while the central region demonstrates higher rates compared to the western region. The variation in the rate of mentally handicapped certificates among regions is influenced not only by traditional culture and welfare level but also exhibits a certain correlation with the level of economic development.

Keywords: certified disabled persons, mentally disabled persons, spatial distribution, China

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Authors: Sun fang, Zhang Wenxin

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This paper establishes an evaluation index system for spatio-temporal patterns of urbanization, with the county as research unit. We use the Entropy Weight method, coefficient variance, the Theil index and ESDA-GIS to analyze spatial patterns and evolutionary characteristics of New-Type Urbanization in the Central Plains Economic Region (CPER) between 2000 and 2011. Results show that economic benefit, non-agricultural employment level and level of market development are the most important factors influencing the level of New-Type Urbanization in the CPER; overall regional differences in New-Type Urbanization have declined while spatial correlations have increased from 2000 to 2011. The overall spatial pattern has changed little, however; differences between the western and eastern areas of the CPER are clear, and the pattern of a strong west and weak east did not change significantly over the study period. Areas with high levels of New-Type Urbanization were mostly distributed along the Beijing-Guangzhou and LongHai Railways on both sides, a new influx of urbanization was tightly clustered around ZhengZhou in the Central Henan Urban Agglomeration, but this trend was found to be weakening slightly. The level of New-Type Urbanization in municipal districts was found to be much higher than it was in the county generally. Provincial borders experienced a lower rate of growth and a lower level of New-Type Urbanization than did any other areas, consistently forming clusters of cold spots and sub-cold spots. The analysis confirms that historical development, location, and diffusion effects of urban agglomeration are the main drivers of changes in New-Type Urbanization patterns in CPER.

Keywords: new-type urbanization, spatial pattern, central plains economic region, spatial evolution

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Authors: Yelbek B. Utepov, Assel T. Mukhamejanova, Aliya K. Aldungarova, Aida G. Nazarova, Sabit A. Karaulov, Nurgul T. Alibekova, Aigul K. Kozhas, Dias Kazhimkanuly, Akmaral K. Tleubayeva

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This research focuses on enhancing geotechnical surveying for foundation design through the spatial interpolation of intermediate soil properties. Traditional geotechnical practices rely on discrete data from borehole drilling, soil sampling, and laboratory analyses, often neglecting the continuous nature of soil properties and disregarding values in intermediate locations. This study challenges these omissions by emphasizing interpolation techniques such as Kriging, Inverse Distance Weighting, and Spline interpolation to capture the nuanced spatial variations in soil properties. The methodology is applied to geotechnical survey data from two construction sites in Astana, Kazakhstan, revealing continuous representations of Young's Modulus, Cohesion, and Friction Angle. The spatial heatmaps generated through interpolation offered valuable insights into the subsurface environment, highlighting heterogeneity and aiding in more informed foundation design decisions for considered cites. Moreover, intriguing patterns of heterogeneity, as well as visual clusters and transitions between soil classes, were explored within seemingly uniform layers. The study bridges the gap between discrete borehole samples and the continuous subsurface, contributing to the evolution of geotechnical engineering practices. The proposed approach, utilizing open-source software geographic information systems, provides a practical tool for visualizing soil characteristics and may pave the way for future advancements in geotechnical surveying and foundation design.

Keywords: soil mechanical properties, spatial interpolation, inverse distance weighting, heatmaps

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Authors: Hailang Yang

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To ensure the confidentiality and integrity of speech signals in communication transmission, this paper proposes a voice signal encryption scheme based on chaotic theory. Firstly, the scheme utilizes chaotic mapping to generate a key stream and then employs the key stream to perform bitwise exclusive OR (XOR) operations for encrypting the speech signal. Additionally, the scheme utilizes a chaotic hash function to generate a Message Authentication Code (MAC), which is appended to the encrypted data to verify the integrity of the data. Subsequently, we analyze the security performance and encryption efficiency of the scheme, comparing and optimizing it against existing solutions. Finally, experimental results demonstrate that the proposed scheme can resist common attacks, achieving high-quality encryption and speed.

Keywords: chaotic theory, XOR encryption, chaotic hash function, Message Authentication Code (MAC)

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Moustafa Osman Mohammed

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The resilient and sustainable of construction ecology is essential to world’s socio-economic development. Environmental resilience is crucial in relating construction ecology to topology of spatial-economic model. Sustainability of spatial-economic model gives attention to green business to comply with Earth’s System for naturally exchange patterns of ecosystems. The systems ecology has consistent and periodic cycles to preserve energy and materials flow in Earth’s System. When model structure is influencing communication of internal and external features in system networks, it postulated the valence of the first-level spatial outcomes (i.e., project compatibility success). These instrumentalities are dependent on second-level outcomes (i.e., participant security satisfaction). These outcomes of model are based on measuring database efficiency, from 2015 to 2025. The model topology has state-of-the-art in value-orientation impact and correspond complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic model; develop a set of sustainability indicators associated with model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate environmental resilience. The model is managing and developing schemes from perspective of multiple sources pollutants through the input–output criteria. These criteria are evaluated the external insertions effects to conduct Monte Carlo simulations and analysis for using matrices in a unique spatial structure. The balance “equilibrium patterns” such as collective biosphere features, has a composite index of the distributed feedback flows. These feedback flows have a dynamic structure with physical and chemical properties for gradual prolong of incremental patterns. While these structures argue from system ecology, static loads are not decisive from an artistic/architectural perspective. The popularity of system resilience, in the systems structure related to ecology has not been achieved without the generation of confusion and vagueness. However, this topic is relevant to forecast future scenarios where industrial regions will need to keep on dealing with the impact of relative environmental deviations. The model attempts to unify analytic and analogical structure of urban environments using database software to integrate sustainability outcomes where the process based on systems topology of construction ecology.

Keywords: system ecology, construction ecology, industrial ecology, spatial-economic model, systems topology

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Authors: Min Zhou, Kaixuan Lin, Yaping Huang

Abstract:

In this paper, the industrial space of metropolitan area in Wuhan is taken as a sample. First of all, it puts forward that the structure of service economy, circle gradient relocation and high degree of regional collaboration are the rules of industrial spatial development in the modern world cities. Secondly, using the economic statistics and land use vector data (1993, 2004, 2010, and 2013) of Wuhan, it analyzes the present situation of industry development and the characteristics of industrial space layout from three aspects of the industrial economic structure, industrial layout, and industrial regional synergy. Then, based on the industrial development regularity of world cities, it puts forward to construct the industrial spatial level of ‘complex industrial concentration area + modular industry unit’ and the industrial spatial structure of ‘13525’. Finally, it comes up with the optimization tactics of the industrial space’s transformation in the future under the background of new economic era.

Keywords: big city of metropolitan area, industrial space, characteristics, layout, strategy

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Authors: Ji-Wook Mauk, Yu-Suk Kim, Hyung-Joon Kim

Abstract:

This study carried out comparative seismic performance of reinforced concrete frames infilled by masonry walls with different heights. Partial and fully infilled RC frames were modeled for the research objectives and the analysis model for a bare reinforced concrete frame was established for comparison. Non-linear static analyses for the studied frames were performed to investigate their structural behavior under extreme loading conditions and to find out their collapse mechanism. It was observed from analysis results that the strengths of the partial infilled RC frames are increased and their ductility is reduced, as infilled masonry walls are higher. Especially, Reinforced concrete frames with a higher partial infilled masonry wall would experience shear failures. Non-linear dynamic analyses using 10 earthquake records show that the bare and fully infilled reinforced concrete frames present stable collapse mechanism while the reinforced concrete frames with a partially infilled masonry wall collapse in more brittle manner due to short-column effects.

Keywords: fully infilled RC frame, partially infilled RC frame, masonry wall, short-column effect

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Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

Abstract:

Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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Authors: Aman Kaur, Colin Ribton, Wamadeva Balachandaran

Abstract:

Electron beam welding due to its inherent advantages is being extensively used for material processing where high precision is required. Especially in aerospace or nuclear industries, there are high quality requirements and the cost of materials and processes is very high which makes it very important to ensure the beam quality is maintained and checked prior to carrying out the welds. Although the processes in these industries are highly controlled, however, even the minor changes in the operating parameters of the electron gun can make large enough variations in the beam quality that can result in poor welding. To measure the beam quality a simple device has been designed that can be used at high powers. The device consists of two slits in x and y axis which collects a small portion of the beam current when the beam is deflected over the slits. The signals received from the device are processed in data acquisition hardware and the dedicated software developed for the device. The device has been used in controlled laboratory environments to analyse the signals and the weld quality relationships by varying the focus current. The results showed matching trends in the weld dimensions and the beam characteristics. Further experimental work is being carried out to determine the ability of the device and signal processing software to detect subtle changes in the beam quality and to relate these to the physical weld quality indicators.

Keywords: electron beam welding, beam quality, high power, weld quality indicators

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Authors: Szu-Hua Wang

Abstract:

Urban ecosystems, as complex coupled human-environment systems, contain abundant natural resources for breeding natural assets and, at the same time, attract urban assets and consume natural resources, triggered by urban development. Land use change illustrates the interaction between human activities and environments factually. However, IPCC (2014) announces that land use change and urbanization due to human activities are the major cause of climate change, leading to serious impacts on urban ecosystem resilience and risk. For this reason, risk assessment and resilience analysis are the keys for responding to climate change on urban ecosystems. Urban spatial planning can guide urban development by land use planning, transportation planning, and environmental planning and affect land use allocation and human activities by building major constructions and protecting important national land resources simultaneously. Urban spatial planning can aggravate climate change and, on the other hand, mitigate and adapt climate change. Research on effects of spatial planning on land use change and climate change is one of intense issues currently. Therefore, this research focuses on developing frameworks for risk assessment and resilience analysis from the aspect of ecosystem based on typhoon precipitation in Taipei area. The integrated method of risk assessment and resilience analysis will be also addressed for applying spatial planning practice and sustainable development.

Keywords: ecosystem, land use change, risk analysis, resilience

Procedia PDF Downloads 417