Search results for: algebraic signal processing
4263 Systematic NIR of Internal Disorder and Quality Detection of Apple Fruit
Authors: Eid Alharbi, Yaser Miaji, Saeed Alzahrani
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The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic convener belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300 nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950 nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950 nm region the online sorting system was constructed.Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology
Procedia PDF Downloads 4974262 Clean Gold Solution from Printed Circuit Board Physical Processing Dust by Selective Complexation
Authors: Iyiola O. Otunniyi, Oluwayimika O. Oluokun
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The two-step leaching process of PCB dust will produce a first leaching stream containing assorted metals that still requires more demanding multistage processing afterward to recover base metals and precious metals. In this work, three-step selective complexations produce a clean gold solution from printed circuit board dust. After optimizing for temperature and concentrations, the first step under oxidative ammonia leaching recovered no gold, 90 % Cu and 50 % Zn. Second step acid leaching recovered no gold, 89 % Fe, 48 % Zn, 94 % Ni. The recoveries generally increased with reducing dust particle sizes, except for zinc under oxidative ammonia, and it was noted that its various alloy forms in PCB could be responsible for this. At the third leaching step using acidified thiourea with 0.1 M H₂O₂ at 25 OC, gold recovery was 99 %. The leaching rate was shown to be chemically controlled, implying that reagent dosage control will compensate for feed assay shifts in an operation design. Copper, zinc and nickel will be easily recoverable from leach solutions of the first two steps in this leaching scheme. The third step produced a clean gold solution for easy processing downstream.Keywords: gold thiourea complexation, printed circuit board, step leaching, selective recovery
Procedia PDF Downloads 134261 Production and Distribution Network Planning Optimization: A Case Study of Large Cement Company
Authors: Lokendra Kumar Devangan, Ajay Mishra
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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.Keywords: production planning, mixed integer optimization, network model, network optimization
Procedia PDF Downloads 714260 RBF Neural Network Based Adaptive Robust Control for Bounded Position/Force Control of Bilateral Teleoperation Arms
Authors: Henni Mansour Abdelwaheb
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This study discusses the design of a bounded position/force feedback controller developed to ensure position and force tracking for bilateral teleoperation arms operating with variable delay, and actuator saturation. Also, an adaptive robust Radial Basis Function (RBF) neural network is used to estimate the environment torque. The parameters of the environment torque are then sent from the slave site to the master site as a non-power signal to avoid passivity problems. Moreover, a nonlinear function is applied to each controller term as a smooth saturation function, providing a bounded control signal and preserving the system’s actuators. Lastly, the Lyapunov approach demonstrates the global stability of the controlled system, and numerical experiment results further confirm the validity of the presented strategy.Keywords: teleoperation manipulators system, time-varying delay, actuator saturation, adaptive robust rbf neural network approximation, uncertainties
Procedia PDF Downloads 774259 Geometallurgy of Niobium Deposits: An Integrated Multi-Disciplined Approach
Authors: Mohamed Nasraoui
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Spatial ore distribution, ore heterogeneity and their links with geological processes involved in Niobium concentration are all factors for consideration when bridging field observations to extraction scheme. Indeed, mineralogy changes of Nb-hosting phases, their textural relationships with hydrothermal or secondary minerals, play a key control over mineral processing. This study based both on filed work and ore characterization presents data from several Nb-deposits related to carbonatite complexes. The results obtained by a wide range of analytical techniques, including, XRD, XRF, ICP-MS, SEM, Microprobe, Spectro-CL, FTIR-DTA and Mössbauer spectroscopy, demonstrate how geometallurgical assessment, at all stage of mine development, can greatly assist in the design of a suitable extraction flowsheet and data reconciliation.Keywords: carbonatites, Nb-geometallurgy, Nb-mineralogy, mineral processing.
Procedia PDF Downloads 1664258 Improved Wearable Monitoring and Treatment System for Parkinson’s Disease
Authors: Bulcha Belay Etana, Benny Malengier, Janarthanan Krishnamoorthy, Timothy Kwa, Lieva VanLangenhove
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Electromyography measures the electrical activity of muscles using surface electrodes or needle electrodes to monitor various disease conditions. Recent developments in the signal acquisition of electromyograms using textile electrodes facilitate wearable devices, enabling patients to monitor and control their health status outside of healthcare facilities. Here, we have developed and tested wearable textile electrodes to acquire electromyography signals from patients suffering from Parkinson’s disease and incorporated a feedback-control system to relieve muscle cramping through thermal stimulus. In brief, the textile electrodes made of stainless steel was knitted into a textile fabric as a sleeve, and their electrical characteristic, such as signal-to-noise ratio, was compared with traditional electrodes. To relieve muscle cramping, a heating element made of stainless-steel conductive yarn sewn onto cotton fabric, coupled with a vibration system, was developed. The system integrated a microcontroller and a Myoware muscle sensor to activate the heating element as well as the vibration motor when cramping occurs, and at the same time, the element gets deactivated when the muscle cramping subsides. An optimum therapeutic temperature of 35.5 °C is regulated by continuous temperature monitoring to deactivate the heating system when this threshold value is reached. The textile electrode exhibited a signal-to-noise ratio of 6.38dB, comparable to that of the traditional electrode’s value of 7.05 dB. For a given 9 V power supply, the rise time was about 6 minutes for the developed heating element to reach an optimum temperature.Keywords: smart textile system, wearable electronic textile, electromyography, heating textile, vibration therapy, Parkinson’s disease
Procedia PDF Downloads 1084257 Methodology for Temporary Analysis of Production and Logistic Systems on the Basis of Distance Data
Authors: M. Mueller, M. Kuehn, M. Voelker
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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing
Procedia PDF Downloads 1344256 Digital Signal Processor Implementation of a Novel Sinusoidal Pulse Width Modulation Algorithm Algorithm for a Reduced Delta Inverter
Authors: Asma Ben Rhouma, Mahmoud Hamouda
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The delta inverter is considered as the reduced three-phase dc/ac converter topology. It contains only three two-quadrant power switches compared to six in the conventional one. This reduced power conversion topology is widely considered in many industrial applications, such as electric traction and large photovoltaic systems. This paper is focused on a new sinusoidal pulse width modulation algorithm (SPWM) developed for the delta inverter. As an unconventional inverter’s structure, irregular modulating functions waveforms of the SPWM switching technique are generated. The performances of the proposed SPWM technique was proven through computer simulations carried out on a delta inverter feeding a three-phase RL load. Digital Signal Processor (DSP) implementation of the novel SPWM algorithm have been realized on a laboratory prototype of the delta inverter feeding an RL load and a squirrel cage induction motor. Experimental results have highlighted its high performances under the proposed SPWM method.Keywords: delta inverter, SPWM, simulation, DSP implementation
Procedia PDF Downloads 1644255 New NIR System for Detecting the Internal Disorder and Quality of Apple Fruit
Authors: Eid Alharbi, Yaser Miaji
Abstract:
The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology
Procedia PDF Downloads 3984254 Novel NIR System for Detection of Internal Disorder and Quality of Apple Fruit
Authors: Eid Alharbi, Yaser Miaji
Abstract:
The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology
Procedia PDF Downloads 3864253 Integrating Wearable-Textiles Sensors and IoT for Continuous Electromyography Monitoring
Authors: Bulcha Belay Etana, Benny Malengier, Debelo Oljira, Janarthanan Krishnamoorthy, Lieva Vanlangenhove
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Electromyography (EMG) is a technique used to measure the electrical activity of muscles. EMG can be used to assess muscle function in a variety of settings, including clinical, research, and sports medicine. The aim of this study was to develop a wearable textile sensor for EMG monitoring. The sensor was designed to be soft, stretchable, and washable, making it suitable for long-term use. The sensor was fabricated using a conductive thread material that was embroidered onto a fabric substrate. The sensor was then connected to a microcontroller unit (MCU) and a Wi-Fi-enabled module. The MCU was programmed to acquire the EMG signal and transmit it wirelessly to the Wi-Fi-enabled module. The Wi-Fi-enabled module then sent the signal to a server, where it could be accessed by a computer or smartphone. The sensor was able to successfully acquire and transmit EMG signals from a variety of muscles. The signal quality was comparable to that of commercial EMG sensors. The development of this sensor has the potential to improve the way EMG is used in a variety of settings. The sensor is soft, stretchable, and washable, making it suitable for long-term use. This makes it ideal for use in clinical settings, where patients may need to wear the sensor for extended periods of time. The sensor is also small and lightweight, making it ideal for use in sports medicine and research settings. The data for this study was collected from a group of healthy volunteers. The volunteers were asked to perform a series of muscle contractions while the EMG signal was recorded. The data was then analyzed to assess the performance of the sensor. The EMG signals were analyzed using a variety of methods, including time-domain analysis and frequency-domain analysis. The time-domain analysis was used to extract features such as the root mean square (RMS) and average rectified value (ARV). The frequency-domain analysis was used to extract features such as the power spectrum. The question addressed by this study was whether a wearable textile sensor could be developed that is soft, stretchable, and washable and that can successfully acquire and transmit EMG signals. The results of this study demonstrate that a wearable textile sensor can be developed that meets the requirements of being soft, stretchable, washable, and capable of acquiring and transmitting EMG signals. This sensor has the potential to improve the way EMG is used in a variety of settings.Keywords: EMG, electrode position, smart wearable, textile sensor, IoT, IoT-integrated textile sensor
Procedia PDF Downloads 754252 Private Coded Computation of Matrix Multiplication
Authors: Malihe Aliasgari, Yousef Nejatbakhsh
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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers
Procedia PDF Downloads 1254251 Advanced Driver Assistance System: Veibra
Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins
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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system
Procedia PDF Downloads 1554250 A Comparison of Alternative Traffic Controls for Interchange Ramp Areas Using Synchro Software
Authors: Mohamed Mesbah, Bruce Janson
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An interchange is the most important component of freeway and highway facilities. It is working as a connector between the highway’s elements. The main goal of designing interchanges is to provide an acceptable level of service and delay to make vehicles move smoothly when they are entering and exiting the interchange. There are many factors that can have a significant impact on the level of service; the main factors are traffic volumes, and type of interchange. This paper will discuss interchange with roundabouts under various values of traffic volumes to determine the level of service of the interchanges that will be studied in this paper and replace the system of interchange from roundabout to traffic signal to make a significant compression between these systems. A secondary goal is to propose improvements for scenarios where the level of service is deemed unacceptable. This will be achieved using Synchro traffic simulation software, which facilitates the simulation and optimization of interchanges to enhance operational efficiency and safety.Keywords: interchange, roundabout, traffic signal, Synchro, delay, level of service, traffic volumes, vehicles, simulation, optimization, adjustment
Procedia PDF Downloads 264249 Nanorods Based Dielectrophoresis for Protein Concentration and Immunoassay
Authors: Zhen Cao, Yu Zhu, Junxue Fu
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Immunoassay, i.e., antigen-antibody reaction, is crucial for disease diagnostics. To achieve the adequate signal of the antigen protein detection, a large amount of sample and long incubation time is needed. However, the amount of protein is usually small at the early stage, which makes it difficult to detect. Unlike cells and DNAs, no valid chemical method exists for protein amplification. Thus, an alternative way to improve the signal is through particle manipulation techniques to concentrate proteins, among which dielectrophoresis (DEP) is an effective one. DEP is a technique that concentrates particles to the designated region through a force created by the gradient in a non-uniform electric field. Since DEP force is proportional to the cube of particle size and square of electric field gradient, it is relatively easy to capture larger particles such as cells. For smaller ones like proteins, a super high gradient is then required. In this work, three-dimensional Ag/SiO2 nanorods arrays, fabricated by an easy physical vapor deposition technique called as oblique angle deposition, have been integrated with a DEP device and created the field gradient as high as of 2.6×10²⁴ V²/m³. The nanorods based DEP device is able to enrich bovine serum albumin (BSA) protein by 1800-fold and the rate has reached 180-fold/s when only applying 5 V electric potential. Based on the above nanorods integrated DEP platform, an immunoassay of mouse immunoglobulin G (IgG) proteins has been performed. Briefly, specific antibodies are immobilized onto nanorods, then IgG proteins are concentrated and captured, and finally, the signal from fluorescence-labelled antibodies are detected. The limit of detection (LoD) is measured as 275.3 fg/mL (~1.8 fM), which is a 20,000-fold enhancement compared with identical assays performed on blank glass plates. Further, prostate-specific antigen (PSA), which is a cancer biomarker for diagnosis of prostate cancer after radical prostatectomy, is also quantified with a LoD as low as 2.6 pg/mL. The time to signal saturation has been significantly reduced to one minute. In summary, together with an easy nanorod fabrication and integration method, this nanorods based DEP platform has demonstrated highly sensitive immunoassay performance and thus poses great potentials in applications for early point-of-care diagnostics.Keywords: dielectrophoresis, immunoassay, oblique angle deposition, protein concentration
Procedia PDF Downloads 1034248 Detecting Music Enjoyment Level Using Electroencephalogram Signals and Machine Learning Techniques
Authors: Raymond Feng, Shadi Ghiasi
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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals
Procedia PDF Downloads 644247 Reading Comprehension in Profound Deaf Readers
Authors: S. Raghibdoust, E. Kamari
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Research show that reduced functional hearing has a detrimental influence on the ability of an individual to establish proper phonological representations of words, since the phonological representations are claimed to mediate the conceptual processing of written words. Word processing efficiency is expected to decrease with a decrease in functional hearing. In other words, it is predicted that hearing individuals would be more capable of word processing than individuals with hearing loss, as their functional hearing works normally. Studies also demonstrate that the quality of the functional hearing affects reading comprehension via its effect on their word processing skills. In other words, better hearing facilitates the development of phonological knowledge, and can promote enhanced strategies for the recognition of written words, which in turn positively affect higher-order processes underlying reading comprehension. The aims of this study were to investigate and compare the effect of deafness on the participants’ abilities to process written words at the lexical and sentence levels through using two online and one offline reading comprehension tests. The performance of a group of 8 deaf male students (ages 8-12) was compared with that of a control group of normal hearing male students. All the participants had normal IQ and visual status, and came from an average socioeconomic background. None were diagnosed with a particular learning or motor disability. The language spoken in the homes of all participants was Persian. Two tests of word processing were developed and presented to the participants using OpenSesame software, in order to measure the speed and accuracy of their performance at the two perceptual and conceptual levels. In the third offline test of reading comprehension which comprised of semantically plausible and semantically implausible subject relative clauses, the participants had to select the correct answer out of two choices. The data derived from the statistical analysis using SPSS software indicated that hearing and deaf participants had a similar word processing performance both in terms of speed and accuracy of their responses. The results also showed that there was no significant difference between the performance of the deaf and hearing participants in comprehending semantically plausible sentences (p > 0/05). However, a significant difference between the performances of the two groups was observed with respect to their comprehension of semantically implausible sentences (p < 0/05). In sum, the findings revealed that the seriously impoverished sentence reading ability characterizing the profound deaf subjects of the present research, exhibited their reliance on reading strategies that are based on insufficient or deviant structural knowledge, in particular in processing semantically implausible sentences, rather than a failure to efficiently process written words at the lexical level. This conclusion, of course, does not mean to say that deaf individuals may never experience deficits at the word processing level, deficits that impede their understanding of written texts. However, as stated in previous researches, it sounds reasonable to assume that the more deaf individuals get familiar with written words, the better they can recognize them, despite having a profound phonological weakness.Keywords: deafness, reading comprehension, reading strategy, word processing, subject and object relative sentences
Procedia PDF Downloads 3394246 Bamboo: A Trendy and New Alternative to Wood
Authors: R. T. Aggangan, R. J. Cabangon
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Bamboo is getting worldwide attention over the last 20 to 30 years due to numerous uses and it is regarded as the closest material that can be used as substitute to wood. In the domestic market, high quality bamboo products are sold in high-end markets while lower quality products are generally sold to medium and low income consumers. The global market in 2006 stands at about 7 billion US dollars and was projected to increase to US$ 17 B from 2015 to 2020. The Philippines had been actively producing and processing bamboo products for the furniture, handicrafts and construction industry. It was however in 2010 that the Philippine bamboo industry was formalized by virtue of Executive Order 879 that stated that the Philippine bamboo industry development is made a priority program of the government and created the Philippine Bamboo Industry Development Council (PBIDC) to provide the overall policy and program directions of the program for all stakeholders. At present, the most extensive use of bamboo is for the manufacture of engineered bamboo for school desks for all public schools as mandated by EO 879. Also, engineered bamboo products are used for high-end construction and furniture as well as for handicrafts. Development of cheap adhesives, preservatives, and finishing chemicals from local species of plants, development of economical methods of drying and preservation, product development and processing of lesser-used species of bamboo, development of processing tools, equipment and machineries are the strategies that will be employed to reduce the price and mainstream engineered bamboo products in the local and foreign market. In addition, processing wastes from bamboo can be recycled into fuel products such as charcoal are already in use. The more exciting possibility, however, is the production of bamboo pellets that can be used as a substitute for wood pellets for heating, cooking and generating electricity.Keywords: bamboo charcoal and light distillates, engineered bamboo, furniture and handicraft industries, housing and construction, pellets
Procedia PDF Downloads 2494245 Classifying and Analysis 8-Bit to 8-Bit S-Boxes Characteristic Using S-Box Evaluation Characteristic
Authors: Muhammad Luqman, Yusuf Kurniawan
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S-Boxes is one of the linear parts of the cryptographic algorithm. The existence of S-Box in the cryptographic algorithm is needed to maintain non-linearity of the algorithm. Nowadays, modern cryptographic algorithms use an S-Box as a part of algorithm process. Despite the fact that several cryptographic algorithms today reuse theoretically secure and carefully constructed S-Boxes, there is an evaluation characteristic that can measure security properties of S-Boxes and hence the corresponding primitives. Analysis of an S-Box usually is done using manual mathematics calculation. Several S-Boxes are presented as a Truth Table without any mathematical background algorithm. Then, it’s rather difficult to determine the strength of Truth Table S-Box without a mathematical algorithm. A comprehensive analysis should be applied to the Truth Table S-Box to determine the characteristic. Several important characteristics should be owned by the S-Boxes, they are Nonlinearity, Balancedness, Algebraic degree, LAT, DAT, differential delta uniformity, correlation immunity and global avalanche criterion. Then, a comprehensive tool will be present to automatically calculate the characteristics of S-Boxes and determine the strength of S-Box. Comprehensive analysis is done on a deterministic process to produce a sequence of S-Boxes characteristic and give advice for a better S-Box construction.Keywords: cryptographic properties, Truth Table S-Boxes, S-Boxes characteristic, deterministic process
Procedia PDF Downloads 3654244 Optimal Protection Coordination in Distribution Systems with Distributed Generations
Authors: Abdorreza Rabiee, Shahla Mohammad Hoseini Mirzaei
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The advantages of distributed generations (DGs) based on renewable energy sources (RESs) leads to high penetration level of DGs in distribution network. With incorporation of DGs in distribution systems, the system reliability and security, as well as voltage profile, is improved. However, the protection of such systems is still challenging. In this paper, at first, the related papers are reviewed and then a practical scheme is proposed for coordination of OCRs in distribution system with DGs. The coordination problem is formulated as a nonlinear programming (NLP) optimization problem with the object function of minimizing total operating time of OCRs. The proposed method is studied based on a simple test system. The optimization problem is solved by General Algebraic Modeling System (GAMS) to calculate the optimal time dial setting (TDS) and also pickup current setting of OCRs. The results show the effectiveness of the proposed method and its applicability.Keywords: distributed generation, DG, distribution network, over current relay, OCR, protection coordination, pickup current, time dial setting, TDS
Procedia PDF Downloads 1394243 A Nonlinear Dynamical System with Application
Authors: Abdullah Eqal Al Mazrooei
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In this paper, a nonlinear dynamical system is presented. This system is a bilinear class. The bilinear systems are very important kind of nonlinear systems because they have many applications in real life. They are used in biology, chemistry, manufacturing, engineering, and economics where linear models are ineffective or inadequate. They have also been recently used to analyze and forecast weather conditions. Bilinear systems have three advantages: First, they define many problems which have a great applied importance. Second, they give us approximations to nonlinear systems. Thirdly, they have a rich geometric and algebraic structures, which promises to be a fruitful field of research for scientists and applications. The type of nonlinearity that is treated and analyzed consists of bilinear interaction between the states vectors and the system input. By using some properties of the tensor product, these systems can be transformed to linear systems. But, here we discuss the nonlinearity when the state vector is multiplied by itself. So, this model will be able to handle evolutions according to the Lotka-Volterra models or the Lorenz weather models, thus enabling a wider and more flexible application of such models. Here we apply by using an estimator to estimate temperatures. The results prove the efficiency of the proposed system.Keywords: Lorenz models, nonlinear systems, nonlinear estimator, state-space model
Procedia PDF Downloads 2544242 Effect of Traffic Composition on Delay and Saturation Flow at Signal Controlled Intersections
Authors: Arpita Saha, Apoorv Jain, Satish Chandra, Indrajit Ghosh
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Level of service at a signal controlled intersection is directly measured from the delay. Similarly, saturation flow rate is a fundamental parameter to measure the intersection capacity. The present study calculates vehicle arrival rate, departure rate, and queue length for every five seconds interval in each cycle. Based on the queue lengths, the total delay of the cycle has been calculated using Simpson’s 1/3rd rule. Saturation flow has been estimated in terms of veh/hr of green/lane for every five seconds interval of the green period until at least three vehicles are left to cross the stop line. Vehicle composition shows an immense effect on total delay and saturation flow rate. The increase in two-wheeler proportion increases the saturation flow rate and reduces the total delay per vehicle significantly. Additionally, an increase in the heavy vehicle proportion reduces the saturation flow rate and increases the total delay for each vehicle.Keywords: delay, saturation flow, signalised intersection, vehicle composition
Procedia PDF Downloads 4654241 Evaluation of Condyle Alterations after Orthognathic Surgery with a Digital Image Processing Technique
Authors: Livia Eisler, Cristiane C. B. Alves, Cristina L. F. Ortolani, Kurt Faltin Jr.
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Purpose: This paper proposes a technically simple diagnosis method among orthodontists and maxillofacial surgeons in order to evaluate discrete bone alterations. The methodology consists of a protocol to optimize the diagnosis and minimize the possibility for orthodontic and ortho-surgical retreatment. Materials and Methods: A protocol of image processing and analysis, through ImageJ software and its plugins, was applied to 20 pairs of lateral cephalometric images obtained from cone beam computerized tomographies, before and 1 year after undergoing orthognathic surgery. The optical density of the images was analyzed in the condylar region to determine possible bone alteration after surgical correction. Results: Image density was shown to be altered in all image pairs, especially regarding the condyle contours. According to measures, condyle had a gender-related density reduction for p=0.05 and condylar contours had their alterations registered in mm. Conclusion: A simple, viable and cost-effective technique can be applied to achieve the more detailed image-based diagnosis, not depending on the human eye and therefore, offering more reliable, quantitative results.Keywords: bone resorption, computer-assisted image processing, orthodontics, orthognathic surgery
Procedia PDF Downloads 1614240 A Novel PWM/PFM Controller for PSR Fly-Back Converter Using a New Peak Sensing Technique
Authors: Sanguk Nam, Van Ha Nguyen, Hanjung Song
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For low-power applications such as adapters for portable devices and USB chargers, the primary side regulation (PSR) fly-back converter is widely used in lieu of the conventional fly-back converter using opto-coupler because of its simpler structure and lower cost. In the literature, there has been studies focusing on the design of PSR circuit; however, the conventional sensing method in PSR circuit using RC delay has a lower accuracy as compared to the conventional fly-back converter using opto-coupler. In this paper, we propose a novel PWM/PFM controller using new sensing technique for the PSR fly-back converter which can control an accurate output voltage. The conventional PSR circuit can sense the output voltage information from the auxiliary winding to regulate the duty cycle of the clock that control the output voltage. In the sensing signal waveform, there has two transient points at time the voltage equals to Vout+VD and Vout, respectively. In other to sense the output voltage, the PSR circuit must detect the time at which the current of the diode at the output equals to zero. In the conventional PSR flyback-converter, the sensing signal at this time has a non-sharp-negative slope that might cause a difficulty in detecting the output voltage information since a delay of sensing signal or switching clock may exist which brings out an unstable operation of PSR fly-back converter. In this paper instead of detecting output voltage at a non-sharp-negative slope, a sharp-positive slope is used to sense the proper information of the output voltage. The proposed PRS circuit consists of a saw-tooth generator, a summing circuit, a sample and hold circuit and a peak detector. Besides, there is also the start-up circuit which protects the chip from high surge current when the converter is turned on. Additionally, to reduce the standby power loss, a second mode which operates in a low frequency is designed beside the main mode at high frequency. In general, the operation of the proposed PSR circuit can be summarized as following: At the time the output information is sensed from the auxiliary winding, a saw-tooth signal from the saw-tooth generator is generated. Then, both of these signals are summed using a summing circuit. After this process, the slope of the peak of the sensing signal at the time diode current is zero becomes positive and sharp that make the peak easy to detect. The output of the summing circuit then is fed into a peak detector and the sample and hold circuit; hence, the output voltage can be properly sensed. By this way, we can sense more accurate output voltage information and extend margin even circuit is delayed or even there is the existence of noise by using only a simple circuit structure as compared with conventional circuits while the performance can be sufficiently enhanced. Circuit verification was carried out using 0.35μm 700V Magnachip process. The simulation result of sensing signal shows a maximum error of 5mV under various load and line conditions which means the operation of the converter is stable. As compared to the conventional circuit, we achieved very small error only used analog circuits compare with conventional circuits. In this paper, a PWM/PFM controller using a simple and effective sensing method for PSR fly-back converter has been presented in this paper. The circuit structure is simple as compared with the conventional designs. The gained results from simulation confirmed the idea of the designKeywords: primary side regulation, PSR, sensing technique, peak detector, PWM/PFM control, fly-back converter
Procedia PDF Downloads 3384239 Roughness Discrimination Using Bioinspired Tactile Sensors
Authors: Zhengkun Yi
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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination
Procedia PDF Downloads 3134238 The Structural Pattern: An Event-Related Potential Study on Tang Poetry
Authors: ShuHui Yang, ChingChing Lu
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Measuring event-related potentials (ERPs) has been fundamental to our understanding of how people process language. One specific ERP component, a P600, has been hypothesized to be associated with syntactic reanalysis processes. We, however, propose that the P600 is not restricted to reanalysis processes, but is the index of the structural pattern processing. To investigate the structural pattern processing, we utilized the effects of stimulus degradation in structural priming. To put it another way, there was no P600 effect if the structure of the prime was the same with the structure of the target. Otherwise, there would be a P600 effect if the structure were different between the prime and the target. In the experiment, twenty-two participants were presented with four sentences of Tang poetry. All of the first two sentences, being prime, were conducted with SVO+VP. The last two sentences, being the target, were divided into three types. Type one of the targets was SVO+VP. Type two of the targets was SVO+VPVP. Type three of the targets was VP+VP. The result showed that both of the targets, SVO+VPVP and VP+VP, elicited positive-going brainwave, a P600 effect, at 600~900ms time window. Furthermore, the P600 component was lager for the target’ VP+VP’ than the target’ SVO+VPVP’. That meant the more dissimilar the structure was, the lager the P600 effect we got. These results indicate that P600 was the index of the structure processing, and it would affect the P600 effect intensity with the degrees of structural heterogeneity.Keywords: ERPs, P600, structural pattern, structural priming, Tang poetry
Procedia PDF Downloads 1404237 Memory Retrieval and Implicit Prosody during Reading: Anaphora Resolution by L1 and L2 Speakers of English
Authors: Duong Thuy Nguyen, Giulia Bencini
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The present study examined structural and prosodic factors on the computation of antecedent-reflexive relationships and sentence comprehension in native English (L1) and Vietnamese-English bilinguals (L2). Participants read sentences presented on the computer screen in one of three presentation formats aimed at manipulating prosodic parsing: word-by-word (RSVP), phrase-segment (self-paced), or whole-sentence (self-paced), then completed a grammaticality rating and a comprehension task (following Pratt & Fernandez, 2016). The design crossed three factors: syntactic structure (simple; complex), grammaticality (target-match; target-mismatch) and presentation format. An example item is provided in (1): (1) The actress that (Mary/John) interviewed at the awards ceremony (about two years ago/organized outside the theater) described (herself/himself) as an extreme workaholic). Results showed that overall, both L1 and L2 speakers made use of a good-enough processing strategy at the expense of more detailed syntactic analyses. L1 and L2 speakers’ comprehension and grammaticality judgements were negatively affected by the most prosodically disrupting condition (word-by-word). However, the two groups demonstrated differences in their performance in the other two reading conditions. For L1 speakers, the whole-sentence and the phrase-segment formats were both facilitative in the grammaticality rating and comprehension tasks; for L2, compared with the whole-sentence condition, the phrase-segment paradigm did not significantly improve accuracy or comprehension. These findings are consistent with the findings of Pratt & Fernandez (2016), who found a similar pattern of results in the processing of subject-verb agreement relations using the same experimental paradigm and prosodic manipulation with English L1 and L2 English-Spanish speakers. The results provide further support for a Good-Enough cue model of sentence processing that integrates cue-based retrieval and implicit prosodic parsing (Pratt & Fernandez, 2016) and highlights similarities and differences between L1 and L2 sentence processing and comprehension.Keywords: anaphora resolution, bilingualism, implicit prosody, sentence processing
Procedia PDF Downloads 1524236 Neural Correlates of Arabic Digits Naming
Authors: Fernando Ojedo, Alejandro Alvarez, Pedro Macizo
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In the present study, we explored electrophysiological correlates of Arabic digits naming to determine semantic processing of numbers. Participants named Arabic digits grouped by category or intermixed with exemplars of other semantic categories while the N400 event-related potential was examined. Around 350-450 ms after the presentation of Arabic digits, brain waves were more positive in anterior regions and more negative in posterior regions when stimuli were grouped by category relative to the mixed condition. Contrary to what was found in other studies, electrophysiological results suggested that the production of numerals involved semantic mediation.Keywords: Arabic digit naming, event-related potentials, semantic processing, number production
Procedia PDF Downloads 5834235 Elevated Temperature Shot Peening for M50 Steel
Authors: Xinxin Ma, Guangze Tang, Shuxin Yang, Jinguang He, Fan Zhang, Peiling Sun, Ming Liu, Minyu Sun, Liqin Wang
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As a traditional surface hardening technique, shot peening is widely used in industry. By using shot peening, a residual compressive stress is formed in the surface which is beneficial for improving the fatigue life of metal materials. At the same time, very fine grains and high density defects are generated in the surface layer which enhances the surface hardness, either. However, most of the processes are carried out at room temperature. For high strength steel, such as M50, the thickness of the strengthen layer is limited. In order to obtain a thick strengthen surface layer, elevated temperature shot peening was carried out in this work by using Φ1mm cast ion balls with a speed of 80m/s. Considering the tempering temperature of M50 steel is about 550 oC, the processing temperature was in the range from 300 to 500 oC. The effect of processing temperature and processing time of shot peening on distribution of residual stress and surface hardness was investigated. As we known, the working temperature of M50 steel can be as high as 315 oC. Because the defects formed by shot peening are unstable when the working temperature goes higher, it is worthy to understand what happens during the shot peening process, and what happens when the strengthen samples were kept at a certain temperature. In our work, the shot peening time was selected from 2 to 10 min. And after the strengthening process, the samples were annealed at various temperatures from 200 to 500 oC up to 60 h. The results show that the maximum residual compressive stress is near 900 MPa. Compared with room temperature shot peening, the strengthening depth of 500 oC shot peening sample is about 2 times deep. The surface hardness increased with the processing temperature, and the saturation peening time decreases. After annealing, the residual compressive stress decreases, however, for 500 oC peening sample, even annealing at 500 oC for 20 h, the residual compressive stress is still over 600 MPa. However, it is clean to see from SEM that the grain size of surface layers is still very small.Keywords: shot peening, M50 steel, residual compressive stress, elevated temperature
Procedia PDF Downloads 4574234 Comparing Image Processing and AI Techniques for Disease Detection in Plants
Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller
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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation
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