Search results for: laser processing
2888 Optimal MRO Process Scheduling with Rotable Inventory to Minimize Total Earliness
Authors: Murat Erkoc, Kadir Ertogral
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Maintenance, repair and overhauling (MRO) of high cost equipment used in many industries such as transportation, military and construction are typically subject to regulations set by local governments or international agencies. Aircrafts are prime examples for this kind of equipment. Such equipment must be overhauled at certain intervals for continuing permission of use. As such, the overhaul must be completed by strict deadlines, which often times cannot be exceeded. Due to the fact that the overhaul is typically a long process, MRO companies carry so called rotable inventory for exchange of expensive modules in the overhaul process of the equipment so that the equipment continue its services with minimal interruption. The extracted module is overhauled and returned back to the inventory for future exchange, hence the name rotable inventory. However, since the rotable inventory and overhaul capacity are limited, it may be necessary to carry out some of the exchanges earlier than their deadlines in order to produce a feasible overhaul schedule. An early exchange results with a decrease in the equipment’s cycle time in between overhauls and as such, is not desired by the equipment operators. This study introduces an integer programming model for the optimal overhaul and exchange scheduling. We assume that there is certain number of rotables at hand at the beginning of the planning horizon for a single type module and there are multiple demands with known deadlines for the exchange of the modules. We consider an MRO system with identical parallel processing lines. The model minimizes total earliness by generating optimal overhaul start times for rotables on parallel processing lines and exchange timetables for orders. We develop a fast exact solution algorithm for the model. The algorithm employs full-delay scheduling approach with backward allocation and can easily be used for overhaul scheduling problems in various MRO settings with modular rotable items. The proposed procedure is demonstrated by a case study from the aerospace industry.Keywords: rotable inventory, full-delay scheduling, maintenance, overhaul, total earliness
Procedia PDF Downloads 5482887 Development of a Computer Aided Diagnosis Tool for Brain Tumor Extraction and Classification
Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran
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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM
Procedia PDF Downloads 2552886 Shallow Water Lidar System in Measuring Erosion Rate of Coarse-Grained Materials
Authors: Ghada S. Ellithy, John. W. Murphy, Maureen K. Corcoran
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Erosion rate of soils during a levee or dam overtopping event is a major component in risk assessment evaluation of breach time and downstream consequences. The mechanism and evolution of dam or levee breach caused by overtopping erosion is a complicated process and difficult to measure during overflow due to accessibility and quickly changing conditions. In this paper, the results of a flume erosion tests are presented and discussed. The tests are conducted on a coarse-grained material with a median grain size D50 of 5 mm in a 1-m (3-ft) wide flume under varying flow rates. Each test is performed by compacting the soil mix r to its near optimum moisture and dry density as determined from standard Proctor test in a box embedded in the flume floor. The box measures 0.45 m wide x 1.2 m long x 0.25 m deep. The material is tested several times at varying hydraulic loading to determine the erosion rate after equal time intervals. The water depth, velocity are measured at each hydraulic loading, and the acting bed shear is calculated. A shallow water lidar (SWL) system was utilized to record the progress of soil erodibility and water depth along the scanned profiles of the tested box. SWL is a non-contact system that transmits laser pulses from above the water and records the time-delay between top and bottom reflections. Results from the SWL scans are compared with before and after manual measurements to determine the erosion rate of the soil mix and other erosion parameters.Keywords: coarse-grained materials, erosion rate, LIDAR system, soil erosion
Procedia PDF Downloads 1162885 Strategies of Risk Management for Smallholder Farmers in South Africa: A Case Study on Pigeonpea (Cajanus cajan) Production
Authors: Sanari Chalin Moriri, Kwabena Kingsley Ayisi, Alina Mofokeng
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Dryland smallholder farmers in South Africa are vulnerable to all kinds of risks, and it negatively affects crop productivity and profit. Pigeonpea is a leguminous and multipurpose crop that provides food, fodder, and wood for smallholder farmers. The majority of these farmers are still growing pigeonpea from traditional unimproved seeds, which comprise a mixture of genotypes. The objectives of the study were to identify the key risk factors that affect pigeonpea productivity and to develop management strategies on how to alleviate the risk factors in pigeonpea production. The study was conducted in two provinces (Limpopo and Mpumalanga) of South Africa in six municipalities during the 2020/2021 growing seasons. The non-probability sampling method using purposive and snowball sampling techniques were used to collect data from the farmers through a structured questionnaire. A total of 114 pigeonpea producers were interviewed individually using a questionnaire. Key stakeholders in each municipality were also identified, invited, and interviewed to verify the information given by farmers. Data collected were subjected to SPSS statistical software 25 version. The findings of the study were that majority of farmers affected by risk factors were women, subsistence, and old farmers resulted in low food production. Drought, unavailability of improved pigeonpea seeds for planting, access to information, and processing equipment were found to be the main risk factors contributing to low crop productivity in farmer’s fields. Above 80% of farmers lack knowledge on the improvement of the crop and also on the processing techniques to secure high prices during the crop off-season. Market availability, pricing, and incidence of pests and diseases were found to be minor risk factors which were triggered by the major risk factors. The minor risk factors can be corrected only if the major risk factors are first given the necessary attention. About 10% of the farmers found to use the crop as a mulch to reduce soil temperatures and to improve soil fertility. The study revealed that most of the farmers were unaware of its utilisation as fodder, much, medicinal, nitrogen fixation, and many more. The risk of frequent drought in dry areas of South Africa where farmers solely depend on rainfall poses a serious threat to crop productivity. The majority of these risk factors are caused by climate change due to unrealistic, low rainfall with extreme temperatures poses a threat to food security, water, and the environment. The use of drought-tolerant, multipurpose legume crops such as pigeonpea, access to new information, provision of processing equipment, and support from all stakeholders will help in addressing food security for smallholder farmers. Policies should be revisited to address the prevailing risk factors faced by farmers and involve them in addressing the risk factors. Awareness should be prioritized in promoting the crop to improve its production and commercialization in the dryland farming system of South Africa.Keywords: management strategies, pigeonpea, risk factors, smallholder farmers
Procedia PDF Downloads 2182884 Subdued Electrodermal Response to Empathic Induction Task in Intimate Partner Violence (IPV) Perpetrators
Authors: Javier Comes Fayos, Isabel Rodríguez Moreno, Sara Bressanutti, Marisol Lila, Angel Romero Martínez, Luis Moya Albiol
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Empathy is a cognitive-affective capacity whose deterioration is associated with aggressive behaviour. Deficient affective processing is one of the predominant risk factors in men convicted of intimate partner violence (IPV perpetrators), since it makes their capacity to empathize very difficult. The objective of this study is to compare the response of electrodermal activity (EDA), as an indicator of emotionality, to an empathic induction task, between IPV perpetrators and men without a history of violence. The sample was composed of 51 men who attended the CONTEXTO program, with penalties for gender violence under two years, and 47 men with no history of violence. Empathic induction was achieved through the visualization of 4 negative emotional-eliciting videos taken from an emotional induction battery of videos validated for the Spanish population. The participants were asked to actively empathize with the video characters (previously pointed out). The psychophysiological recording of the EDA was accomplished by the "Vrije Universiteit Ambulatory Monitoring System (VU-AMS)." An analysis of repeated measurements was carried out with 10 intra-subject measurements (time) and "group" (IPV perpetrators and non-violent perpetrators) as the inter-subject factor. First, there were no significant differences between groups in the baseline AED levels. Yet, a significant interaction between the “time” and “group” was found with IPV perpetrators exhibiting lower EDA response than controls after the empathic induction task. These findings provide evidence of a subdued EDA response after an empathic induction task in IPV perpetrators with respect to men without a history of violence. Therefore, the lower psychophysiological activation would be indicative of difficulties in the emotional processing and response, functions that are necessary for the empathic function. Consequently, the importance of addressing possible empathic difficulties in IPV perpetrator psycho-educational programs is reinforced, putting special emphasis on the affective dimension that could hinder the empathic function.Keywords: electrodermal activity, emotional induction, empathy, intimate partner violence
Procedia PDF Downloads 2072883 Physical Tests on Localized Fluidization in Offshore Suction Bucket Foundations
Authors: Li-Hua Luu, Alexis Doghmane, Abbas Farhat, Mohammad Sanayei, Pierre Philippe, Pablo Cuellar
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Suction buckets are promising innovative foundations for offshore wind turbines. They generally feature the shape of an inverted bucket and rely on a suction system as a driving agent for their installation into the seabed. Water is pumped out of the buckets that are initially placed to rest on the seabed, creating a net pressure difference across the lid that generates a seepage flow, lowers the soil resistance below the foundation skirt, and drives them effectively into the seabed. The stability of the suction mechanism as well as the possibility of a piping failure (i.e., localized fluidization within the internal soil plug) during their installation are some of the key questions that remain open. The present work deals with an experimental study of localized fluidization by suction within a fixed bucket partially embedded into a submerged artificial soil made of spherical beads. The transient process, from the onset of granular motion until reaching a stationary regime for the fluidization at the embedded bucket wall, is recorded using the combined optical techniques of planar laser-induced fluorescence and refractive index matching. To conduct a systematic study of the piping threshold for the seepage flow, we vary the beads size, the suction pressure, and the initial depth for the bucket. This experimental modelling, by dealing with erosion-related phenomena from a micromechanical perspective, shall provide qualitative scenarios for the local processes at work which are missing in the offshore practice so far.Keywords: fluidization, micromechanical approach, offshore foundations, suction bucket
Procedia PDF Downloads 1892882 Reinforcement Learning For Agile CNC Manufacturing: Optimizing Configurations And Sequencing
Authors: Huan Ting Liao
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In a typical manufacturing environment, computer numerical control (CNC) machining is essential for automating production through precise computer-controlled tool operations, significantly enhancing efficiency and ensuring consistent product quality. However, traditional CNC production lines often rely on manual loading and unloading, limiting operational efficiency and scalability. Although automated loading systems have been developed, they frequently lack sufficient intelligence and configuration efficiency, requiring extensive setup adjustments for different products and impacting overall productivity. This research addresses the job shop scheduling problem (JSSP) in CNC machining environments, aiming to minimize total completion time (makespan) and maximize CNC machine utilization. We propose a novel approach using reinforcement learning (RL), specifically the Q-learning algorithm, to optimize scheduling decisions. The study simulates the JSSP, incorporating robotic arm operations, machine processing times, and work order demand allocation to determine optimal processing sequences. The Q-learning algorithm enhances machine utilization by dynamically balancing workloads across CNC machines, adapting to varying job demands and machine states. This approach offers robust solutions for complex manufacturing environments by automating decision-making processes for job assignments. Additionally, we evaluate various layout configurations to identify the most efficient setup. By integrating RL-based scheduling optimization with layout analysis, this research aims to provide a comprehensive solution for improving manufacturing efficiency and productivity in CNC-based job shops. The proposed method's adaptability and automation potential promise significant advancements in tackling dynamic manufacturing challenges.Keywords: job shop scheduling problem, reinforcement learning, operations sequence, layout optimization, q-learning
Procedia PDF Downloads 312881 Time Temperature Dependence of Long Fiber Reinforced Polypropylene Manufactured by Direct Long Fiber Thermoplastic Process
Authors: K. A. Weidenmann, M. Grigo, B. Brylka, P. Elsner, T. Böhlke
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In order to reduce fuel consumption, the weight of automobiles has to be reduced. Fiber reinforced polymers offer the potential to reach this aim because of their high stiffness to weight ratio. Additionally, the use of fiber reinforced polymers in automotive applications has to allow for an economic large-scale production. In this regard, long fiber reinforced thermoplastics made by direct processing offer both mechanical performance and processability in injection moulding and compression moulding. The work presented in this contribution deals with long glass fiber reinforced polypropylene directly processed in compression moulding (D-LFT). For the use in automotive applications both the temperature and the time dependency of the materials properties have to be investigated to fulfill performance requirements during crash or the demands of service temperatures ranging from -40 °C to 80 °C. To consider both the influence of temperature and time, quasistatic tensile tests have been carried out at different temperatures. These tests have been complemented by high speed tensile tests at different strain rates. As expected, the increase in strain rate results in an increase of the elastic modulus which correlates to an increase of the stiffness with decreasing service temperature. The results are in good accordance with results determined by dynamic mechanical analysis within the range of 0.1 to 100 Hz. The experimental results from different testing methods were grouped and interpreted by using different time temperature shift approaches. In this regard, Williams-Landel-Ferry and Arrhenius approach based on kinetics have been used. As the theoretical shift factor follows an arctan function, an empirical approach was also taken into consideration. It could be shown that this approach describes best the time and temperature superposition for glass fiber reinforced polypropylene manufactured by D-LFT processing.Keywords: composite, dynamic mechanical analysis, long fibre reinforced thermoplastics, mechanical properties, time temperature superposition
Procedia PDF Downloads 2022880 A CORDIC Based Design Technique for Efficient Computation of DCT
Authors: Deboraj Muchahary, Amlan Deep Borah Abir J. Mondal, Alak Majumder
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A discrete cosine transform (DCT) is described and a technique to compute it using fast Fourier transform (FFT) is developed. In this work, DCT of a finite length sequence is obtained by incorporating CORDIC methodology in radix-2 FFT algorithm. The proposed methodology is simple to comprehend and maintains a regular structure, thereby reducing computational complexity. DCTs are used extensively in the area of digital processing for the purpose of pattern recognition. So the efficient computation of DCT maintaining a transparent design flow is highly solicited.Keywords: DCT, DFT, CORDIC, FFT
Procedia PDF Downloads 4842879 Operating Parameters and Costs Assessments of a Real Fishery Wastewater Effluent Treated by Electrocoagulation Process
Authors: Mirian Graciella Dalla Porta, Humberto Jorge José, Danielle de Bem Luiz, Regina de F. P. M.Moreira
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Similar to most processing industries, fish processing produces large volumes of wastewater, which contains especially organic contaminants, salts and oils dispersed therein. Different processes have been used for the treatment of fishery wastewaters, but the most commonly used are chemical coagulation and flotation. These techniques are well known but sometimes the characteristics of the treated effluent do not comply with legal standards for discharge. Electrocoagulation (EC) is an electrochemical process that can be used to treat wastewaters in terms of both organic matter and nutrient removal. The process is based on the use of sacrificial electrodes such as aluminum, iron or zinc, that are oxidized to produce metal ions that can be used to coagulate and react with organic matter and nutrients in the wastewater. While EC processes are effective to treatment of several types of wastewaters, applications have been limited due to the high energy demands and high current densities. Generally, the for EC process can be performed without additional chemicals or pre-treatment, but the costs should be reduced for EC processes to become more applicable. In this work, we studied the treatment of a real wastewater from fishmeal industry by electrocoagulation process. Removal efficiencies for chemical oxygen demand (COD), total organic carbon (TOC) turbidity, phosphorous and nitrogen concentration were determined as a function of the operating conditions, such as pH, current density and operating time. The optimum operating conditions were determined to be operating time of 10 minutes, current density 100 A.m-2, and initial pH 4.0. COD, TOC, phosphorous concentration, and turbidity removal efficiencies at the optimum operating conditions were higher than 90% for aluminum electrode. Operating costs at the optimum conditions were calculated as US$ 0.37/m3 (US$ 0.038/kg COD) for Al electrode. These results demonstrate that the EC process is a promising technology to remove nutrients from fishery wastewaters, as the process has both a high efficiency of nutrient removal, and low energy requirements.Keywords: electrocoagulation, fish, food industry, wastewater
Procedia PDF Downloads 2532878 Sorting Fish by Hu Moments
Authors: J. M. Hernández-Ontiveros, E. E. García-Guerrero, E. Inzunza-González, O. R. López-Bonilla
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This paper presents the implementation of an algorithm that identifies and accounts different fish species: Catfish, Sea bream, Sawfish, Tilapia, and Totoaba. The main contribution of the method is the fusion of the characteristics of invariance to the position, rotation and scale of the Hu moments, with the proper counting of fish. The identification and counting is performed, from an image under different noise conditions. From the experimental results obtained, it is inferred the potentiality of the proposed algorithm to be applied in different scenarios of aquaculture production.Keywords: counting fish, digital image processing, invariant moments, pattern recognition
Procedia PDF Downloads 4152877 An Approach to Autonomous Drones Using Deep Reinforcement Learning and Object Detection
Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young
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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving
Procedia PDF Downloads 2572876 Discussion on Microstructural Changes Caused by Deposition Temperature of LZO Doped Mg Piezoelectric Films
Authors: Cheng-Ying Li, Sheng-Yuan Chu
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This article deposited LZO-doped Mg piezoelectric thin films via RF sputtering and observed microstructure and electrical characteristics by varying the deposition temperature. The XRD analysis results indicate that LZO-doped Mg exhibits excellent (002) orientation, and there is no presence of ZnO(100), Influenced by the temperature's effect on the lattice constant, the (002) peak intensity increases with rising temperature. Finally, we conducted deformation intensity analysis on the films, revealing an over fourfold increase in deformation at a processing temperature of 500°C.Keywords: RF sputtering, piezoelectricity, ZnO, Mg
Procedia PDF Downloads 492875 Improving Subjective Bias Detection Using Bidirectional Encoder Representations from Transformers and Bidirectional Long Short-Term Memory
Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock
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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing
Procedia PDF Downloads 1342874 Additive Manufacturing’s Impact on Product Design and Development: An Industrial Case Study
Authors: Ahmed Abdelsalam, Daniel Roozbahani, Marjan Alizadeh, Heikki Handroos
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The aim of this study was to redesign a pressing air nozzle with lower weight and improved efficiency utilizing Selective Laser Melting (SLM) technology based on Design for Additive Manufacturing (DfAM) methods. The original pressing air nozzle was modified in SolidWorks 3D CAD, and two design concepts were introduced considering the DfAM approach. In the proposed designs, the air channels were amended. 3D models for the original pressing air nozzle and introduced designs were created to obtain the flow characteristic data using Ansys software. Results of CFD modeling for the original and two proposed designs were extracted, compared, and analyzed to demonstrate the impact of design on the development of a more efficient pressing air nozzle by AM process. Improved airflow was achieved by optimizing the pressing air nozzle's internal channel for both design concepts by providing 30% and 50.6% fewer pressure drops than the original design. Moreover, utilizing the presented designs, a significant reduction in product weight was attained. In addition, by applying the proposed designs, 48.3% and 70.3% reduction in product weight was attained compared to the original design. Therefore, pressing air nozzle with enhanced productivity and lowered weight was generated utilizing the DfAM-driven designs developed in this study. The main contribution of this study is to investigate the additional possibilities that can be achieved in designing modern parts using the advantage of SLM technology in producing that part. The approach presented in this study can be applied to almost any similar industrial application.Keywords: additive manufacturing, design for additive manufacturing, design methods, product design, pressing air nozzle
Procedia PDF Downloads 1852873 Effect of Roasting Treatment on Milling Quality, Physicochemical, and Bioactive Compounds of Dough Stage Rice Grains
Authors: Chularat Leewuttanakul, Khanitta Ruttarattanamongkol, Sasivimon Chittrakorn
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Rice during grain development stage is a rich source of many bioactive compounds. Dough stage rice contains high amounts of photochemical and can be used for rice milling industries. However, rice grain at dough stage had low milling quality due to high moisture content. Thermal processing can be applied to rice grain for improving milled rice yield. This experiment was conducted to study the chemical and physic properties of dough stage rice grain after roasting treatment. Rice were roasted with two different methods including traditional pan roasting at 140 °C for 60 minutes and using the electrical roasting machine at 140 °C for 30, 40, and 50 minutes. The chemical, physical properties, and bioactive compounds of brown rice and milled rice were evaluated. The result of this experiment showed that moisture content of brown and milled rice was less than 10 % and amylose contents were in the range of 26-28 %. Rice grains roasting for 30 min using electrical roasting machine had high head rice yield and length and breadth of grain after milling were close to traditional pan roasting (p > 0.05). The lightness (L*) of rice did not affect by roasting treatment (p > 0.05) and the a* indicated the yellowness of milled rice was lower than brown rice. The bioactive compounds of brown and milled rice significantly decreased with increasing of drying time. Brown rice roasted for 30 minutes had the highest of total phenolic content, antioxidant activity, α-tocopherol, and ɤ-oryzanol content. Volume expansion and elongation of cooked rice decreased as roasting time increased and quality of cooked rice roasted for 30 min was comparable to traditional pan roasting. Hardness of cooked rice as measured by texture analyzer increased with increasing roasting time. The results indicated that rice grains at dough stage, containing a high amount of bioactive compounds, have a great potential for rice milling industries and the electrical roasting machine can be used as an alternative to pan roasting which decreases processing time and labor costs.Keywords: bioactive compounds, cooked rice, dough stage rice grain, grain development, roasting
Procedia PDF Downloads 1692872 Surface Nanostructure Developed by Ultrasonic Shot Peening and Its Effect on Low Cycle Fatigue Life of the IN718 Superalloy
Authors: Sanjeev Kumar, Vikas Kumar
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Inconel 718 (IN718) is a high strength nickel-based superalloy designed for high-temperature applications up to 650 °C. It is widely used in gas turbines of jet engines and related aerospace applications because of its good mechanical properties and structural stability at elevated temperatures. Because of good performance ratio and excellent process capability, this alloy has been used predominantly for aeronautic engine components like compressor disc and compressor blade. The main precipitates that contribute to high-temperature strength of IN718 are γʹ Ni₃(Al, Ti) and mainly γʹʹ (Ni₃ Nb). Various processes have been used for modification of the surface of components, such as Laser Shock Peening (LSP), Conventional Shot Peening (SP) and Ultrasonic Shot Peening (USP) to induce compressive residual stress (CRS) and development of fine-grained structure in the surface region. Surface nanostructure by ultrasonic shot peening is a novel methodology of surface modification to improve the overall performance of structural components. Surface nanostructure was developed on the peak aged IN718 superalloy using USP and its effect was studied on low cycle fatigue (LCF) life. Nanostructure of ~ 49 to 73 nm was developed in the surface region of the alloy by USP. The gage section of LCF samples was USPed for 5 minutes at a constant frequency of 20 kHz using StressVoyager to modify the surface. Strain controlled cyclic tests were performed for non-USPed and USPed samples at ±Δεt/2 from ±0.50% to ±1.0% at strain rate (ė) 1×10⁻³ s⁻¹ under reversal loading (R=‒1) at room temperature. The fatigue life of the USPed specimens was found to be more than that of the non-USPed ones. LCF life of the USPed specimen at Δεt/2=±0.50% was enhanced by more than twice of the non-USPed specimen.Keywords: IN718 superalloy, nanostructure, USP, LCF life
Procedia PDF Downloads 1192871 Analysis of Vibration of Thin-Walled Parts During Milling Made of EN AW-7075 Alloy
Authors: Jakub Czyżycki, Paweł Twardowski
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Thin-walled components made of aluminum alloys are increasingly found in many fields of industry, and they dominate the aerospace industry. The machining of thinwalled structures encounters many difficulties related to the high susceptibility of the workpiece, which causes vibrations including the most unfavorable ones called chatter. The effect of these phenomena is the difficulty in obtaining the required geometric dimensions and surface quality. The purpose of this study is to analyze vibrations arising during machining of thin-walled workpieces made of aluminum alloy EN AW-7075. Samples representing actual thin-walled workpieces were examined in a different range of dimensions characterizing thin-walled workpieces. The tests were carried out in HSM high-speed machining (cutting speed vc = 1400 m/min) using a monolithic solid carbide endmill. Measurement of vibration was realized using a singlecomponent piezoelectric accelerometer 4508C from Brüel&Kjær which was mounted directly on the sample before machining, the measurement was made in the normal feed direction AfN. In addition, the natural frequency of the tested thin-walled components was investigated using a laser vibrometer for an broader analysis of the tested samples. The effect of vibrations on machining accuracy was presented in the form of surface images taken with an optical measuring device from Alicona. A classification of the vibrations produced during the test was carried out, and were analyzed in both the time and frequency domains. Observed significant influence of the thickness of the thin-walled component on the course of vibrations during machining.Keywords: high-speed machining, thin-walled elements, thin-walled components, milling, vibrations
Procedia PDF Downloads 622870 Hardware Implementation for the Contact Force Reconstruction in Tactile Sensor Arrays
Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín
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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation
Procedia PDF Downloads 2012869 Evaluation of Three Potato Cultivars for Processing (Crisp French Fries)
Authors: Hatim Bastawi
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Three varieties of potatoes, namely Agria, Alpha and Diamant were evaluated for their suitability for industrial production of French fries. The evaluation was under taken after testing quality parameters of specific gravity, dry matter, peeling ratio, and defect after frying and panel test. The variety Agria ranked the best followed by Alpha with regard to the parameters tested. On the other hand, Diamant showed significantly higher defect percentage than the other cultivars. Also, it was significantly judged of low acceptance by panelists.Keywords: cultivars, crisps, French fries
Procedia PDF Downloads 2632868 Fog Computing- Network Based Computing
Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat
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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.Keywords: cloud computing, fog computing, network devices, appstore
Procedia PDF Downloads 3912867 Three-Dimensional Vibration Characteristics of Piezoelectric Semi-Spherical Shell
Authors: Yu-Hsi Huang, Ying-Der Tsai
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Piezoelectric circular plates can provide out-of-plane vibrational displacements on low frequency and in-plane vibrational displacements on high frequency. Piezoelectric semi-spherical shell, which is double-curvature structure, can induce three-dimensional vibrational displacements over a large frequency range. In this study, three-dimensional vibrational characteristics of piezoelectric semi-spherical shells with free boundary conditions are investigated using three experimental methods and finite element numerical modeling. For the experimental measurements, amplitude-fluctuation electronic speckle pattern interferometry (AF-ESPI) is used to obtain resonant frequencies and radial and azimuthal mode shapes. This optical technique utilizes a full-field and non-contact optical system that measures both the natural frequency and corresponding vibration mode shape simultaneously in real time. The second experimental technique used, laser displacement meter is a point-wise displacement measurement method that determines the resonant frequencies of the piezoelectric shell. An impedance analyzer is used to determine the in-plane resonant frequencies of the piezoelectric semi-spherical shell. The experimental results of the resonant frequencies and mode shapes for the piezoelectric shell are verified with the result from finite element analysis. Excellent agreement between the experimental measurements and numerical calculation is presented on the three-dimensional vibrational characteristics of the piezoelectric semi-spherical shell.Keywords: piezoelectric semi-spherical shell, mode shape, resonant frequency, electronic speckle pattern interferometry, radial vibration, azimuthal vibration
Procedia PDF Downloads 2362866 Structural Correlates of Reduced Malicious Pleasure in Huntington's Disease
Authors: Sandra Baez, Mariana Pino, Mildred Berrio, Hernando Santamaria-Garcia, Lucas Sedeno, Adolfo Garcia, Sol Fittipaldi, Agustin Ibanez
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Schadenfreude refers to the perceiver’s experience of pleasure at another’s misfortune. This is a multidetermined emotion which can be evoked by hostile feelings and envy. The experience of Schadenfreude engages mechanisms implicated in diverse social cognitive processes. For instance, Schadenfreude involves heightened reward processing, accompanied by increased striatal engagement and it interacts with mentalizing and perspective-taking abilities. Patients with Huntington's disease (HD) exhibit reductions of Schadenfreude experience, suggesting a role of striatal degeneration in such an impairment. However, no study has directly assessed the relationship between regional brain atrophy in HD and reduced Schadenfreude. This study investigated whether gray matter (GM) atrophy in HD patients correlates with ratings of Schadenfreude. First, we compared the performance of 20 HD patients and 23 controls on an experimental task designed to trigger Schadenfreude and envy (another social emotion acting as a control condition). Second, we compared GM volume between groups. Third, we examined brain regions where atrophy might be associated with specific impairments in the patients. Results showed that while both groups showed similar ratings of envy, HD patients reported lower Schadenfreude. The latter pattern was related to atrophy in regions of the reward system (ventral striatum) and the mentalizing network (precuneus and superior parietal lobule). Our results shed light on the intertwining of reward and socioemotional processes in Schadenfreude, while offering novel evidence about their neural correlates. In addition, our results open the door to future studies investigating social emotion processing in other clinical populations characterized by striatal or mentalizing network impairments (e.g., Parkinson’s disease, schizophrenia, autism spectrum disorders).Keywords: envy, Gray matter atrophy, Huntigton's disease, Schadenfreude, social emotions
Procedia PDF Downloads 3422865 Study of White Salted Noodles Air Dehydration Assisted by Microwave as Compared to Conventional Air Dried Process
Authors: Chiun-C. R. Wang, I-Yu Chiu
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Drying is the most difficult and critical step to control in the dried salted noodles production. Microwave drying has the specific advantage of rapid and uniform heating due to the penetration of microwaves into the body of the product. Microwave-assisted facility offers a quick and energy saving method during food dehydration as compares to the conventional air-dried method for the noodle preparation. Recently, numerous studies in the rheological characteristics of pasta or spaghetti were carried out with microwave–assisted and conventional air driers and many agricultural products were dried successfully. There is very few research associated with the evaluation of physicochemical characteristics and cooking quality of microwave-assisted air dried salted noodles. The purposes of this study were to compare the difference between conventional air and microwave-assisted air drying method on the physicochemical properties and eating quality of rice bran noodles. Three different microwave power including 0.5 KW, 0.75 KW and 1.0 KW installing with 50℃ hot air were applied for dehydration of rice bran noodles in this study. Three proportion of rice bran ranging in 0-20% were incorporated into salted noodles processing. The appearance, optimum cooking time, cooking yield and losses, textural profiles analysis, and sensory evaluation of rice bran noodles were measured in this study. The results indicated that high power (1.0 KW) microwave facility caused partially burnt and porous on the surface of rice bran noodles. However, no significant difference of noodle was appeared on the surface of noodles between low power (0.5 KW) microwave-assisted salted noodles and control set. The optimum cooking time of noodles was decreased as higher power microwave was applied or higher proportion of rice bran was incorporated in the preparation of salted noodles. The higher proportion of rice bran (20%) or higher power of microwave-assisted dried noodles obtained the higher color intensity and the higher cooking losses as compared with conventional air dried noodles. Meanwhile, the higher power of microwave-assisted air dried noodles indicated the larger air cell inside the noodles and appeared little burnt stripe on the surface of noodles. The firmness of cooked rice bran noodles slightly decreased in the cooked noodles which were dried by high power microwave-assisted method. The shearing force, tensile strength, elasticity and texture profiles of cooked rice noodles decreased with the progress of the proportion of rice bran. The results of sensory evaluation indicated conventional dried noodles obtained the higher springiness, cohesiveness and overall acceptability of cooked noodles than high power (1.0 KW) microwave-assisted dried noodles. However, low power (0.5 KW) microwave-assisted dried noodles showed the comparable sensory attributes and acceptability with conventional dried noodles. Moreover, the sensory attributes including firmness, springiness, cohesiveness decreased, but stickiness increased with the increases of rice bran proportion in the salted noodles. These results inferred that incorporation of lower proportion of rice bran and lower power microwave-assisted dried noodles processing could produce faster cooking time and more acceptable quality of cooked noodles as compared to conventional dried noodles.Keywords: white salted noodles, microwave-assisted air drying processing, cooking yield, appearance, texture profiles, scanning electrical microscopy, sensory evaluation
Procedia PDF Downloads 4962864 Dynamic Web-Based 2D Medical Image Visualization and Processing Software
Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail
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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN
Procedia PDF Downloads 1652863 Study of Syntactic Errors for Deep Parsing at Machine Translation
Authors: Yukiko Sasaki Alam, Shahid Alam
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Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.Keywords: syntactic parsing, error analysis, machine translation, deep parsing
Procedia PDF Downloads 5622862 Discovery of Exoplanets in Kepler Data Using a Graphics Processing Unit Fast Folding Method and a Deep Learning Model
Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis
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Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry
Procedia PDF Downloads 2272861 H.263 Based Video Transceiver for Wireless Camera System
Authors: Won-Ho Kim
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In this paper, a design of H.263 based wireless video transceiver is presented for wireless camera system. It uses standard WIFI transceiver and the covering area is up to 100m. Furthermore the standard H.263 video encoding technique is used for video compression since wireless video transmitter is unable to transmit high capacity raw data in real time and the implemented system is capable of streaming at speed of less than 1Mbps using NTSC 720x480 video.Keywords: wireless video transceiver, video surveillance camera, H.263 video encoding digital signal processing
Procedia PDF Downloads 3712860 Neurofeedback for Anorexia-RelaxNeuron-Aimed in Dissolving the Root Neuronal Cause
Authors: Kana Matsuyanagi
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Anorexia Nervosa (AN) is a psychiatric disorder characterized by a relentless pursuit of thinness and strict restriction of food. The current therapeutic approaches for AN predominantly revolve around outpatient psychotherapies, which create significant financial barriers for the majority of affected patients, hindering their access to treatment. Nonetheless, AN exhibit one of the highest mortality and relapse rates among psychological disorders, underscoring the urgent need to provide patients with an affordable self-treatment tool, enabling those unable to access conventional medical intervention to address their condition autonomously. To this end, a neurofeedback software, termed RelaxNeuron, was developed with the objective of providing an economical and portable means to aid individuals in self-managing AN. Electroencephalography (EEG) was chosen as the preferred modality for RelaxNeuron, as it aligns with the study's goal of supplying a cost-effective and convenient solution for addressing AN. The primary aim of the software is to ameliorate the negative emotional responses towards food stimuli and the accompanying aberrant eye-tracking patterns observed in AN patient, ultimately alleviating the profound fear towards food an elemental symptom and, conceivably, the fundamental etiology of AN. The core functionality of RelaxNeuron hinges on the acquisition and analysis of EEG signals, alongside an electrocardiogram (ECG) signal, to infer the user's emotional state while viewing dynamic food-related imagery on the screen. Moreover, the software quantifies the user's performance in accurately tracking the moving food image. Subsequently, these two parameters undergo further processing in the subsequent algorithm, informing the delivery of either negative or positive feedback to the user. Preliminary test results have exhibited promising outcomes, suggesting the potential advantages of employing RelaxNeuron in the treatment of AN, as evidenced by its capacity to enhance emotional regulation and attentional processing through repetitive and persistent therapeutic interventions.Keywords: Anorexia Nervosa, fear conditioning, neurofeedback, BCI
Procedia PDF Downloads 512859 DHL CSI Solution Design Project
Authors: Mohammed Al-Yamani, Yaser Miaji
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DHL Customer Solutions and Innovation Department (CSI) have been experiencing difficulties while comparing quotes for different customers in different years. Currently, the employees are processing data by opening several loaded Excel files where the quotes are and manually copying values to another Excel Workbook where the comparison is made. This project consists of developing a new and effective database for DHL CSI department so that information is stored altogether on the same catalog. That being said, we have been assigned to find an efficient algorithm that can deal with the different formats of the Excel Workbooks to copy and store the express customer rates for core products (DOX, WPX, IMP) for comparisons purposes.Keywords: DHL, solution design, ORACLE, EXCEL
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