Search results for: computer processing of large databases

Authors: Yutaro Kyuma, Sung-Jun Yoo, Kazuhide Ito

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A commuter bus remains important as a means to network public transportation between railway stations and terminals within cities. In some cases, the boarding time becomes longer, and the boarding rate tends to be higher corresponding to the development of urban cities. The interior environmental quality, e.g. temperature and air quality, in a commuter bus is relatively heterogeneous and complex compared to that of an indoor environment in buildings due to several factors: solar radiative heat – which comes from large-area windows –, inadequate ventilation rate caused by high density of commuters, and metabolic heat generation from travelers themselves. In addition to this, under conditions where many passengers ride in the enclosed space, contact and airborne infectious risk have attracted considerable attention in terms of public health. From this point of view, it is essential to develop the prediction method for assessment of interior environmental quality and infection risk in commuter bus cabins. In this study, we developed a numerical commuter bus model integrated with computer simulated persons to reproduce realistic indoor environment conditions with high occupancy during commuting. Here, computer simulated persons were newly designed considering different types of geometries, e.g., standing position, seating position, and individual differences. Here we conducted coupled computational fluid dynamics (CFD) analysis with radiative heat transfer analysis under steady state condition. Distributions of heterogeneous air flow patterns, temperature, and moisture surrounding the human body under some different ventilation system were analyzed by using CFD technique, and skin surface temperature distributions were analyzed using thermoregulation model that integrated into computer simulated person. Through these analyses, we discussed the interior environmental quality in specific commuter bus cabins. Further, inhaled air quality of each passenger was also analyzed. This study may have possibility to design the ventilation system in bus for improving thermal comfort of occupants.

Keywords: computational fluid dynamics, CFD, computer simulated person, CSP, contaminant, indoor environment, public health, ventilation

Procedia PDF Downloads 237

Authors: Hasan Al Bashar Abul Ulayee, AKM Saifun Nabi, MD Mesbah-Ul-Awal

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Alert system for disaster management is common now a day and can play a vital role reducing devastation and saves lives and costs. An alert in right time can save thousands of human life, help to take shelter, manage other assets including live stocks and above all, a right time alert will help to take preparation to face and early recovery of the situation. In a country like Bangladesh where populations is more than 170 million and always facing different types of natural calamities and disasters, an early right time alert is very effective and implementation of alert system is challenging. The challenge comes from the time constraint of alerting the huge number of population. The other method of existing disaster management pre alert is traditional, sequential and non-selective so efficiency is not good enough. This paper describes a way by which alert can be provided to maximum number of people within the short time bound using parallel processing as well as random selection of selective target audience.

Keywords: alert system, Bangladesh, disaster management, parallel processing, SMS

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Authors: B. Varaprasad, C. Srinivasa Rao

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In the manufacturing sector, hard turning has emerged as vital machining process for cutting hardened steels. Besides many advantages of hard turning operation, one has to implement to achieve close tolerances in terms of surface finish, high product quality, reduced machining time, low operating cost and environmentally friendly characteristics. In the present study, three-dimensional CAE (Computer Aided Engineering) based simulation of  hard turning by using commercial software DEFORM 3D has been compared to experimental results of  stresses, temperatures and tool forces in machining of AISI D3 steel using mixed Ceramic inserts (CC6050). In the present analysis, orthogonal cutting models are proposed, considering several processing parameters such as cutting speed, feed, and depth of cut. An exhaustive friction modeling at the tool-work interfaces is carried out. Work material flow around the cutting edge is carefully modeled with adaptive re-meshing simulation capability. In process simulations, feed rate and cutting speed are constant (i.e.,. 0.075 mm/rev and 155 m/min), and analysis is focused on stresses, forces, and temperatures during machining. Close agreement is observed between CAE simulation and experimental values.

Keywords: hard turning, computer aided engineering, computational machining, finite element method

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Authors: Sally A. Brown

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Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aid teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role

Procedia PDF Downloads 80

Authors: Ju-Hong Lee, Ching-Wei Liao

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Adaptive beamforming using antenna array of sensors is useful in the process of adaptively detecting and preserving the presence of the desired signal while suppressing the interference and the background noise. For conventional adaptive array beamforming, we require a prior information of either the impinging direction or the waveform of the desired signal to adapt the weights. The adaptive weights of an antenna array beamformer under a steered-beam constraint are calculated by minimizing the output power of the beamformer subject to the constraint that forces the beamformer to make a constant response in the steering direction. Hence, the performance of the beamformer is very sensitive to the accuracy of the steering operation. In the literature, it is well known that the performance of an adaptive beamformer will be deteriorated by any steering angle error encountered in many practical applications, e.g., the wireless communication systems with massive antennas deployed at the base station and user equipment. Hence, developing effective signal processing techniques to deal with the problem due to steering angle error for array beamforming systems has become an important research work. In this paper, we present an effective signal processing technique for constructing an adaptive beamformer against the steering angle error. The proposed array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. Based on the presumed steering vector and a preset angle range for steering mismatch tolerance, we first create a matrix related to the direction vector of signal sources. Two projection matrices are generated from the matrix. The projection matrix associated with the desired signal information and the received array data are utilized to iteratively estimate the actual direction vector of the desired signal. The estimated direction vector of the desired signal is then used for appropriately finding the quiescent weight vector. The other projection matrix is set to be the signal blocking matrix required for performing adaptive beamforming. Accordingly, the proposed beamformer consists of adaptive quiescent weights and partially adaptive weights. Several computer simulation examples are provided for evaluating and comparing the proposed technique with the existing robust techniques.

Keywords: adaptive beamforming, robustness, signal blocking, steering angle error

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Authors: A.N. Zhilkaidarov, G.K. Iskakova, V.Y. Chernyh

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High-qualified and not-expensive products of daily usage have a big demand on food products’ market. Moreover, it is about independent and irreplaceable product as pasta. Pasta is a product, which represents itself the conserved dough from wheat flour made through special milling process. A wide assortment of the product and its pleasant taste properties allow to use pasta products in very different combinations with other food products. Pasta industry of Kazakhstan has large perspectives of development. There are many premises for it, which includes first an importance of pasta as a social product. Due to for its nutritional and energetically value pasta is the part of must have food. Besides that, the pasta production in Kazakhstan has traditional bases, and nowadays the market of this product develops rapidly as in quantity as well as in quality aspects. Moreover, one of the advantages of this branch is an economical aspect – pasta is the product of secondary processing, and therefore price for sailing is much higher as its own costs.

Keywords: pasta, new wheat sorts, domesic sorts of wheat, macaronic flour

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Authors: Tan Dexian Arthur, James Wei Ming Kwek, Ian Loh, Lee Tee Sin

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Statement of the Problem: Mucoceles most commonly affect the frontal sinus, which results from chronic obstruction of the sinus ostium or cystic dilatation of mucous glands with ductal obstruction. They are known to cause bony erosion of the sinus walls, which can lead to large defects. These defects were typically managed by obliteration or cranialization of the frontal sinus. Although short term outcomes of conservative management of significant posterior table defects from fractures are promising, there have been no studies on the long-term outcomes of large dehiscences in the posterior wall of the frontal sinus. Methodology & Findings : Computed Tomography (CT) Paranasal Sinuses images were analyzed and found complete spontaneous osteogenesis of a large dehiscent frontal sinus posterior wall, secondary to a large mucocele, 9 years from functional endoscopic sinus surgery with the defect managed conservatively. Conclusion & Significance: The dura is well known for its osteogenic properties. Prior studies have showed that dura could induce osteogenesis in cutaneous tissue in the absence of other central nervous system structures. It was also demonstrated that osteogenesis and chondrogenesis were possible in zygomatic fractures by transplanting neonatal dura grafts to the bony defects in rats. Extrapolating from these studies, the authors postulate that the presence of dura beneath the bony deformity of the posterior frontal sinus wall had likely initiated the osteogenesis and restored the bony defect in the patient. In our literature review, we did not find any reports of spontaneous osteogenesis of large frontal sinus defects. While our experience is incidental, it reinforces the osteogenetic potential of an intact dura and further highlights that selected large defects of the posterior wall of the frontal sinus can be conservatively managed.

Keywords: paranasal sinus mucocele, mucocele, osteogenesis, dehiscence

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Authors: Yassine Jamoussi, Ameni Youssfi, Henda Ben Ghezala

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With the growing interest in social networking, the interaction of social actors evolved to a source of knowledge in which it becomes possible to perform context aware-reasoning. The information extraction from social networking especially Twitter and Facebook is one of the problems in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit from the lexical features developed for Twitter and online conversational text in previous works, and to develop an extraction model for constructing a huge knowledge based on actions

Keywords: social networking, information extraction, part-of-speech tagging, natural language processing

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Authors: Ashish Agarwal, Vaibhav Singh

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Harmful emissions from oil and gas processing facilities have long remained a matter of concern for governments and environmentalists throughout the world. This paper analyses Oil and Natural Gas Corporation (ONGC) gas processing plant in Hazira, Gujarat, India. It is the largest gas-processing complex in the country designed to process 41MMSCMD sour natural gas & associated sour condensate. The complex, sprawling over an area of approximate 705 hectares is the mother plant for almost all industries at Hazira and enroute Hazira Bijapur Jagdishpur pipeline. Various sources of pollution from each unit starting from Gas Terminal to Dew Point Depression unit and Caustic Wash unit along the processing chain were examined with the help of different emission data obtained from ONGC. Pollution discharged to the environment was classified into Water, Air, Hazardous Waste and Solid (Non-Hazardous) Waste so as to analyze each one of them efficiently. To protect air environment, Sulphur recovery unit along with automatic ambient air quality monitoring stations, automatic stack monitoring stations among numerous practices were adopted. To protect water environment different effluent treatment plants were used with due emphasis on aquaculture of the nearby area. Hazira plant has obtained the authorization for handling and disposal of five types of hazardous waste. Most of the hazardous waste were sold to authorized recyclers and the rest was given to Gujarat Pollution Control Board authorized vendors. Non-Hazardous waste was also handled with an overall objective of zero negative impact on the environment. The effect of methods adopted is evident from emission data of the plant which was found to be well under Gujarat Pollution Control Board limits.

Keywords: sulphur recovery unit, effluent treatment plant, hazardous waste, sour gas

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Authors: Amandeep Kaur

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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

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Authors: Darshana Lal, Sonu Rana

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Learning Resource Centers (LRC) are acquiring different kinds of documents like books, journals, thesis, dissertations, standard, databases etc. in print and e-form. This article deals with the different types of sources available in LRC. It also discusses the concept of the web, as a tool, as a multimedia system and the different interfaces available on the web. The reasons for establishing LRC are highlighted along with the assignments of LRC. Different features of LRC‘S like self-learning and group learning are described. It also implements a group of activities like reading, learning, educational etc. The use of LRC by students and faculties are given and concluded with the benefits.

Keywords: internet, search engine, resource centre, opac, self-learning, group learning

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Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan

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In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.

Keywords: break even point, fuzzy crisp data, fuzzy sets, productivity, productivity cycle, total productive maintenance

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Authors: Asnate Kirse, Daina Karklina, Sandra Muizniece-Brasava, Ruta Galoburda

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Pulses are high in plant protein and dietary fiber, and contain slowly digestible starches. Innovative products from pulses could increase their consumption and benefit consumer health. This study was conducted to evaluate physicochemical stability of processed cowpea (Vigna unguiculata (L.) Walp. cv. Fradel) and maple pea (Pisum sativum var. arvense L. cv. Bruno) spreads at 5 °C temperature during 62-day storage. Physicochemical stability of pulse spreads was compared after sous vide treatment (80 °C/15 min) and high pressure processing (700 MPa/10 min/20 °C). Pulse spreads were made by homogenizing cooked pulses in a food processor together with salt, citric acid, oil, and bruschetta seasoning. A total of four different pulse spreads were studied: Cowpea spread without and with seasoning, maple pea spread without and with seasoning. Transparent PA/PE and light proof PET/ALU/PA/PP film pouches were used for packaging of pulse spreads under vacuum. The parameters investigated were pH, water activity and mass losses. Pulse spreads were tested on days 0, 15, 29, 42, 50, 57 and 62. The results showed that sous-vide treatment and high pressure processing had an insignificant influence on pH, water activity and mass losses after processing, irrespective of packaging material did not change (p>0.1). pH and water activity of sous-vide treated and high pressure processed pulse spreads in different packaging materials proved to be stable throughout the storage. Mass losses during storage accounted to 0.1% losses. Chosen sous-vide treatment and high pressure processing regimes and packaging materials are suitable to maintain consistent physicochemical quality of the new products during 62-day storage.

Keywords: cowpea, flexible packaging, maple pea, water activity

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Authors: Saifullah Karimullah

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Additive manufacturing techniques are becoming more common with the latest technological advancements. It is composed to bring a revolution in the way products are designed, planned, manufactured, and distributed to end users. Fused deposition modeling (FDM) based 3D printing is one of those promising aspects that have revolutionized the prototyping processes. The purpose of this design and study project is to design a customized laboratory-scale FDM-based 3D printer from locally available sources. The primary goal is to design and fabricate the FDM-based 3D printer. After the fabrication, a tensile test specimen would be designed in Solid Works or [Creo computer-aided design (CAD)] software. A .stl file is generated of the tensile test specimen through slicing software and the G-codes are inserted via a computer for the test specimen to be printed. Different parameters were under studies like printing speed, layer thickness and infill density of the printed object. Some parameters were kept constant such as temperature, extrusion rate, raster orientation etc. Different tensile test specimens were printed for a different sets of parameters of the FDM-based 3d printer. The tensile test specimen were subjected to tensile tests using a universal testing machine (UTM). Design Expert software has been used for analyses, So Different results were obtained from the different tensile test specimens. The best, average and worst specimen were also observed under a compound microscope to investigate the layer bonding in between.

Keywords: additive manufacturing techniques, 3D printing, CAD software, UTM machine

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Authors: Marcus Klein, Martina GrießBach, Richard Kupke

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The current advances in the research and manufacturing of large area graphene layers are promising towards the introduction of this exciting material in the display industry and other applications that benefit from excellent electrical and optical characteristics. New production technologies in the fabrication of flexible displays, touch screens or printed electronics apply graphene layers on non-metal substrates and bring new challenges to the required metrology. Traditional measurement concepts of layer thickness, sheet resistance, and layer uniformity, are difficult to apply to graphene production processes and are often harmful to the product layer. New non-contact sensor concepts are required to adapt to the challenges and even the foreseeable inline production of large area graphene. Dedicated non-contact measurement sensors are a pioneering method to leverage these issues in a large variety of applications, while significantly lowering the costs of development and process setup. Transferred and printed graphene layers can be characterized with high accuracy in a huge measurement range using a very high resolution. Large area graphene mappings are applied for process optimization and for efficient quality control for transfer, doping, annealing and stacking processes. Examples of doped, defected and excellent Graphene are presented as quality images and implications for manufacturers are explained.

Keywords: graphene, doping and defect testing, non-contact sheet resistance measurement, inline metrology

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: José Luis Carrillo-Medina, Roberto Latorre

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Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.

Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network

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Authors: Le Quang Hanh

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Almost all big cities in Vietnam are often located in the river deltas. Therefore the ground condition on these cities is mostly soft soil. As a result, the soil strengthen works are mandatory in order to prevent the harmful to the third parties and tunnel structure itself in urban tunnel projects in Vietnam. This paper will particularly introduce the large diameter jet-grouted column technique that is recently being successfully applied in Ho Chi Minh City in Vietnam. The success application of this technique for protecting the historical sensitive building and for water cutoff objective of launching and arriving shafts in the urban tunnel project, will be analyzed from construction process, quality control and lessons learnt. From this situation, the large diameter jet-grouted column technique can extend to another urban tunnel projects in Vietnam and other countries which have similar soft soil conditions.

Keywords: large diameter, jet grouting, ground improvement, urban tunnel

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Authors: Theresa Slump, Paula Neumeister, Katharina Feldker, Carina Y. Heitmann, Thomas Straube

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A characteristic feature of post-traumatic stress disorder (PTSD) is the automatic processing of disorder-specific stimuli that expresses itself in intrusive symptoms such as intense physical and psychological reactions to trauma-associated stimuli. That automatic processing plays an essential role in the development and maintenance of symptoms. The aim of our study was, therefore, to investigate the behavioral and neural correlates of automatic processing of trauma-related stimuli in PTSD. Although interpersonal traumatization is a form of traumatization that often occurs, it has not yet been sufficiently studied. That is why, in our study, we focused on patients suffering from interpersonal traumatization. While previous imaging studies on PTSD mainly used faces, words, or generally negative visual stimuli, our study presented complex trauma-related and neutral visual scenes. We examined 19 female subjects suffering from PTSD and examined 19 healthy women as a control group. All subjects did a geometric comparison task while lying in a functional-magnetic-resonance-imaging (fMRI) scanner. Trauma-related scenes and neutral visual scenes that were not relevant to the task were presented while the subjects were doing the task. Regarding the behavioral level, there were not any significant differences between the task performance of the two groups. Regarding the neural level, the PTSD patients showed significant hyperactivation of the hippocampus for task-irrelevant trauma-related stimuli versus neutral stimuli when compared with healthy control subjects. Connectivity analyses revealed altered connectivity between the hippocampus and other anxiety-related areas in PTSD patients, too. Overall, those findings suggest that fear-related areas are involved in PTSD patients' processing of trauma-related stimuli even if the stimuli that were used in the study were task-irrelevant.

Keywords: post-traumatic stress disorder, automatic processing, hippocampus, functional magnetic resonance imaging

Procedia PDF Downloads 184

Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Md Habibur Rahman, Jaeho Kim

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Efficient process scheduling is a crucial factor in ensuring optimal system performance and resource utilization in computer systems. While various algorithms have been proposed over the years, there are still limitations to their effectiveness. This paper introduces a new Wait-Optimized Scheduler (WOS) algorithm that aims to minimize process waiting time by dividing them into two layers and considering both process time and waiting time. The WOS algorithm is non-preemptive and prioritizes processes with the shortest WOS. In the first layer, each process runs for a predetermined duration, and any unfinished process is subsequently moved to the second layer, resulting in a decrease in response time. Whenever the first layer is free or the number of processes in the second layer is twice that of the first layer, the algorithm sorts all the processes in the second layer based on their remaining time minus waiting time and sends one process to the first layer to run. This ensures that all processes eventually run, optimizing waiting time. To evaluate the performance of the WOS algorithm, we conducted experiments comparing its performance with traditional scheduling algorithms such as First-Come-First-Serve (FCFS) and Shortest-Job-First (SJF). The results showed that the WOS algorithm outperformed the traditional algorithms in reducing the waiting time of processes, particularly in scenarios with a large number of short tasks with long wait times. Our study highlights the effectiveness of the WOS algorithm in improving process scheduling efficiency in computer systems. By reducing process waiting time, the WOS algorithm can improve system performance and resource utilization. The findings of this study provide valuable insights for researchers and practitioners in developing and implementing efficient process scheduling algorithms.

Keywords: process scheduling, wait-optimized scheduler, response time, non-preemptive, waiting time, traditional scheduling algorithms, first-come-first-serve, shortest-job-first, system performance, resource utilization

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Martin Elstner

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Processing of information by means of handling chemicals is a ubiquitous phenomenon in nature. Technical implementations of chemical information processing lack of low integration densities compared to electronic devices. Stimuli responsive hydrogels are promising candidates for materials with information processing capabilities. These hydrogels are sensitive toward chemical stimuli like metal ions or amino acids. The binding of an analyte molecule induces conformational changes inside the polymer network and subsequently the water content and volume of the hydrogel varies. This volume change can control material flows, and concurrently information flows, in microfluidic devices. The combination of this technology with powerful chemical logic gates yields in a platform for highly integrated chemical circuits. The manufacturing process of such devices is very challenging and rapid prototyping is a key technology used in the study. 3D printing allows generating three-dimensional defined structures of high complexity in a single and fast process step. This thermoplastic master is molded into PDMS and the master is removed by dissolution in an organic solvent. A variety of hydrogel materials is prepared by dispenser printing of pre-polymer solutions. By a variation of functional groups or cross-linking units, the functionality of the hole circuit can be programmed. Finally, applications in the field of bio-molecular analytics were demonstrated with an autonomously operating microfluidic chip.

Keywords: bioanalytics, hydrogels, information processing, microvalve

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Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

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Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

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Authors: Parisa Khoshvaght, Mehdi Hosseinzadeh

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During the past few years, the Residue Number System (RNS) has been receiving considerable interest due to its parallel and fault-tolerant properties. This system is a useful tool for Digital Signal Processing (DSP) since it can support parallel, carry-free, high-speed and low power arithmetic. One of the drawbacks of Residue Number System is the fractional numbers, that is, the corresponding circuit is very hard to realize in conventional CMOS technology. In this paper, we propose a method in which the numbers of transistors are significantly reduced. The related delay is extremely diminished, in the first glance we use this method to solve concerning problem of one decimal functional number some how this proposition can be extended to generalize the idea. Another advantage of this method is the independency on the kind of moduli.

Keywords: computer arithmetic, residue number system, number system, one-Hot, VLSI

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Authors: Gizachew Belay Adugna

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Scalable and cost-effective device fabrication techniques are urgent to commercialize the perovskite solar cells (PSCs) for the next photovoltaic (PV) technology. Herein, large-area films of perovskite and hole-transporting materials (HTMs) were developed via a rapid and scalable thermal-assisting bar-coating process in the open air. High-quality and large crystalline grains of MAPbI₃ with homogenous morphology and thickness were obtained on a large-area (10 cm×10 cm) solution-sheared mp-TiO₂/c-TiO₂/FTO substrate. Encouraging photovoltaic performance of 19.02% was achieved for devices fabricated from the bar-coated perovskite film compared to that from the small-scale spin-coated film (17.27%) with 2,2′,7,7′-tetrakis-(N,N-di-p-methoxyphenylamine)-9,9′-spirobifluorene (spiro-OMeTAD) as an HTM whereas a higher power conversion efficiency of 19.89% with improved device stability was achieved by capping a fluorinated (HYC-2) HTM as an alternative to the traditional spiro-OMeTAD. The fluorinated exhibited better molecular packing in the HTM film and deeper HOMO level compared to the nonfluorinated counterpart; thus, improved hole mobility and overall charge extraction in the device were demonstrated. Furthermore, excellent film processability and an impressive PCE of 18.52% were achieved in the large area bar-coated HYC-2 prepared sequentially on the perovskite underlayer in the open atmosphere, compared to the bar-coated spiro-OMeTAD/perovskite (17.51%). This all-solution approach demonstrated the feasibility of high-quality films on a large-area substrate for PSCs, which is a vital step toward industrial-scale PV production.

Keywords: perovskite solar cells, hole transporting materials, up-scaling process, power conversion efficiency

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Authors: Mayuva Youngsabanant-Areekijseree, Chanikarn Srinark, S. Sengsai, Mayuree Pumipaiboon

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Our project was aimed at morphology of oocytes, follicle cells and follicular fluid proteins study of Large White pig (at local slaughter house in Nakhon Pathom Province). The porcine oocytes and follicular fluid of healthy small follicles (1-2 mm), medium follicles (3-6 mm in diameters) and large follicles (7-8 mm and 10 mm in diameter) were aspirated and collected from the ovary by sterile technique. Then, the oocytes and the follicle cells were separated from the fluid. The oocytes were round shape and surrounded by zona pellucida with numerous layers of cumulus cells. Based on the number of cumulus cell layers surrounding oocytes, the oocytes were classified into 5 types, which were intact-, multi-, partial-cumulus layer oocyte, completely denuded oocyte and degenerative oocyte. The collected oocytes showed high percentages of intact- and multi- cumulus cell layers in the small follicles (53.48%) medium follicles (56.94%) and large follicles (56.52%) which have high potential to develop into mature oocytes in vitro. Proteins from follicular fluid of 3 size follicles were separated by SDS-PAGE and LC/MS/MS. The molecular weight of follicular fluid proteins from the small follicles were 24, 60-65, 79, 110, 140, 160, and > 220 kDa. Meanwhile, the follicular fluid protein from medium and large follicle contained 52, 65, 79, 90, 110, 120, 160, 190 and > 220 kDa. Almost all proteins played important roles in promoting and regulating growth and development of oocytes and ovulation. This finding was an initial tool for in vitro testing and applied biotechnology research. Acknowledgements: The project was funded by a grant from Silpakorn University Research & Development Institute (SURDI) and Faculty of Science, Silpakorn University, Thailand.

Keywords: follicular fluid protein, LC/MS/MS, porcine oocyte, SDS-PAGE, reproductive biology

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Authors: Mahani Razali, Abd Halim Masnan, Nordin Mamat, Seah Siok Peh

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This research is based on three main objectives which are to identify children`s social interaction behaviour during computer play activities, teacher’s role and to explore teacher’s beliefs, views and knowledge about computers use in four Malaysian pre-schools.This qualitative study was carried out among 25 pre-school children and three teachers as the research sample. The data collection procedures involved structured observation which was to identify social interaction behavior among pre-school children through computer play activities; as for semi-structured interviews, it was done to study the perception of the teachers on the acquired of social interaction behavior development among the children. A variety of patterns can be seen within the peer interactions indicating that children exhibit a vast range of social interactions at the computer, and they varied each day. The findings of this study guide us to certain conclusions, which have implications in understanding the phenomena of how computers were used and how its relationship to the children’s social interactions emerge in the four Malaysian preschools. This study provides evidence that the children’s social interactions with peers and adults were mediated by the engagement of the children in the computer environments.

Keywords: computer, play, preschool, social interaction

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Authors: Ricardo Andrés Márquez Ortiz

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Objective: The objective of this literature review is to compile updated information from studies that have addressed the association between dental pathologies and agriculture. Materials and method: The research carried out corresponds to a documentary study of ex post facto retrospective, historiographic, and bibliometric design. An exhaustive bibliographic review search was carried out in databases and the Internet, books and articles on dental anthropology, archeology, and dentistry, on the relationship between dental pathologies and agriculture in prehistoric and current populations from different parts of the world. Subsequently, data collection was carried out through the ATLAS.ti computer program. Conclusions: In an influential article by Turner, which addresses the correlation between caries and the way of subsistence of both prehistoric and modern populations (hunting and gathering, mixed and agricultural economies), an average of 1.3% was found in hunter-gatherer societies, and 10.4% in agricultural societies. Sreebny compared global grain supply data (rice, wheat and corn) with DMF (spoiled, lost and blocked) rates. He concluded that rice has no association with dental caries, corn has a negative correlation, and wheat has a positive correlation. Additionally, intensive monoculture agricultural production systems cause an increase in dental pathologies. Meanwhile, polyculture agriculture, which leads to a more varied diet, generates a better state of dental health.

Keywords: dental pathologies, agricultural production systems, extensive agriculture, dental anthropology

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Authors: Monika Paleczna, Barbara Szmigielska

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The period of adolescence is a time when young people are becoming more and more active and conscious users of the digital world. One of the most frequently undertaken activities by them is computer games. Young players can choose from a wide range of games, including action, adventure, strategy, and logic games. The main aim of this study is to answer the question about the motivation of teenage players. The basic question is what motivates young players to play computer games and what motivates them to play a particular game. Fifty adolescents aged 15-17 participated in the study. They completed a questionnaire in which they determined what motivates them to play, how often they play computer games, and what type of computer games they play most often. It was found that entertainment and learning English are among the most important motives. The most important specific features related to a given game are the knowledge of its previous parts and the ability to play for free. The motives chosen by the players will be described in relation to the concepts of internal and external as well as approach and avoidance motivation. An additional purpose of this study is to present data concerning preferences regarding the type of games and the amount of time they spend playing.

Keywords: computer games, motivation, game preferences, adolescence

Procedia PDF Downloads 162