Search results for: intelligent computational techniques

Authors: Mohammad Salehi, Mohammad Erfan Doraki

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In this paper, airflow analysis inside a desktop computer case is performed by simulating computational fluid dynamics. The purpose is to investigate the cooling process of the central processing unit (CPU) with thermal capacities of 80 and 130 watts. The airflow inside the computer enclosure, selected from the microATX model, consists of the main components of heat production such as CPU, hard disk drive, CD drive, floppy drive, memory card and power supply unit; According to the amount of thermal power produced by the CPU with 80 and 130 watts of power, two different geometries have been used for a direct and radial heat sink. First, the independence of the computational mesh and the validation of the solution were performed, and after ensuring the correctness of the numerical solution, the results of the solution were analyzed. The simulation results showed that changes in CPU temperature and other components linearly increased with increasing CPU heat output. Also, the ambient air temperature has a significant effect on the maximum processor temperature.

Keywords: computational fluid dynamics, CPU cooling, computer case simulation, heat sink

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Authors: Nwachukwu Ifeanyi

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Wind energy is a vital component of the global renewable energy portfolio, with wind turbines serving as the primary means of harnessing this abundant resource. However, the efficiency and stability of wind turbines remain critical challenges in maximizing energy output and ensuring long-term operational viability. This study proposes a comprehensive approach utilizing computational aerodynamics and aeromechanics to optimize wind turbine performance across multiple objectives. The proposed research aims to integrate advanced computational fluid dynamics (CFD) simulations with structural analysis techniques to enhance the aerodynamic efficiency and mechanical stability of wind turbine blades. By leveraging multi-objective optimization algorithms, the study seeks to simultaneously optimize aerodynamic performance metrics such as lift-to-drag ratio and power coefficient while ensuring structural integrity and minimizing fatigue loads on the turbine components. Furthermore, the investigation will explore the influence of various design parameters, including blade geometry, airfoil profiles, and turbine operating conditions, on the overall performance and stability of wind turbines. Through detailed parametric studies and sensitivity analyses, valuable insights into the complex interplay between aerodynamics and structural dynamics will be gained, facilitating the development of next-generation wind turbine designs. Ultimately, this research endeavours to contribute to the advancement of sustainable energy technologies by providing innovative solutions to enhance the efficiency, reliability, and economic viability of wind power generation systems. The findings have the potential to inform the design and optimization of wind turbines, leading to increased energy output, reduced maintenance costs, and greater environmental benefits in the transition towards a cleaner and more sustainable energy future.

Keywords: computation, robotics, mathematics, simulation

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Authors: Xin Jiao, Xin Zhang, Jian Fan, Zhenwei Cai, Yiming Xu

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Tower cranes play a crucial role in the construction industry, facilitating the vertical and horizontal movement of materials and aiding in building construction, especially for high-rise structures. However, tower crane accidents can lead to severe consequences, highlighting the importance of effective safety management and inspection. This paper presents an innovative approach to tower crane inspection utilizing Unmanned Aerial Vehicles (UAVs) and an Intelligent Inspection APP System. The system leverages UAVs equipped with high-definition cameras to conduct efficient and comprehensive inspections, reducing manual labor, inspection time, and risk. By integrating advanced technologies such as Real-Time Kinematic (RTK) positioning and digital image processing, the system enables precise route planning and collection of safety hazards images. A case study conducted on a construction site demonstrates the practicality and effectiveness of the proposed method, showcasing its potential to enhance tower crane safety. On-site testing of UAV intelligent inspections reveals key findings: efficient tower crane hazard inspection within 30 minutes, with a full-identification capability coverage rates of 76.3%, 64.8%, and 76.2% for major, significant, and general hazards respectively and a preliminary-identification capability coverage rates of 18.5%, 27.2%, and 19%, respectively. Notably, UAVs effectively identify various tower crane hazards, except for those requiring auditory detection. The limitations of this study primarily involve two aspects: Firstly, during the initial inspection, manual drone piloting is required for marking tower crane points, followed by automated flight inspections and reuse based on the marked route. Secondly, images captured by the drone necessitate manual identification and review, which can be time-consuming for equipment management personnel, particularly when dealing with a large volume of images. Subsequent research efforts will focus on AI training and recognition of safety hazard images, as well as the automatic generation of inspection reports and corrective management based on recognition results. The ongoing development in this area is currently in progress, and outcomes will be released at an appropriate time.

Keywords: tower crane, inspection, unmanned aerial vehicle (UAV), intelligent inspection app system, safety management

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: B. G. Sheeparamatti, Prashant Hanasi, Vanita Abbigeri

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The objective of this work is to carry out a critical comparison of different actuation mechanisms like electrostatic, thermal, piezoelectric, and magnetic with reference to a microcantilever. The relevant parameters like force generated, displacement are compared in actuation methods. With these results, they help in choosing the best actuation method for a particular application. In this study, Comsol/Multiphysics software is used. Modeling and simulation are done by considering the microcantilever of same dimensions as an actuator using all the above-mentioned actuation techniques. In addition to their small size, micro actuators consume very little power and are capable of accurate results. In this work, a comparison of actuation mechanisms is done to decide the efficient system in the micro domain.

Keywords: actuation techniques, microswitch, micro actuator, microsystems

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Authors: Atousa Khodadadyan, Gabe Mythen, Hirbod Assa, Beverley Bishop

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Risk assessment and the knowledge provided through this process is a crucial part of any decision-making process in the management of risks and uncertainties. Failure in assessment of risks can cause inadequacy in the entire process of risk management, which in turn can lead to failure in achieving organisational objectives as well as having significant damaging consequences on populations affected by the potential risks being assessed. The choice of tools and techniques in risk assessment can influence the degree and scope of decision-making and subsequently the risk response strategy. There are various available qualitative and quantitative tools and techniques that are deployed within the broad process of risk assessment. The sheer diversity of tools and techniques available to practitioners makes it difficult for organisations to consistently employ the most appropriate methods. This tools and techniques adaptation is rendered more difficult in public risk regulation organisations due to the sensitive and complex nature of their activities. This is particularly the case in areas relating to the environment, food, and human health and safety, when organisational goals are tied up with societal, political and individuals’ goals at national and international levels. Hence, recognising, analysing and evaluating different decision support tools and techniques employed in assessing risks in public risk management organisations was considered. This research is part of a mixed method study which aimed to examine the perception of risk assessment and the extent to which organisations practise risk assessment’ tools and techniques. The study adopted a semi-structured questionnaire with qualitative and quantitative data analysis to include a range of public risk regulation organisations from the UK, Germany, France, Belgium and the Netherlands. The results indicated the public risk management organisations mainly use diverse tools and techniques in the risk assessment process. The primary hazard analysis; brainstorming; hazard analysis and critical control points were described as the most practiced risk identification techniques. Within qualitative and quantitative risk analysis, the participants named the expert judgement, risk probability and impact assessment, sensitivity analysis and data gathering and representation as the most practised techniques.

Keywords: decision-making, public risk management organisations, risk assessment, tools and techniques

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Edgar Teixeira, Eurico Carrapatoso

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As 3D displays become increasingly affordable, while production techniques and computational resources to create stereoscopic content being ever more accessible, a new dimension is literally introduced along with new expressive and immersive potentialities in support of designing for the screen. Prospective design visionaries have already at the reach of their hands an innovative and powerful visualization technology, which enables them to actively envision future trends and vanguardist directions. This paper explores the aesthetic and informational potentialities of stereoscopic motion graphics, providing insight on the application of 3D displays in design practice, proposing strategies to investigate stereoscopic communication, discussing potential repercussions to extant theory and impacts on audience.

Keywords: design, visual communication, technology, stereoscopy, 3D media

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

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Authors: Ming-Ta Yang, Jyh-Cherng Gu, Chun-Wei Huang, Jin-Lung Guan

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Time base maintenance (TBM) is conventionally applied by the power utilities to maintain circuit breakers (CBs), transformers, bus bars and cables, which may result in under maintenance or over maintenance. As information and communication technology (ICT) industry develops, the maintenance policies of many power utilities have gradually changed from TBM to condition base maintenance (CBM) to improve system operating efficiency, operation cost and power supply reliability. This paper discusses the feasibility of using intelligent electronic devices (IEDs) to construct a CB CBM management platform. CBs in power substations can be monitored using IEDs with additional logic configuration and wire connections. The CB monitoring data can be sent through intranet to a control center and be analyzed and integrated by the Elipse Power Studio software. Finally, a human-machine interface (HMI) of supervisory control and data acquisition (SCADA) system can be designed to construct a CBM management platform to provide maintenance decision information for the maintenance personnel, management personnel and CB manufacturers.

Keywords: circuit breaker, condition base maintenance, intelligent electronic device, time base maintenance, SCADA

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Authors: Mohammad Reza Akhavan Khaleghi

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This paper shows changes done to the Reduced Finite Element Method (RFEM) that its result will be the most powerful numerical method that has been proposed so far (some forms of this method are so powerful that they can approximate the most complex equations simply Laplace equation!). Finite Element Method (FEM) is a powerful numerical method that has been used successfully for the solution of the existing problems in various scientific and engineering fields such as its application in CFD. Many algorithms have been expressed based on FEM, but none have been used in popular CFD software. In this section, full monopoly is according to Finite Volume Method (FVM) due to better efficiency and adaptability with the physics of problems in comparison with FEM. It doesn't seem that FEM could compete with FVM unless it was fundamentally changed. This paper shows those changes and its result will be a powerful method that has much better performance in all subjects in comparison with FVM and another computational method. This method is not to compete with the finite volume method but to replace it.

Keywords: reduced finite element method, new computational package, new finite element formulation, new higher-order form, new isogeometric analysis

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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: Ahmed Stifi, Sascha Gentes

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The German nuclear industry, while implementing the German policy, believes that the journey towards the green-field, namely phasing out of nuclear energy, should be achieved through green techniques. The most important techniques required for the wide range of decommissioning activities are decontamination techniques, cutting techniques, radioactivity measuring techniques, remote control techniques, techniques for worker and environmental protection and techniques for treating, preconditioning and conditioning nuclear waste. Many decontamination techniques are used for removing contamination from metal, concrete or other surfaces like the scales inside pipes. As the pipeline system is one of the important components of nuclear power plants, the process of decontamination in tubing is of more significance. The development of energy sectors like oil sector, gas sector and nuclear sector, since the middle of 20th century, increased the pipeline industry and the research in the decontamination of tubing in each sector is found to serve each other. The extraction of natural products and material through the pipeline can result in scale formation. These scales can be radioactively contaminated through an accumulation process especially in the petrochemical industry when oil and gas are extracted from the underground reservoir. The radioactivity measured in these scales can be significantly high and pose a great threat to people and the environment. At present, the decontamination process involves using high pressure water jets with or without abrasive material and this technology produces a high amount of secondary waste. In order to overcome it, the research team within Karlsruhe Institute of Technology developed a new sustainable method to carry out the decontamination of tubing without producing any secondary waste. This method is based on vibration technique which removes scales and also does not require any auxiliary materials. The outcome of the research project proves that the vibration technique used for decontamination of tubing is environmental friendly in other words a sustainable technique.

Keywords: sustainable technologies, decontamination, pipeline, nuclear industry

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Authors: Abdulqader Rasool Feqi Mohammed, Ergun Erçelebi̇

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A large number of hospitals from developed countries are adopting hospital information system to bring efficiency in hospital information system. The purpose of this project is to research on new network security techniques in order to enhance the current network security structure of save a hospital information system (HIS). This is very important because, it will avoid the system from suffering any attack. Security architecture was optimized but there are need to keep researching on best means to protect the network from future attacks. In this final project research, security techniques were uncovered to produce best network security results when implemented in an integrated framework.

Keywords: hospital information system, HIS, network security techniques, internet protocol, IP, network

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Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

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The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

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Authors: Ahmed F. Ghanem, Marwa I. Wahba, Asmaa N. El-Dein, Mohamed A. EL-Raey, Ghada E.A. Awad

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Numerous attempts are being performed in order to formulate suitable packaging materials for meat products. However, to the best of our knowledge, the incorporation of free hibiscus extract or its microcapsules in the pure polyvinyl alcohol (PVA) matrix as packaging materials for meats is seldom reported. Therefore, this study aims at protection of the aqueous crude extract of hibiscus flowers utilizing spry drying encapsulation technique. Fourier transform infrared (FTIR), scanning electron microscope (SEM), and zetasizer results confirmed the successful formation of assembled capsules via strong interactions, spherical rough microparticles, and ~ 235 nm of particle size, respectively. Also, the obtained microcapsules enjoy high thermal stability, unlike the free extract. Then, the obtained spray-dried particles were incorporated into the casting solution of the pure PVA film with a concentration 10 wt. %. The segregated free-standing composite films were investigated, compared to the neat matrix, with several characterization techniques such as FTIR, SEM, thermal gravimetric analysis (TGA), mechanical tester, contact angle, water vapor permeability, and oxygen transmission. The results demonstrated variations in the physicochemical properties of the PVA film after the inclusion of the free and the extract microcapsules. Moreover, biological studies emphasized the biocidal potential of the hybrid films against microorganisms contaminating the meat. Specifically, the microcapsules imparted not only antimicrobial but also antioxidant activities to PVA. Application of the prepared films on the real meat samples displayed low bacterial growth with a slight increase in the pH over the storage time up to 10 days at 4 oC which further proved the meat safety. Moreover, the colors of the films did not significantly changed except after 21 days indicating the spoilage of the meat samples. No doubt, the dual-functional of prepared composite films pave the way towards combined active/smart food packaging applications. This would play a vital role in the food hygiene, including also quality control and assurance.

Keywords: PVA, hibiscus, extraction, encapsulation, active packaging, smart and intelligent packaging, meat spoilage

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Edwin Javier Cortes, Surupa Shaw

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In recent years, there has been a growing emphasis on enhancing the efficiency and performance of wind and water turbines to meet the increasing demand for sustainable energy sources. One promising approach is the utilization of advanced flow control techniques to optimize aerodynamic performance. This paper explores the application of advanced flow control techniques in both wind and water turbines, aiming to maximize their efficiency and output. By manipulating the flow of air or water around the turbine blades, these techniques offer the potential to improve energy capture, reduce drag, and minimize turbulence-induced losses. The paper will review various flow control strategies, including passive and active techniques such as vortex generators, boundary layer suction, and plasma actuators. It will examine their effectiveness in optimizing turbine performance under different operating conditions and environmental factors. Furthermore, the paper will discuss the challenges and opportunities associated with implementing these techniques in practical turbine designs. It will consider factors such as cost-effectiveness, reliability, and scalability, as well as the potential impact on overall turbine efficiency and lifecycle. Through a comprehensive analysis of existing research and case studies, this paper aims to provide insights into the potential benefits and limitations of advanced flow control techniques for wind and water turbines. It will also highlight areas for future research and development, with the ultimate goal of advancing the state-of-the-art in turbine technology and accelerating the transition towards a more sustainable energy future.

Keywords: flow control, efficiency, passive control, active control

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Authors: Faisal AlShammari, Abdulmajid Addali

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Monitoring the conditions of rotating machinery as bearing is important in order to improve its stability of works. Acoustic emission (AE) and vibration analysis are some of the most accomplished techniques used for this purpose. Acoustic emission has the ability to detect the initial phase of component degradation. Moreover, it has been observed that the success of vibration analysis does not take place below 100 rpm rotational speed. This because the energy generated below 100 rpm rotational speed is not detectable using conventional vibration. From this pint, this paper has presented a focused review of using acoustic emission techniques for monitoring bearings condition.

Keywords: condition monitoring, stress wave analysis, low-speed bearings, bearing defect diagnosis

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Authors: Leandros A. Maglaras, Jianmin Jiang

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The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

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Authors: Ayman M. Mansour

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In this paper, we propose an intelligent system that is used for monitoring the health conditions of Patients. Monitoring the health condition of Patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will Improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to Faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The propose system will provide an intelligent system that will generate initial diagnosing to the patient case. This will assist and advice clinicians at the point of care. The decision is based on demographic data and laboratory test results of patient data. Using such system with the ability of making medical decisions, the quality of medical care in Jordan and specifically in Tafial is expected to be improved. This will provide more accurate, effective, and reliable diagnoses and treatments especially if the physicians have insufficient knowledge.

Keywords: GSM, SMS, patient, monitoring system, fuzzy logic, multi-agent system

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Authors: Agnieszka S. Dzielendziak, Lindsay-Marie Armstrong, Matthew E. Potter, Robert Raja, Pier J. A. Sazio

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Reducing carbon dioxide, CO₂, is one of the greatest global challenges. Conversion of CO₂ for utilisation across synthetic fuel, pharmaceutical, and agrochemical industries offers a promising option, yet requires significant research to understanding the complex multiscale processes involved. To experimentally understand and optimize such processes at that catalytic sites and exploring the impact of the process at reactor scale, is too expensive. Computational methods offer significant insight and flexibility but require a more detailed multi-scale approach which is a significant challenge in itself. This work introduces a computational approach which incorporates detailed catalytic models, taken from experimental investigations, into a larger-scale computational flow dynamics framework. The reactor-scale species transport approach is modified near the catalytic walls to determine the influence of catalytic clustering regions. This coupling approach enables more accurate modelling of velocity, pressures, temperatures, species concentrations and near-wall surface characteristics which will ultimately enable the impact of overall reactor design on chemical conversion performance.

Keywords: catalysis, CCU, CO₂, multi-scale model

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Authors: Shreya Thusoo, Karan Modi, Ankit Kumar Jha, Rajesh Kumar

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Since the evolution of computational tools and simulation software, there has been considerable increase in research on Soil Structure Interaction (SSI) to decrease the computational time and increase accuracy in the results. To aid the designer with a proper understanding of the response of structure in different soil types, the presented paper compares the deformation, shear stress, acceleration and other parameters of multi-storey building for a specific input ground motion using Response-spectrum Analysis (RSA) method. The response of all the models of different heights have been compared in different soil types. Finite Element Simulation software, ANSYS, has been used for all the computational purposes. Overall, higher response is observed with SSI, while it increases with decreasing stiffness of soil.

Keywords: soil-structure interaction, response spectrum, analysis, finite element method, multi-storey buildings

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: Fiseha M. Guangul, Annissa Muhammed, Aja O. Chikere

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Group task is one method to create the conducive environment for the active teaching-learning process. Performing group task with active involvement of students will benefit the students in many ways. However, in most cases all students do not participate actively in the group task, and hence the intended benefits are not acquired. This paper presents the improvements of students’ participation in the group task and learning from the group task by introducing different techniques to enhance students’ participation. For the purpose of this research Carpentry and Joinery II (WT-392) course from Wood Technology Department at Adama Science and Technology University was selected, and five groups were formed. Ten group tasks were prepared and the first five group tasks were distributed to the five groups in the first day without introducing the techniques that are used to enhance participation of students in the group task. On another day, the other five group tasks were distributed to the same groups and various techniques were introduced to enhance students’ participation in the group task. The improvements of students’ learning from the group task after the implementation of the techniques. After implementing the techniques the evaluation showed that significant improvements were obtained in the students’ participation and learning from the group task.

Keywords: group task, students participation, active learning, the evaluation method

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Authors: Samuel Sii, David Homewood, Brendan Dittmer, Tony Nzembela, Jonathan O’Brien, Niall Corcoran, Dinesh Agarwal

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Introduction: Innovation is key to the advancement of medicine and improvement in patient care. This is particularly true in surgery, where pioneering techniques have transformed operative management from a historically highly risky peri-morbid and disfiguring to the contemporary low-risk, sterile and minimally invasive treatment modality. There is a delicate balance between enabling innovation and minimizing patient harm. Publication and discussion of novel surgical techniques allow for independent expert review. Recent journals have increasingly stringent requirements for publications and often require larger case volumes for novel techniques to be published. This potentially impairs the initial publication of novel techniques and slows innovation. The historical perspective provides a better understanding of how requirements for the publication of new techniques have evolved over time. This is essential in overcoming challenges in developing novel techniques. Aims and Objectives: We explore how novel techniques in Urology have been published over the past 200 years. Our objective is to describe the trend and publication requirements of novel urological techniques, both historical and present. Methods: We assessed all major urological operations using multipronged historical analysis. An initial literature search was carried out through PubMed and Google Scholar for original literature descriptions, followed by reference tracing. The first publication of each pioneering urological procedure was recorded. Data collected includes the year of publication, description of the procedure, number of cases and outcomes. Results: 65 papers describing pioneering techniques in Urology were identified. These comprised of 2 experimental studies, 17 case reports and 46 case series. These papers described various pioneering urological techniques in urological oncology, reconstructive urology and endourology. We found that, historically, techniques were published with smaller case numbers. Often, the surgical technique itself was a greater focus of the publication than patient outcome data. These techniques were often adopted prior to larger publications. In contrast, the risks and benefits of recent novel techniques are often well-defined prior to adoption. This historical perspective is important as recent journals have requirements for larger case series and data outcomes. This potentially impairs the initial publication of novel techniques and slows innovation. Conclusion: A better understanding of historical publications and their effect on the adoption of urological techniques into common practice could assist the current generation of Urologists in formulating a safe, efficacious process in promoting surgical innovation and the development of novel surgical techniques. We propose the reassessment of requirements for the publication of novel operative techniques by splitting technical perspectives and data-orientated case series. Existing frameworks such as IDEAL and ASERNIP-S should be integrated into current processes when investigating and developing new surgical techniques to ensure efficacious and safe innovation within surgery is encouraged.

Keywords: urology, surgical innovation, novel surgical techniques, publications

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Authors: Y. L. Hor, H. S. Chu, V. P. Bui

Abstract:

Composite material is widely used to replace conventional material, especially in the aerospace industry to reduce the weight of the devices. It is formed by combining reinforced materials together via adhesive bonding to produce a bulk material with alternated macroscopic properties. In bulk composites, degradation may occur in microscopic scale, which is in each individual reinforced fiber layer or especially in its matrix layer such as delamination, inclusion, disbond, void, cracks, and porosity. In this paper, we focus on the detection of defect in matrix layer which the adhesion between the composite plies is in contact but coupled through a weak bond. In fact, the adhesive defects are tested through various nondestructive methods. Among them, pulsed phase thermography (PPT) has shown some advantages providing improved sensitivity, large-area coverage, and high-speed testing. The aim of this work is to develop an efficient numerical model to study the application of PPT to the nondestructive inspection of weak bonding in composite material. The resulting thermal evolution field is comprised of internal reflections between the interfaces of defects and the specimen, and the important key-features of the defects presented in the material can be obtained from the investigation of the thermal evolution of the field distribution. Computational simulation of such inspections has allowed the improvement of the techniques to apply in various inspections, such as materials with high thermal conductivity and more complex structures.

Keywords: pulsed phase thermography, weak bond, composite, CFRP, computational modelling, optimization

Procedia PDF Downloads 149

Authors: Choonsik Lee, Les Folio

Abstract:

Pregnant patients may undergo CT in emergencies unrelated with pregnancy, and potential risk to the developing fetus is of concern. It is critical to accurately estimate fetal organ doses in CT scans. We developed a fetal organ dose calculation tool using pregnancy-specific computational phantoms combined with Monte Carlo radiation transport techniques. We adopted a series of pregnancy computational phantoms developed at the University of Florida at the gestational ages of 8, 10, 15, 20, 25, 30, 35, and 38 weeks (Maynard et al. 2011). More than 30 organs and tissues and 20 skeletal sites are defined in each fetus model. We calculated fetal organ dose-normalized by CTDIvol to derive organ dose conversion coefficients (mGy/mGy) for the eight fetuses for consequential slice locations ranging from the top to the bottom of the pregnancy phantoms with 1 cm slice thickness. Organ dose from helical scans was approximated by the summation of doses from multiple axial slices included in the given scan range of interest. We then compared dose conversion coefficients for major fetal organs in the abdominal-pelvis CT scan of pregnancy phantoms with the uterine dose of a non-pregnant adult female computational phantom. A comprehensive library of organ conversion coefficients was established for the eight developing fetuses undergoing CT. They were implemented into an in-house graphical user interface-based computer program for convenient estimation of fetal organ doses by inputting CT technical parameters as well as the age of the fetus. We found that the esophagus received the least dose, whereas the kidneys received the greatest dose in all fetuses in AP scans of the pregnancy phantoms. We also found that when the uterine dose of a non-pregnant adult female phantom is used as a surrogate for fetal organ doses, root-mean-square-error ranged from 0.08 mGy (8 weeks) to 0.38 mGy (38 weeks). The uterine dose was up to 1.7-fold greater than the esophagus dose of the 38-week fetus model. The calculation tool should be useful in cases requiring fetal organ dose in emergency CT scans as well as patient dose monitoring.

Keywords: computed tomography, fetal dose, pregnant women, radiation dose

Procedia PDF Downloads 118

Authors: Anh Duong

Abstract:

The three-phase reading lesson has been put forth around the world as the new and innovative framework which is corresponding to the learner-centered trend in English language teaching and learning. Among three stages, pre-reading attracts many teachers’ and researchers’ attention for its vital role in preparing students with knowledge and interest in reading class. The researcher’s desire to exemplify effectiveness of activities prior to text reading has provoked the current study. Three main aspects were investigated in this paper, i.e. teachers’ and student’s perception of pre-reading stage, teachers’ exploitation of pre-reading techniques and teachers’ recommendation of effective pre-reading activities. Aiming at pre-reading techniques for first-year students at English Department, this study involved 200 fresh-men and 10 teachers from Division 1 to participate in the questionnaire survey. Interviews with the teachers and classroom observation were employed as a tool to take an insight into the responses gained from the early instrument. After a detailed procedure of analyzing data, the researcher discovered that thanks to the participants’ acclamation of pre-reading stage, this phase was frequently conducted by the surveyed teachers. Despite the fact that pre-reading activities apparently put a hand in motivating students to read and creating a joyful learning atmosphere, they did not fulfill another function as supporting students’ reading comprehension. Therefore, a range of techniques and notices when preparing and conducting pre-reading phase was detected from the interviewed teachers. The findings assisted the researcher to propose some related pedagogical implications concerning teachers’ source of pre-reading techniques, variations of suggested activities and first-year reading syllabus.

Keywords: pre-reading stage, pre-reading techniques, teaching reading, language teaching

Procedia PDF Downloads 469

Authors: Chen Xi, Liu Xuebing, Lao Xuerui, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

Abstract:

Climate change is a global problem facing humanity and this is now the consensus of the mainstream scientific community. In accordance with the carbon peak and carbon neutral targets and visions set out in the United Nations Framework Convention on Climate Change, the Kyoto Protocol and the Paris Agreement, this project uses the City Intelligent Model (CIM) and Artificial Intelligence Machine Vision (ICR) as the core technologies to accurately quantify low carbon behaviour into green corn, which is a means of guiding ecologically sustainable living patterns. Using individual communities as management units and blockchain as a guarantee of fairness in the whole cycle of green currency circulation, the project will form a modern resident carbon track management system based on the principle of enhancing the ecological resilience of communities and the cohesiveness of community residents, ultimately forming an ecologically sustainable smart village that can be self-organised and managed.

Keywords: urban planning, urban governance, CIM, artificial Intelligence, sustainable development

Procedia PDF Downloads 65