Search results for: automated dynamic cone penetration

Authors: A. Bentabet, A. Aydin, N. Fenineche

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The mean penetration depth has a most important in the absorption transport phenomena. Analytical model of light ion backscattering coefficients from solid targets have been made by Vicanek and Urbassek. In the present work, we showed a mathematical expression (deterministic model) for Z1/2. In advantage, in the best of our knowledge, relatively only one analytical model exit for electron or positron mean penetration depth in solid targets. In this work, we have presented a simple geometric spherical model of absorbed particles based on CSDA scheme. In advantage, we have showed an analytical expression of the mean penetration depth by combination between our model and the Vicanek and Urbassek theory. For this, we have used the Relativistic Partial Wave Expansion Method (RPWEM) and the optical dielectric model to calculate the elastic cross sections and the ranges respectively. Good agreement was found with the experimental and theoretical data.

Keywords: Bentabet spherical geometric model, continuous slowing down approximation, stopping powers, ranges, mean penetration depth

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Authors: Wang Jianguo, Ding Xiao, Liu Dong, Wang Haiping, Yang Yanhui, Hu Yang

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The hot deformation behavior of Inconel 718 alloy was studied by uniaxial compression tests under the deformation temperature of 940~1040℃ and strain rate of 0.001-10s⁻¹. The double cone compression (DCC) tests develop strains range from 30% to the 79% strain including all intermediate values of stains at different temperature (960~1040℃). DCC tests were simulated by finite element software which shown the strain and strain rates distribution. The result shows that the peak stress level of the alloy decreased with increasing deformation temperature and decreasing strain rate, which could be characterized by a Zener-Hollomon parameter in the hyperbolic-sine equation. The characterization method of hot processing window containing recrystallization volume fraction and average grain size was proposed for double cone compression test of uniform coarse grain, mixed crystal and uniform fine grain double conical specimen in hydraulic press and screw press. The results show that uniform microstructures can be obtained by low temperature with high deformation followed by high temperature with small deformation on the hydraulic press and low temperature, medium deformation, multi-pass on the screw press. The two methods were applied in industrial forgings process, and the forgings with uniform microstructure were obtained successfully.

Keywords: inconel 718 superalloy, hot processing windows, double cone compression, uniform microstructure

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Authors: Sayor Ajfar Aaron, Ashif Newaz, Sajjat Hossain Abir, Mushfiqur Rahman

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This paper examines the transformative potential of quantum computing in the field of cybersecurity, with a focus on advanced penetration testing and forensics. It explores how quantum technologies can be leveraged to identify and exploit vulnerabilities more efficiently than traditional methods and how they can enhance the forensic analysis of cyber-attacks. Through theoretical analysis and practical simulations, this study highlights the enhanced capabilities of quantum algorithms in detecting and responding to sophisticated cyber threats, providing a pathway for developing more resilient cybersecurity infrastructures.

Keywords: cybersecurity, cyber forensics, penetration testing, quantum computing

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Authors: Cristian Pauna

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With few steps away from the 2020, investments in financial markets is a common activity nowadays. In the electronic trading environment, the automated investment software has become a major part in the business intelligence system of any modern financial company. The investment decisions are assisted and/or made automatically by computers using mathematical algorithms today. The complexity of these algorithms requires computer assistance in the investment process. This paper will present several investment strategies that can be automated with algorithmic trading for Deutscher Aktienindex DAX30. It was found that, based on several price action mathematical models used for high-frequency trading some investment strategies can be optimized and improved for automated investments with good results. This paper will present the way to automate these investment decisions. Automated signals will be built using all of these strategies. Three major types of investment strategies were found in this study. The types are separated by the target length and by the exit strategy used. The exit decisions will be also automated and the paper will present the specificity for each investment type. A comparative study will be also included in this paper in order to reveal the differences between strategies. Based on these results, the profit and the capital exposure will be compared and analyzed in order to qualify the investment methodologies presented and to compare them with any other investment system. As conclusion, some major investment strategies will be revealed and compared in order to be considered for inclusion in any automated investment system.

Keywords: Algorithmic trading, automated investment systems, limit conditions, trading principles, trading strategies

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Authors: Keaghan Brown

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The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Jinsiang Shaw, Sheng-Xiang Xu

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This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

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Authors: Ashraf Eid

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Many formulas are set to estimate the pile load capacity based on the in-situ pile load tests. However, discrepancy is obvious between the results of these applications. Some formulas are more adequate than others with respect to soil formation and its characteristics. In this research, attempts were undertaken to evaluate the adequacy of the most well-known formulas based on a series of pile load tests carried out in Port Said city in the northeast of Egypt for major residential projects. Comparisons were undertaken between the different formulas supported by the results of in-situ Cone Penetration Tests (CPT). Based on this study, a guide for engineers for using the proper formula can be adopted with consideration of soil type and characteristics. The Egyptian Code which relies on the results of some formulas is involved in the study as a guiding aspect in the pile design.

Keywords: pile load formula, load test of piles, CPT, Egyptian code

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Authors: Balázs Kulcsár

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Few people now doubt the future of the global energy transition. The only question is whether the pace of renewables' penetration will be sufficient to compete with the rate of warming. Dynamic changes are also taking place in the Hungarian electricity system. In addition to nuclear power, which provides the basic electricity supply, the most dynamic is solar power, which is largely small-scale and residential. The emergence of solar power is outlining the emergence of energy production and supply fabric of municipalities. This creates the potential for over-producing municipalities to supply the electricity needs of neighboring settlements with lower production beyond renewables. By taking advantage of this energy sharing, electricity supply based on pure renewables can be achieved more quickly.

Keywords: renewable energy, energy geography, self-sufficiency, energy transition

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Authors: Ahmed W. Oda, Ahmed El-Desouky, Hassan Mahdy, Osama M. Moussa

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Nanomaterials have many applications in the field of asphalt paving. Two locally produced nanomaterials were used in the asphalt binder modification. The nanomaterials used are Nanosilica (NS), and Nanoclay (NC). The virgin asphalt binder was characterized by the conventional tests. The bitumen was modified by 3%, 5% and 7% of NS and NC. The penetration index(PI), and the retaining penetration (RP) was calculated based on the results of the penetration and the softening point tests. The results show that the RP becomes 95.35% at 5%NS modified bitumen and reaches 97.56% when bitumen is modified with 3% NC. The results show significant improvement in the bitumen stiffness when modified by the two types of nanomaterials, either fresh or aged (stored).

Keywords: bitumen, modified bitumen, aged, stored, nanomaterials

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Authors: Anil Khanal, Ali Osareh, Gary Lebby

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Wind energy offers a significant advantage such as no fuel costs and no emissions from generation. However, wind energy sources are variable and non-dispatchable. The utility grid is able to accommodate the variability of wind in smaller proportion along with the daily load. However, at high penetration levels, the variability can severely impact the utility reserve requirements and the cost associated with it. In this paper, the impact of wind energy is evaluated in detail in formulating the total utility cost. The objective is to minimize the overall cost of generation while ensuring the proper management of the load. Overall cost includes the curtailment cost, reserve cost and the reliability cost as well as any other penalty imposed by the regulatory authority. Different levels of wind penetrations are explored and the cost impacts are evaluated. As the penetration level increases significantly, the reliability becomes a critical question to be answered. Here, we increase the penetration from the wind yet keep the reliability factor within the acceptable limit provided by NERC. This paper uses an economic dispatch (ED) model to incorporate wind generation into the power grid. Power system costs are analyzed at various wind penetration levels using Linear Programming. The goal of this study shows how the increases in wind generation will affect power system economics.

Keywords: wind power generation, wind power penetration, cost analysis, economic dispatch (ED) model

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Authors: Phillip Garrad, Saritha Unnikrishnan

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The recent popularity of connected and autonomous vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks have been instigated by both researchers or white-coat hackers and cyber-criminals. As Connected Vehicles move towards full autonomy, the impact of these cyber-attacks also grows. The current research details challenges faced in cybersecurity testing of CAV, including access and cost of the representative test setup. Other challenges faced are lack of experts in the field. Possible solutions to how these challenges can be overcome are reviewed and discussed. From these findings, a software simulated CAV network is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects in penetration testing in other industries. There is an attempt to introduce similar AI models to the software simulation. The expectation from this implementation is to see similar improvements in runtime and efficiency for the CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing

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Authors: Aprilia, Wei Liang Keith Nguyen, Shu Beng Tor, Gerald Gim Lee Seet, Chee Kai Chua

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Automated remanufacturing process is of great interest in today’s marine and offshore industry. Most of the current remanufacturing processes are carried out manually and hence they are error prone, labour-intensive and costly. In this paper, a conceptual framework for automated remanufacturing is presented. This framework involves the integration of 3D non-contact digitization, adaptive surface reconstruction, additive manufacturing and machining operation. Each operation is operated and interconnected automatically as one system. The feasibility of adaptive surface reconstruction on marine and offshore engineering components is also discussed. Several engineering components were evaluated and the results showed that this proposed system is feasible. Conclusions are drawn and further research work is discussed.

Keywords: adaptive surface reconstruction, automated remanufacturing, automatic repair, reverse engineering

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Authors: Mohamed Islam Dahmani

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This research investigates the performance enhancement of semi-flexible pavements by incorporating self-compacting cement mortar as a cementitious grout. The study is divided into three phases for comprehensive evaluation. In the initial phase, a porous asphalt mixture is formulated with a target voids content of 25-30%. The goal is to achieve optimal interconnected voids that facilitate effective penetration of self-compacting cement mortar. The mixture's compliance with porous asphalt performance standards is ensured through tests such as marshal stability, indirect tensile strength, contabro test, and draindown test. The second phase focuses on creating a self-compacting cement mortar with high workability and superior penetration capabilities. This mortar is designed to fill the interconnected voids within the porous asphalt mixture. The formulated mortar's characteristics are assessed through tests like mini V funnel flow time, slump flow mini cone, as well as mechanical properties such as compressive strength, bending strength, and shrinkage strength. In the final phase, the performance of the semi-flexible pavement is thoroughly studied. Various tests, including marshal stability, indirect tensile strength, high-temperature bending, low-temperature bending, resistance to rutting, and fatigue life, are conducted to assess the effectiveness of the self-compacting cement mortar-enhanced pavement.

Keywords: semi-flexible pavements, cementitious grout, self-compacting cement mortar, porous asphalt mixture, interconnected voids, rutting resistance

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Authors: J. Sharib, D. N. A. Tugi, M. T. Ishak, M. I. A. Adziz

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The main purpose of this research paper conducted was to study the penetration of ⁷Be onto the soil surface for two different seasons in different areas of agricultural activity. The study was conducted during the dry and wet seasons from January to May 2019 in the Sembrong catchment area. The Sembrong Catchment Area is located in the district of Kluang, Johor in the South of Peninsular Malaysia and was selected based on the small size of the catchment and surrounded by various agricultural activities. A total of twenty (20) core soil samples to a depth of 10 cm each were taken using a metal corer made of metal. All these samples were brought to the Radiochemistry and Environment Group (RAS), Nuclear Malaysia, Block 23, Bangi, Malaysia, to enable the preparation, drying and analysis work to be carried out. Furthermore, all samples were oven dried at 45 – 60 ºC so that the dry weight became constant and gently disaggregated. Lastly, dried samples were milled and sieved at 2 mm before being packed into a well-type container and ready for ⁷Be analysis. The result of the analysis shows that the penetration of ⁷Be into the soil surface decreases by an exponential decay. The distribution of profiles to the interior of the soil surface or ho values ranged from 1.56 to 3.62 kg m⁻² and from 2.59 to 4.17 kg m⁻² for both dry and wet seasons. Consequently, the dry season has given a lower ho value when compared to the wet season. In conclusion, ⁷Be is a very suitable tracer to be used in determining the penetration onto the soil surface or ho values for the two different seasons.

Keywords: depth penetration, dry season, wet season, sembrong catchment, well type container

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Authors: Abel S. Huaynacho, Yoni D. Huaynacho

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The improvement of procedure test ASTM D1556, plays an important role in the developing of testing in field to obtain a higher quality of data QA/QC. The traditional process takes a considerable amount of time for only one test. Even making various testing are tasks repeating and it takes a long time to obtain better results. Moreover, if the adequate tools the help these testing are not properly managed, the improvement in the development for various testing could be stooped. This paper presents an optimized process for various testing ASTM D1556 which uses an initial standard process to another one the uses a simpler and improved management tools.

Keywords: cone sand test, density bulk, ASTM D1556, QA/QC

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Authors: Dong Wook Lee, Adrian Mistreanu

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The authors have studied a method for analyzing containment and penetration using an explicit nonlinear Finite Element Analysis. This method may be used in the stage of concept design for the protection of external configurations or components of aircraft engines and nuclear power plant structures. This paper consists of the modeling method, the results obtained from the method and the comparison of the results with those calculated from simple analytical method. It shows that the containment capability obtained by proposed method matches well with analytically calculated containment capability.

Keywords: computer aided engineering, containment analysis, finite element analysis, impact analysis, penetration analysis

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Authors: Baha Vural Kök, Mehmet Yilmaz, Mustafa Akpolat, Cihat Sav

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Various types of additives are used frequently in order to improve the rheological and mechanical properties of bituminous mixtures. Small devices instead of full scale machines are used for bitumen modification in the laboratory. These laboratory scale devices vary in terms of their properties such as mixing rate, mixing blade and the amount of binder. In this study, the effect of mixing rate and time during the bitumen modification processes on conventional and rheological properties of pure and crumb rubber modified binder were investigated. Penetration, softening point, rotational viscosity (RV) and dynamic shear rheometer (DSR) tests were applied to pure and CR modified bitumen. It was concluded that the penetration and softening point test did not show the efficiency of CR obtained by different mixing conditions. Besides, oxidation that occurred during the preparation processes plays a great part in the improvement effects of the modified binder.

Keywords: bitumen, crumb rubber, modification, rheological properties

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Authors: Rimon Rafiah

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This paper will present a combination of two seemingly unrelated models, which are the one for estimating economic development impacts as a result of transportation investment and the other for increasing CAV penetration in order to reduce congestion. Measuring economic development impacts resulting from transportation investments is becoming more recognized around the world. Examples include the UK’s Wider Economic Benefits (WEB) model, Economic Impact Assessments in the USA, various input-output models, and additional models around the world. The economic impact model is based on WEB and is based on the following premise: investments in transportation will reduce the cost of personal travel, enabling firms to be more competitive, creating additional throughput (the same road allows more people to travel), and reducing the cost of travel of workers to a new workplace. This reduction in travel costs was estimated in out-of-pocket terms in a given localized area and was then translated into additional employment based on regional labor supply elasticity. This additional employment was conservatively assumed to be at minimum wage levels, translated into GDP terms, and from there into direct taxation (i.e., an increase in tax taken by the government). The CAV model is based on economic principles such as CAV usage, supply, and demand. Usage of CAVs can increase capacity using a variety of means – increased automation (known as Level I thru Level IV) and also by increased penetration and usage, which has been predicted to go up to 50% by 2030 according to several forecasts, with possible full conversion by 2045-2050. Several countries have passed policies and/or legislation on sales of gasoline-powered vehicles (none) starting in 2030 and later. Supply was measured via increased capacity on given infrastructure as a function of both CAV penetration and implemented technologies. The CAV model, as implemented in the USA, has shown significant savings in travel time and also in vehicle operating costs, which can be translated into economic development impacts in terms of job creation, GDP growth and salaries as well. The models have policy implications as well and can be adapted for use in Japan as well.

Keywords: CAV, economic development, WEB, transport economics

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Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

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The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

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Authors: Bouami Hind, Millot Patrick

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The implementation of automated devices in life-critical systems such as hospitals can bring a new set of challenges related to automation malfunctions. While automation has been identified as great leverage for the medication dispensing system’s security and efficiency, it also increases the complexity of the organization. In particular, the installation and operation stage of automated devices can be complex when malfunctions related to automated systems occur. This paper aims to document operators’ situation awareness about the malfunctions of automated drug delivery systems (ADCs) during their implementation through Saint Brieuc hospital’s feedback. Our evaluation approach has been deployed in Saint Brieuc hospital center’s pharmacy, which has been equipped with automated nominative drug dispensing systems since January of 2021. The analysis of Saint Brieuc hospital center pharmacy’s automation revealed numerous malfunctions related to the implementation of Automated Delivery Cabinets. It appears that the targeted performance is not reached in the first year of implementation in this case study. Also, errors have been collected in patients' automated treatments’ production such as lack of drugs in pill boxes or nominative carnets, excess of drugs, wrong location of the drug, drug blister damaged, non-compliant sachet, or ticket errors. Saint Brieuc hospital center’s pharmacy is doing a tremendous job of setting up and monitoring performance indicators from the beginning of automation and throughout ADC’s operation to control ADC’s malfunctions and meet the performance targeted by the hospital. Health professionals, including pharmacists, biomedical engineers and directors of work, technical services and safety, are heavily involved in an automation project. This study highlights the importance of the evaluation of ADCs’ performance throughout the implementation process and the hospital’s team involvement in automation supervision and management.

Keywords: life-critical systems, situation awareness, automated delivery cabinets, implementation, risks and malfunctions

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Authors: Phang Moon Leng

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Automated Early Warning Scores is a newly developed clinical decision tool that is used to streamline and improve the process of obtaining a patient’s vital signs so a clinical decision can be made at an earlier stage to prevent the patient from further deterioration. This technology provides immediate update on the score and clinical decision to be taken based on the outcome. This paper aims to study the use of an automated early warning score system on whether the technology has assisted the hospital in early detection and escalation of clinical condition and improve patient outcome. The hospital adopted the Modified Early Warning Scores (MEWS) Scoring System and MEWS Clinical Response into Philips IntelliVue Guardian Automated Early Warning Score equipment and studied whether the process has been leaned, whether the use of technology improved the usage & experience of the nurses, and whether the technology has improved patient care and outcome. It was found the steps required to obtain vital signs has been significantly reduced and is used more frequently to obtain patient vital signs. The number of deaths, and length of stay has significantly decreased as clinical decisions can be made and escalated more quickly with the Automated EWS. The automated early warning score equipment has helped improve work efficiency by removing the need for documenting into patient’s EMR. The technology streamlines clinical decision-making and allows faster care and intervention to be carried out and improves overall patient outcome which translates to better care for patient.

Keywords: automated early warning score, clinical quality and safety, patient safety, medical technology

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Authors: Alexander Peikos, Carole Binsfeld

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The aim of this paper is to determine a thermally comfortable air temperature in an automated living room. This calculated temperature should serve as input for a user-specific and dynamic heating control in such a living space. In addition to the usual physical factors (air temperature, humidity, air velocity, and radiation temperature), individual clothing and activity should be taken into account. The calculation of such a temperature is based on different methods and indices which are usually used for the evaluation of the thermal comfort. The thermal insulation of the worn clothing is determined with a Radio Frequency Identification system. The activity performed is only taken into account indirectly through the generated heart rate. All these methods are ultimately very well suited for use in temperature regulation in an automated home, but still require further research and extensive evaluation.

Keywords: smart home, thermal comfort, predicted mean vote, radio frequency identification

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Authors: Cormac Reale, Luke J. Prendergast, Kenneth Gavin

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While significant improvements have been made in axial pile design methods over recent years, the influence of soils natural variability has not been adequately accounted for within them. Soil variability is a crucial parameter to consider as it can account for large variations in pile capacity across the same site. This paper seeks to address this knowledge deficit, by demonstrating how soil spatial variability can be accommodated into existing cone penetration test (CPT) based pile design methods, in the form of layered non-homogeneous random fields. These random fields model the scope of a given property’s variance and define how it varies spatially. A Monte Carlo analysis of the pile will be performed taking into account parameter uncertainty and spatial variability, described using the measured scales of fluctuation. The results will be discussed in light of Eurocode 7 and the effect of spatial averaging on design capacities will be analysed.

Keywords: pile axial design, reliability, spatial variability, CPT

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Authors: Lablali Mohammed, Mes-Adi Hassan, Mazroui M’Hammed

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To tackle the complexity of grasping atomic-scale structures and unraveling the factors affecting the development of thin films. In our work, we perform the deposition of Nb atoms on Cu substrates using the molecular dynamics simulation combined with the embedded atom method to describe the interaction between different atoms. We investigated the impact of varying deposition rates and thermal annealing processes on the microstructural, morphological, and mechanical characteristics of the deposited Nb film. Our findings reveal that Nb atom growth on the Cu substrate occurs in island mode, accompanied by the presence of nucleation phenomena during growth. On the other hand, mixing behavior was observed at the interface between the film and the substrate, where Nb penetration is initially limited to the first Cu layer, whereas Cu atoms diffuse until reaching the third layer in the Nb film. Furthermore, Nb exhibits a BCC structure, with a significant concentration observed at a rate of 5 atoms/ps, and annealing further amplifies these percentages. Deposition at different rates leads to distinct levels of compressive normal and biaxial stress.

Keywords: molecular dynamics, Nb thin film, structure and morphology, atomic penetration

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Authors: Areej R. Banjar, Abraham G. Campbell

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The use of Mixed Reality (MR) in teaching and training is growing popular and can improve students’ ability to perform technical procedures. This short paper outlines the creation of an interactive educational MR 3D application that aims to improve the quality of instruction for dentistry students. This application is called MRImplantology and aims to teach the fundamentals and preoperative planning of dental implant placement. MRImplantology uses cone-beam computed tomography (CBCT) images as the source for 3D dental models that dentistry students will be able to freely manipulate within a 3D MR world to aid their learning process.

Keywords: augmented reality, education, dentistry, cone-beam computed tomography CBCT, head mounted display HMD, mixed reality

Procedia PDF Downloads 190

Authors: T. P. Yu, J. J. Liu, X. L. Zhu, Y. Yin, W. Q. Wang, J. M. Ouyang, F. Q. Shao

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A strong electromagnetic field with E>1015V/m can be supplied by an intense laser such as ELI and HiPER in the near future. Exposing in such a strong laser field, laser-matter interaction enters into the near quantum electrodynamics (QED) regime and highly non-linear physics may occur during the laser-matter interaction. Recently, the multi-photon Breit-Wheeler (BW) process attracts increasing attention because it is capable to produce abundant positrons and it enhances the positron generation efficiency significantly. Here, we propose an all-optical scheme for bright gamma rays and dense positrons generation by irradiating a 1022 W/cm2 laser pulse onto an Al cone filled with near-critical-density plasmas. Two-dimensional (2D) QED particle-in-cell (PIC) simulations show that, the radiation damping force becomes large enough to compensate for the Lorentz force in the cone, causing radiation-reaction trapping of a dense electron bunch in the laser field. The trapped electrons oscillate in the laser electric field and emits high-energy gamma photons in two ways: (1) nonlinear Compton scattering due to the oscillation of electrons in the laser fields, and (2) Compton backwardscattering resulting from the bunch colliding with the reflected laser by the cone tip. The multi-photon Breit-Wheeler process is thus initiated and abundant electron-positron pairs are generated with a positron density ~1027m-3. The scheme is finally demonstrated by full 3D PIC simulations, which indicate the positron flux is up to 109. This compact gamma ray and positron source may have promising applications in future.

Keywords: BW process, electron-positron pairs, gamma rays emission, ultra-intense laser

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Authors: Brahim Mahfoud, Ali Bendjaghlouli

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Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

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Authors: Juang R. Matangaran, Erianto I. Putra, Iis Diatin, Muhammad Mujahid, Qi Adlan

Abstract:

Industrial plantation forest is the producer of logs in Indonesia. Several companies of industrial plantation forest have been successfully planted with fast-growing species, and it entered their annual harvesting period. Heavy machines such as forwarders are used in timber harvesting to extract logs from stump to landing site. The negative impact of using such machines are loss of topsoil and soil compaction. Compacted soil is considered unfavorable for plant growth. The research objectives were to analyze the soil bulk density, rut, and cone index of the soil caused by a forwarder passes, to analyze the relation between several times of forwarder passes to the increase of soil bulk density. A Valmet forwarder was used in this research. Soil bulk density at soil surface and cone index from the soil surface to the 50 cm depth of soil were measured at the harvested area. The result showed that soil bulk density increase with the increase of the Valmet forwarder passes. Maximum soil bulk density occurred after 5 times forwarder Valmet passed. The cone index tended to increase from the surface until 50 cm depth of soil. Rut formed and high soil bulk density indicated the soil compaction occurred by the forwarder operation.

Keywords: bulk density, forwarder Valmet, plantation forest, soil compaction, timber harvesting

Procedia PDF Downloads 145

Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

Abstract:

The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of the Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling human behavior. However, the exclusive use of this technology still seems insufficient to control vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: accuracy assessment, AI-driven mobility, artificial intelligence, automated vehicles

Procedia PDF Downloads 113