Search results for: hybrid block methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17088

Search results for: hybrid block methods

16548 Hybrid Algorithm for Non-Negative Matrix Factorization Based on Symmetric Kullback-Leibler Divergence for Signal Dependent Noise: A Case Study

Authors: Ana Serafimovic, Karthik Devarajan

Abstract:

Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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16547 Technical Assessment of Utilizing Electrical Variable Transmission Systems in Hybrid Electric Vehicles

Authors: Majid Vafaeipour, Mohamed El Baghdadi, Florian Verbelen, Peter Sergeant, Joeri Van Mierlo, Kurt Stockman, Omar Hegazy

Abstract:

The Electrical Variable Transmission (EVT), an electromechanical device, can be considered as an alternative solution to the conventional transmission system utilized in Hybrid Electric Vehicles (HEVs). This study present comparisons in terms of fuel consumption, power split, and state of charge (SoC) of an HEV containing an EVT to a conventional parallel topology and a series topology. To this end, corresponding simulations of these topologies are all performed in presence of control strategies enabling battery charge-sustaining and efficient power split. The power flow through the components of the vehicle are attained, and fuel consumption results of the considered cases are compared. The investigation of the results indicates utilizing EVT can provide significant added values in HEV configurations. The outcome of the current research paves its path for implementation of design optimization approaches on such systems in further research directions.

Keywords: Electrical Variable Transmission (EVT), Hybrid Electric Vehicle (HEV), parallel, series, modeling

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16546 Comparative Study of Deep Reinforcement Learning Algorithm Against Evolutionary Algorithms for Finding the Optimal Values in a Simulated Environment Space

Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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16545 Effect of Different Local Anesthetic Agents on Physiological Parameters and Vital Signs during Extraction in Children

Authors: Rasha F. Sharaf

Abstract:

Administration of local anesthesia for a child is considered a painful procedure, which affects his vital signs, physiological parameters, and his further attitude in the dental clinic. During the extraction of mandibular molars, the nerve block technique is the most commonly used for the administration of local anesthesia; however, this technique requires deep penetration of the needle, which causes pain and discomfort for the child. Therefore, the inferior alveolar nerve block technique can be substituted with an infiltration technique which is not painful if a potent anesthetic solutions will be used. In the current study, the effect of Articaine 4% will be compared to Mepivacaine 2%, and their influence on the vital signs of the child, as well as their ability to control pain during extraction, will be assessed.

Keywords: anesthesia, articaine, pain control, extraction

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16544 Hybrid Wavelet-Adaptive Neuro-Fuzzy Inference System Model for a Greenhouse Energy Demand Prediction

Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

Abstract:

Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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16543 Life Cycle Cost Evaluation of Structures with Hysteretic Dampers

Authors: Jinkoo Kim, Hyungoo Kang, Hyungjun Shin

Abstract:

In this study, a hybrid energy dissipation device is developed by combining a steel slit plate and friction pads to be used for seismic retrofit of structures, and its effectiveness is investigated by comparing the life cycle costs of the structure before and after the retrofit. The seismic energy dissipation capability of the dampers is confirmed by cyclic loading tests. The probabilities of reaching various damage states are obtained by fragility analysis, and the life cycle costs of the model structures are computed using the PACT (Performance Assessment Calculation Tool) program based on FEMA P-58 methodology. The fragility analysis shows that the probabilities of reaching limit states are minimized by the seismic retrofit with hybrid dampers and increasing column size. The seismic retrofit with increasing column size and hybrid dampers results in the lowest repair cost and shortest repair time.

Keywords: slit dampers, friction dampers, seismic retrofit, life cycle cost, FEMA P-58, PACT

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16542 Comparative Analysis of Hybrid Dynamic Stabilization and Fusion for Degenerative Disease of the Lumbosacral Spine: Finite Element Analysis

Authors: Mohamed Bendoukha, Mustapha Mosbah

Abstract:

The Radiographic apparent assumed that the asymptomatic adjacent segment disease ASD is common after lumbar fusion, but this does not correlate with the functional outcomes while compensatory increased motion and stresses at the adjacent level of fusion is well-known to be associated to ASD. Newly developed, the hybrid stabilization are allocated to substituted for mostly the superior level of the fusion in an attempt to reduce the number of fusion levels and likelihood of degeneration process at the adjacent levels during the fusion with pedicle screws. Nevertheless, its biomechanical efficiencies still remain unknown and complications associated with failure of constructs such screw loosening and toggling should be elucidated In the current study, a finite element (FE) study was performed using a validated L2/S1 model subjected to a moment of 7.5 Nm and follower load of 400 N to assess the biomedical behavior of hybrid constructs based on dynamic topping off, semi rigid fusion. The residual range of motion (ROM), stress distribution at the fused and adjacent levels, stress distribution at the disc and the cage-endplate interface with respect to changes of bone quality were investigated. The hybrid instrumentation was associated with a reduction in compressive stresses compared to the fusion construct in the adjacent-level disc and showed high substantial axial force in the implant while fusion instrumentation increased the motion for both flexion and extension.

Keywords: intervertebral disc, lumbar spine, degenerative nuclesion, L4-L5, range of motion finite element model, hyperelasticy

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16541 Assessment of the Electrical, Mechanical, and Thermal Nociceptive Thresholds for Stimulation and Pain Measurements at the Bovine Hind Limb

Authors: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage

Abstract:

Background: Three nociceptive thresholds of thermal, electrical, and mechanical thresholds commonly use to evaluate the local anesthesia in many species, for instance, cow, horse, cat, dog, rabbit, and so on. Due to the lack of investigations to evaluate and/or validate such those nociceptive thresholds, our plan was the comparison of two-foot local anesthesia methods of Intravenous Regional Anesthesia (IVRA) and our modified four-point Nerve Block Anesthesia (NBA). Materials and Methods: Eight healthy nonpregnant nondairy Holstein Frisian cows in a cross-over study design were selected for this study. All cows divided into two different groups to receive two local anesthesia techniques of IVRA and our modified four-point NBA. Three thermal, electrical, and mechanical force and pinpricks were applied to evaluate the quality of local anesthesia methods before and after local anesthesia application. Results: The statistical evaluation demonstrated that our four-point NBA has a qualification to select as a standard foot local anesthesia. However, the recorded results of our study revealed no significant difference between two groups of local anesthesia techniques of IVRA and modified four-point NBA related to quality and duration of anesthesia stimulated by electrical, mechanical and thermal nociceptive stimuli. Conclusion and discussion: All three nociceptive threshold stimuli of electrical, mechanical and heat nociceptive thresholds can be applied to measure and evaluate the efficacy of foot local anesthesia of dairy cows. However, our study revealed no superiority of those three nociceptive methods to evaluate the duration and quality of bovine foot local anesthesia methods. Veterinarians to investigate the duration and quality of their selected anesthesia method can use any of those heat, mechanical, and electrical methods.

Keywords: mechanical, thermal, electrical threshold, IVRA, NBA, hind limb, dairy cow

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16540 Hybrid Structure Learning Approach for Assessing the Phosphate Laundries Impact

Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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16539 Research and Application of the Three-Dimensional Visualization Geological Modeling of Mine

Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao

Abstract:

Today's mining industry is advancing gradually toward digital and visual direction. The three dimensional visualization geological modeling of mine is the digital characterization of mineral deposit, and is one of the key technology of digital mine. The three-dimensional geological modeling is a technology that combines the geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in three-dimensional environment with computer technology, and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provided scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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16538 An Analysis of Conditions for Efficiency Gains in Large ICEs Using Cycling

Authors: Bauer Peter, Murillo Jenny

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This paper investigates the bounds of achievable fuel efficiency improvements in engines due to cycling between two operating points assuming a series hybrid configuration . It is shown that for linear bsfc dependencies (as a function of power), cycling is only beneficial if the average power needs are smaller than the power at the optimal bsfc value. Exact expressions for the fuel efficiency gains relative to the constant output power case are derived. This asymptotic analysis is then extended to the case where transient losses due to a change in the operating point are also considered. The case of the boundary bsfc trajectory where constant power application and cycling yield the same fuel consumption.is investigated. It is shown that the boundary bsfc locations of the second non-optimal operating points is hyperbolic. The analysis of the boundary case allows to evaluate whether for a particular engine, cycling can be beneficial. The introduced concepts are illustrated through a number of real world examples, i.e. large production Diesel engines in series hybrid configurations.

Keywords: cycling, efficiency, bsfc, series hybrid, diesel, operating point

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16537 Applications of AI, Machine Learning, and Deep Learning in Cyber Security

Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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16536 Optimal Design of a PV/Diesel Hybrid System for Decentralized Areas through Economic Criteria

Authors: David B. Tsuanyo, Didier Aussel, Yao Azoumah, Pierre Neveu

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An innovative concept called “Flexy-Energy”is developing at 2iE. This concept aims to produce electricity at lower cost by smartly mix different available energies sources in accordance to the load profile of the region. With a higher solar irradiation and due to the fact that Diesel generator are massively used in sub-Saharan rural areas, PV/Diesel hybrid systems could be a good application of this concept and a good solution to electrify this region, provided they are reliable, cost effective and economically attractive to investors. Presentation of the developed approach is the aims of this paper. The PV/Diesel hybrid system designed consists to produce electricity and/or heat from a coupling between Diesel gensets and PV panels without batteries storage, while ensuring the substitution of gasoil by bio-fuels available in the area where the system will be installed. The optimal design of this system is based on his technical performances; the Life Cycle Cost (LCC) and Levelized Cost of Energy are developed and use as economic criteria. The Net Present Value (NPV), the internal rate of return (IRR) and the discounted payback (DPB) are also evaluated according to dual electricity pricing (in sunny and unsunny hours). The PV/Diesel hybrid system obtained is compared to the standalone Diesel gensets. The approach carried out in this paper has been applied to Siby village in Mali (Latitude 12 ° 23'N 8 ° 20'W) with 295 kWh as daily demand. This approach provides optimal physical characteristics (size of the components, number of component) and dynamical characteristics in real time (number of Diesel generator on, their load rate, fuel specific consumptions, and PV penetration rate) of the system. The system obtained is slightly cost effective; but could be improved with optimized tariffing strategies.

Keywords: investments criteria, optimization, PV hybrid, sizing, rural electrification

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16535 Design and Study of a Hybrid Micro-CSP/Biomass Boiler System for Water and Space Heating in Traditional Hammam

Authors: Said Lamghari, Abdelkader Outzourhit, Hassan Hamdi, Mohamed Krarouch, Fatima Ait Nouh, Mickael Benhaim, Mehdi Khaldoun

Abstract:

Traditional Hammams are big consumers of water and wood-energy. Any approach to reduce this consumption will contribute to the preservation of these two resources that are more and more stressed in Morocco. In the InnoTherm/InnoBiomass 2014 project HYBRIDBATH, funded by the Research Institute for Solar Energy and New Energy (IRESEN), we will use a hybrid system consisting of a micro-CSP system and a biomass boiler for water and space heating of a Hammam. This will overcome the problem of intermittency of solar energy, and will ensure continuous supply of hot water and heat. We propose to use local agricultural residues (olive pomace, shells of walnuts, almonds, Argan ...). Underfloor heating using either copper or PEX tubing will perform the space heating. This work focuses on the description of the system and the activities carried out so far: The installation of the system, the principle operation of the system and some preliminary test results.

Keywords: biomass boiler, hot water, hybrid systems, micro-CSP, parabolic sensor, solar energy, solar fraction, traditional hammam, underfloor heating

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16534 Potentiality of Litchi-Fodder Based Agroforestry System in Bangladesh

Authors: M. R. Zaman, M. S. Bari, M. Kajal

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A field experiment was conducted at the Agroforestry and Environment Research Field, Hajee Mohammad Danesh Science and Technology University, Dinajpur during 2013 to investigate the potentiality of three napier fodder varieties under Litchi orchard. The experiment was consisted of 2 factors RCBD with 3 replications. Among the two factors, factor A was two production systems; S1= Litchi + fodder and S2 = Fodder (sole crop); another factor B was three napier varieties: V1= BARI Napier -1 (Bazra), V2= BARI Napier - 2 (Arusha) and V3= BARI Napier -3 (Hybrid). The experimental results revealed that there were significant variation among the varieties in terms of leaf growth and yield. The maximum number of leaf plant -1 was recorded in variety Bazra (V1) whereas the minimum number was recorded in hybrid variety (V3).Significantly the highest (13.75, 14.53 and14.84 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was also recorded in variety Bazra whereas the lowest (5.89, 6.36 and 9.11 tha-1 at 1st, 2nd v and 3rd harvest respectively) yield was in hybrid variety. Again, in case of production systems, there were also significant differences between the two production systems were founded. The maximum number of leaf plant -1 was recorded under Litchi based AGF system (T1) whereas the minimum was recorded in open condition (T2). Similarly, significantly the highest (12.00, 12.35 and 13.31 tha-1 at 1st, 2nd and 3rd harvest respectively) yield of napier was recorded under Litchi based AGF system where as the lowest (9.73, 10.47 and 11.66 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was recorded in open condition i.e. napier in sole cropping. Furthermore, the interaction effect of napier variety and production systems were also gave significant deviation result in terms of growth and yield. The maximum number of leaf plant -1 was recorded under Litchi based AGF systems with Bazra variety whereas the minimum was recorded in open condition with hybrid variety. The highest yield (14.42, 16.14 and 16.15 tha-1 at 1st, 2nd and 3rd harvest respectively) of napier was found under Litchi based AGF systems with Bazra variety. Significantly the lowest (5.33, 5.79 and 8.48 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was found in open condition i.e. sole cropping with hybrid variety. In case of the quality perspective, the highest nutritive value (DM, ASH, CP, CF, EE, and NFE) was found in Bazra (V1) and the lowest value was found in hybrid variety (V3). Therefore, the suitability of napier production under Litchi based AGF system may be ranked as Bazra > Arusha > Hybrid variety. Finally, the economic analysis showed that maximum BCR (5.20) was found in the Litchi based AGF systems over sole cropping (BCR=4.38). From the findings of the taken investigation, it may be concluded that the cultivation of Bazra napier varieties in the floor of Litchi orchard ensures higher revenue to the farmers compared to its sole cropping.

Keywords: potentiality, Litchi, fodder, agroforestry

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16533 Development of Portable Hybrid Renewable Energy System for Sustainable Electricity Supply to Rural Communities in Nigeria

Authors: Abdulkarim Nasir, Alhassan T. Yahaya, Hauwa T. Abdulkarim, Abdussalam El-Suleiman, Yakubu K. Abubakar

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The need for sustainable and reliable electricity supply in rural communities of Nigeria remains a pressing issue, given the country's vast energy deficit and the significant number of inhabitants lacking access to electricity. This research focuses on the development of a portable hybrid renewable energy system designed to provide a sustainable and efficient electricity supply to these underserved regions. The proposed system integrates multiple renewable energy sources, specifically solar and wind, to harness the abundant natural resources available in Nigeria. The design and development process involves the selection and optimization of components such as photovoltaic panels, wind turbines, energy storage units (batteries), and power management systems. These components are chosen based on their suitability for rural environments, cost-effectiveness, and ease of maintenance. The hybrid system is designed to be portable, allowing for easy transportation and deployment in remote locations with limited infrastructure. Key to the system's effectiveness is its hybrid nature, which ensures continuous power supply by compensating for the intermittent nature of individual renewable sources. Solar energy is harnessed during the day, while wind energy is captured whenever wind conditions are favourable, thus ensuring a more stable and reliable energy output. Energy storage units are critical in this setup, storing excess energy generated during peak production times and supplying power during periods of low renewable generation. These studies include assessing the solar irradiance, wind speed patterns, and energy consumption needs of rural communities. The simulation results inform the optimization of the system's design to maximize energy efficiency and reliability. This paper presents the development and evaluation of a 4 kW standalone hybrid system combining wind and solar power. The portable device measures approximately 8 feet 5 inches in width, 8 inches 4 inches in depth, and around 38 feet in height. It includes four solar panels with a capacity of 120 watts each, a 1.5 kW wind turbine, a solar charge controller, remote power storage, batteries, and battery control mechanisms. Designed to operate independently of the grid, this hybrid device offers versatility for use in highways and various other applications. It also presents a summary and characterization of the device, along with photovoltaic data collected in Nigeria during the month of April. The construction plan for the hybrid energy tower is outlined, which involves combining a vertical-axis wind turbine with solar panels to harness both wind and solar energy. Positioned between the roadway divider and automobiles, the tower takes advantage of the air velocity generated by passing vehicles. The solar panels are strategically mounted to deflect air toward the turbine while generating energy. Generators and gear systems attached to the turbine shaft enable power generation, offering a portable solution to energy challenges in Nigerian communities. The study also addresses the economic feasibility of the system, considering the initial investment costs, maintenance, and potential savings from reduced fossil fuel use. A comparative analysis with traditional energy supply methods highlights the long-term benefits and sustainability of the hybrid system.

Keywords: renewable energy, solar panel, wind turbine, hybrid system, generator

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16532 Evaluation of Regional Anaesthesia Practice in Plastic Surgery: A Retrospective Cross-Sectional Study

Authors: Samar Mousa, Ryan Kerstein, Mohanad Adam

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Regional anaesthesia has been associated with favourable outcomes in patients undergoing a wide range of surgeries. Beneficial effects have been demonstrated in terms of postoperative respiratory and cardiovascular endpoints, 7-day survival, time to ambulation and hospital discharge, and postoperative analgesia. Our project aimed at assessing the regional anaesthesia practice in the plastic surgery department of Buckinghamshire trust and finding out ways to improve the service in collaboration with the anaesthesia team. It is a retrospective study associated with a questionnaire filled out by plastic surgeons and anaesthetists to get the full picture behind the numbers. The study period was between 1/3/2022 and 23/5/2022 (12 weeks). The operative notes of all patients who had an operation under plastic surgery, whether emergency or elective, were reviewed. The criteria of suitable candidates for the regional block were put by the consultant anaesthetists as follows: age above 16, single surgical site (arm, forearm, leg, foot), no drug allergy, no pre-existing neuropathy, no bleeding disorders, not on ant-coagulation, no infection to the site of the block. For 12 weeks, 1061 operations were performed by plastic surgeons. Local cases were excluded leaving 319 cases. Of the 319, 102 patients were suitable candidates for regional block after applying the previously mentioned criteria. However, only seven patients had their operations under the regional block, and the rest had general anaesthesia that could have been easily avoided. An online questionnaire was filled out by both plastic surgeons and anaesthetists of different training levels to find out the reasons behind the obvious preference for general over regional anaesthesia, even if this was against the patients’ interest. The questionnaire included the following points: training level, time taken to give GA or RA, factors that influence the decision, percentage of RA candidates that had GA, reasons behind this percentage, recommendations. Forty-four clinicians filled out the questionnaire, among which were 23 plastic surgeons and 21 anaesthetists. As regards the training level, there were 21 consultants, 4 associate specialists, 9 registrars, and 10 senior house officers. The actual percentage of patients who were good candidates for RA but had GA instead is 93%. The replies estimated this percentage as between 10-30%. 29% of the respondents thought that this percentage is because of surgeons’ preference to have GA rather than RA for their operations without medical support for the decision. 37% of the replies thought that anaesthetists prefer giving GA even if the patient is a suitable candidate for RA. 22.6% of the replies thought that patients refused to have RA, and 11.3% had other causes. The recommendations were in 5 main accesses, which are protocols and pathways for regional blocks, more training opportunities for anaesthetists on regional blocks, providing a separate block room in the hospital, better communication between surgeons and anaesthetists, patient education about the benefits of regional blocks.

Keywords: regional anaesthesia, regional block, plastic surgery, general anaesthesia

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16531 Mode II Fracture Toughness of Hybrid Fiber Reinforced Concrete

Authors: H. S. S Abou El-Mal, A. S. Sherbini, H. E. M. Sallam

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Mode II fracture toughness (KIIc) of fiber reinforced concrete has been widely investigated under various patterns of testing geometries. The effect of fiber type, concrete matrix properties, and testing mechanisms were extensively studied. The area of hybrid fiber addition shows a lake of reported research data. In this paper an experimental investigation of hybrid fiber embedded in high strength concrete matrix is reported. Three different types of fibers; namely steel (S), glass (G), and polypropylene (PP) fibers were mixed together in four hybridization patterns, (S/G), (S/PP), (G/PP), (S/G/PP) with constant cumulative volume fraction (Vf) of 1.5%. The concrete matrix properties were kept the same for all hybrid fiber reinforced concrete patterns. In an attempt to estimate a fairly accepted value of fracture toughness KIIc, four testing geometries and loading types are employed in this investigation. Four point shear, Brazilian notched disc, double notched cube, and double edge notched specimens are investigated in a trial to avoid the limitations and sensitivity of each test regarding geometry, size effect, constraint condition, and the crack length to specimen width ratio a/w. The addition of all hybridization patterns of fiber reduced the compressive strength and increased mode II fracture toughness in pure mode II tests. Mode II fracture toughness of concrete KIIc decreased with the increment of a/w ratio for all concretes and test geometries. Mode II fracture toughness KIIc is found to be sensitive to the hybridization patterns of fiber. The (S/PP) hybridization pattern showed higher values than all other patterns, while the (S/G/PP) showed insignificant enhancement on mode II fracture toughness (KIIc). Four point shear (4PS) test set up reflects the most reliable values of mode II fracture toughness KIIc of concrete. Mode II fracture toughness KIIc of concrete couldn’t be assumed as a real material property.

Keywords: fiber reinforced concrete, Hybrid fiber, Mode II fracture toughness, testing geometry

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16530 Combining Nitrocarburisation and Dry Lubrication for Improving Component Lifetime

Authors: Kaushik Vaideeswaran, Jean Gobet, Patrick Margraf, Olha Sereda

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Nitrocarburisation is a surface hardening technique often applied to improve the wear resistance of steel surfaces. It is considered to be a promising solution in comparison with other processes such as flame spraying, owing to the formation of a diffusion layer which provides mechanical integrity, as well as its cost-effectiveness. To improve other tribological properties of the surface such as the coefficient of friction (COF), dry lubricants are utilized. Currently, the lifetime of steel components in many applications using either of these techniques individually are faced with the limitations of the two: high COF for nitrocarburized surfaces and low wear resistance of dry lubricant coatings. To this end, the current study involves the creation of a hybrid surface using the impregnation of a dry lubricant on to a nitrocarburized surface. The mechanical strength and hardness of Gerster SA’s nitrocarburized surfaces accompanied by the impregnation of the porous outermost layer with a solid lubricant will create a hybrid surface possessing both outstanding wear resistance and a low friction coefficient and with high adherence to the substrate. Gerster SA has the state-of-the-art technology for the surface hardening of various steels. Through their expertise in the field, the nitrocarburizing process parameters (atmosphere, temperature, dwelling time) were optimized to obtain samples that have a distinct porous structure (in terms of size, shape, and density) as observed by metallographic and microscopic analyses. The porosity thus obtained is suitable for the impregnation of a dry lubricant. A commercially available dry lubricant with a thermoplastic matrix was employed for the impregnation process, which was optimized to obtain a void-free interface with the surface of the nitrocarburized layer (henceforth called hybrid surface). In parallel, metallic samples without nitrocarburisation were also impregnated with the same dry lubricant as a reference (henceforth called reference surface). The reference and the nitrocarburized surfaces, with and without the dry lubricant were tested for their tribological behavior by sliding against a quenched steel ball using a nanotribometer. Without any lubricant, the nitrocarburized surface showed a wear rate 5x lower than the reference metal. In the presence of a thin film of dry lubricant ( < 2 micrometers) and under the application of high loads (500 mN or ~800 MPa), while the COF for the reference surface increased from ~0.1 to > 0.3 within 120 m, the hybrid surface retained a COF < 0.2 for over 400m of sliding. In addition, while the steel ball sliding against the reference surface showed heavy wear, the corresponding ball sliding against the hybrid surface showed very limited wear. Observations of the sliding tracks in the hybrid surface using Electron Microscopy show the presence of the nitrocarburized nodules as well as the lubricant, whereas no traces of the lubricant were found in the sliding track on the reference surface. In this manner, the clear advantage of combining nitrocarburisation with the impregnation of a dry lubricant towards forming a hybrid surface has been demonstrated.

Keywords: dry lubrication, hybrid surfaces, improved wear resistance, nitrocarburisation, steels

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16529 Reducing Hazardous Materials Releases from Railroad Freights through Dynamic Trip Plan Policy

Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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16528 The Access to the City in the Medellín Urban Experience

Authors: Mansilla, Juan Camilo

Abstract:

According to many studies, public space in the cities of Global South is constantly morcellated and captured by a multiplicity of actors in a permanent struggle for power. This imposed public space restricts the access to services and political actions to many inhabitants. The author has conducted several focus group sessions using video in a reflective mode with low-income communities in Medellín, Colombia in order to study how people in this city are shift from a physical public space to a hybrid public space shaped by internet. Beyond the fragmented city and the violent urban context manifested by participants, these activities have highlighted how the access to the city is currently going through a dialectic movement between the physical and the digital space. The purpose of this article is to make explicit the link between this hybrid public space and the boundaries of exclusion in the city. Urban marginality is closely related with the idea of access and space. Low-income communities in Medellín assume the digital realm like a “not controlled space” of resistance, where alternative ways of expression like hip hop movement, graffiti, dance, video and virtual communities produce effective changes in the physical realm.

Keywords: access to the city, hybrid public space, low-income communities, Medellín, urban marginality

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16527 High-Production Laser and Plasma Welding Technologies for High-Speed Vessels Production

Authors: V. M. Levshakov, N. A. Steshenkova, N. A. Nosyrev

Abstract:

Application of hulls processing technologies, based on high-concentrated energy sources (laser and plasma technologies), allow improve shipbuilding production. It is typical for high-speed vessels construction using steel and aluminum alloys with high precision hulls required. Report describes high-performance technologies for plasma welding (using direct current of reversed polarity), laser, and hybrid laser-arc welding of hulls structures developed by JSC “SSTC”.

Keywords: flat sections, hybrid laser-arc welding, plasma welding, plasmatron

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16526 Research of the Three-Dimensional Visualization Geological Modeling of Mine Based on Surpac

Authors: Honggang Qu, Yong Xu, Rongmei Liu, Zhenji Gao, Bin Wang

Abstract:

Today's mining industry is advancing gradually toward digital and visual direction. The three-dimensional visualization geological modeling of mine is the digital characterization of mineral deposits and is one of the key technology of digital mining. Three-dimensional geological modeling is a technology that combines geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in a three-dimensional environment with computer technology and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between the distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provides scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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16525 Parallelizing the Hybrid Pseudo-Spectral Time Domain/Finite Difference Time Domain Algorithms for the Large-Scale Electromagnetic Simulations Using Massage Passing Interface Library

Authors: Donggun Lee, Q-Han Park

Abstract:

Due to its coarse grid, the Pseudo-Spectral Time Domain (PSTD) method has advantages against the Finite Difference Time Domain (FDTD) method in terms of memory requirement and operation time. However, since the efficiency of parallelization is much lower than that of FDTD, PSTD is not a useful method for a large-scale electromagnetic simulation in a parallel platform. In this paper, we propose the parallelization technique of the hybrid PSTD-FDTD (HPF) method which simultaneously possesses the efficient parallelizability of FDTD and the quick speed and low memory requirement of PSTD. Parallelization cost of the HPF method is exactly the same as the parallel FDTD, but still, it occupies much less memory space and has faster operation speed than the parallel FDTD. Experiments in distributed memory systems have shown that the parallel HPF method saves up to 96% of the operation time and reduces 84% of the memory requirement. Also, by combining the OpenMP library to the MPI library, we further reduced the operation time of the parallel HPF method by 50%.

Keywords: FDTD, hybrid, MPI, OpenMP, PSTD, parallelization

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16524 Enhancing AI for Global Impact: Conversations on Improvement and Societal Benefits

Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

Abstract:

This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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16523 A Hybrid Multi-Objective Firefly-Sine Cosine Algorithm for Multi-Objective Optimization Problem

Authors: Gaohuizi Guo, Ning Zhang

Abstract:

Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.

Keywords: firefly algorithm, hybrid algorithm, multi-objective optimization, sine cosine algorithm

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16522 Development of Impressive Tensile Properties of Hybrid Rolled Ta0.5Nb0.5Hf0.5ZrTi1.5 Refractory High Entropy Alloy

Authors: M. Veeresham

Abstract:

The microstructure, texture, phase stability, and tensile properties of annealed Ta0.5Nb0.5Hf0.5ZrTi1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Keywords: refractory high entropy alloys, hybrid-rolling, recrystallization, microstructure, tensile properties

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16521 Functional Nanomaterials for Environmental Applications

Authors: S. A. M. Sabrina, Gouget Lammel, Anne Chantal, Chazalviel, Jean Noël, Ozanam François, Etcheberry Arnaud, Tighlit Fatma Zohra, B. Samia, Gabouze Noureddine

Abstract:

The elaboration and characterization of hybrid nano materials give rise to considerable interest due to the new properties that arising. They are considered as an important category of new materials having innovative characteristics by combining the specific intrinsic properties of inorganic compounds (semiconductors) with the grafted organic species. This open the way to improved properties and spectacular applications in various and important fields, especially in the environment. In this work, nano materials based-semiconductors were elaborated by chemical route. The obtained surfaces were grafted with organic functional groups. The functionalization process was optimized in order to confer to the hybrid nano material a good stability as well as the right properties required for the subsequent applications. Different characterization techniques were used to investigate the resulting nano structures, such as SEM, UV-Visible, FTIR, Contact angle and electro chemical measurements. Finally, applications were envisaged in environmental area. The elaborated nano structures were tested for the detection and the elimination of pollutants.

Keywords: hybrid materials, porous silicon, peptide, metal detection

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16520 Mechanical Properties of Carbon Fibre Reinforced Thermoplastic Composites Consisting of Recycled Carbon Fibres and Polyamide 6 Fibres

Authors: Mir Mohammad Badrul Hasan, Anwar Abdkader, Chokri Cherif

Abstract:

With the increasing demand and use of carbon fibre reinforced composites (CFRC), disposal of the carbon fibres (CF) and end of life composite parts is gaining tremendous importance on the issue especially of sustainability. Furthermore, a number of processes (e. g. pyrolysis, solvolysis, etc.) are available currently to obtain recycled CF (rCF) from end-of-life CFRC. Since the CF waste or rCF are neither allowed to be thermally degraded nor landfilled (EU Directive 1999/31/EC), profitable recycling and re-use concepts are urgently necessary. Currently, the market for materials based on rCF mainly consists of random mats (nonwoven) made from short fibres. The strengths of composites that can be achieved from injection-molded components and from nonwovens are between 200-404 MPa and are characterized by low performance and suitable for non-structural applications such as in aircraft and vehicle interiors. On the contrary, spinning rCF to yarn constructions offers good potential for higher CFRC material properties due to high fibre orientation and compaction of rCF. However, no investigation is reported till yet on the direct comparison of the mechanical properties of thermoplastic CFRC manufactured from virgin CF filament yarn and spun yarns from staple rCF. There is a lack of understanding on the level of performance of the composites that can be achieved from hybrid yarns consisting of rCF and PA6 fibres. In this drop back, extensive research works are being carried out at the Textile Machinery and High-Performance Material Technology (ITM) on the development of new thermoplastic CFRC from hybrid yarns consisting of rCF. For this purpose, a process chain is developed at the ITM starting from fibre preparation to hybrid yarns manufacturing consisting of staple rCF by mixing with thermoplastic fibres. The objective is to apply such hybrid yarns for the manufacturing of load bearing textile reinforced thermoplastic CFRCs. In this paper, the development of innovative multi-component core-sheath hybrid yarn structures consisting of staple rCF and polyamide 6 (PA 6) on a DREF-3000 friction spinning machine is reported. Furthermore, Unidirectional (UD) CFRCs are manufactured from the developed hybrid yarns, and the mechanical properties of the composites such as tensile and flexural properties are analyzed. The results show that the UD composite manufactured from the developed hybrid yarns consisting of staple rCF possesses approximately 80% of the tensile strength and E-module to those produced from virgin CF filament yarn. The results show a huge potential of the DREF-3000 friction spinning process to develop composites from rCF for high-performance applications.

Keywords: recycled carbon fibres, hybrid yarn, friction spinning, thermoplastic composite

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16519 Intrusion Detection in Computer Networks Using a Hybrid Model of Firefly and Differential Evolution Algorithms

Authors: Mohammad Besharatloo

Abstract:

Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

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