Search results for: separately excited synchronous machine

Authors: Ibrahim Nasiru Dole, Audu Abdullahi, Dike Michiel Chidozie, Lawal Mansur

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Bambara groundnut is an important grain legume and the seeds in storage suffer infestation by Callosobruchus subinnotatus. Laboratory study was conducted to evaluate the efficacy of raw diatomaceous earth (RDE) and plant powders (Jatropha curcas (L.), Eucalyptus camaldulensis (Dehnh.) and Melia azedarach (L.) against C. subinnotatus infesting stored bambara groundnut seeds. Rearing of the insects and the experiments were conducted in Agricultural Biology Laboratory of the Usmanu Danfodiyo University, Sokoto - Nigeria under ambient conditions (29-33oC and a relative humidity of 44-56%). Four treatments at three levels: RDE at 0.5, 1.0 and 1.5 g while plant powders at 0.5, 1.0 and 2.0 g, standard/check (2.0 g of Actellic dust), and a control. These were separately admixed with 100 g of sterilized seeds in glass jars. Each jar was later infested with thirty, 1-2-days old C. subinnotatus of mixed sexes. Adult mortality was assessed 24, 48, 72 and 96 hours, F1 and F2 progenies, seed damage, weight loss and viability were also assessed after 90 days. Eighty-nine (89%) percent adult mortality was recorded in the highest dose of RDE after 96 hours of exposure. These treatments significantly (P < 0.05) suppressed F1 and F2 progenies emergence in relation to the control. The control suffered significantly (P < 0.05) higher seed damage (51.0 %) and weight loss (40.8%) thereby recording lower seed germination. Therefore, RDE and plant powders could be used against C. subinnotatus on stored bambara groundnut seeds.

Keywords: bambara, callosobruchus subinnotatus, plant powders, raw diatomaceous earth,

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Authors: Mouna Essaadi, Mohamed Khafallah, Abdallah Saad, Hamid Chaikhy

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This paper presents a comparative analysis between conventional direct torque control (C_DTC), Modified direct torque control (M_DTC) and twelve sectors direct torque control (12_DTC).Those different strategies are compared by simulation in term of torque, flux and stator current performances. Finally, a summary of the comparative analysis is presented.

Keywords: C_DTC, M_DTC, 12_DTC, torque dynamic, stator current, flux, performances

Procedia PDF Downloads 601

Authors: Emrah Yaliniz, Ali Kalkanli

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ZE41A magnesium alloy has been extensively used in aerospace industry, especially for use in rotorcraft transmission casings. Due to the improved mechanical properties, the latest generation of magnesium casting alloy EV31A-T6 (Elektron 21® specified in AMS 4429) is seen as a potential replacement for ZE41A in terms of strength. Therefore, the necessity of enhancement has been arisen for ZE41A in order to avoid fully replacement. The main element affecting the strength of ZE41A is Zirconium (Zr), which acts as a grain refiner. The specified range of Zr element for ZE41A alloy is between 0.4 wt % and 1.0 wt % (unless otherwise stated by weight percentage after this point) as stated in AMS 4439. This paper investigates the effects of Zr amount on tensile and metallurgical properties of ZE41A magnesium alloy. The Zr alloying amount for the research has been chosen as 0.5 % and 1 %, which are standard amounts in a commercial alloy (average of 0.4-0.6%) and maximum percent in the standard, separately. 1 % Zr amount has been achieved via Zirmax (66.7 Mg-33.3 Zr) master alloy addition. The ultimate tensile strength of ZE41A with 1% Zr has been increased up to about 220-225 MPa in comparison to 200 MPa given in AMS 4439. The reason for the increase in strength with the addition of Zirmax is based on the decrease in grain size, which was measured about 30 µm. Optical microscope, scanning electron microscopy (SEM) and X-ray Diffraction (XRD) were used to detect the change in the microstructural futures via alloying. The zirconium rich coring at the center of the grains was observed in addition to the grain boundary intermetallic phases and bulk Mg-rich matrix. The solidification characteristics were also identified by using the cooling curve obtained from the sand casting mold during cooling of the alloys.

Keywords: aerospace, grain refinement, magnesium, sand casting, ZE41A

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

Procedia PDF Downloads 223

Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

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Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

Procedia PDF Downloads 61

Authors: Tim Bolle, Franziska Kreimendahl, Thomas Gries, Stefan Jockenhoevel

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The therapeutic treatment of extensive, deep wounds is limited. Autologous split-skin grafts are used as a so-called ‘gold standard’. Most common deficits are the defects at the donor site, the risk of scarring as well as the limited availability and quality of the autologous grafts. The aim of this project is a tissue engineered dermal-epidermal skin replacement to overcome the limitations of the gold standard. A key requirement for the development of such a three-dimensional implant is the formation of a functional capillary-like network inside the implant to ensure a sufficient nutrient and gas supply. Tailored three-dimensional warp knitted spacer fabrics are used to reinforce the mechanically week fibrin gel-based scaffold and further to create a directed in vitro pre-vascularization along the parallel-oriented pile yarns within a co-culture. In this study various three-dimensional warp knitted spacer fabrics were developed in a factorial design to analyze the influence of the machine parameters such as the stitch density and the pattern of the fabric on the scaffold performance and further to determine suitable parameters for a successful fibrin gel-incorporation and a physiological performance of the scaffold. The fabrics were manufactured on a Karl Mayer double-bar raschel machine DR 16 EEC/EAC. A fine machine gauge of E30 was used to ensure a high pile yarn density for sufficient nutrient, gas and waste exchange. In order to ensure a high mechanical stability of the graft, the fabrics were made of biocompatible PVDF yarns. Key parameters such as the pore size, porosity and stress/strain behavior were investigated under standardized, controlled climate conditions. The influence of the input parameters on the mechanical and morphological properties as well as the ability of fibrin gel incorporation into the spacer fabric was analyzed. Subsequently, the pile yarns of the spacer fabrics were colonized with Human Umbilical Vein Endothelial Cells (HUVEC) to analyze the ability of the fabric to further function as a guiding structure for a directed vascularization. The cells were stained with DAPI and investigated using fluorescence microscopy. The analysis revealed that the stitch density and the binding pattern have a strong influence on both the mechanical and morphological properties of the fabric. As expected, the incorporation of the fibrin gel was significantly improved with higher pore sizes and porosities, whereas the mechanical strength decreases. Furthermore, the colonization trials revealed a high cell distribution and density on the pile yarns of the spacer fabrics. For a tailored reinforcing structure, the minimum porosity and pore size needs to be evaluated which still ensures a complete incorporation of the reinforcing structure into the fibrin gel matrix. That will enable a mechanically stable dermal graft with a dense vascular network for a sufficient nutrient and oxygen supply of the cells. The results are promising for subsequent research in the field of reinforcing mechanically weak biological scaffolds and develop functional three-dimensional scaffolds with an oriented pre-vascularization.

Keywords: fibrin-gel, skin replacement, spacer fabric, pre-vascularization

Procedia PDF Downloads 242

Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

Procedia PDF Downloads 134

Authors: Hyeuk Ju Ko, Eui Ju Lee

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Many electronic devices are powered by various rechargeable batteries such as lithium-ion today, but occasionally the batteries undergo thermal runaway and cause fire, explosion, and other hazards. If a battery fire should occur in an electronic device of vehicle and aircraft cabin, it is important to quickly extinguish the fire and cool the batteries to minimize safety risks. Attempts to minimize these risks have been carried out by many researchers but the number of study on the successful extinguishment is limited. Because most rechargeable batteries are operated on the ion state with electron during charge and discharge of electricity, and the reaction of this electrolyte has a big difference with normal combustion. Here, we focused on the effect of ions on reaction stability and pollutant emissions during combustion process. The other importance for understanding ionized fuel combustion could be found in high efficient and environment-friendly combustion technologies, which are used to be operated an extreme condition and hence results in unintended flame instability such as extinction and oscillation. The use of electromagnetic energy and non-equilibrium plasma is one of the way to solve the problems, but the application has been still limited because of lack of excited ion effects in the combustion process. Therefore, the understanding of ion role during combustion might be promised to the energy safety society including the battery safety. In this study, the effects of an ionized fuel on the flame stability and pollutant emissions were experimentally investigated in the hydrocarbon jet diffusion flames. The burner used in this experiment consisted of 7.5 mm diameter tube for fuel and the gaseous fuels were ionized with the ionizer (SUNJE, SPN-11). Methane (99.9% purity) and propane (commercial grade) were used as a fuel and open ambient air was used as an oxidizer. As the performance of ionizer used in the experiment was evaluated at first, ion densities of both propane and methane increased linearly with volume flow rate but the ion density of propane is slightly higher than that of methane. The results show that the overall flame stability and shape such as flame length has no significant difference even in the higher ion concentration. However, the fuel ionization affects to the pollutant emissions such as NOx and soot. NOx and CO emissions measured in post flame region decreased with increasing fuel ionization, especially at high fuel velocity, i.e. high ion density. TGA analysis and morphology of soot by TEM indicates that the fuel ionization makes soot to be matured.

Keywords: battery fires, ionization, jet flames, stability, NOx and soot

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Authors: Tamara Grujic, Mirjana Bonkovic

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Measurements and quantitative analysis of kinematic parameters of human hand movements have an important role in different areas such as hand function rehabilitation, modeling of multi-digits robotic hands, and the development of machine-man interfaces. In this paper the assessment and evaluation of the reach-to-grasp movement by using computerized and robot-assisted method is described. Experiment involved the measurements of hand positions of seven healthy subjects during grasping three objects of different shapes and sizes. Results showed that three dominant phases of reach-to-grasp movements could be clearly identified.

Keywords: human hand, kinematics, measurement and analysis, reach-to-grasp movement

Procedia PDF Downloads 452

Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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The increase in the demand for precision optics, coupled with the absence of much research output in the ultra high precision grinding of precision optics as compared to the ultrahigh precision diamond turning of optical metals has fostered the need for more research in the ultra high precision grinding of an optical lens. Furthermore, the increase in the stringent demands for nanometric surface finishes through lapping, polishing and grinding processes necessary for the use of borosilicate-crown glass in the automotive and optics industries has created the demand to effectively monitor the surface roughness during the production process. Acoustic emission phenomenon has been proven as useful monitoring technique in several manufacturing processes ranging from monitoring of bearing production to tool wear estimation. This paper introduces a rare and unique approach with the application of acoustic emission technique to monitor the surface roughness of borosilicate-crown glass during an ultra high precision grinding process. This research was carried out on a 4-axes Nanoform 250 ultrahigh precision lathe machine using an ultra high precision grinding spindle to machine the flat surface of the borosilicate-crown glass with the tip of the grinding wheel. A careful selection of parameters and design of experiment was implemented using Box-Behnken method to vary the wheel speed, feed rate and depth of cut at three levels with a 3-center point design. Furthermore, the average surface roughness was measured using Taylor Hobson PGI Dimension XL optical profilometer, and an acoustic emission data acquisition device from National Instruments was utilized to acquire the signals while the data acquisition codes were designed with National Instrument LabVIEW software for acquisition at a sampling rate of 2 million samples per second. The results show that the raw and root mean square amplitude values of the acoustic signals increased with a corresponding increase in the measured average surface roughness values for the different parameter combinations. Therefore, this research concludes that acoustic emission monitoring technique is a potential technique for monitoring the surface roughness in the ultra high precision grinding of borosilicate-crown glass.

Keywords: acoustic emission, borosilicate-crown glass, surface roughness, ultra high precision grinding

Procedia PDF Downloads 282

Authors: Soumya Kedia, Puja Agarwala, Mahesh Tirumkudulu

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Linear stability analysis is performed for a radially expanding liquid sheet in the presence of a gas medium. A liquid sheet can break up because of the aerodynamic effect as well as its thinning. However, the study of the aforementioned effects is usually done separately as the formulation becomes complicated and is difficult to solve. Present work combines both, aerodynamic effect and thinning effect, ignoring the non-linearity in the system. This is done by taking into account the formation of the gas boundary layer whilst neglecting viscosity in the liquid phase. Axisymmetric flow is assumed for simplicity. Base state analysis results in a Blasius-type system which can be solved numerically. Perturbation theory is then applied to study the stability of the liquid sheet, where the gas-liquid interface is subjected to small deformations. The linear model derived here can be applied to investigate the instability for sinuous as well as varicose modes, where the former represents displacement in the centerline of the sheet and the latter represents modulation in sheet thickness. Temporal instability analysis is performed for sinuous modes, which are significantly more unstable than varicose modes, for a fixed radial distance implying local stability analysis. The growth rates, measured for fixed wavenumbers, predicated by the present model are significantly lower than those obtained by the inviscid Kelvin-Helmholtz instability and compare better with experimental results. Thus, the present theory gives better insight into understanding the stability of a thin liquid sheet.

Keywords: boundary layer, gas-liquid interface, linear stability, thin liquid sheet

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in diverse domains has created an urgent need for effective utilization of mathematical and statistical sciences in data analytics. This abstract explores the journey from theory to practice, emphasizing the importance of harnessing mathematical and statistical innovations to unlock the full potential of data analytics. Drawing on a comprehensive review of existing literature and research, this study investigates the fundamental theories and principles underpinning mathematical and statistical sciences in the context of data analytics. It delves into key mathematical concepts such as optimization, probability theory, statistical modeling, and machine learning algorithms, highlighting their significance in analyzing and extracting insights from complex datasets. Moreover, this abstract sheds light on the practical applications of mathematical and statistical sciences in real-world data analytics scenarios. Through case studies and examples, it showcases how mathematical and statistical innovations are being applied to tackle challenges in various fields such as finance, healthcare, marketing, and social sciences. These applications demonstrate the transformative power of mathematical and statistical sciences in data-driven decision-making. The abstract also emphasizes the importance of interdisciplinary collaboration, as it recognizes the synergy between mathematical and statistical sciences and other domains such as computer science, information technology, and domain-specific knowledge. Collaborative efforts enable the development of innovative methodologies and tools that bridge the gap between theory and practice, ultimately enhancing the effectiveness of data analytics. Furthermore, ethical considerations surrounding data analytics, including privacy, bias, and fairness, are addressed within the abstract. It underscores the need for responsible and transparent practices in data analytics, and highlights the role of mathematical and statistical sciences in ensuring ethical data handling and analysis. In conclusion, this abstract highlights the journey from theory to practice in harnessing mathematical and statistical sciences in data analytics. It showcases the practical applications of these sciences, the importance of interdisciplinary collaboration, and the need for ethical considerations. By bridging the gap between theory and practice, mathematical and statistical sciences contribute to unlocking the full potential of data analytics, empowering organizations and decision-makers with valuable insights for informed decision-making.

Keywords: data analytics, mathematical sciences, optimization, machine learning, interdisciplinary collaboration, practical applications

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Authors: Saeid Jalilzadeh

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Designing of PSS and SVC controller based on Bacterial Foraging Algorithm (BFA) to improve the stability of power system is proposed in this paper. Same controllers for PSS and SVC has been considered and Single machine infinite bus (SMIB) system with SVC located at the terminal of generator is used to evaluate the proposed controllers. BFA is used to optimize the coefficients of the controllers. Finally simulation for a special disturbance as an input power of generator with the proposed controllers in order to investigate the dynamic behavior of generator is done. The simulation results demonstrate that the system composed with optimized controllers has an outstanding operation in fast damping of oscillations of power system.

Keywords: PSS, SVC, SMIB, optimize controller

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Authors: Sontana Mimapan, Phattarawadee Wattanasuntorn, Phanom Saijit

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Aflatoxin contamination in maize, one of several agriculture crops grown for livestock feeding, is still a problem throughout the world mainly under hot and humid weather conditions like Thailand. In this study Aspergillus flavus (A. Flavus), the key fungus for aflatoxin production especially aflatoxin B1 (AFB1), isolated from naturally infected maize were identified and characterized according to colony morphology and PCR using ITS, Beta-tubulin and calmodulin genes. The strains were analysed for the presence of four aflatoxigenic biosynthesis genes in relation to their capability to produce AFB1, Ver1, Omt1, Nor1, and aflR. Aflatoxin production was then confirmed using immunoaffinity column technique. A loop-mediated isothermal amplification (LAMP) was applied as an innovative technique for rapid detection of target nucleic acid. The reaction condition was optimized at 65C for 60 min. and calcein flurescent reagent was added before amplification. The LAMP results showed clear differences between positive and negative reactions in end point analysis under daylight and UV light by the naked eye. In daylight, the samples with AFB1 producing A. Flavus genes developed a yellow to green color, but those without the genes retained the orange color. When excited with UV light, the positive samples become visible by bright green fluorescence. LAMP reactions were positive after addition of purified target DNA until dilutions of 10⁻⁶. The reaction products were then confirmed and visualized with 1% agarose gel electrophoresis. In this regards, 50 maize samples were collected from dairy farms and tested for the presence of four aflatoxigenic biosynthesis genes using LAMP technique. The results were positive in 18 samples (36%) but negative in 32 samples (64%). All of the samples were rechecked by PCR and the results were the same as LAMP, indicating 100% specificity. Additionally, when compared with the immunoaffinity column-based aflatoxin analysis, there was a significant correlation between LAMP results and aflatoxin analysis (r= 0.83, P < 0.05) which suggested that positive maize samples were likely to be a high- risk feed. In conclusion, the LAMP developed in this study can provide a simple and rapid approach for detecting AFB1 producing A. Flavus genes from maize and appeared to be a promising tool for the prediction of potential aflatoxigenic risk in livestock feedings.

Keywords: Aflatoxin B1, Aspergillus flavus genes, maize, loop-mediated isothermal amplification

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Authors: Nilki Upathissa, Torin Wirasinghe

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This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

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Authors: Frank Fan

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PharmD (Doctor of Pharmacy) education has confronted an increasing challenge — curricular overload, a phenomenon resulting from the expansion of curricular requirements, as PharmD education strives to produce graduates who are practice-ready. The aftermath of the global pandemic has amplified the need for healthcare professionals, leading to a growing trend of assigning more responsibilities to them to address the global healthcare shortage. For instance, the pharmacist’s role has expanded to include not only compounding and distributing medication but also providing clinical services, including minor ailments management, patient counselling and vaccination. Consequently, PharmD programs have responded by continually expanding their curricula adding more requirements. While these changes aim to enhance the education and training of future professionals, they have also led to unintended consequences, including curricular overload, student burnout, and a potential decrease in program quality. To address the issue and ensure program quality, there is a growing need for evidence-based curriculum reforms. My research seeks to integrate Cognitive Load Theory, emerging machine learning algorithms within artificial intelligence (AI), and statistical approaches to develop a quantitative framework for optimizing curriculum design within the PharmD program at the University of Toronto, the largest PharmD program within Canada, to provide quantification and measurement of issues that currently are only discussed in terms of anecdote rather than data. This research will serve as a guide for curriculum planners, administrators, and educators, aiding in the comprehension of how the pharmacy degree program compares to others within and beyond the field of pharmacy. It will also shed light on opportunities to reduce the curricular load while maintaining its quality and rigor. Given that pharmacists constitute the third-largest healthcare workforce, their education shares similarities and challenges with other health education programs. Therefore, my evidence-based, data-driven curriculum analysis framework holds significant potential for training programs in other healthcare professions, including medicine, nursing, and physiotherapy.

Keywords: curriculum, curriculum analysis, health professions education, reflective writing, machine learning

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Authors: G. W. Greubel, A. Kalam

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South Africa finds itself at a confluence of forces where the national electricity supply system is constrained with under-supply primarily from old and failing coal-fired power stations and congested and inadequate transmission and distribution systems. Simultaneously the country attempts to meet carbon reduction targets driven by both an alignment with international goals and a consumer-driven requirement. The constrained electricity system is an aspect of an economy characterized by very low economic growth, high unemployment, and frequent and significant load shedding. The fiscus does not have the funding to build new generation capacity or strengthen the grid. The under-supply is increasingly alleviated by the penetration of wind and solar generation capacity and embedded roof-top solar. However, this increased penetration results in less inertia, less synchronous generation, and less capability for fast frequency response, with resultant instability. The renewable energy facilities assist in solving the under-supply issues, but merely ‘kick the can down the road’ by not contributing to grid stability or by substituting the lost inertia, thus creating an expanding issue for the grid to manage. By technically balancing its electricity demand and supply a company with facilities located across the country can be spared the effects of load shedding, and thus ensure financial and production performance, protect jobs, and contribute meaningfully to the economy. By treating the company’s load (across the country) and its various distributed generation facilities as a ‘virtual grid’ which by design will provide ancillary services to the grid one is able to create a win-win situation for both the company and the grid. This paper provides a review of the technical problems facing the South African electricity system and discusses a hypothetical ‘virtual grid’ concept that may assist in solving the problems. The proposed solution has potential application across emerging markets with constrained power infrastructure or for companies who wish to be entirely powered by renewable energy.

Keywords: load shedding, renewable energy integration, smart grid, virtual grid

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: H. El-Messiry, M. El-Zainy, D. Abdelkhalek

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Cone-beam computed tomography (CBCT) provides high-quality 3-dimensional images of dental structures because of its high spatial resolution. The study of dental morphology is important in research as it provides information about diversities within a population. Many studies have shown different shapes and numbers of roots canals among different races, especially in molars. The aim of this study was to determine the morphology of root canals of mandibular first and third molars in a sample of Egyptian population using CBCT scanning. Fifty mandibular first Molars (M1) and fifty mandibular third (M3) extracted molars were collected. Thick rectangular molds were made using pink wax to hold the samples. Molars were embedded in the wax mold by aligning them in rows leaving arbitrary 0.5cm space between them. The molds with the samples in were submitted for CBCT scan. The number and morphology of root canals were assessed and classified according to Vertucci's classification. The mesial and the distal roots were examined separately. Finally, data was analyzed using Fisher exact test. The most prevalent mesial root canal frequency in M1 was type IV (60%) and type II (40 %), while M3 showed prevalence of type I (40%) and II (40%). Distal root canal morphology showed prevalence of type I in both M1 (66%) and M3 (86%). So, it can be concluded that CBCT scanning provides supplemental information about the root canal configurations of mandibular molars in a sample of Egyptian population. This study may help clinicians in the root canal treatment of mandibular molars.

Keywords: cone beam computed tomography, mandibular first molar, mandibular third molar, root canal morphology

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Authors: Edward Chamisa, Colin C. Smith, Hamutyinei H. Pamburai, Abdul C. Abdulla

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South Africa (SA) adopted International Financial Reporting Standards (IFRS) for listed firms effective 1 January 2005. However, it was not until 2011 that substantial financial reporting enforcement changes were introduced, which were meant to ensure compliance with IFRS. This innovative setting allows us to examine the value relevance of accounting amounts during the (1) pre-IFRS adoption period (2002-2004); (2) post-IFRS adoption, but pre-enforcement changes period (2006-2010); and (3) post-enforcement changes period (2011-2012). The results show that accounting amounts were most value relevant in the post-enforcement changes period (R2, 75.5%) compared to both the pre-IFRS adoption period (adjusted R2 is 24.3%) and the period after IFRS adoption but before enforcement changes (adjusted R2 is 37.5%). Also, during the 2008 financial crisis, the equity book value per share was significantly value relevant (at 1%) but not earnings per share, whereas before the crisis, the opposite was true. We make two important contributions to the literature. First, we identify SA as an innovative setting that allows researchers to examine separately the effects of IFRS adoption and enforcement changes on capital markets and accounting quality. This is a departure from prior studies that are dominated by the European Union setting, where IFRS adoption occurred contemporaneously with enforcement and other regulatory changes. Second, we provide preliminary findings which suggest that while the adoption of IFRS seems to have improved the financial reporting quality of accounting amounts of SA listed firms, its impact appears to be limited unless combined with effective enforcement.

Keywords: international financial reporting standards (ifrs), ifrs adoption, financial reporting enforcement, value relevance, price model, equity book value, earnings per share

Procedia PDF Downloads 55

Authors: Guang Zou, Kian Banisoleiman, Arturo González

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Crack initiation and propagation threatens structural integrity of welded joints and normally inspections are assigned based on crack propagation models. However, the approach based on crack propagation models may not be applicable for some high-quality welded joints, because the initial flaws in them may be so small that it may take long time for the flaws to develop into a detectable size. This raises a concern regarding the inspection planning of high-quality welded joins, as there is no generally acceptable approach for modeling the whole fatigue process that includes the crack initiation period. In order to address the issue, this paper reviews treatment methods for crack initiation period and initial crack size in crack propagation models applied to inspection planning. Generally, there are four approaches, by: 1) Neglecting the crack initiation period and fitting a probabilistic distribution for initial crack size based on statistical data; 2) Extrapolating the crack propagation stage to a very small fictitious initial crack size, so that the whole fatigue process can be modeled by crack propagation models; 3) Assuming a fixed detectable initial crack size and fitting a probabilistic distribution for crack initiation time based on specimen tests; and, 4) Modeling the crack initiation and propagation stage separately using small crack growth theories and Paris law or similar models. The conclusion is that in view of trade-off between accuracy and computation efforts, calibration of a small fictitious initial crack size to S-N curves is the most efficient approach.

Keywords: crack initiation, fatigue reliability, inspection planning, welded joints

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Authors: Bernstein Ran, Shafir Tal, Tsachor Rachelle, Studd Karen, Schuster Assaf

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Laban Movement Analysis (LMA), developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Many applications that use motion capture data might be significantly leveraged if the Laban qualities will be recognized automatically. This paper presents an automated recognition method of Laban qualities from motion capture skeletal recordings and it is demonstrated on the output of Microsoft’s Kinect V2 sensor.

Keywords: Laban movement analysis, multitask learning, Kinect sensor, machine learning

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Authors: Broccolo Cinzia, Grigaliunaite Ruta, Saint-Nom Cloé, Savasta Guido

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The present article analyses the root causes of under-reporting and under-recording of hate crimes against Muslim women in Italy. The main findings emerged from the survey conducted between May and September 2022 within the framework of the TRUST project (co-funded by the CERV programme (CERV-2021-EQUAL) of the European Union) with relevant practitioners and members of the Muslim community, including first-generation and second-generation Muslim women residing in Italy. The findings reveal that multiple factors contribute to the low reporting rate as well as to the flaws in recording episodes of intolerance and hatred against the above-mentioned group. Lack of trust in the judiciary or the police may represent one of the main causes of under-reporting; however, the phenomenon is not limited to such aspects, and additional factors and sources of discrimination paving the way to under-recording have been identified during the survey. The significant “tendency” to not report a case of intolerance as the difficulties in identifying the discriminatory nature of the crime are two faces of the same coin and are particularly intertwined; despite this, at first, both issues need to be assessed and analysed separately in order to take their own specificities into duly consideration. By contrast, the potential solution to low recording and reporting trends should be found collectively, namely by involving all the relevant parties and bodies facing the above-mentioned issues. In this regard, a participatory and multi-agency approach may curb the root causes leading Muslim women not to report and, besides this, support law enforcement officials as well as public authorities in providing a more effective service to the victims of hatred, whether offline or online.

Keywords: hate crime, under-reporting, under-recording, Islamophobia, Muslim women

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Authors: Evren Isen

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In grid-connected renewable energy systems, input power is controlled by AC/DC converter or/and DC/DC converter depending on output voltage of input source. The power is injected to DC-link, and DC-link voltage is regulated by inverter controlling the grid current. Inverter performance is considerable in grid-connected renewable energy systems to meet the utility standards. In this paper, modelling and simulation of hysteresis current controlled single-phase grid-connected inverter that is utilized in renewable energy systems, such as wind and solar systems, are presented. 2 kW single-phase grid-connected inverter is simulated in Simulink and modeled in Matlab-m-file. The grid current synchronization is obtained by phase locked loop (PLL) technique in dq synchronous rotating frame. Although dq-PLL can be easily implemented in three-phase systems, there is difficulty to generate β component of grid voltage in single-phase system because single-phase grid voltage exists. Inverse-Park PLL with low-pass filter is used to generate β component for grid angle determination. As grid current is controlled by constant bandwidth hysteresis current control (HCC) technique, average switching frequency and variation of switching frequency in a fundamental period are considered. 3.56% total harmonic distortion value of grid current is achieved with 0.5 A bandwidth. Average value of switching frequency and total harmonic distortion curves for different hysteresis bandwidth are obtained from model in m-file. Average switching frequency is 25.6 kHz while switching frequency varies between 14 kHz-38 kHz in a fundamental period. The average and maximum frequency difference should be considered for selection of solid state switching device, and designing driver circuit. Steady-state and dynamic response performances of the inverter depending on the input power are presented with waveforms. The control algorithm regulates the DC-link voltage by adjusting the output power.

Keywords: grid-connected inverter, hysteresis current control, inverter modelling, single-phase inverter

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Authors: Diwei Lin, Amanda Tan, Rajinder Singh-Rai

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We present the first reported case of a concomitant Leydig cell tumor (LCT) and paratesticular leiomyoma in an adult male with a known history of bilateral cryptorchidism. An 80-year-old male presented with a 2-month history of a left testicular lump associated with mild discomfort and a gradual increase in size on a background of bilateral cryptorchidism requiring multiple orchidopexy procedures as a child. Ultrasound confirmed a lesion suspicious for malignancy and he proceeded to a left radical orchidectomy. Histopathological assessment of the left testis revealed a concomitant testicular LCT with malignant features and paratesticular leiomyoma. Leydig cell tumors (LCTs) are the most common pure testicular sex cord-stromal tumors, accounting for up to 3% of all testicular tumors. They can occur at almost any age, but are noted to have a bi-modal distribution, with a peak incidence at 6 to 10 and at 20 to 50 years of age. LCT’s are often hormonally active and can lead to feminizing or virilizing syndromes. LCT’s are usually regarded as benign but can rarely exhibit malignant traits. Paratesticular tumours are uncommon and their reported prevalence varies between 3% and 16%. They occur in a complex anatomical area which includes the contents of the spermatic cord, testicular tunics, epididymis and vestigial remnants. Up to 90% of paratesticular tumours are believed to originate from the spermatic cord, though it is often difficult to definitively ascertain the exact site of origin. Although any type of soft-tissue neoplasm can be found in the paratesticular region, the most common benign tumors reported are lipomas of the spermatic cord, adenomatoid tumours of the epididymis and leiomyomas of the testis. Genetic studies have identified potential mutations that could potentially cause LCTs, but there are no known associations between concomitant LCTs and paratesticular tumors. The presence of cryptorchidism in adults with both LCTs and paratesticular neoplasms individually has been previously reported and it appears intuitive that cryptorchidism is likely to be associated with the concomitant presentation in this case report. This report represents the first documented case in the literature of a unilateral concomitant LCT and paratesticular leiomyoma on a background of bilateral cryptorchidism.

Keywords: testicular cancer, leydig cell tumour, leiomyoma, paratesticular neoplasms

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Authors: Yahoel Van Essen, Gordon Ho, Brett Russell, Hans-Georg Worms, Xiao Lin Long, Edward David Cooper, Avner Bachar

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Weeds reduce farm and forest productivity, invade crops, smother pastures and some can harm livestock. Farmers need to spend a significant amount of money to control weeds by means of biological, chemical, cultural, and physical methods. To solve the global agricultural labor shortage and remove poisonous chemicals, a fully autonomous, eco-friendly, and sustainable weeding technology is developed. This takes the form of a weeding robot, ‘Roboweeder’. Roboweeder includes a four-wheel-drive self-driving vehicle, a 4-DOF robotic arm which is mounted on top of the vehicle, an electromagnetic wave generator (magnetron) which is mounted on the “wrist” of the robotic arm, 48V battery packs, and a control/communication system. Cameras are mounted on the front and two sides of the vehicle. Using image processing and recognition, distinguish types of weeds are detected before being eliminated. The electromagnetic wave technology is applied to heat the individual weeds and clusters dielectrically causing them to wilt and die. The 4-DOF robotic arm was modeled mathematically based on its structure/mechanics, each joint’s load, brushless DC motor and worm gear’ characteristics, forward kinematics, and inverse kinematics. The Proportional-Integral-Differential control algorithm is used to control the robotic arm’s motion to ensure the waveguide aperture pointing to the detected weeds. GPS and machine vision are used to traverse the farm and avoid obstacles without the need of supervision. A Roboweeder prototype has been built. Multiple test trials show that Roboweeder is able to detect, point, and kill the pre-defined weeds successfully although further improvements are needed, such as reducing the “weeds killing” time and developing a new waveguide with a smaller waveguide aperture to avoid killing crops surrounded. This technology changes the tedious, time consuming and expensive weeding processes, and allows farmers to grow more, go organic, and eliminate operational headaches. A patent of this technology is pending.

Keywords: autonomous navigation, machine vision, precision heating, sustainable and eco-friendly

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Authors: Samir Lecheb, Ahmed Chellil, Hamza Mechakra, Brahim Safi, Houcine Kebir

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In this paper we studied fracture and dynamic behavior of vertical axis wind turbine blade, the VAWT is a historical machine, it has many properties, structure, advantage, component to be able to produce the electricity. We modeled the blade design then imported to Abaqus software for analysis the modes shapes, frequencies, stress, strain, displacement and stress intensity factor SIF, after comparison we chose the idol material. Finally, the CTS test of glass epoxy reinforced polymer plates to obtain the material fracture toughness Kc.

Keywords: blade, crack, frequency, material, SIF

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Authors: Shailendra Kumar Mishra

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In this paper, we focus on how contextual factors like the physical presence of other perceivers and then developed induced emotional empathy towards a person with disabilities may reduce the automatic negative stereotypes and then response towards that person. We demonstrated in study 1 that negative attitude based on negative stereotypes assessed on ATDP-test questionnaires on five points Linkert-scale are significantly less negative when participants were tested with a group of perceivers and then tested alone separately by applying 3 (positive, indifferent, and negative attitude levels) X 2 (physical presence condition and alone) factorial design of ANOVA test. In the second study, we demonstrate, by applying regression analysis, in the presence of other perceivers, whether in a small group, participants showed more induced emotional empathy through stronger prosociality towards a high distress target like a person with disabilities in comparison of that of other stigmatized persons such as racial biased or gender-biased people. Thus results show that automatic affective response in the form of induced emotional empathy in perceiver and contextual factors like the presence of other perceivers automatically activate stronger prosocial norms and egalitarian goals towards physically challenged persons in comparison to other stigmatized persons like racial or gender-biased people. This leads to less negative attitudes and behaviour towards a person with disabilities.

Keywords: contextual factors, high distress target, induced emotional empathy, stronger prosociality

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Authors: Omaima N. Ahmad AL-Allaf

Abstract:

Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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Authors: Ahmed Yousef A. Al Sultan

Abstract:

Introduction: The aim of this review is based on clinical research that studies the changes in middle cerebral artery velocity using Transcranial Doppler (TCD) and cerebral oxygen saturation using cerebral oximetry in patients undergoing carotid endarterectomy (CEA) surgery under local anesthesia (LA). Patients with or without neurological symptoms during the surgery are taking a role in this study using triplet method of cerebral oximetry, transcranial doppler and awake test in detecting any cerebral ischemic symptoms. Methods: about one hundred patients took part during their CEA surgeries under local anesthesia, using triple assessment mentioned method, Patients requiring general anesthesia be excluded from analysis. All data were recorded at eight surgery stages separately to serve this study. Results: In total regional cerebral oxygen saturation (rSO2), middle cerebral artery (MCA) velocity, and pulsatility index were significantly decreased during carotid artery clamping step in CEA procedures on the targeted carotid side. With most observed changes in MCA velocity during the study. Discussion: Cerebral oxygen saturation and middle cerebral artery velocity were significantly decreased during clamping step of the procedures on the targeted side. The team with neurological symptoms during the procedures showed higher changes of rSO2 and MCA velocity than the team without neurological symptoms. Cerebral rSO2 and MCA velocity significantly increased directly after de-clamping of the internal carotid artery on the affected side.

Keywords: awake testing, carotid endarterectomy, cerebral oximetry, Tanscranial Doppler

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