Search results for: protocol optimization

Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

Abstract:

Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Mukesh Kumar, Mahendra Pal Sharma

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Depleting fossil fuel resources coupled with serious environmental degradation has led to the search for alternative resources for biodiesel production as a substitute of Petro-diesel. Currently, edible, non-edible oils and microalgal plant species are cultivated for biodiesel production. Looking at the demerits of edible and non-edible oil resources, the focus is being given to grow microalgal species having high oil productivities, less maturity time and less land requirement. Out of various microalgal species, Chlorella protothecoides is considered as the most promising species for biodiesel production owing to high oil content (58 %), faster growth rate (24–48 h) and high biomass productivity (1214 mg/l/day). The present paper reports the results of optimization of reaction parameters of transesterification process as well as the kinetics of transesterification with 97% yield of biodiesel. The measurement of fuel quality of microalgal biodiesel shows that the biodiesel exhibit very good oxidation stability (O.S) of 7 hrs, more than ASTM D6751 (3 hrs) and EN 14112 (6 hrs) specifications. The CP and PP of 0 and -3 °C are finding as per ASTM D 2500-11 and ASTM D 97-12 standards. These results show that the microalgal biodiesel does not need any enhancement in O.S & CFP and hence can be recommended to be directly used as MB100 or its blends into diesel engine operation. Further, scope is available for the production of binary blends using poor quality biodiesel for engine operation.

Keywords: fuel quality, methyl ester yield, microalgae, transesterification

Procedia PDF Downloads 214

Authors: Dorith Tavor, Adi Wolfson

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In the past two decades a variety of green solvents have been proposed, including water, ionic liquids, fluorous solvents, and supercritical fluids. However, their implementation in industrial processes is still limited due to their tedious and non-sustainable synthesis, lack of experimental data and familiarity, as well as operational restrictions and high cost. Several years ago we presented, for the first time, the use of glycerol-based solvents as alternative sustainable reaction mediums in both catalytic and non-catalytic organic synthesis. Glycerol is the main by-product from the conversion of oils and fats in oleochemical production. Moreover, in the past decade, its price has substantially decreased due to an increase in supply from the production and use of fatty acid derivatives in the food, cosmetics, and drugs industries and in biofuel synthesis, i.e., biodiesel. The renewable origin, beneficial physicochemical properties and reusability of glycerol-based solvents, enabled improved product yield and selectivity as well as easy product separation and catalyst recycling. Furthermore, their high boiling point and polarity make them perfect candidates for non-conventional heating and mixing techniques such as ultrasound- and microwave-assisted reactions. Finally, in some reactions, such as catalytic transfer-hydrogenation or transesterification, they can also be used simultaneously as both solvent and reactant. In our ongoing efforts to design a viable protocol that will facilitate the acceptance of glycerol and its derivatives as sustainable solvents, pure glycerol and glycerol triacetate (triacetin) as well as various glycerol-triacetin mixtures were tested as sustainable solvents in several representative organic reactions, such as nucleophilic substitution of benzyl chloride to benzyl acetate, Suzuki-Miyaura cross-coupling of iodobenzene and phenylboronic acid, baker’s yeast reduction of ketones, and transfer hydrogenation of olefins. It was found that reaction performance was affected by the glycerol to triacetin ratio, as the solubility of the substrates in the solvent determined product yield. Thereby, employing optimal glycerol to triacetin ratio resulted in maximum product yield. In addition, using glycerol-based solvents enabled easy and successful separation of the products and recycling of the catalysts.

Keywords: glycerol, green chemistry, sustainability, catalysis

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Authors: Piotr Tylec, Julia Wierzbicka, Natalia Gajewska, Krzysztof Przeczek, Grzegorz Torbicz, Alicja Dudek, Magdalena Pisarska-Adamczyk, Mateusz Wierdak, Michal Pedziwiatr

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Introduction: Many patients have described changes in taste perception after weight loss surgery. However, little data is available about short term changes in taste after surgery. Aim: We aimed to evaluate short-term changes in taste preference after bariatric surgeries in comparison to colorectal surgeries. Material and Methods: Between April 2018 and April 2019, a total of 121 bariatric patients and 63 controls participated. Bariatric patients underwent laparoscopic sleeve gastrectomy or Roux-en-Y gastric by-pass. Controls underwent oncological colorectal surgeries. Patients who developed clinical complications requiring restriction of oral intake after surgery or withdraw their consent were excluded from the study. In the end, 85 bariatric patients and 44 controls were included. In all of them, the 16-item ERAS Protocol was applied. Using 10-points Numeric Rating Scale (1-10) patients completed questionnaire and rated their appetite and thirst (1 - no appetite/not thirsty, 10 – normal appetite/very thirsty) and flavoured standardized liquids' taste (1- horrible, 10-very tasty) and food images for the 6 group of taste (sweet, umami, sour, spicy, bitter and salty) (1 - not appetizing, 10 - very appetizing) preoperatively and on the first postoperative day. Data were analysed with Statistica 13.0 PL. Results: Analysed group consist of 129 patients (85 bariatric, 44 controls). Mean age and BMI in a research group was 44.91 years old, 46.22 kg/m² and in control group 62.09 years old, 25.87 kg/m², respectively. Our analysis revealed significant differences in changes of appetite between both groups (research: -4.55 ± 3.76 vs. control: -0.85 ± 4.37; p < 0.05), ratings bitter (research: 0.60 ± 2.98 vs. control: -0.88 ± 2.58; p < 0.05) and salty (research: 1.20 ± 3.50 vs. control: -0.52 ± 2.90; p < 0.05) flavoured liquids and ratings for sweet (research: 1.62 ± 3.31 vs. control: 0.01 ± 2.63; p < 0.05) and bitter (research: 1.21 ± 3.15 vs. control: -0.09 ± 2.25; p < 0.05) food images. There were statistically significant results in the ratings of other images, but in comparison to the control group, they were not statistically significant. Conclusion: The study showed that bariatric surgeries quickly decreases appetite and desire to eat certain types of food, such as salty. Moreover, the bitter taste was more desirable in the research group in comparison to control group. Nevertheless, the sweet taste was more appetible in the bariatric group than in control.

Keywords: bariatric surgery, general surgery, obesity, taste preference

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Authors: Kwame B. O. Amoah

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This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: energy consumption, building energy analysis, energy retrofits, energy-efficiency

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Authors: Hee-Jae Suh, Kyung-Su Kim, Min-Ji Kim, Yeon-Seong Jeong, Ok-Hwan Lee, Jae-Wook Shin, Hyang-Sook Chun, Chan Lee

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Canthaxanthin is keto-carotenoid produced from beta-carotene and it has been approved to be used in many countries as a food coloring agent. Canthaxanthin has been analyzed using High Performance Liquid Chromatography (HPLC) system with various ways of pretreatment methods. Four official methods for verification of canthaxanthin at FSA (UK), AOAC (US), EFSA (EU) and MHLW (Japan) were compared to improve its analytical and the pretreatment method. The Linearity, the limit of detection (LOD), the limit of quantification (LOQ), the accuracy, the precision and the recovery ratio were determined from each method with modification in pretreatment method. All HPLC methods exhibited correlation coefficients of calibration curves for canthaxanthin as 0.9999. The analysis methods from FSA, AOAC, and MLHW showed the LOD of 0.395 ppm, 0.105 ppm, and 0.084 ppm, and the LOQ of 1.196 ppm, 0.318 ppm, 0.254 ppm, respectively. Among tested methods, HPLC method of MHLW with modification in pretreatments was finally selected for the analysis of canthaxanthin in lab, because it exhibited the resolution factor of 4.0 and the selectivity of 1.30. This analysis method showed a correlation coefficients value of 0.9999 and the lowest LOD and LOQ. Furthermore, the precision ratio was lower than 1 and the accuracy was almost 100%. The method presented the recovery ratio of 90-110% with modification in pretreatment method. The cross-validation of coefficient variation was 5 or less among tested three institutions in Korea.

Keywords: analytic method, canthaxanthin, food colorants, pretreatment method

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Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

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Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: mininet, OpenFlow, POX controller, SDN

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

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Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

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Authors: Mohammed Elsayed Lotfy Elsayed Abouzeid, Tomonobu Senjyu

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A novel multi-objective park and ride control approach is presented in this research. Park and ride will encourage the owners of the vehicles to leave their cars in the nearest points (on the edges of the crowded cities) and use public transportation facilities (train, bus, metro, or mon-rail) to reach their work inside the crowded city. The proposed control scheme is used to design electric vehicle charging stations (EVCS) to charge 1000 electric vehicles (EV) during their owners' work time. Cairo, Egypt is used as a case study. Photovoltaic (PV) and battery energy storage system (BESS) are used to meet the EVCS demand. Two multi-objective optimization techniques (MOGA and epsilon-MOGA) are utilized to get the optimal sizes of PV and BESS so as to meet the load demand and minimize the total life cycle cost. Detailed analysis and comparison are held to investigate the performance of the proposed control scheme using MATLAB.

Keywords: Battery Energy Storage System, Electric Vehicle, Park and Ride, Photovoltaic, Multi-objective

Procedia PDF Downloads 141

Authors: Violeta Damjanovic-Behrendt

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This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

Keywords: security, internet of things, cloud computing, stackelberg game, machine learning, naive q-learning

Procedia PDF Downloads 353

Authors: Taufik Rizkiandi, Teuku Yuri M. Zagloel, Andri Dwi Setiawan

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Distribution and growth in the transportation and warehousing business sector decreased by 15,04%. There was a decrease in Gross Domestic Product (GDP) contribution level from rank 7 of 4,41% in 2019 to 3,81% in rank 8 in 2020. A decline in the transportation and warehousing business sector contributes to GDP, resulting in oil and gas companies implementing an efficient supply chain strategy to ensure the availability of goods, especially lubricants. Fluctuating demand for lubricants and warehouse service time limits are essential things that are taken into account in determining an efficient route. Add depots points as a solution so that demand for lubricants is fulfilled (not stock out). However, adding a depot will increase operating costs and storage costs. Therefore, it is necessary to optimize the addition of depots using the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). This research case study was conducted at an oil and gas company that produces lubricants from 2019 to 2021. The study results obtained the optimal route and the addition of a depot with a minimum additional cost. The total cost remains efficient with the addition of a depot when compared to one depot from Jakarta.

Keywords: CVRPTW, optimal route, depot, tabu search algorithm

Procedia PDF Downloads 134

Authors: Elham Azimzadeh, Saeedeh Sepehri, Hamidollah Hassanlouei

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Obesity is associated with postural instability, might influence the quality of daily life, and could be considered a potential factor for falling in obese people. The fat body mass especially in the abdominal area may increase body sway. Furthermore, loss of visual feedback may induce a larger postural sway in obese people. Moreover, Muscle fatigue may impair the work capacity of the skeletal muscle and may alter joint proprioception. So, the purpose of this study was to investigate the effect of physical fatigue and visual feedback on body sway and strength of lower extremities in obese people. 12 obese (4 female, 8 male; BMI >30 kg/m2), and 12 normal weight (4 female, 8 male; BMI: 20-25 kg/m2) subjects aged 37- 47 years participated in this study. The postural stability test on the Biodex balance system was used to characterize postural control along the anterior-posterior (AP) and mediolateral (ML) directions in eyes open and eyes closed conditions and maximal voluntary contraction (MVC) of knee extensors and flexors were measured before and after the high-intensity exhausting exercise protocol on the ergometer bike to confirm the presence of fatigue. Results indicated that the obese group demonstrated significantly greater body sway, in all indices (ML, AP, overall) compared with the normal weight group (eyes open). However, when visual feedback was eliminated, fatigue impaired the balance in the overall and AP indicators in both groups; ML sway was higher only in the obese group after exerting the fatigue in the eyes closed condition. Also, maximal voluntary contraction of knee extensors was impaired in the fatigued normal group but, there was no significant impairment in knee flexors MVC in both group. According to the findings, peripheral fatigue was associated with altered postural control in upright standing when eyes were closed, and that mechanoreceptors of the feet may be less able to estimate the position of the body COM over the base of support in the loss of visual feedback. This suggests that the overall capability of the postural control system during upright standing especially in the ML direction could be lower due to fatigue in obese individuals and could be a predictor of future falls.

Keywords: maximal voluntary contraction, obesity, peripheral fatigue, postural control, visual feedback

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Authors: Gamze Karanfil Celep, Kevser Dincer

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The effects of polymer concentration and electrospinning process parameters on the average diameters of electrospun polyacrylonitrile (PAN) nanofibers were experimentally investigated. Besides, mechanical and thermal properties of PAN nanofibers were examined by tensile test and thermogravimetric analysis (TGA), respectively. For this purpose, the polymer concentration, solution feed rate, supply voltage and tip-to-collector distance were determined as the control factors. To succeed these aims, Taguchi’s L16 orthogonal design (4 parameters, 4 level) was employed for the experimental design. Optimal electrospinning conditions were defined using the signal-to-noise (S/N) ratio that was calculated from diameters of the electrospun PAN nanofibers according to "the-smaller-the-better" approachment. In addition, analysis of variance (ANOVA) was evaluated to conclude the statistical significance of the process parameters. The smallest diameter of PAN nanofibers was observed. According to the S/N ratio response results, the most effective parameter on finding out of nanofiber diameter was determined. Finally, the Taguchi design of experiments method has been found to be an effective method to statistically optimize the critical electrospinning parameters used in nanofiber production. After determining the optimum process parameters of nanofiber production, electrical conductivity and fuel cell performance of electrospun PAN nanofibers on the carbon papers will be evaluated.

Keywords: nanofiber, electrospinning, polyacrylonitrile, Taguchi method

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Authors: Seemab Safdar, Shazia Fatima, Ahmad Qureshy, M. Adnan Saeed, M. Faheem

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Background: Thyroid cancer has 586,000 cases per year worldwide, and this translates to 3% of all tumor diagnoses. 90% of the cases fall under differentiated thyroid carcinoma (DTC), which includes follicular thyroid cancer (FTC) and papillary thyroid cancer (PTC). During their illness, 10% of patients develop distant metastases, and two-thirds of them develop resistance to radioactive iodine (RAI) treatment. It has been shown that in some circumstances, like DTC with high TG levels and negative 131I whole-body scintigraphy (TENIS), [18F] FDG-PET-CT is an effective imaging technique. This study determines the role of [18F] FDG-PET-CT in the treatment of TENIS patients. Methods: 16 patients (n = 12 female; 4 males, age 45 ± 15 years) with histologically proven thyroid cancer (Differentiated and poorly differentiated) and high TG with negative iodine scans were included in this prospective study from January 2024 to June 2024. They underwent scanning in state-of-the-art (GE Discovery MI) [18F] FDG-PET-CT for re-staging or diagnostics of recurrent disease using a standardized protocol. All DTC subtypes and PDTC were included. The referring physicians completed standardized questionnaires both before and after PET-CT to prospectively determine the examination's effect on clinical decision-making. Patient outcomes were measured by analysis of medical records. Moreover, after PET-CT, a change in the pre-PET-CT planned therapies was documented in 32% of cases and additional invasive diagnostic procedures could be waived in 37.5 % of cases. TG levels under TSH stimulation were significantly higher in patients showing PET-CT metastases compared to patients without such findings (68.75%). Results: Without PET-CT, physicians referring to the doctors had not established a complete treatment plan for 45% of patients with thyroid carcinoma. 12/16 patients showed FDG avidity in cervical lymph nodes that were not Iodine avid previously, 2 patients had FDG avid disease in the lungs. In the process, PET-CT helped plan patient management and created a clear plan for treatment in 68.75% of patients. Conclusions: This study confirms that [18F] FDG-PET-CT used in a routine clinical setting has a very important impact on the management of patients with thyroid cancer when TG levels are persistently high in the presence of negative Iodine Scans by initiating treatments and replacing additional imaging and invasive tests.

Keywords: PET-CT, TENIS, role, FDG

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Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Mohammadreza Heydariazad

Abstract:

Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value.

Keywords: wind energy, generator, superconducting inductor, wind turbine power

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Authors: Avijit Dey, Shyam S. Paul, Satbir S. Dahiya, Balbir S. Punia, Luciano A. Gonzalez

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Methane emitted from ruminant livestock not only reduces the efficiency of feed energy utilization but also contributes to global warming. Vegetable oils, a source of poly unsaturated fatty acids, have potential to reduce methane production and increase conjugated linoleic acid in the rumen. However, characteristics of oils, level of inclusion and composition of basal diet influences their efficacy. Therefore, this study was aimed to investigate the effects of sunflower (SFL) and cottonseed (CSL) oils on methanogenesis, volatile fatty acids composition and feed fermentation pattern by in vitro gas production (IVGP) test. Four concentrations (0, 0.1, 0.2 and 0.4ml /30ml buffered rumen fluid) of each oil were used. Fresh rumen fluid was collected before morning feeding from two rumen cannulated buffalo steers fed a mixed ration. In vitro incubation was carried out with sorghum hay (200 ± 5 mg) as substrate in 100 ml calibrated glass syringes following standard IVGP protocol. After 24h incubation, gas production was recorded by displacement of piston. Methane in the gas phase and volatile fatty acids in the fermentation medium were estimated by gas chromatography. Addition of oils resulted in increase (p<0.05) in total gas production and decrease (p<0.05) in methane production, irrespective of type and concentration. Although the increase in gas production was similar, methane production (ml/g DM) and its concentration (%) in head space gas was lower (p< 0.01) in CSL than in SFL at corresponding doses. Linear decrease (p<0.001) in degradability of DM was evident with increasing doses of oils (0.2ml onwards). However, these effects were more pronounced with SFL. Acetate production tended to decrease but propionate and butyrate production increased (p<0.05) with addition of oils, irrespective of type and doses. The ratio of acetate to propionate was reduced (p<0.01) with addition of oils but no difference between the oils was noted. It is concluded that both the oils can reduce methane production. However, feed degradability was also affected with higher doses. Cotton seed oil in small dose (0.1ml/30 ml buffered rumen fluid) exerted greater inhibitory effects on methane production without impeding dry matter degradability. Further in vivo studies need to be carried out for their practical application in animal ration.

Keywords: buffalo, methanogenesis, rumen fermentation, vegetable oils

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Authors: Asiya Rezzouq, Mehdi El Bouchti, Omar Cherkaoui, Sanaa Majid, Souad Zyade

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In recent years, there has been a steady increase in the exploration of new renewable and non-conventional sources for the production of biodegradable nanomaterials. Nature harbours valuable cellulose-rich materials that have so far been under-exploited and can be used to create cellulose derivatives such as cellulose microfibres (CMFs) and cellulose nanocrystals (CNCs). These unconventional sources have considerable potential as alternatives to conventional sources such as wood and cotton. By using agricultural waste to produce these cellulose derivatives, we are responding to the global call for sustainable solutions to environmental and economic challenges. Responsible management of agricultural waste is increasingly crucial to reducing the environmental consequences of its disposal, including soil and water pollution, while making efficient use of these untapped resources. In this study, the main objective was to extract cellulose nanocrystals (CNC) from melon plant residues using methods that are both efficient and sustainable. To achieve this high-quality extraction, we followed a well-defined protocol involving several key steps: pre-treatment of the residues by grinding, filtration and chemical purification to obtain high-quality (CMF) with a yield of 52% relative to the initial mass of the melon plant residue. Acid hydrolysis was then carried out using phosphoric acid and sulphuric acid to convert (CMF) into cellulose nanocrystals. The extracted cellulose nanocrystals were subjected to in-depth characterization using advanced techniques such as transmission electron microscopy (TEM), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction. The resulting cellulose nanocrystals have exceptional properties, including a large specific surface area, high thermal stability and high mechanical strength, making them suitable for a variety of applications, including as reinforcements for composite materials. In summary, the study highlights the potential for recovering agricultural melon waste to produce high-quality cellulose nanocrystals with promising applications in industry, nanotechnology, and biotechnology, thereby contributing to environmental and economic sustainability.

Keywords: cellulose, melon plant residues, cellulose nanocrystals, properties, applications, composite materials

Procedia PDF Downloads 56

Authors: S. Padma, D. H. Tejavathi

Abstract:

Somatic embryogenesis is a remarkable illustration of the dictum of plant totipotency where developmental reconstruction of somatic cells takes place towards the embryogenic pathway. It recapitulates the morphological and developmental process that occurs in zygotic embryogenesis. S. androgynous commonly called as multivitamin plant. The leaves are consumed as green leafy vegetable by the Southeast Asian communities due to their rich nutritional profile. Despite being a good nutritional vegetable with proteins, vitamins, minerals, amino acids, it is warned for excessive intake due to the presence of alkoloid called papaverine. Papaverine at higher concentrations is toxic and leads to a syndrome called Bronchiolitis Obliterans. In the present study, morphogenetic potential of shoot tip, leaf and nodal explants of Sauropus androgynous was investigated to develop and enhance the reliable plant regeneration protocol via somatic embryogenesis. Somatic embryos were derived directly from the embryogenic callus derived from shoot tip, node and leaf cultures on Phillips and Collins (L2) medium supplemented with NAA at various concentrations ranging from 5.3 µM/l to 26.85 µM/l within two months of inoculation. Thus obtained embryos were sub cultured to modified L2 media supplemented with increased vitamin level for the further growth. Somatic embryos with well-developed cotyledons were transferred to normal and modified L2 basal medium for conversion. The plantlets thus obtained were subjected to brief acclimatization before transferring them to land. About 95% of survival rate was recorded. The augmentation process of culturing various explants through somatic embryogenesis using synthetic medium with various plant growth regulators under controlled conditions have aggrandized the commercial production of Sauropus making it easily available over the conventional propagation methods. In addition, regeneration process through somatic embryogenesis has ameliorated the development of desired character in Sauropus with low papaverine content thereby providing a valuable resource to the food and pharmaceutical industry. Based on this research, plant tissue culture techniques have shown promise for economical and convenient application in Sauropus androgynous breeding.

Keywords: L2 medium, multivitamin plant, NAA, papaverine

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

Procedia PDF Downloads 447

Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

Procedia PDF Downloads 585

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Sergio D’Ambrosioa, Azza Dobousa, Chiara Schiraldia, Donatella Ciminib

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Probiotics are living microorganisms that give beneficial effects while consumed. Lactic acid bacteria and bifidobacteria are among the most representative strains assessed as probiotics and exploited as food supplements. Numerous studies demonstrated their potential as a therapeutic candidate for a variety of diseases (restoring gut flora, lowering cholesterol, immune response-enhancing, anti-inflammation and anti-oxidation activities). These beneficial actions are also due to biomolecules produced by probiotics, such as exopolysaccharides (EPSs), that demonstrate plenty of beneficial properties such as antimicrobial, antitumor, anti-biofilm, antiviral and immunomodulatory activities. Limosilactobacillus fermentum is a widely studied member of probiotics; however, few data are available on the development of fermentation and downstream processes for the production of viable biomasses for potential industrial applications. However, few data are available on the development of fermentation processes for the large-scale production of probiotics biomass for industrial applications and for purification processes of EPSs at an industrial scale. For this purpose, L. fermentum strain was isolated from buffalo milk and used as a test example for biotechnological process development. The strain was able to produce up to 109 CFU/mL on a (glucose-based) semi-defined medium deprived of animal-derived raw materials up to the pilot scale (150 L), demonstrating improved results compared to commonly used, although industrially not suitable, media-rich of casein and beef extract. Biomass concentration via microfiltration on hollow fibers, and subsequent spray-drying allowed to recover of about 5.7 × 1010CFU/gpowder of viable cells, indicating strain resistance to harsh processing conditions. Overall, these data demonstrate the possibility of obtaining and maintaining adequate levels of viable L. fermentum cells by using a simple approach that is potentially suitable for industrial development. A downstream EPS purification protocol based on ultrafiltration, precipitation and activated charcoal treatments showed a purity of the recovered polysaccharides of about 70-80%.

Keywords: probiotics, fermentation, exopolysaccharides (EPSs), purification

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

Procedia PDF Downloads 278

Authors: Emma O’ Keeffe, Helen Hughes, Peter McLoughlin, Shiau Pin Tan, Nick McCarthy

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Biosecurity is emerging as one of the most important issues facing the agricultural and forestry community. This is as a result of increased invasion from new pests and diseases with the main protocol for dealing with these species being the use of synthetic pesticides. However, these chemicals have been shown to exhibit negative effects on the environment. Seaweeds represent a vast untapped resource of bio-molecules with a broad range of biological activities including pesticidal. This project investigated both the antifungal and antibacterial activity of seaweed species against two problematic root rot fungi, Armillaria mellea and Heterobasidion annosum and ten quarantine bacterial plant pathogens including Xanthomonas arboricola, Xanthomonas fragariae, and Erwinia amylovora. Four seaweed species were harvested from the South-East coast of Ireland including brown, red and green varieties. The powdered seaweeds were extracted using four different solvents by liquid extraction. The poisoned food technique was employed to establish the antifungal efficacy, and the standard disc diffusion assay was used to assess the antibacterial properties of the seaweed extracts. It was found that extracts of the green seaweed exhibited antifungal activity against H. annosum, with approximately 50% inhibition compared to the negative control. The protectant activities of the active extracts were evaluated on disks of Picea sitchensis, a plant species sensitive to infection from H. annosum and compared to the standard chemical control product urea. The crude extracts exhibited very similar activity to the 10% and 20% w/v concentrations of urea, demonstrating the ability of seaweed extracts to compete with commercially available products. Antibacterial activity was exhibited by a number of seaweed extracts with the red seaweed illustrating the strongest activity, with a zone of inhibition of 15.83 ± 0.41 mm exhibited against X. arboricola whilst the positive control (10 μg/disk of chloramphenicol) had a zone of 26.5 ± 0.71 mm. These results highlight the potential application of seaweed extracts in the forestry and agricultural industries for use as biopesticides. Further work is now required to identify the bioactive molecules that are responsible for this antifungal and antibacterial activity in the seaweed extracts, including toxicity studies to ensure the extracts are non-toxic to plants and humans.

Keywords: antibacterial, antifungal, biopesticides, seaweeds

Procedia PDF Downloads 169