Search results for: thermo-hydraulic performance factor

Authors: Chun-Fang Hsueh, Chen-Kang Chang

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Introduction: Branched-chain amino acids (BCAA) could reduce cerebral uptake of tryptophan, leading to decreased synthesis of serotonin in the brain. Arginine and citrulline could reduce exercise-induced hyperammonemia by increasing nitric oxide synthesis and the urea cycle. The combination of these supplements could reduce exercise-induced central fatigue. The purpose of this study was to examine the effect of BCAA, arginine, and citrulline supplementation on repeated swimming performance in teenage athletes. Methods: Eight male and eight female high school swimmers ingested 0.085 g/kg BCAA, 0.05 g/kg arginine and 0.05 g/kg citrulline (AA trial) or placebo (PL trial) in a randomized cross-over design. One hour after the ingestion, the subjects performed a 50 m sprint with their best style every 2 min for 8 times in an indoor 25 m pool. The subjects were asked to swim with their maximal effort each time. The time, stroke frequency and stroke length in each sprint were recorded. Venous blood samples were collected before and after the exercise. The time for each sprint was analyzed by 2-way analysis of variance with repeated measurement. Results: When all subjects were pooled together, total time for the AA trial was significantly faster than the PL trial (AA: 244.02 ± 22.94 s; PL: 247.55 ± 24.17 s, p < .001). Individual sprint time showed significant trial (p= .001) and trial x time (p= .004) effects. The post-hoc analysis revealed that the AA trial was significantly faster than the PL trial in the 2nd, 5th, and 6th sprint. In female subjects, there is a significant trial effect (p= .004) with the AA trial being faster in the 1st, 2nd, and 5th sprint. On the other hand, the trial effect was not significant (p= .072) in male subjects. Conclusions: The combined supplementation could improve 8 x 50 m performance in high school swimmers. The blood parameters including BCAA, tryptophan, NH₃, nitric oxide, and urea, as well as the stroke frequency and length in each sprint, are being analyzed. The results will be presented in the conference.

Keywords: central fatigue, hyperammonemia, tryptophan, urea

Procedia PDF Downloads 186

Authors: Ayoub Alsarhan, Ahmed Otoom, Yousef Kilani, Abdel-Rahman al-GHuwairi

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Wireless mesh networks (WMNs) have emerged recently to improve internet access and other networking services. WMNs provide network access to the clients and other networking functions such as routing, and packet forwarding. Spectrum scarcity is the main challenge that limits the performance of WMNs. Cognitive radio is proposed to solve spectrum scarcity problem. In this paper, we consider a cognitive wireless mesh network where unlicensed users (secondary users, SUs) can access free spectrum that is allocated to spectrum owners (primary users, PUs). Although considerable research has been conducted on spectrum allocation, spectrum assignment is still considered an important challenging problem. This problem can be solved using cognitive radio technology that allows SUs to intelligently locate free bands and access them without interfering with PUs. Our scheme considers several heuristics for spectrum allocation. These heuristics include: channel error rate, PUs activities, channel capacity and channel switching time. Performance evaluation of the proposed scheme shows that the scheme is able to allocate the unused spectrum for SUs efficiently.

Keywords: cognitive radio, dynamic spectrum access, spectrum management, spectrum sharing, wireless mesh networks

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Authors: Bahamin Bazooyar, Xinyan Wang, Hua Zhao

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As a zero-carbon fuel, hydrogen can be used in combustion engines to avoid carbon emissions. This paper numerically investigates the engine performance of a two-stroke opposed piston hydrogen engine by using three-dimensional (3D) Computational Fluid Dynamics (CFD) simulations. The engine displacement is 12.2 cm, and the compression ratio of 39. RANS simulations with the k-ε turbulence model and coupled chemistry combustion models are performed at an engine speed of 4500 rpm and hydrogen flow rate of up to 100 gr/s. In order to model the hydrogen injection process, the hydrogen nozzle was meshed with refined mesh, and injection pressure varied between 100 and 200 bars. In order to optimize the hydrogen combustion process, the injection timing was optimized between 15 before the top dead center and 10. The results showed that the combustion efficiency was mostly influenced by the injection pressures due to its impact on the fuel/air mixing and charge inhomogeneity. Nitrogen oxide (NOₓ) emissions are well correlated with engine peak temperatures, demonstrating that the thermal NO mechanism is dominant under engine conditions. Through the optimization of hydrogen injection timing and pressure, the peak thermal efficiency of 45 and NOx emission of 15 ppm/kWh can be achieved at an injection timing of 350 CA and pressure of 160 bars.

Keywords: engine, hydrogen, diesel, two-stroke, opposed-piston, decarbonisation

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Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

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The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement; On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: altitude estimation, drone, image processing, trajectory planning

Procedia PDF Downloads 116

Authors: Jimena Lizeth Gomez Delgado, Jhon Jairo Rodriguez, Nicolas Santos, Enrique Mejia Ospino

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Nanotechnology has played an important role in the hydrocarbon industry, recently , due to the unique properties of graphene oxide nanoparticles, they have been incorporated in different studies enhanced oil recovery. Nonetheless, very few studies have used graphene oxide nanoparticles in coreflooding experiments. Herein, the use of Graphene oxide (GO) nanoparticle was explored, exploited and evaluated. The performance of Graphene oxide nanoparticles on the interfacial properties in the presence of different electrolyte concentrations representative of field brine and pH conditions was investigated. Moreover, wettability behavior of the nanofluid at the oil/sand interface was studied used contact angle and Amott Harvey evaluation. Experimental result shows that the adsorption of GO on the sandstone surface changes the wettability of the sandstone from being strongly crude oil-wet to intermediate crude oil-wettability. At 900 ppm formation brine with 8 pH solution and 0.09 wt% nanoparticles concentration, Graphene oxide nanofluid exhibited better performance under the different electrolyte concentration studied. Finally, heavy oil displacement test in sandstone cores showed that oil recovery of Graphene oxide nanofluid had 7% incremental oil recovery over conventional waterflooding.

Keywords: nanoparticle, graphene oxide, nanotechnology, wettability, enhanced oil recovery, coreflooding

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Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

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Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

Procedia PDF Downloads 149

Authors: Kitti Supchukun, Kris Angkanaporn, Teerapong Yata

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The product innovation using a nutraceutical delivery system on improving the growth performance of broilers is the product planning and development to solve the antibiotics banning policy incurred in the local and global livestock production system. Restricting the use of antibiotics can reduce the quality of chicken meat and increase pathogenic bacterial contamination. Although other alternatives were used to replace antibiotics, the efficacy was inconsistent, reflecting on low chicken growth performance and contaminated products. The product innovation aims to effectively deliver the selected active ingredients into the body. This product is tested on the pharmaceutical lab scale and on the farm-scale for market feasibility in order to create product innovation using the nutraceutical delivery system model. The model establishes the product standardization and traceable quality control process for farmers. The study is performed using mixed methods. Starting with a qualitative method to find the farmers' (consumers) demands and the product standard, then the researcher used the quantitative research method to develop and conclude the findings regarding the acceptance of the technology and product performance. The survey has been sent to different organizations by random sampling among the entrepreneur’s population including integrated broiler farm, broiler farm, and other related organizations. The mixed-method results, both qualitative and quantitative, verify the user and lead users' demands since they provide information about the industry standard, technology preference, developing the right product according to the market, and solutions for the industry problems. The product innovation selected nutraceutical ingredients that can solve the following problems in livestock; bactericidal, anti-inflammation, gut health, antioxidant. The combinations of the selected nutraceutical and nanostructured lipid carriers (NLC) technology aim to improve chemical and pharmaceutical components by changing the structure of active ingredients into nanoparticle, which will be released in the targeted location with accurate concentration. The active ingredients in nanoparticle form are more stable, elicit antibacterial activity against pathogenic Salmonella spp and E.coli, balance gut health, have antioxidant and anti-inflammation activity. The experiment results have proven that the nutraceuticals have an antioxidant and antibacterial activity which also increases the average daily gain (ADG), reduces feed conversion ratio (FCR). The results also show a significant impact on the higher European Performance Index that can increase the farmers' profit when exporting. The product innovation will be tested in technology acceptance management methods from farmers and industry. The production of broiler and commercialization analyses are useful to reduce the importation of animal supplements. Most importantly, product innovation is protected by intellectual property.

Keywords: nutraceutical, nano structure lipid carrier, anti-microbial drug resistance, broiler, Salmonella

Procedia PDF Downloads 185

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, S. Harapanahalli, J. Walsh

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The objective of this study was to determine the effects of environmental stressors on the performance of lactating dairy cows and discuss some future trends. There exists a relationship between the meteorological data and milk yield prediction accuracy in pasture-based dairy systems. New precision technologies are available and are being developed to improve the sustainability of the dairy industry. Some of these technologies focus on welfare of individual animals on dairy farms. These technologies allow the automatic identification of animal behaviour and health events, greatly increasing overall herd health and yield while reducing animal health inspection demands and long-term animal healthcare costs. The data set consisted of records from 489 dairy cows at two dairy farms and temperature measured from the nearest meteorological weather station in 2018. The effects of temperature on milk production and behaviour of animals were analyzed. The statistical results indicate different effects of temperature on milk yield and behaviour. The “comfort zone” for animals is in the range 10 °C to 20 °C. Dairy cows out of this zone had to decrease or increase their metabolic heat production, and it affected their milk production and behaviour.

Keywords: behavior, milk yield, temperature, precision technologies

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Authors: Sandeep Kumar, Mahesh Kumar Jat, Rajib Sarkar

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Soil reinforced with randomly distributed fibers is an attractive means to improve the performance of soil in a cost effective manner. Static and dynamic characterization of fiber reinforced soil have become important to evaluate adequate performance for all classes of geotechnical engineering problems. Present study investigates the behaviour of fiber reinforced cohesionless soil through numerical simulation of triaxial specimen. The numerical model has been validated with the existing literature of laboratory triaxial compression testing. A parametric study has been done to find out optimum fiber content for shear resistance. Cyclic triaxial testing has been simulated and the stress-strain response of fiber-reinforced sand has been examined considering different combination of fiber contents. Shear modulus values and damping values of fiber-reinforced sand are evaluated. It has been observed from results that for 1.0 percent fiber content shear modulus increased 2.28 times and damping ratio decreased 4.6 times. The influence of amplitude of cyclic strain, confining pressure and frequency of loading on the dynamic properties of fiber reinforced sand has been investigated and presented.

Keywords: damping, fiber reinforced soil, numerical modelling, shear modulus

Procedia PDF Downloads 282

Authors: Fatima Zahra Falah, Touria El. Ghailassi, Samia Yousfi, Ahmed Moussaif, Hasna Hamdane, Mouna Latifa Bouamrani

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The management and treatment of radioactive wastewater pose significant challenges to environmental safety and public health. This study presents an innovative approach to optimizing radioactive wastewater treatment using a novel biosorbent: chitosan-argan nutshell beads. By employing Response Surface Methodology (RSM), we aimed to determine the optimal conditions for maximum removal efficiency of radioactive contaminants. Chitosan, a biodegradable and non-toxic biopolymer, was combined with argan nutshell powder to create composite beads. The argan nutshell, a waste product from argan oil production, provides additional adsorption sites and mechanical stability to the biosorbent. The beads were characterized using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and X-ray Diffraction (XRD) to confirm their structure and composition. A three-factor, three-level Box-Behnken design was utilized to investigate the effects of pH (3-9), contact time (30-150 minutes), and adsorbent dosage (0.5-2.5 g/L) on the removal efficiency of radioactive isotopes, primarily focusing on cesium-137. Batch adsorption experiments were conducted using synthetic radioactive wastewater with known concentrations of these isotopes. The RSM analysis revealed that all three factors significantly influenced the adsorption process. A quadratic model was developed to describe the relationship between the factors and the removal efficiency. The model's adequacy was confirmed through analysis of variance (ANOVA) and various diagnostic plots. Optimal conditions for maximum removal efficiency were pH 6.8, a contact time of 120 minutes, and an adsorbent dosage of 0.8 g/L. Under these conditions, the experimental removal efficiency for cesium-137 was 94.7%, closely matching the model's predictions. Adsorption isotherms and kinetics were also investigated to elucidate the mechanism of the process. The Langmuir isotherm and pseudo-second-order kinetic model best described the adsorption behavior, indicating a monolayer adsorption process on a homogeneous surface. This study demonstrates the potential of chitosan-argan nutshell beads as an effective and sustainable biosorbent for radioactive wastewater treatment. The use of RSM allowed for the efficient optimization of the process parameters, potentially reducing the time and resources required for large-scale implementation. Future work will focus on testing the biosorbent's performance with real radioactive wastewater samples and investigating its regeneration and reusability for long-term applications.

Keywords: adsorption, argan nutshell, beads, chitosan, mechanism, optimization, radioactive wastewater, response surface methodology

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

Procedia PDF Downloads 128

Authors: R. M. Chandima Ratnayake, Daniel Dyakov

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Super steel materials play vital role in construction and fabrication of structural, piping and pipeline components. They enable to minimize the life cycle costs in assuring the integrity of onshore and offshore operating systems. In this context, Duplex stainless steel (DSS) material related welding on constructions and fabrications play a significant role in maintaining and assuring integrity at an optimal expenditure over the life cycle of production and process systems as well as associated structures. In DSS welding, the factors such as gap geometry, shielding gas supply rate, welding current, and type of the welding process play a vital role on the final joint performance. Hence, an experimental investigation has been performed using engineering robust design approach (ERDA) to investigate the optimal settings that generate optimal super DSS (i.e. UNS S32750) joint performance. This manuscript illustrates the mathematical approach and experimental design, optimal parameter settings and results of verification experiment.

Keywords: duplex stainless steel welding, engineering robust design, mathematical framework, optimal parameter settings

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Authors: Ji Su Kim, Bo Ram Choi, Ju Yeon Cho, Hyukjin Lee

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Epidermal growth factor receptor (EGFR) 19 deletion mutation gene is over-expressed in carcinoma patient. EGFR 19 deletion mutation is known as typical biomarker of non-small cell lung cancer (NSCLC), which one section in the coding exon 19 of EGFR is deleted. Therefore, there have been many attempts over the years to detect EGFR 19 deletion mutation for replacing conventional diagnostic method such as PCR and tissue biopsy. We developed a simple and facile detection platform based on Rolling Circle Amplification (RCA), which provides highly amplified products in isothermal amplification of the ligated DNA template. Limit of detection (~50 nM) and a faster detection time (~30 min) could be achieved by introducing RCA.

Keywords: EGFR19, cancer, diagnosis, rolling circle amplification (RCA), hydrogel

Procedia PDF Downloads 257

Authors: Christoph Opperer

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The rapid urbanization of modern societies and the need for sustainable urban development demand innovative solutions that meet both individual and collective needs while addressing environmental concerns. To address these challenges, this paper presents a study that explores the potential of spatial and energetic/ecological optimization to enhance the performance of urban settlements, focusing on both architectural and urban scales. The study focuses on the application of biological principles and self-organization processes in urban planning and design, aiming to achieve a balance between ecological performance, architectural quality, and individual living conditions. The research adopts a case study approach, focusing on a 10-hectare brownfield site in the south of Vienna. The site is surrounded by a small-scale built environment as an appropriate starting point for the research and design process. However, the selected urban form is not a prerequisite for the proposed design methodology, as the findings can be applied to various urban forms and densities. The methodology used in this research involves dividing the overall building mass and program into individual small housing units. A computational model has been developed to optimize the distribution of these units, considering factors such as solar exposure/radiation, views, privacy, proximity to sources of disturbance (such as noise), and minimal internal circulation areas. The model also ensures that existing vegetation and buildings on the site are preserved and incorporated into the optimization and design process. The model allows for simultaneous optimization at two scales, architectural and urban design, which have traditionally been addressed sequentially. This holistic design approach leads to individual and collective benefits, resulting in urban environments that foster a balance between ecology and architectural quality. The results of the optimization process demonstrate a seemingly random distribution of housing units that, in fact, is a densified hybrid between traditional garden settlements and allotment settlements. This urban typology is selected due to its compatibility with the surrounding urban context, although the presented methodology can be extended to other forms of urban development and density levels. The benefits of this approach are threefold. First, it allows for the determination of ideal housing distribution that optimizes solar radiation for each building density level, essentially extending the concept of sustainable building to the urban scale. Second, the method enhances living quality by considering the orientation and positioning of individual functions within each housing unit, achieving optimal views and privacy. Third, the algorithm's flexibility and robustness facilitate the efficient implementation of urban development with various stakeholders, architects, and construction companies without compromising its performance. The core of the research is the application of global and local optimization strategies to create efficient design solutions. By considering both, the performance of individual units and the collective performance of the urban aggregation, we ensure an optimal balance between private and communal benefits. By promoting a holistic understanding of urban ecology and integrating advanced optimization strategies, our methodology offers a sustainable and efficient solution to the challenges of modern urbanization.

Keywords: sustainable development, self-organization, ecological performance, solar radiation and exposure, daylight, visibility, accessibility, spatial distribution, local and global optimization

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Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

Procedia PDF Downloads 283

Authors: Jiajia Peng

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Tinnitus is one of the common symptoms of ear diseases and is characterized by an abnormal perception of sound without external stimulation. Tinnitus is agony and seriously affects the life of the general population by approximately 1%. Sleep disturbance is a common problem in patients with tinnitus. Lack of sleep will lead to the accumulation of metabolites in the brain and cannot be cleared in time. These substances enhance sympathetic nerve reactivity in the auditory system, resulting in tinnitus occurrence or aggravation. Then, tinnitus may aggravate sleep disturbance, thus forming a vicious circle. Through a systematic review of the relevant literature, we summarize the research on tinnitus and sleep. Although the results suggest that tinnitus is often accompanied by sleep disturbance, the impact of unfavorable sleep habits on tinnitus is not clear. In particular, the relationships between sleep behaviors and other chronic diseases have been revealed. To reduce the incidence rate of tinnitus, clinicians should pay attention to the relevance between different sleep behaviors and tinnitus.

Keywords: tinnitus, sleep, sleep factor, sleep behavior

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Authors: Shosh Kazaz, Shmuel Banai, Vered Zilberberg

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Optimizing high business performance and employee's well-being simultaneously often challenges organizations. 'TIP' intervention enables achieving them both as the given project demonstrates. Increasing outcomes and improving performance were the initial motivators for this explorative project, followed by a request of the head of the Cardiology department: 'I know we are the best at our clinical practice, but we need to take it further and break our own glass ceiling.' Two guided interventions were conducted in two different units within the department, designed to implement advanced managerial and business-oriented tools, along with 'soft tools' based on coaching psychology and particularly wellness coaching. The organ department multi-disciplinary teams were assembled, aiming to manage and lead the process: mapping the patients' flow, creating solutions, implementing, assessing, improving and assimilating them. Approximately four months later, without additional external resources, meaningful results emerged by the teams in terms of business and performance: shortening the hospitalization length at a given procedure (from 7 to 2.1 days); increasing the availability of Catheterization laboratory by 16% daily – resulting profitability raise; improving patients' journey and experience. A year later, those results are maintained. Furthermore, interviews with the participants revealed positive perceptions regarding the department; a higher sense of joyfulness, connectedness, belonging and a better department climate were reported. Additionally, participants reported a higher sense of fulfillment as opposed to their earliest skepticism and cynicism about their ability to enhance outcomes without more resources (budget and/or manpower), experiencing a mindset change toward the possibility of leading personal and professional growth processes. These reports were supported by analyzing a set of questionnaires that the participants completed, parallel to a control group of non-participating colleagues. Although the assessment was taken a year after the completion of the project and during 'covid-19th-3rd national quarantine, the results indicated a significant impact on several personal parameters associated with wellness, compared to the control group. The participants were higher in self-efficacy and organizational commitment; men were higher in resilience and optimism and women were higher in well-being. In conclusion, the 'TIP' relatively short intervention integrates advanced managerial and wellness coaching tools, empowers organizational resources: Team, Individual and Process and by that generates multi-impact measurable results in terms of employee's wellness parameters along with business performance and patient care.

Keywords: coaching, health and wellness, health management, leadership and well-being

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Authors: M. Babul Hasan

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Management sciences (MS), big group of companies and industries or government policies (GP) is affiliated with a huge number of decision ingredients and complicated restrictions. Every factor in MS, every product in Industries or decision in GP is not always bankable in practice. After formulating these models there arises large-scale mixed integer programming (MIP) problem. In this paper, we developed decomposition-based pricing procedure to filter the unnecessary decision ingredients from MIP where the variables in huge number will be abated and the complicacy of restrictions will be elementary. A real life numerical example has been illustrated to demonstrate the methods. We develop the computer techniques for these methods by using a mathematical programming language (AMPL).

Keywords: Lagrangian relaxation, decomposition, sub-problem, master-problem, pricing, mixed IP, AMPL

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Authors: S. M. Mabandla, P. Loveday, C. Gomes, D. T. Maiga, T. T. Phadi

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Lead zirconate titanate (PZT) piezoelectric ceramics are widely used in ultrasonic applications due to their ability to effectively convert electrical energy into mechanical vibrations and vice versa. This paper presents a study on the behaviour of various combinations of pairs of PZT piezoelectric ceramic materials positioned adjacent to each other with an intermediate gap submerged in water, where one piezoelectric ceramic material is excited by a cyclic electric field with constant frequency and amplitude displacement. The transmitted ultrasonic sound propagates through the medium and is received by the PZT ceramic at the other end, the ultrasonic sound signal amplitude displacement experiences attenuation during propagation due to acoustic impedance. The investigation focuses on understanding the causes of extremely high amplitude displacement attenuation that have been observed in various combinations of piezoelectric ceramic pairs that are submerged in water arranged in a manner stipulated earlier. by examining various combinations of pairs of these piezoelectric ceramics, their physical, electrical, and acoustic properties, and behaviour and attributing them to the observed significant signal attenuation. The experimental setup involves exciting one piezoelectric ceramic material at one end with a burst square cyclic electric field signal of constant frequency, which generates a burst of ultrasonic sound that propagates through the water medium to the adjacent piezoelectric ceramic at the other end. Mechanical vibrations of a PZT piezoelectric ceramic are measured using a double-beam laser Doppler vibrometer to mimic the incident ultrasonic waves generated and received ultrasonic waves on the other end due to mechanical vibrations of a PZT. The measured ultrasonic sound wave signals are continuously compared to the applied cyclic electric field at both ends. The impedance matching networks are continuously tuned at both ends to eliminate electromechanical impedance mismatch to improve ultrasonic transmission and reception. The study delves into various physical, electrical, and acoustic properties of the PZT piezoelectric ceramics, such as the electromechanical coupling factor, acoustic coupling, and elasticity, among others. These properties are analyzed to identify potential factors contributing to the unusually high acoustic impedance in the water medium between the ceramics. Additionally, impedance-matching networks are investigated at both ends to offset the high signal attenuation and improve overall system performance. The findings will be reported in this paper.

Keywords: acoustic impedance, impedance mismatch, piezoelectric ceramics, ultrasonic sound

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Authors: Junhai Liao, Yansong Shen, Aibing Yu

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A 3D numerical model is developed to simulate the complicated in-furnace combustion phenomena in the lower part of an ironmaking blast furnace (BF) while using pulverized coal injection (PCI) technology to reduce the consumption of relatively expensive coke. The computational domain covers blowpipe-tuyere-raceway-coke bed in the BF. The model is validated against experimental data in terms of gaseous compositions and coal burnout. Parameters, such as coal properties and some key operational variables, play an important role on the performance of coal combustion. Their diverse effects on different combustion characteristics are examined in the domain, in terms of gas compositions, temperature, and burnout. The heat generated by the combustion of upgraded Victorian brown coal is able to meet the heating requirement of a BF, hence making upgraded brown coal injected into BF possible. It is evidenced that the model is suitable to investigate the mechanism of the PCI operation in a BF. Prediction results provide scientific insights to optimize and control of the PCI operation. This model cuts the cost to investigate and understand the comprehensive combustion phenomena of upgraded Victorian brown coal in a full-scale BF.

Keywords: blast furnace, numerical study, pulverized coal injection, Victorian brown coal

Procedia PDF Downloads 246

Authors: Wei-Neng Wang, Jhy-Yuan Shieh, Jhy-Hwa Chen, Juin-Jen Chang

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This paper incorporate tax evasion into a one-sector real business cycle (RBC) model to explores the quantitative interrelations between income tax rate and equilibrium (in)determinacy, and income tax rate is endogenously determined in order to balance the government budget. We find that the level of the effective income tax rate is key factor for equilibrium (in)determinacy, instead of the level of income tax rate in a tax evasion economy. Under an economy with tax evasion, the higher income tax rate is not sufficiently to lead to equilibrium indeterminate, it must combine with a necessary condition which is the lower fraction of tax evasion and that can result in agents' optimistic expectations to become self-fulfilling and sunspot fluctuation more likely to occur. On the other hand, an economy with tax evasion can see its macroeconomy become more stabilize, and a higher fraction of income tax evasion may has a stronger stabilizing effect.

Keywords: tax evasion, balanced-budget rule, equlibirium (in)determinacy, effective income tax rate

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Authors: Emilija Tribocka

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This contribution presents parts of an ongoing study of a diachronic relationship between two weak verb classes in Norwegian, the a-class (cf. the paradigm of ‘throw’: kasta – kastar – kasta – kasta) and the e-class (cf. the paradigm of ‘buy’: kjøpa – kjøper – kjøpte – kjøpt). The study investigates inflection class shifts between the two classes with Old Norse, the ancestor of Modern Norwegian, as a starting point. Examination of inflection in 38 verbs in four chosen dialect areas (106 places of attestations) demonstrates that the shifts from the a-class to the e-class are widespread to varying degrees in three out of four investigated areas and are more common than the shifts in the opposite direction. The diachronic productivity of the e-class is unexpected for several reasons. There is general agreement that type frequency is an important factor influencing productivity. The a-class (53% of all weak verbs) was more type frequent in Old Norse than the e-class (42% of all weak verbs). Thus, given the type frequency, the expansion of the e-class is unexpected. Furthermore, in the ‘core’ areas of expanded e-class inflection, the shifts disregard phonological principles creating forms with uncomfortable consonant clusters, e.g., fiskte instead of fiska, the preterit of fiska ‘fish’. Later on, these forms may be contracted, i.e., fiskte > fiste. In this contribution, two factors influencing the shifts are presented: phonological form and token frequency. Verbs with the stem ending in a consonant cluster, particularly when the cluster ends in -t, hardly ever shift to the e-class. As a matter of fact, verbs with this structure belonging to the e-class in Old Norse shift to the a-class in Modern Norwegian, e.g., ON e-class verb skipta ‘change’ shifts to the a-class. This shift occurs as a result of the lack of morpho-phonological transparency between the stem and the preterit suffix of the e-class, -te. As there is a phonological fusion between the stem ending in -t and the suffix beginning in -t, the transparent a-class inflection is chosen. Token frequency plays an important role in the shifts, too, in some dialects. In one of the investigated areas, the most token frequent verbs of the ON e-class remain in the e-class (e.g., høyra ‘hear’, leva ‘live’, kjøpa ‘buy’), while less frequent verbs may shift to the a-class. Furthermore, the results indicate that the shift from the a-class to the e-class occurs in some of the most token frequent verbs of the ON a-class in this area, e.g., lika ‘like’, lova ‘promise’, svara ‘answer’. The latter is unexpected as frequent items tend to remain stable. This study presents a case of unexpected productivity, demonstrating that minor patterns can grow and outdo major patterns. Thus, type frequency is not the only factor that determines productivity. The study addresses the role of phonological form and token frequency in the spread of inflection patterns.

Keywords: inflection class, productivity, token frequency, phonological form

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Authors: Istvan Csarnovics, Attila Bonyar, Miklos Veres, Laszlo Himics, Attila Csik, Judit Kaman, Julia Burunkova, Geza Szanto, Laszlo Balazs, Sandor Kokenyesi

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In this work, the performance of gold nanoparticles were investigated for stimulation of photosensitive materials for photonic applications. It was widely used for surface plasmon resonance experiments, not in the last place because of the manifestation of optical resonances in the visible spectral region. The localized surface plasmon resonance is rather easily observed in nanometer-sized metallic structures and widely used for measurements, sensing, in semiconductor devices and even in optical data storage. Firstly, gold nanoparticles on silica glass substrate satisfy the conditions for surface plasmon resonance in the green-red spectral range, where the chalcogenide glasses have the highest sensitivity. The gold nanostructures influence and enhance the optical, structural and volume changes and promote the exciton generation in gold nanoparticles/chalcogenide layer structure. The experimental results support the importance of localized electric fields in the photo-induced transformation of chalcogenide glasses as well as suggest new approaches to improve the performance of these optical recording media. Results may be utilized for direct, micrometre- or submicron size geometrical and optical pattern formation and used also for further development of the explanations of these effects in chalcogenide glasses. Besides of that, gold nanoparticles could be added to the organic light-sensitive material. The acrylate-based materials are frequently used for optical, holographic recording of optoelectronic elements due to photo-stimulated structural transformations. The holographic recording process and photo-polymerization effect could be enhanced by the localized plasmon field of the created gold nanostructures. Finally, gold nanoparticles widely used for electrochemical and optical sensor applications. Although these NPs can be synthesized in several ways, perhaps one of the simplest methods is the thermal annealing of pre-deposited thin films on glass or silicon surfaces. With this method, the parameters of the annealing process (time, temperature) and the pre-deposited thin film thickness influence and define the resulting size and distribution of the NPs on the surface. Localized surface plasmon resonance (LSPR) is a very sensitive optical phenomenon and can be utilized for a large variety of sensing purposes (chemical sensors, gas sensors, biosensors, etc.). Surface-enhanced Raman spectroscopy (SERS) is an analytical method which can significantly increase the yield of Raman scattering of target molecules adsorbed on the surface of metallic nanoparticles. The sensitivity of LSPR and SERS based devices is strongly depending on the used material and also on the size and geometry of the metallic nanoparticles. By controlling these parameters the plasmon absorption band can be tuned and the sensitivity can be optimized. The technological parameters of the generated gold nanoparticles were investigated and influence on the SERS and on the LSPR sensitivity was established. The LSPR sensitivity were simulated for gold nanocubes and nanospheres with MNPBEM Matlab toolbox. It was found that the enhancement factor (which characterize the increase in the peak shift for multi-particle arrangements compared to single-particle models) depends on the size of the nanoparticles and on the distance between the particles. This work was supported by GINOP- 2.3.2-15-2016-00041 project, which is co-financed by the European Union and European Social Fund. Istvan Csarnovics is grateful for the support through the New National Excellence Program of the Ministry of Human Capacities, supported by the ÚNKP-17-4 Attila Bonyár and Miklós Veres are grateful for the support of the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.

Keywords: light sensitive nanocomposites, metallic nanoparticles, photonic application, plasmonic nanostructures

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Fahad Ibrahim, Raphaël Akamavi

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Bangladesh has encountered several industrial disasters (e.g. fire and building collapse tragedies) leading to the loss of valuable human lives. Irrespective of various institutions’ making effort to improve the safety situation, industry compliance and safety behaviour have not yet been improved. Hence, one question remains, to what extent does the institutional elements efficient enough to make any difference in improving safety behaviours? Thus, this study explores the relationship between institutional perspective and safety performance. Structural equation modelling results, using survey data from 256 RMG workers’ of 128 garments manufacturing factories in Bangladesh, show that institutional facets strongly influence management safety commitment to induce workers participation in safety activities and reduce workplace accident rates. The study also found that by upholding industrial standards and inspecting the safety situations, institutions facets significantly and directly affect workers involvement in safety participations and rate of workplace accidents. Additionally, workers involvement to safety practices significantly predicts the safety environment of the workplace. Subsequently, our findings demonstrate that institutional culture, norms, and regulations enact play an important role in altering management commitment to set-up a safer workplace environment. As a result, when workers’ perceive their management having high level of commitment to safety, they are inspired to be involved more in the safety practices, which significantly alter the workplace safety situation and lessen injury experiences. Due to the fact that institutions have strong influence on management commitment, legislative members should endorse, regulate, and strictly monitor workplace safety laws to be exercised by the factory owners. Further, management should take initiatives for adopting OHS features and conceive strategic directions (i.e., set up safety committees, risk assessments, innovative training) for promoting a positive safety climate to provide a safe workplace environment. Arguably, an inclusive public-private partnership is recommended for ensuring better and safer workplace for RMG workers. However, as our data were under a cross-sectional design; the respondents’ perceptions might get changed over a period of time and hence, a longitudinal study is recommended. Finally, further research is needed to determine the impact of improvement mechanisms on workplace safety performance, such as how workplace design, safety training programs, and institutional enforcement policies protect the well-being of workers.

Keywords: institutional perspective, management commitment, safety participation, work injury, safety performance, occupational health and safety

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Authors: Tao Chen, ShiHua Liu, JiWei Zhang

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Assembly of the proton exchange membrane fuel cells (PEMFC) has a very important influence on its performance and efficiency. The various components of PEMFC stack are usually locked and fixed by bolts. Locking bolt will cause the deformation of the bipolar plate and the other components, which will affect directly the deformation degree of the integral parts of the PEMFC as well as the performance of PEMFC. This paper focuses on the object of three-cell stack of PEMFC. Finite element simulation is used to investigate the deformation of bipolar plate caused by quantity and layout of bolts, bolt locking pressure, and bolt locking sequence, etc. Finally, we made a conclusion that the optimal combination packaging scheme was adopted to assemble the fuel cell stack. The scheme was in use of 3.8 MPa locking pressure imposed on the fuel cell stack, type Ⅱ of four locking bolts and longitudinal locking method. The scheme was obtained by comparatively analyzing the overall displacement contour of PEMFC stack, absolute displacement curve of bipolar plate along the given three paths in the Z direction and the polarization curve of fuel cell. The research results are helpful for the fuel cell stack assembly.

Keywords: bipolar plate, deformation, finite element simulation, fuel cell, locking bolt

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Authors: Taleb Hosni Abderrahmane, Berga Abdelmadjid

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The development of numerical analysis and its application to geomechanics problems have provided geotechnical engineers with extremely powerful tools. One of the most important problems in geotechnical engineering is the slope stability assessment. It is a very difficult task due to several aspects such the nature of the problem, experimental consideration, monitoring, controlling, and assessment. The main objective of this paper is to perform a comparative numerical study between the following methods: The Limit Equilibrium (LEM), Finite Element (FEM), Limit Analysis (LAM) and Distinct Element (DEM). The comparison is conducted in terms of the safety factors and the critical slip surfaces. Through the results, we see the feasibility to analyse slope stability by many methods.

Keywords: comparison, factor of safety, geomechanics, numerical methods, slope analysis, slip surfaces

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Authors: Bahare Askarian, Suchithra Rajendran

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Maintaining the freshness and quality of perishable goods during distribution is a critical challenge for logistics companies. This study presents a comprehensive framework aimed at optimizing the distribution of perishable goods through a mathematical model of the Transportation Inventory Location Routing Problem (TILRP). The model incorporates the impact of product age on customer demand, addressing the complexities associated with inventory management and routing. To tackle this problem, we develop both simple and hybrid metaheuristic algorithms designed for small- and medium-scale scenarios. The hybrid algorithm combines Biogeographical Based Optimization (BBO) algorithms with local search techniques to enhance performance in small- and medium-scale scenarios, extending our approach to larger-scale challenges. Through extensive numerical simulations and sensitivity analyses across various scenarios, the performance of the proposed algorithms is evaluated, assessing their effectiveness in achieving optimal solutions. The results demonstrate that our algorithms significantly enhance distribution efficiency, offering valuable insights for logistics companies striving to improve their perishable goods supply chains.

Keywords: perishable goods, meta-heuristic algorithm, vehicle problem, inventory models

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Authors: Mulatu Kassie Birhanu

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Electrochemical reduction of CO₂ is an emerging and current issue for its conversion in to valuable product upon minimization of its atmospheric level for contribution of maintaining within the range of permissible limit. Among plenty of electro-catalysts gold and copper are efficient and effective catalysts, which are synthesized and applicable for this research work. The two metal catalysts were prepared in inert environment with different compositions through co-reduction process from their corresponding precursors and then by adding multi-walled carbon nano-tube as a supporter and enhanced the conductivity. The catalytic performance of CO₂ reduction for each composition was performed and resulted an outstanding catalytic activity with generation of high current density (70 mA/cm² at 0.91V vs. RHE) and relatively small onset potential. The catalytic performance, compositions, morphologies, structure and geometric arrangements were evaluated by electrochemical analysis (LSV, impedance, chronoamperometry & tafel plot), EDS, SEM and XAS respectively. The composite metals showed better selectivity of products and faradaic efficiencies due to the synergetic effects of the combined nano-particles in addition to the impact of grain size in reduction of CO₂. Carbon monoxide, hydrogen, formate and ethanol are the reduction products, which are detected and quantifiable by chromatographic techniques considering their physical state of each product.

Keywords: carbondioxide, faradaic efficiency, electrocatalyst, current density

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