Search results for: engine performance analysis

Authors: Venuka Kuruwita Arachchige Don, Mohamed Shaheen, Chris Goodier

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Aerated autoclaved concrete (AAC) is known for its lightweight, easy handling, high thermal insulation, and extremely porous structure. Investigation of pore behavior in AAC is crucial for characterizing the material, standardizing design and production techniques, enhancing the mechanical, durability, and thermal performance, studying the effectiveness of protective measures, and analyzing the effects of weather conditions. The significant details of pores are complicated to observe with acknowledged accuracy. The High-resolution Field Emission Scanning Electron Microscope (FESEM) image analysis is a promising technique for investigating the pore behavior and density of AAC, which is adopted in this study. Mercury intrusion porosimeter and gas pycnometer were employed to characterize porosity distribution and density parameters. The analysis considered three different densities of AAC blocks and three layers in the altitude direction within each block. A set of understandings was presented to extract and analyze the details of pore shape, pore size, pore connectivity, and pore percentages from FESEM images of AAC. Average pore behavior outcomes per unit area were presented. Comparison of porosity distribution and density parameters revealed significant variations. FESEM imaging offered unparalleled insights into porosity behavior, surpassing the capabilities of other techniques. The analysis conducted from a multi-staged approach provides porosity percentage occupied by various pore categories, total porosity, variation of pore distribution compared to AAC densities and layers, number of two-dimensional and three-dimensional pores, variation of apparent and matrix densities concerning pore behaviors, variation of pore behavior with respect to aluminum content, and relationship among shape, diameter, connectivity, and percentage in each pore classification.

Keywords: autoclaved aerated concrete, density, imaging technique, microstructure, porosity behavior

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Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

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The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

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Authors: Zakarya Kourdi, Mohammed Khaouani, Benyounes Bouazza, Ahlam Guen-Bouazza, Amine Boursali

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In this paper, we have evaluated the thermal effect for high electron mobility transistors (HEMTs) heterostructure InAlN/GaN with a gate length 30nm high-performance. It also shows the analysis and simulated these devices, and how can be used in different application. The simulator Tcad-Silvaco software has used for predictive results good for the DC, AC and RF characteristic, Devices offered max drain current 0.67A; transconductance is 720 mS/mm the unilateral power gain of 180 dB. A cutoff frequency of 385 GHz, and max frequency 810 GHz These results confirm the feasibility of using HEMTs with InAlN/GaN in high power amplifiers, as well as thermal places.

Keywords: HEMT, Thermal Effect, Silvaco, InAlN/GaN

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Authors: Ebrahim Sabermaash Eshghi, Donna Sandsmark

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In changing modern economic conditions of the world, one the most important issues facing managers of firms, is increasing the sales and profitability through sales of newly developed products. This is while purpose of decreasing unnecessary costs is one of the most essential programs of smart managers for more implementation with new conditions in current business. In modern life, condition of misgiving is dominant in all of the industries. Accordingly, in this research, influence of different aspects of presenting products to the market is investigated. This study is done through a Quantitative-Qualitative (Interviews and Questionnaire) approach. In sum, 103 of informed managers and experts of Pars-Khazar Company have been examined through census. Validity of measurement tools was approved through judgments of experts. Reliability of tools was gained through Cronbach's alpha coefficient in size of 0.930 and in sum, validity and reliability of tools were approved generally. Results of regression test revealed that the influence of all aspects of product introduction supported the performance of product, positively and significantly. In addition that influence of two new factors raised from the interview, namely Human Resource Management and Management of product’s pre-test on performance of products was approved.

Keywords: introducing products, performance, home appliances, price, advertisement, production

Procedia PDF Downloads 205

Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui

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In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.

Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas

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Authors: Haiyoung Jung, Mi Joung Leem, Sun Hwa Lee

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Background & Objective: Glucose-6-phosphate dehydrogenase (G6PD) deficiency is a genetic abnormality that results in an inadequate amount of G6PD, leading to increased susceptibility of red blood cells to reactive oxygen species and hemolysis. The present study aimed to evaluate the careSTARTTM S1 analyzer for measuring G6PD activity to hemoglobin (Hb) ratio. Methods: Precision for G6PD activity and hemoglobin measurement was evaluated using control materials with two levels on five repeated runs per day for five days. The analytic performance of the careSTARTTM S1 analyzer was compared with spectrophotometry in 40 patient samples. Reference ranges suggested by the manufacturer were validated in 20 healthy males and females each. Results: The careSTARTTM S1 analyzer demonstrated precision of 6.0% for low-level (14~45 U/dL) and 2.7% for high-level (60~90 U/dL) control in G6PD activity, and 1.4% in hemoglobin (7.9~16.3 u/g Hb). A comparison study of G6PD to Hb ratio between the careSTARTTM S1 analyzer and spectrophotometry showed an average difference of 29.1% with a positive bias of the careSTARTTM S1 analyzer. All normal samples from the healthy population were validated for the suggested reference range for males (≥2.19 U/g Hb) and females (≥5.83 U/g Hb). Conclusion: The careSTARTTM S1 analyzer demonstrated good analytical performance and can replace the current spectrophotometric measurement of G6PD enzyme activity. In the aspect of the management of clinical laboratories, it can be a reasonable option as a point-of-care analyzer with minimal handling of samples and reagents, in addition to the automatic calculation of the ratio of measured G6PD activity and Hb concentration, to minimize any clerical errors involved with manual calculation.

Keywords: POCT, G6PD, performance evaluation, careSTART

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Authors: Philipp Stehle, Dragoljub Vrankovic, Montaha Anjass

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Due to its high availability and extremely high specific capacity, silicon (Si) is the most promising anode material for next generation lithium-ion batteries (LIBs). However, Si anodes are suffering from high volume changes during cycling causing unstable solid-electrolyte interface (SEI). One approach for mitigation of these effects is to embed Si particles into a carbon matrix to create silicon/carbon composites (Si/C). These typically show more stable electrochemical performance than bare silicon materials. Nevertheless, the same failure mechanisms mentioned earlier appear in a less pronounced form. In this work, we further improved the cycling performance of two commercially available Si/C materials by coating thin metal oxide films of different thicknesses on the powders via Atomic Layer Deposition (ALD). The coated powders were analyzed via ICP-OES and AFM measurements. Si/C-graphite anodes with automotive-relevant loadings (~3.5 mAh/cm2) were processed out of the materials and tested in half coin cells (HCCs) and full pouch cells (FPCs). During long-term cycling in FPCs, a significant improvement was observed for some of the ALD-coated materials. After 500 cycles, the capacity retention was already up to 10% higher compared to the pristine materials. Cycling of the FPCs continued until they reached a state of health (SOH) of 80%. By this point, up to the triple number of cycles were achieved by ALD-coated compared to pristine anodes. Post-mortem analysis via various methods was carried out to evaluate the differences in SEI formation and thicknesses.

Keywords: silicon anodes, li-ion batteries, atomic layer deposition, silicon-carbon composites, surface coatings

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Authors: Nabilah Zainal Abidin, Fawazul Khair Ibrahim, Raja Nafida Raja Shahminan

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This paper discusses on how componential analysis is used in architecture, mainly in determining the absence and presence of furniture in Traditional Malay Houses. The house samples were retrieved from the reports archived by the Centre of Built Environment in the Malay World (KALAM) of Universiti Teknologi Malaysia (UTM). Findings from the analysis indicate that furniture available in the spaces of the houses is determined by the culture of the people and the availability of certain furniture is influenced by the activities that are carried out within the space.

Keywords: componential analysis, sustainable furniture, traditional malay house

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Authors: Siham Rahoui, Amr Mahfouz, Amr Arisha

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In a highly competitive environment characterised by uncertainty and disruptions, such as the recent COVID-19 outbreak, supply chains (SC) face the challenge of maintaining their cost at minimum levels while continuing to provide customers with high-quality products and services. More importantly, businesses in such an economic context strive to maintain survival by keeping the cost of undertaken activities (such as logistics) low and in-house. To do so, managers need to understand the costs associated with different products and services in order to have a clear vision of the SC performance, maintain profitability levels, and make strategic decisions. In this context, SC literature explored different costing models that sought to determine the costs of undertaking supply chain-related activities. While some cost accounting techniques have been extensively explored in the SC context, more contributions are needed to explore the potential of time driven activity-based costing (TDABC). More specifically, more applications are needed in the manufacturing context of the SC, where the debate is ongoing. The aim of the study is to assess the capability of the technique to assess the operational performance of the logistics function. Through a case study methodology applied to a manufacturing company operating in the automotive industry, TDABC evaluates the efficiency of the current configuration and its logistics processes. The study shows that monitoring the process efficiency and cost efficiency leads to strategic decisions that contributed to improve the overall efficiency of the logistics processes.

Keywords: efficiency, operational performance, supply chain costing, time driven activity based costing

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Authors: Desplanches Maxime

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

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

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Authors: Mohammad Reza Fazeli

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Nowadays, the fourth industry, known as the digital transformation of industries, is seen as one of the top subjects in the history of structural revolution, which has led to the high-tech and tactical dominance of the organization. In the face of these profits, the undefined and non-transparent nature of the after-effects of investing in digital transformation has hindered many organizations from attempting this area of this industry. One of the important frameworks in the field of understanding digital transformation in all organizations is the maturity model of digital transformation. This model includes two main parts of digital transformation maturity dimensions and digital transformation maturity stages. Mediating factors of digital maturity and organizational performance at the individual (e.g., motivations, attitudes) and at the organizational level (e.g., organizational culture) should be considered. For successful technology adoption processes, organizational development and human resources must go hand in hand and be supported by a sound communication strategy. Maturity models are developed to help organizations by providing broad guidance and a roadmap for improvement. However, as a result of a systematic review of the literature and its analysis, it was observed that none of the 18 maturity models in the field of digital transformation fully meet all the criteria of appropriateness, completeness, clarity, and objectivity. A maturity assessment framework potentially helps systematize assessment processes that create opportunities for change in processes and organizations enabled by digital initiatives and long-term improvements at the project portfolio level. Cultural characteristics reflecting digital culture are not systematically integrated, and specific digital maturity models for the service sector are less clearly presented. It is also clearly evident that research on the maturity of digital transformation as a holistic concept is scarce and needs more attention in future research.

Keywords: digital transformation, organizational performance, maturity models, maturity assessment

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Authors: Lee Siong Wee, Tan Kang Hai, Yang En-Hua

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This paper presents the results of an experimental study undertaken to evaluate the local bond stress-slip response of short embedment of reinforcing bars in normal concrete (NC) and high performance fiber reinforced cement composites (HPFRCC) blocks. Long embedment was investigated as well to gain insights on the distribution of strain, slip, bar stress and bond stress along the bar especially in post-yield range. A total of 12 specimens were tested, by means of pull-out of the reinforcing bars from concrete blocks. It was found that the enhancement of local bond strength can be reached up to 50% and ductility of the bond behavior was improved significantly if HPFRCC is used. Also, under a constant strain at loaded end, HPFRCC has delayed yielding of bars at other location from the loaded end. Hence, the reduction of bond stress was slower for HPFRCC in comparison with NC. Due to the same reason, the total slips at loaded end for HPFRCC was smaller than NC as expected. Test results indicated that HPFRCC has better bond slip behavior which makes it a suitable material to be employed in anchorage zone such as beam-column joints.

Keywords: bond stress, high performance fiber reinforced cement composites, slip, strain

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Authors: Julie Anne Braun, Leonardo D. da Fonseca, Gerson C. Parreira, Ricardo J. E. Andrade

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Polyurethanes (PU) are multifunctional polymers used across various industries. In construction, thermosetting polyurethanes are applied as coatings for flooring, paints, and waterproofing. They are widely specified in Brazil for waterproofing concrete structures like roof slabs and parking decks. Applied to concrete, they form a fully adhered membrane, providing a protective barrier with low water absorption, high chemical resistance, impermeability to liquids, and low vapor permeability. Their mechanical properties, including tensile strength (1 to 35 MPa) and Shore A hardness (83 to 88), depend on resin molecular weight and functionality, often using Methylene diphenyl diisocyanate. PU production, reliant on fossil-derived isocyanates and polyols, contributes significantly to carbon emissions. Sustainable alternatives, such as biopolyurethanes from renewable sources, are needed. Castor oil is a viable option for synthesizing sustainable polyurethanes. As a bio-based feedstock, castor oil is extensively cultivated in Brazil, making it a feasible option for the national market and ranking third internationally. This study aims to develop and characterize castor oil-based biopolyurethane for high-performance waterproofing and coating applications. A comparative analysis between castor oil-based PU and polyether polyol-based PU was conducted. Mechanical tests (tensile strength, Shore A hardness, abrasion resistance) and surface properties (contact angle, water absorption) were evaluated. Thermal, chemical, and morphological properties were assessed using thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The results demonstrated that both polyurethanes exhibited high mechanical strength. Specifically, the tensile strength for castor oil-based PU was 19.18 MPa, compared to 12.94 MPa for polyether polyol-based PU. Similarly, the elongation values were 146.90% for castor oil-based PU and 135.50% for polyether polyol-based PU. Both materials exhibited satisfactory performance in terms of abrasion resistance, with mass loss of 0.067% for castor oil PU and 0.043% for polyether polyol PU and Shore A hardness values of 89 and 86, respectively, indicating high surface hardness. The results of the water absorption and contact angle tests confirmed the hydrophilic nature of polyether polyol PU, with a contact angle of 58.73° and water absorption of 2.53%. Conversely, the castor oil-based PU exhibited hydrophobic properties, with a contact angle of 81.05° and water absorption of 0.45%. The results of the FTIR analysis indicated the absence of a peak around 2275 cm-1, which suggests that all of the NCO groups were consumed in the stoichiometric reaction. This conclusion is supported by the high mechanical test results. The TGA results indicated that polyether polyol PU demonstrated superior thermal stability, exhibiting a mass loss of 13% at the initial transition (around 310°C), in comparison to castor oil-based PU, which experienced a higher initial mass loss of 25% at 335°C. In summary, castor oil-based PU demonstrated mechanical properties comparable to polyether polyol PU, making it suitable for applications such as trafficable coatings. However, its higher hydrophobicity makes it more promising for watertightness. Increasing environmental concerns necessitate reducing reliance on non-renewable resources and mitigating the environmental impacts of polyurethane production. Castor oil is a viable option for sustainable polyurethanes, aligning with emission reduction goals and responsible use of natural resources.

Keywords: polyurethane, castor oil, sustainable, waterproofing, construction industry

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Authors: Chiara De Amicis, Sonia Falconieri, Mesut Tastan

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In this study, we analyze the language employed by Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs) during earnings conference calls from a gender perspective. We find evidences that conference calls held by female CEOs and/or CFOs exhibit a higher level of optimism compared to conference calls held by male CEOs and/or CFOs. Moreover, female managers tend to present and discuss firm performances with less vagueness as compared to their male colleagues. We then observe the market reaction around each earnings conference call: while manager optimism is perceived as a good signal by investors, manager vagueness significantly dampens the market reaction around the call. Whether the gender of the CEO and/or the CFO delivering the conference call affects investors’ perceptions about the firm performance is still an open question. Some evidences show that the language employed by female managers conveys more valuable information for market participants as compared to the language employed by their male counterparts. This study contributes to a growing literature in finance and accounting that uses textual analysis to assess the informativeness of corporate disclosure. To our knowledge, this is the first paper that aims at answering the question whether the gender of firm’s top managers does matter when it comes to assess the informativeness of corporate spoken communication. We believe that our results will be of relevance for future research in the field. Moreover, our evidence may be used in support of the debate if a larger participation by women in the management of companies should be encouraged or not.

Keywords: conference calls, even study, gender, market reaction, textual analysis

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Authors: G. Kloudova, M. Stehlik

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Optimal human performance is a key goal in the professional setting of military pilots, which is a highly challenging atmosphere. The aviation environment requires substantial cognitive effort and is rich in potential stressors. Therefore, it is important to analyze variables such as mental workload to ensure safe conditions. Pilot mental workload could be measured using several tools, but most of them are very subjective. This paper details research conducted with military pilots using psychophysiological methods such as electroencephalography (EEG) and heart rate (HR) monitoring. The data were measured in a simulator as well as under real flight conditions. All of the pilots were exposed to highly demanding flight tasks and showed big individual response differences. On that basis, the individual pattern for each pilot was created counting different EEG features and heart rate variations. Later on, it was possible to distinguish the most difficult flight tasks for each pilot that should be more extensively trained. For training purposes, an application was developed for the instructors to decide which of the specific tasks to focus on during follow-up training. This complex system can help instructors detect the mentally demanding parts of the flight and enhance the training of military pilots to achieve optimal performance.

Keywords: cognitive effort, human performance, military pilots, psychophysiological methods

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Authors: Akan C. Offong, E. J. Anthony, Vasilije Manovic

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A modified steady-state numerical model is developed for the electrochemical reduction of CO₂ to formic acid. The numerical model achieves a CD (current density) (~60 mA/cm²), FE-faradaic efficiency (~98%) and conversion (~80%) for CO₂ electro-reduction to formic acid in a microfluidic cell. The model integrates charge and species transport, mass conservation, and momentum with electrochemistry. Specifically, the influences of Bi-Sn based nanoparticle catalyst (on the cathode surface) at different mole fractions and 1-ethyl-3-methyl imidazolium tetra-fluoroborate ([EMIM][BF₄]) electrolyte, on CD, FE and CO₂ conversion to formic acid is studied. The reaction is carried out at a constant concentration of electrolyte (85% v/v., [EMIM][BF₄]). Based on the mass transfer characteristics analysis (concentration contours), mole ratio 0.5:0.5 Bi-Sn catalyst displays the highest CO₂ mole consumption in the cathode gas channel. After validating with experimental data (polarisation curves) from literature, extensive simulations reveal performance measure: CD, FE and CO₂ conversion. Increasing the negative cathode potential increases the current densities for both formic acid and H₂ formations. However, H₂ formations are minimal as a result of insufficient hydrogen ions in the ionic liquid electrolyte. Moreover, the limited hydrogen ions have a negative effect on formic acid CD. As CO₂ flow rate increases, CD, FE and CO₂ conversion increases.

Keywords: carbon dioxide, electro-chemical reduction, ionic liquids, microfluidics, modelling

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

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Authors: Anil Anand

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Despite enormous strides made during the past decade, particularly with the adoption and expansion of community policing, there remains much that police leaders can do to improve police-public relations. The urgency is particularly evident in cities across the United States and Europe where an increasing number of police interactions over the past few years have ignited large, sometimes even national, protests against police policy and strategy, highlighting a gap between what police leaders feel they have archived in terms of public satisfaction, support, and legitimacy and the perception of bias among many marginalized communities. The decision on which one policing strategy is chosen over another, how many resources are allocated, and how strenuously the policy is applied resides primarily with the police and the units and subunits tasked with its enforcement. The scope and opportunity for police officers in impacting social attitudes and social policy are important elements that cannot be overstated. How do police leaders, for instance, decide when to apply one strategy—say community-based policing—over another, like intelligence-led policing? How do police leaders measure performance and success? Should these measures be based on quantitative preferences over qualitative, or should the preference be based on some other criteria? And how do police leaders define, allow, and control discretionary decision-making? Mending Broken Fences Policing provides police and security services leaders with a model based on social cohesion, that incorporates intelligence-led and community policing (IP-CP), supplemented by a quality/quantity/crime (QQC) framework to provide a four-step process for the articulable application of police intervention, performance measurement, and application of discretion.

Keywords: social cohesion, quantitative performance measurement, qualitative performance measurement, sustainable leadership

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Authors: Mohammed Idaan Hassan Al-Majidi

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An analysis of twenty one assorted brands of vegetable oils in Babylon Iraq, reveals varying levels of cholesterol content. Cholesterol was found to be present in most of the oil brands sampled using three standard methods. Cholesterol was detected in seventeen of the vegetable oil brands with concentration of less than 1 mg/ml while seven of the oil brands had cholesterol concentrations ranging between 1-4 mg/ml. Low iodine values were obtained in four of the vegetable oil brands and three of them had high acid values. High performance liquid chromatography (HPLC) confirmed the presence of cholesterol at varying concentrations in all the oil brands and gave the lowest detectable cholesterol values in all the oil brands. The Laser brand made from rapeseed had the highest cholesterol concentration of 3.2 mg/ml while Grand brand made from groundnuts had the least concentration (0.12 mg/ml) of cholesterol using HPLC analysis. Leibermann-Burchard method showed that Gino brand from palm kernel had the least concentration of cholesterol (3.86 mg/ml ±0.032) and the highest concentration of 3.996 mg/ml ±0.0404 was obtained in Sesame seed oil brand. This report is important in view of health implications of cholesterol in our diets. Consequently, we have been able to show that there is no cholesterol free oil in the market as shown on the vegetable oil brand labels. Therefore, companies producing and marketing vegetable oils are enjoined to desist from misleading the public by labeling their products as “cholesterol free”. They should indicate the amount of cholesterol present in the vegetable oil, no matter how small the quantity may be.

Keywords: vegetable oils, heart diseases, leibermann-burchard, cholesterol

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Authors: Eftychia Kessopoulou, Styliani Xanthopoulou, Ypatia Theodorakioglou, George Tsiotras, Katerina Gotzamani

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Public sector managers frequently herald that implementing best practices as a set of standards, may lead to superior organizational performance. However, recent research questions the objectification of best practices, highlighting: a) the inability of public sector organizations to develop innovative administrative practices, as well as b) the adoption of stereotypical renowned practices inculcated in the public sector by international governance bodies. The process through which organizations construe what a best practice is, still remains a black box that is yet to be investigated, given the trend of continuous changes in public sector performance, as well as the burgeoning interest of sharing popular administrative practices put forward by international bodies. This study aims to describe and understand how organizational best practices are constructed by public sector performance management teams, like benchmarkers, during the benchmarking-mediated performance improvement process and what mechanisms enable this construction. A critical realist action research methodology is employed, starting from a description of various approaches on best practice nature when a benchmarking-mediated performance improvement initiative, such as the Common Assessment Framework, is applied. Firstly, we observed the benchmarker’s management process of best practices in a public organization, so as to map their theories-in-use. As a second step we contextualized best administrative practices by reflecting the different perspectives emerged from the previous stage on the design and implementation of an interview protocol. We used this protocol to conduct 30 semi-structured interviews with “best practice” process owners, in order to examine their experiences and performance needs. Previous research on best practices has shown that needs and intentions of benchmarkers cannot be detached from the causal mechanisms of the various contexts in which they work. Such causal mechanisms can be found in: a) process owner capabilities, b) the structural context of the organization, and c) state regulations. Therefore, we developed an interview protocol theoretically informed in the first part to spot causal mechanisms suggested by previous research studies and supplemented it with questions regarding the provision of best practice support from the government. Findings of this work include: a) a causal account of the nature of best administrative practices in the Greek public sector that shed light on explaining their management, b) a description of the various contexts affecting best practice conceptualization, and c) a description of how their interplay changed the organization’s best practice management.

Keywords: benchmarking, action research, critical realism, best practices, public sector

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Authors: Antonio Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also analyses the strategy follow in the innovation process, as suggested by Freeman and Soete, and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. Can conclude that the Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: footwear, innovation, “low-tech” industry, Oslo manual

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Authors: R. Hosny, Mahmoud F. Mubarak, Heba M. Salem, Asmaa A. Abdelrahman

Abstract:

Oilfield scaling is a major problem in the oil and gas industry. Scale issues cost the industry millions of dollars in damage and lost production every year. One of the main causes of global production decline is scale. In this study, solid scale inhibitors based on silver tungstate loaded KIT-6 were synthesized and evaluated in both static and scale inhibition modeling. The silver tungstate loaded KIT-6 catalysts were synthesized via a simple impregnated method using 3D mesoporous KIT-6 as support. The synthesized materials were characterized using wide and low XRD, N2 adsorption–desorption analysis, TGA analysis, and FTIR, SEM, and XPS analysis. The scale inhibition efficiency of the synthesized materials was evaluated using a static scale inhibition test. The results of this study demonstrate the potential application of silver tungstate-loaded KIT-6 solid scale inhibitors for the oil and gas industry. The results of this study will contribute to the development of new and innovative solid scale inhibitors based on silver tungstate-loaded KIT-6. The inhibition efficiency of the scale inhibitor increases, and calcite scale inhibitor decreases with increasing pH (2 to8), it proposes that the scale inhibitor was more effective under alkaline conditions. An inhibition efficiency of 99% on calcium carbonate can be achieved at the optimal dosage of 7.5 ppm at 55oC, indicating that the scale inhibitor exhibits a relatively good inhibition performance on calcium carbonate. The use of these materials can potentially lead to more efficient and cost-effective solutions for scaling inhibition in various industrial processes.

Keywords: produced water treatment, solid scale inhibitors, calcite, silver tungestate, 3 D mesoporous KIT-6, oilfield scales, adsorption

Procedia PDF Downloads 138

Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

Abstract:

In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

Procedia PDF Downloads 218

Authors: Fabrizio Ascione, Martina Borrelli, Rosa Francesca De Masi, Silvia Ruggiero, Giuseppe Peter Vanoli

Abstract:

The refurbishment of public buildings is one of the key factors of energy efficiency policy of European States. Educational buildings account for the largest share of the oldest edifice with interesting potentialities for demonstrating best practice with regards to high performance and low and zero-carbon design and for becoming exemplar cases within the community. In this context, this paper discusses the critical issue of dealing the energy refurbishment of a university building in heating dominated climate of South Italy. More in detail, the importance of using validated models will be examined exhaustively by proposing an analysis on uncertainties due to modelling assumptions mainly referring to the adoption of stochastic schedules for occupant behavior and equipment or lighting usage. Indeed, today, the great part of commercial tools provides to designers a library of possible schedules with which thermal zones can be described. Very often, the users do not pay close attention to diversify thermal zones and to modify or to adapt predefined profiles, and results of designing are affected positively or negatively without any alarm about it. Data such as occupancy schedules, internal loads and the interaction between people and windows or plant systems, represent some of the largest variables during the energy modelling and to understand calibration results. This is mainly due to the adoption of discrete standardized and conventional schedules with important consequences on the prevision of the energy consumptions. The problem is surely difficult to examine and to solve. In this paper, a sensitivity analysis is presented, to understand what is the order of magnitude of error that is committed by varying the deterministic schedules used for occupation, internal load, and lighting system. This could be a typical uncertainty for a case study as the presented one where there is not a regulation system for the HVAC system thus the occupant cannot interact with it. More in detail, starting from adopted schedules, created according to questioner’ s responses and that has allowed a good calibration of energy simulation model, several different scenarios are tested. Two type of analysis are presented: the reference building is compared with these scenarios in term of percentage difference on the projected total electric energy need and natural gas request. Then the different entries of consumption are analyzed and for more interesting cases also the comparison between calibration indexes. Moreover, for the optimal refurbishment solution, the same simulations are done. The variation on the provision of energy saving and global cost reduction is evidenced. This parametric study wants to underline the effect on performance indexes evaluation of the modelling assumptions during the description of thermal zones.

Keywords: energy simulation, modelling calibration, occupant behavior, university building

Procedia PDF Downloads 134

Authors: Praveen Battula

Abstract:

Any high performance car has the tendency to over steer and Understeer under slippery conditions, An Electronic Stability Control System is needed under these conditions to regulate the steering of the car. It uses Anti-Lock Braking System (ABS) and Traction Control and Wheel Speed Sensor, Steering Angle Sensor, Rotational Speed Sensors to correct the problems. The focus of this paper is to improve the driving dynamics and safety by controlling the forces applied on each wheel. ESC Control the Yaw Stability, traction controls the Roll Stability, where actually the vehicle slip rate and lateral acceleration is controlled. ESC uses differential braking on all four brakes independently to control the vehicle’s motion. A mathematical model is developed in Simulink for the FlexRay based Electronic Stability Control. Vehicle steering is developed using Neuro Fuzzy Logic Controller. 7 Degrees of Freedom Vehicle Model is used as a Plant Model using dSpace autobox. The Performance of the system is assessed using two different road Scenarios, Vehicle Control under standard maneuvering conditions. The entire system is set using Dspace Control Desk. Results are provided by comparison of how a Vehicle with and without Electronic Stability Control which shows an improved performance in control.

Keywords: ESC, flexray, chassis control, steering, neuro fuzzy, vehicle dynamics

Procedia PDF Downloads 441

Authors: Mohamed Gar Alalm

Abstract:

This study aims to investigate various operating conditions that affect the performance of the electro-Fenton process for degradation of pesticides. Stainless steel electrodes were utilized in the electro-Fenton cell due to their relatively low cost. The favored conditions of current intensity, pH, iron loading, and pesticide concentration were deeply discussed. Complete removal of pesticide was attained at the optimum conditions. The degradation kinetics were described by pseudo- first-order pattern. In addition, a response surface model was developed to describe the performance of electro-Fenton process under different operational conditions. The model indicated that the coefficient of determination was (R² = 0.995).

Keywords: electro-Fenton, stainless steel, pesticide, wastewater

Procedia PDF Downloads 137

Authors: Nabil Shawkat, Jamil Saquer

Abstract:

Social media has accelerated our ability to engage with others and eliminated many communication barriers. On the other hand, the widespread use of social media resulted in an increase in online hate speech. This has drastic impacts on vulnerable individuals and societies. Therefore, it is critical to detect hate speech to prevent innocent users and vulnerable communities from becoming victims of hate speech. We investigate the performance of different deep learning and machine learning algorithms on three different datasets. Our results show that the BERT model gives the best performance among all the models by achieving an F1-score of 90.6% on one of the datasets and F1-scores of 89.7% and 88.2% on the other two datasets.

Keywords: hate speech, machine learning, deep learning, abusive words, social media, text classification

Procedia PDF Downloads 126

Authors: J. H. Lv, W. Z. Wang, S.W. Liu

Abstract:

The major concern in the aviation industry is the flight safety. Although great effort has been put onto the development of material and system reliability, the failure cases of fatal accidents still occur nowadays. Due to the complexity of the aviation system, and the interaction among the failure components, the failure analysis of the related equipment is a little difficult. This study focuses on surveying the failure cases in aviation, which are extracted from failure analysis journals, including Engineering Failure Analysis and Case studies in Engineering Failure Analysis, in order to obtain the failure sensitive factors or failure sensitive parts. The analytical results show that, among the failure cases, fatigue failure is the largest in number of occurrence. The most failed components are the disk, blade, landing gear, bearing, and fastener. The frequently failed materials consist of steel, aluminum alloy, superalloy, and titanium alloy. Therefore, in order to assure the safety in aviation, more attention should be paid to the fatigue failures.

Keywords: aerospace, disk, failure analysis, fatigue

Procedia PDF Downloads 325

Authors: Jennifer E. Lynette

Abstract:

This study describes the development process of a methodological framework for quality standards used to measure the efficiency and quality of response efforts of trained personnel at emergency events. This paper describes the techniques used to develop the initial framework and its potential application to professions under the broader field of emergency management. The example described in detail in this paper applies the framework specifically to fire response activities by firefighters. Within the quality standards framework, the fire response process is chronologically mapped. Individual variables within the sequence of events are identified. Through in-person data collection, questionnaires, interviews, and the expansion of the incident reporting system, this study identifies and categorizes previously unrecorded variables involved in the response phase of a fire. Following a data analysis of each variable using a quantitative or qualitative assessment, the variables are ranked pertaining to the magnitude of their impact to the event outcome. Among others, key indicators of quality performance in the analysis involve decision communication, resource utilization, response techniques, and response time. Through the application of this framework and subsequent utilization of quality standards indicators, there is potential to increase efficiency in the response phase of an emergency event; thereby saving additional lives, property, and resources.

Keywords: emergency management, fire, quality standards, response

Procedia PDF Downloads 305

Authors: Assad Maalouf, Lunjin Lu, James Lynott

Abstract:

We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

Procedia PDF Downloads 176