Search results for: engine performance analysis

Authors: Karima Megdouli

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The ejector, a central element within the CO₂ transcritical ejection refrigeration system, holds significant importance in enhancing refrigeration capacity and minimizing compressor power usage. This study's objective is to introduce a technique for enhancing the effectiveness of the CO₂ transcritical two-phase ejector, utilizing Taguchi and ANOVA analysis. The investigation delves into the impact of geometric parameters, secondary flow temperature, and primary flow pressure on the efficiency of the ejector. Results indicate that employing a combination of Taguchi and ANOVA offers increased reliability and superior performance when optimizing the design of the CO₂ two-phase ejector.

Keywords: ejector, supersonic, Taguchi, ANOVA, optimization

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Authors: Sun-Hee Lee, Amanda Kraley

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The “MeToo” movement is a social movement against sexual abuse and harassment. Though the hashtag went viral in 2017 following different cultural flashpoints in different countries, the initial response was quiet in South Korea. This radically changed in January 2018, when a high-ranking senior prosecutor, Seo Ji-hyun, gave a televised interview discussing being sexually assaulted by a colleague. Acknowledging public anger, particularly among women, on the long-existing problems of sexual harassment and abuse, the South Korean media have focused on several high-profile cases. Analyzing the media representation of these cases is a window into the evolving South Korean discourse around “MeToo.” This study presents a linguistic analysis of “MeToo” discourse in South Korea by utilizing a corpus-based approach. The term corpus (pl. corpora) is used to refer to electronic language data, that is, any collection of recorded instances of spoken or written language. A “MeToo” corpus has been collected by extracting newspaper articles containing the keyword “MeToo” from BIGKinds, big data analysis, and service and Nexis Uni, an online academic database search engine, to conduct this language analysis. The corpus analysis explores how Korean media represent accusers and the accused, victims and perpetrators. The extracted data includes 5,885 articles from four broadsheet newspapers (Chosun, JoongAng, Hangyore, and Kyunghyang) and 88 articles from two Korea-based English newspapers (Korea Times and Korea Herald) between January 2017 and November 2020. The information includes basic data analysis with respect to keyword frequency and network analysis and adds refined examinations of select corpus samples through naming strategies, semantic relations, and pragmatic properties. Along with the exponential increase of the number of articles containing the keyword “MeToo” from 104 articles in 2017 to 3,546 articles in 2018, the network and keyword analysis highlights ‘US,’ ‘Harvey Weinstein’, and ‘Hollywood,’ as keywords for 2017, with articles in 2018 highlighting ‘Seo Ji-Hyun, ‘politics,’ ‘President Moon,’ ‘An Ui-Jeong, ‘Lee Yoon-taek’ (the names of perpetrators), and ‘(Korean) society.’ This outcome demonstrates the shift of media focus from international affairs to domestic cases. Another crucial finding is that word ‘defamation’ is widely distributed in the “MeToo” corpus. This relates to the South Korean legal system, in which a person who defames another by publicly alleging information detrimental to their reputation—factual or fabricated—is punishable by law (Article 307 of the Criminal Act of Korea). If the defamation occurs on the internet, it is subject to aggravated punishment under the Act on Promotion of Information and Communications Network Utilization and Information Protection. These laws, in particular, have been used against accusers who have publicly come forward in the wake of “MeToo” in South Korea, adding an extra dimension of risk. This corpus analysis of “MeToo” newspaper articles contributes to the analysis of the media representation of the “MeToo” movement and sheds light on the shifting landscape of gender relations in the public sphere in South Korea.

Keywords: corpus linguistics, MeToo, newspapers, South Korea

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Authors: Ogunwole Cecilia Oluwakemi, Wahid Damilola Olanipekun, Omoyele Olufemi Samuel, Timothy Ayomitunde Aderemi

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The issues relating to corporate governance in both locally and internationally managed firms cannot be overemphasized because the lack of efficient corporate governance could orchestrate serious problems in any organization. Against this backdrop, this study examines the nexus between corporate governance and performance of firms from 2012 to 2020, using the case study of the Nigerian stock exchange. Consequently, data was collected from forty (40) listed firms on the Nigerian Stock Exchange. The study employed a fixed effect technique of estimation to address the objective of the study. It was discovered from the study that the influence of corporate governance components such as gender diversity, board independence and managerial ownership led to a significant positive impact on the performance of the firms under the investigation. In view of the above finding, this study makes the following recommendations for the policymakers in Nigeria that anytime the goal of the policymakers is the improvement of performance of the listed firms in the Nigerian stock exchange, board independence and a balance in the inclusion of male and female among the board of directors should be encouraged in these firms.

Keywords: corporate, governance, firms, performance, Nigeria, stock, exchange

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Authors: Balogun Azeez Olawale, Azeez S. A.

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Post occupancy evaluation (POE) is a process of assessing building performance for its users and intended function during the occupation. User satisfaction impacts the performance of educational environments and their users: students, faculty, and staff. In addition, buildings are maintained and managed by teams that spend a large amount of time and capital on their long-term sustenance. By evaluating the feedback from users of higher education facilities, university planning departments are more prepared to understand the inputs for programming and future project planning. In addition, university buildings will be closer to meeting user and maintenance needs. This paper reports on a research team made up of academics, facility personnel, and users that have developed a plan to improve the quality of campus facilities through a POE exercise on a recently built project. This study utilized a process of focus group interviews representing the different users and subsequent surveys. The paper demonstrates both the theory and practice of POE in higher education and learning environment through the case example of four universities in Nigeria's POE exercise.

Keywords: post occupancy evaluation, building performance, building analysis, building evaluation, quality control, building assessment, facility management, design quality

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Authors: G. Massaad, E. Roziere, A. Loukili, L. Izoret

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Based on the monitoring of mass, hydrostatic weighing, and the amount of leached OH- we deduced the nature of leached and precipitated minerals, the amount of lost aggregates and the evolution of porosity and cracking during the sulphate attack. Using these information, we are able to draw the volume / mass changes brought by mineralogical variations and cracking of the cement matrix. Then we defined a new performance indicator, the averaged density, capable to resume along the test of sulphate attack the occurred physicochemical variation occurred in the cementitious matrix and then highlight.

Keywords: monitoring strategy, performance indicator, sulphate attack, mechanism of degradation

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Joaquin Ticzon, Christian Demition, Jaime Honra

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Additive manufacturing (AM) or 3D printing has been one of the emerging trends present in various industries, particularly in prototyping. This review focuses on the impact of additive manufacturing on a motor vehicle's performance aiming to investigate potential advancements to further revolutionize the way parts are manufactured. One of the most common problems faced in the automotive industry is carbon footprint emissions from motor vehicles, which was stated to be remedied by lightweight; additively manufactured parts helped reduce these emissions due to weight reduction provided by additively manufactured parts. Composed of various techniques for AM as well as materials utilized during the manufacturing process, which differ in terms of the quality and performance it provides during its application on the final product. Given this, the generative design will not be discussed in such a detailed manner because the focus will revolve around the effects on the performance of a vehicle due to additively manufactured parts.

Keywords: additive manufacturing (AM), automotive, computer aided design (CAD), generative design

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Authors: Okoro Ikechukwu Ralph, Fuat Kara

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The discoveries of hydrocarbon reserves has clearly drifted offshore, and in deeper waters - areas where the industry still has limited knowledge; and that were hitherto, regarded as being out of reach. This shift presents significant and increased challenges in technology requirements needed to guarantee safety of personnel, environment and equipment; ensure high reliability of installed equipment; and provide high level of confidence in security of investment and company reputation. Nowhere are these challenges more apparent than on subsea well integrity and production performance. The past two decades has witnessed enormous rise in deep and ultra-deep water offshore field developments for the recovery of hydrocarbons. Subsea installed equipment at the seabed has been the technology of choice for these developments. This paper discusses the role of Subsea Control module (SCM) as a vital factor for deep-water well integrity and production performance. A case study for Deep-water well integrity and production performance is analysed.

Keywords: offshore reliability, production performance, subsea control module, well integrity

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Authors: Ari Prasetyo, Taufik Faturohman

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The COVID-19 pandemic in Indonesia is part of the ongoing worldwide pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was confirmed to have spread to Indonesia on 2 March 2020. Moreover, the government of Indonesia has been conducting a local lockdown to limit people's movement from one city to another city. Therefore, this situation has impact on business operation, especially on highway companies listed on the Indonesia stock exchange. This study evaluates and measures three companies’ financial performance and health conditions before and during the COVID-19 pandemic from 2016 – 2020. The measurement is conducted by using financial ratio analysis and the Altman Z-score method. The ratio used to measure the financial ratio analysis is taken from the decree of the Ministry of SOE’s KEP-100/MBU/2002 about the company’s health level condition. From the decree, there are eight financial ratios used such as return on equity (ROE), return on investment (ROI), current ratio, cash ratio, collection period, inventory turnover, total asset turnover, and total equity to total asset. Altman Z-score is used to calculate the financial distress condition. The result shows that the highway companies for the period 2016 – 2020 are as follows: PT Jasa Marga (Persero) Tbk (AA, BB, BB, BB, C), PT Citra Marga Nusaphala Persada Tbk (BB, AA, BB, BBB, C), and PT Nusantara Infrastructure Tbk (BB, BB, AA, BBB, C). In addition, the Altman Z-score assessment performed in 2016-2020 shows that PT Jasa Marga (Persero) Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020. PT Citra Marga Nusaphala Persada Tbk was in the grey zone area for 2015-2019 and in the distress zone for 2020. PT Nusantara Infrastructure Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020.

Keywords: financial performance, financial ratio, Altman Z-score, financial distress, highway company

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Authors: Abdulaziz Alkathiry

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Concussion is a common brain injury that affect physical and cognitive performance. While several studies indicated that adolescents are more likely to develop concussion, in the last decade concussion has been mainly explored in adults. Migraine has been identified as a common symptom reported after concussion and was tied with worse prognoses. Hence, we aimed to investigate the effect of migraine on functional performance and self-reported symptoms in children with concussion. This cross-sectional study involved 35 symptomatic children aged 9 – 17 years recruited within 1 year from their concussion injury at a tertiary balance center. Participants’ symptoms and functional performance were assessed using the post-concussion symptoms scale (PCSS) and the functional gait assessment (FGA) respectively. Concussed children with migraine showed significantly worse symptoms including fatigue, sleeping impairment, difficulty concentrating, and visual problems (P < 0.05). Functional performance didn’t show differences between concussed children with and without migraine. Although concussed children with and without migraine didn’t show any differences on functional performance, worse cognitive symptoms were found in concussed children with migraine. A customized treatment approach is indicated in the presence of migraine for the management of children with concussion. Keywords: Concussion; Migraine; Balance; Post-Concussion Symptoms Scale; Functional Gait Assessment

Keywords: concussion, migraine, post-concussion symptoms scale, functional gait assessment, balance

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Authors: Qingyu Zhang, Helin Ma, Lili Weng, Mei Cao

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Green supply chain management has been an important organizational strategy to reduce environmental risks and improve financial performance. Firms have to adopt green supply chain practices to meet the official regulations and reduce peer pressure in China. This paper exhibits an empirical study of the drivers of green supply chain management practices and the environmental and economic performance of green supply chain management implementation in Chinese firms. While China is the fastest-growing emerging economy, it has paid a high ecological price. It is reported that China hosts 7 of the world’s 10 most polluted cities. The continued environmental deterioration and the resultant heightened regulatory control and public scrutiny have posed new operating challenges to firms conducting business in China. These challenges make the country an ideal setting to conduct the present study. A research questionnaire was developed to gather data in China. The questionnaire targeted managers and employees in Chinese companies. The data were collected in the last quarter of 2015, involving industries such as electronic & communicational equipment, textile & clothing, pharmaceutical & healthcare, and so on. This study confirms and validates that (1) both internal and external drivers play a significant role in the implementation of green supply chain management practices; (2) green purchase and investment recovery have a significant impact on firms’ environmental and economic performance; (3) with the improvement of the firms’ environmental performance, their economic performance will improve.

Keywords: economic performance, environmental performance, external driver, green supply chain management

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Authors: Zhihao Zhao, Ali El-Nagger, Johnson Kau, Chris Olson, Douglas Tomlinson, Scott X. Chang

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One strategy to reduce CO₂ emissions from cement production is to reduce the amount of Portland cement produced by replacing it with supplementary cementitious materials (SCMs). Biochar is a potential SCM that is an eco-friendly and stable porous pyrolytic material. However, the effects of biochar addition on the performances of Portland cement composites are not fully understood. This meta-analysis investigated the impact of biochar addition on the 7- and 28-day compressive strength of Portland cement composites based on 606 paired observations. Biochar feedstock type, pyrolysis conditions, pre-treatments and modifications, biochar dosage, and curing type all influenced the compressive strength of Portland cement composites. Biochars obtained from plant-based feedstocks (except rice and hardwood) improved the 28-day compressive strength of Portland cement composites by 3-13%. Biochars produced at pyrolysis temperatures higher than 450 °C, with a heating rate of around 10 °C/min, increased the 28-day compressive strength more effectively. Furthermore, the addition of biochars with small particle sizes increased the compressive strength of Portland cement composites by 2-7% compared to those without biochar addition. Biochar dosage of < 2.5% of the binder weight enhanced both compressive strengths and common curing methods maintained the effect of biochar addition. However, when mixing the cement, adding fine and coarse aggregates such as sand and gravel affects the concrete and mortar's compressive strength, diminishing the effect of biochar addition and making the biochar effect nonsignificant. We conclude that appropriate biochar addition could maintain or enhance the mechanical performance of Portland cement composites, and future research should explore the mechanisms of biochar effects on the performance of cement composites.

Keywords: biochar, Portland cement, constructure, compressive strength, meta-analysis

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Authors: Amit Arora, P. M. V. Subbarao, R. S. Agarwal

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This study attempts to find promising locations of upwash delta winglets for an inline finned tube heat exchanger. Later, location of winglets that delivers highest improvement in thermal performance is identified. Numerical results clearly showed that optimally located upwash delta winglets not only improved the thermal performance of fin area in tube wake and tubes, but also improved overall thermal performance of heat exchanger.

Keywords: apparent friction factor, delta winglet, fin and tube heat exchanger, longitudinal vortices

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Authors: Natalia Strobel, Jan Kratzer

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Achieving effective innovation is a complex task and during this process firms (especially SMEs) often face obstacles. However, research into obstacles to innovation focusing on SMEs is very scarce. In this study, we propose a theoretical framework for describing these obstacles to innovation and investigate their influence on the innovative performance of SMEs. Data were collected in 2013 through face-to-face interviews with executives of 49 technology SMEs from Germany. The semi-structured interviews were designed on the basis of scales for measuring innovativeness, financial/competitive performance and obstacles to innovation, next to purely open questions. We find that the internal obstacles lack the know-how, capacity overloading, unclear roles and tasks, as well as the external obstacle governmental bureaucracy negatively influence the innovative performance of SMEs. However, in contrast to prior findings this study shows that cooperation ties of firms might also negatively influence the innovative performance.

Keywords: innovation, innovation process, obstacles, SME

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Authors: Ali Kadir, O. Anwar Beg

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Thermal barrier coatings are among the most popular methods for providing corrosion protection in high temperature applications including aircraft engine systems, external spacecraft structures, rocket chambers etc. Many different materials are available for such coatings, of which ceramics generally perform the best. Motivated by these applications, the current investigation presents detailed finite element simulations of coating stress analysis for a 3- dimensional, 3-layered model of a test sample representing a typical gas turbine component scenario. Structural steel is selected for the main inner layer, Titanium (Ti) alloy for the middle layer and Silicon Carbide (SiC) for the outermost layer. The model dimensions are 20 mm (width), 10 mm (height) and three 1mm deep layers. ANSYS software is employed to conduct three types of analysis- static structural, thermal stress analysis and also computational fluid dynamic erosion/corrosion analysis (via ANSYS FLUENT). The specified geometry which corresponds to corrosion test samples exactly is discretized using a body-sizing meshing approach, comprising mainly of tetrahedron cells. Refinements were concentrated at the connection points between the layers to shift the focus towards the static effects dissipated between them. A detailed grid independence study is conducted to confirm the accuracy of the selected mesh densities. To recreate gas turbine scenarios; in the stress analysis simulations, static loading and thermal environment conditions of up to 1000 N and 1000 degrees Kelvin are imposed. The default solver was used to set the controls for the simulation with the fixed support being set as one side of the model while subjecting the opposite side to a tabular force of 500 and 1000 Newtons. Equivalent elastic strain, total deformation, equivalent stress and strain energy were computed for all cases. Each analysis was duplicated twice to remove one of the layers each time, to allow testing of the static and thermal effects with each of the coatings. ANSYS FLUENT simulation was conducted to study the effect of corrosion on the model under similar thermal conditions. The momentum and energy equations were solved and the viscous heating option was applied to represent improved thermal physics of heat transfer between the layers of the structures. A Discrete Phase Model (DPM) in ANSYS FLUENT was employed which allows for the injection of continuous uniform air particles onto the model, thereby enabling an option for calculating the corrosion factor caused by hot air injection (particles prescribed 5 m/s velocity and 1273.15 K). Extensive visualization of results is provided. The simulations reveal interesting features associated with coating response to realistic gas turbine loading conditions including significantly different stress concentrations with different coatings.

Keywords: thermal coating, corrosion, ANSYS FEA, CFD

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Authors: Qingli Lei

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This study investigates the impact of family socioeconomic status and parental involvement on the academic performance of elementary school students, specifically focusing on migrant students in China. The findings reveal that gender has a stronger influence on academic performance compared to local status and parental tutoring time. Female students tend to achieve higher scores than males. Parental education level does not significantly predict academic performance, while parent tutoring time does have a significant impact. Furthermore, there is a significant interaction between local status and parental education level, indicating that migrant students with lower-educated parents perform better than their local counterparts, while local children excel when their parents' education levels are higher. These results emphasize the importance of parental involvement, particularly for immigrant students, and highlight the need for interventions that enhance parental engagement in education to improve academic outcomes.

Keywords: academic performance, family socioeconomic status, migrant students, parental involvement

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Authors: Păcurar Diana Istina

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The indissoluble link between aesthetics and semiotics, the harmonization and semiotic understanding of the interactions between the viewer and the object being looked at, are the basis of the practical demonstration of the importance of aesthetic perception within the theater performance. The design of a theater performance includes several structures, some considered from the beginning, art forms (i.e., the text), others being represented by simple, common objects (e.g., scenographic elements), which, if reunited, can trigger a certain aesthetic perception. The audience is delivered, by the team involved in the performance, a series of auditory and visual signs with which they interact. It is necessary to explain some notions about the physiological support of the transformation of different types of stimuli at the level of the cerebral hemispheres. The cortex considered the superior integration center of extransecal and entanged stimuli, permanently processes the information received, but even if it is delivered at a constant rate, the generated response is individualized and is conditioned by a number of factors. Each changing situation represents a new opportunity for the viewer to cope with, developing feelings of different intensities that influence the generation of meanings and, therefore, the management of interactions. In this sense, aesthetic perception depends on the detection of the “correctness” of signs, the forms of which are associated with an aesthetic property. Fairness and aesthetic properties can have positive or negative values. Evaluating the emotions that generate judgment and implicitly aesthetic perception, whether we refer to visual emotions or auditory emotions, involves the integration of three areas of interest: Valence, arousal and context control. In this context, superior human cognitive processes, memory, interpretation, learning, attribution of meanings, etc., help trigger the mechanism of anticipation and, no less important, the identification of error. This ability to locate a short circuit produced in a series of successive events is fundamental in the process of forming an aesthetic perception. Our main purpose in this research is to investigate the possible conditions under which aesthetic perception and its minimum content are generated by all these structures and, in particular, by interactions with forms that are not commonly considered aesthetic forms. In order to demonstrate the quantitative and qualitative importance of the categories of signs used to construct a code for reading a certain message, but also to emphasize the importance of the order of using these indices, we have structured a mathematical analysis that has at its core the analysis of the percentage of signs used in a theater performance.

Keywords: semiology, aesthetics, theatre semiotics, theatre performance, structure, aesthetic perception

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

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In recent years, the failure accidents in petrochemical industry have been frequent, and have posed great security problems in personnel and property. The improvement of petrochemical safety is highly requested in order to prevent re-occurrence of severe accident. This study focuses on surveying the failure cases occurred in petrochemical field, which were extracted from journals of engineering failure, including engineering failure analysis and case studies in engineering failure analysis. The relation of failure mode, failure mechanism, type of components, and type of materials was analyzed in this study. And the analytical results showed that failures occurred more frequently in vessels and piping among the petrochemical equipment. Moreover, equipment made of carbon steel and stainless steel accounts for the majority of failures compared to other materials. This may be related to the application of the equipment and the performance of the material. In addition, corrosion failures were the largest in number of occurrence in the failure of petrochemical equipment, in which stress corrosion cracking accounts for a large proportion. This may have a lot to do with the service environment of the petrochemical equipment. Therefore, it can be concluded that the corrosion prevention of petrochemical equipment is particularly important.

Keywords: cases analysis, corrosion, failure, petrochemical industry

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Authors: Natalia Strobel, Jan Kratzer

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In this paper, we test whether different types of research and development (R&D) alliances positively impact the radical innovation performance of firms. We differentiate between the R&D alliances without extern R&D orders and embeddedness in knowledge source network. We test the differences between the domestically diversified R&D alliances and R&D alliances diversified abroad. Moreover, we test how non-price competition influences the impact of domestically diversified R&D alliances, and R&D alliance diversified abroad on radical innovation performance. Our empirical analysis is based on the comprehensive Swiss innovation panel, which allowed us to study 3520 firms between the years between 1996 and 2011 in 3 years intervals. We analyzed the data with a linear estimation with Swamy-Aurora transformation using plm package in R software. Our results show as hypothesized a positive impact of R&D alliances diversity abroad as well as domestically on radical innovation performance. The effect of non-price interaction is in contrast to our hypothesis, not significant. This suggests that diversity of R&D alliances is highly advantageous independent of non-price competition.

Keywords: R&D alliances, partner diversity, knowledge source diversity, non-price competition, absorptive capacity

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Gulfam Haider, sana danish

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Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

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Authors: Narvada Ramdhany, Reena Bhattu Babajee

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The 2007-2008 Global Financial Crisis which initiated in the US had a global outreach, impacting the financial and banking sectors of several economies; such as European countries, developing and emerging countries in Asia, Latin America and Africa. European countries represent one of the main sources of export earnings for Mauritius and given that Europe has been quite profoundly affected by the crisis, the Mauritian economy also could have been negatively affected. This study is being undertaken to see if the crisis had a spill-over effect on the Mauritian banking system. It will also enable to determine if the measures put in place to counteract the crisis by regulatory authorities have been effective. The study will be carried out on 17 banks and data will be collected over a time frame of seven years; with a pre-crisis period from 2005 to 2007 and a post-crisis period from 2009 to 2011. The impact of the crisis as such will be measured through the financial performance of the banks, using financial ratios and regression analysis. The results show that during the period concerned Mauritian banks have remained solvent and relatively stable. One of the main explanations put forward to explain the resilience of the banking sector to the crisis is that foreign exposure was relatively low. Another explanation put forward is that Mauritian banks normally transact mainly with prime borrowers unlike most the banks which were affected by the financial crisis.  

Keywords: global financial crisis, banking sector, financial performance, Mauritian banks

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Authors: Liseane Padilha Thives, Mayara S. S. Lima, João Victor Staub De Melo, Glicério Trichês

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Red mud is a waste resulting from the processing of bauxite to alumina, the raw material of the production of aluminum. The large quantity of red mud generated and inadequately disposed in the environment has motivated researchers to develop methods for reinsertion of this waste into the productive cycle. This work aims to evaluate the resistance to permanent deformation of dense asphalt mixtures with red mud filler. The red mud was characterized by tests of X-ray diffraction, fluorescence, specific mass, laser granulometry, pH and scanning electron microscopy. For the analysis of the influence of the quantity of red mud in the mechanical performance of asphalt mixtures, a total filler content of 7% was established. Asphalt mixtures with 3%, 5% and 7% red mud were produced. A conventional mixture with 7% stone powder filler was used as reference. The asphalt mixtures were evaluated for performance to permanent deformation in the French Rutting Tester (FRT) traffic simulator. The mixture with 5% red mud presented greater resistance to permanent deformation with rutting depth at 30,000 cycles of 3.50%. The asphalt mixtures with red mud presented better performance, with reduction of the rutting of 12.63 to 42.62% in relation to the reference mixture. This study confirmed the viability of reinserting the red mud in the production chain and possible usage in the construction industry. The red mud as filler in asphalt mixtures is a reuse option of this waste and mitigation of the disposal problems, as well as being an environmentally friendly alternative.

Keywords: asphalt mixtures, permanent deformation, red mud, pavements

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Authors: Nurul Nadrah

Abstract:

As a result of the COVID-19 pandemic, a movement control order was implemented, leading to the adoption of online learning as a substitute for conventional classroom instruction. Thus, this study aims to determine the differences in skill performance between online learning and conventional methods among nursing students. We employed a quasi-experimental design with purposive sampling, involving a total of 59 nursing students, and used online learning as the intervention. As a result, the study found there was a significant difference in student skill performance between online learning and conventional methods. As a conclusion, in times of hardship, it is necessary to implement alternative pedagogical approaches, especially in critical fields like nursing, to ensure the uninterrupted progression of educational programs. This study suggests that online learning can be effectively employed as a means of imparting knowledge to nursing students during their training.

Keywords: nursing education, online learning, skill performance, conventional learning method

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Authors: R. Khrifou, M. Galai, R. Touir, M. Ebn Touhami, Y. Ramli

Abstract:

A 2-(5-methyl-2-Nitro-1H-imidazol-1-yl)ethyl benzoate (IMDZ-B) was synthesized and characterized using elemental analyses, NMR, and Fourier transform infrared (FTIR) techniques. Its effect on brass corrosion in 1.0 M H₃PO₄ solution was investigated by using electrochemical measurements coupled with X-ray diffraction analysis (XRD), Scanning electron microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX). The polarization measurements showed that the IMDZ-B acts as a mixed-type inhibitor. Indeed, it is found that the IMDZ-B compound is a very good inhibitor, and its inhibition efficiency increases with concentration to reach a maximum of 99.5 % at 10-³ M. In addition, the obtained electrochemical parameters from impedance indicated that the IMDZ-B molecules act by adsorption on metallic surfaces. This adsorption was found to obey Langmuir’s adsorption isotherm. However, the temperature effect on the performance of IMDZ-B was also studied. It is found that the IMDZ-B takes its performance at high temperatures. In addition, the obtained kinetic and thermodynamic parameters showed that the IMDZ-B molecules act via two adsorption modes, physisorption and chemisorptions, and its process is endothermic and spontaneous. Finally, the XRD and SEM/EDX analyses confirmed the electrochemical obtained results.

Keywords: low concentration, anti-corrosion brass, IMDZ-B product, phosphoric acid solution, electrochemical, SEM\EDAX analysis

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Authors: Sooyoung Cho, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

Abstract:

Series hybrid UAV(Unmanned aerial vehicle) that is proposed in this paper performs VTOL(Vertical take-off and landing) using the battery and generator, and it applies the series hybrid system with combination of the small engine and generator when cruising flight. This system can be described as the next-generation system that can dramatically increase the UAV flight times. Also, UAV systems require a large energy at the time of VTOL to be conducted for a short time. Therefore, this paper designs PMSG(Permanent Magnet Synchronous Generator) having a high specific power considering VTOL through the FEA.

Keywords: PMSG, VTOL, UAV, high specific power density

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Authors: Eudjen Cinc

Abstract:

Work with a human voice, especially with a child s voice and cultivating the sound of the choir, presents an area of crucial importance for a conductor. We use the term conductor because it needs to be understood that regardless of whether we have in front of us an amateur or a professional choir, whether they are singers with a wealth of experience or children who are still developing and educating their inner ear so that in the future they could contribute to the development of choir music, the person who stands in front of the group and works with them, needs to have the characteristics of a conductor. Voice formation is a long-term process, without which there is no success in both solo and collective music performance.

Keywords: music group, conductor, collective, performance

Procedia PDF Downloads 213

Authors: Lojaine Okacha

Abstract:

In the past half-century, researchers started paying attention to enhancing the performance of urban spaces. Their idea of performance comprised urban climate performance, space synthesis, economic performance, and enhancing the quality of life in space. However, they all agreed that the key to achieving any of the previously mentioned development projects is good governance. Having good governance allows citizens to participate freely in the urbanization or development projects within cities. Consequently, using the city resources and assets as efficiently as possible, and ensures the fulfillment of the users’ needs and requests. This paper aims to propose an effective participation framework to help citizens have their voices heard and participate in the decisions that will affect their living situation. The framework allows governments to use their public resources to their best. However, this study focuses on public participation in third-world countries with unitary decentralized governance systems such as Egypt. It summarizes the challenges facing the participation practices, identifies the keys to a successful participation process, and draws on dominant effective participation practice lying on the relationship between the levels of participation, stakeholders participating, the urban development stages, the city-systems, and participation process. These components are integrated to create a real-world effective participation Framework. The results of the analysis were incredible and produced a functional and progressive approach for effective public participation to introduce to the governments. The model itself is combined with additional principles allowing the best practice to the process. The framework is finally compared with a real case of urban development.

Keywords: public participation, good governance, urban development, city systems

Procedia PDF Downloads 188

Authors: D. Shakirah Shukor, A. Aminudin, Hashim U. A., Waziralilah N. Fathiah, T. Vikneshvaran

Abstract:

The interior noise control is essential to be explored due to the interior acoustic analysis is significant in the systems such as automobiles, aircraft, air-handling system and diesel engine exhausts system. In this research, experimental work was undertaken for canceling an active noise in the rectangular enclosure. The rectangular enclosure was fabricated with multiple speakers and microphones inside the enclosure. A software program using digital signal processing is implemented to evaluate the proposed method. Experimental work was conducted to obtain the acoustic behavior and characteristics of the rectangular enclosure and noise cancellation based on active noise control in low-frequency range. Noise is generated by using multispeaker inside the enclosure and microphones are used for noise measurements. The technique for noise cancellation relies on the principle of destructive interference between two sound fields in the rectangular enclosure. One field is generated by the original or primary sound source, the other by a secondary sound source set up to interfere with, and cancel, that unwanted primary sound. At the end of this research, the result of output noise before and after cancellation are presented and discussed. On the basis of the findings presented in this research, an active noise cancellation in the rectangular enclosure is worth exploring in order to improve the noise control technologies.

Keywords: active noise control, digital signal processing, noise cancellation, rectangular enclosure

Procedia PDF Downloads 265