Search results for: innovative method and tools

Authors: Dimitrios Triantakonstantis, Demetris Stathakis

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Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

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Authors: Haolun Sun, Ping Wang, Mei Wu, Meng Zhang, Bin Hou, Ling Yang, Xiaohua Ma, Yue Hao

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Gallium nitride (GaN) is an attractive material for next-generation power devices. It is noted that the performance of GaN-based high electron mobility transistors (HEMTs) is always limited by the self-heating effect. In response to the problem, integrating devices with polycrystalline diamond (PCD) has been demonstrated to be an efficient way to alleviate the self-heating issue of the GaN-based HEMTs. Among all the heat-spreading schemes, using PCD to cap the epitaxial layer before the HEMTs process is one of the most effective schemes. Now, the mainstream method of fabricating the PCD-capped HEMTs is to deposit the diamond heat-spreading layer on the AlGaN surface, which is covered by a thin nucleation dielectric/passivation layer. To achieve the pattern etching of the diamond heat spreader and device preparation, we selected SiN as the hard mask for diamond etching, which was deposited by plasma-enhanced chemical vapor deposition (PECVD). The conventional diamond etching method first uses F-based etching to remove the SiN from the special window region, followed by using O₂/Ar plasma to etch the diamond. However, the results of the scanning electron microscope (SEM) and focused ion beam microscopy (FIB) show that there are lots of diamond pillars on the etched diamond surface. Through our study, we found that it was caused by the high roughness of the diamond surface and the existence of the overlap between the diamond grains, which makes the etching of the SiN hard mask insufficient and leaves micro-masks on the diamond surface. Thus, a cyclic etching method was proposed to solve the problem of the residual SiN, which was left in the F-based etching. We used F-based etching during the first step to remove the SiN hard mask in the specific region; then, the O₂/Ar plasma was introduced to etch the diamond in the corresponding region. These two etching steps were set as one cycle. After the first cycle, we further used cyclic etching to clear the pillars, in which the F-based etching was used to remove the residual SiN, and then the O₂/Ar plasma was used to etch the diamond. Whether to take the next cyclic etching depends on whether there are still SiN micro-masks left. By using this method, we eventually achieved the self-terminated etching of the diamond and the smooth surface after the etching. These results demonstrate that the cyclic etching method can be successfully applied to the integrated preparation of polycrystalline diamond thin films and GaN HEMTs.

Keywords: AlGaN/GaN heterojunction, O₂/Ar plasma, cyclic etching, polycrystalline diamond

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Authors: Xiao Yihong, Li Zhixuan, Wong Kah Seng, Shen Xingcang

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Requirement Elicitation is one of the important factors in developing any new application. Most systems fail just because of wrong elicitation practice. As a result, developers always choose different methods in different fields to achieve optimal results. This paper analyses four cases to understand the effectiveness of different requirement elicitation methods in the field of mobile shopping applications. The elicitation methods we studied included interviews, questionnaires, prototypes, analysis of existing systems, focus groups, brainstorming, and so on. Through the research and analysis results, we ensured the need for a mixture of elicitation methods. Meanwhile, the method adopted should be determined according to the scale of the project and be operated in a reasonable order to ensure the high efficiency of requirement elicitation.

Keywords: requirements elicitation method, shopping, mobile application, software requirement engineering

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Authors: Zheming Cao

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Control loops are the most important components in the wind turbine system. Product quality, operation safety, and the economic performance are directly or indirectly connected to the performance of control systems. This paper proposed a performance evaluation method based on minimum-variance for wind turbine control system. This method can be applied on PID controller for pitch control system in the wind turbine. The good performance result demonstrated in the paper was achieved by retuning and optimizing the controller settings based on the evaluation result. The concepts presented in this paper are illustrated with the actual data of the industrial wind farm.

Keywords: control performance, evaluation, minimum-variance, wind turbine

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Authors: Kawser Ahmed, K. Bousson, Milca F. Coelho

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4D flight trajectory optimization is one of the key ingredients to improve flight efficiency and to enhance the air traffic capacity in the current air traffic management (ATM). The present paper explores the iterative dynamic programming (IDP) as a potential numerical optimization method for 4D flight trajectory optimization. IDP is an iterative version of the Dynamic programming (DP) method. Due to the numerical framework, DP is very suitable to deal with nonlinear discrete dynamic systems. The 4D waypoint representation of the flight trajectory is similar to the discretization by a grid system; thus DP is a natural method to deal with the 4D flight trajectory optimization. However, the computational time and space complexity demanded by the DP is enormous due to the immense number of grid points required to find the optimum, which prevents the use of the DP in many practical high dimension problems. On the other hand, the IDP has shown potentials to deal successfully with high dimension optimal control problems even with a few numbers of grid points at each stage, which reduces the computational effort over the traditional DP approach. Although the IDP has been applied successfully in chemical engineering problems, IDP is yet to be validated in 4D flight trajectory optimization problems. In this paper, the IDP has been successfully used to generate minimum length 4D optimal trajectory avoiding any obstacle in its path, such as a no-fly zone or residential areas when flying in low altitude to reduce noise pollution.

Keywords: 4D waypoint navigation, iterative dynamic programming, obstacle avoidance, trajectory optimization

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Authors: Hussam Elias, Ninovic Perez, Holger Hirsch

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The completion of the EMC regulations worldwide is growing steadily as the usage of electronics in our daily lives is increasing more than ever. In this paper, we introduce a novel method to perform the final phase of Electromagnetic compatibility (EMC) measurement and to reduce the required test time according to the norm EN 55032 by using a developed tool and the conventional neural network(CNN). The neural network was trained using real EMC measurements, which were performed in the Semi Anechoic Chamber (SAC) by CETECOM GmbH in Essen, Germany. To implement our proposed method, we wrote software to perform the radiated electromagnetic interference (EMI) measurements and use the CNN to predict and determine the position of the turntable that meets the maximum radiation value.

Keywords: conventional neural network, electromagnetic compatibility measurement, mean absolute error, position error

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Authors: Kevin Fernagut, Olivier Flauzac, Erick M. G. Robledo, Florent Nolot

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The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-Based Virtual Machine (KVM), Linux Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: containerization, containers, cybersecurity, cyberattacks, isolation, performance, virtualization, virtual machines

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Authors: Bharat Prasad Neupane

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Given the widespread concentration on beliefs, values, emotions, critical incidents, and practices in exploring teachers’ professional identities, this study presents the trajectories of identity construction of three English language teachers from Nepal, analyzing their storied lives from schoolteachers to university professors. For this purpose, the article considered the three-dimensional professional development model to explore the effective mediation by the state agencies, culture and the policies, appropriate support from the organizations, and the bottom-up initiatives taken by the teachers in their professional development. Besides, the professional development journey derived from the in-depth interview of the participants is analyzed by employing communities of practice theory, particularly engagement, alignment, and imagination, as theoretical categories to discover their professional identities. The analysis revealed that passion for language, creativity, and motivation to learn English during childhood initially encouraged them to study English. In addition, inspiration from their teachers during their schooling and later a competitive working environment motivated them to experiment with innovative teaching approaches and establish themselves in the profession. Furthermore, diversification in university teaching according to university requirements and resultant divergence from the professional root ultimately transformed their identity beyond English teachers. Finally, university policy, customization of teachers as per the university requirement, and their survival strategy as English teachers in a university where technical subjects are given more priority has impacted their professional identities.

Keywords: teachers’ professional development, English language teaching, professional identity, communities of practice

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Authors: M. Madheswaran, A. R. Prashant, S. Ramakrishna, V. Ramesh Naidu, P. Govindan, P. Aravindakshan

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Shock Response spectrum (SRS) tests are one of the tests that are conducted on some critical systems of spacecraft as part of environmental testing. The SRS tests are conducted to simulate the pyro shocks that occur during launch phases as well as during deployment of spacecraft appendages. Some of the methods to carryout SRS tests are pyro technique method, impact hammer method, drop shock method and using electro dynamic shakers. The pyro technique, impact hammer and drop shock methods are open loop tests, whereas SRS testing using electrodynamic shaker is a controlled closed loop test. SRS testing using electrodynamic shaker offers various advantages such as simple test set up, better controllability and repeatability. However, it is important to devise a a proper test methodology so that safety of the electro dynamic shaker and that of test specimen are not compromised. This paper discusses the challenges that are involved in conducting SRS tests, shaker validation and the necessary precautions to be considered. Approach involved in choosing various test parameters like synthesis waveform, spectrum convergence level, etc., are discussed. A case study of SRS test conducted on an optical payload of Indian Geo stationary spacecraft is presented.

Keywords: maxi-max spectrum, SRS (shock response spectrum), SDOf (single degree of freedom), wavelet synthesis

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Authors: Tiron-Tudor Adriana, Farcas Teodora Viorica, Ciolomic Ioana Andreea

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The issue of human capital mobility inside Europe is still an open one. Even though there were created some tools in order to better move from one country to another to work and study the number of the people doing this is very low because of various factors presented in this paper. The "rethinking educational" agenda of the European Commission has open the floor for new projects which can create steps towards a European language for skills and competences, qualifications. One of these projects is the Partnership for Exchange of experience in Student on-the-job Training. As part of this project, we are interested to see the situation of the human capital inside EU and the elements that were created until now to support this mobility. Also, the main objective of the project is to make a comparison between the four countries involved in PEST project (Romania, Hungary, Finland, and Estonia), at the education and internship level. The results are helpful for the follow of the project, for identifying where changes can be done and need to be done.

Keywords: ECVET, human capital mobility, partnership exchange, students on the job mobility, vocational education and training

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Authors: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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Authors: Chia-Yi Wu, Jung-Chen Chang, Wen-Yu Hu, Ming-Been Lee

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In nearly all physical health conditions, suicide risk is increased compared to healthy people even after adjustment for age, gender, mental health, and substance use diagnoses. In order to highlight the importance of suicide risk assessment for the inpatients and early identification and engagement for inpatients’ mental health problems, a study was designed aiming at developing a comprehensive psychosomatic nursing engagement (PSNE) model with standardized operation procedures informing how nurses communicate, assess, and engage with the inpatients with emotional distress. The purpose of the study was to promote the gatekeeping role of clinical nurses in performing brief assessment and interventions to detect depression and anxiety symptoms among the inpatients, particularly in non-psychiatric wards. The study will be carried out in a 2000-bed university hospital in Northern Taiwan in 2019. We will select a ward for trial and develop feasible procedures and in-job training course for the nurses to offer mental health care, which will also be validated through professional consensus meeting. The significance of the study includes the following three points: (1) The study targets at an important but less-researched area of PSNE model in the cultural background of Taiwan, where hospital service is highly accessible, but mental health and suicide risk assessment are hardly provided by non-psychiatric healthcare personnel. (2) The issue of PSNE could be efficient and cost-effective in the identification of suicide risks at an early stage to prevent inpatient suicide or to reduce future suicide risk by early treatment of mental illnesses among the high-risk group of hospitalized patients who are more than three-times lethal to suicide. (3) Utilizing a brief tool with its established APP ('The Five-item Brief Symptom Rating Scale, BSRS-5'), we will invent the standardized procedure of PSNE and referral steps in collaboration with the medical teams across the study hospital. New technological tools nested within nursing assessment/intervention will concurrently be invented to facilitate better care quality. The major outcome measurements will include tools for early identification of common mental distress and suicide risks, i.e., the BSRS-5, revised BSRS-5, and the 9-item Concise Mental Health Checklist (CMHC-9). The main purpose of using the CMHC-9 in clinical suicide risk assessment is mainly to provide care and build-up therapeutic relationship with the client, so it will also be used to nursing training highlighting the skills of supportive care. Through early identification of the inpatients’ depressive symptoms or other mental health care needs such as insomnia, anxiety, or suicide risk, the majority of the nursing clinicians would be able to engage in critical interventions that alleviate the inpatients’ suffering from mental health problems, given a feasible nursing input.

Keywords: mental health care, clinical outcome improvement, clinical nurses, suicide prevention, psychosomatic nursing

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Authors: Achim Kampker, Heiner Hans Heimes, Mathias Ordung, Jan-Philip Ganser

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In the past years, the automotive industry has changed significantly. Innovative mobility concepts have become more important, and electric vehicles see a chance of replacing vehicles with combustion engines in the long term. However, the coming years will be characterized by coexistence. In this context, there are two possible production scenarios: One the one hand, electric vehicles could be manufactured in bespoke assembly lines. Concerning the uncertainty regarding sales figures development, this alternative boasts a high investment risk. Therefore, an integrated assembly building upon existing structures also seems a feasible solution. This empirical study aims at validating hypotheses concerning theoretical and practical challenges of the integrated production in the final assembly. In order to take a test of approaches of the research by analyzing censored feedback of professionals, these hypotheses are validated in the framework of an expert study. For this purpose, hypotheses have been generated on the basis of a requirements analysis and a concept specification. Thereupon, a list of question has been implemented and deduced from the hypotheses to execute an online- and written-survey and interviews with professionals. The interpretation and evaluation of the findings includes an inter-component comparison for the electric drivetrain. Furthermore, key drivers for a sufficient integrated product and process design are presented.

Keywords: automotive industry, final assembly, integrated manufacturing, product and process development

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Authors: Danilo F. Rodrigues, Hérida Regina N. Salgado

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Introduction: The emergence of resistant microorganisms to a large number of clinically approved antimicrobials has been increasing, which restrict the options for the treatment of bacterial infections. As a strategy, drugs with high antimicrobial activities are in evidence. Stands out a class of antimicrobial, the cephalosporins, having as fourth generation cefepime (CEF) a semi-synthetic product which has activity against various Gram-positive bacteria (e.g. oxacillin resistant Staphylococcus aureus) and Gram-negative (e.g. Pseudomonas aeruginosa) aerobic. There are few studies in the literature regarding the development of microbiological methodologies for the analysis of this antimicrobial, so researches in this area are highly relevant to optimize the analysis of this drug in the industry and ensure the quality of the marketed product. The development of microbiological methods for the analysis of antimicrobials has gained strength in recent years and has been highlighted in relation to physicochemical methods, especially because they make possible to determine the bioactivity of the drug against a microorganism. In this context, the aim of this work was the development and validation of a microbiological method for quantitative analysis of CEF in powder lyophilized for injectable solution by turbidimetric assay. Method: For performing the method, Staphylococcus aureus ATCC 6538 IAL 2082 was used as the test microorganism and the culture medium chosen was the Casoy broth. The test was performed using temperature control (35.0 °C ± 2.0 °C) and incubated for 4 hours in shaker. The readings of the results were made at a wavelength of 530 nm through a spectrophotometer. The turbidimetric microbiological method was validated by determining the following parameters: linearity, precision (repeatability and intermediate precision), accuracy and robustness, according to ICH guidelines. Results and discussion: Among the parameters evaluated for method validation, the linearity showed results suitable for both statistical analyses as the correlation coefficients (r) that went 0.9990 for CEF reference standard and 0.9997 for CEF sample. The precision presented the following values 1.86% (intraday), 0.84% (interday) and 0.71% (between analyst). The accuracy of the method has been proven through the recovery test where the mean value obtained was 99.92%. The robustness was verified by the parameters changing volume of culture medium, brand of culture medium, incubation time in shaker and wavelength. The potency of CEF present in the samples of lyophilized powder for injectable solution was 102.46%. Conclusion: The turbidimetric microbiological method proposed for quantification of CEF in lyophilized powder for solution for injectable showed being fast, linear, precise, accurate and robust, being in accordance with all the requirements, which can be used in routine analysis of quality control in the pharmaceutical industry as an option for microbiological analysis.

Keywords: cefepime hydrochloride, quality control, turbidimetric assay, validation

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Authors: Muslim Khan, Kenneth B. Jensen, Kevin A. Francesconi

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Trace amounts (ca 1 µg/L, 13 nM) of arsenic are present in sea water mostly as the oxyanion arsenate. In contrast, arsenic is present in marine biota (animals and algae) at very high levels (up to100,000 µg/kg) a significant portion of which is present as lipid-soluble compounds collectively termed arsenolipids. The complex nature of sea water presents an analytical challenge to detect trace compounds and monitor their environmental path. We developed a simple method using liquid-liquid extraction combined with HPLC-High Resolution Mass Spectrometer capable of detecting trace of arsenolipids (99 % of the sample matrix while recovering > 80 % of the six target arsenolipids with limit of detection of 0.003 µg/L.)

Keywords: arsenolipids, sea water, HPLC-high resolution mass spectrometry

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Authors: Abdul Hafeez, Samiya Shehzadi

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This research paper presents a different approach towards eco-friendly textile design by developing a sustainable composite fabric from orange peel for ladies' undergarments. The research focuses on utilizing orange peel to develop a unique orange leather/composite (fabric) through a process involving heating, extracting, and subsequent sun-drying to obtain the composite. The sustainable composite fabric shows properties that are favorable to the development of environmentally friendly undergarments, which not only offer UV protection but also possess healing properties for the skin. Through comprehensive testing and analysis, it has been determined that the orange peel composite fabric has zero harmful effects on the skin, making it a safe and desirable material for intimate wear. Furthermore, the research suggests that the orange peel composite fabric has the potential to reduce the rate of cancer cell growth. While the exact mechanisms and factors contributing to this effect require further investigation, the initial findings indicate promising aspects of the fabric in terms of potential cancer-preventive properties. Research contribution to the field of sustainable textile design by introducing a usual and eco-friendly approach utilizing orange peel waste. This work opens up avenues for further exploration and development of innovative materials that are both sustainable and beneficial for human health.

Keywords: sustainability, composite textiles, extracting, undergarments, eco-friendly, orange peels

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Authors: Nükhet Konuk, N. Gamze Turan, Yüksel Ardalı

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Cities play a vital role in the social fabric of countries and in national and regional economic growth worldwide; however, the environmental effects of such growth need to be assessed and managed better. The critical and most immediate problems faced by cities of developing countries are the health impacts of urban pollution that derive from inadequate water, sanitation, drainage and solid waste services, poor urban and industrial waste management, and air pollution. As globalization continues, earth's natural processes transform local problems into international issues. The aim of this study is to provide a broad overview of the pollution from urban wastes and emissions in Turkey which is a developing country. It is aimed to underline the significance of reorganizing the institutional tools in a worldwide perspective in order to generate coherent solutions to urban problems, and to enhance urban quality.

Keywords: environmental pollution, developing countries, environmental degradation, urban environmental problems

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Authors: Riccardo Angiuli, Michele Giannuzzi, Rodolfo Franchi, Gabriele Papadia

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Temperature knowledge in machining is fundamental to improve the numerical and FEM models used for the study of some critical process aspects, such as the behavior of the worked material and tool. The extreme conditions in which they operate make it impossible to use traditional measuring instruments; infrared thermography can be used as a valid measuring instrument for temperature measurement during metal cutting. In the study, a large experimental program on superduplex steel (ASTM A995 gr. 5A) cutting was carried out, the relevant cutting temperatures were measured by infrared thermography when certain cutting parameters changed, from traditional values to extreme ones. The values identified were used to calibrate a FEM model for the prediction of residual life of the tools. During the study, the problems related to the detection of cutting temperatures by infrared thermography were analyzed, and a dedicated procedure was developed that could be used during similar processing.

Keywords: machining, infrared thermography, FEM, temperature measurement

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Authors: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Manjinder Bajwa, Mahipal Singh, Ashish Tulli

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In the research, the effect of varying cutting parameters, design parameters and heat treatment processes were studied on the cutting performance (Tool life) of a PVD coated tool. Thus, in a quest for these phenomenon comparison, a single coated tool and a multicoated tool were analyzed after suitable heat treatment process. TNMG shaped insert with single coating of TiCN and multi-coating of TiAlN/TiN were developed on tungsten carbide substrate. These coated inserts were then successfully annealed and normalized for a temperature of 350°C for 30 minutes and their cutting performance was evaluated as per the flank wear obtained after turning of mild steel. The results showed that heat treatment had a suitable impact on the tool life of the coated insert and also led to increase in the micro-hardness of the tool coatings and decrease in the wear rate.

Keywords: PVD coatings, flank wear, micro-hardness, annealing, normalizing

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: Samarjeet Singh, Shubhank Arya, Shubham Chauhan

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In recent years, the rise in carbon emissions and the widespread effects of global warming have brought new energy vehicles into the spotlight. Electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), both producing zero tailpipe emissions, are seen as promising alternatives. This paper examines the working, structural characteristics, and safety designs of EVs and HFCVs, comparing their carbon emissions, charging infrastructure, energy efficiency, and safety features. The analysis reveals that both EVs and HFCVs significantly reduce carbon emissions and enhance safety compared to traditional vehicles, with EVs showing greater emission reductions. Moreover, EVs are advancing more rapidly in terms of charging infrastructure compared to hydrogen energy vehicles. However, HFCVs exhibit lower energy efficiency than EVs. In terms of safety, both types surpass conventional vehicles, though EVs are more prone to overheating and fire hazards due to battery design issues. Current research suggests that EV technology and its supporting infrastructure are more comprehensive, cost-effective, and efficient in reducing carbon emissions. With continued investment in the development of new energy vehicles and potential advancements in hydrogen energy production, the future for HFCVs appears promising. The paper also expresses optimism for innovative solutions that could accelerate the growth of hydrogen energy vehicles.

Keywords: electric vehicles, fuel cell electric vehicles, automotive engineering, energy transition

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Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

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Authors: Andrey Norov

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In the recent years, Samoilov Research Institute for Mineral Fertilizers JSC “NIUIF”, the oldest (established in September 1919) industry-oriented institute in Russia, has developed a range of sustainable, environment-friendly, zero-waste technologies that ensure minimal consumption of materials and energy resources and fully consistent with the principles of Green Chemistry that include: - Ecofriendly energy and resource saving technology of sulfuric acid from sulfur according to DC-DA scheme (double conversion - double absorption); - Improved zero-waste technology of wet phosphoric acid (WPA) by dihydrate-hemihydrate process applicable to various types of phosphate raw materials; - Flexible, efficient, zero-waste, universal technology of NP / NPS / NPK / NPKS fertilizers with maximum heat recovery from chemical processes; - Novel, zero-waste, no-analogue technology of granular PK / PKS / NPKS fertilizers with controlled dissolution rate and nutrient supply into the soil, which allows to process a number of wastes and by-products; - Innovative resource-saving joint processing of wastes from the production of phosphogypsum and fluorosilicic acid (FSA) into ammonium sulfate with simultaneous neutralization of fluoride compounds with no lime used. - New fertilizer technology of increased environmental and agrochemical efficiency (currently under development). All listed green technologies are patented with Russian and Eurasian patents. The development of ecofriendly, safe, green technologies is ongoing in JSC “NIUIF”.

Keywords: NPKS fertilizers, FSA, sulfuric acid, WPA

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Authors: I. A. Farhat, M. Bin Hasan

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A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

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Authors: E. L. Elghazy, A. M. Sanad, M. G. Ghoneim

Abstract:

Over the past two decades research has shown that fiber reinforced polymers can be efficiently, economically and safely used for strengthening and rehabilitation of reinforced concrete (RC) structures. Designing FRP confined concrete columns requires reliable analytical tools that predict the level of performance and ductility enhancement. A numerical procedure is developed aiming at determining the type and thickness of FRP jacket needed to achieve a certain level of ductility enhancement. The procedure starts with defining the stress strain curve, which is used to obtain moment curvature relationship then displacement ductility ratio of reinforced concrete cross-sections subjected to bending moment and axial force. Three sets of published experimental tests were used to validate the numerical procedure. Comparisons between predicted results obtained by using the proposed procedure and actual results of experimental tests proved the reliability of the proposed procedure.

Keywords: columns, confinement, ductility, FRP, numerical

Procedia PDF Downloads 437

Authors: Mahdiye Khorasani, Arjun Vijay, Ali Mashayekh, Christian Trapp

Abstract:

The performance of Proton Exchange Membrane Fuel Cell (PEMFC) is highly dependent on the pressure and mass flow of media (Hydrogen and air) throughout the cells and the stack. Higher pressure, on the one hand, results in higher output power of the stack but, on the other hand, increases the electrical power demand of the compressor. In this work, a simulation model of a PEMFC system for vehicle and airplane applications is developed. With this new model, the effect of different pressures and air mass flow rates are investigated to discover the optimum operating point in a PEMFC system, and innovative operation strategies are implemented to optimize reactants flow while minimizing electrical power demand of the compressor for optimum performance. Additionally, a fuel cell system test bench is set up, which contains not only all the auxiliary components for conditioning the gases, reactants, and flows but also a dynamic titling table for testing different orientations of the stack to simulate the flight conditions during take-off and landing and off-road-vehicle scenarios. The results of simulation will be tested and validated on the test bench for future works.

Keywords: air mass flow effect, optimization of operation, pressure effect, PEMFC system, PEMFC system simulation

Procedia PDF Downloads 160

Authors: Iara Rezende, Djalma Silva, Alcino Costa Neto

Abstract:

Considering the transformations of the contemporary world linked to globalization and climate changes caused by global warming, the environmental and energy issues have been increasingly present in the decisions of the world scenario. Thus, the aim of reducing the impacts caused by human activities there are the energy efficiency measures, which are also applicable in the scope of Civil Engineering. Considering that a large part of the energy demand from buildings is related to the need to adapt the internal environment to the users comfort and productivity, measures capable of reducing this need can minimize the climate changes impacts and also the energy consumption of the building. However, these important measures are currently little used by civil engineers, either because of the interdisciplinarity of the subject, the time required to apply certain methods or the difficult interpretation of the results obtained by computational programs that often have a complex and little applied approach. Thus, it was proposed the development of a Java application with a simpler and applied approach to evaluate the thermal performance of a building in order to obtain results capable of assisting the civil engineers in the decision making related to the users thermal comfort. The program was built in Java programming language and the method used for the evaluation was the Center Scientifique et Technique du Batiment (CSTB) method. The program was used to evaluate the thermal performance of a university classroom. The analysis was carried out from simulations considering the worst climatic situation of the building occupation. Thus, at the end of the process, the favorable result was obtained regarding the classroom comfort zone and the feasibility of using the program, thus achieving the proposed objectives.

Keywords: building occupation, CSTB method, energy efficiency measures, Java application, thermal comfort

Procedia PDF Downloads 123

Authors: Valeria Corinaldesi, Nicola Generosi, Jacopo Donnini

Abstract:

Ultra high performance concrete (UHPC) is an innovative material which tends to exhibit superior properties such as incredible mechanical and durability performance and non-brittleness behavior. Over the last twenty years, phenomenal advances have taken place in the research and application of UHPC. Recently, the approach is to improve UHPC sustainability by reducing its embodied energy. First of all, this goal can be achieved by reducing Portland cement dosage. In this work, an experimental investigation was carried out to characterize the mechanical behavior and durability of UHPCs prepared by reducing the cement amount by 30% in order to verify the impact of lower cement content and higher water-to-cement ratio on both mechanical performance and durability, if any. Eight different UHPC mixtures were compared, with two different cement dosages (either 1000 or 700 kg) and four different brass-coated steel fibres dosages (0 - 50 - 100 - 150 kg), in terms of 28-day compressive and flexural strengths. Then, the mixtures prepared with the lower cement content were further investigated in terms of abrasion resistance, water absorption, freezing and thawing cycles, and resistance to sulphate attack. Results obtained showed the feasibility of reducing cement dosage without compromising mechanical performance and UHPC's extraordinary durability.

Keywords: abrasion resistance, durability, eco-efficiency, freeze-thawing cycles, steel fibres, sulphate exposure, sustainability, UHPC

Procedia PDF Downloads 62

Authors: Sam Khozama, Ali M. Mayya

Abstract:

Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

Procedia PDF Downloads 146