Search results for: operation cost

Authors: Chen-Yu Chen, Wei-Mon Yan, Chi-Nan Lai, Jian-Hao Su

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The proton exchange membrane fuel cell (PEMFC) becomes more important as an alternative energy source recently. Maintaining proper water content in the membrane is one of the key requirements for optimizing the PEMFC performance. The planar membrane humidifier has the advantages of simple structure, low cost, low-pressure drop, light weight, reliable performance and good gas separability. Thus, it is a common external humidifier for PEMFCs. In this work, a planar membrane humidifier for kW-scale PEMFCs is developed successfully. The heat and mass transfer of humidifier is discussed, and its performance is analyzed in term of dew point approach temperature (DPAT), water vapor transfer rate (WVTR) and water recovery ratio (WRR). The DPAT of the humidifier with the counter flow approach reaches about 6°C under inlet dry air of 50°C and 60% RH and inlet humid air of 70°C and 100% RH. The rate of pressure loss of the humidifier is 5.0×10² Pa/min at the torque of 7 N-m, which reaches the standard of commercial planar membrane humidifiers. From the tests, it is found that increasing the air flow rate increases the WVTR. However, the DPAT and the WRR are not improved by increasing the WVTR as the air flow rate is higher than the optimal value. In addition, increasing the inlet temperature or the humidity of dry air decreases the WVTR and the WRR. Nevertheless, the DPAT is improved at elevated inlet temperatures or humidities of dry air. Furthermore, the performance of the humidifier with the counter flow approach is better than that with the parallel flow approach. The DPAT difference between the two flow approaches reaches up to 8 °C.

Keywords: heat and mass transfer, humidifier performance, PEM fuel cell, planar membrane humidifier

Procedia PDF Downloads 293

Authors: Maryam Torabi, Habibi, Abdolahi, Mohammadi, Hassanzadeh, Darban Maghami, Baghi

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Sheeppox Virus (SPPV) and goatpox virus (GTPV) are considerable diseases of sheep, and goats, caused by viruses of the Capripoxvirus (CaPV) genus. They are responsible for economic losses. Animal mortality, morbidity, cost of vaccinations, and restrictions in animal products’ trade are the reasons of economic losses. Control and eradication of CaPV depend on early detection of outbreaks so that molecular detection and genetic analysis could be effective to this aim. This study was undertaken to molecularly characterize SPPV and GTPV strains that have been circulating in Iran. 120 skin papules and nodule biopsies were collected from different regions of Iran and were examined for SPPV, GTPV viruses using TaqMan Real -Time PCR. Some of these amplified genes were sequenced, and phylogenetic trees were constructed. Out of the 120 samples analysed, 98 were positive for CaPV by Real- Time PCR (81.6%), and most of them wereSPPV. then 10 positive samples were sequenced and characterized by amplifying the ORF 103CaPV gene. sequencing and phylogenetic analysis for these positive samples revealed a high percentage of identity with SPPV isolated from different countries in Middle East. In conclusions, molecular characterization revealed nearly complete identity with all recent SPPVs strains in local countries that requires further studies to monitor the virus evolution and transmission pathways to better understand the virus pathobiology that will help for SPPV control.

Keywords: molecular epidemiology, Real-Time PCR, phylogenetic analysis, capripoxviruses

Procedia PDF Downloads 122

Authors: Erwin, Cheng-Cheng Chen, Charles J. Salim

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One of the method to solve the lateral torsional buckling (LTB) problem is by using side plates to increased the buckling resistance of the beam. Some modifications in designing the side plates are made in this study to simplify the construction in the field and reduce the cost. At certain region, side plates are not added: (1) At the beam end to preserve some spaces for bolt installation, but the beam is strengthened by adding cover plate at both flanges and (2) at the middle span of the beam where the moment is smaller. Three small scale full span beam specimens are tested under cyclic loading to investigate the LTB resistant and the ductility of the proposed design method. Test results show that the LTB deformation can be effectively suppressed and very high ductility level can be achieved. Following the test, a finite element analysis (FEA) model is established and is verified using the test results. An intensive parametric study is conducted using the established FEA model. The analysis reveals that the length of side plates is the most important parameter determining the performance of the beam and the required side plates length is determined by some parameters which are (1) beam depth to flange width ratio, (2) beam slenderness ratio (3) strength and thickness of the side plates, (4) compactness of beam web and flange, and (5) beam yield strength. At the end of the paper, a design formula to calculate the required side plate length is suggested.

Keywords: cover plate, earthquake resistant design, lateral torsional buckling, side plate, steel structure

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Authors: Christodoulou Christos, Politis Anastasios

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The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.

Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction

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Authors: Agnieszka A. Malinowska, R. Hejmanowski

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A number of European cities are strongly affected by ground movements caused by anthropogenic activities or post-anthropogenic metamorphosis. Those are mainly water pumping, current mining operation, the collapse of post-mining underground voids or mining-induced earthquakes. These activities lead to large and small-scale ground displacements and a ground ruptures. The ground movements occurring in urban areas could considerably affect stability and safety of structures and infrastructures. The complexity of the ground deformation phenomenon in relation to the structures and infrastructures vulnerability leads to considerable constraints in assessing the threat of those objects. However, the increase of access to the free software and satellite data could pave the way for developing new methods and strategies for environmental risk mitigation and management. Open source geographical information systems (OS GIS), may support data integration, management, and risk analysis. Lately, developed methods based on fuzzy logic and experts methods for buildings and infrastructure damage risk assessment could be integrated into OS GIS. Those methods were verified base on back analysis proving their accuracy. Moreover, those methods could be supported by ground displacement observation. Based on freely available data from European Space Agency and free software, ground deformation could be estimated. The main innovation presented in the paper is the application of open source software (OS GIS) for integration developed models and assessment of the threat of urban areas. Those approaches will be reinforced by analysis of ground movement based on free satellite data. Those data would support the verification of ground movement prediction models. Moreover, satellite data will enable our mapping of ground deformation in urbanized areas. Developed models and methods have been implemented in one of the urban areas hazarded by underground mining activity. Vulnerability maps supported by satellite ground movement observation would mitigate the hazards of land displacements in urban areas close to mines.

Keywords: fuzzy logic, open source geographic information science (OS GIS), risk assessment on urbanized areas, satellite interferometry (InSAR)

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Authors: Yiannis Vacanas, Kyriacos Themistocleous, Athos Agapiou, Diofantos Hadjimitsis

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Building Information Modelling (BIM) technology is considered by construction professionals as a very valuable process in modern design, procurement and project management. Construction professionals of all disciplines can use a single 3D model which BIM technology provides, to design a project accurately and furthermore monitor the progress of construction works effectively and efficiently. Unmanned Aerial Vehicles (UAVs), a technology initially developed for military applications, is now without any difficulty accessible and has already been used by commercial industries, including the construction industry. UAV technology has mainly been used for collection of images that allow visual monitoring of building and civil engineering projects conditions in various circumstances. UAVs, nevertheless, have undergone significant advances in equipment capabilities and now have the capacity to acquire high-resolution imagery from many angles in a cost effective manner, and by using photogrammetry methods, someone can determine characteristics such as distances, angles, areas, volumes and elevations of an area within overlapping images. In order to examine the potential of using a combination of BIM and UAV technologies in construction project management, this paper presents the results of a case study of a typical road construction project where the combined use of the two technologies was used in order to achieve efficient and accurate as-built data collection of the works progress, with outcomes such as volumes, and production of sections and 3D models, information necessary in project progress monitoring and efficient project management.

Keywords: BIM, project management, project monitoring, UAV

Procedia PDF Downloads 288

Authors: R. S. Quintal, J. L. Tesch Santos, M. D. Davis, E. C. de Santana, M. de F. Bandeira dos Santos

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The objective is to identify the contributions from the introduction of the computerized system deal within the Accounting Department of Brazilian Navy Financial Directorship and its possible effects on the budgetary and financial harvest of Brazilian Navy. The relevance lies in the fact that the management process is responsible for the continuous improvement of organizational performance through higher levels of quality in their activities. Improvements in organizational processes have direct effects on crops cost, quality, reliability, flexibility and speed. The method of study of this research is the case study. The choice of case study attended, among other demands, a need for greater flexibility to study processes related to a computerized system. The sources of evidence were used literature, documentary and direct observation. Direct observation was made by monitoring the implementation of the computerized system in the Division of Management Analysis. The main findings of the study point to the fact that the computerized system may contribute significantly to the standardization of information. There was improvement of internal processes in the division of management analysis, made possible the consolidation of a standard management and performance analysis that contribute to global homogeneity in the treatment of information essential to the process of decision making. This study has limitations related to the fact the search result be subject exclusively to the case studied, and it is impossible to generalize to other organs of government.

Keywords: process management, management control, business intelligence, Brazilian Navy

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Authors: Antwi Kwaku Dei, Lyford Conrad Power

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This paper investigates the outcome of participating in the government of Ghana block farm program on rural households’ farm productivity, income, food security and nutritional status in Northern Ghana using cross-sectional data. Data analysis was done using the Instrumental Variable and the Heckman Selection Bias procedures. Our analysis indicates that participation in the block farm program significantly increased directly the productivity of maize, rice, and soybean by 21.3 percent, 15.8 percent, and 12.3 percent respectively. Also, the program participation was found to increase households’ farm income by 20 percent in northern Ghana. Furthermore, program participation was found to improve household food security and nutrition by 19 percent and 14 percent respectively through income effect. Based on the benefit-cost ratio of 1.59 the results from the study recommends that the program is expanded to other communities in the northern region. Further analysis indicates that rural households’ decision to participate in food security intervention programs is significantly influenced by factors including the gender of the household head, the age of the household head, and household size. Results of the study further show that gender of household head, household size, household monthly income, household assets, women educational status, the age of women, marital status of women, are significant determinants of food security and nutrition status in Northern Ghana.

Keywords: block farm program, farm productivity, , household food security, Northern Ghana

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Authors: Mannan Mridha, Usama Gazay, Kosovare V. Aslani, Hugo Linder, Alice Ravizza, Carmelo de Maria

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In most developing countries, although the vast majority of the people are living in the rural areas, the qualified medical doctors are not available there. Health care workers and paramedics, called village doctors, informal healthcare providers, are largely responsible for the rural medical care. Mishaps due to wrong diagnosis and inappropriate medication have been causing serious suffering that is preventable. While innovators have created many devices, the vast majority of these technologies do not find applications to address the needs and conditions in low-resource settings. The primary motive is to address the acute lack of affordable medical technologies for the poor people in low-resource settings. A low cost smart medical device that is portable, battery operated and can be used at any point of care has been developed to detect breathing rate, electrocardiogram (ECG) and arterial pulse rate to improve diagnosis and monitoring of patients and thus improve care and safety. This simple and easy to use smart medical device can be used, managed and maintained effectively and safely by any health worker with some training. In order to empower the health workers and village doctors, our device is being further developed to integrate with ICT tools like smart phones and connect to the medical experts wherever available, to manage the serious health problems.

Keywords: e-health for low resources settings, health awareness education, improve patient care and safety, smart and affordable medical device

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Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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Authors: Xing Wang, Lin Feng, Xuan Zou, Hongchen liu

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Immediate Implantation after tooth extraction is considered to be the ideal way to retain the alveolar bone, but some scholars believe the aesthetic effect in the Early Implantation case are more reliable. In this study, 89 patients were added to this retrospective study up to 5 years. Assessment indicators was including the survival of the implant (peri-implant infection, implant loosening, shedding, crowns and occlusal), aesthetics (color and fullness gums, papilla height, probing depth, X-ray alveolar crest height, the patient's own aesthetic satisfaction, doctors aesthetics score), repair defects around the implant (peri-implant bone changes in height and thickness, whether the use of autologous bone graft, whether to use absorption/repair manual nonabsorbable material), treatment time, cost and the use of antibiotics.The results demonstrated that there is no significant difference in long-term success rate of immediate implantation, early implantation and delayed implantation (p> 0.05). But the results indicated immediate implantation group could get get better aesthetic results after two years (p< 0.05), but may increase the risk of complications and failures (p< 0.05). High-risk indicators include gingival recession, labial bone wall damage, thin gingival biotypes, planting position and occlusal restoration bad and so on. No matter which type of implanting methods was selected, the extraction methods and bone defect amplification techniques are observed as a significant factors on aesthetic effect (p< 0.05).

Keywords: immediate implantation, long-term effects, aesthetics area, dental implants

Procedia PDF Downloads 344

Authors: R. N. Jay A. Ablog, M. N. Dyanne R. Del Carmen, Roma Rose A. Dela Cruz, Joselle Dara M. Estrada, Luke Clifferson M. Gagarin, Florence T. Lang-ay, Ma. Dayanara O. Mariñas, Maria Christina S. Nepa, Jahraine Chyle B. Ocampo, Mark Reynie Renz V. Silva, Jenny Lyn L. Soriano, Loreal Cloe M. Suva, Jackelyn R. Torres

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Background: To date, there is dearth of literature as to the effect of relaxation techniques in lowering the stress level of mothers of children with autism spectrum disorder (ASD). Aim: To investigate the effectiveness of 4-week relaxation techniques in stress level reduction of mothers of children with ASD. Methods: Quasi experimental design. It included 25 mothers (10-experimental, 15-control) who were chosen via purposive sampling. The mothers were recruited in the different SPED centers in Baguio City and La Trinidad and in the community. Statistics used were T-test and Related T-Test. Results: The overall weighted mean score after 4-week training is 2.3, indicating that the relaxation techniques introduced were moderately effective in lowering stress level. Statistical analysis (T-test; CV=4.51>TV=2.26) shown a significant difference in the stress level reduction of mothers in the experimental group pre and post interventions. There is also a significant difference in the stress level reduction in the control and the experimental group (Related T-test; CV=2.08 >TV=2.07). The relaxation techniques introduced were favorable, cost-effective, and easy to perform interventions to decrease stress level.

Keywords: relaxation techniques, mindful eating, progressive muscle relaxation, breathing exercise, autism spectrum disorder

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

Procedia PDF Downloads 115

Authors: Zhiyong Li, Hiroshi Katayama

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Since 1990s, e-commerce and internet business have been grown gradually over the word and customers tend to express their demand attributes in terms of specification requirement on parts, component, product structure etc. This paper deals with designing effective decoupling points for build to order systems under e-commerce environment, which can be realized through tradeoff relation analysis between two major criteria, customer order lead time and value of work in progress. These KPIs are critical for successful BTO business, namely time-based service effectiveness on coping with customer requirements for the first issue and cost effective ness with risk aversive operations for the second issue. Approach of this paper consists of investigation of successful business standing for BTO scheme, manufacturing model development of this scheme, quantitative evaluation of proposed models by calculation of two KPI values under various decoupling point distributions and discussion of the results brought by pattern of decoupling point distribution, where some cases provide the pareto optimum performances. To extract the relevant trade-off relation between considered KPIs among 2-dimensional resultant performance, useful logic developed by former research work, i.e. Katayama and Fonseca, is applied. Obtained characteristics are evaluated as effective information for managing BTO manufacturing businesses.

Keywords: build-to-order (BTO), decoupling point, e-commerce, order-to-delivery lead time (ODLT), work in progress (WIP)

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Authors: Thea Freese, Michael Gille, Andrew Hursthouse, John Struthers

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Ship operators on the North and Baltic Sea have been experiencing increased political interest in marine environmental protection and cleaner vessel operations. Stricter legislation on SO2 and NOx emissions, ballast water management and other measures of protection are currently being phased in or will come into force in the coming years. These measures benefit the health of the marine environment, while increasing company’s operational costs. In times of excess shipping capacity and linked consolidation in the industry non-compliance with environmental rules is one way companies might hope to stay competitive with both intra- and inter-modal trade. Around 5-15% of industry participants are believed to neglect laws on vessel-source pollution willingly or unwillingly. Exploratory in-depth interviews conducted with 12 experts from various stakeholder groups informed the researchers about variables influencing compliance levels, including awareness and apprehension, willingness to comply, ability to comply and effectiveness of controls. Semi-structured expert interviews were evaluated using qualitative content analysis. A model of determinants of compliance was developed and is presented here. While most vessel operators endeavour to achieve full compliance with environmental rules, a lack of availability of technical solutions, expediency of implementation and operation and economic feasibility might prove a hindrance. Ineffective control systems on the other hand foster willing non-compliance. With respect to motivations, lacking time, lacking financials and the absence of commercial advantages decrease compliance levels. These and other variables were inductively developed from qualitative data and integrated into a model on environmental compliance. The outcomes presented here form part of a wider research project on economic effects of maritime environmental legislation. Research on determinants of compliance might inform policy-makers about actual behavioural effects of shipping companies and might further the development of a comprehensive legal system for environmental protection.

Keywords: compliance, marine environmental protection, exploratory qualitative research study, clean vessel operations, North and Baltic Sea area

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Authors: Abhimanyu Pati, Prabir K. Bandyopadhyay

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The paper intends to highlight the significance of Digital Manufacturing (DM) strategy in support and achievement of business strategy and goals of any manufacturing organization. Towards this end, DM initiatives have been given a process perspective, while not undermining its technological significance, with a view to link its benefits directly with fulfilment of customer needs and expectations in a responsive and cost-effective manner. A digital process model has been proposed to categorize digitally enabled organizational processes with a view to create synergistic groups, which adopt and use digital tools having similar characteristics and functionalities. This will throw future opportunities for researchers and developers to create a unified technology environment for integration and orchestration of processes. Secondly, an effort has been made to apply “what” and “how” features of Quality Function Deployment (QFD) framework to establish the relationship between customers’ needs – both for external and internal customers, and the features of various digital processes, which support for the achievement of these customer expectations. The paper finally concludes that in the present highly competitive environment, business organizations cannot thrive to sustain unless they understand the significance of digital strategy and integrate it with their business strategy with a clearly defined implementation roadmap. A process-oriented approach to DM strategy will help business executives and leaders to appreciate its value propositions and its direct link to organization’s competitiveness.

Keywords: knowledge management, cloud computing, knowledge management approaches, cloud-based knowledge management

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Authors: Christopher Benedikt Jakob

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Human beings are intrigued by luxury watches for decades. It is fascinating that customers pay an enormous amount of money for specific wristwatch models. It is fascinating that customers of the luxury watch industry accept a yearly price increase. This behavior increases their desirability even more. Luxury watches are perceived as status symbols, but they are additionally accepted as a currency without the disadvantage of currency fluctuations. It is obvious that the symbolic value is more important as the functional value with reference to the buying-reasons as regards luxury watches. Nowadays human beings do not need a wristwatch to read the time. Tablets, notebooks, smartphones, the watch in the car and watches on public places are used to inform people about the current time. This is one of the reasons why there is a trend that people do not wear wristwatches anymore. Due to these facts, this study has the intention to give answers to the question why people invest an enormous amount of money on the consumption of luxury watches and why those watches are seen as a status symbol. The study examines why the luxury watch industry records significant growth rates. The self-expression model is used as an appropriate methodology to find reasons why human beings purchase specific luxury watches. This evaluative approach further discusses if human beings are aware of their current self and their ideal self and how they express them. Furthermore, the research critically evaluates the people’s social self and their ideal social self. One of the goals is to identify if customers know why they like specific luxury watches and dislike others although they have the same quality and cost comparable prices.

Keywords: luxury watch, brand awareness, buying-behaviour, consumer, self-expression

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Authors: R. Padmini, G. V. Manoj Kumar

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Structural insulated panels (SIPs) are a high-performance building system for residential and light commercial construction. The panels consist of an insulating foam core sandwiched between two structural facings, typically oriented strand board (OSB). SIPs are manufactured under factory controlled conditions and can be fabricated to fit nearly any building design. The result is a building system that is extremely strong, energy efficient and cost effective. Building with SIPs will save you time, money and labor. Building with SIPs generally costs about the same as building with wood frame construction when you factor in the labor savings resulting from shorter construction time and less job-site waste. Other savings are realized because smaller heating and cooling systems are required with SIP construction. Structural insulated panels (SIPs) are one of the most airtight and well-insulated building systems available, making them an inherently green product. An airtight SIP building will use less energy to heat and cool, allow for better control over indoor environmental conditions, and reduce construction waste. Green buildings use less energy, reducing carbon dioxide emissions and playing an important role in combating global climate change. Buildings also use a tremendous amount of natural resources to construct and operate. Constructing green buildings that use these resources more efficiently, while minimizing pollution that can harm renewable natural resources, is crucial to a sustainable future.

Keywords: high performance, under factory controlled, wood frame, carbon dioxide emissions, natural resources

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

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Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

Procedia PDF Downloads 142

Authors: G. K. Awari, Vishwajeet V. Ambade, S. W. Rajurkar

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The field of additive manufacturing is growing, and discoveries are being made. 3D printing machines are also being developed to accommodate a wider range of 3D printing materials, including plastics, metals (metal AM powders), composites, filaments, and other materials. There are numerous printing materials available for industrial additive manufacturing. Such materials have their unique characteristics, advantages, and disadvantages. In order to avoid errors in additive manufacturing, key elements such as 3D printing material type, texture, cost, printing technique and procedure, and so on must be examined. It can be complex to select the best material for a particular job. Polylactic acid (PLA) is made from sugar cane or cornstarch, both of which are renewable resources. "Black plastic" is another name for it. Because it is safe to use and print, it is frequently used in primary and secondary schools. This is also how FDM screen printing is done. PLA is simple to print because of its low warping impact. It's also possible to print it on a cold surface. When opposed to ABS, it allows for sharper edges and features to be printed. This material comes in a wide range of colours. Polylactic acid (PLA) is the most common material used in fused deposition modelling (FDM). PLA can be used to print a wide range of components, including medical implants, household items, and mechanical parts. The mechanical behaviour of the printed item is affected by variations in infill patterns that are subjected to compressive tests in the current investigation to examine their behaviour under compressive stresses.

Keywords: fused deposition modelling, polylactic acid, infill density, infill pattern, compressive strength

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Authors: Benyelles Zakaria, Yousfi Djaafar, Karoui Moussa Sofiane

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Agriculture is fundamental and remains an important objective in the Algerian economy, based on traditional techniques and structures, it generally has a purpose of consumption. Collection of agricultural statistics in Algeria is done using traditional methods, which consists of investigating the use of land through survey and field survey. These statistics suffer from problems such as poor data quality, the long delay between collection of their last final availability and high cost compared to their limited use. The objective of this work is to develop a processing chain for a reliable inventory of agricultural land by trying to develop and implement a new method of extracting information. Indeed, this methodology allowed us to combine data from remote sensing and field data to collect statistics on areas of different land. The contribution of remote sensing in the improvement of agricultural statistics, in terms of area, has been studied in the wilaya of Sidi Bel Abbes. It is in this context that we applied a method for extracting information from satellite images. This method is called the non-negative matrix factorization, which does not consider the pixel as a single entity, but will look for components the pixel itself. The results obtained by the application of the MNF were compared with field data and the results obtained by the method of maximum likelihood. We have seen a rapprochement between the most important results of the FMN and those of field data. We believe that this method of extracting information from satellite data leads to interesting results of different types of land uses.

Keywords: blind source separation, hyper-spectral image, non-negative matrix factorization, remote sensing

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Authors: Fadi Chammas, Saad Alkhaldi, Tariq Alghamdi, Stefano Alexandirs

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The operating conditions and corrosive nature of the process fluid in the Haradh and Hawiyah areas are subjecting facility piping to undesirable corrosion phenomena. Therefore, production headers inside remote headers have been internally cladded with high alloy material to mitigate the corrosion damage mechanism. Corrosion mitigation in the jump-over lines, constructed between the existing flowlines and the newly constructed facilities to provide operational flexibility, is proposed. This corrosion mitigation system includes the application of fusion bond epoxy (FBE) coating on the internal surface of the pipe and depositing corrosion-resistant alloy (CRA) weld layers at pipe and fittings ends to protect the carbon steel material. In addition, high alloy CRA weld material is used to deposit the girth weld between the 90-degree elbows and mating internally coated segments. A rigorous testing and qualification protocol was established prior to actual adoption at the Haradh and Hawiyah Field Gas Compression Program, currently being executed by Saudi Aramco. The proposed mitigation system, aimed at applying the cladding at the ends of the internally FBE coated pipes/elbows, will resolve field joint coating challenges, eliminate the use of approximately (1700) breakout flanges, and prevent the potential hydrocarbon leaks.

Keywords: pipelines, corrosion, cost-saving, project completion

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Chibuzo Okoye Daniels, Gillian Glegg, Lynda Rodwell

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Marine debris from fishing nets to medical equipment to food packaging that play major roles in boosting the economy and protecting human health is now more than an environmental problem that can be solved by legislation, law enforcement and technical solutions. It has also been identified as a cultural problem that can only be addressed by identifying instruments that can be used to change human attitudes and behaviors. This may be through management approaches, education and involvement of all sectors/interests, including the public. To contribute to the sustainable development of coastal Nigeria, two case study areas (Ikoyi and Victoria Islands of Lagos State) were used to evaluate the socio-economic impacts of marine debris problem in coastal Nigeria. The following methods were used: (1) semi-structured interviews with key stakeholders and businesses on beaches, waterfronts and waterways within the study areas and (2) observational study of beaches, waterfronts and waterways within the study areas. The results of the study have shown that marine debris is a cultural and multi-sectoral problem that poses great threat not only to the environmental sustainability of the study areas but also to the wellbeing of its citizens and the economy of coastal Nigeria. Current solid waste and marine debris management practices are inefficient due to inadequate knowledge of how to tackle the problem. To ensure environmental sustainability in coastal Nigeria and avoid waste of scarce financial resources, adequate, appropriate and cost effective solutions to the marine debris problem need to be identified and effectively transferred for implementation in the study areas.

Keywords: sustainability, coastal Nigeria, study areas, aquaculture

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Authors: Zohreh Fallah, Edward P. L. Roberts

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One of the big challenges for produced water treatment is removing oil from water in the form of emulsified droplets which are not easily separated. An attractive approach is adsorption, as it is a simple and effective process. However, adsorbents must be regenerated in order to make the process cost effective. Several sorbents have been tested for treating oily wastewater. However, some issues such as high energy consumption for activated carbon thermal regeneration have been reported. Due to their significant electrical conductivity, Graphite Intercalation Compounds (GIC) were found to be suitable to be regenerated electrochemically. They are non-porous materials with low surface area and fast adsorptive capacity which are useful for removal of low concentration of organics. An innovative adsorption/regeneration process has been developed at the University of Manchester in which adsorption of organics are done by using a patented GIC adsorbent coupled with subsequent electrochemical regeneration. The oxidation of adsorbed organics enables 100% regeneration so that the adsorbent can be reused over multiple adsorption cycles. GIC adsorbents are capable of removing a wide range of organics and pollutants; however, no comparable report is available for removal of emulsified oil in produced water using abovementioned process. In this study the performance of this technology for the removal of emulsified oil in wastewater was evaluated. Batch experiments were carried out to determine the adsorption kinetics and equilibrium isotherm for both real produced water and model emulsions. The amount of oil in wastewater was measured by using the toluene extraction/fluorescence analysis before and after adsorption and electrochemical regeneration cycles. It was found that oil in water emulsion could be successfully treated by the treatment process and More than 70% of oil was removed.

Keywords: adsorption, electrochemical regeneration, emulsified oil, produced water

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Authors: Namfon Samsalee, Rungsinee Sothornvit

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Turmeric is a natural plant herb and generally extracted as essential oil and widely used in food, cosmetic, pharmaceutical products including insect repellent. However, turmeric oil is a volatile essential oil which is easy to be lost during storage or exposure to light. Therefore, biopolymers such as protein and polysaccharide can be used as wall materials to encapsulate the essential oil which will solve this drawback. Approximately 60% plasma from porcine blood contains 6-7% of protein content mainly albumin and globulin which can be a good source of animal protein at the low-cost biopolymer from by-product. Microencapsulation is a useful technique to entrap volatile compounds in the biopolymer matrix and protect them to degrade. The objective of this research was to investigate the different ratios of two biopolymers (PPP and maltodextrin; MD) as wall materials at 100:0, 75:25, 50:50, 25:75 and 0:100 at a fixed ratio of wall material: core material (turmeric oil) at 3:1 (oil in water) on the qualities of microencapsulated powder using freeze drying. It was found that the combination of PPP and MD showed higher solubility of microencapsules compared to the use of PPP alone (P < 0.05). Moreover, the different ratios of wall materials also affected on color (L*, a* and b*) of microencapsulated powder. Morphology of microencapsulated powder using a scanning electron microscope showed holes on the surface reflecting on free oil content and encapsulation efficiency of microencapsules. At least 50% of MD was needed to increase encapsulation efficiency of microencapsulates rather than using only PPP as the wall material (P < 0.05). Microencapsulated turmeric oil powder can be useful as food additives to improve food texture, as a biopolymer material for edible film and coating to maintain quality of food products.

Keywords: microencapsulation, turmeric oil, porcine plasma protein, maltodextrin

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Authors: Shriya Chawla, Vinayak Malhotra

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Space exploration has noted an exponential rise in the past two decades. The world has started probing the alternatives for efficient and resourceful sustenance along with utilization of advanced technology viz., satellites on earth. Space propulsion forms the core of space exploration. Of all the issues encountered, space debris has increasingly threatened the space exploration and propulsion. The efforts have resulted in the presence of disastrous space debris fragments orbiting the earth at speeds up to several kilometres per hour. Debris are well known as a potential damage to the future missions with immense loss of resources, mankind, and huge amount of money is invested in active research on them. Appreciable work had been done in the past relating to active space debris-removal technologies such as harpoon, net, drag sail. The primary emphasis is laid on confined removal. In recently, remove debris spacecraft was used for servicing and capturing cargo ships. Airbus designed and planned the debris-catching net experiment, aboard the spacecraft. The spacecraft represents largest payload deployed from the space station. However, the magnitude of the issue suggests that active space debris-removal technologies, such as harpoons and nets, still would not be enough. Thus, necessitating the need for better and operative space debris removal system. Techniques based on diverting the path of debris or the spacecraft to avert damage have turned out minimal usage owing to limited predictions. Present work focuses on an active hybrid space debris removal system. The work is motivated by the need to have safer and efficient space missions. The specific objectives of the work are 1) to thoroughly analyse the existing and conventional debris removal techniques, their working, effectiveness and limitations under varying conditions, 2) to understand the role of key controlling parameters in coupled operation of debris capturing and removal. The system represents the utilization of the latest autonomous technology available with an adaptable structural design for operations under varying conditions. The design covers advantages of most of the existing technologies while removing the disadvantages. The system is likely to enhance the probability of effective space debris removal. At present, systematic theoretical study is being carried out to thoroughly observe the effects of pseudo-random debris occurrences and to originate an optimal design with much better features and control.

Keywords: space exploration, debris removal, space crafts, space accidents

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Authors: Elcin Timur Cakmak, Ayse Oguzlar

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This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

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