Search results for: future design

Authors: Saveria Capecchi

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The aim of the quali-quantitative research conducted in the spring of 2021 (still in the midst of the Covid-19 emergency) was to analyze the relationship between the imaginary of 142 girls aged 10-12 from two Italian cities in the Emilia-Romagna region (the capital, Bologna, and Parma) and the influence that various socialization agents can have on it, with particular attention to social media. In order to investigate the relationship between imagination and media, two tools were used: first, the girls wrote an essay in class about their future lives, imagining waking up one morning as a thirty-year-old adults. Six types of "dreams" reflecting the values and lifestyles characteristic of contemporary Italian society emerged. Additionally, the girls completed a questionnaire on their leisure time and, in particular, media consumption aimed at identifying their favorite characters. The results provided insights into understanding the reference values and lifestyles that define their subculture (they belong to the so-called Generation Z). Another interesting aspect of this research is the possibility of comparing the results with those of a similar study on preadolescent imaginary conducted in 1995, involving 292 girls from Milan and Bologna, belonging to the Millennial generation. The narratives about the imagined adult life reflect some crucial changes undergone by Italian society in a quarter of a century: there are advancements towards gender equality, and the imagined family is increasingly detached from tradition. There is a more persistent dream of a life marked by beauty, wealth, and fame, while at the same time, there is a greater social commitment, from solidarity with marginalized people to environmentalism. Furthermore, the mentioned new digital and robotic professions will project us into the near future.

Keywords: gender equality, gender stereotypes, imaginary, preadolescents, social media

Procedia PDF Downloads 48

Authors: Prat Yotyawilai, Taratip Suwannasart

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Business Process Model and Notation (BPMN) is more important in the business process and creating functional models, and is a standard for OMG, which becomes popular in various organizations and in education. Researches related to software testing based on models are prominent. Although most researches use the UML model in software testing, not many researches use the BPMN Model in creating test cases. Therefore, this research proposes a design of a tool for generating test cases from the BPMN. The model is analyzed and the details of the various components are extracted before creating a flow graph. Both details of components and the flow graph are used in generating test cases.

Keywords: software testing, test case, BPMN, flow graph

Procedia PDF Downloads 552

Authors: Sewe Silvanus Odhiambo

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Globally, many governments have publicly recognized private security firms as essential services providers. The private security firms face a lot of challenges, but the COVID-19 situation also has exacerbated them to another level. This paper locates its relevance in the post-coronavirus era. The COVID-19 pandemic has redefined the world operation, which shows a higher impact on the security field. Accordingly, the purpose of the study was to examine the role of corporate governance on the performance of private security firms in a post-covid pandemic era in Kenya. The study employed a descriptive research design, which included a quantitative approach and secondary data. The study was carried in the month of July 2021 from the registered private security firms. After targeting all private security firms, only 54 firms had disclosed their annual report by the time of conducting the study. The results depicted that pandemic has affected the performance of private security firms measures unfavorably. Further, boards of directors show a positive association with security firm performance. The study recommends that there is need board of directors to enhance management’s risk assessments in the midst of COVID-19; ensure that there are business continuity plans; there is organizational resilience; there is need for the development of new digital strategies; enabling the digital workforce in the firms and have effective communication plans with both internal and external stakeholders to deal with uncertainties and develop more post-COVID practices for boards of directors to improve performance of private security firms in Kenya. The practical implications of the study are that the research outcomes might assist regulatory bodies, investors, policymakers, and the security sector in general in their formulation of public and corporate governance strategies concerning future emergency preparedness and responses. This study also provides a unique contribution to the literature of COVID-19 and security firm performance in emerging economies context.

Keywords: COVID-19, corporate governance, firm performance, private security firms

Procedia PDF Downloads 155

Authors: Jung–Min Yang

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Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.

Keywords: asynchronous sequential machines, corrective control, model matching, input/output control

Procedia PDF Downloads 338

Authors: Yekini N. Asafe, Haastrup A. Victor, Lawal N. Olawale, Okikiola F. Mercy

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Recent increase in access to personal computer and networking systems have made it feasible to perform much of cumbersome and costly paper-based administration in all organization. Desktop computers, networking systems, high capacity storage devices and telecommunications system is currently allowing the transfer of various format of data to be processed, stored and dissemination for the purpose of decision making. Going paperless is more of benefits compare to full paper-based office. This paper proposed a model for design and implementation of e-administration system (paperless campus) for an institution of learning. If this model is design and implemented it will reduced cost and complexity of educational administration also eliminate menaces and environmental hazards attributed to paper-based administration within schools and colleges.

Keywords: e-administration, educational administration, paperless campus, paper-based administration

Procedia PDF Downloads 371

Authors: Palanisamy Samyraj, Sriram Yogesh, Kishore Kumar, Vaishak Cibi

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The project is about design and analysis of crankshaft using Al-Al2O3 composite material. The project is mainly concentrated across two areas one is to design and analyze the composite material, and the other is to work on the practical model. Growing competition and the growing concern for the environment has forced the automobile manufactures to meet conflicting demands such as increased power and performance, lower fuel consumption, lower pollution emission and decrease noise and vibration. Metal matrix composites offer good properties for a number of automotive components. The work reports on studies on Al-Al2O3 as the possible alternative material for a crank shaft. These material have been considered for use in various components in engines due to the high amount of strength to weight ratio. These materials are significantly taken into account for their light weight, high strength, high specific modulus, low co-efficient of thermal expansion, good air resistance properties. In addition high specific stiffness, superior high temperature, mechanical properties and oxidation resistance of Al2O3 have developed some advanced materials that are Al-Al2O3 composites. Crankshafts are used in automobile industries. Crankshaft is connected to the connecting rod for the movement of the piston which is subjected to high stresses which cause the wear of the crankshaft. Hence using composite material in crankshaft gives good fuel efficiency, low manufacturing cost, less weight.

Keywords: metal matrix composites, Al-Al2O3, high specific modulus, strength to weight ratio

Procedia PDF Downloads 269

Authors: Yulin Liang

Abstract:

Under the background of protecting ecology, natural education is an effective way for people to understand nature. At the same time, it is a new means of sustainable development of eco-tourism, which can improve the functions of China 's protected areas and develop new business formats for the development of national parks. This study takes national park gateway communities as the research object and uses literature review, inductive reasoning and other research methods to sort out the development process of natural education in China and the research progress of natural education design in national park gateway communities. Finally, it discuss how gateway communities can use natural education to transform their development methods and provide theoretical and practical basis for the development of gateway communities in national parks.

Keywords: nature education, gateway communities, national park, sustainable development

Procedia PDF Downloads 55

Authors: B. Bergström, A. Ladd, A. Jones, L. Rosso, P. Michael

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Attitudes toward treatment manuals serve as a meaningful predictor of general attitudes toward evidence-based practice. Despite demonstrating high effectiveness in treating many mental disorders, manualized treatments have been underutilized by practitioners. Thus, one can assess the state of the field regarding the adoption of evidence-based practices by surveying practitioner attitudes towards manualized treatments. This study is an adapted replication that assesses psychology graduate student attitudes towards manualized treatments, as a general marker for attitudes towards evidence-based practice. Training programs provide future clinicians with the foundation for critical skills in clinical practice. Research demonstrates that post-graduate continuing education has little to no effect on clinical practice; thus, graduate programs serve as the primary, and often final platform for all future practice. However, there are little empirical data identifying the attitudes and training of graduate students in utilizing manualized treatments. The empirical analysis of this study indicates an increase in positive attitudes among graduate student attitudes towards manualized treatments (within the United States), when compared to past surveys of professional psychologists. Findings from this study may inform graduate programs of barriers for students in developing positive attitudes toward manualized treatments and evidence-based practice. This study also serves as a preliminary predictor of the state-of-the field, in regards to professional psychologists attitudes towards evidence-based practice, if attitudes remain stable. This study indicates that the attitudes toward utilizing evidence-based practices, such as treatment manuals, has become more positive since year 2000.

Keywords: exposure therapy, evidence based practice, manualized treatments, student attitudes

Procedia PDF Downloads 159

Authors: Lilik Sudiajeng, Wiraga Wayan, Lanang Parwita I Gusti

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This is the ongoing research started in 2013 with the final aim is to design the recharge wells both for housing and industry for ground water conservation in Bali - Indonesia. The research started in Denpasar Regency, one of the strategic areas in Bali. The research showed that there is some critical area of ground water resources, especially in north and west part of Denpasar Regency. It driven by the rapid increase of the tourism industry which is followed by the high rate of population, change of land use that leads to the decreasing of rain water catchment areas, and less awareness on preserve natural resources, including ground water. Focus Group Discussion concluded that in order to solve the problem of groundwater crisis, requires the contribution of all parties, started from making simple recharge well for housing. Because of the availability of land is limited and expensive, it is necessary to present an ergonomic shallow recharge well in accordance with the ability of the family or community. The ergonomics shallow recharge well is designed based on the data of hydrology and the characteristics of soil. The design is very flexible depending on the availability of land, environmentally friendly, energy efficient, culture-based, and affordable. To meet the recommended standard of ground water quality, then it equipped with a filtration and sedimentation ponds. Before design recharge wells is disseminated to the public, it is necessary to analyze the effectiveness of the wells to harvest and absorb rainwater into the ground.

Keywords: ergonomics, ground water resources, recharge well, sustainable

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Authors: Ishan Arora, Anurag Rathore

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The primary objective of this work was to study the effect of resin chemistry, pH and molarity of binding and elution buffer on aggregate removal using Cation Exchange Chromatography and find the optimum conditions which can give efficient aggregate removal with minimum loss of yield. Four different resins were used for carrying out the experiments: Fractogel EMD SO3-(S), Fractogel EMD COO-(M), Capto SP ImpRes and S Ceramic HyperD. Runs were carried out on the AKTA Avant system. Design of Experiments (DOE) was used for analysis using the JMP software. The dependence of the yield obtained using different resins on the operating conditions was studied. Success has been achieved by obtaining yield greater than 90% using Capto SP ImpRes and Fractogel EMD COO-(M) resins. It has also been found that a change in the operating conditions generally has different effects on the yields obtained using different resins.

Keywords: aggregates, cation exchange chromatography, design of experiments, monoclonal antibodies

Procedia PDF Downloads 255

Authors: Conor Blunt, Mariluz del Pino-de Elias, Grace Cott, Saoirse Tracy, Rainer Melzer

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The European Green Deal announced in 2021 details agricultural chemical pesticide use and synthetic fertilizer application to be reduced by 50% and 20% by 2030. Increasing and maintaining expected yields under these ambitious goals has strained the agricultural sector. This intergovernmental plan has identified plant biostimulants as one potential input to facilitate this new phase of sustainable agriculture; these products are defined as microorganisms or substances that can stimulate soil and plant functioning to enhance crop nutrient use efficiency, quality and tolerance to abiotic stresses. Spring barley is Ireland’s most widely sown tillage crop, and grain destined for malting commands the most significant market price. Heavy erratic rainfall is forecasted in Ireland’s climate future, and barley is particularly susceptible to waterlogging. Recent findings suggest that plant receptivity to biostimulants may depend on the level of stress inflicted on crops to elicit an assisted plant response. In this study, three biostimulants of different genesis (seaweed, protein hydrolysate and bacteria) are applied to ‘RGT Planet’ malting barley fertilized at three different rates (0 kg/ha, 40 kg/ha, 75 kg/ha) of calcium ammonium nitrogen (27% N) under non-stressed and waterlogged conditions. This 4x3x2 factorial trial design was planted in a completed randomized block with one plant per experimental unit. Leaf gas exchange data and key agronomic and grain quality parameters were analyzed via ANOVA. No penalty on productivity was evident on plants receiving 40 kg/ha of N and bio stimulant compared to 75 kg/ha of N treatments. The main effects of nitrogen application and waterlogging provided the most significant variation in the dataset.

Keywords: biostimulant, Barley, malting, NUE, waterlogging

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the newly developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: demand forecasting, machine learning, risk management, supply chain design

Procedia PDF Downloads 87

Authors: Christopher Meyer, Laima Gerlitz

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European Ports are about to take an important step towards their future economic development. Existing legislatives such as the European Green Deal are changing the perspective on ports as individual logistic institutions and demand a more holistic view on ports in their characteristic as ecosystem involving several different actors in an interdisciplinary and multilevel approach. A special role is taken by small and medium-sized ports facing the same political restriction and future goals - such as reducing environmental impacts with 2030 and 2050 as targets - while suffering from low financing capacity, outdated infrastructure, low innovation measures and missing political support. In contrast, they are playing a key role in regional economic development and cross-border logistics as well as facilitator for the regional hinterland. Also, in comparison to their big counterparts, small and medium-sized ports are often located within or close to city areas. This does not only bear more challenges especially when it comes to the environmental performance, but can also carry out growth potentials by putting the city as a key actor into the port ecosystem. For city development, the Smart City concept is one of the key strategies currently applied mostly on demonstration level in selected cities. Hence, the basic idea behind is par to the Smart Port concept. Thus, this paper is analysing potential synergetic effects resulting from the application of Smart City and Smart Port concepts for small and medium-sized ports' ecosystems closely located to cities with focus on innovation application, greening measurements and economic performances as well as strategic positioning of the ports in Smart City initiatives.

Keywords: port-city ecosystems, regional development, sustainability transition, innovation policy

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Authors: Kunj Parikh, S. Bhattacharya, V. Natarajan

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TCAD numerical simulation is one of the most tried and tested powerful tools for designing devices in semiconductor foundries worldwide. It has also been used to explain conduction in organic thin films where the processing temperature is often enough to make homogeneous samples (often imperfect, but homogeneously imperfect). In this report, we have presented the results of TCAD simulation in multi-grain thin films. The work has addressed the inhomogeneity in one dimension, but can easily be extended to two and three dimensions. The effect of grain boundaries has mainly been approximated as barriers located at the junction between two adjacent grains. The effect of the value of grain boundary barrier, the bulk traps, and the measurement temperature have been investigated.

Keywords: polycrystalline thin films, space charge limited conduction, Technology Computer-Aided Design (TCAD) simulation, traps

Procedia PDF Downloads 210

Authors: M. B. Ricardo De Oliveira, A. Borghi-Silva, E. Paravizo, F. Lizarelli, L. Di Thomazzo, D. Braatz

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Prototypes are a critical feature in the product development process, as they help the project team visualize early concept flaws, communicate ideas and introduce an initial product testing. Involving stakeholders, such as consumers and users, in prototype tests allows the gathering of valuable feedback, contributing for a better product and making the design process more participatory. Even though recent studies have shown that user evaluation of prototypes is valuable, few articles provide a method or protocol on how designers should conduct it. This multidisciplinary study (involving the areas of physiotherapy, engineering and computer science) aims to develop an evaluation protocol, using an ergometric step prototype as the product prototype to be assessed. The protocol consisted of performing two tests (the 2 Minute Step Test and the Portability Test) to allow users (patients) and consumers (physiotherapists) to have an experience with the prototype. Furthermore, the protocol contained four Likert-Scale questionnaires (one for users and three for consumers), that inquired participants about how they perceived the design characteristics of the product (performance, safety, materials, maintenance, portability, usability and ergonomics), in their use of the prototype. Additionally, the protocol indicated the need to conduct interviews with the product designers, in order to link their feedback to the ones from the consumers and users. Both tests and interviews were recorded for further analysis. The participation criteria for the study was gender and age for patients, gender and experience with 2 Minute Step Test for physiotherapists and involvement level in the product development project for designers. The questionnaire's reliability was validated using Cronbach's Alpha and the quantitative data of the questionnaires were analyzed using non-parametric hypothesis tests with a significance level of 0.05 (p <0.05) and descriptive statistics. As a result, this study provides a concise evaluation protocol which can assist designers in their development process, collecting quantitative feedback from consumer and users, and qualitative feedback from designers.

Keywords: Product Design, Product Evaluation, Prototypes, Step

Procedia PDF Downloads 111

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 121

Authors: Widari

Abstract:

This study aims to determine the relationship of fast food consumption preferences with macro and micro nutrient adequacy students of SMP Negeri 5 Padang. This study used a cross sectional study conducted on 100 students of SMP Negeri 5 Padang. The variables studied were fast food preferences, nutrition adequacy macronutrients (carbohydrate, protein, fat, fiber) and micro nutrients (sodium, calcium, iron). Confounding factor in this study was the physical activity level because it was considered quite affecting food consumption of students. Data collected by using a questionnaire food recall as many as 2 x 24 hours to see the history of the respondents eat at school day and on holidays. Then, data processed using software Nutrisurvey and Microsoft Excel 2010. The analysis was performed on samples that have low and medium category on physical activity. The physical activity was not analyzed with another variable to see the strength of the relationship between independent and dependent variables. So that, do restrictions on physical activity variables in an attempt to get rid of confounding in design. Univariate and bivariate analyzes performed using SPSS 16.0 for Windows with Kolmogrov-Smirnov statistical tests, confidence level = 95% (α = 0,05). Results of univariate analysis showed that more than 70% of respondents liked fast food. On average, respondents were malnourished macro; malnourished fiber (100%), carbohydrates (72%), and protein (56%), whereas for fat, excess intake of the respondents (41%). Furthermor, many respondents who have micronutrient deficiencies; 98% for sodium, 96% for iron, and 91% for calcium. The results of the bivariate analysis showed no significant association between fast food consumption preferences with macro and micro nutrient adequacy (p > 0,05). This happens because in the fact not all students who have a preference for fast food actually eat them. To study better in the future, it is expected sampling really like and eat fast food in order to obtain better analysis results.

Keywords: fast food, nutritional adequacy, preferences, students

Procedia PDF Downloads 371

Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

Procedia PDF Downloads 111

Authors: Pengcheng Xiang Jr., Xueqing Sun, Dong Ngoduy

Abstract:

In the context of rapid urbanization, urban sprawl has brought about extensive negative impacts on ecosystems and the environment, resulting in a gradual shift from "incremental growth" to ‘stock growth’ in cities. A detailed urban growth boundary is a prerequisite for urban renewal and management. This study takes Shenyang City, China, as the study area and evaluates the spatial distribution of urban spatial suitability in the study area from the perspective of spatial constraints-suitability using multi-source data and simulates the future rigid and elastic growth boundaries of the city in the study area using the CA-Markov model. The results show that (1) the suitable construction area and moderate construction area in the study area account for 8.76% and 19.01% of the total area, respectively, and the suitable construction area and moderate construction area show a trend of distribution from the urban centre to the periphery, mainly in Shenhe District, the southern part of Heping District, the western part of Dongling District, and the central part of Dadong District; (2) the area of expansion of construction land in the study area in the period of 2023-2030 is 153274.6977hm2, accounting for 44.39% of the total area of the study area; (3) the rigid boundary of the study area occupies an area of 153274.6977 hm2, accounting for 44.39% of the total area of the study area, and the elastic boundary of the study area contains an area of 75362.61 hm2, accounting for 21.69% of the total area of the study area. The study constructed a method for urban growth boundary delineation, which helps to apply remote sensing to guide future urban spatial growth management and urban renewal.

Keywords: urban growth boundary, spatial constraints, spatial suitability, urban sprawl

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Authors: Monojit Manna, Arpan Adhikary

Abstract:

In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: Misbahuddin Mahammad, P. Chandra Sekhar, Metuku Shyamsunder

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The oversampled output of a sigma-delta modulator is decimated to Nyquist sampling rate by decimation filters. The decimation filters work twofold; they decimate the sampling rate by a factor of OSR (oversampling rate) and they remove the out band quantization noise resulting in an increase in resolution. The speed, area and power consumption of oversampled converter are governed largely by decimation filters in sigma-delta A/D converters. The scope of the work is to design a decimation filter for sigma-delta ADC and simulation using MATLAB. The decimation filter structure is based on cascaded-integrated comb (CIC) filter. A second decimation filter is using CIC for large rate change and cascaded FIR filters, for small rate changes, to improve the frequency response. The proposed structure is even more hardware efficient.

Keywords: sigma delta modulator, CIC filter, decimation filter, compensation filter, noise shaping

Procedia PDF Downloads 453

Authors: Dara Satyadileep, Abdallah S. Berrouk

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Selective absorption of Hydrogen Sulphide (H2S) using methyldiethanol amine (MDEA) has become a point of interest as means of minimizing capital and operating costs of gas sweetening plants. This paper discusses the prominence of optimum design of column internals to best achieve H2S selectivity using MDEA. To this end, a kinetics-based process simulation model has been developed for a commercial gas sweetening unit. Trends of sweet gas H2S & CO2 contents as function of fraction active area (and hence residence time) have been explained through analysis of interdependent heat and mass transfer phenomena. Guidelines for column internals design in order to achieve desired degree of H2S selectivity are provided. Also the effectiveness of various operating conditions in achieving H2S selectivity for an industrial absorber with fixed internals is investigated.

Keywords: gas sweetening, H2S selectivity, methyldiethanol amine, process simulation, residence time

Procedia PDF Downloads 338

Authors: Zahra Yazdani Paraii, Zohreh Yazdani Paraei

Abstract:

Many urban designers and planners have been involved in the design of environmentally friendly or nature adaptable urban development models due to increase in urban populations in the recent century, limitation on natural resources, climate change, and lack of enough water and food. Ecological city is one of the latest models proposed to accomplish the latter goal. In this work, the existing establishing indicators of the ecological city are used regarding energy, water, land use and transportation issues. The model is used to compare the function of traditional settlements of Iran. The result of investigation shows that the specifications and functions of the traditional settlements of Iran fit well into the ecological city model. It is found that the inhabitants of the old cities and villages in Iran had founded ecological cities based on their knowledge of the environment and its natural opportunities and limitations.

Keywords: ecological city, traditional city, urban design, environment

Procedia PDF Downloads 247

Authors: Dorsa Pourmojib, Marc J. Boutin

Abstract:

Urban space is used everyday by a diverse range of urban dwellers, each with different expectations. In this space, opportunities and resources are not distributed equitably among urban dwellers, despite the importance of inclusivity. In addition, some marginalized groups may not be considered. These include people with low incomes, immigrants from diverse cultures, various age groups, and those with special needs. To this end, this research aims to enhance social equity in urban space by bridging the gap between social equity and spatial equity in the urban context. This gap in the knowledge base related to urban design may be present for several reasons; lack of studies on relationship between social equity and spatial equity in urban open space, lack of practical design strategies for promoting social equity in urban open space, lack of proper site analysis in terms of context and users of the site both for designing new urban open spaces and developing the existing ones, and lack of researchers that are designers and finally it could be related to priorities of the city’s policies in addressing such issues, since it is time, money and energy consuming. The main objective of this project is addressing the aforementioned gap in the knowledge by exploring the relationship between social equity and spatial equity in urban open space. Answering the main question of this research is a promising step to this end; 'What are the considerations towards providing social equity through the design of urban elements that offer spatial equity?' To answer the main question of this research there are several secondary questions which should be addressed. Such as; how can the characteristics of social equity be translated to spatial equity? What are the diverse user’s needs and which of their needs are not considered in that site? What are the specific elements in the site which should be designed in order to promote social equity? What is the current situation of social and spatial equity in the proposed site? To answer the research questions and achieve the proposed objectives, a three-step methodology has been implemented. Firstly, a comprehensive research framework based on the available literature has been presented. Afterwards, three different urban spaces have been analyzed in terms of specific key research questions as the precedent studies; Naqsh-e Jahan Square (Iran), Superkilen Park (Denmark) and Campo Dei Fiori (Italy). In this regard, a proper gap analysis of the current situation and the proposed situation of these sites has been conducted. Finally, by combining the extracted design considerations from the precedent studies and the literature review, practical design strategies have been introduced as a result of this research. The presented guidelines enable the designers to create socially equitable urban spaces. To conclude, this research proposes a spatial approach to social inclusion and equity in urban space by presenting a practical framework and criteria for translating social equity to spatial equity in urban areas.

Keywords: inclusive urban design, social equity, social inclusion, spatial equity

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Authors: Kumud Singh, Janvin Itteera, Priti Ukarde, Sanjay Malhotra, P. PMarathe, Ayan Bandyopadhay, Rakesh Meena, Vikram Rawat, L. M. Joshi

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Application of Permanent magnet technology to high frequency miniature klystron tubes to be utilized for space applications improves the efficiency and operational reliability of these tubes. But nevertheless the task of generating magnetic focusing forces to eliminate beam divergence once the beam crosses the electrostatic focusing regime and enters the drift region in the RF section of the tube throws several challenges. Building a high quality magnet focusing lens to meet beam optics requirement in cathode gun and RF interaction region is considered to be one of the critical issues for these high frequency miniature tubes. In this paper, electromagnetic design and particle trajectory studies in combined electric and magnetic field for optimizing the magnetic circuit using 3D finite element method (FEM) analysis software is presented. A rectangular configuration of the magnet was constructed to accommodate apertures for input and output waveguide sections and facilitate coupling of electromagnetic fields into the input klystron cavity and out from output klystron cavity through coupling loops. Prototype lenses have been built and have been tested after integration with the klystron tube. We discuss the design requirements and challenges, and the results from beam transmission of the prototype lens.

Keywords: beam transmission, Brillouin, confined flow, miniature klystron

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Authors: David Cook, Brynhildur Davidsdottir, Dadi. M. Kristofersson

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The approval of development projects with significant environmental impacts implies that the economic costs of the affected environmental resources must be less than the financial benefits, but such irreversible decisions are frequently made without ever attempting to estimate the monetary value of the losses. Due to this knowledge gap in the processes informing decision-making, development projects are commonly approved despite the potential for social welfare to be undermined. Heeding a repeated call by the OECD to commence economic accounting of environmental impacts as part of the cost-benefit analysis process for Icelandic energy projects, this paper sets out the results pertaining to the nation’s first two contingent valuation studies of geothermal areas likely to be developed in the near future. Interval regression using log-transformation was applied to estimate willingness to pay (WTP) for the preservation of the high-temperature Eldvörp and Hverahlíð fields. The estimated mean WTP was 8,333 and 7,122 ISK for Eldvörp and Hverahlíð respectively. Scaled up to the Icelandic population of national taxpayers, this equates to estimated total economic value of 2.10 and 1.77 billion ISK respectively. These results reinforce arguments in favour of accounting for the environmental impacts of Iceland’s future geothermal power projects as a mandatory component of the exploratory and production license application process. Further research is necessary to understand the economic impacts to specific ecosystem services associated with geothermal environments, particularly connected to changes in recreational amenity. In so doing, it would be possible to gain greater comprehension of the various components of total economic value, evolving understanding of why one geothermal area – in this case, Eldvörp – has a higher preservation value than another.

Keywords: decision-making, contingent valuation, geothermal energy, preservation

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Authors: Sungho Kim, Dae Shik Kim, Jong Min Lee

Abstract:

Fluid catalytic cracking (FCC) process is one of the most important process in modern refinery indusrty. This paper focuses on the fluid catalytic cracking (FCC) process. As the FCC process is difficult to model well, due to its nonlinearities and various interactions between its process variables, rigorous process modeling of whole FCC plant is demanded for control and plant-wide optimization of the plant. In this study, a process design for the FCC plant includes riser reactor, main fractionator, and gas processing unit was developed. A reactor model was described based on four-lumped kinetic scheme. Main fractionator, gas processing unit and other process units are designed to simulate real plant data, using a process flowsheet simulator, Aspen PLUS. The custom reactor model was integrated with the process flowsheet simulator to develop an integrated process model.

Keywords: fluid catalytic cracking, simulation, plant data, process design

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Authors: Moch Agus Choiron

Abstract:

Crash box design has been developed to obtain optimum energy absorption. In this study, two-segment crash box design with holes is investigated under oblique load. The deformation behavior and crash energy absorption are observed. The analysis was performed using finite element method. The crash test components were impactor, crash box, and fixed rigid base. Impactor and the fixed base material are modelled as a rigid, and crash box material as bilinear isotropic hardening. The models consist of 2 and 4 holes laid within ¼, ½ and ¾ from first segment length. 100 mm aluminum crash box and frontal crash velocity of 16 km/jam were selected. Based on simulation results, it can be concluded that 2 holes located at ¾ has the largest crash energy absorption. This behavior associated with deformation pattern, which produces higher number of folding than other models.

Keywords: crash Box, two-segments, holes configuration, oblique load, deformation pattern

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Authors: H. Tai Pham, Bae Wisup, Sungmin Jung, Ivan Efriza, Ratna Widyaningsih, Byung Un Min

Abstract:

The middle-phase-microemulsion in Alkaline-Surfactant-Polymer (ASP) solution and oil play important roles in the success of an ASP flooding process. The high quality microemulsion phase has ultralow interfacial tensions and it can increase oil recovery. The research used optimal experimental design and response-surface-methodology to predict the optimum concentration of chemicals in ASP solution for maximum microemulsion quality. Secondly, this optimal ASP formulation was implemented in core flooding test to investigate the effective injection volume. As the results, the optimum concentration of surfactants in the ASP solution is 0.57 wt.% and the highest effective injection volume is 19.33% pore volume.

Keywords: optimize, ASP, response surface methodology, solubilization ratio

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Authors: Devika Nair, Sean Bellairs, Ken Evans

Abstract:

Flow and erosion modeling provides an avenue for simulating the fine suspended sediment in surface water systems like streams and creeks. Fine suspended sediment is highly mobile, and many contaminants that may have been released by any sort of catchment disturbance attach themselves to these sediments. Therefore, a knowledge of fine suspended sediment transport is important in assessing contaminant transport. The CAESAR-Lisflood Landform Evolution Model, which includes a hydrologic model (TOPMODEL) and a hydraulic model (Lisflood), is being used to assess the sediment movement in tropical streams on account of a disturbance in the catchment of the creek and to determine the dynamics of sediment quantity in the creek through the years by simulating the model for future years. The accuracy of future simulations depends on the calibration and validation of the model to the past and present events. Calibration and validation of the model involve finding a combination of parameters of the model, which, when applied and simulated, gives model outputs similar to those observed for the real site scenario for corresponding input data. Calibrating the sediment output of the CAESAR-Lisflood model at the catchment level and using it for studying the equilibrium conditions of the landform is an area yet to be explored. Therefore, the aim of the study was to calibrate the CAESAR-Lisflood model and then validate it so that it could be run for future simulations to study how the landform evolves over time. To achieve this, the model was run for a rainfall event with a set of parameters, plus discharge and sediment data for the input point of the catchment, to analyze how similar the model output would behave when compared with the discharge and sediment data for the output point of the catchment. The model parameters were then adjusted until the model closely approximated the real site values of the catchment. It was then validated by running the model for a different set of events and checking that the model gave similar results to the real site values. The outcomes demonstrated that while the model can be calibrated to a greater extent for hydrology (discharge output) throughout the year, the sediment output calibration may be slightly improved by having the ability to change parameters to take into account the seasonal vegetation growth during the start and end of the wet season. This study is important to assess hydrology and sediment movement in seasonal biomes. The understanding of sediment-associated metal dispersion processes in rivers can be used in a practical way to help river basin managers more effectively control and remediate catchments affected by present and historical metal mining.

Keywords: erosion modelling, fine suspended sediments, hydrology, surface water systems

Procedia PDF Downloads 81