Search results for: thoughtful decision support system
23534 Project Stakeholders' Perceptions of Sustainability: A Case Example From the Turkish Construction Industry
Authors: F. Heyecan Giritli, Gizem Akgül
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Because of the raising population of world; the need for houses, buildings and infrastructures are increasing rapidly. Energy and water consumption, waste production continues to increase. If this situation of resources continues, there will be a significant loss for next generations. Therefore, there are a lot of researches and solutions developed in the world. Also sustainability criteria are collected together by some countries to serve construction industry with certification systems. Sustainable building production process’s scope requires different path from traditional building production process. Moreover, the key objective of sustainable buildings is that the process includes whole life cycle duration. The process approaches from the decision of the project to the end of it; so the project team is needed from the beginning of the integrated project delivery model. Further more, by defining project team at the beginning of the project provides communication among the team members and defined problem solving and decision making methods. In this research includes the certification systems among the world to comprehend the head lines and assessment criteria. Therefore, it is understand that usually all green building criteria have the same contents. The aim of this research is to assess the sustainable project stakeholder’ perceptions in Turkish construction industry from the point of occupation, job title and years of experience. Therefore, a survey is made to assess the perceptions of each attendant. In Turkey, sustainability criteria are not clearly defined; on the other hand some regulations like waste management, energy efficiency are made by legal agencies. LEED certification system is the most popular system in Turkey that has attended and certificated. From the LEED official data, it’s understood that 308 project registered in Turkey. Therefore, LEED sustainability criteria are used in the survey. Head lines of LEED certification criteria; sustainable sites, water efficiency, energy and atmosphere, material and resources, indoor environmental quality, innovation and regional priority are indicated to assess the perceptions of survey participants. Moreover, only surveying of criteria are not enough; so the equipment, methods, risks and benefits also considered.Keywords: LEED, sustainability, perceptions, stakeholders, construction, Turkey, risk, benefit
Procedia PDF Downloads 30123533 Topology Optimization of the Interior Structures of Beams under Various Load and Support Conditions with Solid Isotropic Material with Penalization Method
Authors: Omer Oral, Y. Emre Yilmaz
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Topology optimization is an approach that optimizes material distribution within a given design space for a certain load and boundary conditions by providing performance goals. It uses various restrictions such as boundary conditions, set of loads, and constraints to maximize the performance of the system. It is different than size and shape optimization methods, but it reserves some features of both methods. In this study, interior structures of the parts were optimized by using SIMP (Solid Isotropic Material with Penalization) method. The volume of the part was preassigned parameter and minimum deflection was the objective function. The basic idea behind the theory was considered, and different methods were discussed. Rhinoceros 3D design tool was used with Grasshopper and TopOpt plugins to create and optimize parts. A Grasshopper algorithm was designed and tested for different beams, set of arbitrary located forces and support types such as pinned, fixed, etc. Finally, 2.5D shapes were obtained and verified by observing the changes in density function.Keywords: Grasshopper, lattice structure, microstructures, Rhinoceros, solid isotropic material with penalization method, TopOpt, topology optimization
Procedia PDF Downloads 13623532 Integrated Gas Turbine Performance Diagnostics and Condition Monitoring Using Adaptive GPA
Authors: Yi-Guang Li, Suresh Sampath
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Gas turbine performance degrades over time, and the degradation is greatly affected by environmental, ambient, and operating conditions. The engines may degrade slowly under favorable conditions and result in a waste of engine life if a scheduled maintenance scheme is followed. They may also degrade fast and fail before a scheduled overhaul if the conditions are unfavorable, resulting in serious secondary damage, loss of engine availability, and increased maintenance costs. To overcome these problems, gas turbine owners are gradually moving from scheduled maintenance to condition-based maintenance, where condition monitoring is one of the key supporting technologies. This paper presents an integrated adaptive GPA diagnostics and performance monitoring system developed at Cranfield University for gas turbine gas path condition monitoring. It has the capability to predict the performance degradation of major gas path components of gas turbine engines, such as compressors, combustors, and turbines, using gas path measurement data. It is also able to predict engine key performance parameters for condition monitoring, such as turbine entry temperature that cannot be directly measured. The developed technology has been implemented into digital twin computer Software, Pythia, to support the condition monitoring of gas turbine engines. The capabilities of the integrated GPA condition monitoring system are demonstrated in three test cases using a model gas turbine engine similar to the GE aero-derivative LM2500 engine widely used in power generation and marine propulsion. It shows that when the compressor of the model engine degrades, the Adaptive GPA is able to predict the degradation and the changing engine performance accurately using gas path measurements. Such a presented technology and software are generic, can be applied to different types of gas turbine engines, and provide crucial engine health and performance parameters to support condition monitoring and condition-based maintenance.Keywords: gas turbine, adaptive GPA, performance, diagnostics, condition monitoring
Procedia PDF Downloads 8823531 Artificially Intelligent Context Aware Personal Computer Assistant (ACPCA)
Authors: Abdul Mannan Akhtar
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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection
Procedia PDF Downloads 46423530 Universal Design for Learning: Its Impact for Enhanced Performance in General Psychology
Authors: Jose Gay D. Gallego
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This study examined the learning performance in General Psychology of 297 freshmen of the CPSU-Main through the Pre and Post Tests. The instructional intervention via Universal Design for Learning (UDL) was applied to 33% (97 out of 297) of these freshmen as the Treatment Group while the 67% (200) belonged to the Control Group for traditional instructions. Statistical inferences utilized one-way Analysis of Variance for mean differences; Pearson R Correlations for bivariate relationships, and; Factor Analysis for significant components that contributed most to the Universal Design for Learning instructions. Findings showed very high levels of students’ acquired UDL skills. Results in the pre test in General Psychology, respectively, were low and average when grouped into low and high achievers. There was no significant mean difference in the acquired nine UDL components when categorized into seven colleges to generalize that between colleges they were on the same very high levels. Significant differences were found in three test areas in General Psychology in eight colleges whose students in College of teacher education taking the lead in the learning performance. Significant differences were also traced in the post test in favor of the students in the treatment group. This proved that UDL really impacted the learning performance of the low achieving students. Significant correlations were revealed between the components of UDL and General Psychology. There were twenty four significant itemized components that contributed most to UDL instructional interventions. Implications were emphasized to maximizing the principles of UDL with the contention of thoughtful planning related to the four curricular pillars of UDL: (a) instructional goals, (b) instructional delivery methods, (c) instructional materials, and (d) student assessments.Keywords: universal design for learning, enhanced performance, teaching innovation, technology in education, social science area
Procedia PDF Downloads 27723529 Investigating Salience Theory’s Implications for Real-Life Decision Making: An Experimental Test for Whether the Allais Paradox Exists under Subjective Uncertainty
Authors: Christoph Ostermair
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We deal with the effect of correlation between prospects on human decision making under uncertainty as proposed by the comparatively new and promising model of “salience theory of choice under risk”. In this regard, we show that the theory entails the prediction that the inconsistency of choices, known as the Allais paradox, should not be an issue in the context of “real-life decision making”, which typically corresponds to situations of subjective uncertainty. The Allais paradox, probably the best-known anomaly regarding expected utility theory, would then essentially have no practical relevance. If, however, empiricism contradicts this prediction, salience theory might suffer a serious setback. Explanations of the model for variable human choice behavior are mostly the result of a particular mechanism that does not come to play under perfect correlation. Hence, if it turns out that correlation between prospects – as typically found in real-world applications – does not influence human decision making in the expected way, this might to a large extent cost the theory its explanatory power. The empirical literature regarding the Allais paradox under subjective uncertainty is so far rather moderate. Beyond that, the results are hard to maintain as an argument, as the presentation formats commonly employed, supposably have generated so-called event-splitting effects, thereby distorting subjects’ choice behavior. In our own incentivized experimental study, we control for such effects by means of two different choice settings. We find significant event-splitting effects in both settings, thereby supporting the suspicion that the so far existing empirical results related to Allais paradoxes under subjective uncertainty may not be able to answer the question at hand. Nevertheless, we find that the basic tendency behind the Allais paradox, which is a particular switch of the preference relation due to a modified common consequence, shared by two prospects, is still existent both under an event-splitting and a coalesced presentation format. Yet, the modal choice pattern is in line with the prediction of salience theory. As a consequence, the effect of correlation, as proposed by the model, might - if anything - only weaken the systematic choice pattern behind the Allais paradox.Keywords: Allais paradox, common consequence effect, models of decision making under risk and uncertainty, salience theory
Procedia PDF Downloads 19923528 Cooperative Communication of Energy Harvesting Synchronized-OOK IR-UWB Based Tags
Authors: M. A. Mulatu, L. C. Chang, Y. S. Han
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Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration
Procedia PDF Downloads 49223527 Testing and Validation Stochastic Models in Epidemiology
Authors: Snigdha Sahai, Devaki Chikkavenkatappa Yellappa
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This study outlines approaches for testing and validating stochastic models used in epidemiology, focusing on the integration and functional testing of simulation code. It details methods for combining simple functions into comprehensive simulations, distinguishing between deterministic and stochastic components, and applying tests to ensure robustness. Techniques include isolating stochastic elements, utilizing large sample sizes for validation, and handling special cases. Practical examples are provided using R code to demonstrate integration testing, handling of incorrect inputs, and special cases. The study emphasizes the importance of both functional and defensive programming to enhance code reliability and user-friendliness.Keywords: computational epidemiology, epidemiology, public health, infectious disease modeling, statistical analysis, health data analysis, disease transmission dynamics, predictive modeling in health, population health modeling, quantitative public health, random sampling simulations, randomized numerical analysis, simulation-based analysis, variance-based simulations, algorithmic disease simulation, computational public health strategies, epidemiological surveillance, disease pattern analysis, epidemic risk assessment, population-based health strategies, preventive healthcare models, infection dynamics in populations, contagion spread prediction models, survival analysis techniques, epidemiological data mining, host-pathogen interaction models, risk assessment algorithms for disease spread, decision-support systems in epidemiology, macro-level health impact simulations, socioeconomic determinants in disease spread, data-driven decision making in public health, quantitative impact assessment of health policies, biostatistical methods in population health, probability-driven health outcome predictions
Procedia PDF Downloads 623526 Enabling Non-invasive Diagnosis of Thyroid Nodules with High Specificity and Sensitivity
Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.
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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine
Procedia PDF Downloads 5823525 Judicial Personality: Observing the Acceptable Limits
Authors: Sonia Anand Knowlton
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In many ways, judges can express their personality within and beyond their role as a judge. Judges can use their unique backgrounds and life experiences to inform their legal reasons and can also participate in certain extrajudicial activities outside of their role on the bench. For many judges, the line between the expression of this judicial personality, on the one hand, and the consequence of jeopardizing the public’s perception of their impartiality, on the other, is ambiguous if not wholly unclear. In the famous Canadian decision R v RDS, for instance, a Black judge who was hearing a case about police violence against a Black person was accused of being biased after she acknowledged that her community’s racial dynamics may have impacted the police’s conduct. Many within the legal community might find comfort in the belief that judges do not need to bring their ‘personality’ to the bench in order to uncover the law’s truths and impartially apply it. Indeed, and for a good reason, judges are often discouraged from allowing their personality to shine through in their role as a judge – because the expression of judicial personality can compromise the public perception of the impartiality of the administration of justice. This paper evaluates the theoretical constraints on the expression of judicial personality as a tool for legal decision-making and argues that judges from minority groups are held to a higher level of impartiality. Specifically, minority judges are disproportionately constrained from 1) using life experience to apply the law and 2) engaging in certain extrajudicial activities.Keywords: judging, legal decision making, judicial personality, extrajudicial activities
Procedia PDF Downloads 7323524 Lived Experience of Breast Cancer for Arab Muslim Women
Authors: Nesreen M. Alqaissi
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Little is known about the lived experiences of breast cancer among Arab Muslim women. The researcher used a qualitative interpretive phenomenological research design to explore the lived experiences of breast cancer as described by Jordanian Muslim women. A purposive sample of 20 women with breast cancer was recruited. Data were collected utilizing individual semi-structured interviews, and analyzed using Heideggerian Hermeneutical methodology. Results: Five related themes and one constitutive pattern: (a) breast cancer means death; (b) matriarchal family members as important source of support; (c) spirituality as a way to live and survive breast cancer; (d) concealing cancer experiences to protect self and families; (e) physicians as protectors and treatment decision makers; (f) the constitutive pattern: culture influencing Jordanian women experiences with breast cancer. In conclusion, researchers and healthcare providers should consider the influence of culture, spirituality, and families, when caring for women with breast cancer from Jordan.Keywords: breast cancer, Arab Muslim, Jordan, lived experiences, spirituality, culture
Procedia PDF Downloads 51423523 A Multi-Objective Decision Making Model for Biodiversity Conservation and Planning: Exploring the Concept of Interdependency
Authors: M. Mohan, J. P. Roise, G. P. Catts
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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker
Procedia PDF Downloads 33723522 Medical Knowledge Management since the Integration of Heterogeneous Data until the Knowledge Exploitation in a Decision-Making System
Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal
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Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks
Procedia PDF Downloads 39523521 Implementing Service Learning in the Health Education Curriculum
Authors: Karen Butler
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Johnson C. Smith University, one of the nation’s oldest Historically Black Colleges and Universities, has a strong history of service learning and community service. We first integrated service learning and peer education into health education courses in the spring of 2000. Students enrolled in the classes served as peer educators for the semester. Since then, the program has evolved and expanded but remains an integral part of several courses. The purpose of this session is to describe our program in terms of development, successes, and obstacles, and feedback received. A detailed description of the service learning component in HED 235: Drugs and Drug Education and HED 337: Environmental Health will be provided. These classes are required of our Community Health majors but are also popular electives for students in other disciplines. Three sources of student feedback were used to evaluate and continually modify the component: the SIR II course evaluation, service learning reflection papers, and focus group interviews. Student feedback has been largely positive. When criticism was given, it was thoughtful and constructive – given in the spirit of making it better for the next group. Students consistently agreed that the service learning program increased their awareness of pertinent health issues; that both the service providers and service recipients benefited from the project; and that the goals/issues targeted by the service learning component fit the objectives of the course. Also, evidence of curriculum and learning enhancement was found in the reflection papers and focus group sessions. Service learning sets up a win-win situation. It provides a way to respond to campus and community health needs while enhancing the curriculum, as students learn more by doing things that benefit the health and wellness of others. Service learning is suitable for any health education course and any target audience would welcome the effort.Keywords: black colleges, community health, health education, service learning
Procedia PDF Downloads 34023520 Purchasing Decision-Making in Supply Chain Management: A Bibliometric Analysis
Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri
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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer
Procedia PDF Downloads 8523519 Conceptualizing IoT Based Framework for Enhancing Environmental Accounting By ERP Systems
Authors: Amin Ebrahimi Ghadi, Morteza Moalagh
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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability
Procedia PDF Downloads 17223518 Proposal of a Model Supporting Decision-Making on Information Security Risk Treatment
Authors: Ritsuko Kawasaki, Takeshi Hiromatsu
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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization
Procedia PDF Downloads 37923517 Identification of Factors Influencing Costs in Green Projects
Authors: Nazirah Zainul Abidin, Nurul Zahirah Mokhtar Azizi
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Cost has always been the leading concern in green building development. The perception that construction cost for green building is higher than conventional buildings has only made the discussion of green building cost more difficult. Understanding the factors that will influence the cost of green construction is expected to shed light into what makes green construction more or at par with conventional projects, or perhaps, where cost can be optimised. This paper identifies the elements of cost before shifting the attention to the influencing factors. Findings from past studies uncovered various factors related to cost which are grouped into five focal themes i.e. awareness, knowledge, financial, technical, and government support. A conceptual framework is produced in a form of a flower diagram indicating the cost influencing factors of green building development. These factors were found to be both physical and non-physical aspects of a project. The framework provides ground for the next stage of research that is to further explore how these factors influence the project cost and decision making.Keywords: green project, factors influencing cost, hard cost, soft cost
Procedia PDF Downloads 34523516 Investigations into the Efficiencies of Steam Conversion in Three Reactor Chemical Looping
Authors: Ratnakumar V. Kappagantula, Gordon D. Ingram, Hari B. Vuthaluru
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This paper analyzes a three reactor chemical looping process for hydrogen production from natural gas, allowing for carbon dioxide capture through chemical looping technology. An oxygen carrier is circulated to separate carbon dioxide, to reduce steam for hydrogen production and to supply oxygen for combustion. In this study, the emphasis is placed on the steam conversion in the steam reactor by investigating the hydrogen efficiencies of the complete system at steam conversions of 15.8% and 50%. An Aspen Plus model was developed for a Three Reactor Chemical Looping process to study the effects of operational parameters on hydrogen production is investigated. Maximum hydrogen production was observed under stoichiometric conditions. Different conversions in the steam reactor, which was modelled as a Gibbs reactor, were found when Gibbs-identified products and user identified products were chosen. Simulations were performed for different oxygen carriers, which consist of an active metal oxide on an inert support material. For the same metal oxide mass flowrate, the fuel reactor temperature decreased for different support materials in the order: aluminum oxide (Al2O3) > magnesium aluminate (MgAl2O4) > zirconia (ZrO2). To achieve the same fuel reactor temperature for the same oxide mass flow rate, the inert mass fraction was found to be 0.825 for ZrO2, 0.7 for MgAl2O4 and 0.6 for Al2O3. The effect of poisoning of the oxygen carrier was also analyzed. With 3000 ppm sulfur-based impurities in the feed gas, the hydrogen product energy rate of the process were found to decrease by 0.4%.Keywords: aspen plus, chemical looping combustion, inert support balls, oxygen carrier
Procedia PDF Downloads 32823515 Instant Location Detection of Objects Moving at High Speed in C-OTDR Monitoring Systems
Authors: Andrey V. Timofeev
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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems
Procedia PDF Downloads 47023514 Analyzing Perceptions of Leadership Capacities After a Year-Long Leadership Development Training: An Exploratory Study of School Leaders in South Africa
Authors: Norma Kok, Diemo Masuko, Thandokazi Dlongwana, Komala Pillay
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CONTEXT: While many school principals have been outstanding teachers and have inherent leadership potential, many have not had access to the quality of leadership development or support that empowers them to produce high-quality education outcomes in extremely challenging circumstances. Further, school leaders in under-served communities face formidable challenges arising from insufficient infrastructure, overcrowded classrooms, socio-economic challenges within the community, and insufficient parental involvement, all of which put a strain on principals’ ability to lead their schools effectively. In addition few school leaders have access to other supportive networks, and many do not know how to build and leverage social capital to create opportunities for their schools and learners. Moreover, we know that fostering parental involvement in their children’s learning improves a child’s morale, attitude, and academic achievement across all subject areas, and promotes better behaviour and social adjustment. Citizen Leader Lab facilitates the Partners for Possibility (PfP) programme to provide leadership development and support to school leaders serving under-resourced communities in South Africa to create effective environments of learning. This is done by creating partnerships between school leaders and private-sector business leaders over a 12-month period. (185) OBJECTIVES: To explore school leaders’ perceptions of their leadership capacities and changes at their schools after being exposed to a year-long leadership development training programme. METHODS: School leaders gained new leadership capacities e.g. resilience, improved confidence, communication and conflict resolution skills - catalysing into improved cultures of collaborative decision-making and environments for enhanced teaching and learningprogramme based on the 70:20:10 model whereby: 10% of learning comes from workshops, 20% of learning takes place through peer learning and 70% of learning occurs through experiential learning as partnerships work together to identify and tackle challenges in targeted schools. Participants completed a post-programme questionnaire consisting of structured and unstructured questions and semi-structured interviews were conducted with them and their business leader. The interviews were audio-recorded, transcribed and thematic content analysis was undertaken. The analysis was inductive and emerging themes were identified. A code list was generated after coding was undertaken using computer software (Dedoose). Quantitative data gathered from surveys was aggregated and analysed. RESULTS: School leadership found the programme interesting and rewarding. They gained new leadership capacities such as resilience, improved confidence, communication and conflict resolution skills - catalyzing into improved cultures of collaborative decision-making and environments for enhanced teaching and learning. New networks resulted in tangible outcomes such as upgrades to school infrastructure, water and sanitation, vegetable gardens at schools resulting in nutrition for learners and/or intangible outcomes such as skills for members of school management teams (SMTs). Collaborative leadership led to SMTs being more aligned, efficient, and cohesive; and teachers being more engaged and motivated. Notable positive changes at the school inspired parents and community members to become more actively involved in the school and in their children’s education. CONCLUSION: The PfP programme leads to improved leadership capacities and improved school culture which leads to improved teaching and learning and new resources for schools.Keywords: collaborative decision-making, collaborative leadership, community involvement, confidence
Procedia PDF Downloads 9123513 Studies of Rule Induction by STRIM from the Decision Table with Contaminated Attribute Values from Missing Data and Noise — in the Case of Critical Dataset Size —
Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno
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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to realworld data.Keywords: rule induction, decision table, missing data, noise
Procedia PDF Downloads 39623512 The Use Support Vector Machine and Back Propagation Neural Network for Prediction of Daily Tidal Levels Along The Jeddah Coast, Saudi Arabia
Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati
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Sea level rise threatens to increase the impact of future storms and hurricanes on coastal communities. Accurate sea level change prediction and supplement is an important task in determining constructions and human activities in coastal and oceanic areas. In this study, support vector machines (SVM) is proposed to predict daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal parameter values of kernel function are determined using a genetic algorithm. The SVM results are compared with the field data and with back propagation (BP). Among the models, the SVM is superior to BPNN and has better generalization performance.Keywords: tides, prediction, support vector machines, genetic algorithm, back-propagation neural network, risk, hazards
Procedia PDF Downloads 46823511 Analysing the Applicability of a Participatory Approach to Life Cycle Sustainability Assessment: Case Study of a Housing Estate Regeneration in London
Authors: Sahar Navabakhsh, Rokia Raslan, Yair Schwartz
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Decision-making on regeneration of housing estates, whether to refurbish or re-build, has been mostly triggered by economic factors. To enable sustainable growth, it is vital that environmental and social impacts of different scenarios are also taken into account. The methodology used to include all the three sustainable development pillars is called Life Cycle Sustainability Assessment (LCSA), which comprises of Life Cycle Assessment (LCA) for the assessment of environmental impacts of buildings. Current practice of LCA is regularly conducted post design stage and by sustainability experts. Not only is undertaking an LCA at this stage less effective, but issues such as the limited scope for the definition and assessment of environmental impacts, the implication of changes in the system boundary and the alteration of each of the variable metrics, employment of different Life Cycle Impact Assessment Methods and use of various inventory data for Life Cycle Inventory Analysis can result in considerably contrasting results. Given the niche nature and scarce specialist domain of LCA of buildings, the majority of the stakeholders do not contribute to the generation or interpretation of the impact assessment, and the results can be generated and interpreted subjectively due to the mentioned uncertainties. For an effective and democratic assessment of environmental impacts, different stakeholders, and in particular the community and design team should collaborate in the process of data collection, assessment and analysis. This paper examines and evaluates a participatory approach to LCSA through the analysis of a case study of a housing estate in South West London. The study has been conducted throughout tier-based collaborative methods to collect and share data through surveys and co-design workshops with the community members and the design team as the main stakeholders. The assessment of lifecycle impacts is conducted throughout the process and has influenced the decision-making on the design of the Community Plan. The evaluation concludes better assessment transparency and outcome, alongside other socio-economic benefits of identifying and engaging the most contributive stakeholders in the process of conducting LCSA.Keywords: life cycle assessment, participatory LCA, life cycle sustainability assessment, participatory processes, decision-making, housing estate regeneration
Procedia PDF Downloads 14723510 The Effect of Law on Politics
Authors: Boukrida Rafiq
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Democracy is based on the notion that all citizens have the right to participate in the managing of political affairs and that every citizens input is of equal importance. This basic assumption clearly places emphasis on public participation in maintaining a stable democracy. The level of public participation, however is highly contested with many theorists arguing that too much public participation would overwhelm and ultimately cripple democratic systems. On the other hand, others who favor high levels of participation argue that more citizen involvement leads to greater representation. Regardless of these disagreements over the utopian level of participation, there is widespread agreement amongst scholars that, at the very least, some participation is necessary to maintain democratic systems. The ways in which citizens participate vary greatly and depending on the method used, influence political decision making at varying levels. The method of political participation is a key in controlling public influence over political affairs and therefore is also an integral part of maintaining democracy, whether it be "thin" (low levels of participation) or "Robust" (high levels of participation). High levels of participation or "robust" democracy are argued by some theorists to enhance democracy through providing the opportunity for more issues to be represented during decision making. The notion of widespread participation was first advanced by classical theorists.Keywords: assumption clearly places emphasis, ultimately cripple, influence political decision making at varying, classical theorists
Procedia PDF Downloads 46023509 Hindi Speech Synthesis by Concatenation of Recognized Hand Written Devnagri Script Using Support Vector Machines Classifier
Authors: Saurabh Farkya, Govinda Surampudi
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Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)
Procedia PDF Downloads 49923508 Exploring Challenges Faced by People Living with HIV/AIDS After Disclosure in Sub-Saharan Countries
Authors: Veliswa Nonfundo Hoho, Jabulani Gilford Kheswa
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HIV/AIDS has been a long-term condition worldwide, which does not only affect physical health but also causes psychological and social challenges in people living with this condition. In Sub-Saharan countries, namely; Nigeria, Uganda, Zimbabwe and South Africa, people living with HIV/AIDS come across different challenges especially after one has disclosed his/her status. They experience stigma and discrimination, isolation, lack of accessing and receiving treatment, lack of support and experience psychological distress. By using the evidence-based systematic review as a form of methodology, journal articles, dissertations, internet, and books were explored. This paper seeks to describe the challenges faced by people living with HIV/AIDS after disclosure, which forms a critical component of HIV/AIDS prevention and treatment interventions. The disclosure process model is used to underpin the study. This theory allows one to understand when and why interpersonal and verbal self-disclosure is beneficial for individuals who live with concealable stigmatized identities such as HIV/AIDS. Literature findings advocate that both negative and positive results were noted after disclosing one’s HIV status and psychosocial well-being of the majority of people living with HIV/AIDS also get affected especially in societies which subscribe HIV/AIDS pandemic to witchcraft. As for the infected homosexuals, research indicates that they suffer in silence and to cover their emotional emptiness due to ostracism, they often report low- self-efficacy with regard to condom use and become susceptible to reinfections which further place their lives at heightened risk for low immune system. In this regard, this paper challenges the policies which protect the dignity of people living with HIV/AIDS and calls for unity and financial support in favour of psychoeducational programmes and support groups aimed at curbing discrimination.Keywords: disclosure, discrimination, homosexuality, self-efficacy
Procedia PDF Downloads 23523507 Integrating Renewable Energy Forecasting Systems with HEMS and Developing It with a Bottom-Up Approach
Authors: Punit Gandhi, J. C. Brezet, Tim Gorter, Uchechi Obinna
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This paper introduces how weather forecasting could help in more efficient energy management for smart homes with the use of Home Energy Management Systems (HEMS). The paper also focuses on educating consumers and helping them make more informed decisions while using the HEMS. A combined approach of technical and user perspective has been selected to develop a novel HEMS-product-service combination in a more comprehensive manner. The current HEMS switches on/off the energy intensive appliances based on the fluctuating electricity tariffs, but with weather forecasting, it is possible to shift the time of use of energy intensive appliances to maximum electricity production from the renewable energy system installed in the house. Also, it is possible to estimate the heating/cooling load of the house for the day ahead demand. Hence, relevant insight is gained in the expected energy production and consumption load for the next day, facilitating better (more efficient, peak shaved, cheaper, etc.) energy management practices for smart homes. In literature, on the user perspective, it has been observed that consumers lose interest in using HEMS after three to four months. Therefore, to further help in better energy management practices, the new system had to be designed in a way that consumers would sustain their interaction with the system on a structural basis. It is hypothesized that, if consumers feel more comfortable with using such system, it would lead to a prolonged usage, including more energy savings and hence financial savings. To test the hypothesis, a survey for the HEMS is conducted, to which 59 valid responses were recorded. Analysis of the survey helped in designing a system which imparts better information about the energy production and consumption to the consumers. It is also found from the survey that, consumers like a variety of options and they do not like a constant reminder of what they should do. Hence, the final system is designed to encourage consumers to make an informed decision about their energy usage with a wide variety of behavioral options available. It is envisaged that the new system will be tested in several pioneering smart energy grid projects in both the Netherlands and India, with a continued ‘design thinking’ approach, combining the technical and user perspective, as the basis for further improvements.Keywords: weather forecasting, smart grid, renewable energy forecasting, user defined HEMS
Procedia PDF Downloads 23123506 The Experiences and Needs of Mothers’ of Children With Cancer in Coping With the Child's Disease
Authors: Maarja Karbus, Elsbet Lippmaa, Kadri Kööp, Mare Tupits
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Aim: The aim is to describe the experiences and needs of mothers of children with cancer in coping with the child's illness. Background: Cancer affects different life areas. Especially if it is a child, in this case the whole family is involved. Loved ones are mentally affected, there are limitations, and life changes need to be made to make the whole treatment regimen and recovery as comfortable as possible. Also, the whole process is expensive and time consuming. The research is part of a larger project that covers the experiences and needs of parents of children with chronic illness and coping strategies related to the child's illness. Design: Qualitative, empirical, descriptive research. Method: Semi-structured interviews were used to collect data and inductive content analysis was used to analyze the data. The interviews were conducted in the autumn of 2020, 5 respondents participated in the research. Results and Conclusions: The research revealed that the mothers' experiences of coping with a child's disease included health-related experiences, material aspects, changes in lifestyle, support systems and contact with professionals. Regarding the organizational and material aspects of life, the subjects presented experiences with economic problems, adaptation of changes in lifestyle, access to information and changes in the treatment process. With regard to health, the respondents identified experiences with the mother's physical and mental health and experiences with the health of an ill child. The experience of different support systems was related to the support of family, friends, acquaintances, various organizations and specialists. Experiences with specialist support included experiences with family relationships and positive and negatiive experiences with staff. The mothers' needs in dealing with the child's disease included the mother's emotional needs, the support of other family members, and the need for various support systems and services. The needs of coping with the child were the need for understanding, support, confidence, the need to be strong and courageous, the need to ignore one's own needs, and the need for personal time and rest. The needs of other family members included the needs of an ill child and the need to pay attention to other children in the family. The needs of different supporters and services were related to different helpers and different services.Keywords: cancer, mother, coping, child, need, experience, illness
Procedia PDF Downloads 15023505 Option Pricing Theory Applied to the Service Sector
Authors: Luke Miller
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This paper develops an options pricing methodology to value strategic pricing strategies in the services sector. More specifically, this study provides a unifying taxonomy of current service sector pricing practices, frames these pricing decisions as strategic real options, demonstrates accepted option valuation techniques to assess service sector pricing decisions, and suggests future research areas where pricing decisions and real options overlap. Enhancing revenue in the service sector requires proactive decision making in a world of uncertainty. In an effort to strategically price service products, revenue enhancement necessitates a careful study of the service costs, customer base, competition, legalities, and shared economies with the market. Pricing decisions involve the quality of inputs, manpower, and best practices to maintain superior service. These decisions further hinge on identifying relevant pricing strategies and understanding how these strategies impact a firm’s value. A relatively new area of research applies option pricing theory to investments in real assets and is commonly known as real options. The real options approach is based on the premise that many corporate decisions to invest or divest in assets are simply an option wherein the firm has the right to make an investment without any obligation to act. The decision maker, therefore, has more flexibility and the value of this operating flexibility should be taken into consideration. The real options framework has already been applied to numerous areas including manufacturing, inventory, natural resources, research and development, strategic decisions, technology, and stock valuation. Additionally, numerous surveys have identified a growing need for the real options decision framework within all areas of corporate decision-making. Despite the wide applicability of real options, no study has been carried out linking service sector pricing decisions and real options. This is surprising given the service sector comprises 80% of the US employment and Gross Domestic Product (GDP). Identifying real options as a practical tool to value different service sector pricing strategies is believed to have a significant impact on firm decisions. This paper identifies and discusses four distinct pricing strategies available to the service sector from an options’ perspective: (1) Cost-based profit margin, (2) Increased customer base, (3) Platform pricing, and (4) Buffet pricing. Within each strategy lie several pricing tactics available to the service firm. These tactics can be viewed as options the decision maker has to best manage a strategic position in the market. To demonstrate the effectiveness of including flexibility in the pricing decision, a series of pricing strategies were developed and valued using a real options binomial lattice structure. The options pricing approach discussed in this study allows service firms to directly incorporate market-driven perspectives into the decision process and thus synchronizing service operations with organizational economic goals.Keywords: option pricing theory, real options, service sector, valuation
Procedia PDF Downloads 355