Search results for: natural intelligence
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7210

Search results for: natural intelligence

5950 A Deep Learning Approach to Calculate Cardiothoracic Ratio From Chest Radiographs

Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

Abstract:

The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

Procedia PDF Downloads 98
5949 Improvement of Microscopic Detection of Acid-Fast Bacilli for Tuberculosis by Artificial Intelligence-Assisted Microscopic Platform and Medical Image Recognition System

Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

Abstract:

The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

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5948 Ecolodging as an Answer for Sustainable Development and Successful Resource Management: The Case of North West Coast in Alexandria

Authors: I. Elrouby

Abstract:

The continued growth of tourism in the future relies on maintaining a clean environment by achieving sustainable development. The erosion and degradation of beaches, the deterioration of coastal water quality, visual pollution of coastlines by massive developments, all this has contributed heavily to the loss of the natural attractiveness for tourism. In light of this, promoting the concept of sustainable coastal development is becoming a central goal for governments and private sector. An ecolodge is a small hotel or guesthouse that incorporates local architectural, cultural and natural characteristics, promotes environmental conservation through minimizing the use of waste and energy and produces social and economic benefits for local communities. Egypt has some scattered attempts in some areas like Sinai in the field of ecolodging. This research tends to investigate the potentials of the North West Coast (NWC) in Alexandria as a new candidate for ecolodging investments. The area is full of primitive natural and man-made resources. These, if used in an environmental-friendly way could achieve cost reductions as a result of successful resource management for investors on the one hand, and coastal preservation on the other hand. In-depth interviews will be conducted with stakeholders in the tourism sector to examine their opinion about the potentials of the research area for ecolodging developments. The candidates will be also asked to rate the importance of the availability of certain environmental aspects in such establishments such as the uses of resources that originate from local communities, uses of natural power sources, uses of an environmental-friendly sewage disposal, forbidding the use of materials of endangered species and enhancing cultural heritage conservation. The results show that the area is full of potentials that could be effectively used for ecolodging investments. This if efficiently used could attract ecotourism as a supplementary type of tourism that could be promoted in Alexandria aside cultural, recreational and religious tourism.

Keywords: Alexandria, ecolodging, ecotourism, sustainability

Procedia PDF Downloads 200
5947 Comparative Germination Studies in Mature Seeds of Haloxylon Salicornicum

Authors: Laila Almulla

Abstract:

As native plants are better adapted to the local environment, can endure long spells of drought, withstand high soil salinity levels and provide a more natural effect to landscape projects, their use in landscape projects are gaining popularity. Standardization of seed germination methods and raising the hardened plants of selected native plants for their use in landscape projects will both conserve natural resources and produce sustainable greenery. In the present study, Haloxylon salicornicum, a perennial herb with a potential use for urban greenery was selected for seed germination tests as there is an urgent need to mass multiply them for their large-scale use. Among the nine treatments tried with different concentrations of gibberelic acid (GA3) and dry heat, the seeds responded with treatments when the wings were removed. The control as well as 250 GA3 treatments produced the maximum germination of 86%.

Keywords: dormancy, gibberelic acid, germination trays , vigor index

Procedia PDF Downloads 400
5946 From Battles to Balance and Back: Document Analysis of EU Copyright in the Digital Era

Authors: Anette Alén

Abstract:

Intellectual property (IP) regimes have traditionally been designed to integrate various conflicting elements stemming from private entitlement and the public good. In IP laws and regulations, this design takes the form of specific uses of protected subject-matter without the right-holder’s consent, or exhaustion of exclusive rights upon market release, and the like. More recently, the pursuit of ‘balance’ has gained ground in the conceptualization of these conflicting elements both in terms of IP law and related policy. This can be seen, for example, in European Union (EU) copyright regime, where ‘balance’ has become a key element in argumentation, backed up by fundamental rights reasoning. This development also entails an ever-expanding dialogue between the IP regime and the constitutional safeguards for property, free speech, and privacy, among others. This study analyses the concept of ‘balance’ in EU copyright law: the research task is to examine the contents of the concept of ‘balance’ and the way it is operationalized and pursued, thereby producing new knowledge on the role and manifestations of ‘balance’ in recent copyright case law and regulatory instruments in the EU. The study discusses two particular pieces of legislation, the EU Digital Single Market (DSM) Copyright Directive (EU) 2019/790 and the finalized EU Artificial Intelligence (AI) Act, including some of the key preparatory materials, as well as EU Court of Justice (CJEU) case law pertaining to copyright in the digital era. The material is examined by means of document analysis, mapping the ways ‘balance’ is approached and conceptualized in the documents. Similarly, the interaction of fundamental rights as part of the balancing act is also analyzed. Doctrinal study of law is also employed in the analysis of legal sources. This study suggests that the pursuit of balance is, for its part, conducive to new battles, largely due to the advancement of digitalization and more recent developments in artificial intelligence. Indeed, the ‘balancing act’ rather presents itself as a way to bypass or even solidify some of the conflicting interests in a complex global digital economy. Indeed, such a conceptualization, especially when accompanied by non-critical or strategically driven fundamental rights argumentation, runs counter to the genuine acknowledgment of new types of conflicting interests in the copyright regime. Therefore, a more radical approach, including critical analysis of the normative basis and fundamental rights implications of the concept of ‘balance’, is required to readjust copyright law and regulations for the digital era. Notwithstanding the focus on executing the study in the context of the EU copyright regime, the results bear wider significance for the digital economy, especially due to the platform liability regime in the DSM Directive and with the AI Act including objectives of a ‘level playing field’ whereby compliance with EU copyright rules seems to be expected among system providers.

Keywords: balance, copyright, fundamental rights, platform liability, artificial intelligence

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5945 Performance of Non-Deterministic Structural Optimization Algorithms Applied to a Steel Truss Structure

Authors: Ersilio Tushaj

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The efficient solution that satisfies the optimal condition is an important issue in the structural engineering design problem. The new codes of structural design consist in design methodology that looks after the exploitation of the total resources of the construction material. In recent years some non-deterministic or meta-heuristic structural optimization algorithms have been developed widely in the research community. These methods search the optimum condition starting from the simulation of a natural phenomenon, such as survival of the fittest, the immune system, swarm intelligence or the cooling process of molten metal through annealing. Among these techniques the most known are: the genetic algorithms, simulated annealing, evolution strategies, particle swarm optimization, tabu search, ant colony optimization, harmony search and big bang crunch optimization. In this study, five of these algorithms are applied for the optimum weight design of a steel truss structure with variable geometry but fixed topology. The design process selects optimum distances and size sections from a set of commercial steel profiles. In the formulation of the design problem are considered deflection limitations, buckling and allowable stress constraints. The approach is repeated starting from different initial populations. The design problem topology is taken from an existing steel structure. The optimization process helps the engineer to achieve good final solutions, avoiding the repetitive evaluation of alternative designs in a time consuming process. The algorithms used for the application, the results of the optimal solutions, the number of iterations and the minimal weight designs, will be reported in the paper. Based on these results, it would be estimated, the amount of the steel that could be saved by applying structural analysis combined with non-deterministic optimization methods.

Keywords: structural optimization, non-deterministic methods, truss structures, steel truss

Procedia PDF Downloads 230
5944 Covid Medical Imaging Trial: Utilising Artificial Intelligence to Identify Changes on Chest X-Ray of COVID

Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

Abstract:

Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

Procedia PDF Downloads 93
5943 The Aspect of the Digital Formation in the Solar Community as One Prototype to Find the Algorithmic Sustainable Conditions in the Global Environment

Authors: Kunihisa Kakumoto

Abstract:

Purpose: The global environmental problem is now raised in the global dimension. The sprawl phenomenon over the natural limitation is to be made a forecast beforehand in an algorithmic way so that the condition of our social life can hopefully be protected under the natural limitation. The sustainable condition in the globe is now to be found to keep the balance between the capacity of nature and the possibility of our social lives. The amount of water on the earth is limited. Therefore, on the reason, sustainable conditions are strongly dependent on the capacity of water. The amount of water can be considered in relation to the area of the green planting because a certain volume of the water can be obtained in the forest, where the green planting can be preserved. We can find the sustainable conditions of the water in relation to the green planting area. The reduction of CO₂ by green planting is also possible. Possible Measure and the Methods: Until now, by the opportunity of many international conferences, the concept of the solar community as one prototype has been introduced by technical papers. The algorithmic trial calculation on the basic concept of the solar community can be taken into consideration. The concept of the solar community is based on the collected data of the solar model house. According to the algorithmic results of the prototype, the simulation work in the globe can be performed as the algorithmic conversion results. This algorithmic study can be simulated by the amount of water, also in relation to the green planting area. Additionally, the submission of CO₂ in the solar community and the reduction of CO₂ by green planting can be calculated. On the base of these calculations in the solar community, the sustainable conditions on the globe can be simulated as the conversion results in an algorithmic way. The digital formation in the solar community can also be taken into consideration by this opportunity. Conclusion: For the finding of sustainable conditions around the globe, the solar community as one prototype has been taken into consideration. The role of the water is very important because the capacity of the water supply is very limited. But, at present, the cycle of the social community is not composed by the point of the natural mechanism. The simulative calculation of this study can be shown by the limitation of the total water supply. According to this process, the total capacity of the water supply and the capable residential number of the population and the areas can be taken into consideration by the algorithmic calculation. For keeping enough water, the green planting areas are very important. The planting area is also very important to keep the balance of CO₂. The simulative calculation can be performed by the relation between the submission and the reduction of CO₂ in the solar community. For the finding of this total balance and the sustainable conditions, the green planting area and the total amount of water can be recognized by the algorithmic simulative calculation. The study for the finding of sustainable conditions can be performed by the simulative calculations on the algorithmic model in the solar community as one prototype. The example of one prototype can be in balance. The activity of the social life must be in the capacity of the natural mechanism. The capable capacity of the natural environment in our world is very limited.

Keywords: the solar community, the sustainable condition, the natural limitation, the algorithmic calculation

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5942 Important Factors for Successful Solution of Emotional Situations: Empirical Study on Young People

Authors: R. Lekaviciene, D. Antiniene

Abstract:

Attempts to split the construct of emotional intelligence (EI) into separate components – ability to understand own and others’ emotions and ability to control own and others’ emotions may be meaningful more theoretically than practically. In real life, a personality encounters various emotional situations that require exhibition of complex EI to solve them. Emotional situation solution tests enable measurement of such undivided EI. The object of the present study is to determine sociodemographic and other factors that are important for emotional situation solutions. The study involved 1,430 participants from various regions of Lithuania. The age of participants varied from 17 years to 27 years. Emotional social and interpersonal situation scale EI-DARL-V2 was used. Each situation had two mandatory answering formats: The first format contained assignments associated with hypothetical theoretical knowledge of how the situation should be solved, while the second format included the question of how the participant would personally resolve the given situation in reality. A questionnaire that contained various sociodemographic data of subjects was also presented. Factors, statistically significant for emotional situation solution, have been determined: gender, family structure, the subject’s relation with his or her mother, mother’s occupation, subjectively assessed financial situation of the family, level of education of the subjects and his or her parents, academic achievement, etc. The best solvers of emotional situations are women with high academic achievements. According to their chosen study profile/acquired profession, they are related to the fields in social sciences and humanities. The worst solvers of emotional situations are men raised in foster homes. They are/were bad students and mostly choose blue-collar professions.

Keywords: emotional intelligence, emotional situations, solution of situation, young people

Procedia PDF Downloads 180
5941 Drones, Rebels and Bombs: Explaining the Role of Private Security and Expertise in a Post-piratical Indian Ocean

Authors: Jessica Kate Simonds

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The last successful hijacking perpetrated by Somali pirates in 2012 represented a critical turning point for the identity and brand of Indian Ocean (IO) insecurity, coined in this paper as the era of the post-piratical. This paper explores the broadening of the PMSC business model to account and contribute to the design of a new IO security environment that prioritises foreign and insurgency drone activity and Houthi rebel operations as the main threat to merchant shipping in the post-2012 era. This study is situated within a longer history of analysing maritime insecurity and also contributes a bespoke conceptual framework that understands the sea as a space that is produced and reproduced relative to existing and emerging threats to merchant shipping based on bespoke models of information sharing and intelligence acquisition. This paper also makes a prominent empirical contribution by drawing on a post-positivist methodology, data drawn from original semi-structured interviews with senior maritime insurers and active merchant seafarers that is triangulated with industry-produced guidance such as the BMP series as primary data sources. Each set is analysed through qualitative discourse and content analysis and supported by the quantitative data sets provided by the IMB Piracy Reporting center and intelligence networks. This analysis reveals that mechanisms such as the IGP&I Maritime Security Committee and intelligence divisions of PMSC’s have driven the exchanges of knowledge between land and sea and thus the reproduction of the maritime security environment through new regulations and guidance to account dones, rebels and bombs as the key challenges in the IO, beyond piracy. A contribution of this paper is the argument that experts who may not be in the highest-profile jobs are the architects of maritime insecurity based on their detailed knowledge and connections to vessels in transit. This paper shares the original insights of those who have served in critical decision making spaces to demonstrate that the development and refinement of industry produced deterrence guidance that has been accredited to the mitigation of piracy, have shaped new editions such as BMP 5 that now serve to frame a new security environment that prioritises the mitigation of risks from drones and WBEID’s from both state and insurgency risk groups. By highlighting the experiences and perspectives of key players on both land and at sea, the key finding of this paper is outlining that as pirates experienced a financial boom by profiteering from their bespoke business model during the peak of successful hijackings, the private security market encountered a similar level of financial success and guaranteed risk environment in which to prospect business. Thus, the reproduction of the Indian Ocean as a maritime security environment reflects a new found purpose for PMSC’s as part of the broader conglomerate of maritime insurers, regulators, shipowners and managers who continue to redirect the security consciousness and IO brand of insecurity.

Keywords: maritime security, private security, risk intelligence, political geography, international relations, political economy, maritime law, security studies

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5940 Inorganic Anion Removal from Water Using Natural Adsorbents

Authors: A. Ortuzar, I. Escondrillas, F. Mijangos

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There is a need for new systems that can be attached to drinking water treatment plants and have the required treatment capacity as well as the selectivity regarding components derived from anthropogenic activities. In a context of high volumes of water and low concentration of contaminants, adsorption/interchange processes are appealing since they meet the required features. Iron oxides such as siderite and molysite, which are respectively based on FeCO3 and FeCl3, can be found in nature. In this work, their observed performance, raw or roasted at different temperatures, as adsorbents of some inorganic anions is discussed. Roasted 1:1 FeCO3: FeCl3 mixture was very selective for arsenic and allowed a 100% removal of As from a 10 mg L-1 As solution. Besides, the 1:1 FeCO3 and FeCl3 mixture roasted at 500 ºC showed good selectivity for, in order of preference, arsenate, bromate, phosphate, fluoride and nitrate anions with distribution coefficients of, respectively, 4200, 2800, 2500 0.4 and 0.03 L g-1.

Keywords: drinking water, natural adsorbent materials, removal, selectivity

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5939 An Overview of Electronic Waste as Aggregate in Concrete

Authors: S. R. Shamili, C. Natarajan, J. Karthikeyan

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Rapid growth of world population and widespread urbanization has remarkably increased the development of the construction industry which caused a huge demand for sand and gravels. Environmental problems occur when the rate of extraction of sand, gravels, and other materials exceeds the rate of generation of natural resources; therefore, an alternative source is essential to replace the materials used in concrete. Now-a-days, electronic products have become an integral part of daily life which provides more comfort, security, and ease of exchange of information. These electronic waste (E-Waste) materials have serious human health concerns and require extreme care in its disposal to avoid any adverse impacts. Disposal or dumping of these E-Wastes also causes major issues because it is highly complex to handle and often contains highly toxic chemicals such as lead, cadmium, mercury, beryllium, brominates flame retardants (BFRs), polyvinyl chloride (PVC), and phosphorus compounds. Hence, E-Waste can be incorporated in concrete to make a sustainable environment. This paper deals with the composition, preparation, properties, classification of E-Waste. All these processes avoid dumping to landfills whilst conserving natural aggregate resources, and providing a better environmental option. This paper also provides a detailed literature review on the behaviour of concrete with incorporation of E-Wastes. Many research shows the strong possibility of using E-Waste as a substitute of aggregates eventually it reduces the use of natural aggregates in concrete.

Keywords: dumping, electronic waste, landfill, toxic chemicals

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5938 Studying Medicinal Plants of Rajasthan Used by Tribes for Different Diseases

Authors: Rekha Vijayvergia

Abstract:

Around seven percent of tribal population of India lives in Rajasthan. Rajasthan has rich cultural diversity and biodiversity. Ethno-botany can be defined as the total natural and traditional relationship and the interactions between man and his surrounding plant wealth from times immemorial, due to sheer, necessity, intuition, observation, and experimentation. Medicinal plants are valuable and are used for the production of various drugs. These plants produce a high diversity of natural products or secondary metabolites like Mahanimbicine, Andrographine, murrayaline, lupeol, and limonin etc. with a prominent function in the protection against diseases like diabetes, kidney stones, osteoporosis, tumours, opthalmia, leucorrhoea, bronchial asthma, diarrhea, cancer, etc. The present report gives an account of traditional medicinal uses of common medicinal plants of Rajasthan. A total of 18 plant species belonging to 13 families are reported, that are being used for various purposes.

Keywords: ethno botany, Rajasthan, secondary metabolites, traditional medicines

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5937 A Thorough Analysis on The Dialog Application Replika

Authors: Weeam Abdulrahman, Gawaher Al-Madwary, Fatima Al-Ammari, Razan Mohammad

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This research discusses the AI features in Replika which is a dialog with a customized characters application, interaction and communication with AI in different ways that is provided for the user. spreading a survey with questions on how the AI worked is one approach of exposing the app to others to utilize and also we made an analysis that provides us with the conclusion of our research as a result, individuals will be able to try out the app. In the methodology we explain each page that pops up in the screen while using replika and Specify each part and icon.

Keywords: Replika, AI, artificial intelligence, dialog app

Procedia PDF Downloads 177
5936 Experimental Investigation of Heat Pipe with Annular Fins under Natural Convection at Different Inclinations

Authors: Gangacharyulu Dasaroju, Sumeet Sharma, Sanjay Singh

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Heat pipe is characterised as superconductor of heat because of its excellent heat removal ability. The operation of several engineering system results in generation of heat. This may cause several overheating problems and lead to failure of the systems. To overcome this problem and to achieve desired rate of heat dissipation, there is need to study the performance of heat pipe with annular fins under free convection at different inclinations. This study demonstrates the effect of different mass flow rate of hot fluid into evaporator section on the condenser side heat transfer coefficient with annular fins under natural convection at different inclinations. In this study annular fins are used for the experimental work having dimensions of length of fin, thickness of fin and spacing of fin as 10 mm, 1 mm and 6 mm, respectively. The main aim of present study is to discover at what inclination angles the maximum heat transfer coefficient shall be achieved. The heat transfer coefficient on the external surface of heat pipe condenser section is determined by experimental method and then predicted by empirical correlations. The results obtained from experimental and Churchill and Chu relation for laminar are in fair agreement with not more than 22% deviation. It is elucidated the maximum heat transfer coefficient of 31.2 W/(m2-K) at 25˚ tilt angle and minimal condenser heat transfer coefficient of 26.4 W/(m2-K) is seen at 45˚ tilt angle and 200 ml/min mass flow rate. Inclination angle also affects the thermal performance of heat pipe. Beyond 25o inclination, heat transport rate starts to decrease.

Keywords: heat pipe, annular fins, natural convection, condenser heat transfer coefficient, tilt angle

Procedia PDF Downloads 154
5935 Artificial Intelligence in Management Simulators

Authors: Nuno Biga

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Artificial Intelligence (AI) has the potential to transform management into several impactful ways. It allows machines to interpret information to find patterns in big data and learn from context analysis, optimize operations, make predictions sensitive to each specific situation and support data-driven decision making. The introduction of an 'artificial brain' in organization also enables learning through complex information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) sensitive to context, that provides users useful suggestions to pursue the following operations such as: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time existing bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed and demonstrated through a pilot project (BIG-AI). Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of data is powered in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" (VA) that players can use during the Game. Each participant in the VA permanently asks himself about the decisions he should make during the game to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making, through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, as they gain a better understanding of the issues along time, reflect on good practice and rely on their own experience, capability and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator designated as “Serious Game Controller” (SGC) is responsible for supporting the players with further analysis. The recommended actions by the SGC may differ or be similar to the ones previously provided by the VA, ensuring a higher degree of robustness in decision-making. Additionally, all the information should be jointly analyzed and assessed by each player, who are expected to add “Emotional Intelligence”, an essential component absent from the machine learning process.

Keywords: artificial intelligence, gamification, key performance indicators, machine learning, management simulators, serious games, virtual assistant

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5934 ChatGPT 4.0 Demonstrates Strong Performance in Standardised Medical Licensing Examinations: Insights and Implications for Medical Educators

Authors: K. O'Malley

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Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora.

Keywords: artificial intelligence, ChatGPT, generative ai, large language models, licensing exam, medical education, medicine, university

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5933 Artificial Law: Legal AI Systems and the Need to Satisfy Principles of Justice, Equality and the Protection of Human Rights

Authors: Begum Koru, Isik Aybay, Demet Celik Ulusoy

Abstract:

The discipline of law is quite complex and has its own terminology. Apart from written legal rules, there is also living law, which refers to legal practice. Basic legal rules aim at the happiness of individuals in social life and have different characteristics in different branches such as public or private law. On the other hand, law is a national phenomenon. The law of one nation and the legal system applied on the territory of another nation may be completely different. People who are experts in a particular field of law in one country may have insufficient expertise in the law of another country. Today, in addition to the local nature of law, international and even supranational law rules are applied in order to protect basic human values and ensure the protection of human rights around the world. Systems that offer algorithmic solutions to legal problems using artificial intelligence (AI) tools will perhaps serve to produce very meaningful results in terms of human rights. However, algorithms to be used should not be developed by only computer experts, but also need the contribution of people who are familiar with law, values, judicial decisions, and even the social and political culture of the society to which it will provide solutions. Otherwise, even if the algorithm works perfectly, it may not be compatible with the values of the society in which it is applied. The latest developments involving the use of AI techniques in legal systems indicate that artificial law will emerge as a new field in the discipline of law. More AI systems are already being applied in the field of law, with examples such as predicting judicial decisions, text summarization, decision support systems, and classification of documents. Algorithms for legal systems employing AI tools, especially in the field of prediction of judicial decisions and decision support systems, have the capacity to create automatic decisions instead of judges. When the judge is removed from this equation, artificial intelligence-made law created by an intelligent algorithm on its own emerges, whether the domain is national or international law. In this work, the aim is to make a general analysis of this new topic. Such an analysis needs both a literature survey and a perspective from computer experts' and lawyers' point of view. In some societies, the use of prediction or decision support systems may be useful to integrate international human rights safeguards. In this case, artificial law can serve to produce more comprehensive and human rights-protective results than written or living law. In non-democratic countries, it may even be thought that direct decisions and artificial intelligence-made law would be more protective instead of a decision "support" system. Since the values of law are directed towards "human happiness or well-being", it requires that the AI algorithms should always be capable of serving this purpose and based on the rule of law, the principle of justice and equality, and the protection of human rights.

Keywords: AI and law, artificial law, protection of human rights, AI tools for legal systems

Procedia PDF Downloads 75
5932 Partial Replacement of GGBS in Concrete for Prevention of Natural Resources

Authors: M. Murmu, Govardhan, J. Satya Eswari

Abstract:

Concrete is the most common and widely used building material. Concrete is basically made of aggregates, both fine and coarse, glued by a cement paste which is made of cement and water. Each one of these constituents of concrete has a negative environmental impact and gives rise to different sustainability issues. The current concrete construction practice is unsustainable because, not only it consumes enormous quantities of stones, sand, and drinking water, but also one billion tons a year of cement, which is not an environment friendly material. Preventing the reduction of natural resources and enhancing the usage of waste materials has become a challenge to the scientist and engineers. A number of studies have been conducted concerning the protection of natural resources, prevention of environmental pollution and contribution to the economy by using this waste material. This paper outlines the influence of Ground Granulated Blast furnace Slag (GGBS) as partial replacement of fine aggregate on mechanical properties of concrete. The strength of concrete is determined having OPC binder, replaced the fine aggregate with15%, 30%, 45% respectively. For this purpose, characteristics concrete mix of M25 with partial replacement of cement with GGBS is used and the strength of concrete cubes and cylinder have determined. The strength of concrete specimens has been compared with the reference specimen. Also X-ray diffraction (XRD) and scanning electron microscope (SEM) tests have been performed to examine the hydration products and the microstructure of the tested specimens. A correlation has been established between the developmental strength concrete with and without GGBS through analysis of hydration products and the microstructure.

Keywords: GGBS, sand, concrete, workability

Procedia PDF Downloads 503
5931 A Review on the Use of Plastic Waste with Viable Materials in Composite Construction Block

Authors: Mohan T. Harish, Masson Lauriane, Sreevalsa Kolathayar

Abstract:

Environmental issues raise alarm in the constructional field which implies a need for exploring new construction materials derived from the waste and residual products. This paper presents a detailed review of the alternatives approaches employed in the construction field using plastic waste in mixture with mixed with fillers. A detailed analysis of the plastic waste used in concrete, with soil, sand, clay and natural residues like sawdust, rice husk etc are presented. The different process carried forward was also discussed along with the scrutiny of the change in mechanical properties. The effect of coupling agents in the proposed mixture has been appraised in detail which gives implications for its future application in the field of plastic waste with viable materials in composite construction blocks.

Keywords: plastic waste, composite materials, construction block, concrete, natural residue, coupling agent

Procedia PDF Downloads 252
5930 Artificial Intelligence and Robotics in the Eye of Private Law with Special Regards to Intellectual Property and Liability Issues

Authors: Barna Arnold Keserű

Abstract:

In the last few years (what is called by many scholars the big data era) artificial intelligence (hereinafter AI) get more and more attention from the public and from the different branches of sciences as well. What previously was a mere science-fiction, now starts to become reality. AI and robotics often walk hand in hand, what changes not only the business and industrial life, but also has a serious impact on the legal system. The main research of the author focuses on these impacts in the field of private law, with special regards to liability and intellectual property issues. Many questions arise in these areas connecting to AI and robotics, where the boundaries are not sufficiently clear, and different needs are articulated by the different stakeholders. Recognizing the urgent need of thinking the Committee on Legal Affairs of the European Parliament adopted a Motion for a European Parliament Resolution A8-0005/2017 (of January 27th, 2017) in order to take some recommendations to the Commission on civil law rules on robotics and AI. This document defines some crucial usage of AI and/or robotics, e.g. the field of autonomous vehicles, the human job replacement in the industry or smart applications and machines. It aims to give recommendations to the safe and beneficial use of AI and robotics. However – as the document says – there are no legal provisions that specifically apply to robotics or AI in IP law, but that existing legal regimes and doctrines can be readily applied to robotics, although some aspects appear to call for specific consideration, calls on the Commission to support a horizontal and technologically neutral approach to intellectual property applicable to the various sectors in which robotics could be employed. AI can generate some content what worth copyright protection, but the question came up: who is the author, and the owner of copyright? The AI itself can’t be deemed author because it would mean that it is legally equal with the human persons. But there is the programmer who created the basic code of the AI, or the undertaking who sells the AI as a product, or the user who gives the inputs to the AI in order to create something new. Or AI generated contents are so far from humans, that there isn’t any human author, so these contents belong to public domain. The same questions could be asked connecting to patents. The research aims to answer these questions within the current legal framework and tries to enlighten future possibilities to adapt these frames to the socio-economical needs. In this part, the proper license agreements in the multilevel-chain from the programmer to the end-user become very important, because AI is an intellectual property in itself what creates further intellectual property. This could collide with data-protection and property rules as well. The problems are similar in the field of liability. We can use different existing forms of liability in the case when AI or AI led robotics cause damages, but it is unsure that the result complies with economical and developmental interests.

Keywords: artificial intelligence, intellectual property, liability, robotics

Procedia PDF Downloads 203
5929 Vibration Characteristics of Functionally Graded Thick Hollow Cylinders Using Galerkin Method

Authors: Pejman Daryabor, Kamal Mohammadi

Abstract:

In the present work, the study of vibration characteristics of a functionally graded thick hollow cylinder is investigated. The cylinder natural frequencies are obtained using Galerkin finite element method. The functionally graded cylinder is assumed to be made from many subcylinders. Each subcylinder is considered as an isotropic layer. Material’s properties in each layer are constant and functionally graded properties result by exponential function of layer radius in multilayer cylinder. To validate the FE results code, plane strain model of functionally graded cylinder are also modeled in ABAQUS. Analytical results are validated for both models. Also, a good agreement is found between the present results and those reported in the literature.

Keywords: natural frequency, functionally graded material, finite element method, thick cylinder

Procedia PDF Downloads 473
5928 Investigating the Properties of Asphalt Concrete Containing Recycled Fillers

Authors: Hasan Taherkhani

Abstract:

Increasingly accumulation of the solid waste materials has become a major environmental problem of communities. In addition to the protection of environment, the recycling and reusing of the waste materials are financially beneficial. Waste materials can be used in highway construction. This study aimed to investigate the applicability of recycled concrete, asphalt and steel slag powder, as a replacement of the primary mineral filler in asphalt concrete has been investigated. The primary natural siliceous aggregate filler, as control, has been replaced with the secondary recycled concrete, asphalt and steel slag powders, and some engineering properties of the mixtures have been evaluated. Marshal Stability, flow, indirect tensile strength, moisture damage, static creep and volumetric properties of the mixtures have been evaluated. The results show that, the Marshal Stability of the mixtures containing recycled powders is higher than that of the control mixture. The flow of the mixtures containing recycled steel slag is lower, and that of the mixtures containing recycled asphalt and cement concrete powder is found to be higher than that of the control mixture. It is also found that the resistance against moisture damage and permanent deformation of the mixture can be improved by replacing the natural filler with the recycled powders. The volumetric properties of the mixtures are not significantly influenced by replacing the natural filler with the recycled powders.

Keywords: filler, steel slag, recycled concrete, recycled asphalt concrete, tensile strength, moisture damage, creep

Procedia PDF Downloads 277
5927 Overweight and Neurocognitive Functioning: Unraveling the Antagonistic Relationship in Adolescents

Authors: Swati Bajpai, S. P. K Jena

Abstract:

Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

Procedia PDF Downloads 487
5926 Comparative Parametric Analysis on the Dynamic Response of Fibre Composite Beams with Debonding

Authors: Indunil Jayatilake, Warna Karunasena

Abstract:

Fiber Reinforced Polymer (FRP) composites enjoy an array of applications ranging from aerospace, marine and military to automobile, recreational and civil industry due to their outstanding properties. A structural glass fiber reinforced polymer (GFRP) composite sandwich panel made from E-glass fiber skin and a modified phenolic core has been manufactured in Australia for civil engineering applications. One of the major mechanisms of damage in FRP composites is skin-core debonding. The presence of debonding is of great concern not only because it severely affects the strength but also it modifies the dynamic characteristics of the structure, including natural frequency and vibration modes. This paper deals with the investigation of the dynamic characteristics of a GFRP beam with single and multiple debonding by finite element based numerical simulations and analyses using the STRAND7 finite element (FE) software package. Three-dimensional computer models have been developed and numerical simulations were done to assess the dynamic behavior. The FE model developed has been validated with published experimental, analytical and numerical results for fully bonded as well as debonded beams. A comparative analysis is carried out based on a comprehensive parametric investigation. It is observed that the reduction in natural frequency is more affected by single debonding than the equally sized multiple debonding regions located symmetrically to the single debonding position. Thus it is revealed that a large single debonding area leads to more damage in terms of natural frequency reduction than isolated small debonding zones of equivalent area, appearing in the GFRP beam. Furthermore, the extents of natural frequency shifts seem mode-dependent and do not seem to have a monotonous trend of increasing with the mode numbers.

Keywords: debonding, dynamic response, finite element modelling, novel FRP beams

Procedia PDF Downloads 117
5925 Construction Sustainability Improvement through Using Recycled Aggregates in Concrete Production

Authors: Zhiqiang Zhu, Khalegh Barati, Xuesong Shen

Abstract:

Due to the energy consumption caused by the construction industry, the public is paying more and more attention to the sustainability of the buildings. With the advancement of research on recycled aggregates, it has become possible to replace natural aggregates with recycled aggregates and to achieve a reduction in energy consumption of materials during construction. The purpose of this paper is to quantitatively compare the emergy consumption of natural aggregate concrete (NAC) and recycled aggregate concrete (RAC). To do so, the emergy analysis method is adopted. Using this technique, it can effectively analyze different forms of energy and substance. The main analysis object is the direct and indirect emergy consumption of the stages in concrete production. Therefore, for indirect energy, consumption of production machinery and transportation vehicle also need to be considered. Finally, the emergy values required to produce the two concrete types are compared to analyze whether the RAC can reduce emergy consumption.

Keywords: sustainable construction, NAC, RAC, emergy, concrete

Procedia PDF Downloads 150
5924 Impact of School Environment on Socio-Affective Development: A Quasi-Experimental Longitudinal Study of Urban and Suburban Gifted and Talented Programs

Authors: Rebekah Granger Ellis, Richard B. Speaker, Pat Austin

Abstract:

This study used two psychological scales to examine the level of social and emotional intelligence and moral judgment of over 500 gifted and talented high school students in various academic and creative arts programs in a large metropolitan area in the southeastern United States. For decades, numerous models and programs purporting to encourage socio-affective characteristics of adolescent development have been explored in curriculum theory and design. Socio-affective merges social, emotional, and moral domains. It encompasses interpersonal relations and social behaviors; development and regulation of emotions; personal and gender identity construction; empathy development; moral development, thinking, and judgment. Examining development in these socio-affective domains can provide insight into why some gifted and talented adolescents are not successful in adulthood despite advanced IQ scores. Particularly whether nonintellectual characteristics of gifted and talented individuals, such as emotional, social and moral capabilities, are as advanced as their intellectual abilities and how these are related to each other. Unique characteristics distinguish gifted and talented individuals; these may appear as strengths, but there is the potential for problems to accompany them. Although many thrive in their school environments, some gifted students struggle rather than flourish. In the socio-affective domain, these adolescents face special intrapersonal, interpersonal, and environmental problems. Gifted individuals’ cognitive, psychological, and emotional development occurs asynchronously, in multidimensional layers at different rates and unevenly across ability levels. Therefore, it is important to examine the long-term effects of participation in various gifted and talented programs on the socio-affective development of gifted and talented adolescents. This quasi-experimental longitudinal study examined students in several gifted and talented education programs (creative arts school, urban charter schools, and suburban public schools) for (1) socio-affective development level and (2) whether a particular gifted and talented program encourages developmental growth. The following research questions guided the study: (1) How do academically and artistically talented gifted 10th and 11th grade students perform on psychometric scales of social and emotional intelligence and moral judgment? Do they differ from their age or grade normative sample? Are their gender differences among gifted students? (2) Does school environment impact 10th and 11th grade gifted and talented students’ socio-affective development? Do gifted adolescents who participate in a particular school gifted program differ in their developmental profiles of social and emotional intelligence and moral judgment? Students’ performances on psychometric instruments were compared over time and by type of program. Participants took pre-, mid-, and post-tests over the course of an academic school year with Defining Issues Test (DIT-2) assessing moral judgment and BarOn EQ-I: YV assessing social and emotional intelligence. Based on these assessments, quantitative differences in growth on psychological scales (individual and school) were examined. Change scores between schools were also compared. If a school showed change, artifacts (culture, curricula, instructional methodology) provided insight as to environmental qualities that produced this difference.

Keywords: gifted and talented education, moral development, socio-affective development, socio-affective education

Procedia PDF Downloads 162
5923 Color Image Enhancement Using Multiscale Retinex and Image Fusion Techniques

Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

Abstract:

In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: image enhancement, multiscale retinex, image fusion, EGMSR

Procedia PDF Downloads 458
5922 Enhance Concurrent Design Approach through a Design Methodology Based on an Artificial Intelligence Framework: Guiding Group Decision Making to Balanced Preliminary Design Solution

Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

Abstract:

This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

Procedia PDF Downloads 136
5921 Simulation of Turboexpander Potential in a City Gate Station under Variations of Feed Characteristic

Authors: Tarannom Parhizkar, Halle Bakhteeyar

Abstract:

This paper presents a feasibility assessment of an expansion system applied to the natural gas transportation process in Iran. Power can be generated from the pressure energy of natural gas along its supply chain at various pressure reduction points by using turboexpanders. This technology is being applied in different countries around the world. The system consists of a turboexpander reducing the natural gas pressure and providing mechanical energy to drive electric generator. Moreover, gas pre-heating, required to prevent hydrate formation, is performed upstream of expansion stage using burner. The city gate station (CGS) has a nominal flow rate in range of 45000 to 270000 cubic meters per hour and a pressure reduction from maximum 62 bar at the upstream to 6 bar. Due to variable feed pressure and temperature in this station sensitivity analysis of generated electricity and required heat is performed. Results show that plant gain is more sensible to pressure variation than temperature changes. Furthermore, using turboexpander to reduce the pressure result in an electrical generation of 2757 to 17574 kW with the value of approximately 4 million US$ per year. Moreover, the required heat range to prevent a hydrate formation is almost 2189 to 14157 kW. To provide this heat, a burner is used with a maximum annual cost of 268,640 $ burner fuel. Therefore, the actual annual benefit of proposed plant modification is approximately over 6,5 million US$.

Keywords: feasibility study, simulation, turboexpander, feed characteristic

Procedia PDF Downloads 502