Search results for: artificial agency
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2868

Search results for: artificial agency

1158 Reflections on Economic Recession in the Early Period of Islam: Lessons for Nigeria

Authors: Khalid Ishola Bello

Abstract:

No condition is permanent in life. This phenomenon is more evident in the socio-economic and political life of man regardless of race, colour or religious affiliation. As the economy of an individual or nation stands to be favourable at one time, it may also experience decline and become unbearable at another time. Muslims, towards the third decade of Islam, experienced economic hardship due to some natural and artificial factors. The recession, which lasted for four years, was rescued by different approaches, and economic prosperity was later regained. Some years ago, Nigeria was drastically affected by an economic recession characterized by high rates of unemployment, illiquidity and inflation, which have caused depression to many individuals and organizations. It is the aim of this paper to look into the causes and remedies of the recession in that early period of Islam in order to suggest a way out of the unfriendly economic situation of Nigeria. An analytical method is adopted to draw some lessons from the situation of Muslims of that time to address the current economic challenges in Nigeria. Though Nigeria is not under any natural disaster, the causes seem to be a deliberate reaction of some Nigerians against the government's attempts to curb corruption at all costs and lapses in some government policies.

Keywords: recession, hardship, spiritual, lessons, early period of Islam

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1157 Empowered Women Entrepreneurs and Sustainable Rural Tourism: A Study into the Voices and Experiences of Local Women in the Sundarbans Area of Bangladesh

Authors: Jakia Rajoana

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The aim of this paper is to examine the role of women entrepreneurs in bringing about sustainable rural tourism (SRT) development in Sundarbans area of Bangladesh. Theoretically, it draws upon empowerment and entrepreneurial marketing concepts. Women entrepreneurship development and lack of empowered women as role models is an important issue for developing economies in South Asia. Despite the substantial role women play in rural economy of Sundarbans, their contribution remains overlooked as enterprises led by them are run on an informal basis and their business acumen is not taken seriously both by their families and society at large. Studies on SRT fail to engage in sufficient depth with the term applied in this paper as ‘invisible women on the margins’ who run their enterprises with no formal training or societal/familial support. Moreover, the link between their (non) tourism enterprise and their empowerment remains under-theorized. Thus empirically, this research seeks to fill a significant gap by focusing on a considerably under-researched Sundarbans region. Methodologically, this study follows a qualitative research design using visual ethnographic approach. Participant observation, semi-structured interviews, and documentation are the primary data collection instruments in three coastal communities – Munshigonj, Burigoalini and Gabura – in the Sundarbans area. By focusing on the narratives of these under-investigated women, this work aims to provide in-depth and nuanced insights into salient issues on marginal communities experience from rural women’s perspectives. Initial findings illustrate that the Sundarbans women have low income due to no or little education. In addition, socio-cultural and religious factors also restrict the scope of their extensive contribution to workplace. In addition, physical and social violence which is a common occurrence for these women inhibits their agency and contributes to their disempowerment.

Keywords: gender, empowerment, entrepreneurial marketing, sustainable rural tourism, Sundarbans

Procedia PDF Downloads 287
1156 Stabilization of Rotational Motion of Spacecrafts Using Quantized Two Torque Inputs Based on Random Dither

Authors: Yusuke Kuramitsu, Tomoaki Hashimoto, Hirokazu Tahara

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The control problem of underactuated spacecrafts has attracted a considerable amount of interest. The control method for a spacecraft equipped with less than three control torques is useful when one of the three control torques had failed. On the other hand, the quantized control of systems is one of the important research topics in recent years. The random dither quantization method that transforms a given continuous signal to a discrete signal by adding artificial random noise to the continuous signal before quantization has also attracted a considerable amount of interest. The objective of this study is to develop the control method based on random dither quantization method for stabilizing the rotational motion of a rigid spacecraft with two control inputs. In this paper, the effectiveness of random dither quantization control method for the stabilization of rotational motion of spacecrafts with two torque inputs is verified by numerical simulations.

Keywords: spacecraft control, quantized control, nonlinear control, random dither method

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1155 Model and Neural Control of the Depth of Anesthesia during Surgery

Authors: Javier Fernandez, Mayte Medina, Rafael Fernandez de Canete, Nuria Alcain, Juan Carlos Ramos-Diaz

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At present, the experimentation of anesthetic drugs on patients requires a regulation protocol, and the response of each patient to several doses of entry drug must be well known. Therefore, the development of pharmacological dose control systems is a promising field of research in anesthesiology. In this paper, it has been developed a non-linear compartmental the pharmacokinetic-pharmacodynamical model which describes the anesthesia depth effect in a sufficiently reliable way over a set of patients with the depth effect quantified by the Bi-Spectral Index. Afterwards, an Artificial Neural Network (ANN) predictive controller has been designed based on the depth of anesthesia model so as to keep the patient in the optimum condition while he undergoes surgical treatment. For the purpose of quantifying the efficiency of the neural predictive controller, a classical proportional-integral-derivative controller has also been developed to compare both strategies. Results show the superior performance of predictive neural controller during BiSpectral Index reference tracking.

Keywords: anesthesia, bi-spectral index, neural network control, pharmacokinetic-pharmacodynamical model

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1154 Smart Mobility Planning Applications in Meeting the Needs of the Urbanization Growth

Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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1153 Toxicological Effects of Atmospheric Fine Particulate Matter on Human Bronchial Epithelial Cells: Metabolic Activation, Genotoxicity and Epigenetic Modifications

Authors: M. Borgie, Z. Dagher, F. Ledoux, A. Verdin, F. Cazier, H. Greige, P. Shirali, D. Courcot

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In October 2013, the International Agency for Research on Cancer (IARC) classified outdoor air pollution and fine particulate matter (PM2.5) as carcinogenic to humans. Despite the clearly relationship established by epidemiological studies between PM exposure and the onset of respiratory and cardiovascular diseases, uncertainties remain about the physiopathological mechanisms responsible for these diseases. The aim of this work was to evaluate the toxicological effects of two samples of atmospheric PM2.5 collected at urban and rural sites on human bronchial epithelial cells, BEAS-2B, especially to investigate the metabolic activation of organic compounds, the alteration of epigenetic mechanisms (i.e. microRNAs genes expression), the phosphorylation of H2AX and the telomerase activity. Our results showed a significant increase in CYP1A1, CYP1B1, and AhRR genes expression, miR-21 gene expression, H2AX phosphorylation and telomerase activity in BEAS-2B cells after their exposure to PM2.5, both in a dose and site-dependent manner. These results showed that PM2.5, especially urban PM, are able to induce the expression of metabolizing enzymes which can provide metabolic biotransformation of organic compounds into more toxic and carcinogenic metabolites, and to induce the expression of the oncomiR miR-21 which promotes cell growth and enhances tumor invasion and metastasis in lung cancer. In addition, our results have highlighted the role of PM2.5 in the activation of telomerase, which can maintain the telomeres length and subsequently preventing cell death, and have also demonstrated the ability of PM2.5 to induce DNA breaks and thus to increase the risk of mutations or chromosomal translocations that lead to genomic instability. All these factors may contribute to cell abnormalities, and thus the development of cancer.

Keywords: BEAS-2B cells, carcinogenesis, epigenetic alterations and genotoxicity, PM2.5

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1152 Impact of Private Oil Palm Expansion on Indonesia Tropical Forest Deforestation Rate: Case Study in the Province of Riau

Authors: Arzyana Sunkar, Yanto Santosa, Intan Purnamasari, Yohanna Dalimunthe

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A variety of negative allegations have criticized the Indonesian oil palm plantations as being environmentally unfriendly. One of the important allegations thus must be verified is that expansion of Indonesian oil palm plantation has increased the deforestation rate of primary tropical forest. In relation to this, a research was conducted to study the origin or history of the status and land use of 8 private oil palm plantations (with a total of 46,372.38 ha) located in Riau Province. Several methods were employed: (1) conducting analysis of overlay maps between oil palm plantation studied with the 1986 Forest Map Governance Agreement (TGHK) and the 1994 and 2014 Riau Provincial Spatial Plans(RTRWP); (2) studying the Cultivation Right on Land (HGU) documents including the Forestry Ministerial Decree on the release of forest area and (3) interpretation of lands at imagery of bands 542, covering 3 years before and after the oil palm industries operated. In addition, field cross-checked, and interviews were conducted with National Land Agency, Plantation and Forestry Office and community figures. The results indicated that as much as 1.95% of the oil palm plantations under study were converted from production forest, 30.34% from limited production forest and 67.70% from area for other usage /conversion production forest. One year prior to the establishment of the plantations, the land cover types comprised of rubber plantations (49.96%), secondary forest (35.99%), bare land (10.17%), shrubs (3.03%) and mixed dryland farming-shrubs (0.84%), whereas the land use types comprised of 35.99% forest concession areas, 14.04% migrants dryland farms, and 49.96% Cultivation Right on Land of other companies. These results indicated that most of the private oil palm plantations under study, resulted from the conversion of production forests and the previous land use were not primary forest but rubber plantations and secondary forests.

Keywords: land cover types, land use history, primary forest, private oil palm plantations

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1151 Determining the Electrospinning Parameters of Poly(ε-Caprolactone)

Authors: M. Kagan Keler, Sibel Daglilar, Isil Kerti, Oguzhan Gunduz

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Electrospinning is a versatile way to occur fibers at nano-scale and polycaprolactone is a biomedical material which has a wide usage in cartilage defects and tissue regeneration. PCL is biocompatible and durable material which can be used in bio-implants. Therefore, electrospinning process was chosen as a fabrication method to get PCL fibers in an effective way because of its significant adjustments. In this research study, electrospinning parameters was evaluated during the producing of polymer tissue scaffolds. Polycaprolactone’s molecular weight was 80.000 Da and was employed as a tissue material in the electrospinning process. PCL was decomposed in dimethylformamid(DMF) and chloroform(CF) with the weight ratio of 1:1. Different compositions (1%, 3%, 5%, 10% and 20 %) of PCL was prepared in the laboratory conditions. All solvents with different percentages of PCL have been taken into the syringe and loaded into the electrospinning system. In electrospinning dozens of trial were applied to get homogeneously uniform scaffold samples. Taylor cone which is crucial point for electrospinning characteristic was occurred and changed in different voltages up to the material compositions’ conductivity. While the PCL percentages were increasing in the electrospinning, structure started to arise with droplets, which was an expressive problem for tissue scaffold. The vertical and horizontal layouts were applied to produce non-woven structures at all.

Keywords: tissue engineering, artificial scaffold, electrospinning, biocomposites

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1150 Multiclass Support Vector Machines with Simultaneous Multi-Factors Optimization for Corporate Credit Ratings

Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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1149 Exploring Tweet Geolocation: Leveraging Large Language Models for Post-Hoc Explanations

Authors: Sarra Hasni, Sami Faiz

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In recent years, location prediction on social networks has gained significant attention, with short and unstructured texts like tweets posing additional challenges. Advanced geolocation models have been proposed, increasing the need to explain their predictions. In this paper, we provide explanations for a geolocation black-box model using LIME and SHAP, two state-of-the-art XAI (eXplainable Artificial Intelligence) methods. We extend our evaluations to Large Language Models (LLMs) as post hoc explainers for tweet geolocation. Our preliminary results show that LLMs outperform LIME and SHAP by generating more accurate explanations. Additionally, we demonstrate that prompts with examples and meta-prompts containing phonetic spelling rules improve the interpretability of these models, even with informal input data. This approach highlights the potential of advanced prompt engineering techniques to enhance the effectiveness of black-box models in geolocation tasks on social networks.

Keywords: large language model, post hoc explainer, prompt engineering, local explanation, tweet geolocation

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1148 Simulation of Flood Inundation in Kedukan River Using HEC-RAS and GIS

Authors: Reini S. Ilmiaty, Muhammad B. Al Amin, Sarino, Muzamil Jariski

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Kedukan River is an artificial river which serves as a Watershed Boang drainage channel in Palembang. The river has upstream and downstream connected to Musi River, that often overflowing and flooding caused by the huge runoff discharge and high tide water level of Musi River. This study aimed to analyze the flood water surface profile on Kedukan River continued with flood inundation simulation to determine flooding prone areas in research area. The analysis starts from the peak runoff discharge calculations using rational method followed by water surface profile analysis using HEC-RAS program controlled by manual calculations using standard stages. The analysis followed by running flood inundation simulation using ArcGIS program that has been integrated with HEC-GeoRAS. Flood inundation simulation on Kedukan River creates inundation characteristic maps with depth, area, and circumference of inundation as the parameters. The inundation maps are very useful in providing an overview of flood prone areas in Kedukan River.

Keywords: flood modelling, HEC-GeoRAS, HEC-RAS, inundation map

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1147 Impact of Sociocultural Factors on Management and Utilization of Solid Waste in Ibadan Metropolis, Nigeria

Authors: Olufunmilayo Folaranmi

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This research was carried out to examine the impact of socio-cultural factors on the management and utilization of solid waste in Ibadan Metropolis. A descriptive survey research design was adopted for the study while a systematic and stratified random sampling technique was used to select 300 respondents which were categorized into high, middle and low-density areas. Four hypothesis were tested using chi-square test on variables of unavailability of waste disposal facilities and waste management, negligence of contractors to liaise with community members, lack of adequate environmental education and waste management and utilization, low level of motivation of sanitation workers with solid wastes management, lack of community full participation with solid waste management and utilization. Results showed that significant effect of waste disposal facilities on solid waste management and utilization (X2 +16.6, P < .05). Also, there is a significant relationship between negligence of the contractors to liaise with community elites with improper disposal (X2 = 87.5, P < .05). The motivation of sanitation workers is significantly related to solid waste management (X2 = 70.4, P < .05). Adequate environmental education and awareness influenced solid waste management. There was also a significant relationship between lack of community participation with waste management disposal and improper waste disposal. Based on the findings from the study it was recommended that the quality of life in urban centers should be improved, social welfare of the populace enhanced and environment should be adequately attended to. Poverty alleviation programmes should be intensified and made to live beyond the life of a particular administration, micro-credit facilities should be available to community members to promote their welfare. Lastly, sustained environmental education programmes for citizens at all levels of education, formal and informal through the use of agencies like Ethical and Attitudinal Reorientation Commission (EARCOM) and the National Orientation Agency (NOA).

Keywords: management, social welfare, socio-cultural factors, solid waste

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1146 Movement Optimization of Robotic Arm Movement Using Soft Computing

Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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1145 Capacity Building on Small Automatic Tracking Antenna Development for Thailand Space Sustainability

Authors: Warinthorn Kiadtikornthaweeyot Evans, Nawattakorn Kaikaew

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The communication system between the ground station and the satellite is very important to guarantee contact between both sides. Thailand, led by Geo-Informatics and Space Technology Development Agency (GISTDA), has received satellite images from other nation's satellites for a number of years. In 2008, Thailand Earth Observation Satellite (THEOS) was the first Earth observation satellite owned by Thailand. The mission was monitoring our country with affordable access to space-based Earth imagery. At this time, the control ground station was initially used to control the THEOS satellite by our Thai engineers. The Tele-commands were sent to the satellite according to requests from government and private sectors. Since then, GISTDA's engineers have gained their skill and experience to operate the satellite. Recently the desire to use satellite data is increasing rapidly due to space technology moving fast and giving us more benefits. It is essential to ensure that Thailand remains competitive in space technology. Thai Engineers have started to improve the performance of the control ground station in many different sections, also developing skills and knowledge in areas of satellite communication. Human resource skills are being enforced with development projects through capacity building. This paper focuses on the hands-on capacity building of GISTDA's engineers to develop a small automatic tracking antenna. The final achievement of the project is the first phase prototype of a small automatic tracking antenna to support the new technology of the satellites. There are two main subsystems that have been developed and tested; the tracking system and the monitoring and control software. The prototype first phase functions testing has been performed with Two Line Element (TLE) and the mission planning plan (MPP) file calculated from THEOS satellite by GISTDA.

Keywords: capacity building, small tracking antenna, automatic tracking system, project development procedure

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1144 The Predictive Value of Serum Bilirubin in the Post-Transplant De Novo Malignancy: A Data Mining Approach

Authors: Nasim Nosoudi, Amir Zadeh, Hunter White, Joshua Conrad, Joon W. Shim

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De novo Malignancy has become one of the major causes of death after transplantation, so early cancer diagnosis and detection can drastically improve survival rates post-transplantation. Most previous work focuses on using artificial intelligence (AI) to predict transplant success or failure outcomes. In this work, we focused on predicting de novo malignancy after liver transplantation using AI. We chose the patients that had malignancy after liver transplantation with no history of malignancy pre-transplant. Their donors were cancer-free as well. We analyzed 254,200 patient profiles with post-transplant malignancy from the US Organ Procurement and Transplantation Network (OPTN). Several popular data mining methods were applied to the resultant dataset to build predictive models to characterize de novo malignancy after liver transplantation. Recipient's bilirubin, creatinine, weight, gender, number of days recipient was on the transplant waiting list, Epstein Barr Virus (EBV), International normalized ratio (INR), and ascites are among the most important factors affecting de novo malignancy after liver transplantation

Keywords: De novo malignancy, bilirubin, data mining, transplantation

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1143 Sounds of Power: An Ethnoorganological Approach to Understanding Colonial Music Culture in the Peruvian Andes

Authors: Natascha Reich

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In colonial Peru, the Spanish crown relied on religious orders, most notably Dominicans, Franciscans, and Jesuits, for accelerating processes of colonization. The dissemination of Christian art, architecture, and music, and most of all, the agency of indigenous people in their production played a key role in facilitating the acceptance of the new religious and political system. Current research on Peruvian colonial music culture and its role as a vehicle for colonization focus on practices in urban centers. The lack of (written) primary sources seems to turn rural areas into a less attractive research territory for musicologists. This paper advocates for a more inclusive approach. By investigating seventeenth-century pipe organs as material remains of Franciscan missionary music culture, it shows how reactions to colonial forces and Christianization in rural Andean locations could follow tendencies different from those in urban areas. Indigenous musicians in cities tried to 'fit' into the European system in order to be accepted by the ruling Spanish elite. By contrast, the indigenous-built pipe organs in the rural Peruvian Colca-Valley show distinctly native-Andean influences. This paper argues that this syncretism can be interpreted as hybridity in Homi K. Bhabha’s sense, as a means of the colonized to undermine the power of the colonizer and to advance reactionary politics. Not only will it show the necessity of considering rural Peruvian music history in modern scholarship for arriving at a more complete picture of colonial culture, but it will also evidence the advantages of a mixed-methodology approach. Historical organology, combined with concepts from ethnomusicology and post-colonial studies, proves as a useful tool in the absence or scarcity of written primary sources.

Keywords: cultural hybridity, music as reactionary politics, Latin American pipe organs, Peruvian colonial music

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1142 Super-ellipsoidal Potential Function for Autonomous Collision Avoidance of a Teleoperated UAV

Authors: Mohammed Qasim, Kyoung-Dae Kim

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In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: artificial potential function, autonomous collision avoidance, teleoperation, quadrotor

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1141 Transfer Function Model-Based Predictive Control for Nuclear Core Power Control in PUSPATI TRIGA Reactor

Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

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1140 Ethical Considerations for Conducting Research on Violence against Women with Disabilities: Discussing Issues of Reasonable Accommodation, Capacity and Equal Participation

Authors: Ingrid Van Der Heijden, Naeemah Abrahams, Jane Harries

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Background: Women with disabilities are largely missing from global research on violence prevention, yet research shows that women with disabilities are a particularly marginalised group who experience heightened levels and unique forms of violence than men with disabilities, and women without disabilities. They face heightened stigma, discrimination, and violence due to their gender and their disability. Including women with disabilities in violence, research helps inform policy and prevention interventions that are relevant and inclusive. To ensure their inclusion in violence research, we need ethical guidelines that are sensitive to their heightened risk and vulnerability, that recognize the diversity in the disabled population, but that also promote disabled people’s agency in defining their own violence prevention needs and agendas. Objective: To highlight pertinent ethical issues around women with disabilities’ inclusion and participation in violence research. Methodology: Considering the lack of formalized guidelines for research of people with disabilities, we draw from the literature on international ethics guidelines for researching violence against women, and the Emancipatory Disability Research paradigm, as well as drawing from our own experiences from the field in applying the guidelines when doing research with disabled women. Findings: Following the guiding ethical principles of respect, benefit, justice, and do no harm, we argue that reasonable accommodation, capacity, and equal participation need to be considered in conceptualizing and conducting ethical violence research with women with disabilities. We conclude that disability research in the area of violence is highly politicized and must be carefully scrutinized to ensure justice and the contribution of women with disabilities to their own welfare. Implications: We suggest that these issues are practically applied in the field and tested and critiqued to enhance best practice for undertaking ethical research with this particular group. It is important that not only researchers and ethics committees, but also disabled women and disabled organizations, are involved in enhancing and formalizing ethical research guidelines for marginalized populations.

Keywords: capacity, emancipatory disability research paradigm equal participation, reasonable accommodation, research ethics, violence against women with disabilities

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1139 Using AI Based Software as an Assessment Aid for University Engineering Assignments

Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

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As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

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1138 Malaria Parasite Detection Using Deep Learning Methods

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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1137 A Bioinspired Anti-Fouling Coating for Implantable Medical Devices

Authors: Natalie Riley, Anita Quigley, Robert M. I. Kapsa, George W. Greene

Abstract:

As the fields of medicine and bionics grow rapidly in technological advancement, the future and success of it depends on the ability to effectively interface between the artificial and the biological worlds. The biggest obstacle when it comes to implantable, electronic medical devices, is maintaining a ‘clean’, low noise electrical connection that allows for efficient sharing of electrical information between the artificial and biological systems. Implant fouling occurs with the adhesion and accumulation of proteins and various cell types as a result of the immune response to protect itself from the foreign object, essentially forming an electrical insulation barrier that often leads to implant failure over time. Lubricin (LUB) functions as a major boundary lubricant in articular joints, a unique glycoprotein with impressive anti-adhesive properties that self-assembles to virtually any substrate to form a highly ordered, ‘telechelic’ polymer brush. LUB does not passivate electroactive surfaces which makes it ideal, along with its innate biocompatibility, as a coating for implantable bionic electrodes. It is the aim of the study to investigate LUB’s anti-fouling properties and its potential as a safe, bioinspired material for coating applications to enhance the performance and longevity of implantable medical devices as well as reducing the frequency of implant replacement surgeries. Native, bovine-derived LUB (N-LUB) and recombinant LUB (R-LUB) were applied to gold-coated mylar surfaces. Fibroblast, chondrocyte and neural cell types were cultured and grown on the coatings under both passive and electrically stimulated conditions to test the stability and anti-adhesive property of the LUB coating in the presence of an electric field. Lactate dehydrogenase (LDH) assays were conducted as a directly proportional cell population count on each surface along with immunofluorescent microscopy to visualize cells. One-way analysis of variance (ANOVA) with post-hoc Tukey’s test was used to test for statistical significance. Under both passive and electrically stimulated conditions, LUB significantly reduced cell attachment compared to bare gold. Comparing the two coating types, R-LUB reduced cell attachment significantly compared to its native counterpart. Immunofluorescent micrographs visually confirmed LUB’s antiadhesive property, R-LUB consistently demonstrating significantly less attached cells for both fibroblasts and chondrocytes. Preliminary results investigating neural cells have so far demonstrated that R-LUB has little effect on reducing neural cell attachment; the study is ongoing. Recombinant LUB coatings demonstrated impressive anti-adhesive properties, reducing cell attachment in fibroblasts and chondrocytes. These findings and the availability of recombinant LUB brings into question the results of previous experiments conducted using native-derived LUB, its potential not adequately represented nor realized due to unknown factors and impurities that warrant further study. R-LUB is stable and maintains its anti-fouling property under electrical stimulation, making it suitable for electroactive surfaces.

Keywords: anti-fouling, bioinspired, cell attachment, lubricin

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1136 River Network Delineation from Sentinel 1 Synthetic Aperture Radar Data

Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

Abstract:

In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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1135 Optimizing Operation of Photovoltaic System Using Neural Network and Fuzzy Logic

Authors: N. Drir, L. Barazane, M. Loudini

Abstract:

It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: maximum power point tracking, neural networks, photovoltaic, P&O

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1134 An Aesthetic Spatial Turn - AI and Aesthetics in the Physical, Psychological, and Symbolic Spaces of Brand Advertising

Authors: Yu Chen

Abstract:

In line with existing philosophical approaches, this research proposes a conceptual model with an innovative spatial vision and aesthetic principles for Artificial Intelligence (AI) application in brand advertising. The model first identifies the major constituencies in contemporary advertising on three spatial levels—physical, psychological, and symbolic. The model further incorporates the relationships among AI, aesthetics, branding, and advertising and their interactions with the major actors in all spaces. It illustrates that AI may follow the aesthetic principles-- beauty, elegance, and simplicity-- to reinforce brand identity and consistency in advertising, to collaborate with stakeholders, and to satisfy different advertising objectives on each level. It proposes that, with aesthetic guidelines, AI may assist consumers to emerge into the physical, psychological, and symbolic advertising spaces and helps transcend the tangible advertising messages to meaningful brand symbols. Conceptually, the research illustrates that even though consumers’ engagement with brand mostly begins with physical advertising and later moves to psychological-symbolic, AI-assisted advertising should start with the understanding of brand symbolic-psychological and consumer aesthetic preferences before the physical design to better resonate. Limits of AI and future AI functions in advertising are discussed.

Keywords: AI, spatial, aesthetic, brand advertising

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1133 Developing an Accurate AI Algorithm for Histopathologic Cancer Detection

Authors: Leah Ning

Abstract:

This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

Procedia PDF Downloads 91
1132 Optimizing Pavement Construction Procedures in the Southern Desert of Libya

Authors: Khlifa El Atrash, Gabriel Assaf

Abstract:

Libya uses a volumetric analysis in designing asphalt mixtures, which can also be upgraded in hot, arid weather. However, in order to be effective, it should include many important aspects which are materials, environment, and method of construction. However, the quality of some roads was below a satisfactory level. This paper examines the factors that contribute to low quality of road performance in Libya. To evaluate these factors, a questionnaire survey and a laboratory comparative study were performed for a few mixes under-represented of temperature and traffic load. In laboratory, rutting test conducted on two different asphalt mixture, these mixes included, an asphalt concrete mix using local aggregate and asphalt binder B(60/70) at the optimum Marshall asphalt content, another mixes designed using Superpave design procedure with the same materials and performance asphalt binder grade PG (70-10). In the survey, the questionnaire was distributed to 55 engineers and specialists in this field. The interview was conducted to a few others, and the factors that were leading to poor performance of asphalt roads were listed as; 1) Owner Experience and technical staff 2) Asphalt characteristics 3) Updating and development of Asphalt Mix Design methods 4) Lack of data collection by authorization Agency 5) Construction and compaction process 6) Mentoring and controlling mixing procedure. Considering and improving these factors will play an important role to improve the pavement performances, longer service life, and lower maintenance costs. This research summarized some recommendations for making asphalt mixtures used in hot, dry areas. Such asphalt mixtures should use asphalt binder which is less affected by pavement temperature change and traffic load. The properties of the mixture, such as durability, deformation, air voids, and performance, largely depend on the type of materials, environment, and mixing method. These properties, in turn, affect the pavement performance.

Keywords: volumetric analysis, pavement performances, hot climate, traffic load, pavement temperature, asphalt mixture, environment, design and construction

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1131 The Dependence of the Liquid Application on the Coverage of the Sprayed Objects in Terms of the Characteristics of the Sprayed Object during Spraying

Authors: Beata Cieniawska, Deta Łuczycka, Katarzyna Dereń

Abstract:

When assessing the quality of the spraying procedure, three indicators are used: uneven distribution of precipitation of liquid sprayed, degree of coverage of sprayed surfaces, and deposition of liquid spraying However, there is a lack of information on the relationship between the quality parameters of the procedure. Therefore, the research was carried out at the Institute of Agricultural Engineering of Wrocław University of Environmental and Life Sciences. The aim of the study was to determine the relationship between the degree of coverage of sprayed surfaces and the deposition of liquid in the aspect of the parametric characteristics of the protected plant using selected single and double stream nozzles. Experiments were conducted under laboratory conditions. The carrier of nozzles acted as an independent self-propelled sprayer used for spraying, whereas the parametric characteristics of plants were determined using artificial plants as the ratio of the vertical projection surface and the horizontal projection surface. The results and their analysis showed a strong and very strong correlation between the analyzed parameters in terms of the characteristics of the sprayed object.

Keywords: degree of coverage, deposition of liquid, nozzle, spraying

Procedia PDF Downloads 334
1130 A Cooperative Signaling Scheme for Global Navigation Satellite Systems

Authors: Keunhong Chae, Seokho Yoon

Abstract:

Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

Procedia PDF Downloads 280
1129 Verification and Validation of Simulated Process Models of KALBR-SIM Training Simulator

Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

Abstract:

Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) wherein the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation and Control design team. This paper discusses the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), steady state, transient state

Procedia PDF Downloads 266