Search results for: intelligent transportation systems
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10658

Search results for: intelligent transportation systems

8228 HPSEC Application as a New Indicator of Nitrification Occurrence in Water Distribution Systems

Authors: Sina Moradi, Sanly Liu, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Soha Habibi, Rose Amal

Abstract:

In recent years, chloramine has been widely used for both primary and secondary disinfection. However, a major concern with the use of chloramine as a secondary disinfectant is the decay of chloramine and nitrification occurrence. The management of chloramine decay and the prevention of nitrification are critical for water utilities managing chloraminated drinking water distribution systems. The detection and monitoring of nitrification episodes is usually carried out through measuring certain water quality parameters, which are commonly referred to as indicators of nitrification. The approach taken in this study was to collect water samples from different sites throughout a drinking water distribution systems, Tailem Bend – Keith (TBK) in South Australia, and analyse the samples by high performance size exclusion chromatography (HPSEC). We investigated potential association between the water qualities from HPSEC analysis with chloramine decay and/or nitrification occurrence. MATLAB 8.4 was used for data processing of HPSEC data and chloramine decay. An increase in the absorbance signal of HPSEC profiles at λ=230 nm between apparent molecular weights of 200 to 1000 Da was observed at sampling sites that experienced rapid chloramine decay and nitrification while its absorbance signal of HPSEC profiles at λ=254 nm decreased. An increase in absorbance at λ=230 nm and AMW < 500 Da was detected for Raukkan CT (R.C.T), a location that experienced nitrification and had significantly lower chloramine residual (<0.1 mg/L). This increase in absorbance was not detected in other sites that did not experience nitrification. Moreover, the UV absorbance at 254 nm of the HPSEC spectra was lower at R.C.T. than other sites. In this study, a chloramine residual index (C.R.I) was introduced as a new indicator of chloramine decay and nitrification occurrence, and is defined based on the ratio of area underneath the HPSEC spectra at two different wavelengths of 230 and 254 nm. The C.R.I index is able to indicate DS sites that experienced nitrification and rapid chloramine loss. This index could be useful for water treatment and distribution system managers to know if nitrification is occurring at a specific location in water distribution systems.

Keywords: nitrification, HPSEC, chloramine decay, chloramine residual index

Procedia PDF Downloads 284
8227 A System for Visual Management of Research Resources Focusing on Accumulation of Polish Processes

Authors: H. Anzai, H. Nakayama, H. Kaminaga, Y. Morimoto, Y. Miyadera, S. Nakamura

Abstract:

Various research resources such as papers and presentation slides are handled in the process of research activities. It is extremely important for smooth progress of the research to skillfully manage those research resources and utilize them for further investigations. However, number of the research resources increases more and more. Moreover, there are the differences in usage of each kind of research resource and their accumulation styles. So, it is actually difficult to satisfactorily manage and use the accumulated research resources. Therefore, a lack of tidiness of the resources causes the problems such as an oversight of the problem to be polish. Although there have existed research projects on support for management of research resources and for sharing of know-how, almost existing systems have not been effective enough since these systems have not sufficiently considered the polish process. This paper mainly describes a system that enables the strategic management of research resources together with polish process and their practical use.

Keywords: research resource, polish process, information sharing, knowledge management, information visualization

Procedia PDF Downloads 377
8226 Neural Reshaping: The Plasticity of Human Brain and Artificial Intelligence in the Learning Process

Authors: Seyed-Ali Sadegh-Zadeh, Mahboobe Bahrami, Sahar Ahmadi, Seyed-Yaser Mousavi, Hamed Atashbar, Amir M. Hajiyavand

Abstract:

This paper presents an investigation into the concept of neural reshaping, which is crucial for achieving strong artificial intelligence through the development of AI algorithms with very high plasticity. By examining the plasticity of both human and artificial neural networks, the study uncovers groundbreaking insights into how these systems adapt to new experiences and situations, ultimately highlighting the potential for creating advanced AI systems that closely mimic human intelligence. The uniqueness of this paper lies in its comprehensive analysis of the neural reshaping process in both human and artificial intelligence systems. This comparative approach enables a deeper understanding of the fundamental principles of neural plasticity, thus shedding light on the limitations and untapped potential of both human and AI learning capabilities. By emphasizing the importance of neural reshaping in the quest for strong AI, the study underscores the need for developing AI algorithms with exceptional adaptability and plasticity. The paper's findings have significant implications for the future of AI research and development. By identifying the core principles of neural reshaping, this research can guide the design of next-generation AI technologies that can enhance human and artificial intelligence alike. These advancements will be instrumental in creating a new era of AI systems with unparalleled capabilities, paving the way for improved decision-making, problem-solving, and overall cognitive performance. In conclusion, this paper makes a substantial contribution by investigating the concept of neural reshaping and its importance for achieving strong AI. Through its in-depth exploration of neural plasticity in both human and artificial neural networks, the study unveils vital insights that can inform the development of innovative AI technologies with high adaptability and potential for enhancing human and AI capabilities alike.

Keywords: neural plasticity, brain adaptation, artificial intelligence, learning, cognitive reshaping

Procedia PDF Downloads 37
8225 Energy Interaction among HVAC and Supermarket Environment

Authors: Denchai Woradechjumroen, Haorong Li, Yuebin Yu

Abstract:

Supermarkets are the most electricity-intensive type of commercial buildings. The unsuitable indoor environment of a supermarket provided by abnormal HVAC operations incurs waste energy consumption in refrigeration systems. This current study briefly describes significantly solid backgrounds and proposes easy-to-use analysis terminology for investigating the impact of HVAC operations on refrigeration power consumption using the field-test data obtained from building automation system (BAS). With solid backgrounds and prior knowledge, expected energy interactions between HVAC and refrigeration systems are proposed through Pearson’s correlation analysis (R value) by considering correlations between equipment power consumption and dominantly independent variables (driving force conditions). The R value can be conveniently utilized to evaluate how strong relations between equipment operations and driving force parameters are. The calculated R values obtained from field data are compared to expected ranges of R values computed by energy interaction methodology. The comparisons can separate the operational conditions of equipment into faulty and normal conditions. This analysis can simply investigate the condition of equipment operations or building sensors because equipment could be abnormal conditions due to routine operations or faulty commissioning processes in field tests. With systematically solid and easy-to-use backgrounds of interactions provided in the present article, the procedures can be utilized as a tool to evaluate the proper commissioning and routine operations of HVAC and refrigeration systems to detect simple faults (e.g. sensors and driving force environment of refrigeration systems and equipment set-point) and optimize power consumption in supermarket buildings. Moreover, the analysis will be used to further study FDD research for supermarkets in future.

Keywords: energy interaction, HVAC, R-value, supermarket buildings

Procedia PDF Downloads 413
8224 A Review of Deformation and Settlement Monitoring on the Field: Types and Applications

Authors: Hassan Ali, Abdulrahman Hamid

Abstract:

This paper discusses using of instruments to monitor deformation and settlement. Specifically, it concentrates on field instruments such as inclinometer and plate load test and their applications in the field. Inclinometer has been used effectively to monitor lateral earth movements and settlement in landslide areas, embankments and foundations. They are also used to monitor the deflection of retaining walls and piles under load. This paper is reviewing types of inclinometer systems, comparison between systems, applications, field accuracy and correction. The paper also will present a case study of using inclinometer to monitor the creep movements within the ancient landslide on The Washington Park Station. Furthermore, the application of deformation and settlement instruments in Saudi Arabia will be discussed in this manuscript.

Keywords: inclinometer, plate load test, backfills, sand, deformation and settlement

Procedia PDF Downloads 257
8223 Adaptive Cooperative Control of Nonholonomic Mobile Robot Based on Immersion and Invariance

Authors: Imil Hamda Imran, Sami El Ferik

Abstract:

This paper deals with adaptive cooperative control of non holonomic mobile robot moved together in a given formation. The controller is designed based on the Immersion and Invariance (I&I) approach. I&I is a framework for adaptive stabilization of nonlinear systems with uncertain parameters. We investigate the tracking control of non holonomic mobile robot with uncertainties in The I&I-based adaptive controller regulates the angular and linear velocity of non holonomic mobile robot. The results demonstrate that the ability of I&I-based adaptive cooperative control in tracking the position of non holonomic mobile robot.

Keywords: nonholonomic mobile robot, immersion and invariance, adaptive control, uncertain nonlinear systems

Procedia PDF Downloads 480
8222 Humans Trust Building in Robots with the Help of Explanations

Authors: Misbah Javaid, Vladimir Estivill-Castro, Rene Hexel

Abstract:

The field of robotics is advancing rapidly to the point where robots have become an integral part of the modern society. These robots collaborate and contribute productively with humans and compensate some shortcomings from human abilities and complement them with their skills. Effective teamwork of humans and robots demands to investigate the critical issue of trust. The field of human-computer interaction (HCI) has already examined trust humans place in technical systems mostly on issues like reliability and accuracy of performance. Early work in the area of expert systems suggested that automatic generation of explanations improved trust and acceptability of these systems. In this work, we augmented a robot with the user-invoked explanation generation proficiency. To measure explanations effect on human’s level of trust, we collected subjective survey measures and behavioral data in a human-robot team task into an interactive, adversarial and partial information environment. The results showed that with the explanation capability humans not only understand and recognize robot as an expert team partner. But, it was also observed that human's learning and human-robot team performance also significantly improved because of the meaningful interaction with the robot in the human-robot team. Moreover, by observing distinctive outcomes, we expect our research outcomes will also provide insights into further improvement of human-robot trustworthy relationships.

Keywords: explanation interface, adversaries, partial observability, trust building

Procedia PDF Downloads 192
8221 DBN-Based Face Recognition System Using Light Field

Authors: Bing Gu

Abstract:

Abstract—Most of Conventional facial recognition systems are based on image features, such as LBP, SIFT. Recently some DBN-based 2D facial recognition systems have been proposed. However, we find there are few DBN-based 3D facial recognition system and relative researches. 3D facial images include all the individual biometric information. We can use these information to build more accurate features, So we present our DBN-based face recognition system using Light Field. We can see Light Field as another presentation of 3D image, and Light Field Camera show us a way to receive a Light Field. We use the commercially available Light Field Camera to act as the collector of our face recognition system, and the system receive a state-of-art performance as convenient as conventional 2D face recognition system.

Keywords: DBN, face recognition, light field, Lytro

Procedia PDF Downloads 452
8220 Machine Learning for Classifying Risks of Death and Length of Stay of Patients in Intensive Unit Care Beds

Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

Abstract:

Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

Procedia PDF Downloads 86
8219 Problems Encountered during the Education Process in Hakkari

Authors: Mukadder Baran, Medine Baran Türkan, Gülbeyaz Baran Durmaz

Abstract:

The objective of this work is to collect and evaluate the thoughts about Hakkari's education system of the highschool pupils of the city of Hakkari. To this end, semi-directed questionnaire forms were used. The samples of this work are made up of 24 pupils studying at four different highschools. In order to analyze the data collected, the content analysis method was used. According to the results of this work, the following factors bear an influence on the conditions of education in Hakkari: political environment, feudal resources, family, teacher, geographic conditions, social environment, transportation, difficulties related to economic resources or the access to information. Proceeding from these results, we believe that the bettermen of the conditions of education in Hakkari will improve the pupils' level of achievement. In turn, the rise in educational levels will lay the ground for a more effective participation in democratic processes. In this manner, the rise in educational level will result in a progress in society and ensure the more active participation of individuals in the socio-economic process.

Keywords: economic resources, education, political environment, poverty

Procedia PDF Downloads 452
8218 Performance Management in Serbian Banks: Balanced Scorecard Approach

Authors: Nela Milosevic, Sladjana Barjaktarovic Rakocevic, Sladjana Benkovic, Nemanja Milanovic

Abstract:

Nowadays, performance measurement systems play a key role in evaluating the strategic performances of an organization. On the other hand, there has been a shift towards the Balanced Scorecard (BSC), which has been recognized as a valuable managerial approach. The main goal of this paper is to analyze the main performances of Serbian banks measured at the branches level, through the usage of the Balanced Scorecard framework. Although an extensive number of practitioners have an interest in the Balanced Scorecard approach, little empirical research has been conducted on the implementation of its concept in the service sector like banks, especially within developing countries. From the beginning of August till the end of September 2015, authors have been conducting in-depth interviews among a number of experts from the most successful banks in Serbia. The results show that the non-financial measures, especially, customer oriented indicators and product/ service oriented indicators, seem to be very important factors for improving not only the financial situation within the bank, but also overall business performances. Additionally, the findings prove that there is the cause-effect relationship between non-financial and financial dimensions of the Balanced Scorecard. Having in mind that the banks are still using outdated performance evaluation systems, such as annual, quarterly and monthly reports, we hope that this paper will contribute to the knowledge of how banks in Serbia may apply the Balanced Scorecard approach to evaluate their performance on the most efficient and effective way.

Keywords: balanced scorecard approach, bank management, performance measurement systems, strategic performances

Procedia PDF Downloads 325
8217 Efficiency of DMUs in Presence of New Inputs and Outputs in DEA

Authors: Esmat Noroozi, Elahe Sarfi, Farha Hosseinzadeh Lotfi

Abstract:

Examining the impacts of data modification is considered as sensitivity analysis. A lot of studies have considered the data modification of inputs and outputs in DEA. The issues which has not heretofore been considered in DEA sensitivity analysis is modification in the number of inputs and (or) outputs and determining the impacts of this modification in the status of efficiency of DMUs. This paper is going to present systems that show the impacts of adding one or multiple inputs or outputs on the status of efficiency of DMUs and furthermore a model is presented for recognizing the minimum number of inputs and (or) outputs from among specified inputs and outputs which can be added whereas an inefficient DMU will become efficient. Finally the presented systems and model have been utilized for a set of real data and the results have been reported.

Keywords: data envelopment analysis, efficiency, sensitivity analysis, input, out put

Procedia PDF Downloads 436
8216 Battery Replacement Strategy for Electric AGVs in an Automated Container Terminal

Authors: Jiheon Park, Taekwang Kim, Kwang Ryel Ryu

Abstract:

Electric automated guided vehicles (AGVs) are becoming popular in many automated container terminals nowadays because they are pollution-free and environmentally friendly vehicles for transporting the containers within the terminal. Since efficient operation of AGVs is critical for the productivity of the container terminal, the replacement of batteries of the AGVs must be conducted in a strategic way to minimize undesirable transportation interruptions. While a too frequent replacement may lead to a loss of terminal productivity by delaying container deliveries, missing the right timing of battery replacement can result in a dead AGV that causes a severer productivity loss due to the extra efforts required to finish post treatment. In this paper, we propose a strategy for battery replacement based on a scoring function of multiple criteria taking into account the current battery level, the distances to different battery stations, and the progress of the terminal job operations. The strategy is optimized using a genetic algorithm with the objectives of minimizing the total time spent for battery replacement as well as maximizing the terminal productivity.

Keywords: AGV operation, automated container terminal, battery replacement, electric AGV, strategy optimization

Procedia PDF Downloads 380
8215 Seismic Response and Sensitivity Analysis of Circular Shallow Tunnels

Authors: Siti Khadijah Che Osmi, Mohammed Ahmad Syed

Abstract:

Underground tunnels are one of the most popular public facilities for various applications such as transportation, water transfer, network utilities and etc. Experience from the past earthquake reveals that the underground tunnels also become vulnerable components and may damage at certain percentage depending on the level of ground shaking and induced phenomena. In this paper a numerical analysis is conducted in evaluating the sensitivity of two types of circular shallow tunnel lining models to wide ranging changes in the geotechnical design parameter. Critical analysis has been presented about the current methods of analysis, structural typology, ground motion characteristics, effect of soil conditions and associated uncertainties on the tunnel integrity. The response of the tunnel is evaluated through 2D non-linear finite element analysis, which critically assesses the impact of increasing levels of seismic loads. The finding from this study offer significant information on improving methods to assess the vulnerability of underground structures.

Keywords: geotechnical design parameter, seismic response, sensitivity analysis, shallow tunnel

Procedia PDF Downloads 431
8214 Sustainable Cities: Viability of a Hybrid Aeroponic/Nutrient Film Technique System for Cultivation of Tomatoes

Authors: D. Dannehl, Z. Taylor, J. Suhl, L. Miranda, R., Ulrichs, C., Salazar, E. Fitz-Rodriguez, I. Lopez-Cruz, A. Rojano-Aguilar, G. Navas-Gomez, U. Schmidt

Abstract:

Growing environmental and sustainability concerns have driven continual modernization of horticultural practices, especially for urban farming. Controlled environment and soilless production methods are increasing in popularity because of their efficient resource use and intensive cropping capabilities. However, some popular substrates used for hydroponic cultivation, particularly rock wool, represent a large environmental burden in regard to their manufacture and disposal. Substrate-less hydroponic systems are effective in producing short cropping cycle plants such as lettuce or herbs, but less information is available for the production of plants with larger root-systems and longer cropping times. Here, we investigated the viability of a hybrid aeroponic/nutrient film technique (AP/NFT) system for the cultivation of greenhouse tomatoes (Solanum lycopersicum ‘Panovy’). The plants grown in the AP/NFT system had a more compact phenotype, accumulated more Na+ and less P and S than the rock wool grown counterparts. Due to forced irrigation interruptions, we propose that the differences observed were cofounded by the differing severity of water-stress for plants with and without substrate. They may also be caused by a higher root zone temperature predominant in plants exposed to AP/NFT. However, leaf area, stem diameter, and number of trusses did not differ significantly. The same was found for leaf pigments and plant photosynthetic efficiency. Overall, the AP/NFT system appears to be viable for the production of greenhouse tomato, enabling the environment to be relieved by way of lessening rock wool usage.

Keywords: closed aeroponic systems, fruit quality, nutrient dynamics, substrate waste reduction, urban farming systems, water savings

Procedia PDF Downloads 259
8213 Sensor and Sensor System Design, Selection and Data Fusion Using Non-Deterministic Multi-Attribute Tradespace Exploration

Authors: Matthew Yeager, Christopher Willy, John Bischoff

Abstract:

The conceptualization and design phases of a system lifecycle consume a significant amount of the lifecycle budget in the form of direct tasking and capital, as well as the implicit costs associated with unforeseeable design errors that are only realized during downstream phases. Ad hoc or iterative approaches to generating system requirements oftentimes fail to consider the full array of feasible systems or product designs for a variety of reasons, including, but not limited to: initial conceptualization that oftentimes incorporates a priori or legacy features; the inability to capture, communicate and accommodate stakeholder preferences; inadequate technical designs and/or feasibility studies; and locally-, but not globally-, optimized subsystems and components. These design pitfalls can beget unanticipated developmental or system alterations with added costs, risks and support activities, heightening the risk for suboptimal system performance, premature obsolescence or forgone development. Supported by rapid advances in learning algorithms and hardware technology, sensors and sensor systems have become commonplace in both commercial and industrial products. The evolving array of hardware components (i.e. sensors, CPUs, modular / auxiliary access, etc…) as well as recognition, data fusion and communication protocols have all become increasingly complex and critical for design engineers during both concpetualization and implementation. This work seeks to develop and utilize a non-deterministic approach for sensor system design within the multi-attribute tradespace exploration (MATE) paradigm, a technique that incorporates decision theory into model-based techniques in order to explore complex design environments and discover better system designs. Developed to address the inherent design constraints in complex aerospace systems, MATE techniques enable project engineers to examine all viable system designs, assess attribute utility and system performance, and better align with stakeholder requirements. Whereas such previous work has been focused on aerospace systems and conducted in a deterministic fashion, this study addresses a wider array of system design elements by incorporating both traditional tradespace elements (e.g. hardware components) as well as popular multi-sensor data fusion models and techniques. Furthermore, statistical performance features to this model-based MATE approach will enable non-deterministic techniques for various commercial systems that range in application, complexity and system behavior, demonstrating a significant utility within the realm of formal systems decision-making.

Keywords: multi-attribute tradespace exploration, data fusion, sensors, systems engineering, system design

Procedia PDF Downloads 166
8212 Artificial Intelligence and Machine Vision-Based Defect Detection Methodology for Solid Rocket Motor Propellant Grains

Authors: Sandip Suman

Abstract:

Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

Procedia PDF Downloads 85
8211 Optimization of Maintenance of PV Module Arrays Based on Asset Management Strategies: Case of Study

Authors: L. Alejandro Cárdenas, Fernando Herrera, David Nova, Juan Ballesteros

Abstract:

This paper presents a methodology to optimize the maintenance of grid-connected photovoltaic systems, considering the cleaning and module replacement periods based on an asset management strategy. The methodology is based on the analysis of the energy production of the PV plant, the energy feed-in tariff, and the cost of cleaning and replacement of the PV modules, with the overall revenue received being the optimization variable. The methodology is evaluated as a case study of a 5.6 kWp solar PV plant located on the Bogotá campus of the Universidad Nacional de Colombia. The asset management strategy implemented consists of assessing the PV modules through visual inspection, energy performance analysis, pollution, and degradation. Within the visual inspection of the plant, the general condition of the modules and the structure is assessed, identifying dust deposition, visible fractures, and water accumulation on the bottom. The energy performance analysis is performed with the energy production reported by the monitoring systems and compared with the values estimated in the simulation. The pollution analysis is performed using the soiling rate due to dust accumulation, which can be modelled by a black box with an exponential function dependent on historical pollution values. The pollution rate is calculated with data collected from the energy generated during two years in a photovoltaic plant on the campus of the National University of Colombia. Additionally, the alternative of assessing the temperature degradation of the PV modules is evaluated by estimating the cell temperature with parameters such as ambient temperature and wind speed. The medium-term energy decrease of the PV modules is assessed with the asset management strategy by calculating the health index to determine the replacement period of the modules due to degradation. This study proposes a tool for decision making related to the maintenance of photovoltaic systems. The above, projecting the increase in the installation of solar photovoltaic systems in power systems associated with the commitments made in the Paris Agreement for the reduction of CO2 emissions. In the Colombian context, it is estimated that by 2030, 12% of the installed power capacity will be solar PV.

Keywords: asset management, PV module, optimization, maintenance

Procedia PDF Downloads 25
8210 Design of a Real Time Closed Loop Simulation Test Bed on a General Purpose Operating System: Practical Approaches

Authors: Pratibha Srivastava, Chithra V. J., Sudhakar S., Nitin K. D.

Abstract:

A closed-loop system comprises of a controller, a response system, and an actuating system. The controller, which is the system under test for us, excites the actuators based on feedback from the sensors in a periodic manner. The sensors should provide the feedback to the System Under Test (SUT) within a deterministic time post excitation of the actuators. Any delay or miss in the generation of response or acquisition of excitation pulses may lead to control loop controller computation errors, which can be catastrophic in certain cases. Such systems categorised as hard real-time systems that need special strategies. The real-time operating systems available in the market may be the best solutions for such kind of simulations, but they pose limitations like the availability of the X Windows system, graphical interfaces, other user tools. In this paper, we present strategies that can be used on a general purpose operating system (Bare Linux Kernel) to achieve a deterministic deadline and hence have the added advantages of a GPOS with real-time features. Techniques shall be discussed how to make the time-critical application run with the highest priority in an uninterrupted manner, reduced network latency for distributed architecture, real-time data acquisition, data storage, and retrieval, user interactions, etc.

Keywords: real time data acquisition, real time kernel preemption, scheduling, network latency

Procedia PDF Downloads 135
8209 Using Q-Learning to Auto-Tune PID Controller Gains for Online Quadcopter Altitude Stabilization

Authors: Y. Alrubyli

Abstract:

Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

Procedia PDF Downloads 159
8208 Prospect and Challenges of Public Bicycle Sharing System in Indian Cities

Authors: Anil Kumar

Abstract:

Public Bicycle System (PBS), generally known as Public Bicycle Share System or Bike-Share, is a service provided to the everyday commuters in which several cycles are available on the shared system. The concept of PBS is new to the people of India and requires more study in the fields of essential requirements, major infrastructural requirements, social acceptability, and various challenges. In various Indian cities, MRTS, BRTS, Monorail, and other modes of transport have been adopted for the main haul of transport. These modes take more time, space and are also expensive to implement. At the same time, the PBS system is more economical and takes less time to implement. The main benefit of the PBS system is that it is more environmentally friendly. PBS is being implemented in many Indian cities for public use, but various challenges are associated with this. The study aims to determine what are the basic infrastructural requirements for PBS in India, as well as to determine to what extent a Public Bike Sharing System can provide a quality and efficient service to passengers as a primary method of transportation.

Keywords: public bicycle sharing system, sustainable transport, infrastructure, smart city

Procedia PDF Downloads 181
8207 Comparison of Steel and Composite Analysis of a Multi-Storey Building

Authors: Çiğdem Avcı Karataş

Abstract:

Mitigation of structural damage caused by earthquake and reduction of fatality is one of the main concerns of engineers in seismic prone zones of the world. To achieve this aim many technologies have been developed in the last decades and applied in construction and retrofit of structures. On the one hand Turkey is well-known a country of high level of seismicity; on the other hand steel-composite structures appear competitive today in this country by comparison with other types of structures, for example only-steel or concrete structures. Composite construction is the dominant form of construction for the multi-storey building sector. The reason why composite construction is often so good can be expressed in one simple way - concrete is good in compression and steel is good in tension. By joining the two materials together structurally these strengths can be exploited to result in a highly efficient design. The reduced self-weight of composite elements has a knock-on effect by reducing the forces in those elements supporting them, including the foundations. The floor depth reductions that can be achieved using composite construction can also provide significant benefits in terms of the costs of services and the building envelope. The scope of this paper covers analysis, materials take-off, cost analysis and economic comparisons of a multi-storey building with composite and steel frames. The aim of this work is to show that designing load carrying systems as composite is more economical than designing as steel. Design of the nine stories building which is under consideration is done according to the regulation of the 2007, Turkish Earthquake Code and by using static and dynamic analysis methods. For the analyses of the steel and composite systems, plastic analysis methods have been used and whereas steel system analyses have been checked in compliance with EC3 and composite system analyses have been checked in compliance with EC4. At the end of the comparisons, it is revealed that composite load carrying systems analysis is more economical than the steel load carrying systems analysis considering the materials to be used in the load carrying system and the workmanship to be spent for this job.

Keywords: composite analysis, earthquake, steel, multi-storey building

Procedia PDF Downloads 554
8206 An Investigation on the Internal Quality Assurance System of Higher Education in Indonesia

Authors: Andi Mursidi

Abstract:

This study aims to investigate why the internal quality assurance system as the basis for the assessment of external quality assurance systems is not well developed at universities in Indonesia. To answer this problem, technical analysis used single instrumental case study with the respondents from ten universities. The findings of this study are the internal quality assurance system that is applied so far (1) only to gain accreditation; and (2) considered as a liability rather than as a necessity to meet the demands of quality standards. It needs strong commitment from internal stakeholders at the college/university to establish internal quality assurance systems that exceed the national standards of higher education. A high quality college/ university will have a good accreditation rank.

Keywords: internal stakeholders, internal quality assurance system, commitment, higher education

Procedia PDF Downloads 275
8205 Enhanced Retrieval-Augmented Generation (RAG) Method with Knowledge Graph and Graph Neural Network (GNN) for Automated QA Systems

Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

Abstract:

In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

Procedia PDF Downloads 13
8204 Comparing the Motion of Solar System with Water Droplet Motion to Predict the Future of Solar System

Authors: Areena Bhatti

Abstract:

The geometric arrangement of planet and moon is the result of a self-organizing system. In our solar system, the planets and moons are constantly orbiting around the sun. The aim of this theory is to compare the motion of a solar system with the motion of water droplet when poured into a water body. The basic methodology is to compare both motions to know how they are related to each other. The difference between both systems will be that one is extremely fast, and the other is extremely slow. The role of this theory is that by looking at the fast system we can conclude how slow the system will get to an end. Just like ripples are formed around water droplet that move away from the droplet and water droplet forming those ripples become small in size will tell us how solar system will behave in the same way. So it is concluded that large and small systems can work under the same process but with different motions of time, and motion of the solar system is the slowest form of water droplet motion.

Keywords: motion, water, sun, time

Procedia PDF Downloads 133
8203 An Approach to Analyze Testing of Nano On-Chip Networks

Authors: Farnaz Fotovvatikhah, Javad Akbari

Abstract:

Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

Procedia PDF Downloads 472
8202 The Food Industry in Nigeria: Development and Quality Assurance

Authors: Agi Sunday, Agih Ukuru Agih

Abstract:

In Nigeria, the food processing sector is dominated by small and medium enterprises, as well as multinational food companies. Quality standards are usually related to improving the safety of food products suitable for consumption in accordance to specifications by food regulatory bodies. These standards are essential elements for local and international businesses which contribute to economic progress through industrial development and trade. This review takes a critical look on the Nigerian food industry development in terms of quality standards that are necessary to be given consideration in the production of food and also ways of improving food production in Nigeria through the use of Total Quality Management (TQM) technique and the use of computerized systems to produce high quality and high value products while at the same time reducing production time and cost.

Keywords: food industry, quality assurance, Nigeria, TQM, computerized systems

Procedia PDF Downloads 440
8201 Learning to Recommend with Negative Ratings Based on Factorization Machine

Authors: Caihong Sun, Xizi Zhang

Abstract:

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

Procedia PDF Downloads 231
8200 A Review of Sustainable Energy-Saving Solutions in Active and Passive Solar Systems of Zero Energy Buildings Based on the Internet of Things

Authors: Hanieh Sadat Jannesari, Hoori Jannesar, Alireza Hajian HosseinAbadi

Abstract:

In general, buildings are responsible for a considerable share of consumed energy and carbon emissions worldwide and play a significant role in formulating sustainable development strategies. Therefore, a lot of effort is put into the design and construction of zero-energy buildings (ZEBs) to help eliminate the problems associated with the reduction of energy resources and environmental degradation. Two strategies are significant in designing ZEBs: minimizing the need for energy utilization in buildings (particularly for cooling and heating) through highly energy-efficient designs and using renewable energies and other technologies to meet the remaining energy needs. This paper reviews the works related to these two strategies concerning sustainable energy-saving solutions using renewable energy technologies and the Internet of Things in ZEBs. Drawing on the theories and recently implemented projects of energy engineers in ZEBs, we have reported the required technologies within the framework of this paper’s objectives. Overall, solutions based on renewable and sustainable technologies such as photovoltaic (PV) modules, thermal collectors, Phase Change Material (PCM) techniques, etc., are used in active and passive systems designed for various applications in such buildings as cooling, heating, lighting, cooking, etc. The results obtained from examining these projects show that it is possible to minimize the amount of energy required to be produced for and consumed by these buildings.

Keywords: active and passive renewable energy systems, internet of things, storage, zero energy buildings

Procedia PDF Downloads 7
8199 An Adaptive CFAR Algorithm Based on Automatic Censoring in Heterogeneous Environments

Authors: Naime Boudemagh

Abstract:

In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

Procedia PDF Downloads 586