Search results for: agent based model
38726 New Method to Increase Contrast of Electromicrograph of Rat Tissues Sections
Authors: Lise Paule Labéjof, Raíza Sales Pereira Bizerra, Galileu Barbosa Costa, Thaísa Barros dos Santos
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Since the beginning of the microscopy, improving the image quality has always been a concern of its users. Especially for transmission electron microscopy (TEM), the problem is even more important due to the complexity of the sample preparation technique and the many variables that can affect the conservation of structures, proper operation of the equipment used and then the quality of the images obtained. Animal tissues being transparent it is necessary to apply a contrast agent in order to identify the elements of their ultrastructural morphology. Several methods of contrastation of tissues for TEM imaging have already been developed. The most used are the “in block” contrastation and “in situ” contrastation. This report presents an alternative technique of application of contrast agent in vivo, i.e. before sampling. By this new method the electromicrographies of the tissue sections have better contrast compared to that in situ and present no artefact of precipitation of contrast agent. Another advantage is that a small amount of contrast is needed to get a good result given that most of them are expensive and extremely toxic.Keywords: image quality, microscopy research, staining technique, ultra thin section
Procedia PDF Downloads 43738725 Collision Avoidance Based on Model Predictive Control for Nonlinear Octocopter Model
Authors: Doğan Yıldız, Aydan Müşerref Erkmen
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The controller of the octocopter is mostly based on the PID controller. For complex maneuvers, PID controllers have limited performance capability like in collision avoidance. When an octocopter needs avoidance from an obstacle, it must instantly show an agile maneuver. Also, this kind of maneuver is affected severely by the nonlinear characteristic of octocopter. When these kinds of limitations are considered, the situation is highly challenging for the PID controller. In the proposed study, these challenges are tried to minimize by using the model predictive controller (MPC) for collision avoidance with a nonlinear octocopter model. The aim is to show that MPC-based collision avoidance has the capability to deal with fast varying conditions in case of obstacle detection and diminish the nonlinear effects of octocopter with varying disturbances.Keywords: model predictive control, nonlinear octocopter model, collision avoidance, obstacle detection
Procedia PDF Downloads 19438724 Comprehensive Risk Assessment Model in Agile Construction Environment
Authors: Jolanta Tamošaitienė
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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.Keywords: assessment, environment, agile, model, risk
Procedia PDF Downloads 25838723 ePA-Coach: Design of the Intelligent Virtual Learning Coach for Senior Learners in Support of Digital Literacy in the Context of Electronic Patient Record
Authors: Ilona Buchem, Carolin Gellner
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Over the last few years, the call for the support of senior learners in the development of their digital literacy has become prevalent, mainly due to the progression towards ageing societies paired with advances in digitalisation in all spheres of life, including e-health and electronic patient record (EPA). While major research efforts in supporting senior learners in developing digital literacy have been invested so far in e-learning focusing on knowledge acquisition and cognitive tasks, little research exists in learning models which target virtual mentoring and coaching with the help of pedagogical agents and address the social dimensions of learning. Research from studies with students in the context of formal education has already provided methods for designing intelligent virtual agents in support of personalised learning. However, this research has mostly focused on cognitive skills and has not yet been applied to the context of mentoring/coaching of senior learners, who have different characteristics and learn in different contexts. In this paper, we describe how insights from previous research can be used to develop an intelligent virtual learning coach (agent) for senior learners with a focus on building the social relationship between the agent and the learner and the key task of the agent to socialize learners to the larger context of digital literacy with a focus on electronic health records. Following current approaches to mentoring and coaching, the agent is designed not to enhance and monitor the cognitive performance of the learner but to serve as a trusted friend and advisor, whose role is to provide one-to-one guidance and support sharing of experiences among learners (peers). Based on literature review and synopsis of research on virtual agents and current coaching/mentoring models under consideration of the specific characteristics and requirements of senior learners, we describe the design framework which was applied to design an intelligent virtual learning coach as part of the e-learning system for digital literacy of senior learners in the ePA-Coach project founded by the German Ministry of Education and Research. This paper also presents the results from the evaluation study, which compared the use of the first prototype of the virtual learning coach designed according to the design framework with a voice narration in a multimedia learning environment with senior learners. The focus of the study was to validate the agent design in the context of the persona effect (Lester et al., 1997). Since the persona effect is related to the hypothesis that animated agents are perceived as more socially engaging, the study evaluated possible impacts of agent coaching in comparison with voice coaching on motivation, engagement, experience, and digital literacy.Keywords: virtual learning coach, virtual mentor, pedagogical agent, senior learners, digital literacy, electronic health records
Procedia PDF Downloads 12138722 Decoding the Structure of Multi-Agent System Communication: A Comparative Analysis of Protocols and Paradigms
Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov
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Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.Keywords: communication, multi-agent systems, protocols, consensus
Procedia PDF Downloads 7938721 Reflection on Using Bar Model Method in Learning and Teaching Primary Mathematics: A Hong Kong Case Study
Authors: Chui Ka Shing
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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.Keywords: bar model method, curriculum development, mathematics education, problem solving
Procedia PDF Downloads 22538720 The Thinking of Dynamic Formulation of Rock Aging Agent Driven by Data
Authors: Longlong Zhang, Xiaohua Zhu, Ping Zhao, Yu Wang
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The construction of mines, railways, highways, water conservancy projects, etc., have formed a large number of high steep slope wounds in China. Under the premise of slope stability and safety, the minimum cost, green and close to natural wound space repair, has become a new problem. Nowadays, in situ element testing and analysis, monitoring, field quantitative factor classification, and assignment evaluation will produce vast amounts of data. Data processing and analysis will inevitably differentiate the morphology, mineral composition, physicochemical properties between rock wounds, by which to dynamically match the appropriate techniques and materials for restoration. In the present research, based on the grid partition of the slope surface, tested the content of the combined oxide of rock mineral (SiO₂, CaO, MgO, Al₂O₃, Fe₃O₄, etc.), and classified and assigned values to the hardness and breakage of rock texture. The data of essential factors are interpolated and normalized in GIS, which formed the differential zoning map of slope space. According to the physical and chemical properties and spatial morphology of rocks in different zones, organic acids (plant waste fruit, fruit residue, etc.), natural mineral powder (zeolite, apatite, kaolin, etc.), water-retaining agent, and plant gum (melon powder) were mixed in different proportions to form rock aging agents. To spray the aging agent with different formulas on the slopes in different sections can affectively age the fresh rock wound, providing convenience for seed implantation, and reducing the transformation of heavy metals in the rocks. Through many practical engineering practices, a dynamic data platform of rock aging agent formula system is formed, which provides materials for the restoration of different slopes. It will also provide a guideline for the mixed-use of various natural materials to solve the complex, non-uniformity ecological restoration problem.Keywords: data-driven, dynamic state, high steep slope, rock aging agent, wounds
Procedia PDF Downloads 12038719 Design Channel Non Persistent CSMA MAC Protocol Model for Complex Wireless Systems Based on SoC
Authors: Ibrahim A. Aref, Tarek El-Mihoub, Khadiga Ben Musa
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This paper presents Carrier Sense Multiple Access (CSMA) communication model based on SoC design methodology. Such model can be used to support the modelling of the complex wireless communication systems, therefore use of such communication model is an important technique in the construction of high performance communication. SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design). We use a swarm system to validate CSMA designed model and to show how advantages of incorporating communication early in the design process. The wireless communication created through the modeling of CSMA protocol that can be used to achieve communication between all the agents and to coordinate access to the shared medium (channel).Keywords: systemC, modelling, simulation, CSMA
Procedia PDF Downloads 43138718 Model of Optimal Centroids Approach for Multivariate Data Classification
Authors: Pham Van Nha, Le Cam Binh
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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization
Procedia PDF Downloads 21338717 A Crop Growth Subroutine for Watershed Resources Management (WRM) Model
Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu
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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studiesKeywords: crop yield, roughness coefficient, PAR, WRM model
Procedia PDF Downloads 41238716 Deep Reinforcement Learning Approach for Optimal Control of Industrial Smart Grids
Authors: Niklas Panten, Eberhard Abele
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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control
Procedia PDF Downloads 20138715 On the Application and Comparison of Two Geostatistics Methods in the Parameterisation Step to Calibrate Groundwater Model: Grid-Based Pilot Point and Head-Zonation Based Pilot Point Methods
Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas
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Properly selecting the most suitable and effective geostatistics method in the parameterization step of groundwater modeling is critical to attain a satisfactory model. In this paper, two geostatistics methods, i.e., Grid-Based Pilot Point (GB-PP) and Head-Zonation Based Pilot Point (HZB-PP) methods, were applied in an eogenetic karst catchment and compared using as model performances and computation time the criteria. Overall, the results show that appropriate selection of method is substantial in the parameterization of physically-based groundwater models, as it influences both the accuracy and simulation times. It was found that GB-PP method performed comparably superior to HZB-PP method. However, reflecting its model performances, HZB-PP method is promising for further application in groundwater modeling.Keywords: groundwater model, geostatistics, pilot point, parameterization step
Procedia PDF Downloads 16838714 Modeling the Impact of Time Pressure on Activity-Travel Rescheduling Heuristics
Authors: Jingsi Li, Neil S. Ferguson
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Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management
Procedia PDF Downloads 11638713 Rapid Processing Techniques Applied to Sintered Nickel Battery Technologies for Utility Scale Applications
Authors: J. D. Marinaccio, I. Mabbett, C. Glover, D. Worsley
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Through use of novel modern/rapid processing techniques such as screen printing and Near-Infrared (NIR) radiative curing, process time for the sintering of sintered nickel plaques, applicable to alkaline nickel battery chemistries, has been drastically reduced from in excess of 200 minutes with conventional convection methods to below 2 minutes using NIR curing methods. Steps have also been taken to remove the need for forming gas as a reducing agent by implementing carbon as an in-situ reducing agent, within the ink formulation.Keywords: batteries, energy, iron, nickel, storage
Procedia PDF Downloads 44338712 Bounded Rational Heterogeneous Agents in Artificial Stock Markets: Literature Review and Research Direction
Authors: Talal Alsulaiman, Khaldoun Khashanah
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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks
Procedia PDF Downloads 35638711 A Crop Growth Subroutine for Watershed Resources Management (WRM) Model 1: Description
Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu
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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.Keywords: runoff, roughness coefficient, PAR, WRM model
Procedia PDF Downloads 37938710 3D Model of Rain-Wind Induced Vibration of Inclined Cable
Authors: Viet-Hung Truong, Seung-Eock Kim
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Rain–wind induced vibration of inclined cable is a special aerodynamic phenomenon because it is easily influenced by many factors, especially the distribution of rivulet and wind velocity. This paper proposes a new 3D model of inclined cable, based on single degree-of-freedom model. Aerodynamic forces are firstly established and verified with the existing results from a 2D model. The 3D model of inclined cable is developed. The 3D model is then applied to assess the effects of wind velocity distribution and the continuity of rivulets on the cable. Finally, an inclined cable model with small sag is investigated.Keywords: 3D model, rain - wind induced vibration, rivulet, analytical model
Procedia PDF Downloads 49238709 Presenting the Mathematical Model to Determine Retention in the Watersheds
Authors: S. Shamohammadi, L. Razavi
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This paper based on the principle concepts of SCS-CN model, a new mathematical model for computation of retention potential (S) presented. In the mathematical model, not only precipitation-runoff concepts in SCS-CN model are precisely represented in a mathematical form, but also new concepts, called “maximum retention” and “total retention” is introduced, and concepts of potential retention capacity, maximum retention, and total retention have been separated from each other. In the proposed model, actual retention (F), maximum actual retention (Fmax), total retention (S), maximum retention (Smax), and potential retention (Sp), for the first time clearly defined, so that Sp is not variable, but a function of morphological characteristics of the watershed. Indeed, based on the mathematical relation of the conceptual curve of SCS-CN model, the proposed model provides a new method for the computation of actual retention in watershed and it simply determined runoff based on. In the corresponding relations, in addition to Precipitation (P), Initial retention (Ia), cumulative values of actual retention capacity (F), total retention (S), runoff (Q), antecedent moisture (M), potential retention (Sp), total retention (S), we introduced Fmax and Fmin referring to maximum and minimum actual retention, respectively. As well as, ksh is a coefficient which depends on morphological characteristics of the watershed. Advantages of the modified version versus the original model include a better precision, higher performance, easier calibration and speed computing.Keywords: model, mathematical, retention, watershed, SCS
Procedia PDF Downloads 46238708 PLO-AIM: Potential-Based Lane Organization in Autonomous Intersection Management
Authors: Berk Ecer, Ebru Akcapinar Sezer
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Traditional management models of intersections, such as no-light intersections or signalized intersection, are not the most effective way of passing the intersections if the vehicles are intelligent. To this end, Dresner and Stone proposed a new intersection control model called Autonomous Intersection Management (AIM). In the AIM simulation, they were examining the problem from a multi-agent perspective, demonstrating that intelligent intersection control can be made more efficient than existing control mechanisms. In this study, autonomous intersection management has been investigated. We extended their works and added a potential-based lane organization layer. In order to distribute vehicles evenly to each lane, this layer triggers vehicles to analyze near lanes, and they change their lane if other lanes have an advantage. We can observe this behavior in real life, such as drivers, change their lane by considering their intuitions. Basic intuition on selecting the correct lane for traffic is selecting a less crowded lane in order to reduce delay. We model that behavior without any change in the AIM workflow. Experiment results show us that intersection performance is directly connected with the vehicle distribution in lanes of roads of intersections. We see the advantage of handling lane management with a potential approach in performance metrics such as average delay of intersection and average travel time. Therefore, lane management and intersection management are problems that need to be handled together. This study shows us that the lane through which vehicles enter the intersection is an effective parameter for intersection management. Our study draws attention to this parameter and suggested a solution for it. We observed that the regulation of AIM inputs, which are vehicles in lanes, was as effective as contributing to aim intersection management. PLO-AIM model outperforms AIM in evaluation metrics such as average delay of intersection and average travel time for reasonable traffic rates, which is in between 600 vehicle/hour per lane to 1300 vehicle/hour per lane. The proposed model reduced the average travel time reduced in between %0.2 - %17.3 and reduced the average delay of intersection in between %1.6 - %17.1 for 4-lane and 6-lane scenarios.Keywords: AIM project, autonomous intersection management, lane organization, potential-based approach
Procedia PDF Downloads 14238707 An Interactive Institutional Framework for Evolution of Enterprise Technological Innovation Capabilities System: A Complex Adaptive Systems Approach
Authors: Sohail Ahmed, Ke Xing
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This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). This research proposed an analytical framework for ETICS, its concepts, and theory by integrating CAS methodology into the management of the technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution, and realization of the technological innovation capabilities in complex dynamic environments. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS, and summarizes the sources of technological innovation, the elements of each subject, and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions, and government agencies with the leading enterprises in industrial settings. The study was exploratory and based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of the enterprise's technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on the enterprise’s research and development personnel, investments in technological processes, and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.Keywords: complex adaptive system, echo model, enterprise technological innovation capability system, research institutions, multi-agents
Procedia PDF Downloads 14138706 Synthesis and Characterization of Renewable Resource Based Green Epoxy Coating
Authors: Sukanya Pradhan, Smita Mohanty, S. K Nayak
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Plant oils are a great renewable source for being a reliable starting material to access new products with a wide spectrum of structural and functional variations. Even though petroleum products might also render the same, but it would also impose a high risk factor of environmental and health hazard. Since epoxidized vegetable oils are easily available, eco-compatible, non-toxic and renewable, hence these have drawn much of the attentions in the polymer industrial sector especially for the development of eco-friendly coating materials. In this study a waterborne epoxy coating was prepared from epoxidized soyabean oil by using triethanolamine. Because of its hydrophobic nature, it was a tough and tedius task to make it hydrophilic. The hydrophobic biobased epoxy was modified into waterborne epoxy by the help of a plant based anhydride as curing agent. Physico-mechanical, chemical resistance tests and thermal analysis of the green coating material were carried out which showed good physic-mechanical, chemical resistance properties as well as environment friendly. The complete characterization of the final material was done in terms of scratch hardness, gloss test, impact resistance, adhesion and bend test.Keywords: epoxidized soybean oil, waterborne, curing agent, green coating
Procedia PDF Downloads 54538705 Prediction on Housing Price Based on Deep Learning
Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang
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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.Keywords: deep learning, convolutional neural network, LSTM, housing prediction
Procedia PDF Downloads 30938704 A Multi-Cluster Enterprise Framework for Evolution of Knowledge System among Enterprises, Governments and Research Institutions
Authors: Sohail Ahmed, Ke Xing
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This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). Starting from CAS theory, this study proposed an analytical framework for ETICS, its concepts and theory by integrating CAS methodology into the management of technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution and realization of the technological innovation capabilities in complex dynamic environment. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS and summarizes the sources of technological innovation, the elements of each subject and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions and government agencies with the leading enterprises in industrial settings. The study was exploratory based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of enterprise technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on enterprise’s research and development personal, investments in technological processes and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.Keywords: complex adaptive system, echo model, enterprise knowledge system, research institutions, multi-agents.
Procedia PDF Downloads 7338703 Model Based Simulation Approach to a 14-Dof Car Model Using Matlab/Simulink
Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu
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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation
Procedia PDF Downloads 23738702 Agents and Causers in the Experiencer-Verb Lexicon
Authors: Margaret Ryan, Linda Cupples, Lyndsey Nickels, Paul Sowman
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The current investigation explored the thematic roles of the nouns specified in the lexical entries of experiencer verbs. While prior experimental research assumes experiencer and theme roles for both subject-experiencer (SE) and object-experiencer (OE) verbs, syntactic theorists have posited additional agent and causer roles. Experiment 1 provided evidence for an agent as participants assigned a high degree of intentionality to the logical subject of a subset of SE and OE actives and passives. Experiment 2 provided evidence for a causer as participants assigned high levels of causality to the logical subjects of experiencer sentences generally. However, the presence of an agent, but not a causer, coincided with processing ease. Causality may be an aspect rather than a thematic role. The varying thematic roles amongst experiencer-verb sentences have important implications for stimulus selection because we cannot presume processing is similar across differing sentence subtypes.Keywords: sentence comprehension, lexicon, canonicity, processing, thematic roles, syntax
Procedia PDF Downloads 12638701 Deep Reinforcement Learning with Leonard-Ornstein Processes Based Recommender System
Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi
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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process
Procedia PDF Downloads 15038700 ACBM: Attention-Based CNN and Bi-LSTM Model for Continuous Identity Authentication
Authors: Rui Mao, Heming Ji, Xiaoyu Wang
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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM
Procedia PDF Downloads 16138699 Efficient Frequent Itemset Mining Methods over Real-Time Spatial Big Data
Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz
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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query
Procedia PDF Downloads 16638698 Reconfigurable Consensus Achievement of Multi Agent Systems Subject to Actuator Faults in a Leaderless Architecture
Authors: F. Amirarfaei, K. Khorasani
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In this paper, reconfigurable consensus achievement of a team of agents with marginally stable linear dynamics and single input channel has been considered. The control algorithm is based on a first order linear protocol. After occurrence of a LOE fault in one of the actuators, using the imperfect information of the effectiveness of the actuators from fault detection and identification module, the control gain is redesigned in a way to still reach consensus. The idea is based on the modeling of change in effectiveness as change of Laplacian matrix. Then as special cases of this class of systems, a team of single integrators as well as double integrators are considered and their behavior subject to a LOE fault is considered. The well-known relative measurements consensus protocol is applied to a leaderless team of single integrator as well as double integrator systems, and Gersgorin disk theorem is employed to determine whether fault occurrence has an effect on system stability and team consensus achievement or not. The analyses show that loss of effectiveness fault in actuator(s) of integrator systems affects neither system stability nor consensus achievement.Keywords: multi-agent system, actuator fault, stability analysis, consensus achievement
Procedia PDF Downloads 34038697 A New Verification Based Congestion Control Scheme in Mobile Networks
Authors: P. K. Guha Thakurta, Shouvik Roy, Bhawana Raj
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A congestion control scheme in mobile networks is proposed in this paper through a verification based model. The model proposed in this work is represented through performance metric like buffer Occupancy, latency and packet loss rate. Based on pre-defined values, each of the metric is introduced in terms of three different states. A Markov chain based model for the proposed work is introduced to monitor the occurrence of the corresponding state transitions. Thus, the estimation of the network status is obtained in terms of performance metric. In addition, the improved performance of our proposed model over existing works is shown with experimental results.Keywords: congestion, mobile networks, buffer, delay, call drop, markov chain
Procedia PDF Downloads 446