Search results for: autonomous agent
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2027

Search results for: autonomous agent

1787 A Linear Programming Approach to Assist Roster Construction Under a Salary Cap

Authors: Alex Contarino

Abstract:

Professional sports leagues often have a “free agency” period, during which teams may sign players with expiring contracts.To promote parity, many leagues operate under a salary cap that limits the amount teams can spend on player’s salaries in a given year. Similarly, in fantasy sports leagues, salary cap drafts are a popular method for selecting players. In order to sign a free agent in either setting, teams must bid against one another to buy the player’s services while ensuring the sum of their player’s salaries is below the salary cap. This paper models the bidding process for a free agent as a constrained optimization problem that can be solved using linear programming. The objective is to determine the largest bid that a team should offer the player subject to the constraint that the value of signing the player must exceed the value of using the salary cap elsewhere. Iteratively solving this optimization problem for each available free agent provides teams with an effective framework for maximizing the talent on their rosters. The utility of this approach is demonstrated for team sport roster construction and fantasy sport drafts, using recent data sets from both settings.

Keywords: linear programming, optimization, roster management, salary cap

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1786 Linear Quadratic Gaussian/Loop Transfer Recover Control Flight Control on a Nonlinear Model

Authors: T. Sanches, K. Bousson

Abstract:

As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

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1785 The Effect of Metformin in Combination with Dexamethasone on the CXCR4 Level in Multiple Myeloma Cell Line

Authors: Seyede Sanaz Seyedebrahimi, Shima Rahimi, Shohreh Fakhari, Ali Jalili

Abstract:

Background: CXCR4, as a chemokine receptor, plays well-known roles in various types of cancers. Several studies have been conducted to overcome CXCR4 axis acts in multiple myeloma (MM) pathogenesis and progression. Dexamethasone, a standard treatment for multiple myeloma, has been shown to increase CXCR4 levels in multiple myeloma cell lines. Herein, we focused on the effects of metformin and dexamethasone on CXCR4 at the cellular level and the migration rate of cell lines after exposure to a combination compared to single-agent models. Materials and Method: Multiple myeloma cell lines (U266 and RPMI8226) were cultured with different metformin and dexamethasone concentrations in single-agent and combination models. The simultaneous combination doses were calculated by CompuSyn software. Cell surface and mRNA expression of CXCR4 were determined using flow cytometry and the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay, respectively. The Transwell cell migration assay evaluated the migration ability. Results: In concurred with previous studies, our results showed a dexamethasone up-regulation effect on CXCR4 in a dose-dependent manner. Although, the metformin single-agent model could reduce CXCR4 expression of U266 and RPMI8226 in cell surface and mRNA expression level. Moreover, the administration of metformin and dexamethasone simultaneously exerted a higher suppression effect on CXCR4 expression than the metformin single-agent model. The migration rate through the combination model's matrigel membrane was remarkably lower than the metformin and dexamethasone single-agent model. Discussion: According to our findings, the combination of metformin and dexamethasone effectively inhibited dexamethasone-induced CXCR4 expression in multiple myeloma cell lines. As a result, metformin may be counted as an alternative medicine combined with other chemotherapies to combat multiple myeloma. However, more research is required.

Keywords: CXCR4, dexamethasone, metformin, migration, multiple myeloma

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1784 A Bio-Inspired Approach for Self-Managing Wireless Sensor and Actor Networks

Authors: Lyamine Guezouli, Kamel Barka, Zineb Seghir

Abstract:

Wireless sensor and actor networks (WSANs) present a research challenge for different practice areas. Researchers are trying to optimize the use of such networks through their research work. This optimization is done on certain criteria, such as improving energy efficiency, exploiting node heterogeneity, self-adaptability and self-configuration. In this article, we present our proposal for BIFSA (Biologically-Inspired Framework for Wireless Sensor and Actor networks). Indeed, BIFSA is a middleware that addresses the key issues of wireless sensor and actor networks. BIFSA consists of two types of agents: sensor agents (SA) that operate at the sensor level to collect and transport data to actors and actor agents (AA) that operate at the actor level to transport data to base stations. Once the sensor agent arrives at the actor, it becomes an actor agent, which can exploit the resources of the actors and vice versa. BIFSA allows agents to evolve their genetic structures and adapt to the current network conditions. The simulation results show that BIFSA allows the agents to make better use of all the resources available in each type of node, which improves the performance of the network.

Keywords: wireless sensor and actor networks, self-management, genetic algorithm, agent.

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1783 Motivation for Therapy in Clinical Social Work in Kuwait

Authors: Hend Almaseb

Abstract:

​The motivational model proposed by Self-Determination Theory provided an explanation for clients’ motivation for therapy. Among a sample of 78 inpatient residents in the Addiction Treatment Center, this study examined the relationship between three types of motivation (Autonomous, Controlled, and Amotivation) and each of the following variables: Age, Marital Status, Educational Level of Participant, and Number of Years of Addiction. In addition, the study investigated whether or not the participants are motivated to receive therapy. The results showed 1) a significant relationship between Controlled Motivation and the following variables: Age, Marital Status, and Number of Years of Addiction; 2) a significant relationship between Autonomous Motivation and Number of Years of Addiction; and a significant relationship between Educational Level and Amotivation. The results also illustrated that the participants of this study were not motivated to seek therapy.

Keywords: addiction, clinical social work, motivation, self-determination

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1782 Reinforcement Learning for Self Driving Racing Car Games

Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh

Abstract:

This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.

Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming

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1781 Simulation of the Evacuation of Ships Carrying Dangerous Goods from Tsunami

Authors: Yoshinori Matsuura, Saori Iwanaga

Abstract:

The Great East Japan Earthquake occurred at 14:46 on Friday, March 11, 2011. It was the most powerful known earthquake to have hit Japan. The earthquake triggered extremely destructive tsunami waves of up to 40.5 meters in height. We focus on the ship’s evacuation from tsunami. Then we analyze about ships evacuation from tsunami using multi-agent simulation and we want to prepare for a coming earthquake. We developed a simulation model of ships that set sail from the port in order to evacuate from the tsunami considering the ship carrying dangerous goods.

Keywords: Ship’s evacuation, multi-agent simulation, tsunami

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1780 Flexible Integration of Airbag Weakening Lines in Interior Components: Airbag Weakening with Jenoptik Laser Technology

Authors: Markus Remm, Sebastian Dienert

Abstract:

Vehicle interiors are not only changing in terms of design and functionality but also due to new driving situations in which, for example, autonomous operating modes are possible. Flexible seating positions are changing the requirements for passive safety system behavior and location in the interior of a vehicle. With fully autonomous driving, the driver can, for example, leave the position behind the steering wheel and take a seated position facing backward. Since autonomous and non-autonomous vehicles will share the same road network for the foreseeable future, accidents cannot be avoided, which makes the use of passive safety systems indispensable. With JENOPTIK-VOTAN® A technology, the trend towards flexible predetermined airbag weakening lines is enabled. With the help of laser beams, the predetermined weakening lines are introduced from the backside of the components so that they are absolutely invisible. This machining process is sensor-controlled and guarantees that a small residual wall thickness remains for the best quality and reliability for airbag weakening lines. Due to the wide processing range of the laser, the processing of almost all materials is possible. A CO₂ laser is used for many plastics, natural fiber materials, foams, foils and material composites. A femtosecond laser is used for natural materials and textiles that are very heat-sensitive. This laser type has extremely short laser pulses with very high energy densities. Supported by a high-precision and fast movement of the laser beam by a laser scanner system, the so-called cold ablation is enabled to predetermine weakening lines layer by layer until the desired residual wall thickness remains. In that way, for example, genuine leather can be processed in a material-friendly and process-reliable manner without design implications to the components A-Side. Passive safety in the vehicle is increased through the interaction of modern airbag technology and high-precision laser airbag weakening. The JENOPTIK-VOTAN® A product family has been representing this for more than 25 years and is pointing the way to the future with new and innovative technologies.

Keywords: design freedom, interior material processing, laser technology, passive safety

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1779 Histone Deacetylases Inhibitor - Valproic Acid Sensitizes Human Melanoma Cells for alkylating agent and PARP inhibitor

Authors: Małgorzata Drzewiecka, Tomasz Śliwiński, Maciej Radek

Abstract:

The inhibition of histone deacetyles (HDACs) holds promise as a potential anti-cancer therapy because histone and non-histone protein acetylation is frequently disrupted in cancer, leading to cancer initiation and progression. Additionally, histone deacetylase inhibitors (HDACi) such as class I HDAC inhibitor - valproic acid (VPA) have been shown to enhance the effectiveness of DNA-damaging factors, such as cisplatin or radiation. In this study, we found that, using of VPA in combination with talazoparib (BMN-637 – PARP1 inhibitor – PARPi) and/or Dacarabazine (DTIC - alkylating agent) resulted in increased DNA double strand break (DSB) and reduced survival (while not affecting primary melanocytes )and proliferation of melanoma cells. Furthermore, pharmacologic inhibition of class I HDACs sensitizes melanoma cells to apoptosis following exposure to DTIC and BMN-637. In addition, inhibition of HDAC caused sensitization of melanoma cells to dacarbazine and BMN-637 in melanoma xenografts in vivo. At the mRNA and protein level histone deacetylase inhibitor downregulated RAD51 and FANCD2. This study provides that combining HDACi, alkylating agent and PARPi could potentially enhance the treatment of melanoma, which is known for being one of the most aggressive malignant tumors. The findings presented here point to a scenario in which HDAC via enhancing the HR-dependent repair of DSBs created during the processing of DNA lesions, are essential nodes in the resistance of malignant melanoma cells to methylating agent-based therapies.

Keywords: melanoma, hdac, parp inhibitor, valproic acid

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1778 Integrating Distributed Architectures in Highly Modular Reinforcement Learning Libraries

Authors: Albert Bou, Sebastian Dittert, Gianni de Fabritiis

Abstract:

Advancing reinforcement learning (RL) requires tools that are flexible enough to easily prototype new methods while avoiding impractically slow experimental turnaround times. To match the first requirement, the most popular RL libraries advocate for highly modular agent composability, which facilitates experimentation and development. To solve challenging environments within reasonable time frames, scaling RL to large sampling and computing resources has proved a successful strategy. However, this capability has been so far difficult to combine with modularity. In this work, we explore design choices to allow agent composability both at a local and distributed level of execution. We propose a versatile approach that allows the definition of RL agents at different scales through independent, reusable components. We demonstrate experimentally that our design choices allow us to reproduce classical benchmarks, explore multiple distributed architectures, and solve novel and complex environments while giving full control to the user in the agent definition and training scheme definition. We believe this work can provide useful insights to the next generation of RL libraries.

Keywords: deep reinforcement learning, Python, PyTorch, distributed training, modularity, library

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1777 Autonomous Flight Control for Multirotor by Alternative Input Output State Linearization with Nested Saturations

Authors: Yong Eun Yoon, Eric N. Johnson, Liling Ren

Abstract:

Multirotor is one of the most popular types of small unmanned aircraft systems and has already been used in many areas including transport, military, surveillance, and leisure. Together with its popularity, the needs for proper flight control is growing because in most applications it is required to conduct its missions autonomously, which is in many aspects based on autonomous flight control. There have been many studies about the flight control for multirotor, but there is still room for enhancements in terms of performance and efficiency. This paper presents an autonomous flight control method for multirotor based on alternative input output linearization coupled with nested saturations. With alternative choice of the output of the multirotor flight control system, we can reduce computational cost regarding Lie algebra, and the linearized system can be stabilized with the introduction of nested saturations with real poles of our own design. Stabilization of internal dynamics is also based on the nested saturations and accompanies the determination of part of desired states. In particular, outer control loops involving state variables which originally are not included in the output of the flight control system is naturally rendered through this internal dynamics stabilization. We can also observe that desired tilting angles are determined by error dynamics from outer loops. Simulation results show that in any tracking situations multirotor stabilizes itself with small time constants, preceded by tuning process for control parameters with relatively low degree of complexity. Future study includes control of piecewise linear behavior of multirotor with actuator saturations, and the optimal determination of desired states while tracking multiple waypoints.

Keywords: automatic flight control, input output linearization, multirotor, nested saturations

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1776 Complex Technology of Virtual Reconstruction: The Case of Kazan Imperial University of XIX-Early XX Centuries

Authors: L. K. Karimova, K. I. Shariukova, A. A. Kirpichnikova, E. A. Razuvalova

Abstract:

This article deals with technology of virtual reconstruction of Kazan Imperial University of XIX - early XX centuries. The paper describes technologies of 3D-visualization of high-resolution models of objects of university space, creation of multi-agent system and connected with these objects organized database of historical sources, variants of use of technologies of immersion into the virtual environment.

Keywords: 3D-reconstruction, multi-agent system, database, university space, virtual reconstruction, virtual heritage

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1775 Effect of Clinical Parameters on Strength of Reattached Tooth Fragment in Anterior Teeth: Systematic Review and Meta-Analysis

Authors: Neeraj Malhotra, Ramya Shenoy

Abstract:

Objective: To assess the effect of clinical parameters (bonding agent, preparation design & storage media) on the strength of reattached anterior tooth fragment. Methodology: This is a systematic review and meta-analysis for articles referred from MEDLINE, PUBMED, and GOOGLE SCHOLAR. The articles on tooth reattachment and clinical factors affecting fracture strength/bond strength/fracture resistance of the reattached tooth fragment in anterior teeth and published in English from 1999 to 2016 were included for final review. Results: Out of 120 shortlisted articles, 28 articles were included for the systematic review and meta-analysis based on 3 clinical parameters i.e. bonding agent, tooth preparation design & storage media. Forest plot & funnel plots were generated based on individual clinical parameter and their effect on strength of reattached anterior tooth fragment. Results based on analysis suggest combination of both conclusive evidence favoring the experimental group as well as in-conclusive evidence for individual parameter. Conclusion: There is limited evidence as there are fewer articles supporting each parameter in human teeth. Bonding agent had showed better outcome in selected studies.

Keywords: bonding agent, bond strength, fracture strength, preparation design, reattachment, storage media

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1774 Towards a Computational Model of Consciousness: Global Abstraction Workspace

Authors: Halim Djerroud, Arab Ali Cherif

Abstract:

We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning, and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we propose a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment.

Keywords: artificial consciousness, cognitive architecture, global abstraction workspace, multi-agent system

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1773 Existential and Possessive Constructions in Modern Standard Arabic Two Strategies Reflecting the Ontological (Non-)Autonomy of Located or Possessed Entities

Authors: Fayssal Tayalati

Abstract:

Although languages use very divergent constructional strategies, all existential constructions appear to invariably involve an implicit or explicit locative constituent. This locative constituent either surface as a true locative phrase or are realized as a possessor noun phrase. However, while much research focuses on the supposed underlying syntactic relation of locative and possessive existential constructions, not much is known about possible semantic factors that could govern the choice between these constructions. The main question that we address in this talk concerns the choice between the two related constructions in Modern Standard Arabic (MAS). Although both are used to express the existence of something somewhere, we can distinguish three contexts: First, for some types of entities, only the EL construction is possible (e.g. (1a) ṯammata raǧulun fī l-ḥadīqati vs. (1b) *(kāna) ladā l-ḥadīqati raǧulun). Second, for other types of entities, only the possessive construction is possible (e.g. (2a) ladā ṭ-ṭawilati aklun dāʾiriyyun vs. (2b) *ṯammata šaklun dāʾiriyyun ladā/fī ṭ-ṭawilati). Finally, for still other entities, both constructions can be found (e.g. (3a) ṯammata ḥubbun lā yūṣafu ladā ǧārī li-zawǧati-hi and (3b) ladā ǧārī ḥubbun lā yūṣafu li-zawǧati-hi). The data covering a range of ontologically different entities (concrete objects, events, body parts, dimensions, essential qualities, feelings, etc.) shows that the choice between the existential locative and the possessive constructions is closely linked to the conceptual autonomy of the existential theme with respect to its location or to the whole that it is a part of. The construction with ṯammata is the only possible one to express the existence of a fully autonomous (i.e. nondependent) entity (concrete objects (e.g.1) and abstract objects such as events, especially the ones that Grimshaw called ‘simple events’). The possessive construction with (kāna) ladā is the only one used to express the existence of fully non-autonomous (i.e. fully dependent on a whole) entities (body parts, dimensions (e.g. 2), essential qualities). The two constructions alternate when the existential theme is conceptually dependent but separable of the whole, either because it has an autonomous (independent) existence of the given whole (spare parts of an object), or because it receives a relative autonomy in the speech through a modifier (accidental qualities, feelings (e.g. 3a, 3b), psychological states, among some other kinds of themes). In this case, the modifier expresses an approximate boundary on a scale, and provides relative autonomy to the entity. Finally, we will show that kinship terms (e.g. son), which at first sight may seem to constitute counterexamples to our hypothesis, are nonetheless supported by it. The ontological (non-)autonomy of located or possessed entities is also reflected by morpho-syntactic properties, among them the use and the choice of determiners, pluralisation and the behavior of entities in the context of associative anaphora.

Keywords: existence, possession, autonomous entities, non-autonomous entities

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1772 Design and Implementation of Neural Network Based Controller for Self-Driven Vehicle

Authors: Hassam Muazzam

Abstract:

This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

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1771 Marine Environmental Monitoring Using an Open Source Autonomous Marine Surface Vehicle

Authors: U. Pruthviraj, Praveen Kumar R. A. K. Athul, K. V. Gangadharan, S. Rao Shrikantha

Abstract:

An open source based autonomous unmanned marine surface vehicle (UMSV) is developed for some of the marine applications such as pollution control, environmental monitoring and thermal imaging. A double rotomoulded hull boat is deployed which is rugged, tough, quick to deploy and moves faster. It is suitable for environmental monitoring, and it is designed for easy maintenance. A 2HP electric outboard marine motor is used which is powered by a lithium-ion battery and can also be charged from a solar charger. All connections are completely waterproof to IP67 ratings. In full throttle speed, the marine motor is capable of up to 7 kmph. The motor is integrated with an open source based controller using cortex M4F for adjusting the direction of the motor. This UMSV can be operated by three modes: semi-autonomous, manual and fully automated. One of the channels of a 2.4GHz radio link 8 channel transmitter is used for toggling between different modes of the USMV. In this electric outboard marine motor an on board GPS system has been fitted to find the range and GPS positioning. The entire system can be assembled in the field in less than 10 minutes. A Flir Lepton thermal camera core, is integrated with a 64-bit quad-core Linux based open source processor, facilitating real-time capturing of thermal images and the results are stored in a micro SD card which is a data storage device for the system. The thermal camera is interfaced to an open source processor through SPI protocol. These thermal images are used for finding oil spills and to look for people who are drowning at low visibility during the night time. A Real Time clock (RTC) module is attached with the battery to provide the date and time of thermal images captured. For the live video feed, a 900MHz long range video transmitter and receiver is setup by which from a higher power output a longer range of 40miles has been achieved. A Multi-parameter probe is used to measure the following parameters: conductivity, salinity, resistivity, density, dissolved oxygen content, ORP (Oxidation-Reduction Potential), pH level, temperature, water level and pressure (absolute).The maximum pressure it can withstand 160 psi, up to 100m. This work represents a field demonstration of an open source based autonomous navigation system for a marine surface vehicle.

Keywords: open source, autonomous navigation, environmental monitoring, UMSV, outboard motor, multi-parameter probe

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1770 Designing an Agent-Based Model of SMEs to Assess Flood Response Strategies and Resilience

Authors: C. Li, G. Coates, N. Johnson, M. Mc Guinness

Abstract:

In the UK, flooding is responsible for significant losses to the economy due to the impact on businesses, the vast majority of which are Small and Medium Enterprises (SMEs). Businesses of this nature tend to lack formal plans to aid their response to and recovery from disruptive events such as flooding. This paper reports on work on how an agent-based model (ABM) is being developed based on interview data gathered from SMEs at-risk of flooding and/or have direct experience of flooding. The ABM will enable simulations to be performed allowing investigations of different response strategies which SMEs may employ to lessen the impact of flooding, thus strengthening their resilience.

Keywords: ABM, flood response, SMEs, business continuity

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1769 Effect on Haemolymph Cellular Parameters of Periplaneta Americana Following Challenge with Agrobacterium Tumefaciens: A Possible Microbial Control Agent

Authors: Fouzia Qamar, Shahida Hasnain

Abstract:

The present study is primarily concerned with the alteration in haemocyte profile of adult male Periplaneta americana with emphasis on the effect of bacterial inoculations on the haemogram i.e., total haemocyte count (THC) and differential haemocyte count (DHC) of different haemocyte types of the target insect. Haemolymph cellular profile showed considerable alterations under the effect of nine strains of Agrobacterium tumefaciens after 8, 16 and 24 hrs of treatment thereby signifying the potential role of Agrobacterium tumefaciens as a possible biocontrol agent against the house hold pests.

Keywords: Agrobacterium tumefaciens, Periplaneta americana, Haemolymph, cellular parametes

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1768 A New Multi-Target, Multi-Agent Search and Rescue Path Planning Approach

Authors: Jean Berger, Nassirou Lo, Martin Noel

Abstract:

Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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1767 A Block World Problem Based Sudoku Solver

Authors: Luciana Abednego, Cecilia Nugraheni

Abstract:

There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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1766 Artificial Intelligence Methods for Returns Expectations in Financial Markets

Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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1765 Strength & Density of an Autoclaved Aerated Concrete Using Various Air Entraining Agent

Authors: Shashank Gupta, Shiva Garg

Abstract:

The purpose of the present paper is to study the changes in the strength characteristics of autoclaved aerated concrete (AAC) and also the density when different expansion agents are used. The expansion agent so used releases air in the concrete thereby making it lighter by reducing its density. It also increases the workability of the concrete. The various air entraining agents used for this study are hydrogen peroxide, oleic acid, and olive oil. The addition of these agents causes the concrete to rise like cake but it reduces the strength of concrete due to the formation of air voids. The amount of agents chosen for concrete production are 0.5%, 1%, 1.5% by weight of cement.

Keywords: AAC, olive oil, hydrogen peroxide, oleic acid, steam curing

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1764 AER Model: An Integrated Artificial Society Modeling Method for Cloud Manufacturing Service Economic System

Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

Abstract:

With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

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1763 An Efficient Hybrid Approach Based on Multi-Agent System and Emergence Method for the Integration of Systematic Preventive Maintenance Policies

Authors: Abdelhadi Adel, Kadri Ouahab

Abstract:

This paper proposes a hybrid algorithm for the integration of systematic preventive maintenance policies in hybrid flow shop scheduling to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

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1762 Effects of Coupling Agent on the Properties of Henequen Microfiber (NF) Filled High Density Polyethylene (HDPE) Composites

Authors: Pravin Gaikwad, Prakash Mahanwar

Abstract:

The main objective of incorporating natural fibers such as Henequen microfibers (NF) into the High-Density Polyethylene (HDPE) polymer matrix is to reduce the cost and to enhance the mechanical as well as other properties. The Henequen microfibers were chopped manually to 5-7mm in length and added into the polymer matrix at the optimized concentration of 8 wt %. In order to facilitate the link between Henequen microfibers (NF) and HDPE matrix, coupling agent such as Glycidoxy (Epoxy) Functional Methoxy Silane (GPTS) at various concentrations from 0.1%, 0.3%, 0.5%, 0.7%, 0.9%, and 1% by weight to the total fibers were added. The tensile strength of the composite increased marginally while % elongation at break of the composites decreased with increase in silane loading by wt %. Tensile modulus and stiffness observed increased at 0.9 wt % GPTS loading. Flexural as well as impact strength of the composite decreased with increase in GPTS loading by weight %. Dielectric strength of the composite also found increased marginally upto 0.5wt % silane loading and thereafter remained constant.

Keywords: Henequen microfibers (NF), polymer composites, HDPE, coupling agent, GPTS

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1761 The Quotation-Based Algorithm for Distributed Decision Making

Authors: Gennady P. Ginkul, Sergey Yu. Soloviov

Abstract:

The article proposes to use so-called "quotation-based algorithm" for simulation of decision making process in distributed expert systems and multi-agent systems. The idea was adopted from the techniques for group decision-making. It is based on the assumption that one expert system to perform its logical inference may use rules from another expert system. The application of the algorithm was demonstrated on the example in which the consolidated decision is the decision that requires minimal quotation.

Keywords: backward chaining inference, distributed expert systems, group decision making, multi-agent systems

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1760 A Principal-Agent Model for Sharing Mechanism in Integrated Project Delivery Context

Authors: Shan Li, Qiuwen Ma

Abstract:

Integrated project delivery (IPD) is a project delivery method distinguished by a shared risk/rewards mechanism and multiparty agreement. IPD has drawn increasingly attention from construction industry because of its efficiency of solving adversarial problems and reliability to deliver high-performing buildings. However, some evidence showed that some project participants obtained less profit from IPD projects than the typical projects. They attributed it to the unfair IPD sharing mechanism, which resulted in additional time and cost of negotiation on the sharing fractions among project participants. The study is aimed to investigate the reward distribution by constructing a principal-agent model. Based on cooperative game theory, it is examined how to distribute the shared project rewards between client and non-client parties, and identify the sharing fractions among non-client parties. It is found that at least half of the project savings should be allocated to the non-client parties to motivate them to create more project value. Second, the client should raise his sharing fractions when the integration among project participants is efficient. In addition, the client should allocate higher sharing fractions to the non-client party who is more able. This study can help the IPD project participants make fair and motivated sharing mechanisms.

Keywords: cooperative game theory, IPD, principal agent model, sharing mechanism

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1759 Artificial Intelligent Tax Simulator to Minimize Tax Liability for Multinational Corporations

Authors: Sean Goltz, Michael Mayo

Abstract:

The purpose of this research is to use Global-Regulation.com database of the world laws, focusing on tax treaties between countries, in order to create an AI-driven tax simulator that will run an AI agent through potential tax scenarios across countries. The AI agent goal is to identify the scenario that will result in minimum tax liability based on tax treaties between countries. The results will be visualized by a three dimensional matrix. This will be an online web application. Multinational corporations are running their business through multiple countries. These countries, in turn, have a tax treaty with many other countries to regulate the payment of taxes on income that is transferred between these countries. As a result, planning the best tax scenario across multiple countries and numerous tax treaties is almost impossible. This research propose to use Global-Regulation.com database of word laws in English (machine translated by Google and Microsoft API’s) in order to create a simulator that will include the information in the tax treaties. Once ready, an AI agent will be sent through the simulator to identify the scenario that will result in minimum tax liability. Identifying the best tax scenario across countries may save multinational corporations, like Google, billions of dollars annually. Given the nature of the raw data and the domain of taxes (i.e., numbers), this is a promising ground to employ artificial intelligence towards a practical and beneficial purpose.

Keywords: taxation, law, multinational, corporation

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1758 End-to-End Control and Management of Multi-AS Virtual Service Networks Using SDN and Autonomic Computing Architecture

Authors: Yong Xue, Daniel A. Menascé

Abstract:

Automated and end-to-end network resource management and provisioning for virtual service networks in a multiple autonomous systems (a.k.a multi-AS) environment is a challenging and open problem. This paper proposes a novel, scalable and interoperable high-level architecture that incorporates a number of emerging enabling technologies including Software Defined Network (SDN), Network Function Virtualization (NFV), Service Oriented Architecture (SOA), and Autonomic Computing. The proposed architecture can be used to not only automate network resource management and provisioning for virtual service networks across multiple autonomous substrate networks, but also provide an adaptive capability for achieving optimal network resource management and maintaining network-level end-to-end network performance as well. The paper argues that this SDN and autonomic computing based architecture lays a solid foundation that can facilitate the development of the future Internet based on the pluralistic paradigm.

Keywords: virtual network, software defined network, virtual service network, adaptive resource management, SOA, multi-AS, inter-domain

Procedia PDF Downloads 498