An amoeboid algorithm for solving linear transportation problem

Transportation Problem (TP) is one of the basic operational research problems, which plays an important role in many practical applications. In this paper, a bio-inspired mathematical model is proposed to handle the Linear Transportation Problem (LTP) in directed networks by modifying the original amoeba model Physarum Solver. Several examples are used to prove that the provided model can effectively solve Balanced Transportation Problem (BTP), Unbalanced Transportation Problem (UTP), especially the Generalized Transportation Problem (GTP), in a nondiscrete way. © 2013 Elsevier B.V. All rights reserved.

A novel Physarum-Based ant colony system for solving the real-world traveling salesman problem

The solutions to Traveling Salesman Problem can be widely applied in many real-world problems. Ant colony optimization algorithms can provide an approximate solution to a Traveling Salesman Problem. However, most ant colony optimization algorithms suffer premature convergence and low convergence rate. With these observations in mind, a novel ant colony system is proposed, which employs the unique feature of critical tubes reserved in the Physaurm-inspired mathematical model. A series of experiments are conducted, which are consolidated by two realworld Traveling Salesman Problems. The experimental results show that the proposed new ant colony system outperforms classical ant colony system, genetic algorithm, and particle swarm optimization algorithm in efficiency and robustness.

To shut them up or to clarify: restraining the spread of rumors in online social networks

Restraining the spread of rumors in online social networks (OSNs) has long been an important but difficult problem to be addressed. Currently, there are mainly two types of methods 1) blocking rumors at the most influential users or community bridges, or 2) spreading truths to clarify the rumors. Each method claims the better performance among all the others according to their own considerations and environments. However, there must be one standing out of the rest. In this paper, we focus on this part of work. The difficulty is that there does not exist a universal standard to evaluate them. In order to address this problem, we carry out a series of empirical and theoretical analysis on the basis of the introduced mathematical model. Based on this mathematical platform, each method will be evaluated by using real OSN data.We have done three types of analysis in this work. First, we compare all the measures of locating important users. The results suggest that the degree and betweenness measures outperform all the others in the Facebook network. Second, we analyze the method of the truth clarification method, and find that this method has a long-term performance while the degree measure performs well only in the early stage. Third, in order to leverage these two methods, we further explore the strategy of different methods working together and their equivalence. Given a fixed budget in the real world, our analysis provides a potential solution to find out a better strategy by integrating both types of methods together. From both the academic and technical perspective, the work in this paper is an important step towards the most practical and optimal strategies of restraining rumors in OSNs.

Can we beat DDoS attacks in clouds?

Cloud is becoming a dominant computing platform. Naturally, a question that arises is whether we can beat notorious DDoS attacks in a cloud environment. Researchers have demonstrated that the essential issue of DDoS attack and defense is resource competition between defenders and attackers. A cloud usually possesses profound resources and has full control and dynamic allocation capability of its resources. Therefore, cloud offers us the potential to overcome DDoS attacks. However, individual cloud hosted servers are still vulnerable to DDoS attacks if they still run in the traditional way. In this paper, we propose a dynamic resource allocation strategy to counter DDoS attacks against individual cloud customers. When a DDoS attack occurs, we employ the idle resources of the cloud to clone sufficient intrusion prevention servers for the victim in order to quickly filter out attack packets and guarantee the quality of the service for benign users simultaneously. We establish a mathematical model to approximate the needs of our resource investment based on queueing theory. Through careful system analysis and real-world data set experiments, we conclude that we can defeat DDoS attacks in a cloud environment. © 2013 IEEE.

Recent advances in machining of Austempered Ductile Iron to avoid machining induced microstructural phase transformation reaction

Austempered Ductile Iron (ADI) is a type of nodular, ductile cast iron subjected to heat treatments-austenitising and austempering. Whilst machining is conducted prior to heat treatment and offers no significant difficulty, machining post heat treatment is demanding and often avoided. Phase transformation of retained austenite to martensite leading to poor machinability characteristics is a common problem experienced during machining. Study of phase transformations is an investigative study on the factors-plastic strain (εp) and thermal energy (Q) which effect phase transformations during machining. The experimental design consists of face milling grade 1200 at variable Depth of Cut (DoC) range from 1 to 4 mm, coolant on/off, at constant speed, 1992 rpm and feed rate, 0.1 mm/tooth. Plastic strain (εp) and martensite content (M) at fracture point for each grade was evaluated by tensile testing. The effect of thermal energy (Q) on phase transformations was also verified through temperature measurements at DoC 3 and 1 mm using thermocouples embedded into the workpiece. Finally, the amount of plastic strain (εp) and thermal energy (Q) responsible for a given martensite increase (M) during milling was related and calculated using a mathematical function, M=f (εp, Q). The future work of the thesis involves an in-depth study on the new link discovered through this research: mathematical model relating the role of plastic strain and thermal energy in martensite formation.

Mortgage-Backed Securities (MBS): Is It a Curse or a Blessing for the Australian Home Loan Market? A Natural Experiment

The Australian home loan market has seen a significant and persistent boom over more than two decades. Theextant literature exploring the underlying factors explaining this boom has predominantly looked at thedemand side rather than the supply side. In this paper, we look at a major supply-side issue, the introductionof mortgage-backed securities and its likely impact on the home loan market. In doing so, we have developeda mathematical model that theorises this likely relationship. Our mathematical model predicts possibleexistence of an unstable equilibrium in the home loan market in the presence of mortgage-backed securities.We have subsequently backed up our theoretical exercise with sound empirical evidence acquired andanalysed as a natural experiment in the Australian scenario using quarterly market data on home loans andmortgage-backed securities data for a 36-year period from 1976 to 2012. Using unknown structural breaktests, we have identified significant breaks around late 1992 to mid-1995, clearly indicating that there weresignificant changes in the housing market due to the introduction of mortgage-backed securities in early1993. We have also performed a stability test confirming that under certain conditions this market canbecome unstable.

Equivalent dynamic thermoviscoelastic modeling of ionic polymers

Ionic polymers have attracted considerable attention due to their interesting sensing and actuating behavior which make them a proper choice for use in a wide range of applications including biomimetic robots and biomedical devices. The complicated electro-chemo-mechanical dynamics of ionic polymer actuators is a drawback for their applications in functional devices. Therefore, establishing a mathematical model which could effectively predict the actuators' dynamic behavior is of great interest. In this paper, a mathematical model, named equivalent dynamic thermoviscoelastic (EDT) model, based on thermal analogy and beam theory is proposed for dynamic analysis of bending-type ionic polymer actuators. Then, the developed model is extended for analyzing the performance of the actuator in finite element software. The finite element analysis of the actuator enables consideration of material and geometric nonlinearities and facilitates modeling of functional devices based on the ionic polymer actuators. The proposed modeling approach is validated using experimental data.

Enhanced thermal stability and lifetime of epoxy nanocomposites using covalently functionalized clay: Experimental and modelling

The present work aims at finding a relationship between kinetic models of thermal degradation process with the physiochemical structure of epoxy-clay nanocomposites in order to understand its service temperature. In this work, two different types of modified clays, including clay modified with (3-aminopropyl)triethoxysilane (APTES) and a commercial organoclay, were covalently and non-covalently incorporated into epoxy matrix, respectively. The effect of different concentrations of silanized clay on thermal behaviour of epoxy nanocomposites were first investigated in order to choose the optimum clay concentration. Afterwards, thermal characteristics of the degradation process of epoxy nanocomposites were obtained by TGA analysis and the results were employed to determine the kinetic parameters using model-free isoconversional and model-fitting methods. The obtained kinetic parameters were used to model the entire degradation process. The results showed that the incorporation of the different modified clay into epoxy matrix change the mathematical model of the degradation process, associating with different orientations of clay into epoxy matrix confirming by XRD results. The obtained models for each epoxy nanocomposite systems were used to investigate the dependence of degradation rate and degradation time on temperature and conversion degree. Our results provide an explanation as to how the life time of epoxy and its nanocomposites change in a wide range of operating temperatures as a result of their structural changes.

Development of a novel soft parallel robot equipped with polymeric artificial muscles

This paper presents the design, analysis and fabrication of a novel low-cost soft parallel robot for biomedical applications, including bio-micromanipulation devices. The robot consists of two active flexible polymer actuator-based links, which are connected to two rigid links by means of flexible joints. A mathematical model is established between the input voltage to the polymer actuators and the robot's end effector position. The robot has two degrees-of-freedom, making it suitable for handling planar micromanipulation tasks. Moreover, a number of robots can be configured to operate in a cooperative manner for increasing micromanipulation dexterity. Finally, the experimental results demonstrate two main motion modes of the robot.

Nonlinear large deformation dynamic analysis of electroactive polymer actuators

Electroactive polymers have attracted considerable attention in recent years due to their sensing and actuating properties which make them a material of choice for a wide range of applications including sensors, biomimetic robots, and biomedical micro devices. This paper presents an effective modeling strategy for nonlinear large deformation (small strains and moderate rotations) dynamic analysis of polymer actuators. Considering that the complicated electro-chemo-mechanical dynamics of these actuators is a drawback for their application in functional devices, establishing a mathematical model which can effectively predict the actuator's dynamic behavior can be of paramount importance. To effectively predict the actuator's dynamic behavior, a comprehensive mathematical model is proposed correlating the input voltage and the output bending displacement of polymer actuators. The proposed model, which is based on the rigid finite element (RFE) method, consists of two parts, namely electrical and mechanical models. The former is comprised of a ladder network of discrete resistive-capacitive components similar to the network used to model transmission lines, while the latter describes the actuator as a system of rigid links connected by spring-damping elements (sdes). Both electrical and mechanical components are validated through experimental results.

Fabrication of polymeric microchannels with focused and defocused CO2 lasers

 The control of energy distribution or energy intensity inside a laser spot using a defocusing method enables the formation of high-quality microchannels of multiple cross-sections in polycarbonate. Moreover, a thermal mathematical model of the process was developed to aid understanding of the process and to allow channel topology prediction.

Hybrid technique of ant colony and particle swarm optimization for short term wind energy forecasting

Wind farms are producing a considerable portion of the world renewable energy. Since the output power of any wind farm is highly dependent on the wind speed, the power extracted from a wind park is not always a constant value. In order to have a non-disruptive supply of electricity, it is important to have a good scheduling and forecasting system for the energy output of any wind park. In this paper, a new hybrid swarm technique (HAP) is used to forecast the energy output of a real wind farm located in Binaloud, Iran. The technique consists of the hybridization of the ant colony optimization (ACO) and particle swarm optimization (PSO) which are two meta-heuristic techniques under the category of swarm intelligence. The hybridization of the two algorithms to optimize the forecasting model leads to a higher quality result with a faster convergence profile. The empirical hourly wind power output of Binaloud Wind Farm for 364 days is collected and used to train and test the prepared model. The meteorological data consisting of wind speed and ambient temperature is used as the inputs to the mathematical model. The results indicate that the proposed technique can estimate the output wind power based on the wind speed and the ambient temperature with an MAPE of 3.513%.

Step by step analyzing, modeling and simulation of single and double array PV system in different environmental variability

This research analyses the mathematical model of the PV array with all the parameters involved, in the sequential steps. Then it is going to simulate the I-V and P-V characteristics of PV array in different climatology conditions, by using both MATLAB M-file and Simulink. Finally the capability of this method is demonstrated in simulated results, which are performed for both Single and Double Array PV system.

A review on otolith models in human perception

The vestibular system, which consists of semicircular canals and otolith, are the main sensors mammals use to perceive rotational and linear motions. Identifying the most suitable and consistent mathematical model of the vestibular system is important for research related to driving perception. An appropriate vestibular model is essential for implementation of the Motion Cueing Algorithm (MCA) for motion simulation purposes, because the quality of the MCA is directly dependent on the vestibular model used. In this review, the history and development process of otolith models are presented and analyzed. The otolith organs can detect linear acceleration and transmit information about sensed applied specific forces on the human body. The main purpose of this review is to determine the appropriate otolith models that agree with theoretical analyses and experimental results as well as provide reliable estimation for the vestibular system functions. Formulating and selecting the most appropriate mathematical model of the vestibular system is important to ensure successful human perception modelling and simulation when implementing the model into the MCA for motion analysis.

A feasible IP traceback framework through dynamic deterministic packet marking

DDoS attack source traceback is an open and challenging problem. Deterministic packet marking (DPM) is a simple and effective traceback mechanism, but the current DPM based traceback schemes are not practical due to their scalability constraint. We noticed a factor that only a limited number of computers and routers are involved in an attack session. Therefore, we only need to mark these involved nodes for traceback purpose, rather than marking every node of the Internet as the existing schemes doing. Based on this finding, we propose a novel marking on demand (MOD) traceback scheme based on the DPM mechanism. In order to traceback to involved attack source, what we need to do is to mark these involved ingress routers using the traditional DPM strategy. Similar to existing schemes, we require participated routers to install a traffic monitor. When a monitor notices a surge of suspicious network flows, it will request a unique mark from a globally shared MOD server, and mark the suspicious flows with the unique marks. At the same time, the MOD server records the information of the marks and their related requesting IP addresses. Once a DDoS attack is confirmed, the victim can obtain the attack sources by requesting the MOD server with the marks extracted from attack packets. Moreover, we use the marking space in a round-robin style, which essentially addresses the scalability problem of the existing DPM based traceback schemes. We establish a mathematical model for the proposed traceback scheme, and thoroughly analyze the system. Theoretical analysis and extensive real-world data experiments demonstrate that the proposed traceback method is feasible and effective.