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Emerging Industry 5.0 pushes advanced automation towards resilient solutions with enhanced human role. Resilience as an ability to sustain processes in the face of disruptions and adversarial attacks requires careful modelling and simulation. Cellular automata are efficient mathematical models used to simulate the behavior of complex systems, which change their state based on a set of predefined rules. In this paper, we suggest several updates to cellular automata (particularly Conway's "Game of Life") to address resilience. These include "Life and Creation", "War and Peace", and their hybrid "War and Creation" capable of addressing the important components of resilience, such as controllable creativity and adversarial interactions. Inherited in these updates and known advantages of cellular automata, such as simplicity, emergent behavior, parallelism, and adaptability, makes it a powerful simulation tool for a wide range of Industry 5.0 systems that involve humans, smart infrastructure, their complex and adversarial interactions, safety, and resilience. [ABSTRACT FROM AUTHOR]

This research paper focuses on the development of advanced mathematical models for disease diagnosis and prediction, and the subsequent creation of automated systems based on these models. These systems leverage a range of mathematical models and incorporate cutting-edge information technology achievements to provide medical professionals with valuable decision-making support. By amalgamating mathematical rigor and technological innovation, this research endeavors to enhance the accuracy and efficiency of medical diagnoses, thereby improving patient care and healthcare outcomes. This study delves into the persistent need for contemporary information systems, where information plays a crucial role in decision-making. It aims to provide an objective approach to addressing pressing medical challenges, particularly in disease diagnosis and prediction, enhancing the effectiveness of these critical tasks. Automated medical information systems, built on advanced mathematical models, significantly empower physicians. Machine diagnostics, relying on deterministic logic, the phase interval method, and information-probabilistic logic, bolster diagnostic capabilities. Functional entropy enables individuals to handle vague information, aiding decision-making. Assessing imprecision and uncertainty computationally diminishes subjectivity, while employing fuzzy set theory enhances diagnostic modeling. Mathematical models assess diagnostic indicators, and linguistic variables quantify resemblance. The diagnostic model for primary biliary cirrhosis and active hepatitis utilizes a diagnostic table and gradient projection. This comprehensive study advances medical diagnostics through mathematical models and automated systems, addressing critical healthcare challenges. [ABSTRACT FROM AUTHOR]

This manuscript discusses the positional systems used in intelligent robots. One of the characteristic problems that arise in such systems is associated with friction, including sticking during the process. Friction greatly affects the positioning accuracy of the actuators of controlled robots, especially if a pneumatic actuator is used as a motor. The work is devoted to the study and solution of this problem. Since it is impossible to completely eliminate the effect of friction, ways to minimize this effect are being investigated using a targeted choice of system parameters. For this purpose, the method of multicriteria optimization of a detailed mathematical model is applied on the example of a pneumatic positional system, as the most sensitive to friction. The paper considers the first stage of optimization associated with visualization and preliminary analysis of the process in order to prepare it for performing a system procedure. The dynamics equations of an intelligent positional system are written out, both in full-size and dimensionless one. The most convenient mathematical model of friction is presented terms of its use in the process of optimizing the entire control system. A procedure for visualizing the optimization process in the form of a graphical interface has been developed. The first stage of the intelligent drive system optimization procedure has been carried out. The paper presents at which parameters of the control system the "stick-slip" effect has less influence on the positioning process. [ABSTRACT FROM AUTHOR]

In this paper, the stabilization and set point tracking of the utility boiler is achieved via the Proportional-Integral-Derivative (PID) controller, tuned using the versions of metaheuristic Particle Swarm Optimization (PSO) algorithms. The utility boiler model dynamics are based on the Bell and Astrom boiler turbine system. Initially, the non-linear mathematical model is obtained using the first principles data from the plant model. Further, Taylor series approximation is applied to linearize the non-linear equations around the equilibrium point to implement a stable controller for the plant. Finally, the PID controller gains for the plant model are determined using the PSO algorithms to achieve the desired response. For tuning the PID controller, three PSO algorithms namely standard PSO, Adaptive PSO (APSO) and Improved Adaptive PSO (IAPSO) are proposed. The performance of the proposed PSO based PID control algorithms are evaluated using error metrics such as Integral Absolute Error (IAE), Integral Time Absolute Error (ITAE) and Integral Square Error (ISE). The simulation results show that the proposed APSO and IAPSO algorithms have improved performance when compared to regular PSO algorithms and are capable of optimizing the control parameters. [ABSTRACT FROM AUTHOR]

Magnetic localization techniques are used in in vivo therapy, drug delivery, and surgical localization widely due to their ability to locate in an unobstructed environment precisely. The Levenberg-Marquardt (L-M) algorithm is one of the most common magnetic localization algorithms due to its fast optimization speed and high precision, but it requires high initial values such that improper initial values can easily lead to local optimization. In this paper, the performance of ten commonly used intelligent optimization algorithms is compared based on the mathematical model of the permanent magnet. The final position of the magnet is obtained by a fusion algorithm that uses the result of the intelligent optimization algorithm as the initial value of L-M. The real-time localization accuracy of this fusion algorithm is verified on a hardware platform and experiments demonstrate that the integration of the TSA algorithm and L-M algorithm fusion yields higher performance of the magnetic positioning system. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method to address coherent interference (pilot contamination) in Massive MIMO by incorporating control over propagation environment through Intelligent Reflecting Surfaces. In earlier research it was established that each mobile device has unique spatial signature which can be used as identifier even if they are sharing same pilot sequence. However in certain circumstances when their signals are received at BS with same Angle of Arrival their spatial structure become similar thus their individual identity is lost. This situation adds error in acquisition of channel state information, the accuracy of which is the key to benefit from Massive MIMO. This paper present a method to resolve the mentioned accepted gap using mathematical basis and simulation methods. A mathematical model of Massive MIMO is presented which is widely accepted by the subject modeling community. The model is then used to generate the basis for the presented algorithm through further mathematical studies and simulations. The basic algorithm used for the resolution of pilot contamination problem is finally presented in this paper. The algorithm was simulated using MATLAB and simulation results are tabulated to identify the results of pilot de-contamination after incorporating signal propagation control. [ABSTRACT FROM AUTHOR]

Intelligent Reflection Surface (IRS) will be widely used in future communication system construction to reduce construction costs and improve coverage. However, IRS systems are generally equipped with controllers to receive wireless signal instructions, this increases the vulnerability of future communications. In this paper, we present an attack tactic to provide a way of thinking for the future defense deployment. At the beginning, the hacker cannot know the whole communication system, then it continuously attacks the IRS system, monitor the communication system, and sequentially learns new information about the system in each attacking round in order to attack more effectively in the next round. A two-layer optimal mathematical model is presented to describe the BS and the hacker's decision. And the two-layer optimization which is difficult to solve is transformed into a single layer linear optimization by using equivalent transformation and dual transformation. A series of mathematical experiments are used to test different scenarios applicable to different monitoring style, and verify that the tactic proposed in this paper can effectively interfere with the system. [ABSTRACT FROM AUTHOR]

The paper presents the optimization of the geraniol transformation process based on the RSM method (response surface methodology). RSM is a fusion of statistical and mathematical modeling methods and explores the relationships between several explanatory variables and one or more response variables. The interaction among process variables can be determined by statistical techniques. It can be utilized in multi-criteria optimization. The influence of the most important process parameters, such as temperature, catalyst concentration and reaction time, is shown. The response functions characterizing the process were: conversion of geraniol, selectivity of thunbergol and selectivity of 6,11-dimethyl-2,6,10-dodecatrien-1-ol. For individual process parameters, their influence on all initial parameters in the form of second-degree polynomials was determined and such as process conditions were determined to achieve their maximum. [ABSTRACT FROM AUTHOR]

In this paper we show how a parametric discussion on the optimal objective values to two mathematical models involved in a fuzzy standard data envelopment analysis can provide an analytic description to the membership functions of the fuzzy efficiencies of the decision-making units. We recall the mathematical models under discussion from the literature, but we approach them from a novel perspective, thus providing an analytical alternative to the numerical methods used so far in the literature. [ABSTRACT FROM AUTHOR]

This paper focuses on training the mathematical models for prediction of optimal livestock feed blend for animal. In this paper, three functions are trained to find the most optimal percentage of price, nutrients and water. For this purpose three objective functions has been prepared using corresponding values of feed ingredients and an algorithm is developed using ANN. The objective functions are trained with 5000 random values to find the optimized results and prediction ability is compared with existing model. Developed algorithm shows superiority over the existing programming models. [ABSTRACT FROM AUTHOR]

Abstract This paper discusses how natural language could be supported in further developing the Common Model of Cognition following the TalaMind approach toward human-level artificial intelligence. These thoughts are presented as answers to questions posed by Peter Lindes, Paul Rosenbloom, and reviewers of this paper, followed by a description of the TalaMind demonstration system, and a general discussion of theoretical and strategic issues for the Common Model of Cognition. [ABSTRACT FROM AUTHOR]

The paper discusses the classic problem of designing automatic ship course-keeping control systems using a relatively new methodology called Active Disturbance Rejection Control (ADRC). A comparative analysis of simulation results obtained via ADRC versus a traditional autopilot based on the PID algorithm was performed. The novelty of this article lies in the use of a complete realistic mathematical model of the ship both as a simulation model and as a framework for derivation a simplified model structure, appropriate for controller design. The results obtained indicate higher efficiency of the ADRC autopilot compared to the PID variant. Another important feature of using ADRC control over PID is the elimination of the tuning problem. [ABSTRACT FROM AUTHOR]

In the area of human digital twins, the designed model should be as close as possible to the reality. The weight variable is one of the interested parameters of these mathematical models, as well as its interaction with other vital signals. The aim of this paper is including the information gathered from weight sensors of a person in its digital twin. To do this it is described an algorithm that filters and forecasts the human weight to use it in indexes such as BMI. It has been applied to a real sample and the results obtained are good. [ABSTRACT FROM AUTHOR]

In this paper, we extend the classic SIR model to find an optimal lockdown policy to balance between the economy and people's health during the outbreak of COVID-19. In our model, we intend to solve a two phases optimisation problem: policymakers control the lockdown rate to maximise the overall welfare of the society; people in different health statuses take different decisions on their working hours and consumption to maximise their utility. We develop a novel method to estimate parameters for the model through various additional sources of data. We use the Cournot equilibrium to model people's behaviour. The analysis of simulation results provides scientific suggestions for policymakers to make critical decisions on when to start the lockdown and how strong it should be during the whole period of the outbreak. [ABSTRACT FROM AUTHOR]

Aiming at the two types of SAR spoofing jamming problems of range delay and azimuth Doppler frequency modulation, this paper proposes a multi-channel two-dimensional hybrid baseline anti-spoofing jamming method, which realizes the SAR deception jamming. The necessary condition for this method to use multi-channel coherent accumulation is phase synchronization between channels, otherwise it is the principle of non-coherent accumulation, phase compensation is used to suppress interfering targets, thereby enhancing the radar's anti-spoofing interference capability. First, by constructing the SAR geometric model and related mathematical derivation, the principle of deception interference is introduced, and then the cumulative effect of phase compensation based on the two-dimensional hybrid baseline based on multiple channels is analyzed, and the principle of suppressing deception interference is introduced. Finally, the effectiveness and correctness of the anti-spoofing jamming method are verified through the simulation experiment of anti-spoofing jamming with multipoint targets. [ABSTRACT FROM AUTHOR]

The paper presents models for describing the operating scenarios of automated systems. The authors introduce and analyze the category "the life cycle of automated system scenarios". The life cycle consists of a sequence of stages. The leading success factor of any scenario is the support of the scenario during all stages of its life cycle. The most important stages of the scenario life cycle are the following: the stage of forming the event set for generating the scenario, the stage of performing the sequence of scenario events and the stage of situational analysis of the external and internal environment of the event. In the article it is proposed to use a theoretical set model in order to select an element from a set of alternatives. The elements are events for designing a scenario. The model uses fuzzy logic and is based on the process of controlling an array of parameters if variants are available. The model is used to support the stage of forming a set of events for generating the scenario. The mathematical model of automated system operation which is used to support the stage of performing the sequence of scenario events is suggested in the article. The model is based on the principle of information logistics: each parameter (a set of data) is in the right place in the automated system, 'just-in-time' and in the required format. A modified frame model is proposed to support situational analysis. Situational analysis is used to operate the event algorithms and to determine the next event in the scenario. The modified frame model is based on the use of fuzzy logic procedures in a frame network. [ABSTRACT FROM AUTHOR]

Mathematical modelling helps to describe the functional and causal relationships between objects in the physical world. The complexity of these models increases as more components and variables are added to maintain and observe. Differential equations are regularly used in these models, as they are able to display the interactions between several variables and describe non-linear behaviour. Differential equations are commonly used in immune response mathematical models to help describe these complex and dynamic interactions within the immune system of the organism. Time delays in the immune system are common and are often disregarded due to the low-resolution of models, which provide limited description of the specific section of immune system being studied. The few models that incorporate time delays are mostly at the epidemiological level, to track the spread of the virus in the population. In this paper we review the applications of the models based on differential equations and describe their potential utilization for the studies of immune response in SARS-CoV-2. [ABSTRACT FROM AUTHOR]

In order to solve the problem of estimating the model parameters of hemodynamic model under low frequency interference, a new model parameter estimation algorithm (CSCKS) is proposed in this paper for the hemodynamic model with low frequency interference. The algorithm is based on SCKS algorithm to improve, its estimation effect is obviously better than the existing SCKS algorithm and DEM algorithm. We simulate the proposed algorithm and some other traditional algorithms to evaluate the estimation performance of CSCKS proposed in this paper under different Signal to Interference Ratio (SIR) and different integration steps, and through the simulation results, the estimated results of the algorithm were analyzed and compared. [ABSTRACT FROM AUTHOR]

Transportation modeling and simulation play an important role in the planning and management of emergency evacuation. It is often indispensable for the preparedness and timely response to extreme events occurring in highly populated areas. Reliable and robust agent-based evacuation models are of great importance to support evacuation decision making. Nevertheless, these models rely on numerous hypothetical causal relationships between the evacuation behavior and a variety of factors including socio-economic characteristics and storm intensity. Understanding the impacts of these factors on evacuation behaviors (e.g., destination and route choices) is crucial in preparing optimal evacuation plans. This paper aims to contribute to the literature by integrating well-calibrated behavior models with an agent-based evacuation simulation model in the context of hurricane evacuation. Specifically, discrete choice models were developed to estimate the evacuation behaviors based on large-scale survey data in Northern New Jersey. Monte-Carlo Markov Chain (MCMC) sampling method was used to estimate evacuation propensity and destination choices for the whole population. Finally, evacuation of over a million residents in the study area was simulated using agent-based simulation built in MATSim. The agent-based modeling framework proposed in this paper provides an integrated methodology for evacuation simulation with specific consideration of agents’ behaviors. The simulation results need to be further validated and verified using real-world evacuation data. [ABSTRACT FROM AUTHOR]

Nowadays, the number of papers on the topic of Knowledge Management and Knowledge Management System is still widely discussed. The study of Knowledge Management System (KMS) issues are based on Systematic Literature Review (SLR). It aims to analyze the state of the art, identify current popular issues on KMS, and offer directions for future research agenda. The methodology used in this paper is based on the systematic literature review to collect, synthesize and analyze numerous papers on a variety of topics that are closely related to knowledge management system issues that published in the last two decades. Based on fifty-four papers reviewed from six electronic databases, the result of this paper obtained fourteen current issues on knowledge management system. Moreover, the top three popular issues consist of the development of capabilities and features of KMS, Big Data issues on KMS, and adoption to new technology issue for KMS respectively. The conclusion of this study emphasized the big data phenomenon as the most contemporary topic for the future research area besides the growing of required KMS capabilities and features development. [ABSTRACT FROM AUTHOR]

Nowadays, drones are popular with their multipurpose functioning. They can be applied in different environments, especially those that are harmful and can cause health hazards to the human being. However, drones are expensive, have limitations in the lifting capabilities, difficult in control, and auto-balancing. This paper focuses on deriving a mathematical model of the quadcopter with its characteristic properties to solve the auto-balancing problem. The research determines the mathematical model of the unmanned aerial vehicles (UAV) and then incorporates characteristic values of the constructed model (I xx , τ thrust and etc.) to the general model. The derived equation is used in identifying the controlling parameters of the quadcopter. The key focus of this research is to develop a cost-effective, self-stabilizing, and robust control system using affordable components. A gyroscope MPU6050, a transmitter, and a receiver (with at least 4 inputs) were integrated with microcontrollers to develop the system. [ABSTRACT FROM AUTHOR]

The paper presents a general method for constructing a mathematical model of multi-link robot-manipulators. For the 3-DOF manipulator, kinematic equations and differential equations of dynamics are obtained. To study mathematical models of the dynamics of robotic manipulators and applications in software control systems, it is necessary to develop special analytical methods for solving systems of differential equations. An analytical method of transformations applied for the study of mathematical models of the dynamics of 3-DOF robot-manipulators. The method allows to obtain a solution in an analytical form, taking into account all nonlinear components of the system of differential equations. The software package for study of nonlinear mathematical models was developed and implemented. The problem of software control of electric drives of 3-DOF robot-manipulator is considered and control actions are determined that ensure the fulfillment of a given trajectory by the manipulator. The method for constructing and analyzing a mathematical model of manipulators presented in this work can be used to study a wide class of multi-link manipulators with many degrees of freedom. [ABSTRACT FROM AUTHOR]

In the paper there is discussed the problem of constructing and implementation the mathematical models for control algorithms of concurrent processes. For the control object example there was taken an example of 3D Cartesian machine. The control algorithm is mathematically described with use of Finite State Machine methodology in canonical and concurrent variants. Implementation examples are given, problem of resources consumption and operation time is discussed and the conclusion is d drawn. [ABSTRACT FROM AUTHOR]

Statistics from Innovation Union Scoreboard 2015 1 shows that the Baltic States have a low innovation index in comparison with other European countries. One of the main reasons is that a lot of developed prototypes do not use in the business area and stay at the research laboratories. Research organization does not have a direct link to the market. The purpose of this paper is to contribute to the solution of problems in Latvian innovation system. Authors of this paper have selected innovation, knowledge and technology transfer model as the bridge between academia and market. During research work selected Information Technology (IT) research results developed in Riga Technical University (Latvia) were validated according to proposed technology transfer model. The paper presents a description of the communication process with the information technology developers and potential end-users and document results of it. [ABSTRACT FROM AUTHOR]

This paper discusses a mixed methodological approach to address cost and schedule delays in large-scale engineering programs (LSEP). Research has identified potential causes or factors for schedule delays, such as: ineffective human resources policies and practices, consolidation of the aerospace industry, too many stakeholders, and lack of knowledge-based acquisition practices. Current methods and tools are ineffective in helping project managers to accurately predict schedule performance during LSEP development. The authors describe research to investigate the feasibility of: (1) deriving quantitative and qualitative causal factors correlating to schedule performance during LSEP development; (2) developing a framework and a tailorable predictive model using the causal factors in a Bayesian Network (BN) model; and (3) using the resultant framework and BN model, with expert knowledge elicited from subject matter experts, to predict schedule performance and inform decision makers on actions needed to manage schedule performance. Finally, this paper discusses a version of a BN model developed by mapping a conceptualization of the framework created using a systemigram with a BN pattern that includes dependencies from causal and control factors to schedule performance. The BN incorporates a direct causal dependence of schedule performance and mitigation actions to the consequences of schedule performance. [ABSTRACT FROM AUTHOR]

Entity resolution is an important application in field of data cleaning. Standard approaches like deterministic methods and probabilistic methods are generally used for this purpose. Many new approaches using single layer perceptron, crowdsourcing etc. are developed to improve the efficiency and also to reduce the time of entity resolution. The approaches used for this purpose also depend on the type of dataset, labeled or unlabeled. This paper presents a new method for labeled data which uses single layered convolutional neural network to perform entity resolution. It also describes how crowdsourcing can be used with the output of the convolutional neural network to further improve the accuracy of the approach while minimizing the cost of crowdsourcing. The paper also discusses the data pre-processing steps used for training the convolutional neural network. Finally it describes the airplane sensor dataset which is used for demonstration of this approach and then shows the experimental results achieved using convolutional neural network. [ABSTRACT FROM AUTHOR]

Over the last years we have seen a rapid expansion within the area of Internet of Things (IoT) applications. For many applications' use cases, such as rescue monitor systems, the problem of localization (i.e. determine the physical location of nodes) is critical. This paper studies and evaluates the usage of mathematical model of multilateration algorithms using Time Difference of Arrival (TDoA) as a solution for positioning over Long Range Wide Area Network (LoRaWAN). The research is carried out using simulations in Python by configuring the constant positions of the Gateways inside an outdoor area. The proposed algorithms can be integrated in application for tracking people at any time and especially routing people from vulnerable groups. Through multilateration and algorithm's prediction, we can have an accuracy of 40-60m in location positioning ideal for search and rescue use cases. [ABSTRACT FROM AUTHOR]

In this paper a major amount of work has been listed regarding multi-objective optimization problem using evolutionary algorithms. From time immemorial optimization have been required in every industry for improvement of the business or other scientific results. Evolutionary algorithms is a direct search algorithm and has been applied for various mathematical models to attain optimal results because of its adaptability with the system. The aim of the study is to find a multi-objective transportation problem by using evolutionary algorithm in bipartite graph. In multi-travelling salesman problem the objective to derive the optimal sequencing schedule of a salesman which is formed as a multiple objective problem. [ABSTRACT FROM AUTHOR]

In this paper we consider an approach to the creation of self-organizing neural networks that provide patterns in sensory signals, based on the optimization of local parameters to optimize the functioning of a single neuron. The neural network provides optimization of the global parameter "well-being" as an integral characteristic of local parameters for all neurons of the network. A mathematical model of a spike neuron with time and resource constraints has been developed. A number of experiments have been carried out, which showed the principal possibility of automatic formation of ensembles corresponding to the peculiarities in the patterns of input signals as a result of optimization of the global parameter of the network under conditions of lack of resources. [ABSTRACT FROM AUTHOR]

Diverse machine learning methods have been successfully used to discover classifying rule among classification data. Sometimes, executing a decision may however indirectly alter feature values of the classified objects, further influencing their classes under the discovered classifying rule. Actually, mining such classification conducting knowledge (CC-knowledge) hidden under the decision from related data can be very helpful to future decision-makings. Hence, this paper proposes an evolutionary robust GRBF-NN model to imitate the mathematical mapping between the feature values before and after executing the decision. A dual-loop nested robust training (DNRT) method is correspondingly developed to determine the weights and parameters using M-AdaBoost and NSGAII respectively in the inner and outer loop. Its remarkable merit is that it considers the classification information by integrating the given classifying rule into both training loops, ensuring the reasonability of prediction. In order to enhance the model's generalization, the outer loop defines a regularized term and regards it as another optimizing objective of NSGAII besides the training error. Finally, several datasets are employed to verify the effectiveness of the proposed method for CC-knowledge acquisition. [ABSTRACT FROM AUTHOR]

The paper describes a new approach based on the hybridization of Simulated Annealing algorithm and Tabu Search (SA-TS) to solve the Ambulance Routing Problem (ARP).In this research, we present a mathematical model for the addressed problem (ARP) based on the Vehicle Routing Problem (VRP) formulation. In this work, we aim to offer an efficient routing solution to the ambulance vehicles for emergency demands when a disaster or more than accidents occur at the same time. Our proposed approach solves this problem with the application of the cluster-first route-second method to a standard VRP. We propose the k-Means algorithm for the cluster phase and a hybrid meta-heuristic Simulated Annealing-Tabu Search (SA-TS) for the routing phase of the problem. Our approach (k-Means) gives cultures very close to the exact solution and better than the Petal algorithm. Also for the routing phase, experimental results show competitive solutions compared with recent literature review approaches using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) approaches on Augerat et al (1995) benchmark datasets while improving processing times. [ABSTRACT FROM AUTHOR]

In this paper, the friction compensation method of SCARA robot is proposed. During the operation, the friction force in the system causes the heat to the robot and system. Since heat which occurred in the system is accumulated for a long time, the robot and system have been damaged. Moreover, performance and stability of the system have been reduced. Therefore, compensation of friction force is an important method for increase performance and stability of the system. In this paper, the disturbance observer is used with mathematic modelling of friction compensation for compensate the friction force in the system. From the simulation results, the system which has a friction force compensation can show the increasing of performance and stability. [ABSTRACT FROM AUTHOR]

This paper presents a 3x3 antenna array of ractangular topology is designed to operate at Ku Band. The antenna has been designed as arrays of patches, where number of elements, spacing's and feeding currents has been optimized to fulfil the requirements of low side lobe level and good cross polarization. The operating frequency of array is from 12 to 18 GHz. The antenna array has been designed and simulated on FR4 Substrate with dielectric constant of 4.4. This paper presents that, the detail steps of designing and simulating the rectangular patch antenna and rectangular patch antenna Array in Ku-band. The design is analysed by FEM based HFSS 14.0 by which return loss, 3D polar plot, Directivity, VSWR and Gain of the antenna are computed. The software simulated results are shows that the proposed antenna array provides good performance in terms of return loss, VSWR and Gain. [ABSTRACT FROM AUTHOR]

Understanding and analysing security risks is an essential task when designing and maintaining a systems’ security. The first risk analysis should be performed during the system design. Identified risks have to be updated during the lifecycle when security controls are implemented or new threats appear. Visualization facilitates the risk analysis process, but visualizing the huge amount of risks with diverse causalities is challenging. This paper concentrates on risk visualization and related challenges. The paper presents a semantic model for risk visualization and structuring implemented into the Metric Visualization System (MVS). The proposed model and tool support make risk visualization consistent and ensures that it includes mutual connections of risks. The contribution helps designers to analyse risks and to select security controls in a justified manner. [ABSTRACT FROM AUTHOR]

This paper reports on the results of the Zero Resource Speech Challenge 2015, the first unified benchmark for zero resource speech technology, which aims at the unsupervised discovery of subword and word units from raw speech. This paper discusses the motivation for the challenge, its data sets, tasks and baseline systems. We outline the ideas behind the systems that were submitted for the two challenge tracks: unsupervised subword unit modeling and spoken term discovery, and summarize their results. The results obtained by participating teams show great promise; many systems beat the provided baselines and some even perform better than comparable supervised systems. [ABSTRACT FROM AUTHOR]

This paper describes the method of representation of the Dynamic Social Network. Authors begin the discussion with a formal introduction where they had brought out the need of the emergence of the Dynamic Social Network and its application in the various fields of science. Authors has carried forward the discussion with description of the two models of the Dynamic Social Network. Portions of the paper is a review work. In the followed section of this work, discussion is carried about how these models can be represented as one of the basic type of Finite State Machine. Finally the paper concludes with a real life example and the application of Dynamic Social Network in MANETS. [ABSTRACT FROM AUTHOR]

This paper tries to model the code obfuscation as satisfiability problem. In this paper, we try to develop the model to represent the obfuscated code as the satisfiable problem which could be then checked by the SAT solver to check whether at certain instances the model is satisfiable. We provide the notion of converting the SSA format of the instructions to the propositional logic and then by the help of the theorem provers, we tell whether both the code snippets of obfuscated code are same or not. This can be done by converting both codes from their original code to the mathematical signature or relational encoding and then checking their logical equivalence. [ABSTRACT FROM AUTHOR]

Vehicular Adhoc Network is a special form of the Mobile Adhoc Network which has received remarkable attention with the growing era. It is capable of providing data communication between the mobile vehicles. It focuses on safety related applications and Internet accessing related applications. The basic model of the VANETs consists of On Board Units (OBUs) and Road Side Units (RSUs). These units communicate through an open wireless medium, creating a threat to the network. As the malicious node can attack the privacy information such as the user's identity, tracing preferences etc., if the node is not properly protected. Therefore, there is a need of security requirements to secure it. The paper describes various requirements, characteristics, challenging issues and techniques of security in VANETs. In this paper a theoretical analysis of different security techniques of Vehicular Adhoc Networks has been done which compare different schemes at different levels like hardware, authentication, privacy and certification techniques etc. [ABSTRACT FROM AUTHOR]

This paper presents evolution of Automatic variable key cryptosystem with study and analysis of state of symmetric cryptosystem. It presents framework of AVK model and extension by parameterized approach. The evaluation of cryptosystem from perspective of cryptanalyst has been presented. The paper opens direction of “Cryptic Mining “discipline. The AVK approach finds application in low power secure device communication, which is most desirable feature of Internet of Things. [ABSTRACT FROM AUTHOR]

Design and development of a Web map application as part of Geographic Information Systems (GIS) is a complex activity because of specific areas and stakeholders that are involved in this process. The quality aspect of the requirement definition process is important for application functionality. The complexity of web applications has increased in the last few years and web map applications have made great progress from simple map portrayal to complex applications with a large number of functions. Enterprise modelling (EM) can be used for a multitude of different purposes, like visualization of the current situation, analysis of the reasons for shortcomings or problems, development of strategies for business or IT, optimization of processes, or establishment of new cooperation with other enterprises, as well adapted to the versatile purpose in the design of an information system. The aim of this paper is to discuss opportunities and a new approach supported by enterprise models for designing web map applications. The outcomes of this paper are: (1) taxonomy of a web map application and support of enterprise modelling for functionality analysis; (2) extension of EM to specify requirements for web map application; (3) description of practical applications of the findings. [ABSTRACT FROM AUTHOR]

Mobile devices have gained popularity worldwide. The mobile device flexibility has encouraged users to turn their mobile devices into primary hubs for storing information. This paper adopts the classical CW-Lite security models as the framework and the human behavioral patterns as the context. The selected behavioral aspects refer to mobile application and mobility, deployed as major characteristics that determine security control decisions. This proposed paper requires the application of human behavioral context on mobile phones. The solution involves the novel use of behavioral aspects to improve the security of mobile phones. Two important scenarios are incorporated: analytic hierarchy process (AHP) mobile application and AHP mobility. The proposed methodology is superior because it can detect the change in the user behavior in comparison with an intruder. The applied intelligent human behavioral context on the CW-Lite model shows the advantages of AHP in detecting the changes in the user behavior and in authenticating the identity of the main user. These advantages ensure reliability and security of the phone. [ABSTRACT FROM AUTHOR]

Today, Indonesian citizen experience a fast changing lifestyle related to information and communication technology (ICT) utility, such as gadget and internet. The ease of information and knowledge retrieval to support learning process comes with problems to be taken care of such as information overload, negative content, netiquette negligence, and gadget addiction. Meanwhile, Indonesia will face an upcoming challenge in the economic sector, Free Trade Area of the Asia-Pacific (FTAAP) in 2020. An initiative for economic integration uses ICT as economic hub to promote every sector growth in economy. A concept explored in this research context to answers those problems mentioned above and to overcome the upcoming challenge is improving quality of Indonesian human resources through digital literacy education. This paper discusses a learning system model dedicated to deliver digital literacy education to the Indonesian citizen. Objectives of this research are increasing awareness towards digital literacy concept and preparing citizen to be digitally literate and competent using ICT to support their learning process, doing their work more effective and efficient, and preparing Indonesian young generation to become qualified workforce competing in FTAAP 2020, furthermore international work competition. This paper delivers analysis for learning system model as a result from the initial research of research series about digital literacy education in Indonesia. Resulting model justified by sets of detailed scenario about how this model works. [ABSTRACT FROM AUTHOR]

The aim of this paper is to design a conceptual model that can be used by practitioners and researchers to better understand how they can possibly use Enterprise Content Management Systems (ECMS) in supporting their business operations. In designing the model, this research has reviewed ECMS literature that provides insight on how these technologies work. ECMS researchers point to two possible ways to understand and explore how ECMS is used to support business operations. These two possible ways provides a direction to this study which is, to: (1) consider organization's business process structure as a starting point to understand ECMS-use; and (2) examine the interaction between technologies (ECMS), the organizational context, processes, business needs and users that shape certain ways of using these technologies. At the end of this paper, a research model that guide practitioners to understand ways to maximize and benefit from ECMS-use is presented. Business and IT managers could use the model to better understand ways to apply ECMS in their daily work practices to conduct business. On the other hand, IS researchers could use this model to further conduct empirical investigation to get a deeper understanding of ECMS-use and uncover qualities that have not been discovered in this study. [ABSTRACT FROM AUTHOR]

The main theme of this paper is to provide a cognitive architecture, MHP/RT (Model Human Processor with Realtime Constraints), that is appropriate for describing the idea, “The agent would not be getting an informational input or a reinforcement, but the inputs would be better described as perturbations on a self-organizing complex systems”, as stated in the call for the workshop, Enaction, Complex Systems and Cognitive Architectures. MHP/RT describes a cyclic process of action selection and memorization while one lives in the world, and the memory is gradually structured as multi-dimensional frames as one interacts with the environment. Behavioral processing constraints are imposed by conscious and unconscious processes, and behavior must be synchronized with the ever-changing external and internal environments. This paper provides a brief explanation of MHP/RT and multi-dimensional memory frames, followed by how memory is structured as one develops. [ABSTRACT FROM AUTHOR]

In this paper, novel method based on loss sensitivity approach is utilized to determine optimal locations and size of the capacitors in radial distribution system to reduce power losses and improve voltage profile. Reduction in power loss enhances energy efficiency in distribution system also releases feeder capacity. Distribution system has combination of different type of loads (Industrial, commercial and Residential). Load models have significant impact on selecting capacitor size for better deployment of reactive power support. The main contribution of the paper is: (i) Capacitor allocation for radial distribution network using sensitivity approach, (ii) capacitor allocation and sizes calculation for radial distribution system with load growth and winter load variations, (iii) comparison of the results obtained with single and multi-capacitors placement with load growth and load variations, (iv) The loss savings and overall cost savings per annum with capacitors placement. In this paper we considered the impact of time varying load flow with realistic load model. The load growth factor is considered in the study which is essential for the planning and expansion of the existing systems. The impact of the realistic load model as ZIP load model has been considered for study of the systems. The results have been obtained for the distribution network of UK Distribution Corporation consisting of 38 buses. [ABSTRACT FROM AUTHOR]

This paper proposes a mathematical model and a computational approach applied to the study of the interaction between a moving platform and pedestrians walking on it. A ship deck motion used as a basic scenario for simulation is realized in three modes reproducing heaving, pitching or rolling rotations of the vessel. Behavior of virtual passengers is emulated by the Social Force pedestrian model modified with additional forces. In this paper the mathematical definitions of both models and their software implementations are discussed. The results of the experiments reproducing various combinations of characteristics of the ship motion are presented and compared with a case where it remained stationary. The paper is concluded with an analysis of the simulation results and perspectives for further research. [ABSTRACT FROM AUTHOR]

This paper discusses the general concept of Bayesian Network classifier and the optimisation of a predictive spatial model using Naive Bayes (NB) on secondary mineral deposit data. A different NB modelling approaches to mineral distribution data was used to predict the occurrence of a particular mineral deposit in a given area, which include; predictive attributes sub-selection, normalised attributes selection, NB dependent attributes and the strictness to NB model assumptions of attributes independence selection. The performance of the model was determined by selecting a model with the best predictive accuracy. The NB classifier that violates assumptions of attributes independence was used to compare with other forms of NB. The aim is to improve the general performance of the model through the best selection of predictive attribute data. The paper elaborates the workings of a Bayesian Network learning model, the concept of NB and its application to predicting mineral deposit potentials. The result of the optimised NB model based on predictive accuracies and the Receivr Operating Characteristics (ROC) value is also determined. [ABSTRACT FROM AUTHOR]

Non-Von Neumann computational architectures have lately aroused significant interest as substrates for complex computation. One recent development in this domain is the Polychronous Wavefront Computing (PWC) computational model based on multiple wavefront dynamics. This model is an abstraction and simplification of the artificial neural network paradigm based on temporal and spatial patterns of activity in a pulse propagating media and their interaction with transponders. While this framework is capable of computing basic logical functions and exhibiting interesting dynamic behaviors, methods for unsupervised training of the framework have not been identified. The lack of input weights and the spatio-temporal nature of the PWC framework make direct application of weight adjusting learning methods (e.g., backpropagation) impractical. The paper will describe research into unsupervised learning for PWCs inspired by Spike-Timing-Dependent Plasticity (STDP) methods used with other types of polychronous models. The method is based on adding Leaky Integrate-and-Fire semantics to the PWC framework allowing analysis of activating wavefronts and determination of the optimal location for future stimulation. The transponder's location is then incrementally adjusted to improve its future response. The paper will discuss the learning approach and examine the results of applying the method over a series of stimulations to sample configurations. [ABSTRACT FROM AUTHOR]

This paper discusses the viability of using Bayesian Network (BN) models to support qualification planning in order to predict the suitability of Six Degrees of Freedom (6DOF) vibration testing for qualification. Qualification includes environmental testing such as temperature, vibration, and shock to support a stochastic argument about the suitability of a design. Qualification is becoming more complex and restricted yet available new technologies are not fully utilized. Technology has advanced to the state where 6DOF vibration shakers and control systems capable of high frequency tests are possible, but the problem using these systems is far more complex than traditional single degree of freedom (SDOF) tests. This challenges systems engineers as they strive to plan qualification in an environment where technical, environmental, and political constraints are coupled with the traditional cost, risk and schedule constraints. New technologies are also available for systems engineers to combine technical understanding with cost, risk and schedule factors to aid in decision making for complex problems such as qualification planning. BN models may provide the framework to aid Systems Engineers in planning qualification efforts with complex constraints. This paper discusses related work, the current approach and results of this research. [ABSTRACT FROM AUTHOR]

There is a current need for Unmanned Aerial Vehicle (UAV) systems architecture generation and assessment models. Architecture assessment models that presently exist tend to be fractional and do not account for all dynamic attributes that should be considered in the architecture assessment. There are infinite possibilities of architecture assessment modeling methods that can be used to assess conceptual systems architecture. Developing a good architecture assessment model for evaluating the functional and systems architecture reduces system ambiguity while increasing the tangibility of the system. This paper will present an assessment model specifically for UAV systems and this model can also be adapted to virtually any type of complex adaptive system. On new complex UAV systems it is essential evaluate the appropriate Level of Autonomy (LOA) required to satisfy customer and mission requirements. The assessment model detailed in this paper combines known design heuristics with quantitative, qualitative, and visual representations that assess the probability that the generated architecture will meet performance and capability requirements. The architecture assessment model will assess and generate a combined score that will indicate if the architecture is acceptable or unacceptable. Future UAV systems may reach a LOA that would be considered as Artificial Intelligence (AI); and this pursuit will increase the need for advanced LOA architecture modeling and assessment. [ABSTRACT FROM AUTHOR]