Hasil untuk "Cybernetics"

Harry G. Johnson, N. Wiener

N. Wiener

I. Grondman, L. Buşoniu, G. D. Lopes et al.

Katherine Hayles

K. Narayanan, D. O’Leary, A. Rosenfeld

V.V. Kotlyar, E.G. Abramochkin, A.A. Kovalev et al.

The optical vortices with the complex amplitude which is presented by the product of the Gaussian function and two Bessel functions with a complex root dependence of the arguments on the cylindrical coordinates and a constant parameter that determines the type of intensity distribution. These beams can be named Bessel-Bessel-Gaussian beams (BBG beams). An explicit expression for the complex amplitude of such beams at any distance from the waist is presented. We have demonstrated that BBG beams have an anomalously high rotation speed: the intensity rotates by almost 45 degrees at a distance much smaller than the Rayleigh length. It is shown that the parameter allow to control the topological charge of the BBG beam. The topological charge increases in jumps by an even number with an increase in the positive value of the parameter.

Fidanova Stefka

Sensor networks are widely used nowadays. They can be used with various applications, such as monitoring, tracking, communication, and many more. The positioning of the sensors in the network is of great importance. It should enable full coverage, communication between sensors, and transmission of collected data. On the other hand, it is important to do this with as few sensors as possible. When the network is used for monitoring, it is important to consider the presence of impenetrable obstacles. They cover part of the coverage area of some of the sensors. This requires a different positioning of the sensors compared to the case without obstacles. For the solution, we propose an algorithm based on Ant Colony Optimization (ACO) methodology. We have shown how the algorithm works, when there are impenetrable obstacles in the observed space. Using the obstacles, areas of arbitrary shape can be modeled.

Muhammad Faisal Yaqoob, Christian Gollee, Christer-Clifford Schenke et al.

The application of robotics has evolved significantly through every industry. Robots do provide a wide range of motion, however their advantage of having lightweight components also limit the rigidity of the tool center point. Compensatory techniques involving joint stiffness determination and model-based predictions is one potential approach while another modern solution is the usage of precision gears. Higher rigidity and lower backlash found in precision gears as compared to conventional gears enable increased accuracy when carrying out production processes with industrial robots. A study at Fraunhofer IWU confirmed this by examining the impact of precision gear on a six-axis robot's accuracy during a milling process. Replacing all gears with precision gear technology or building new robots with them will certainly increase process accuracy. However, with over a half million robots already installed worldwide, there is a definite need to streamline the gear selection while enhancing the accuracy of existing robots with minimal effort and cost. This paper presents a proof of concept to develop a gear selection tool which utilizes robot’s MBS (multibody simulation) model involving gear parameters and process requirements to simplify gear selection for industrial processes. This tool aims to address the question “Which gear(s) needs to be replaced/installed in a robot to achieve the required/improved movement accuracy for an existing or new process?”

Fatemeh Arvaneh, Faraneh Zarafshan, Abbas Karimi

This study investigates the application of heuristic and meta-heuristic algorithms to address resource allocation challenges in Internet of Things (IoT) applications within fog computing environments. The primary advantage of these algorithms lies in their ability to optimize functions without the need for stringent restrictions, allowing adaptability to various linear, nonlinear, continuous, or discrete problems. Through the implementation and comparison of the Cheetah algorithm, Gray Wolf algorithm, Particle Swarm-Gravitational Search algorithm, and Gray Wolf-Cuckoo Search algorithm using MATLAB software in a simulation environment, the study aims to minimize criterion function and total time and energy consumption for IoT applications. Preliminary results indicate that the statistical average performance of the Cheetah algorithm surpasses that of the Gray Wolf algorithm, the combined Particle Swarm-Gravitational Search algorithm, and the Gray Wolf-Cuckoo Search algorithm. This suggests the efficacy of the Cheetah algorithm in IoT resource allocation optimization within fog computing environments. The study provides insights into the comparative performance of these algorithms, laying the foundation for further exploration into enhancing resource allocation strategies in the dynamic and resource-constrained IoT and fog computing landscapes.

Olszewski Adam

The main purpose of this paper, which takes the form of an essay, is an attempt to answer the question of the limits of artificial intelligence (AI). In the introductory section, we present the key milestones in AI development, both historical and future projections, in which two terms – Artificial Human (AH) and Artificial ‘god’ (AG) – play a special role. In the second section, we clarify the question of the limits of AI by indicating the hypothetical goal of AI development. The third section develops the argument proposed by C. F. Weizsäcker, originally formulated for cybernetics. The conclusion of this argument is optimistic about limitations to the possibilities of cybernetic simulations. We apply this argument to AI and subject it to a critique which ultimately undermines the legitimacy of its conclusion. We base the critique on two well-known results: the theorem of the unsolvability of the halting problem and Gödel’s first incompleteness theorem, and we formulate two objections interpreted without adopting Church’s thesis. In the crucial fourth section, we present a third objection in the form of a hypothesis for which we argue that AI (AH), understood as a subject, will always be solipsistic.

Mostafa Amini, Mohammad Hassanzadeh, Mostafa Morshedi

Objectives: The purpose of this research was to improve the five steps of Schallmo's methodology for digital transformation of business models, using Schumacher’s digital maturity assessment model, three approaches to business model transformation based on Heikkilä's recommendations and to improve digital innovation approach. The business model changes are based on Stampfl’s recommendations. Methods: This research has a combined methodology which consists of a validity review study method and action research method in a manufacturing SME. This improved methodology has been used in strategic planning for the digital transformation of the business model of one of Iran's manufacturing companies. Results: After reviewing the various documents of the Schallmo’s five-step framework, it was improved by Schumacher's maturity model for industry 4.0, approaches of business model transformation recommended by Heikkilä et al. and various types of business model innovation as described by Stampfl. Then the improved framework was used to map the target state of company's digital transformation. Conclusions: Since the proposed model of this research, in addition to improving the Schallmo model, has been implemented in a real company, so it seems that it can be used by Digital transformation planning and digital operating models as well as change managers and consultants.

Augusto Gonzalez, Frank Quintela, Dario A. Leon et al.

The topology of gene expression space for a set of 12 cancer types is studied by means of an entropy-like magnitude, which measures the volumes of the regions occupied by tumor and normal samples, i.e., the number of available states (genotypes) that can be classified as tumor-like or normal-like, respectively. Computations show that the number of available states is much greater for tumors than for normal tissues, suggesting the irreversibility of the progression to the tumor phase. The entropy is nearly constant for tumors, whereas it exhibits a higher variability in normal tissues, probably due to tissue differentiation. In addition, we show an interesting correlation between the fraction (tumor/normal) of available states and the overlap between the tumor and normal sample clouds, interpreted as a way of reducing the decay rate to the tumor phase in more ordered or structured tissues.

Marcel Fajkus, Jan Nedoma, Radek Martinek et al.

The publication focus on a pilot study (design, implementation and verification) of a dynamic weighing system designed for weighing of municipal waste during the dumping of garbage containers. The presented solution is based on fiber Bragg gratings (FBG) and can be additionally implemented into the lifting equipment of commonly employed garbage trucks. The weighing principle is based on the measurement of deformation effect and vibration response of the lifting equipment during the dumping of garbage bins. The measuring system leverages the advantages of power measurement, which use the conversion of the spectral shift of modulated light signal during the measurement to the change in optical power of a pair of spectral overlapping Bragg gratings. Two different methods are presented and discussed: the amplitude method, which analyze the maximum amplitude change of the signal and/or the method, which analyze the time period of the dampened oscillation of the lifting device. Due to the small dimensions, the complete system can be installed together with FBG sensors directly onto the lifting device. The pilot tests of the presented system were carried out for over 4 months, showing an accuracy of up to ±4.04 kg in the range of 10–100 kg for standardized containers used for municipal waste. The system worked in completely standalone mode and the garbage trucks were not modified in any inconvenient way.

Sergey N. Smirnov, Andrey Yu. Zanochkin

For the superreplication problem with discrete time, a guaranteed deterministic formulation is considered: the problem is to guarantee coverage of the contingent liability on sold option under all admissible scenarios. These scenarios are defined by means of a priori defined compacts dependent on price prehistory: the price increments at each point in time must lie in the corresponding compacts. In a general case, we consider a market with trading constraints and assume the absence of transaction costs. The formulation of the problem is game theoretic and leads to the Bellman–Isaacs equations. This paper analyses the solution to these equations for a specific pricing problem, i.e., for a binary option of the European type, within a multiplicative market model, with no trading constraints. A number of solution properties and an algorithm for the numerical solution of the Bellman equations are derived. The interest in this problem, from a mathematical prospective, is related to the discontinuity of the option payoff function.

Victor Ukleev

The hybrid input-output algorithm is a phase retrieval method that provides solution for the phase problem of coherent X-ray diffraction imaging of micro- and nano-objects from the diffraction pattern alone without using any focusing optics. In this paper, we have studied a tolerance of this algorithm to missing information at the center of the diffraction pattern, which is a frequent problem in problems of small-angle scattering. We considered the particular problem of the stability of the algorithm in the case of scattering from an ordered structure and provided a qualitative and quantitative description of the degradation of image reconstruction with an increase in the amount of missing information.

P. Kokol

Fei-Yue Wang, Dimitar Filev, W. Pedrycz et al.

Inspired by the idealism embodied in Russell and Whitehead’s “Principia Mathematica,” Wiener marched along a different and unique path toward sciences of intelligence and behavior which culminated at “Cybernetics: Or Control and Communication in the Animal and the Machine” 70 years ago. Since then, we have witnessed the birth of Cognitive Science, Artificial Intelligence (AI), Computational Intelligence, and many other new research fields and disciplines, all of which have been catalyzed by Cybernetics. The IEEE Systems, Man, AND Cybernetics Society and this Transactions on Cybernetics have become the focal point of the broad cybernetics community by promoting the theory, practice, and interdisciplinary aspects of systems science and engineering, human-machine systems, and cybernetics principles. It is a time of celebration and reflection.

Wonki Lee, DaeEun Kim

This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.

S. Yiannoudes

S. Nielsen