Hasil untuk "Cybernetics"

Dingqi Yang, Daqing Zhang, V. Zheng et al.

R. Birnbaum

Ramin Mousa, Saeed Chamani, Mohammad Morsali et al.

Skin cancer (SC) is a life-threatening disease where early diagnosis is critical for effective treatment and survival. While deep learning (DL) has advanced skin cancer diagnosis (SCD), current methods generally yield suboptimal accuracy and efficiency due to challenges in extracting multiscale features from dermoscopic images and optimizing complex model parameters through efficient exploration of the space of hyperparameters. To address this, we propose an approach integrating late Discrete Wavelet Transform (DWT) with pre-trained convolutional neural networks (CNNs) and swarm-based optimization. The late DWT decomposes CNN-extracted feature maps into low- and high-frequency components to improve the detection of subtle lesion patterns, while a self-attention mechanism further refines this by weighing feature importance, focusing on relevant diagnostic information. To refine hyperparameters, three novel swarm-based optimizers – Modified Gorilla Troops Optimizer (MGTO), Improved Gray Wolf Optimization (IGWO), and Fox Optimization (FOX) – are employed searching the space of the hyperparameters to fine-tune the model for superior performance. In comparison to existing methods, experiments on the ISIC-2016 and ISIC-2017 datasets show enhanced classification performance, obtaining at least a 1% accuracy gain. Thus, the suggested framework offers a reliable and effective way to diagnose skin cancer automatically.

Vladyslav Yavtukhovskyi, Violeta Tretynyk

Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, one of the major pain points when adopting them is the lack of ability to interpret what is the reasoning behind their conclusion. Because of this, various explainable artificial intelligence (XAI) methods have been developed; however, it is unclear if they show reasoning or the same aspects of reasoning of CNNs. In recent years some of the most popular methods, LIME[2], SHAP[3], and Grad-CAM [4], were evaluated using tabular data and it was showed how significantly different results are [5] or some were evaluated on a matter of trustworthiness with human evaluation on medical images [6], there is still a lack of measure of how different these methods are on image classification models. This study uses correlation and a popular segmentation measure, Intersection over Union (IoU) [7], to evaluate their differences. The purpose of the article. The aim of this work is to evaluate the level of differences between SHAP, LIME, and Grad-CAM on an image classification task. Results. In this study, we evaluated the similarity between image explanations generated by SHAP, LIME, and Grad-CAM using two different models trained for specific image classification tasks. The evaluation was performed on two datasets, with one fine tuned and one pre-trained model. The datasets were the CBIS-DDSM breast cancer dataset with fine tuned ResNet-18 model, and the Imagenet Object Classification Challenge (IOCC) with a VGG-16 pre-trained model. Our analysis revealed that while all of the methods aim to approximate feature importance, their outputs significantly differ, which makes it difficult to define the true reasoning of the model. Quantitative similarity metrics confirmed that these methods were most often independent, with less than half overlap on average. To add to that, metrics were also significantly different depending on the dataset or the model. The definition of what should be the ground truth or has the best practical use for these methods is complicated, as research contains both numerous variations of fidelity metrics and significantly varies in human-based evaluation perspectives. Future work can include evaluation of the impact of method parameters on the overlap, further investigation on the impact of the dataset and the selected model on the similarity, or quantitative comparison of the models with human-based metrics, such as comparing saliency maps with segmentation masks.

Loredana Caruccio, Stefano Cirillo, Giuseppe Polese et al.

In the last year, Large Language Models (LLMs) have transformed the way of tackling problems, opening up new perspectives in various works and research fields, due to their ability to generate and understand human languages. In this regard, the recent release of Claude 2.0 has contributed to the processing of more complex prompts. In this scenario, the goal of this paper is to evaluate the effectiveness of Claude 2.0 in a specific classification task. In particular, we considered the Forest cover-type problem, concerning the prediction of a cover-type value according to the geospatial characterization of target worldwide areas. To this end, we propose a novel iterative prompt template engineering approach, which integrates files by exploiting prompts and evaluates the quality of responses provided by the LLM. Moreover, we conducted several comparative analyses to evaluate the effectiveness of Claude 2.0 with respect to online and batch learning models. The results demonstrated that, although some online and batch models performed better than Claude 2.0, the new iterative prompt engineering approach improved the quality of responses, leading to better performance with increases ranging from 14% to 32% in terms of accuracy, precision, recall, and F1-score.

A. Androon, O. V. Tikhonova

Objectives. The work sets out to evaluate the noise immunity of the signal modulation method in 5G networks using a filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) and to analyze the bit error rate (BER).Methods. In the work, probability theory and mathematical statistics methods are applied according to computer modeling approaches.Results. An analysis of BER for the signal modulation method in 5G networks, which uses a bank of filters with multiple carriers with offset quadrature amplitude modulation under noise conditions, is presented. The resistance of the method to intra-cell, inter-cell, and inter-beam types of interference in the 5G channel, as well as additive white Gaussian noise, is investigated. The graphical and numerical data obtained through computer modeling demonstrates improved BER in 5G networks using FBMC-OQAM. The presented comparative analysis of error probability in the FBMC-OQAM system under various types of noise and interference emphasizes the impact of these factors on the quality of information transmission.Conclusions. The FBMC-OQAM method is characterized by the low impact on the error probability of the data transmission system in 5G networks of various types of interference including intra-cell and inter-cell interference, inter-beam interference, and nonlinear distortions. However, it will be necessary to further optimize the method and develop algorithms for enhancing error probability in the FBMC-OQAM system under real conditions in 5G networks. The research results can be used in the development of 5G networks.

Тураева Н.М.

В данной статье рассматривается математическая модель цифровой системы автоматического сопровождения цели по дальности, которая, в отличие от существующих, удовлетворяет по всем требованиям устойчивости и качеству системы измерения дальности и автоматического сопровождения цели. Также в статье показана структурная схема и построена математическая модель преобразователя «код-временная задержка», которая исследована на устойчивость и качество, определены допустимые области параметров цифрового управляющего устройства, обеспечивающие устойчивость работы построенной математической модели. Определены допустимые области параметров алгоритма работы цифрового управляющего устройства, при которых система автоматического сопровождения дальности соответствует своему предназначению.

Hamzeh Ali Islaminasab, Hamid Moridian

SUBJECT & OBJECTIVES: The emergent spiritualities have a special and new look at man and his relationship with the Almighty God, leading to humanism in some cases. Deepak Chopra believes man has a lot of ability due to his mind and he can know God without the need for divine religions. He can also behave like God and participate in the creation of the Universe with the Almighty God and control the material world and the universe. On the other hand, Mulla Sadra considers all human abilities to be related to his Nafs (soul), which can possess abilities and dominate existence if connected to God Almighty.METHOD & FINDING: This article is a critical research answering the question of what the position of humans in the universe is. The findings of the research show that Chopra imagined that divine religions were created to nurture and develop human abilities, especially the physical type; While the purpose of divine religions is the spiritual evolution of man.CONCLUSION: Using the qualitative method in the analysis of Chopra's writings based on Mulla Sadra's views, we can draw the following conclusion: Although man is composed of two domains, Nafs (soul) and the body, his most important domain is his soul, for which, although man has abilities, his abilities are due to his connection to the Almighty God.

Alexander L. Fradkov, A. Shepeljavyi

In the article the history of cybernetics and artificial intelligence in the world and, particularly in the USSR is outlined starting from the 1940s-1950s. The rapid development of these areas in the 1960s is described in more detail. Special attention is paid to the results of Leningrad (St. Petersburg) researchers, particularly to the work of Vladimir Yakubovich and his scientific school on machine learning, pattern recognition, adaptive systems, intelligent robots and their importance for the further development of cybernetics and artificial intelligence.

Matteo Capucci, Bruno Gavranovi'c, Jules Hedges et al.

We propose a categorical framework for processes which interact bidirectionally with both an environment and a 'controller'. Examples include open learners, in which the controller is an optimiser such as gradient descent, and an approach to compositional game theory closely related to open games, in which the controller is a composite of game-theoretic agents. We believe that 'cybernetic' is an appropriate name for the processes that can be described in this framework.

V. Liagkou, C. Stylios, Lamprini Pappa et al.

Industry 4.0 has risen as an integrated digital manufacturing environment, and it has created a novel research perspective that has thrust research to interdisciplinarity and exploitation of ICT advances. This work presents and discusses the main aspects of Industry 4.0 and how intelligence can be embedded in manufacturing to create the smart factory. It briefly describes the main components of Industry 4.0, and it focuses on the security challenges that the fully interconnected ecosystem of Industry 4.0 has to meet and the threats for each component. Preserving security has a crucial role in Industry 4.0, and it is vital for its existence, so the main research directions on how to ensure the confidentiality and integrity of the information shared among the Industry 4.0 components are presented. Another view is in light of the security issues that come as a result of enabling new technologies.

Aleksandr V. Bolodurin, Andrey A. Altuhov

The issue of protecting the firmware and the memory area for storing variables (NVRAM - Non Volatile Random Access Memory) of the UEFI (Unified Extensible Firmware Interface) system are discussed in the paper. The research methodology is a deduction. The problem of trusted computer loading, in particular, the proprietarity of the UEFI stage, is relevant in the field of computer security. For an introduction to the context and subject field, the components and environment of the UEFI system, attack vectors on the system, the consequences of successful attacks for the user and built-in security tools are briefly described. The advantages and disadvantages of using two memory areas with different access modes as a way to protect critical UEFI system data are considered. As a memory area with a configurable access policy, it is proposed to use the hardware implementation of the resident security component (HRSC). Finally, the functionality of the HRSC and the applicability of this solution for ensuring the security of the UEFI system are considered. As a result, the justification of the applicability of the HRSC as a tool for differentiating access to critical parts of UEFI firmware and NVRAM was obtained. In addition, the advantages of using the HRSC as a memory area with a configurable access policy are identified. In particular those are the ease of implementation, variability of access differentiation and platform independence from the model and architecture of a computer with UEFI.

Asma ul Husna, Shamshad Ahmad

With the development of knowledge as economy, knowledge become the asset for the organizations. In this context, it is very essential organizational strategy to cop up with environmental changes. order to survive and compete effectively in the global environment. Research purpose of the study is to examine the relationship between knowledge management and job satisfaction among the university librarians of the Punjab, Pakistan. For data collection process survey research method was used. On the basis of literature review, a questionnaire was designed for data collection. The analyzed data showed a good relationship of the research main constructs between satisfaction of librarians’ jobs and different aspects of knowledge management. It was evaluated that there was a good relation of knowledge acquisition and knowledge sharing with job satisfaction. There is positive impact of knowledge management process on an organization and help improve efficiency and effectiveness. Beside this, job satisfaction is a important aspect for organizational success. It plays a significant role in achieving the organizational goals. The study concluded that both job satisfaction and KM draw a significant task in increasing the services availability, efficiency, effectiveness, productivity and performance of the professionals. Academic libraries and other organizations can use the findings of this study to improve their practices. This might help to increase innovation, productivity, opportunity and competitive advantages.

E. Tunstel, M. Cobo, E. Herrera-Viedma et al.

To commemorate the 50th anniversary of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, this article examines and reports on its past to current topical coverage of systems science and engineering toward exploring the evolving focus of the research community. Results of a systematic bibliometric analysis are presented with associated conclusions, implications, and summary of topical areas. In addition, respective views regarding the current state of the field and where it is headed are offered by recent leaders of the IEEE Systems, Man, and Cybernetics Society, including its continued relevance and role in the advancement of systems technology.

M. Yolles

Metacybernetics refers to the higher cybernetic orders that arise in living system agencies. Agencies are complex, and for them to be viable and hence survive, they require both stability and uncertainty reduction. Metacybernetics is defined through a metasystem hierarchy, and is mostly known through 1st and 2nd order cybernetics. In this exploratory paper the purpose is to create a framework that can underpin metacybernetics and explain the relationship between different cybernetic orders. The framework is built on agency theory which has both substructural and superstructural dimensions. Substructure has an interest in stability, is concerned with the generation of higher cybernetic orders, and is serviced by horizontal recursion. Superstructure is concerned with uncertainty reduction by uncovering hidden material or regulatory relationships, and is serviced by vertical recursion. Philosophical aspects to the framework are discussed, making distinction between global rationality through critical realism, and local rationality that relates to different cybernetic orders that correspond to bounding paradigms like positivism and constructivism.

B. Scott

This publication meets a long-felt need to show the relevance of cybernetics for the social sciences (including psychology, sociology, and anthropology). User-friendly descriptions of the core concepts of cybernetics are provided, with examples of how they can be used in the social sciences. It is explained how cybernetics functions as a transdiscipline that unifies other disciplines and a metadiscipline that provides insights about how other disciplines function. An account of how cybernetics emerged as a distinct field is provided, following interdisciplinary meetings in the 1940s, convened to explore feedback and circular causality in biological and social systems. How encountering cybernetics transformed the author’s thinking and his understanding of life in general, is also recounted.

Shantanu Tilak, M. Glassman, I. Kuznetcova et al.

This article outlines links between cybernetics and psychology through the black box metaphor using a tripartite narrative. The first part explores first-order cybernetic approaches to opening the black box. These developments run parallel to the decline of radical behaviorism and advancements in information processing theory and neuropsychology. We then describe how cybernetics migrates towards a second-order approach (expanding and questioning features of first-order inquiry), understanding applications of rule-based tools to sociocultural phenomena and dynamic mental models, inspiring radical constructivism, and also accepting social constructivism. Psychology, however, enters the cognitive revolution, adhering to the computer metaphor of first-order cyberneticians to streamline human consciousness. The article concludes by outlining how second-order cybernetic approaches emerging in the 1990s may provide cues to psychologists to adopt mixed methods, and bioecological models in the information age, uniting understandings of observable human activity, inner perceptions, and physiological processes across contexts to understand consciousness.

Vincent August

Network concepts are omnipresent in contemporary diagnoses (network society), management practices (network governance), social science methods (network analysis) and theories (network theory). Instigating a critical analysis of network concepts, this article explores the sources and relevance of networks in Foucault’s social theory. I argue that via Foucault we can trace network concepts back to cybernetics, a research programme that initiated a shift from ‘being’ to ‘doing’ and developed a new theory of regulation based on connectivity and codes, communication and circulation. This insight contributes to two debates: Firstly, it highlights a neglected influence on Foucault’s theory that travelled from cybernetics via structuralism and Canguilhem into his concept of power. Secondly, it suggests that network society and governance are neither a product of neoliberalism nor of technological artefacts, such as the Internet. They rather resulted from a distinct tradition of cybernetically inspired theories and practices.

Yanbo Huang, Qin Zhang

Yingxu Wang, W. Kinsner, S. Kwong et al.

Brain-inspired cognitive systems (BCSs) are an emerging field of cybernetics, cognitive science, and system science. BCSs study not only the intelligence science foundations of artificial intelligence (AI) and cognitive systems, but also formal models of the brain embodied by computational intelligence. This article presents the brain and intelligence science foundations of BCS toward hybrid intelligent systems and the symbiotic intelligence of humanity. It explores the transdisciplinary theoretical foundations of system, brain, intelligence, knowledge, cybernetic, and cognitive sciences toward the next generation of knowledge processors beyond classic data processors for autonomous computing systems. A BCS provides an overarching platform for cognitive cybernetics, humanity, and systems to enable emerging hybrid societies shared by humans and intelligent machines.