Hasil untuk "Cybernetics"

Soumyadeep Ray, Pronaya Bhattacharya, Ebrahim A. Mattar et al.

This survey examines the convergence of Explainable Artificial Intelligence (XAI) and Quantum Computing (QC) toward precision medicine. We review developments from 2018 to 2025, summarizing quantum algorithms, quantum-machine-learning models and XAI techniques applied to drug discovery, disease diagnosis, patient monitoring and biomarker identification. We introduce a taxonomy of hybrid and quantum-explainable approaches, evaluate NISQ hardware and encoding constraints, and compare interpretability methods (SHAP, LIME, QSHAP, QLRP, TSBA). Two case studies (doxorubicin cardiotoxicity prediction and pre-symptomatic IBD flare forecasting) demonstrate hybrid variational-quantum pipelines wrapped with SHAP-based explanations. We identify practical barriers (noise, data encoding, regulation, privacy) and outline research directions to benchmark clinical quantum advantage and develop scalable, transparent QXAI frameworks. The survey aims to guide interdisciplinary efforts toward trustworthy, scalable quantum-enabled precision healthcare.

Joachim Wallisch, Markus Lindner, Øyvind Wiig Petersen et al.

Electrothermal de-icing systems are a popular approach to protect unmanned aerial vehicles (UAVs) from the performance degradation caused by in-cloud icing. However, their power and energy requirements must be minimized to make these systems viable for small and medium-sized fixed-wing UAVs. Thermal de-icing systems allow intercycle ice accretions and can result in runback icing. Intercycle and runback ice increase the aircraft’s drag, requiring more engine thrust and energy. This study investigates the aerodynamic influence of intercycle and runback ice on a typical UAV wing. Lift and drag coefficients from a wind tunnel campaign and Ansys FENSAP-ICE simulations are compared. Intercycle ice shapes result in a drag increase of approx. 50% for a realistic cruise angle of attack. While dispersed runback ice increases the drag by 30% compared to the clean wing, a spanwise ice ridge can increase the drag by more than 170%. The results highlight that runback ice can significantly influence the drag coefficient. Therefore, it is important to design the de-icing system and its operation sequence to minimize runback ice. Understanding the need to minimize runback ice helps in designing viable de-icing systems for UAVs.

Anna S. Kolosova, Anna S. Kameneva, Georgii G. Chukov et al.

The major algorithms and methods of machine learning are considered. A possibility of machine learning and neural network using for electronic equipment quality prediction is assessed. The paper provides examples of the successful application of these algorithms to improve such quality of electronic components indicators as reliability, resistance to external influencing factors, etc. Before testing electronic components on resistance to external influencing factors it is necessary to identify samples of electronic components by fluoroscopy in order to identify possible heterogeneity in the structure of samples belonging to the same batch. A solution of the electronic components batches uniformity problem using computer vision and clustering algorithms is proposed.

Malihe Sabeti, Reza Boostani, Ehsan Moradi et al.

Early closure of cranial vault sutures, defined as craniosynostosis is a relatively common condition with somehow specific head and face abnormality for each subtype. Early diagnosis results in a better prognosis but pediatricians and primary care providers are not so familiar with these abnormalities while taking 3D CT scan of skull, predisposes the growing brain to harmful effects of radiation. Thus, developing a user-friendly and accurate diagnostic system would be helpful. This study aimed to diagnose simple suture synostosis by using machine learning based methods in digital photographs of child head. Digital photos of 145 craniosynostosis infants, operated in Mofid children hospital (Tehran, Iran) are used in this study. Head border is identified by GrabCut algorithm segmentation method and then several anthropometric indices such as cranial index (CI), cranial vault asymmetry index (CVAI), anterior–midline width ratio (AMWR) and anterior–posterior​ width ratio (APWR) and left–right height ratio (LRHR) are calculated. Moreover, statistical pattern matching indices (Chi-square (CS), Hu moment invariants (HuMI), absolute difference of white pixels probability (AbsDifWPP) and pixel intensity (PI)) are calculated and compared to anthropometric indices. The classification results for statistical pattern matching indices varied in the range of 85%–92% which is statistically higher than hand crafted indices. Our proposed approach could diagnose and classify common subtypes of single suture craniosynostosis and could help pediatricians and parents in early diagnosis and follow-up of this disorder.

Alexander Yu. Nikiforov

R. Goodspeed

Ekaterini Nikolarea

In this study the author will present how Human Intelligence (HI – nous), in co-operation with Artificial Intelligence (AI) – Internet can communicate his/her knowledge and interdisciplinary research to an international context (i.e., Erasmus exchange programs and/or international conferences). Having over a twenty-year experience of teaching ESP/EAP at a non-English University and over a twenty-five-year experience of editing research papers in English, the writer will present how a nous/student/researcher and an academic can use to his/her advantage IT tools, such as electronic dictionaries and forums. Finally, the author of this study will propose: (a) a couple of methods, which can be applied through AI (i.e., Google or any other search engines) so that the non-English nous/student/researcher/academic (a nous) will be certain that s/he communicates "correctly" and "appropriately" his/her research in an international context whose primary language of communication is English; and (b) a specific bilingual (or multilingual) knowledge management tool (i.e. an electronic TDB: Terminological Data Bank).

V. N. Isakov, V. S. Lankina

The article is devoted to the issues of numerical calculation of the characteristics of the electromagnetic field of radiating apertures. Тhe radiating aperture is a universal electrodynamic model used in the analysis of a special class of antennas, in particular, mirror and horn antennas, in the study of diffraction phenomena, in the planning of radio wave propagation paths, and when solving problems of wireless transmission of electric energy at a distance. The structure of the electromagnetic field of a radiating aperture in the intermediate and far zones is of the greatest interest according to the needs of practice. However, the theoretical solutions of these problems are usually difficult to obtain, except for some special cases related to the far zone. This leads to the development of appropriate computational models. This paper is aimed at generalization and systematization of experience in developing software for the simulation of electromagnetic field characteristics of radiating apertures in the intermediate and far zones. This paper considers an approach to developing a computational model of a radiating aperture that may be used to calculate the characteristics of electromagnetic field in the intermediate and far zones. Examples of results obtained for circular and ring apertures describing the structure of their electromagnetic field are given. Examples of flight diagrams of a circular aperture are given. The effect of “searchlight” localization of the electromagnetic field in the intermediate zone of a circular emitting aperture is demonstrated. The effect of mutual compensation of neighbouring Fresnel zones using the circular emitting aperture model is demonstrated. A program was developed for calculating the characteristics of the electromagnetic field of radiating holes in the intermediate and far zones. The results can also be used as illustration material for teaching the academic disciplines “Electrodynamics and radio wave propagation” and “Microwave devices and antennas”.

R. Kline

Jocelyn Chapman

Cyberneticians are an eclectic group, connected by their affinity for a way of seeing and knowing that is unfamiliar to most people—namely, one based on “the circularity of observing and communicating” (Von Foerster, 2003b, p. 289). For those unversed in cybernetics, the term itself can seem cryptic. The range of definitions—most rather enigmatic—probably contributes to the obscurity of cybernetics today. At the same time, the definitions can be part of the allure of cybernetics. For example, Klaus Krippendorff (2008) proposed this enticing definition of cybernetics: “an inter-disciplinary discourse that brings forth radically reflexive realities” (p. 183). Thomas Rid (2016) commented that “the word [cybernetics] refuses to be either noun or prefix. Its meaning is equally evasive, hazy and uncertain,” and yet, “whatever it is, it is always stirring, it is always about the future, and it always has been” (p. xi). One way to learn more about how stirring cybernetics is, and how it might relate to the future, is through life stories of cyberneticians. I have invited these authors to share their story regarding cybernetics so we might learn how they discovered cybernetics, how that discovery has influenced their work and lives, and what excites them about cybernetics. From these authors, we gain a greater sense of the richness and versatility of cybernetics as an approach to transdisciplinary inquiry. I believe “inquiring minds” is a trait that connects cyberneticians. Ranulph Glanville (2013) implied this when ruminating on the differences between cybernetics and systems thinkers: “Cybernetics seems to be more general, more philosophical, and more abstract than systems theory, which seems full of subdivisions, more pragmatic and more ‘real world.’ Perhaps cyberneticians are fascinated by questions whereas systemists like answers” (p. 47). An extreme example of cyberneticians’ high valuing of questions is found in Paul Pangaro’s (2016) recent discussion of his “deep interest in creating a better-question engine” (p. 17) that could generate questions and then rank them for presentation to humans who would ultimately do the question selecting. For the love of good questions! Indeed, the personal narratives of these authors show an appreciation for interesting questions and transdisciplinary inquiry.

Bruce Clarke

At mid-career as a tenured professor of modern literature, I finally found cybernetics. It was a slow-rolling revelation, a protracted unraveling, for it took me quite a while to unwrap cybernetics’ conceptual core from out of the layers of adjacent or covering discourses that had obscured or forgotten their own origins in the fecundity of cybernetic ideas. Heinz von Foerster’s relation to the Whole Earth Catalog and the systems counterculture around CoEvolution Quarterly were instrumental for my subsequent cybernetic development toward the work of Maturana, Varela, and Luhmann on the one hand, and Lovelock and Margulis on the other.

Tai Hoang, Huy Le, Tho Quan

Aspect-based Opinion Summary (AOS), consisting of aspect discovery and sentiment classification steps, has recently been emerging as one of the most crucial data mining tasks in e-commerce systems. Along this direction, the LDA-based model is considered as a notably suitable approach, since this model offers both topic modeling and sentiment classification. However, unlike traditional topic modeling, in the context of aspect discovery, it is often required some initial seed words, whose prior knowledge is not easy to be incorporated into LDA models. Moreover, LDA approaches rely on sampling methods, which need to load the whole corpus into memory, making them hardly scalable. In this research, we study an alternative approach for AOS problem, based on Autoencoding Variational Inference (AVI). Firstly, we introduce the Autoencoding Variational Inference for Aspect Discovery (AVIAD) model, which extends the previous work of Autoencoding Variational Inference for Topic Models (AVITM) to embed prior knowledge of seed words. This work includes enhancement of the previous AVI architecture and also modification of the loss function. Ultimately, we present the Autoencoding Variational Inference for Joint Sentiment/Topic (AVIJST) model. In this model, we substantially extend the AVI model to support the JST model, which performs topic modeling for corresponding sentiment. The experimental results show that our proposed models enjoy higher topic coherent, faster convergence time and better accuracy on sentiment classification, as compared to their LDA-based counterparts.

Tommy Kubica, Tenshi Hara, Iris Braun et al.

Education in schools and universities suffers from different problems like the lack of interaction between the lecturer and the students as well as the fear of asking irrelevant questions or providing wrong answers in front of a large audience. A lot of systems exist that try to solve these issues by means of technical tools; e.g., audience response systems. Each of these individual systems supports different functional scopes with different didactic purposes in order to support specific use cases. For the lecturer, it is very hard to choose an appropriate system. Besides the functional scope, there are a lot of predefined limitations, such as a given room with technical restrictions or a favorite operating system and presentation software to present the slides. This paper gives an overview of fifty existing systems (with varying degree of detail) and proposes a filter mechanism based on the index card metaphor to select appropriate systems depending on their individual limitations. In order to simplify this selection process for the lecturer, the filter mechanism is implemented in a web-based selection tool.

G. Cecchin, Gerry Lane, W. Ray

V. Lepskiy

In the paper, a philosophical and methodological analysis of the evolution of cybernetics in the context of the development of scientific rationality is carried out. The evolution of cybernetics is represented as a movement from the methodology of “observable systems” (N. Wiener) and to the methodology of “observing systems” (von Foerster) and to the methodology of self-developing reflexive-active environments. Special attention is paid to the formation of a new promising direction for post-non-classical cybernetics of self-developing poly-subject (reflexive-active) environments, which, given the correlation with previous stages of cybernetics development (with classical and non-classical scientific rationality), we define as thirdorder cybernetics. The analysis of the basics of the formation of third-order cybernetics was carried out with consideration of interrelated aspects: philosophical, methodological, theoretical, and methodical. We also provide model of self-developing poly-subject (reflexive-active) environments as well as a system of ontologies, defining the mechanisms of functioning of such self-organizing poly-subject environments and active elements that organize the communication space (natural, artificial intelligence, and combined formations). The ontology system also makes it possible to integrate cybernetics of the first, second, and third order. Some sociohumanitarian trends in the development of cybernetics are considered: from an external observer to a distributed observer; from monodisciplinary to transdisciplinary approaches; from activity approach to subject-activity one, and further to subject-oriented approach; from information to active knowledge; from ethics of goals to ethics of strategic subjects. Potential opportunities for using third-order cybernetics are described, in order to improve the quality of solving a number of important scientific and practical problems of controlling social systems. Information is provided on the directions of approbation of a third-order cybernetics concept for improving state administration, based on a system of distributed situational centers, and there is its approbation at international scientific conferences.

Kushal Anjaria, Arun Mishra

Chang-Shing Lee, Mei-Hui Wang, L. Ko et al.

Machine learning has recently become very popular in cybernetics systems, but it has always been considered an important research area in the computational intelligence field. Nevertheless, when it comes to smart machines, it is not just about methodologies; we also need to consider systems, cybernetics, and sometimes even humans. Rémi Coulom, a freelance developer of Go programs, notes, "Online games are usually played at a faster pace, which favors the computer over humans," and, still, he expects a strong correlation in performance in serious tournament games [1]. This is why Go games were played on site rather than just on the Internet at the special event "Human and Smart Machine Co-Learning" [11], which was held during the IEEE International Conference on Systems, Man, and Cybernetics (SMC) on 5 October 2017 in Banff, Canada.

Sergey Bibikov, Nikolay Kazanskiy, Vladimir Fursov

This paper considers a vegetation type recognition algorithm in which the conjugacy indicator with a subspace spanned by endmember vectors is taken as a proximity measure. We show that with proper data preprocessing, including vector components weighting and class partitioning into subclasses, the proposed method offers a higher recognition quality when compared to a support vector machine (SVM) method implemented in MatLab software. This implementation provides good results with the SVM method for a fairly difficult classification test using the Indian Pines dataset with 16 classes containing similar vegetation types. The difficulty of the test is caused by high correlation between the classes. Thus, the results show a possibility for the recognition of a large variety of vegetation types, including the narcotic plants.

Simov Kiril, Osenova Petya

With the availability of large language data online, cross-linked lexical resources (such as BabelNet, Predicate Matrix and UBY) and semantically annotated corpora (SemCor, OntoNotes, etc.), more and more applications in Natural Language Processing (NLP) have started to exploit various semantic models. The semantic models have been created on the base of LSA, clustering, word embeddings, deep learning, neural networks, etc., and abstract logical forms, such as Minimal Recursion Semantics (MRS) or Abstract Meaning Representation (AMR), etc.

Yasmine Koubaa, Mohamed Boukattaya, Tarak Damak

This article designs a novel adaptive trajectory tracking controller for nonholonomic wheeled mobile robot under kinematic and dynamic uncertainties. A new velocity controller, in which kinematic parameter is estimated, produces velocity command of the robot. The designed adaptive sliding mode dynamic controller incorporates an estimator term to compensate for the external disturbances and dynamic uncertainties and a feedback term to improve the closed-loop stability and account for the estimation error of external disturbances. The system stability is analyzed using Lyapunov theory. Computer simulations affirm the robustness of the designed control scheme.