Hasil untuk "Cybernetics"

Kateryna Chystoforova, Urbano Reviglio

Given the growing complexity of platform governance, the role of experts in digital policy-making processes is becoming more critical. However, there remains a gap in the literature regarding the specific role of experts in shaping platform governance processes. To explore this research gap, this study examines the perspectives of experts involved in the Code of Practice on Disinformation, a co-regulatory governance mechanism established by the European Union. Through a total of 40 semi-structured interviews with disinformation and policy experts, we analyse the perceptions of their role in shaping this process. We found ambivalent opinions on the efficacy of the Code and widespread distrust for platforms, particularly regarding content moderation and data sharing practices. Our analysis also reveals key limitations and challenges involved in platform governance such as systemic resource asymmetries. The article calls for further research on deepening our understanding of the pivotal role experts play in platform governance and content moderation in order to identify strategies for enhancing their impact on digital policymaking.

Martina Srutova, Vaclav Kremen, Lenka Lhotska

Long QT syndrome (LQTS) presents a group of inheritable channelopathies with prolonged ventricular repolarization, leading to syncope, ventricular tachycardia, and sudden death. Differentiating LQTS genotypes is crucial for targeted management and treatment, yet conventional genetic testing remains costly and time-consuming. This study aims to improve the distinction between LQTS genotypes, particularly LQT3, through a novel electrocardiogram (ECG)-based approach. Patients with LQT3 are at elevated risk due to arrhythmia triggers associated with rest and sleep. Employing a database of genotyped long QT syndrome E-HOL-03-0480-013 ECG signals, we introduced two innovative parameterization techniques—area under the ECG curve and wave transformation into the unit circle—to classify LQT3 against LQT1 and LQT2 genotypes. Our methodology utilized single-lead ECG data with a 200 Hz sampling frequency. The support vector machine (SVM) model demonstrated the ability to discriminate LQT3 with a recall of 90% and a precision of 81%, achieving an F1-score of 0.85. This parameterization offers a potential substitute for genetic testing and is practical for low frequencies. These single-lead ECG data could enhance smartwatches’ functionality and similar cardiovascular monitoring applications. The results underscore the viability of ECG morphology-based genotype classification, promising a significant step towards streamlined diagnosis and improved patient care in LQTS.

Naoki Yamada, Takefumi Hiraguri, Tomotaka Kimura et al.

The purpose of this study is to discuss epidemic communication for drones to share information in flight and to develop a wireless system for implementation. Various theoretical studies have been conducted on epidemic communication, but their applications are not clear, so a system that assumes practical use is developed. As the main evaluation items, we analyzed the effect of communication interference between drones on the amount of data transmission, and furthermore, proposed an optimal transmission method depending on the flight speed. In these analysis results, we designed functions to be implemented in drones, developed wireless devices, and confirmed their operation through demonstration tests using actual drones. Based on the results of this research, we succeeded in identifying issues to be addressed in order to implement the system on drones and in developing an epidemic communication system based on the results of demonstration experiments, thereby contributing to the realization of inter-drone communication in the future.

Dario Vuger

In this paper, the author will propose a new reading of Heidegger’s reflections on technology based on Gilbert Simondon’s critique of cybernetics as a major opponent of Norbert Wiener’s philosophy, whose thought project almost single-handedly established the science of information systems management as the grounding discipline of modern science. Simondon proposes the establishment of a techno-culture of open machines in which man finds himself as a technician and mechanologist of a new social nexus. But for such a project, it is first necessary to develop a radically disruptive attitude towards everyday language, which hides in itself the means to rethink our attitudes towards the everyday challenges of techno-scientific enframing of the world.

Imran Iqbal, Gbenga Abiodun Odesanmi, Jianxiang Wang et al.

Increase in popularity of deep learning in various research areas leads to use it in resolving image classification problems. The objective of this research is to compare and to find learning algorithms which perform better for image classification task with small dataset. We have also tuned the hyperparameters associated with optimizers and models to improve performance. First, we performed several experiments using eight learning algorithms to come closer to optimal values of hyperparameters. Then, we executed twenty-four final experiments with near optimum values of hyperparameters to find the best learning algorithm. Experimental results showed that the AdaGrad learning algorithm achieves better accuracy, lesser training time, as well as fewer memory utilization compared to the rest of the learning algorithms.

Tamirat Temesgen Dufera

This paper is aimed at applying deep artificial neural networks for solving system of ordinary differential equations. We developed a vectorized algorithm and implemented using python code. We conducted different experiments for selecting better neural architecture. For the learning of the neural network, we utilized the adaptive moment minimization method. Finally, we compare the method with one of the traditional numerical methods-Runge–Kutta order four. We have shown that, the artificial neural network could provide better accuracy for smaller numbers of grid points.

Samuel Teague, Javaan Chahl

Many common navigation solutions fall short when an aircraft’s GPS signal is either jammed or spoofed. This is typically due to the iterative nature of the estimation process, which requires an acceptably accurate initial estimate, or due to the accumulated error of inertial sensors, which are unable to directly observe the position of an aircraft. A mechanism is presented in this paper which operates on qualitative information, allowing an aircraft to remain within a vicinity despite an absence of precision localization. A long-short-term-memory neural network was used for time series classification of radio signal strength data on a light weight fixed wing UAV. Simulation results show that the two class classifier is able to determine the motion of an aircraft with respect to a radio beacon with 97.73% accuracy. The classes used for classification represent motion as either towards, or away from a beacon. A simple high level controller was designed to use the classification output and converge on a beacon. Results from this paper indicate that this unique application of qualitative navigation by the application of time series classification offers a viable alternative to aircraft navigation in GPS denied environments.

Neemias Lemus-Cortez, Claudio Gaete-Peralta, Jaime Huincahue

The objective of this research was to analyze the construction of mathematical knowledge associated with the linear inequalities that Chilean students carried out through graphic argumentation, in a modelling process framed in the Socioepistemological Theory of Educational Mathematics. To fulfill this objective, the methodology was qualitative and consisted of a case study in which 28 Chilean 12th grade students participated in a classroom situation where a modelling process was applied through the use of a mobile phone application called Sound Analyzer that designs graphs of a sound in decibels according to time. The students described the number of decibels of a certain song and identified the time intervals in which that song exceeded the number of decibels established by regulation by the Ministry of the Environment of Chile. As a result of the investigation, it was found that the students were able to generate, in a modelling process and through graphic argumentation, a resignification of mathematical knowledge associated with linear inequalities.

Linda Monsees

Cryptoparties (CPs) are a global movement of forums where citizens can come to learn how to improve their digital privacy and security. The present paper is one of the few empirical studies on CPs and is based on participant observation of three CPs. I demonstrate that the organisers of CPs strive for an egalitarian space for teaching and learning. Even though this goal is not always achieved, CPs might still serve as an example of citizen education in a technological society where every citizen needs to deal with complex technological issues. In addition, this paper contributes to the emerging debate on ‘doing internet governance’, broadening our focus to include user-based and decentred practices. I argue for the political relevance of CPs showing how they enact decentred threat-scenarios to a non-expert public.

Andrii Protsenko, Valerii Ivanov

The importance of finding a path for autonomous moving robots is indispensable, because the successful achievement of the target location depends on the solution of this problem.There are a large number of different methods of finding the way, which differ in the accuracy of work, speed, the need for additional equipment.Underground environments, such as mines and tunnels, differ from other structures and open space, and therefore, require different approach when performing pathfinding, as narrow, curved passages and heterogeneous structure could render some of the pathfinding methods ineffective. However, methods based on rapidly exploring random trees (RRT) maintain their effectiveness because they are unaffected by the complexity of the environment. In this article presented a comparisonof the three RRT-based methods: RRT, RRT-connect and RRT*.

Michiyo Suzuki, Zu Soh, Hiroki Yamashita et al.

To clarify the tissue responsible for a biological function, that function can be experimentally perturbed by an external stimulus, such as radiation. Radiation can be precisely and finely administered and any subsequent change in function examined. To investigate the involvement of the central nervous system (CNS) in <i>Caenorhabditis elegans’</i> locomotion, we irradiated a limited 20-µm-diameter area of the CNS with a single dose and evaluated the resulting effects on motility. However, whether irradiated area (beam size)-dependent or dose-dependent effects on motility occur via targeted irradiation remain unknown. In the present study, we examined the irradiated area- and dose-dependent effects of CNS-targeted irradiation on the motility of <i>C. elegans</i> using a collimating microbeam system and confirmed the involvement of the CNS and body-wall muscle cells around the CNS in motility. After CNS-targeted microbeam irradiation, <i>C. elegans’</i> motility was assayed. The results demonstrated a dose-dependent effect of CNS-targeted irradiation on motility reflecting direct effects on the irradiated CNS. In addition, when irradiated with 1000-Gy irradiation, irradiated area (beam size)-dependent effects were observed. This method has two technical advantages: Performing a series of on-chip imaging analyses before and after irradiation and targeted irradiation using a distinct ion-beam size.

Mallik Avijit, Ahmed Sharif, Hossain G. M. M. et al.

Leakage of Liquefied Petroleum Gas and Liquified Natural Gas (LPG/LNG) produces hazardous and toxic impact on humans and other living creatures. The authors developed a system to monitor and control the gas leakage concentration. MQ-6 gas sensor is used for sensing the level of gas concentration in a closed volume. To monitor the consequences of environmental changes an IoT platform hosted by “Thingspeak” platform has been introduced. Both robust and cloud-forwarded controls have been applied to prevent uncontrolled leakage of those gases and auto-ignition. This type of system can be directly applied to the engine chamber/ fuel chamber of the modern marine vessels using dual fuel power cycle with LPG/LNG as secondary fuel-flamer. The results from the experiments clearly indicate satisfactory actuation speed and accuracy. The trials performed by the authors showed about 99% efficiency of signal transmission and actuation.