Hasil untuk "Cybernetics"

Tomáš Mimra, Martin Augustynek, Marek Penhaker et al.

Background: The objective assessment of hearing in non-cooperative populations, such as neonates, remains a challenge. While Brainstem Evoked Response Audiometry (BERA) is the gold standard, its sensitivity to motion artifacts necessitates alternatives. Objective: This scoping review maps the current literature on functional near-infrared spectroscopy (fNIRS) as a supplementary method in objective audiometry. Data Synthesis: fNIRS shows potential to detect cortical hemodynamic responses, particularly to complex stimuli like speech, which BERA cannot fully assess. Key advantages include motion tolerance and suitability for pediatric and cochlear implant populations. However, the literature reveals significant heterogeneity in stimulation protocols and data processing. Evidence suggests fNIRS is better suited for assessing higher-level auditory processing rather than replacing BERA for threshold estimation. Conclusions: fNIRS is a promising complementary tool. However, due to the lack of standardized protocols and large-scale validation studies, it is not yet a direct clinical replacement for BERA. Future work must focus on protocol standardization and establishing robust normative data.

Hanna Antonova

Introduction. Wireless sensor networks are a part of information and communication technologies and the basis of the Internet of Things technologies. Data are collected, transmitted and processed in real time with the wireless sensor networks. The typical WSN consists of the large number wireless sensor nodes and the coordinator. The wireless network is based on wireless communication standards. Today, WSNs are used in the variety of industries such as medicine, military and digital agriculture. The purpose is to provide a comprehensive analysis of a wireless sensor node for use in digital agriculture. Results. The author analysed wireless communication standards for use in digital agriculture. The typical wireless node architecture is analysed. The parameters of the wireless node are identified. The types of Energy Harvesting Systems (EHS) and their functions are reviewed and analysed. Based on the requires of the wireless node for digital agriculture, the list of photovoltaic energy converters is proposed. In addition, the list of power management integrated circuits is suggested for the Energy Harvesting System. A Classification of Power Supplies for Wireless Sensor Nodes and Networks are developed. The types of sensors for use in digital agriculture are analysed. Conclusions. The main wireless communication standards for digital agriculture are Wi-Fi, IEEE 802.15.4, ZigBee, Bluetooth 4.0, GPRS, 4G, LoRaWAN and NB-IoT. The parameters of the wireless node are identified for further modelling. The list of photovoltaic energy converters is given. The types of power management integrated circuits are proposed. The classification enable to simplify the selection of WSN power supplies for network development. Based on the analysis of sensor parameters for digital agriculture, it is concluded that practically there are no wireless sensors on the world market for the express estimation of plants state.

Gizem Gültekin-Várkonyi

Facial recognition technologies (FRTs) are used by law enforcement agencies (LEAs) for various purposes, including public security, as part of their legally mandated duty to serve the public interest. While these technologies can aid LEAs in fulfilling their public security responsibilities, they pose significant risks to data protection rights. This article identifies four specific risks associated with the use of FRT by LEAs for public security within the frameworks of the General Data Protection Regulation and Artificial Intelligence Act. These risks particularly concern compliance with fundamental data protection principles, namely data minimisation, purpose limitation, data and system accuracy, and administrative challenges. These challenges arise due to legal, technical, and practical factors in developing algorithms for law enforcement. Addressing these risks and exploring practical mitigations, such as broadening the scope of data protection impact assessments, may enhance transparency and ensure that FRT is used for public security in a manner that serves the public interest.

Ebrahim Fathi, Timothy R. Carr, Mohammad Faiq Adenan et al.

The Marcellus Shale and Energy Environmental Laboratory (MSEEL) provides a comprehensive dataset and field tests that can be used to study the significance of preexisting natural fractures in different subsurface engineering problems such as the effectiveness of the stimulation of an unconventional reservoir, optimized geothermal fluids movement and integrity of the CO2 storage site. Conventionally natural fracture intensity is obtained using sonic and micro-resistivity imaging logs. However, these techniques significantly suffer from two major deficiencies: Human bias in log interpretation and extremely long interpretation time. These two deficiencies are well-recognized in the industry; however, no standard procedures exist to address them. In this study, a new automated machine learning workflow (AMLW) is introduced that uses the LWD high-resolution acceleration data along the horizontal laterals to predict the natural fracture intensities originally obtained using sonic and micro-resistivity imaging. The accuracy and robustness of the new workflow to predict the near wellbore fracture intensities are tested using both regression and classification approaches. Both the regression and classification approaches were able to predict the fracture intensities with high accuracy (average Mean Squared Error of 0.0085 for regression and average accuracy of 0.94 in the confusion matrix for classification). We have shown that only 10%–15% of the labeled resistivity image log is required for training and validation of the machine-learning model. The Automated workflow resulted in K-Neighbors Regressor and classifier algorithms as the best algorithms with a 52.74% and 139.3% improvement in comparison to the Gradient Boosting Regression algorithm (i.e. the fifth best algorithm).

Sergey V. Zapechnikov

The paper is devoted to the analysis of privacy-preserving machine learning systems based on the concept of secure three-party computations. After general information about the purposes of secure multi-party computations and privacy-preserving machine learning, an overview of existing privacy-preserving machine learning systems and perspectives for their development is offered. An analysis of the work of leading foreign research teams allows to identify several criteria essential for evaluating privacy-preserving machine learning systems based on multi-party secure computations. A comparative analysis of privacy-preserving machine learning systems is carried out according to a dedicated system of criteria. The further subject of consideration is only systems based on three-party secure computations. The main attention is paid to the algorithmic aspects of the organization of such systems, the methods and protocols of information security implemented in them. Systems secure to various types of adversary are considered, both based on universal modules of secure two-party computations, and specialized ones designed to ensure the privacy of specific machine learning methods, such as neural networks. Examples of prototypes of such systems are considered in detail. Based on the results of the analysis, conclusions are made about the prospects for developing privacy-preserving machine learning systems, and the tasks of future research are described.

Shogo Uehara, Shigehiro Hashimoto, Sakyo Shimada et al.

A biological cell is flexible and must deform to pass through a narrow gap. Therefore, in capillaries and in liver and spleen sinusoids, vascular constrictions plays the role of a filter to sort healthy from damaged cells <em>in vivo</em>. In this study, deformation of a cell during accelerated passage through a microgap in a microflow channel was analyzed <em>in vitro</em>. A gap with the rectangular cross section (7 μm height, 0.8 mm width, and 0.1 mm length) was inserted at the middle of a microflow channel using photolithography. Myoblasts (C2C12: mouse myoblast cells) were used in the test. The flow rate of the medium fluid, in which cells were suspended, was controlled by the pressure head between the inlet and outlet. The deformation of smaller cells passing through the microgap with an accelerated velocity was observed with an inverted phase-contrast microscope. The results show that each elongated smalller (diameter < 15 μm) cell tends to tilt parallel to the flow direction during its transit through the gap.

Rusudan Makhachashvili, Ivan Semenist

Transformative shifts in the knowledge economy of the XXI century, Industry 4.0 and Web 4.0 development and elaboration of networked society, emergency digitization of all social communicative spheres due to pandemic measures have imposed pressing revisions onto interdisciplinary and cross-sectorial job market demands of university level education, curriculum design and learning outcomes. The COVID-19 pandemic induced amplified digitalization measures in the higher education sphere, informed by the need to take quick comprehensive action in order to achieve the overarching result to transform educational and communicative scenarios into interdisciplinary digital, remote, and hybrid formats. The consequent functional tasks to meet this challenge in the educational sphere worldwide are estimated as 1) to adapt the existent educational scenarios to digital, remote and hybrid formats; 2) to upgrade e-competence and digital literacy of all stakeholders of the educational process and industry; 3) to activate complex interdisciplinary skillsets, otherwise latent or underutilized in the professional interaction; 4) to introduce functional technical solutions for facilitation of formal and informal educational workflow and communication. The findings of the comprehensive framework research project 'TRANSITION' disclose a wide scope of generalized theoretical and applied issues, permeating the social and educational context worldwide: global event horizon and paradigm shifts in the interdisciplinary trends of digital education in the Covid-19 timeframe and beyond; transformative changes and avenues of development of the network society and education as an interdisciplinary socio-cultural institution and industry in the digital age; global experiences, universal/generic challenges, technical advances and specific national gains in quality assurance of online and hybrid learning in the Covid-19 paradigm.

Katrina L. Dell, Daniel E. Payne, Vaclav Kremen et al.

Background: While the effects of prolonged sleep deprivation (≥24 h) on seizure occurrence has been thoroughly explored, little is known about the effects of day-to-day variations in the duration and quality of sleep on seizure probability. A better understanding of the interaction between sleep and seizures may help to improve seizure management. Methods: To explore how sleep and epileptic seizures are associated, we analysed continuous intracranial electroencephalography (EEG) recordings collected from 10 patients with refractory focal epilepsy undergoing ordinary life activities between 2010 and 2012 from three clinical centres (Austin Health, The Royal Melbourne Hospital, and St Vincent's Hospital of the Melbourne University Epilepsy Group). A total of 4340 days of sleep-wake data were analysed (average 434 days per patient). EEG data were sleep scored using a semi-automated machine learning approach into wake, stages one, two, and three non-rapid eye movement sleep, and rapid eye movement sleep categories. Findings: Seizure probability changes with day-to-day variations in sleep duration. Logistic regression models revealed that an increase in sleep duration, by 1·66 ± 0·52 h, lowered the odds of seizure by 27% in the following 48 h. Following a seizure, patients slept for longer durations and if a seizure occurred during sleep, then sleep quality was also reduced with increased time spent aroused from sleep and reduced rapid eye movement sleep. Interpretation: Our results suggest that day-to-day deviations from regular sleep duration correlates with changes in seizure probability. Sleeping longer, by 1·66 ± 0·52 h, may offer protective effects for patients with refractory focal epilepsy, reducing seizure risk. Furthermore, the occurrence of a seizure may disrupt sleep patterns by elongating sleep and, if the seizure occurs during sleep, reducing its quality.

E.A. Terekhin

The paper presents results of the analysis of long-term changes in the vegetation cover of abandoned agricultural lands in the forest-steppe zone of the Central Chernozem Region using time series of the Normalized Difference Vegetation Index (NDVI), which are measured using MOD13Q1 data. The vegetation index dynamics linked with the proportion of forest communities formed on the abandoned agricultural lands is investigated. The index values for the period of mid-August are the most informative for analyzing the share of forest communities growing on the abandoned agricultural land. Abandoned agricultural lands with coniferous forests have a higher correlation with NDVI than fallows with deciduous species. In the period 2000-2018, for all types of abandoned arable lands, the presence of a positive statistically significant trend component of the vegetation index long-term series is established. Using a slope angle coefficient of the NDVI trend line, a spatio-temporal analysis of the rate of formation of forest stands in the forest-steppe fallows at the beginning of the XXI century was carried out. Features of this process are studied.

Mikkel Leite Arnø, John-Morten Godhavn, Ole Morten Aamo

In the streaming learning setting, an agent is presented with a data stream on which to learn from in an online fashion. A common problem is catastrophic forgetting of old knowledge due to updates to the model. Mitigating catastrophic forgetting has received a lot of attention, and a variety of methods exist to solve this problem. In this paper, we present a divided and prioritized experience replay approach for streaming regression, in which relevant observations are retained in the replay, and extra focus is added to poorly estimated observations through prioritization. Using a real-world dataset, the method is compared to the standard sliding window approach. A statistical power analysis is performed, showing how our approach improves performance on rare, important events at a trade-off in performance for more common observations. Close inspections of the dataset are provided, with emphasis on areas where the standard approach fails. A rephrasing of the problem to a binary classification problem is performed to separate common and rare, important events. These results provide an added perspective regarding the improvement made on rare events. • We divide the prediction space in a streaming regression setting • Observations in the experience replay are prioritized for further training by the model’s current error

S.S. Stafeev, V.D. Zaicev

It is shown theoretically and numerically that circularly and linearly polarized incident beams produce at the tight focus identical circularly symmetric distributions of an on-axis energy flux. It is also shown that the on-axis energy fluxes from radially and azimuthally polarized optical vortices with unit topological charge are equal to each other. An optical vortex with azimuthal polarization is found to generate the minimum focal spot measured for the intensity (all other parameters being equal). Slightly larger (by a fraction of a percent) is the spot size calculated for the energy flux for the circularly and linearly polarized light. The spot size in terms of intensity is of importance in light-matter interaction, whereas the spot size in terms of energy flux affects the resolution in optical microscopy.

Saiedjavad Zarqani, Farideh Madahi

Methodology:In terms of objective and collecting data (made by systematic approach), this research is placed in sort of applied and descriptive research respectively. in order to collect data, we used a researcher-made questionnaire.The statistical population is all students of Tarbiat Modares University in both master and doctoral degrees. Sampling was done randomly and the sample size, according to Cochran formula, is 374 personsFindings:The results obtained by structural model indicated that there is a meaningful relation between the variable defined as attitude towards jobs future and the variable information-seeking behavior of students. The results of Kruskal-Wallis and Uman‌- Whitney tests showed that there was no difference between postgraduate and PhD students in terms of attitude towards jobs future. In addition, there was no difference among students of various groups given the variable towards to job future. while he reaction of students of various groups towards information-seeking behaviors was similar, there exist a significant difference between master and doctoral students in terms of information-seeking behaviorOriginality: As far as the results of this research is concerned, there is a meaningful relation between the information-seeking behavior and the attitudes of students toward their job future. Improving the attitudes to job future and motivating them, we can expect their information-seeking behavior would be improved. The discrepancy between graduate and doctoral students in terms of information-seeking behaviors indicates that universities, or more accurately, central libraries can play a greater role to enhance information-seeking skills of students as well as their level of information knowledge.

توران باقری

هدف: پژوهش حاضر با هدف شناسایی میزان انطباق معماری اطلاعات سطح خارجی نرم‌افزار سیمرغ از دیدگاه کتابداران کتابخانه‌های تخصصی سازمان مدیریت و برنامه‌‌ریزی استان‌های کشور انجام گرفته است. روش‌شناسی: این پژوهش از نوع کاربردی است که به روش پیمایشی و به صورت توصیفی انجام شده است. جامعه آماری پژوهش شامل کتابداران (60 نفر) کتابخانه‌‌های تخصصی سازمان مدیریت و برنامه‌‌ریزی استان‌های کشور بود. ابزار گردآوری داده‌ها پرسشنامه‌‌ای محقق ساخته‌ است که در سه مؤلفه سطح خارجی، وضعیت تعاملی، قابلیت‌ها و امکانات معماری اطلاعات نرم‌افزار سیمرغ را مورد بررسی قرار داده است. روایی توسط تعدادی از اساتید مورد تأیید قرار گرفت و پایایی آن با آلفای کرونباخ 93% تأیید شد. داده‌ها با نرم‌افزار SPSS و با آنالیز واریانس و آزمون تی مستقل مورد تجزیه ‌و تحلیل قرار گرفت. یافته‌ها: یافته‌‌های پژوهش نشان داد که وضعیت معماری اطلاعات نرم افزار سیمرغ در مؤلفه‌‌های سطح خارجی با میانگین 55/3، وضعیت تعاملی با میانگین 73/3، قابلیت‌ها و امکانات معماری اطلاعات با میانگین52/3 مطلوب است.