Independent Processing Research Articles

USING OF THE MODELS IN PRACTICE-ORIENTED EDUCATION DURING LEARNING OF PEDIATRIC DENTISTRY

Teachers of clinical departments of establishments of higher medical education are faced with the problem of practical training of students, and many methods have been proposed for its improvement.
 The purpose of the study was to consider the models of practice-oriented education that can be used
 during the teaching of pediatric therapeutic dentistry.
 One Minute Preceptor model is used by the teacher during a 1-5-minute conversation with the student to guide diagnostic and treatment processes; initially a student examines a patient, then presents the clinical case, after which the teacher manages his behavioral reactions.
 SNAPPS model (Summarize + Narrow + Analyze + Probe + Plan + Select) describes 6 stages of the clinical training. The model includes analysis of the medical history and examination methods, choice of the diagnoses for differential diagnostic, proper differential diagnosis, questions to the teacher about uncertainties, discussion of patient’s treatment plan and questions and sources related to the clinical case for independent processing.
 Within the framework of pattern recognition and reproduction model (standard cases), student talks about the main problem that worries the patient and offers his diagnosis based on key symptoms during 30 seconds. Teacher personally examines patient, makes a diagnosis or discusses why it cannot be made with certainty, and evaluates the student’s actions.
 All described models of practice-oriented learning improve the expression of reasoning without much impact on the time spent for case presentation. Pattern recognition and reproduction model is especially useful in dentistry to recognize widespread clinical cases. One Minute Preceptor model, which involves the initiative and mentoring role of the teacher, fits well for beginners, while SNAPPS model, that focused on independent work of students, for strong students.

A dual colorimetric-electrochemical microfluidic paper-based analytical device for point-of-care testing of ischemic strokes.

A novel microfluidic paper-based analytical device with dual colorimetric and electrochemical detection (dual μPAD) was developed for the assessment of transferrin saturation (TSAT) in samples from ischemic stroke patients. TSAT was calculated from the ratio between transferrin-bound iron, which was colorimetrically measured, and the total iron-binding capacity, which was electrochemically measured. To this end, a μPAD was smartly designed, which integrated both colorimetric and electrochemical detection reservoirs, communicating via a microchannel acting as a chemical reactor, and with preloading/storing capabilities (reagent-free device). This approach allowed the dual and simultaneous determination of both parameters, providing an improvement in the reliability of the results due to an independent signal principle and processing. The μPADs were validated by analyzing a certified reference material, showing excellent accuracy (Er ≤ 5%) and precision (RSD ≤ 2%). Then they were applied to the analysis of diagnosed serum samples from ischemic stroke patients. The results were compared to those provided by a free-interference method (urea-PAGE). Impressively, both methods exhibited a good correlation (r = 0.96, p < 0.05) and no significant differences were found between them (slope 1.0 ± 0.1 and the intercept 1 ± 4, p < 0.05), demonstrating the excellent accuracy of our approach during the analysis of complex samples from ischemic stroke patients, using just 90 μL of clinical samples and taking less than 90 min in comparison with the 18 hours required by the urea-PAGE approach. The developed fully integrated colorimetric-electrochemical μPAD is a promising ready to use reagent-free device for the point-of-care testing of TSAT, which can be used to assist physicians in the fast diagnosis and prognosis of ischemic strokes, where the decision-time is crucial for the patient's survival.

Opto-Electrochemical Synaptic Memory in Supramolecularly Engineered Janus 2D MoS2.

Artificial synapses combining multiple yet independent signal processing strategies in a single device are key enabler to achieve high-density of integration, energy efficiency, and fast data manipulation in brain-like computing. By taming functional complexity, the use of hybrids comprising multiple materials as active components in synaptic devices represents a powerful route to encode both short-term potentiation (STP) and long-term potentiation (LTP) in synaptic circuitries. To meet such a grand challenge, herein a novel Janus 2D material is developed by dressing asymmetrically the two surfaces of 2D molybdenum disulfide (MoS2 ) with an electrochemically-switchable ferrocene (Fc)/ ferrocenium (Fc+ ) redox couple and an optically-responsive photochromic azobenzene (Azo). Upon varying the magnitude of the electrochemical stimulus, it is possible to steer the transition between STP and LTP, thereby either triggering electrochemical doping of Fc/Fc+ pair on MoS2 or controlling an adsorption/desorption process of such redox species on MoS2 .In addition, a lower magnitude LTP is recorded by activating the photoisomerization of azobenzene chemisorbed molecules and therefore modulating the dipole-induced doping of the 2D semiconductor. Significantly, the interplay of electrochemical and optical stimuli makes it possible to construct artificial synapses where LTP can be boosted to 4-bit (16 memory states) while simultaneously functioning as STP.

Pipelined correlated minimum weight perfect matching of the surface code

We describe a pipeline approach to decoding the surface code using minimum weight perfect matching, including taking into account correlations between detection events. An independent no-communication parallelizable processing stage reweights the graph according to likely correlations, followed by another no-communication parallelizable stage for high confidence matching. A later general stage finishes the matching. This is a simplification of previous correlated matching techniques which required a complex interaction between general matching and re-weighting the graph. Despite this simplification, which gives correlated matching a better chance of achieving real-time processing, we find the logical error rate practically unchanged. We validate the new algorithm on the fully fault-tolerant toric, unrotated, and rotated surface codes, all with standard depolarizing noise. We expect these techniques to be applicable to a wide range of other decoders.

Virtual human speech emotion recognition based on multi-channel CNN: MFCC, LPC, and F0 features

Convolutional neural networks (CNNs) have shown promise in virtual human speech emotion expression. Previous studies have utilized CNNs for speech emotion recognition and achieved good results. However, there are research gaps in avatar speech emotion expression, particularly concerning speaker characteristics, and limited available datasets. To address these issues, this paper collects and pre-processes speech data from multiple speakers, using features such as Mel Frequency Cepstral Coefficient (MFCC) and Linear Predictive Coding (LPC). A multi-channel CNN (MUC-CNN) model is designed to fuse different feature information and update model parameters using the Adam optimization algorithm. The model‘s performance is compared with classical methods like Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbors (k-NN) to determine its applicability and optimize its design and training process. Experimental evaluation shows that the MUC-CNN model outperforms classical methods in recognizing and expressing emotions in virtual human speech. By incorporating MFCC, LPC, and F0 features, the model‘s recognition capabilities are improved. The multi-channel architecture allows independent processing of each feature type, enhancing the model‘s discriminative aptitude. The performance of the model is influenced by the quantity of convolutional layers and kernels utilized. The outcomes highlight the effectiveness of the proposed MUC-CNN model for the recognition and expression of speech emotions in virtual human interactions. Future research can explore alternative feature information and refine the model architecture to further optimize performance. This technology has the potential to enhance user experience and interaction in various fields, including speech interaction, virtual reality, games, and education.

The Village Empowerment Through Circular and Green Economic Programs Through Independent Waste Management

Tofu and organic waste are problems that are high on the agenda in Yogyakarta, especially in Sleman and Bantul. This area is also the largest center of the tofu industry and essential oil from red lemongrass in DIY. Through the Community Service (Abdimas) program in collaboration with Rumah Maggot Barepan Bangkit (RMBB) and the Sereh Merah Farmer Group in the Integrated Community Service Program program with MBKM Based on IKU for Private Universities in 2022-2023 in collaboration with the Directorate of Research, Technology, and Community Service Kemdikbudristek, UST Faculty of Agriculture and Faculty of Pharmacy Duta Bangsa University, try to empower the community with circular and green economiy activities the waste becomes money. This activity aims to increase the capacity of the community to become an independent waste processing center, teaching the processing of lemongrass leaves into fertilizer, processing maggot into pellets, processing and packaging kasgot into fertilizer and planting media. This service is divided into three stages, taking place from 2022 - 2023. The activities are divided into three stages. The first stage is socialization of independent lemongrass waste management, introduction of soil improver factors, and processing maggot into pellets.The second stage is a workshop on making POC and biofertilizer made from lemongrass, processing maggot into pellets, processing kasgot into fertilizer and planting media.The third stage is practice and application, making biofertilizer, POC, and floating pellets in the two fostered communities. It is hoped that this service will create a circular economy where the community can manage waste independently, get benefits from waste management and economic turnover in the village. In addition, it will create a green economy, where there is no more waste generated from the activity and the waste becomes money.

A Line Length Independent, Pseudo-Transmission Permittivity Sensor Basing on Dielectric Waveguides

This contribution introduces a novel, dielectric waveguide based, permittivity sensor. Next to the fundamental hybrid mode theory, which predicts exceptional wave propagation behavior, a design concept is presented that realizes a pseudo-transmission measurement approach for attenuating feed-side reflections. Furthermore, a transmission line length independent signal processing is introduced, which fosters the robustness and applicability of the sensor concept. Simulation and measurement results that prove the sensor concept and validate the high measurement accuracy, are presented and discussed in detail.

Effectiveness of Flash Card Media-Oriented Group Investigation Learning Models on Learning Outcomes of Elementary Students

The purpose of this study was to determine the effectiveness of the flash card media-oriented group investigation (GI) learning model on the learning outcomes of elementary students. The approach used in this study is a quantitative approach with pre-experimental methods and the type of One Group Pretest-Posttest design. With the overall population of SD Inpres Oeba 2 class V students 22 people. Sampling using nonprobability sampling saturated sampling where all members of the population are sampled. The data collection technique was obtained from a multiple choice written test. The data analysis technique used descriptive analysis and inferential statistics with the help of the SPSS version 22 application. The results showed that independent t-test data processing obtained a sig value of 0.000 &lt;0.05, then Ha was accepted and H0 was rejected or in other words there was a significant difference between pretest and posttest classes in improving student learning outcomes in the material for the digestive tract of food in humans. Thus, the Flash Card Oriented Group Investigation (GI) learning model can improve the Learning Outcomes of Class V Students of SD Inpres Oeba 2 Kupang City.

Bidynamical all-optical reservoir computing for parallel task processing.

A bidynamical all-optical reservoir computing (RC) system for parallel task processing is proposed based on a unidirectional semiconductor optical amplifier optical fiber loop. The polarization dynamics and intensity dynamics are excited by the input signals injected into the reservoir via phase modulation and intensity modulation, respectively. Simultaneous computation of two independent tasks is implemented based on the dynamical responses in polarization and intensity of the optical fiber loop. To our knowledge, this is the first time that two kinds of dynamical responses of an all-optical RC system are used as independent task processing channels to implement parallel task processing. The proposed RC system can achieve good parallel task processing performance with low system cost.

Autonomy and Knowledge Processes - a Systematic Literary Review

Knowledge processes, such as knowledge creation, sharing and application, enable knowledge production that increases innovation and superior organizational performance. Knowledge processes are ultimately and fundamentally conducted – or not engaged in – by the individuals. Hence, knowledge production is disrupted if individuals are prevented from using their knowledge production potential. One potential factor that causes disruption in knowledge production is the lack of autonomy. As autonomy means self-governance and independency, it enables independent and unique knowledge processing by the individual, and thereby supports both individual and collective level knowledge production. Despite the importance of the role of autonomy in knowledge production, there is no research-based knowledge of which knowledge process have been studied from the perspective of autonomy, and what has been left unexplored. This research clarifies the research literature by finding out which knowledge processes have been studied from the point of view of autonomy. Also, what has been found concerning the relationship between autonomy and knowledge processes is considered. The research was conducted as a systematic literature review supplemented by qualitative content analysis in which the articles up the year 2022 from databases Scopus and Web of Science were reviewed. The most notable finding of this study is the lack of research between autonomy and knowledge identification and the paucity of research between autonomy and knowledge internalization. This is a significant finding since knowledge identification affect what knowledge is processed and produced in the organization. Internalizations in turn affects knowledge-based orientation and knowledge production in the organizational environment. This paper contributes to the organizational research literature by summing up the existing research on the interface of autonomy and knowledge processes and provides a refined understanding on the central role of autonomy in the effective implementation of knowledge processes, as well as avenues for future research.

Research on energy-saving conventional submarine air-conditioning system based on heat and humidity load calculation

The built-in air-conditioning and ventilation system of modern conventional submarines still adopts duct ventilation, which has high working noise, high energy consumption, poor dehumidification effect, and is mainly inter-cooled. For the air quality, hot and humid environment and comfort requirements in the submarine cabin. This project proposes an energy-saving cold storage air-conditioning system suitable for submarines. It adopts the air control method of temperature and humidity independent processing, and combines solution dehumidification and cold storage technology to independently control the temperature and humidity of the cabin, so as to achieve the purpose of efficient dehumidification and energy saving. The system makes full use of the limited space inside the submarine, reduces the energy consumption of refrigeration, improves the underwater endurance and concealment, and provides a healthy and comfortable air environment for the crew of the submarine, which has important strategic value.

Development of a digital training for social and emotional competences for medical assistants in vocational education and training in Germany

This paper describes a digital training for social and emotional competences for prospective medical assistants (MAs) in Germany. Social and emotional competences (SEC) are necessary for the collaboration with colleagues as well as for the contact with clients, patients or customers. The German dual system of vocational education and training (VET) therefore considers them as essential parts of the profile of most training occupations. Nevertheless, few materials exist so far for the systematic training of these competences. In former studies three social and emotional competences have been identified as essential for MAs: emotion regulation, perspective coordination and communication strategies. At the same time development needs have been identified for all of them. To address these needs the three hours online training programme SECOTrain (Social and Emotional Competence Training) has been developed, which offers separate training sessions for all three competences. The aim of the paper is to depict how the fostering of social and emotional competences can be approached via a digital training, report our experiences with this endeavour and to discuss associated advantages as well as challenges and ways to deal with them. Digital formats offer new possibilities and chances for education and training, as they facilitate access to the content in a standardized and efficient way. An independent processing of trainings is made possible, regardless of time and teacher. At the same time, this comes along with a risk of overstraining some learners, as problems of understanding or motivation may occur. SECOTrain transfers pedagogical ideas into the context of digital learning to reduce these risks as much as possible. Each of the three training sessions follows the principles of the Cognitive Apprenticeship approach and is inspired by existing theories and trainings. Video sequences of typical critical interaction situations serve as material for explanation, application and reflection to support a strong practical orientation. Effects of the training will be evaluated in a pretest–posttest-follow-up experimental design. The paper presents goals and content as well as methods, pedagogical principles and theoretical foundation of SECOTrain. Furthermore, results of a small pilot study are presented and discussed with regard to further adjusting the training to the needs of the target group. At the end, an outline of the planned evaluation is given.

Massively parallel FDTD-FBMC simulations of nonlinear hole dynamics in silicon at cryogenic temperatures driven by intense EM THz pulses

THz spectroscopy with intense electromagnetic (EM) pulses offers unique avenues to study the charge carrier dynamics in semiconductors. Quantitative analysis of the experiment requires a detailed microscopic model that is based on the wave propagation within the sample and on the strongly nonparabolic dispersion relation of the valence bands. With a finite difference time domain (FDTD) solver for the EM wave in conjunction with a full band Monte Carlo (FBMC) model for the holes the generation of higher harmonics by the nonlinear hole response in the p-doped silicon sample can be simulated. Due to impurity freeze-out at the cryogenic temperature the hole density is low and the FDTD solver can be decoupled from the FBMC model by a perturbation approach. This enables the independent processing of a very large number of holes on a computer cluster with nearly 100% computational efficiency resulting in a very low level of stochastic noise, which is necessary to achieve a reasonable signal to noise ratio for the faint higher harmonics. The simulations show that at THz frequencies and cryogenic temperatures strong generation of higher harmonics is only possible, if the band structure is nonparabolic.

A framework for the design of sustainable multi-input second-generation biorefineries through process simulation: A case study for the valorization of lignocellulosic and starchy waste from the plantain agro-industry

The plantain agro-industry generates different residues in the harvest and post-harvest stages. Therefore, new processes for its valorization are required. The aim of this research was to propose a general methodological framework for the design and analysis of multi-input biorefineries for the valorization of residues with a high content of lignocellulosic and starchy materials. This approach was based on the independent processing of the starchy and lignocellulosic materials in the first steps of the biorefinery and relies on process simulation and hierarchic process design procedures. A case study for the design of a multi-input biorefinery for the valorization of residues from the plantain agro-industry was performed by applying the framework proposed. The biorefinery was simulated using SuperPro Designer software. The results obtained suggest that the best alternative for the valorization of plantain residues under Colombian conditions corresponded to the following distribution of key residues: 100% leaf sheaths processed into the natural fiber production section, and 25% peels and 25% rachis processed into the starch extraction and liquefaction section; with this distribution, an NPV of $21,348,000 can be achieved. This work shows that waste from the plantain agro-industry exhibits high potential as a feedstock for the production of value-added products.

Late ERP correlates of confidence for auditory categorization of complex sounds

Recent research suggests that confidence judgments relate to the quality of early sensory representations and later modality independent processing stages. It is not known whether the nature of this finding might vary based on task and/or stimulus characteristics (e.g., detection vs. categorization). The present study investigated the neural correlates of confidence using electroencephalography (EEG) in an auditory categorization task. This allowed us to examine whether the early event-related potentials (ERPs) related to confidence in detection also apply to a more complex auditory task. Participants listened to frequency-modulated (FM) tonal stimuli going up or down in pitch. The rate of FM tones ranged from slow to fast, making the stimuli harder or easier to categorize. Tone-locked late posterior positivity (LPP) but not N1 or P2 amplitudes were larger for (correct-only) trials rated with high than low confidence. These results replicated for trials presenting stimuli at individually identified threshold levels (rate of change producing ∼71.7% correct performance). This finding suggests that, in this task, neural correlates of confidence do not vary based on difficulty level. We suggest that the LPP is a task general indication of the confidence for an upcoming judgment in a variety of paradigms.

A queueing model of visual search

Understanding how attentional resources are deployed in visual processing is a fundamental and highly debated topic. As an alternative to theoretical models of visual search that propose sequences of separate serial or parallel stages of processing, we suggest a queueing processing structure that entails a serial transition between parallel processing stages. We develop a continuous-time queueing model for standard visual search tasks to formalize and implement this notion. Specified as a finite-time, single-line, multiserver queueing system, the model accounts for both accuracy and response time (RT) data in visual search on a distributional level. It assumes two stages of processing. Visual stimuli first go through a massively parallel preattentive stage of feature encoding. They wait if necessary and then enter a limited-capacity attentive stage serially where multiple processing channels (“servers”) integrate features of several stimuli in parallel. A core feature of our model is the serial transition from the unlimited-capacity preattentive processing stage to the limited-capacity attentive processing stage. It enables asynchronous attentive processing of multiple stimuli in parallel and is more efficient than a simple chain of two successive, strictly parallel processing stages. The model accounts for response errors by means of two underlying mechanisms, namely, imperfect processing of the servers and, in addition, incomplete search adopted by the observer to maximize search efficiency under an accuracy constraint. For statistical inference, we develop a Monte-Carlo-based parameter estimation procedure, using maximum likelihood (ML) estimation for accuracy-related parameters and minimum distance (MD) estimation for RT-related parameters. We fit the model to two large empirical data sets from two types of visual search tasks. The model captures the accuracy rates almost perfectly and the observed RT distributions quite well, indicating a high explanatory power. The number of independent parallel processing channels that explain both data sets best was five. We also perform a Monte-Carlo model uncertainty analysis and show that the model with the correct number of parallel channels is selected for more than 90% of the simulated samples.

The Microarchitecture of DOJO, Tesla’s Exa-Scale Computer

The Tesla-built DOJO system is a scalable solution targeted towards Machine Learning training applications. It is based on the D1 custom compute chip which packs together 354 independent processors, resulting in 362 TFlops of compute and 440 MB of internal SRAM storage. While maintaining full programmability, DOJO emphasizes distribution of resources and an extremely high bandwidth interconnect, allowing it to scale from small systems all the way to Exa-Flop supercomputers.

Lightweight Semantic Architecture Modeling by 3D Feature Line Detection

Existing architecture semantic modeling methods in 3D complex urban scenes continue facing difficulties, such as limited training data, lack of semantic information, and inflexible model processing. Focusing on extracting and adopting accurate semantic information into a modeling process, this work presents a framework for lightweight modeling of buildings that joints point clouds semantic segmentation and 3D feature line detection constrained by geometric and photometric consistency. The main steps are: (1) Extraction of single buildings from point clouds using 2D-3D semi-supervised semantic segmentation under photometric and geometric constraints. (2) Generation of lightweight building models by using 3D plane-constrained multi-view feature line extraction and optimization. (3) Introduction of detailed semantics of building elements into independent 3D building models by using fine-grained segmentation of multi-view images to achieve high-accuracy architecture lightweight modeling with fine-grained semantic information. Experimental results demonstrate that it can perform independent lightweight modeling of each building on point cloud at various scales and scenes, with accurate geometric appearance details and realistic textures. It also enables independent processing and analysis of each building in the scenario, making them more useful in practical applications.

СИСТЕМИ БАЗОВИХ ЕКВІВАЛЕНТНИХ ПРИКЛАДІВ ДЛЯ ВИВЧЕННЯ ТЕМ ТЕОРЕТИЧНОЇ ТА ТЕХНІЧНОЇ МЕХАНІКИ

TECHNICAL MECHANICS The article examines the use of systems of basic equivalent examples of problem solving for the study of topics of theoretical and technical mechanics during extreme distance learning in war conditions. It is shown that solving sets of problems on relevant topics to consolidate theoretical material and form relevant practical knowledge, abilities and skills necessary in the future conducting more complex applied calculations of systems and structures. At the same time, in the modern realities of war in the conditions of a long-term and extremely complex educational process, both in a mixed and completely remote format, when the enemy inflicts insidious terrorist attacks on civilian infrastructure, and primarily energy life support, circumstances arise when quite complex material on the relevant topic, part of the students, due to the impossibility of connecting to the video conference of the couple according to the schedule, have to actually work in full on their own, even with intermittent access to electronic media due to scheduled and unscheduled power outages. This creates additional new requirements for the content of the lecture material with the maximum step-by-step explanation of all components of each topic in the complex of educational and methodological support of the discipline, primarily for files with lecture texts, which are displayed for students on the appropriate educational platform (messenger) for each classes in theoretical and technical mechanics. It has been determined that an important component of the distance educational process in the study of theoretical and technical mechanics is a system of examples equivalent to problems for relevant practical classes with a detailed "talking" of all the steps of solving typical problems that are submitted for processing on this topic for current control. This becomes even more relevant in the conditions of war, when the lecture material on each topic presented in Google Classroom (or MOODLE, WIKI) is supported by a system of detailed problem-solving examples (completely similar to those presented in practical classes) from the minimum basic level to of increased complexity, which enables the student, even with completely independent processing, to form relevant multi-level practical skills on this topic. The elements of the proposed systems of basic equivalent examples of solving problems on the topics "Basic concepts and axioms of the statics of an absolutely rigid body" and "System of convergent forces" are given.

THE INFLUENCE OF FINANCIAL FACTORS AND LOCAL GOVERNMENT CHARACTERISTICS ON FINANCIAL DISTRESS

The success of regional autonomy can be reflected in the quality of the public services provided. This research was conducted in the local government of cities and regencies in Central Java Province. This study aimed to identify and analyze the effect of financial factors and local government characteristics on financial distress in city and district regional governments in Central Java Province for the 2017-2021 period. This research uses causal associative research with a quantitative approach. In determining the sample, a purposive sampling method was used with a population of all regencies and cities in Central Java Province for the 2017-2021 period. This study utilized eight independent variables and data processing instruments used in Microsoft Excel and Econometric Views (E-Views) version 10 with a panel data regression model.&#x0D; This study's results are partially the effectiveness and efficiency ratio that affect financial distress. While the other six variables (income growth ratio, independence ratio, regional solvency ratio, population, and audit opinion) partially do not affect financial distress. However, simultaneously the independent variables affect financial distress.