Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation into Short-Circuit Ruggedness of 1.2 kV 4H-SiC MOSFETs

The shout-circuit ruggedness of prototype 1.2kV SiC MOSFETs has been investigated. The short-circuit measurements were carried out at 25 °C and 125 °C with a dc bus voltage of 800 V and an on/off state gate voltage of +20/-10 V. The small difference in tfail between 25 °C and 125 °C indicates that the destructive breakdown occurs at temperatures much higher than 125 °C. The temperature at destructive breakdown estimated from the Wunsch-Bell formula is about 1400 °C. At such high temperatures, intrinsic carriers are increased markedly and generated heat leads to the destructive breakdown. tfail of all the SiC-MOSFETs studied is longer than 10 μs, meaning that the short-circuit ruggedness satisfies system requirements. These results show that the SiC-MOSFETs are promising for power electronics applications.
Model Development and Simulation of Transient Behavior of Heavy Duty Gas Turbines

This paper describes models for the transient analysis of heavy duty gas turbines, and presents dynamic simulation results of a modern gas turbine for electric power generation. Basic governing equations have been derived from integral forms of unsteady conservation equations. Mathematical models of each component are described with the aid of unsteady one-dimensional governing equations and steady-state component characteristics. Special efforts have been made to predict compressor characteristics including the effect of movable vanes, which govern the operating behavior of a whole engine. The derived equation sets are solved numerically by a fully implicit method. A controller model that maintains constant rotational speed and target temperature (turbine inlet or exhaust temperature) is used to simulate practical operations. Component models, especially those of the compressor, are validated through comparison with test data, The dynamic behavior of a 150 MW class engine is simulated. The time-dependent variations of engine parameters such as power, rotational speed, fuel, temperature, and guide vane angles are compared with field data. Simulated results are fairly close to the operation data.
Experimental analysis of a new zero-voltage switching synchronous rectifier buck converter

High-efficiency converters with excellent low ripple regulated output load must feature the outstanding switching loss reduction mechanism. The rapid advancement of low-loss converter design has posed stringent challenges to designers for efficient power delivery and tight voltage regulation. In this work, the new synchronous rectifier buck converter (SRBC) circuit is proposed. It has been found that the SRBC can operate effectively at 1 MHz switching frequency with low switching and gate drive losses operating in zero-voltage switching condition.
A Study about Brahmi (Bacopa monnieri) Preparation Steps on Its Saponin Quantity

Brahmi (Bacopa monnieri) is a medicinal herb containing bioactive compounds (Bacosides) in the saponin group that enhances memory and prevents dementia. Brahmi is not favored for cooking because it is very bitter. Nowadays, most people consume Brahmi as supplementary food, which makes it more expensive than consuming in food form, not getting fibers and other nutrients. Currently, there are only few studies that work to alleviate in Brahmi. Therefore, this study aimed to find out the saponin quantity in Brahmi after some pretreatments and the effect of these treatments on Bacosides and bitterness. Thus, suitable preparation steps for Brahmi have the highest remaining saponin quantity and are consumable. There were various techniques of preparation, depending on the concentration of salt used in crumpling and 1 time boiling of Brahmi to reduce its bitterness. The salt concentrations used in this study were 0, 10, and 20 % (w/w) compared with the fresh herb. The saponin quantity was analyzed by high-performance liquid chromatography (HPLC). The results showed that the total amount of saponin in boiled Brahmi that crumpled with 0, 10, and 20 % were significantly lower than fresh Brahmi (p < 0.05). Brahmi was crumpled with 10 % salt before boiling had the highest total saponin quantity of 2.69±0.02 g/kg of fresh weight and the highest tasting scores. Thus, the preparation of crumpling with 10 % salt before cooking, was suitable because consumers gained the highest saponin and accepted the taste of food containing Brahmi. HIGHLIGHTS Brahmi have many health benefits not only memory enhancer but also prevention of dementia People used Brahmi as supplementary food because it is very bitter and not favored for cooking Reduce the bitter with non chemical as crumpling with 10 % salt concentration before cooking was highest saponin and accepted the taste of food containing Brahmi
EFEKTIVITAS FILM ANIMASI ‘SAHABAT PEMBERANI’ DALAM MENUMBUHKAN NILAI-NILAI ANTI KORUPSI DI SDN BARENGKRAJAN I KECAMATAN KRIAN KABUPATEN SIDOARJO

Penelitian ini bertujuan untuk mengetahui efektivitas film animasi Sahabat Pemberani dalam menumbuhan nilai-nilai anti korupsi di SDN Barengkrajan 1 Krian. Penelitian ini dilakukan dengan menggunakan desain penelitian The One group Pre-test and Post-test. Dalam desain penelitian terdapat langkah-langkah yang akan menunjukkan urutan kegiatan penelitian, yaitu tes awal, perlakuan, dan tes akhir. Untuk menjawab rumusan masalah menggunakan uji-t. Lokasi penelitian berada di SDN Barengkrajan I Krian. Dengan sampel penelitian 32 siswa kelas III. Teknik pengumpulan data berupa angket dan dokumentasi. Berdasarkan data di lapangan dan hasil analisis data, ditemukan bahwa kemampuan pemahaman siswa tentang nilai-nilai anti korupsi mengalami peningkatan. Berdasarkan nilai dalam distribusi t, bila dk= n-1= 31 dengan taraf kesalahan 5% maka harga t tabel = 2,042. Berdasarkan perhitungan ternyata t hitung 4,541. Karena t hitung > t tabel yakni 4,541 > 2,042 maka Ha diterima dan Ho ditolak, artinya dapat disimpulkan bahwa ada pengaruh antara menumbuhkan nilai-nilai anti korupsi melalui Film Animasi ‘Sahabat Pemberani’ terhadap peningkatan pemahaman siswa tentang nilai-nilai anti korupsi. Kata Kunci: Efektivitas, Film Animasi, dan Nilai-nilai Anti Korupsi Abstract The goal of research was to understand the effectivenes of animated film’Sahabat Pemberani’in growing the value of the anti-corruption in primary school of Barengkrajan in Krian region. The research is conducted by research use one group pre-test post-test design. There are stepst in the design study that will show the order research activities, namely a test early, treatment, and final test. To answer the problem of using the test formula – t. This research locations are in primary school. With the sample of 32 students a class 3. The technique of poll dala collectionan documentation.Based on data in the field and analysis of data, found that the ability of understanding about the value of anti-corruption students increased. Based on the value of the data distribution-t, if the council dk= n-1= 31 with level of error 5% the price of –t table = 2,042. Based on the calculation t count it turns out 4,541. Cause the price of –t > the price of –t table 4,541 > 2,042 so Ha accepted and Ho rejected, it means we can conclude that there is between growing influence of anti-corruption values through animated film ‘Sahabat Pemberani’ on the increased understanding of students aabout the anti-corruption. Keywords: The effectiveness, Animated film, and Anti-corruption values
High-resolution remote sensing vehicle automatic detection based on feature fusion convolutional neural network

Vehicle detection technology based on remote sensing images, as a new method of collecting traffic flow information, provides new ideas for traffic management. A feature-fusion-based convolutional neural network vehicle detection method is proposed. On the basis of image preprocessing, first use the VGG16 convolutional neural network to obtain multi-level features, and then use variable-scale stacking to obtain the basic feature layer to achieve the acquisition of deep convolution features, and then construct a feature pyramid to divide the basic feature layer operation, finally use the attention mechanism to fuse hierarchical information, and then efficiently extract vehicle features. In the example high-resolution remote sensing image vehicle automatic detection experiment, the vehicle automatic detection accuracy rate was 88.7%, and the false detection rate was 1.4%. The experiment shows that this model is better for automatic vehicle detection in high-resolution remote sensing images, especially in dense urban traffic scenes. good detection effect.
Secure Integration of IoT and Cloud Computing

Mobility Technique Is a fairly latest invention that relates to an information storage and processing architecture that is separate from the wireless phone. The IoT is a brand-new concept. The Internet of Things (IoT) is a comparatively recent networking technologies that is increasing popularity swiftly. IoT is more particularly linked to wireless telecommunications. The primary aim of wireless network-based interaction and collaboration amongst things and objects is to achieve the goal established for them as a united entity. Additionally, both Digital Storage and the Iot are quickly evolving cellular networking capabilities. This article provides a summary of the Internet of Things (IoT) and Data Storage, with an emphasis on the security concerns that both technologies face. We purposefully mix the 2 acquired notifications to look for commonalities and see what advantages there are in integrating them. Finally, we will discuss Cloud Computing's contribution to IoT technologies. As a result, it demonstrates how Cloud Computing technology enhances IoT functionality. Finally, we look at the security issues that come with combining IoT with Cloud Computing.
Hyperthermia Enhances Doxorubicin Therapeutic Efficacy against A375 and MNT-1 Melanoma Cells

Melanoma is the deadliest form of skin cancer, and its incidence has alarmingly increased in the last few decades, creating a need for novel treatment approaches. Thus, we evaluated the combinatorial effect of doxorubicin (DOX) and hyperthermia on A375 and MNT-1 human melanoma cell lines. Cells were treated with DOX for 24, 48, and 72 h and their viabilities were assessed. The effect of DOX IC10 and IC20 (combined at 43 °C for 30, 60, and 120 min) on cell viability was further analyzed. Interference on cell cycle dynamics, reactive oxygen species (ROS) production, and apoptosis upon treatment (with 30 min at 43 °C and DOX at the IC20 for 48 h) were analyzed by flow cytometry. Combined treatment significantly decreased cell viability, but not in all tested conditions, suggesting that the effect depends on the drug concentration and heat treatment duration. Combined treatment also mediated a G2/M phase arrest in both cell lines, as well as increasing ROS levels. Additionally, it induced early apoptosis in MNT-1 cells, while in A375 cells this effect was similar to the one caused by hyperthermia alone. These findings demonstrate that hyperthermia enhances DOX effect through cell cycle arrest, oxidative stress, and apoptotic cell death.
AUTONOMOUS SPEED SPRAYER GUIDANCE USING MACHINE VISION AND FUZZY LOGIC

A Fuzzy Logic Controller (FLC) was developed for autonomous operation of a speed sprayer in an orchard. The operation of the FLC was graphically simulated under the real condition of the orchard. Machine vision was used to determine vehicle heading and four ultrasonic sensors were used to detect obstacles during the operation. Operation time duration of the hydraulic cylinders was inferred as output of the FLC. The results of simulation showed that the speed sprayer could be operated autonomously by the FLC that used sensor inputs from machine vision and ultrasonic sensors. After the graphic simulation, autonomous speed sprayer operation in a real orchard was conducted using the developed FLC. Orchard image analysis and signals of ultrasonic sensors were processed in real time. The speed sprayer was modified to be steered by two hydraulic cylinders. The results of field test showed that the speed sprayer could be operated by the FLC. The ultrasonic sensors didn’t contribute to the improvement of guidance performance; however, they assisted the speed sprayer to avoid trees or obstacles in emergent situations.
Sniffing Serial-Based Substation Devices: A Complement to Security-Centric Data Collection

One of the key aids in ensuring security in the substation is data collection. Collected substation data can be applied to data analytics to infer the substation's security status. However, most of the data collected are measurement logs and Ethernet-based traffic data. The industrial network market share shows that serial-based protocols still exist, and it will take some time before they are phased out. Also, data from serial-based traffic is sourced mostly from SCADA; thus, when SCADA is compromised, the data inferred from it can be misleading. To the best of our knowledge, there is no work on data collection involving serial-based protocols such as DNP3 serial, Modbus-RTU and IEC 60870-5-101; hence, we propose a custom serial sniffer that captures data from serial devices and logs them. Such complementary data can be transmitted to a Security Operations Centre (SOC) to provide a second view to confirm the substation's status. Our bench-marking of the serial sniffer shows negligible utilization of CPU and memory resources for DNP3 serial, Modbus-RTU and IEC 60870-5-101; and we can conclude that it is stable across all protocols. Our sniffer code can be embedded into serial-to-Ethernet protocol converters due to its lightweight nature. Our work can complement data collection within substations until the migration to Ethernet-based protocols is complete.
The fundamental role of DELLA protein and regulatory mechanism during plant growth and development

Gibberellins (GAs) play a major role in a variety of key plant development processes, especially in promoting seed germination, stem and root growth, and fruit development. DELLA proteins are the core elements in GA signal transduction pathway, which exist in the plant nucleus and belong to the GRAS protein family. DELLA proteins negatively regulate the GA signaling pathway and biosynthesis, inhibiting plant growth. DELLA proteins can also interact with F-box, PIFS, ROS, SCLl3 and other proteins to enhance plant response to various adverse environmental influences such as drought, low and high temperature, heavy metal stresses. In addition, DELLA proteins can also partially regulate plant growth and development through interacting plant hormones such as ABA (abscisic acid), CK (cytokinin), ET (ethylene), BR (brassinosteroid) and JA (jasmine). This review summarized the basic characteristics of DELLA proteins, the transduction of hormone and environmental signals, as well as the regulation of plant growth and developments. DELLA proteins have broad application prospects in modern agricultural production in the future, but the molecular mechanism of DELLA proteins regulating plant growth and development are still unclear, and needs further study.
24GHz Digital beamforming radar with T-shaped antenna array for three-dimensional object detection

This paper introduces a radar system for three-dimensional (3D) object detection and imaging. The presented 3D measurement method combines the frequency-modulated continuous wave (FMCW) approach for range measurements with a multiple-input multiple-output (MIMO) technique for digital beamforming in two dimensions. With an orthogonal arrangement of the antenna arrays for transmit and receive, the angular information is obtained in azimuth and elevation without mechanical beamsteering. The proposed principle allows performing 3D imaging by means of the acquired range, azimuth, and elevation information with a minimum of required hardware. Starting from the realization of the 3D radar imaging concept, the hardware architecture and the developed prototype are discussed in detail. Furthermore, the object detection capability of the 3D imaging radar system is demonstrated by measurements. The results show that the introduced 3D measurement concept in its realization is well suited for numerous applications.
ImproveCog, a cognitive stimulation program for people with mild cognitive impairment and dementia: First stage of development

Cognitive stimulation seems to be an important tool to slow the rate of cognitive decline due to dementia. This study describes the development of a cognitive stimulation program (ImproveCog) for people with Mild Cognitive Impairment, Alzheimer’s Disease, and behavioral variant Frontotemporal Dementia, within the Medical Research Council framework. Stage 1 established the theoretical and evidence basis of the program through a review of the existing cognitive stimulation programs as well as cognitive exercises and their efficacy (Pre-Clinical Phase) and includes qualitative testing through five focus group with eighteen health professionals and twelve individual interviews with people with cognitive impairment (Phase I - Modeling). An initial version of the program, which consisted of twelve 90-min weekly sessions and included a manual with cognitive stimulation exercises to be performed at home, was ready to be implemented in a pilot study to create a final version of ImproveCog.
A Detailed Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

Teaching computing in K-12 is often introduced focusing on algorithms and programming concepts using block-based programming environments, such as App Inventor. Yet, learning programming is a complex process and novices struggle with several difficulties. Thus, to be effective, instructional units need to be designed regarding not only the content but also its sequencing taking into consideration difficulties related to the concepts and the idiosyncrasies of programming environments. Such systematic sequencing can be based on large-scale project analyses by regarding the volition, incentive, and opportunity of students to apply the relevant program constructs as latent psychometric constructs using Item Response Theory to obtain quantitative ‘difficulty’ estimates for each concept. Therefore, this article presents the results of a large-scale data-driven analysis of the demonstrated use in practice of algorithms and programming concepts in App Inventor. Based on a dataset of more than 88,000 App Inventor projects assessed automatically with the CodeMaster rubric, we perform an analysis using Item Response Theory. The results demonstrate that the easiness of some concepts can be explained by their inherent characteristics, but also due to the characteristics of App Inventor as a programming environment. These results can help teachers, instructional and curriculum designers in the sequencing, scaffolding, and assessment design of programming education in K-12.
Towards Driver's State Recognition on Real Driving Conditions

In this work a methodology for detecting drivers' stress and fatigue and predicting driving performance is presented. The proposed methodology exploits a set of features obtained from three different sources: (i) physiological signals from the driver (ECG, EDA, and respiration), (ii) video recordings from the driver's face, and (iii) environmental information. The extracted features are examined in terms of their contribution to the classification of the states under investigation. The most significant indicators are selected and used for classification using various classifiers. The approach has been validated on an annotated dataset collected during real-world driving. The results obtained from the combination of physiological signals, video features, and driving environment parameters indicate high classification accuracy (88% using three fatigue scales and 86% using two stress scales). A series of experiments on a simulation environment confirms the association of fatigue states with driving performance.
A novel nonparametric approach for the identification of the glucose-insulin system in Type 1 diabetic patients

Abstract In this paper we consider the problem of predicting future values of subcutaneous glucose (glucose concentration in the interstitial fluid) in Type-1 diabetes patients, exploiting information on injected insulin, carbohydrates intake and past subcutaneous glucose samples measured by a Continuous Glucose Monitor sensor. Prediction can be used to warn the patient of upcoming possibly harmful events, such as hypoglycemia or hyperglycemia. In addition, an effective prediction is a key ingredient in Model Predictive Control, a technique successfully applied in the development of the so called artificial pancreas. Derivation of individualized predictors is crucial to cope with the wide inter-subject variability. For this reason we explored the application of linear black-box identification methods to derive patient-tailored predictors. Together with the mainstream technique in system identification, the Prediction Error Method, we investigate a novel and promising nonparametric method based on Gaussian regression. The considered methods are applied to data collected on 20 subjects, during two 21-hours hospital admissions for each subject. One of the major challenges of this problem is that the available dataset is short and the glucose-insulin system has very high complexity. The quality of the prediction was compared on the basis of three metrics commonly used in system identification, namely Coefficient of Determination, Fit and Root Mean Squared Error. On a system identification perspective the present work is a comparison of a novel system identification approach with the state-of-the-art one on a particularly difficult and relevant case of study. The nonparametric technique improves prediction performance and reduces computational burden associated with predictor identification.
A framework for comparative evaluation of lean performance of firms using fuzzy TOPSIS

Adoption of lean practices is considered a vital strategic tool for firms to thrive in today’s competitive times. Comparative evaluation of leanness of the companies has assumed crucial importance in the wake of increasing globalisation and phenomenal advancement in technology. Evaluation of policies and practices on an ongoing basis helps organisations identify the potential opportunities for improvement. Only limited efforts devoted to assessing the relative lean status of firms have been made so far and there is an express need to articulate a framework for measurement of lean adaptation. Here, a systematic fuzzy multi-criteria decision making (MCDM) evaluation model based on technique for order preference by similarity to ideal solution (TOPSIS) is proposed for relative lean ranking of firms. Fuzzy set theory concepts are used to deal with problems of vagueness, uncertainties, inexactness of data and the subjectivity associated with human judgment. An illustrative numerical example is included to elucidate the computational process. Sensitivity analysis is also carried out to demonstrate the robustness and efficacy of the adapted methodology.
Estudo de caso de trabalhos de conclusão de curso do ensino superior em Design Gráfico e Digital: A experiência IED

Neste artigo, professores do curso de Design Gráfico e Digital do Istituto Europeo di Design (IED SP) realizam um mapeamento da produção de Trabalhos de Conclusão de Curso (TCCs) executados sob sua supervisão de 2016 a 2019 a fim de verificar como as temáticas pesquisadas e os projetos realizados neste período foram se ajustando às diretrizes do Projeto Pedagógico do Curso e aos contextos e dilemas que formam as práticas acadêmicas e profissionais no campo do design. A primeira seção traz um panorama das principais questões teóricas que animam o debate das relações entre a pesquisa e a prática do design. Na segunda seção, aborda-se a importância do TCC para o desenvolvimento do perfil do egresso para, então, na terceira seção, se concentrar nos procedimentos de amostragem e na análise de exemplos de TCCs, tendo como objetivo a identificação da produção baseada no reconhecimento de padrões temáticos e metodológicos resultantes do processo de orientação.