Miracle-dz/UniFAR-FTUs huggingface dataset:
Examination and Evaluation of High-Efficiency Motor Drive Using Motors for Electric Vehicle Equipped with Optimization Algorithms

We have proposed a novel control method that in which proportional-integral (PI) control and optimized control are combined to stabilize permanent-magnet synchronous motors (PMSMs) for electric vehicles (EVs). The inverter current, which maximizes the torque and minimizes power, is calculated by the optimized control method. The simulations and experiments were performed to verify the effectiveness of the control. The experiment was carried out using the RX62T microcomputer, which is an IC for automobile control, and a digital control system (PE-Expert4). Compared with the conventional speed PI control, the optimized control suppresses the decrease in motor speed and shortens the recovery time. As a result, we confirmed that the responsiveness was improved by 33%. From this result, the optimized control method, which simultaneously controls and monitor speed, was shown to be effective in solving the problems of the conventional method.
94 GHz Three-Dimensional Imaging Radar for Environmental Detection

At present, With the development of technology, the high resolution of millimeter wave (terahertz) can be applied to environmental sensing imaging. In this paper, Using the frequency-modulated continuous-wave (FMCW) radar technique with a 1GHz bandwidth, we show experimentally that a high-resolution real time imaging radar operating at 93.5–94.5GHz is capable of detecting different car models at standoff ranges of 12 m. We also achieved 3D high-resolution imaging of the building. at 140 meters
Hybrid Architecture of Face and Action Recognition Systems for Proctoring on a Graphic Processor

A solution has been developed due to problem of face recognition and actions when we are trying to process images of human faces in real time on the server. Approaches to solving the problem of face recognition and actions on images are considered. The solution of the problem of action’s recognition in real time is considered. An action recognition system was used for proctoring.A hybrid architecture was developed for face and action recognition. The FaceNet algorithm was used to implement the system. We used the faces of a person that was filmed to collect the dataset. The results obtained show a high accuracy of the face recognition percentage. Face and motion recognition is implemented in Windows Server 2016. A special web application was developed to test these algorithms.To reduce processing time and recognition algorithms were used like bandwidth, resize images. In addition, the entire process of video processing for proctoring was launched in the graphics server. With the web app, you can see how well the face recognition algorithm and the result of the action recognition algorithm are.
Limiting Viral Spread: Automated Cyber Operations and the Principles of Distinction and Discrimination in the Grey Zone

The fact that States resort to automated cyber operations like NotPetya, which spread virally and have indiscriminate effects, raises the question of how the use of these might be regulated. As automated operations have thus far fallen below the threshold of the use of force, the letter of international humanitarian law (IHL) does not provide such regulation. In IHL, the principles of distinction and discrimination hold that attacks should in their targeting distinguish between the civilian population and combatants, and between civilian objects and military objectives. Attacks must not be indiscriminate, and operations that might foreseeably spread to affect civilian objects are prohibited. This paper draws inspiration from the legal principles of distinction and discrimination to suggest a non-binding norm for responsible State behaviour with regard to automated operations that fall below the threshold of the use of force: the norm proposes that States should design cyber operations so as to prevent them from indiscriminately inflicting damage. The paper finds that in the case of automatedcyber operations, a distinction between the nature of the operation and the use of the operation does not make sense because the design (nature) of the malware defines the use. In order to conform with the norm, responsible States should conduct a review of cyber operations prior to their execution. Finally, as the paper illustrates with a comparative analysis of NotPetya and Stuxnet, the post-incident forensic analysis of an operation can allow third parties and victims to determine whether the operation's designer conformed with the norm. This can help set a normative benchmark by providing a basis upon which States may call out unacceptable behaviour.
Design of UWB Patch Antenna with 5G Lower Band Notch Characteristics Using Ring Shape Resonator

ASEAN countries have proposed fifth generation (5G) forums for 5G applications at a frequency of 4.5–5.5 GHz and band stop antenna for 5G lower band from 4.5 GHz to 5.5 GHz. One UWB antenna have been designed and proposed by using RT 5880 with partial grounding on rectangular patch and ring shape resonator (RSR) on the ground. A single band notched UWB antenna were designed for 5G lower band application by using a rectangular slot at the top of the radiating patch and by adding RSR on ground plane of UWB antenna. The VSWR, return loss, gain and 2-D radiation pattern, surface current, radiation efficiency as well as gain prove that the proposed antenna has excellent performance in notched band and entire UWB band bandwidth frequencies. Therefore, the proposed antenna is also an excellent candidate for lower band 5G wireless applications.
Low-Inductance Asymmetrical Hybrid GaN HEMT Switching Cell Design for the FCML Converter in High Step-Down Applications

Proper utilization of GaN devices generally necessitates ultra-low inductance printed circuit board (PCB) layout in the main commutation loop or switching cell of a power converter. The flying c apacitor m ultilevel ( FCML) t opology in particular contains many of these switching cells, thus design optimization becomes critical. A novel asymmetrical cell layout design with sub-1 nH commutation loop inductance is proposed and characterized for the FCML by utilizing a transient- and impedance-based measurement technique in conjunction with 3D field simulation. To validate its efficacy, this switching cell design is demonstrated within a prototype high performance step-down intermediate bus converter supply (vout = 48 V) with wide input voltage range (vin = 48 to 340 V).
New Topology Of Asymmetrical Nine-Level Cascaded Hybrid Bridge Multilevel Inverter

recently the researchers in multilevel inverter (MLI) have interested in reducing the number of switches and sources with acceptable total harmonic distortion (THD %) of the output voltage waveform to reduce losses and costs. This paper present a new concept of asymmetrical cascaded hybrid bridge multilevel inverter (ACHB-MLI) to produce nine-level output waveform with only seven switches and two DC supplies instead of sixteen switches and four DC supplies used in the conventional cascaded hybrid bridge multilevel inverter (CHB-MLI). The proposed topology is investigated under phase disposition pulse width modulation technique (PD-PWM) and the results have been compared with conventional cascaded multilevel inverter. The simulation results are provided using MATLAB Simulink.
Forecasting Accuracy Improvement of Solar Power Plant's Generation

Forecasting RES generation is an important task both in finding the optimal location for newly commissioned RES generation facilities, and in solving problems of existing electric power systems with a high share of RES. Therefore, obtaining high accuracy of forecasting results is one of the main conditions for the successful development of renewable energy sources. This paper studies ways to improve the accuracy of forecasting the solar power plant generation using machine learning methods. The paper describes the application of preprocessing and preparation of initial data on the forecasting accuracy. The paper also analyzes the application of three different regression models to solving the forecasting problem and gives an accuracy evaluation of each of the models.
Fuzzy Logic based Handover Management in Small Cell Networks

In order to meet high data traffic demands in fifth generation (5G) networks, many small cells (eNBs) are needed. This approach is used in next-generation wireless communication to increase network capacity and coverage in dense networks. However, this approach can cause handover delays and unnecessary handover (ping-pong effect). In order to overcome these problems, fuzzy logic-based handover management has been proposed in small cell networks. In fuzzy logic-based handover management, mobile nodes select the most suitable small cells with RSSI, SNR, and Jitter parameters. Thanks to this approach, mobile nodes determine the most suitable small cells with fuzzy logic decision mechanism in next generation 5G small cell networks. Fuzzy logic-based handover management and traditional handover algorithm have been compared using delay and handover numbers. According to the results, it has been observed that the proposed approach gives more successful results than the traditional handover algorithm.
POSTER: Leveraging PIFO Queues for Scheduling in Time-Sensitive Networks

Time-Sensitive Networking emerged as a convergent Ethernet-based real-time networking standard for industrial applications. To support real-time, jitter-free isochronous traffic the corresponding TSN mechanism denoted Time Aware Shaper requires special hardware support. In this work, we propose a path to building TSN networks on top of programmable switches. Specifically, we show here how to leverage a data structure amenable to programmable data planes known as Push-in First-out (PIFO) queue to support TSN traffic scheduling for isochronous real-time, as well as, best effort traffic.
Artificial Intelligence Assisted Parametric Design by Splitting Inductance in Dual Active Bridge Converter

There is abundant research about achieving zero-voltage switching (ZVS) of dual active bridge (DAB) converters, among which the splitting of interfacing inductance and placing on both sides of the transformer is an effective method for extending the ZVS region for all the switching devices. However, the traditional analytical model can hardly imitate the proposed converter precisely under the high switching frequency (i.e.>1MHz) due to the complex converter model with the consideration of the parasitic components. Thus, the converter system can be regarded as a gray-box model. Consequently, artificial intelligence (AI) techniques can be utilized for the targeted optimization inside this gray-box. In this case, a genetic algorithm is employed in the DAB converter parametric design with an explicit fitness desire. The methodology of implementing AI techniques into converter parametric design is introduced and verified with a 1 MHz Gallium Nitride (GaN) based DAB converter prototype.
Machine-learning-based telemetry for monitoring long-haul optical transmission impairments: methodologies and challenges [Invited]

Current management of optical communication systems is conservative, manual-based, and time-consuming. To improve this situation, building an intelligent closed-loop control system is becoming an active topic of the industry. One of the key techniques to achieve such a management system is physical layer impairment telemetry, with the help of which the controller can make proper instructions. However, it is challenging to implement an accurate telemetry module due to the complex mechanisms of various impairments. To overcome that, many studies have been done. In this paper, those recent studies are reviewed, and the design of telemetry is discussed systematically. We analyze metrics for evaluating system performance and mechanisms of various impairments comprehensively, which are the theoretical foundations for designing telemetry modules. We then summarize a unified workflow for designing telemetry modules based on the review of previous works. Its effectiveness is then verified by concrete use cases of our previous studies. Finally, we discuss the challenges of deploying machine-learning-based telemetry techniques in optical communication systems.
Role of Biomarker in COVID-19: A Study from Tertiary Care Center

Background: The COVID-19 infection affects all age groups and both genders. Recent studies have suggested that elder subjects are more prone to COVID-19 infection and its complications compared to young and middle-aged subjects. To investigate COVID-19 infection affecting patients with different age groups (young age, middle age and elder age) with biomarkers. Methods: Data was collected retrospectively from Yashoda Hospital Hyderabad, and study period from April 2020 to October 2020. Results: Out of 115 patients, men were 83 (72.3%) mean age was 55.7 ± 14.5 years (age range 18 to 89 years) mean duration of hospital stay was 10.9 ± 6.0 days (stay in hospital range 6 to 29 days). Hypertension was seen in 24 (20.8%), diabetes in 12 (10.4%), previous history of cardiovascular disease in 11 (9.5%) and previous history of cerebrovascular disease in 6 (5.2%). Mechanical ventilator support was required in 21 (18.2%), lung area affected on CT chest appearance was less than 25% in 50 (43%), 25% to 49% in 35 (30.4%), ≥ 50% in 30 (26%). Mean C-Reactive Protein (CRP) value was 68.7 ± 18.6 mg/L, mean D-dimer 1471.8 ± 591.4 ng/ml, mean procalcitonin 1787.1 ± 550.8 ng/ml, mean interleukin-6 was 11.4 ± 3.8pg/ml and mean serum ferritin was 428 ± 167.9 ng/ml. Among the age groups, 17.3% were young, 38.2% were middle aged and 44.3% were elderly and the overall mortality was 4.3%. The elder age group was significantly associated with longer mean duration of hospital (p=0.02), higher mean CRP value (p=0.006), mean D-dimer value (p<0.0001), mean procalcitonin (p<0.001), mean interleukin-6 (p=0.001), mean serum ferritin (p=0.001) values compared to young and middle age patients. Conclusion: Our study found elder age group constituted 44.3% of COVID-19 infected patients and inflammatory markers CRP, D-dimer, procalcitonin, interleukin-6 and serum ferritin levels were significantly higher in them.
Investigations into the thermodynamic, kinetic, and structural properties of TCR -- peptide/MHC interactions

by Kathryn Michelle Armstrong The protein-protein recognition event that occurs at the interface between a T cell receptor (TCR) and a peptide presented by a major histocompatibility complex molecule (peptide/MHC) is essential to the adaptive immune system. This work examines TCR binding thermodynamics and compares these measurements to structural and functional features to gain insight into the determinants of TCR specificity, cross-reactivity, and binding affinity. We have been studying the A6 TCR, which recognizes the Tax peptide presented by the class I MHC HLA-A2. We examined the A6-Tax/HLA-A2 complex formation via isothermal titration calorimetry (ITC) in order to study the thermodynamics of binding. However, binding caused a pKa shift in one or more ionizable groups, indicated by binding thermodynamics that varied with solution conditions. Calorimetric experiments with a variety of buffers, pH values, and temperatures were used to characterize the A6Tax/HLA-A2 interaction. The data were fit globally to extract the intrinsic binding Kathryn Michelle Armstrong thermodynamic parameters. These parameters were compared to structural properties to help elucidate the basis for molecular recognition in this system. Additionally, a high-affinity A6 TCR mutant, A6c134, binding to Tax/HLA-A2 was examined. The A6c134 variant has an approximately 800-fold stronger affinity for Tax/HLA-A2 as measured by SPR. This increase in affinity is due to a significantly slower off-rate for the A6c134-Tax/HLA-A2 complex than for the wild-type A6 counterpart. Crystallographically, the topology of the mutant and wild-type complex are similar, with small differences at the interface. Calorimetric data indicate that the A6c134 mutant binds Tax/HLA-A2 with opposing thermodynamics as compared to the wild-type interaction. Overall, the studies of A6 and A6c134 binding their cognate ligand, Tax/HLA-A2, have shown that each TCR binds with different thermodynamics and kinetics, despite maintaining similar binding footprints. Further studies on the movement of the CDR loops are proposed to give insight to the ground state of the TCRpMHC interaction and the binding pathway behind the observed thermodynamic and kinetic parameters.
Design of Thickened Fluids Rich in Proteins Intended for Dysphagia Management

Results of the design of food products that behave as structured fluids and that deliver attributes tailored for dysphasic people are presented in the paper. Dysphagia refers to any disruption in the swallowing processes. Dietary strategies for dysphagia management may include altering food textures and modifying liquid consistencies, while maintaining a high nutritive profile and acceptable sensory attributes. Products presented in the paper are designed by taking into account sustainability criteria. Further knowledge is needed at the product’s mesoscale to improve physical behaviour of the designed structured fluids.
Recent advances in the synthesis of hierarchically porous silica materials on the basis of porous glasses

The thermal phase separation and subsequent leaching of sodium borosilicate glasses is a well established route for the preparation of porous glasses exhibiting adjustable pore sizes in the range of 1 nm up to almost 1 μm as well as a very flexible geometric shape. The combination of this route with a large spectrum of synthesis strategies for the implementation of an additional pore system enables the preparation of hierarchically porous glass-based materials. This review covers a wide range of preparative routes for hierarchically porous silica materials starting from the sodium borosilicate glass with a special emphasis on the very recent developments in this versatile field of materials engineering.
Controlled Synthesis of Tellurium Nanostructures from Nanotubes to Nanorods and Nanowires and Their Template Applications

In the present study, we report a facile hydrothermal route developed to synthesize various 1D tellurium nanostructures including nanotubes, nanowires, and nanorods on a large scale. Te nanotubes with a tunable diameter from 200 nm to 2 μm are fabricated in NaOH solution. With poly(vinyl pyrrolidone) as the surfactant, ultrathin Te nanowires with a diameter of 5−8 nm are synthesized in NaOH solution. However, in both cases, only Te nanorods are obtained if NaOH is not added. The formation of Te nanotubes is attributed to the depletion of Te atoms at the surface of seeds. The influence of the reaction conditions including pH value, reaction temperature, reducing agent, and reactant concentration on the size and morphology of the Te nanostructures is investigated and the structural evolution with different growth rate is illustrated. A reduction reaction rate controlled growth mechanism has been proposed for the variable nanostructures. In addition, the obtained Te nanostructures are ideal templates to synt.
Behaviour of Uniaxial Reinforced Concrete Columns Strengthened with Ultra-High Performance Concrete and Fiber Reinforced Polymers

This article investigates the behaviour of strengthened concrete columns using jacketing ultra-high-performance fiber reinforced concrete (UHPFRC) and carbon fiber-reinforced polymer (CFRP) under uniaxial loaded. The jacket was connected to the column core using shear connectors and (CFRP) fixed as a strip on the tension zone between the column cores and the jacketing. Seven column samples of square cross-section (120 x120) mm at the midsection with overall length of 1250 mm were cast using normal strength concrete (NSC) and having similar longitudinal and transverse reinforcement. The samples were made and tested under axial load at eccentricity equal to 120 mm up to failure. Test parameters were the thickness of jackets (25 and 35) mm and the width of CFRP (0,8, and 12) cm. Column specimens were tested, one of them was reference without any strengthening, and the other specimens divided into two groups (A, and B), and each group included three specimens based on the parameters. Group (A) has UHPFRC jacket thickness 25 mm and CFRP width (0,8, and 12) cm respectively, and group (B) has UHPFRC jacket thickness 35 mm and CFRP width (0,8, and 12) cm respectively. The outcomes of the article show that increasing the thickness of jacket, and width of CFRP lead to increase in the load carrying capacity about (110.5%,168.4%, and 184.2%) for group A, and (157.9%,226.3%, and 263.2%) for group B compared with the reference column due to delay in the appearance of cracks and their distribution. The mid-height lateral displacement of columns was decreased about (66.6%,42.3%, and 35.9%) for group A, and (46.15%,38.46%, and 32.3%) for group B, also the axial deformation of specimens decreased about (71.7%,60.86%, and 55.86%) for group A, and (65.5%,60.5%, and 53.4) for group B compared with the reference column. The ductility of columns that were strengthened with UHPFRC jacket only was increased about (13.67%,19.66%) for thickness(25,35) mm respectively, because of that UHPFRC jacket was contented on steel fibers, and the percentage decrease of ductility was about (5.1%,and 12%) for group (A), (1%,and 9.4%) for group (B) when bonded CFRP in the tension zone with width (8 ,and 12) cm respectively. The results show improvement in the initial and secant stiffness when, increased the thickness of jacket, and width of CFRP because of increase in the size of columns and improvement in the modulus of elasticity. The toughness increase was about (273.97%,301.55%, and 304.5%) for group A, and (453.69%,511.93%, and 524.28%) for group B compared with the reference column because of increase in the size of specimens and delay the appearance of cracks.
Comparison of Various Detection Systems Coupled to High Performance Liquid Chromatography for Determination of Tocopherols in Meat. The Influence and Comparison of the Most Popular Sample Preparation Method

The presented data are of practical importance in terms of vitamin E determination in meat and other foodstuffs. Selection of a proper separation and detection method as well as sample preparation protocol might affect the reliability of results. Application of a sensitive method and such sample preparation procedures that do not cause significant degradation of the analyte ensures the reliability of the results. The conducted research has proved that the fluorescence detector (FLD) is the most sensitive of the detection systems tested and provides the LOD values in 3.8-38.5 ng ml-1 range. Ion trap was proved to be less a sensitive detector against vitamin E when compared to FLD. When atmospheric pressure chemical ionisation (APCI) was utilised the LOD values observed for γ- and α- tocopherole were 0.2 and 0.5 μg ml-1, respectively. However when atmospheric pressure photo/chemical ionisation (APPI/APCI) was used a significant increase in the ionization efficiency of δ-tocopherol was observed, which caused increases in the instrument sensitivity (LOD=1.0 μg ml-1). Sample preparation protocol based on extraction of the biological sample with ethanol and hexane with simultaneous change in partitioning coefficient, results in significantly higher recovery rates when compared to methods based on sample saponification and extraction with other solvents. Vitamin E contents in the tested pork samples were found to be in the 0.0-6.0 mg kg-1 range, depending on the determination method utilised.
PALLADIUM CATALYZED CROSS-COUPLING REACTIONS FOR THE SYNTHESIS OF 2,5-DISUBSTITUTEDFURANS

: A convenient synthesis of 2,5-bisarvlfurans, 2,5-bisbenzylfurans and 2,5-bisbenzoyIfurans employing 2.5-bis(tri-n-butylstannyl)furan and palladium catalyzed cross-coupling reactions is described.