bluuebunny/crossref_metadata_2025_split huggingface dataset:
Uncertainty of PIV/PTV based Eulerian pressure estimation using velocity uncertainty
Authors: Zhang Jiacheng , Bhattacharya Sayantan , Vlachos Pavlos P 
Published: February 2022

Abstract
This work introduces a method to estimate the uncertainty of the pressure fields reconstructed from particle image velocimetry / particle tracking velocimetry (PIV/PTV) measurements by propagating the instantaneous velocity vector uncertainty through the pressure reconstruction. The uncertainty propagations through the calculation and integration of pressure gradients are modelled as linear transformations. The autocorrelation coefficient was modelled and incorporated in the uncertainty estimation to reproduce the effect of the autocorrelation of velocity errors on the reconstructed pressure’s accuracy. The method was first tested on synthetic velocity fields contaminated with varying levels of artificial noise correlated in space, time, or between components. The error analysis shows that the proposed method could predict the spatiotemporal variations of the pressure errors. The estimated pressure uncertainty also captures the effects of the velocity noise level, the autocorrelation, and the different pressure-gradient integration methods, with more than 80% accuracy in most test cases. The method was applied to an experimental vortex ring flow with planar PIV and a laminar pipe flow with volumetric PTV. The error analysis shows that the obtained pressure uncertainty possessed similar spatial and statistical distributions as the pressure errors. The results also indicate that the performance of the proposed uncertainty estimation method depends on the accuracy of the velocity uncertainty. The proposed uncertainty estimation method exhibits reliability in obtaining the local and instantaneous pressure uncertainty from the PIV/PTV measurements.
A high performance trench gate tunneling field effect transistor based on quasi-broken gap energy band alignment heterojunction
Authors: Chen Shupeng , Wang Shulong , Liu Hongxia , Han Tao , Zhang Hao 
Published: February 2022

Abstract
In this letter, a tunneling field effect transistor based on quasi-broken gap energy band alignment (QB-TFET) is proposed and investigated by simulation method. To offering high on-state current, InGaAs/GaAsSb heterojunction with quasi-broken gap energy band alignment is applied to QB-TFET to improve the band-to-band tunneling rate. Trench gate structure and InGaAs pocket layer are applied to further increase the tunneling efficiency. To suppress the leakage current caused by the off-state tunneling path from source to drain, an intrinsic InGaAs spacer is inserted between n+ InGaAs drain and p+ GaAsSb source. In order to further improve the control ability of gate voltage on channel, TiO2 is used as the gate dielectric of the proposed QB-TFET. Moreover, the effect of x and y fraction of In
x
Ga1–x
As and GaAs
y
Sb1–y
on quasi-broken gap tunneling junction are studied in this work. The electrical characteristic change of QB-TFET with different x and y fraction is analyzed. The proposed QB-TFET is compared with other works and shows an obvious advantage on performance. As a result, a large on-state current (I
on) of 921 μA μm−1 can be obtained. Moreover, steep average subthreshold swing (SSavg) of 4.9 mV/dec can be achieved when I
on = 1 μA μm−1.
Tuning the interfacial friction force and thermal conductance by altering phonon properties at contact interface
Authors: Dong Yun , Ding Yusong , Rui Zhiyuan , Lian Fangming , Hui Weibin , Wu Jie , Wu Zhiguo , Yan Pengxun 
Published: February 2022

Abstract
Controlling friction force and thermal conductance at solid/solid interface is of great importance but remains a significant challenge. In this work, we propose a method to control the matching degree of phonon spectra at the interface through modifying the atomic mass of contact materials, thereby regulating the interfacial friction force and thermal conductance. Results of Debye theory and molecular dynamics simulations show that the cutoff frequency of phonon spectrum decreases with increasing atomic mass. Thus, two contact surfaces with equal atomic mass have same vibrational characteristics, so that more phonons could pass through the interface. In these regards, the coupling strength of phonon modes on contact surfaces makes it possible to gain insight into the nonmonotonic variation of interfacial friction force and thermal conductance. Our investigations suggest that the overlap of phonon modes increases energy scattering channels and therefore phonon transmission at the interface, and finally, an enhanced energy dissipation in friction and heat transfer ability at interface.
SuPART: supervised projective adapted resonance theory for automatic quality assurance approval of radiotherapy treatment plans
Authors: Kamran Hootan , Aleman Dionne M , McIntosh Chris , Purdie Thomas G 
Published: February 2022

Abstract
Radiotherapy is a common treatment modality for the treatment of cancer, where treatments must be carefully designed to deliver appropriate dose to targets while avoiding healthy organs. The comprehensive multi-disciplinary quality assurance (QA) process in radiotherapy is designed to ensure safe and effective treatment plans are delivered to patients. However, the plan QA process is expensive, often time-intensive, and requires review of large quantities of complex data, potentially leading to human error in QA assessment. We therefore develop an automated machine learning algorithm to identify ‘acceptable’ plans (plans that are similar to historically approved plans) and ‘unacceptable’ plans (plans that are dissimilar to historically approved plans). This algorithm is a supervised extension of projective adaptive resonance theory, called SuPART, that learns a set of distinctive features, and considers deviations from them indications of unacceptable plans. We test SuPART on breast and prostate radiotherapy datasets from our institution, and find that SuPART outperforms common classification algorithms in several measures of accuracy. When no falsely approved plans are allowed, SuPART can correctly auto-approve 34% of the acceptable breast and 32% of the acceptable prostate plans, and can also correctly reject 53% of the unacceptable breast and 56% of the unacceptable prostate plans. Thus, usage of SuPART to aid in QA could potentially yield significant time savings.
Tri-stable stochastic resonance coupling system driven by dual-input signals and its application in bearing fault detection
Authors: Zhang Gang , Zeng Yujie , He Lifang 
Published: February 2022

Abstract
Stochastic resonance is of great significance for extracting fault signals of bearings. A novel tri-stable stochastic resonance coupling system driven by dual-input signals(DTDTSR) is proposed in this paper, which significantly improve Spectral Amplification(SA) and amplitude of traditional two-dimensional tri-stable stochastic resonance system(TDTSR). Firstly, under the condition of adiabatic approximation theory, the Steady-state Probability Density(SPD), Mean First Pass Time(MFPT) and SA are derived, and the system parameters’ influence on them are analyzed. Then, using SA as the measurement index, numerical simulations are carried out and system parameters are optimized by adaptive genetic algorithm to achieve optimal performance. So DTDTSR, TDTSR and classical tri-stable stochastic resonance system(CTSR) are applied to weak periodic signals detection and compared with each other. The experimental results show that DTDTSR has a large SA and amplitude, which proves that the synergistic effect of coupled system and dual input signal drive can better promote the generation of stochastic resonance. Finally, the three systems and wavelet transform method are applied in two kinds of engineering bearing fault detection, and adaptive genetic algorithm is also used to optimize the system parameters. The experiments reveal are similar to the previous one, proving that DTDTSR is indeed optimal among the three systems. This system is therefore very adaptable and advanced in practical engineering applications.
Solving time-dependent Schrödinger equation in momentum space with application to strong-field problems
Authors: Jheng Shih-Da , Jiang Tsin-Fu 
Published: February 2022

Abstract
We present a numerical method to solve the time-dependent Schrödinger equation (TDSE) in momentum representation (p-space). We show that the method is practically useful and easier than the coordinate space (r-space) method when continuous states are involved. For a single-active electron (SAE) atom, the numerically complete eigenset can be accurately constructed in p-space by quadrature method which bypasses the singularities in the Coulombic kernel. Although there is an ingenious Lande subtraction for dealing with the singularity but is not straightforward. We formulate the time marching algorithms for an SAE atom in linearly polarized (LP) laser pulse and in circularly polarized (CP) pulse, respectively. We show calibrations to literature results to justify the formulations. Argon in a resonant and a nonresonant CP pulse are investigated and show distinct properties from the case of tunneling regime. Together with the currently available powerful graphics processing unit (GPU) for massively parallel computing, the p-space method could provide a useful alternative tool for some problems such as atoms in intense light pulses.
Inflation with 0 ≤ c
s ≤ 1
Authors: Gorji Mohammad Ali , Motohashi Hayato , Mukohyama Shinji 
Published: February 2022

Abstract
We investigate a novel single field inflationary scenario which allows
a transition between a slow-roll k-inflation with c
s of order unity
and a ghost inflation with c
s ≃ 0, where c
s is the sound
speed for the curvature perturbations. We unify the two phases
smoothly by appropriately taking into account a higher derivative
scordatura term, which is always there from the effective field theory
point of view but which becomes important only in the c
s ≃ 0
regime. The model achieves the whole range of 0 ≤ c
s ≤ 1
avoiding strong coupling and gradient instability, and allows us to
access the c
s ≃ 0 regime in a self-consistent manner. We also
discuss implications to the formation of primordial black holes.
Design of RFSoC-based Digital Phased Array Feed (PAF) and Hybrid Architecture Beamforming System
Authors: Pei Xin , Wang Na , Werthimer Dan , Duan Xue-Feng , Li Jian , Ergesh Toktonur , Liu Qi , Cai Ming-Hui 
Published: February 2022

Abstract
As the number of array elements and bandwidth increase, the design challenges of the Phased Array Feed (PAF) front-end and its signal processing system increase. Aiming at the ng-PAF of the 110 m radio telescope, this article introduces the concept of fully digital receivers and attempts to use Radio Frequency System-on-Chip (RFSoC) technology to digitize close to the feed array, reduce the complexity and analog components of the front-end, and improve the fidelity of the signals. The article discusses the digital beamforming topology and designs a PAF signal processing experimental system based on RFSoC+GPU hybrid architecture. The system adopts a ZCU111 board to design RF-direct digitization and preprocessing front-end, which can sample eight signals up to 2.048 GSPS, 12 bit, channelize the signals into 1024 chunks, then reorder into four data streams and select one of the 256 MHz frequency bands to output through four 10 Gb links. A GPU server is equipped with four RTX 3090 GPUs running four HRBF_HASHPIPE instances, each receiving a 64 MHz bandwidth signal for high-throughput real-time beamforming. The experimental system uses a signal generator to emulate Sa-like signals and propagates through rod antennas, which verifies the effectiveness of the beamforming algorithm. Performance tests show that after algorithm optimization, the average processing time for a given 4 ms data is less than 3 ms in the four-GPU parallel processing mode. The RFSoC integrated design shows significant advantages in power consumption and electromagnetic radiation compared with discrete circuits according to the measurement results.
Topology Identification of the Hindmarsh-Rose Model via Deterministic Learning
Authors: Chen Danfeng , Li Junsheng , Cai Yuping 
Published: February 2022

Abstract
In this paper, the complex dynamic behavior of the Hindmarsh-Rose (HR) model which characterizes the neuron cell is analyzed numerically. And the unknown topology of the system in dynamic environment is locally accurately identified based on the deterministic learning (DL) algorithm. Firstly, the influence of different parameters on the dynamic behavior of the HR model are investigated. Then, the nonlinear dynamics of the HR model under unknown dynamic environment is locally accurately identified. In addition, the identified system dynamics can be stored in the form of constant neural network. The achievement of this work can provide more incentives and possibilities for the application of HR model in clinic and other related researches. Simulation studies are included to demonstrate the effectiveness.
3D-RPP: a novel 3D vision-based Pose Perception Approach for Industrial Robots
Authors: Li Mo , Niu Jianwei , Dou Yuanbo , Ren Tao , Li Qingfeng , Yu Xiaolong 
Published: February 2022

Abstract
Enhanced by artificial intelligence, industrial robots are becoming more powerful, gaining a large variety of applications in intelligent factories. Pose perception, the aim of which is to obtain the joint coordinates of the robot in the camera coordinate system, has been proposed as a promising technology for multi-robot intelligent interaction. A large number of efforts have been made on studying robot pose perception. However, most of existing studies estimate the position of robot joints in 3D space by just using 2D color images, and perform pose perception by estimating the position of joint key points in the image, which could become infeasible in scenarios with various camera views and background environments. To address the issue, considering the information about the robot itself as a prior knowledge, we propose a novel approach for robot pose perception, named 3D-RPP. We adopt a 3D visual point cloud to estimate the rigid transformation of the camera coordinate system with respect to the robot base coordinate system, which effectively improves the accuracy of the obtained robot joint position in the camera coordinate system. We conduct extensive experiments on ROKAE xMate3 robot to investigate the performance of 3D-RPP, and the experimental results show that 3D-RPP could solve the pose perception problem well.
Techno-economic assessment of a hybrid solar PV/syngas/battery power system for off-grid application: Long Pahangai-Indonesia case study
Authors: Aditya I A , Simaremare A 
Published: February 2022

Abstract
This paper presents the design of the hybrid renewable energy system (HRES) composed of photovoltaic, batteries, biomass gasifiers, and diesel generators to determine the optimal configuration of the system located in Long Pahangai, Indonesia. Long pahangai is one of the remote villages in Indonesia that has not enjoyed 24-hour electricity. This paper presents optimal modeling of the Hybrid Optimization Model for Electric Renewable (HOMER) to find the most cost-effective configurations for electricity requirement of 1.219,1 kWh/day primary load. The results suggest that a PV-Diesel-Gasifier-Battery system is the best optimal design for Long Pahangai in terms of cost of energy (COE) and Total Net Present Cost (TNPC). The sensitivity analysis also identifies the influence of diesel price, biomass price, biomass gasification ratio, substitution ratio, and minimum fossil fraction.
Fuel spray and flame characteristic of biodiesel blend for CFB coal-fired steam power plant start-up process
Authors: Sitanggang Ruly Bayu , Hapsari Tiva Winahyu Dwi , Alif Hamdan Hartono , Cahyo Nur 
Published: February 2022

Abstract
This study aims to obtain the spray and flame characteristics of biodiesel blend fuel used in the ignition system of a Circulating Fluidized Bed (CFB) coal-fired steam power plant. Characterization of the chemical composition, physics of fuel, handling of biodiesel in handling system to the burner, and the characterization of combustion in the burner simulator are studied. The primary data in this study is the data from the combustion trial results in the burner simulator, while the secondary data is in the form of operation data and power plant design data. Biodiesel has properties close to diesel oil and allows use in blending to a specific ratio. The result shows that the spraying angle of biodiesel and blends are narrower than the B0 condition, and the distance of flame become shorter along with the increase in biodiesel content. These phenomena can cause the burner difficult to ignite, which can be overcome by adjusting the igniter position into the fuel spray distribution zone. Because biodiesel is easily oxidized, it is necessary to maintain the fuel lines kept clean, primarily when the system is not operating for a long time. Biodiesel has a higher viscosity and density than petroleum diesel which can cause problems with the injection start-up burner. The use of biodiesel fuel requires more stringent handling, adding filters, isolating fuel oil tanks from rainwater and humid air, and replacing materials that are not compatible with biodiesel in pipe fittings and gasket.
Analysis of control rod effect on the safety operation parameter of the RSG-GAS Core
Authors: Kuntoro Iman , Pinem Surian , Surbakti Tukiran 
Published: February 2022

Abstract
The operation cycle of the RSG-GAS reactor is regulated by control rod positions from the lowest to uppest positions. It is of necessary to know the effect of this control rods positions to the safety operation parameter a long the cycle. The objective of this research is to confince that the changes of safety operation parameter still meet the its safety limits. The neutronics and thermalhydraulics parameter to be observed are power peaking factor, kinetic and steady state parameters. Calculations are conducted by a combination code of WIMSD/5 and MTRDYN. The main results of maximum axial power peaking factor is 1.84 at control rod position of 20 cm. The maximum temperature of cooling, cladding and fuel are consecutively 67.18 °C, 122.26 °C, and 123.24 °C. These results lay far under safety limits of maximum temperature of coolant and fuel of 100 °C dan 200 °C at steady state operation of the RSG-GAS reactor which means that the reactor operation is safe as long as the cicle operation.
Synthesis and characterization of gadolinium nanoparticles using polyol method as a candidate for MRI Contrast Agent
Authors: Setiawan H , Triyatna F , Nurmanjaya A , Subechi M , Sarwono D A , Billah A A , Rindiyantono F 
Published: February 2022

Abstract
This research is related to the preparation and initial characterization of gadolinium nanoparticles as a Magnetic Resonance Imaging (MRI) contrast agent. Nanomaterial-based contrast agents aim to improve clearer imaging, longer examination retention times with lower toxicity than gadolinium ion-based contrast agents, and evaluate the potential use of MRI contrast agents for early detection of cancer. Gadolinium nanoparticles were synthesized using polyol method with stabilizer and chemical reaction process at high temperature. The stabilizers used are diethylene glycol (DEG) and triethylene glycol (TEG). The reaction process was carried out at 180°C for 4 hours to obtain gadolinium nanoparticles with uniform size and shape. The results of hydrodynamic and visual measurements using DLS and HRTEM instruments on the gadolinium nanoparticles produced were 50 nm and 18 nm, respectively. The results of the characterization of the crystal structure obtained the X-ray diffraction pattern in the crystal plane (222), which is a typical for the Gd2O3 crystal phase. Characterization of chemical bonds using FTIR showed absorption at 1438-1627 cm−1, 1000-1138 cm−1 and 450-795 cm−1 indicated the presence of Gd-O bond vibrations, while absorption at 1310-1466 cm−1 indicated the presence of Gd-O-Gd bonds. This is evidenced by the similarity with the absorption peak of commercial Gd2O3. The content of free Gd3+ ions found in the synthesized products detected was only about 0.99% of the Gd3+ precursors used.
Salt Farmer measurement performance system facing Covid-19 pandemic used interval type-2 FAHP Method
Authors: Kustiyahningsih Y , Rahmanita E , Purbandini  , Kholifah N 
Published: February 2022

Abstract
Indonesia is an archipelagic country with a coastline of about 81,000 km and has a variety of very large biological and non-biological resources. Position as an archipelagic country with a very wide sea causes each region to have the potential to produce salt. The Covid-19 pandemic has resulted in various negative impacts on several fields such as the economy, social, SMEs and community services. Covid-19 has also resulted in a decrease in salt production and farmers also have difficulty marketing it. The research problem is the large number of salt farmers and number of indicators in providing assistance so that a model for measuring performance of salt farmers is needed. This performance measurement model is guided by several indicators, namely land area (K1), production result (K2), business capital (K3), and marketing system (K4). The method used Interval type-2 Fuzzy Analytic Hierarchy Process (IVFAHP). IVFAHP is used to determine indicators that most influence measurement of salt farmers. This study aims to build a model for measuring performance of salt farmers to increase economic productivity and ability of human resources to deal with COVID-19 pandemic. The contribution is a group-based decision by developing the fuzzy interval type-2 method with triangular fuzzy number (TFN) one midpoints. The findings from study are that the most influential indicators in dealing with COVID-19 pandemic are business capital and salt marketing. This research also produces recommendations for improvement salt farmers in an effort to increase salt production.
Hybrid FAHP and TOPSIS to determine recommendation for improving SMEs facing Covid-19 pandemic
Authors: Kustiyahningsih Y , Rahmanita E , Anamisa D. R. 
Published: February 2022

Abstract
The Covid-19 pandemic has had an impact on domestic economy, such as a decrease in people’s consumption and purchasing power, a decline in company performance, as well as SMEs. This situation, SMEs sector controls 99.99% of all existing businesses, employs 97.16% of private sector workforce, and contributes 57.5% to Indonesia’s gross product. Various government program efforts in helping Batik SMEs players face Covid-19 pandemic so that they are right on target. The large number of SMEs in Bangkalan is around 166,768, causing department to find it difficult to determine recommendations for improvement for each MSME. Based on these problems, a cooperative model for the SMEs industry is needed so that official work program runs smoothly on target. The method used is FAHP and TOPSIS integration method, FAHP method is used to determine weighting and TOPSIS method is used for ranking and recommendations for improvement. The advantage of FAHP is consistency index to control error rate of decision. TOPSIS method is capable of making multi-criteria decisions based on alternative SMEs industry mapping process. The purpose is make a recommendation model for improvement using hybrid method of FAHP and TOPSIS with balanced scorecard indicators for learning and growth perspective. The research contribution is to make decisions based on group recommendations and consistency ratio (CR) is less than 0.1. The findings research, that the influential indicators are batik business ownership and variations of batik motifs. The recommendations for improvement, the average MSME still does not have branding.