Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal Management of a Li-Ion Battery for Electric Vehicles Using PCM and Water-Cooling Board

A novel thermal management system (TMS) for Li-ion battery module using phase change material (PCM) and cooling water as the heat dissipation source to control battery temperature rise has been developed. Graphite sheets were applied to compensate low thermal conductivity of battery and PCM and improve temperature uniformity of the batteries. One discharge (1C rate)-charge (2C rate) circle was applied in battery modules to test the effectiveness of this TMS. A three dimensional numerical model of the battery module with the TMS was conducted. The results show that this TMS basically meets the demand about the maximum temperature difference of battery module and totally keeps the maximum temperature within the optimum operating temperature range (≤45°C).
Selection of CVD Diamond Crystals for X-ray Monochromator Applications Using X-ray Diffraction Imaging

A set of 20 single crystal diamond plates synthesized using chemical vapor deposition (CVD) was studied using X-ray diffraction imaging to determine their applicability as side-bounce (single-reflection) Laue monochromators for synchrotron radiation. The crystal plates were of optical grade (as provided by the supplier) with (001) nominal surface orientation. High dislocation density was found for all samples. Distortions in the crystal lattice were quantified for low-index Laue reflections of interests using rocking curve topography. Maps of effective radius of curvature in the scattering plane were calculated using spline interpolation of the rocking curve peak position across the studied plates. For several selected plates, nearly flat regions with large effective radius of curvature were found ( R 0 ≳ 30 - 70 m, some regions as large as 1 × 4 mm 2 ). The average width of the rocking curve for these regions was found to be about 150 μ rad (r.m.s.). These observations suggest that the selected CVD diamond plates could be used as intermediate-bandwidth monochromators refocusing the radiation source to a specific location downstream with close to 1:1 distance ratio.
Compact CMOS spectral sensor for the visible spectrum

A compact single-shot complementary metal-oxide semiconductor (CMOS) spectral sensor for the visible range (wavelength 400–700 nm) is presented. The sensor consists of two-dimensional silicon nitride-based photonic crystal (PC) slabs atop CMOS photodetectors. The PC slabs are fabricated using one-step lithography and amenable to monolithic integration into CMOS image sensors. Featuring a small footprint of 300 μm×350 μm, the sensor can successfully measure the spectra over the 400–700 wavelength range with a best resolution of 1 nm. The footprint of the sensor may be further reduced to enable hyperspectral imaging with high spatial resolution.
Non-Uniform Filter Bank Visualization based Prediction Models for Respiratory Signals

Chronic respiratory disorders (CRDs) and lower res piratory illness are the common widespread infection emphasized by obstruction of flow of air in alveoli. Listening to breathe sounds of the respiratory system is a traditional technique used for diagnosing chronic disorders in patients. However, the outcomes of diagnosis can be sensed only by skilled therapist which imposes limitations on quantifiable results. This urged to the development of technology driven tools for detecting the disorders. Most of the earlier studies focused on analyzing the breathe sounds using different filter banks (FBs) such as Discrete cosine transform (DCT) FBs, Wavelet FBs, Mel FBs and s pectrograms for classification using CNN deep learning models. Owing to the nature of exactly matching the frequency characteristics of FBs with that of human ears, Octave FBs and Cross over FBs are proposed in this work. The filter coefficients extracted using proposed FBs are transformed into s pectrogram time Frequency Visualization and are classified using three Transfer learning (TL) viz. GoogLeNet, S queezeNet and ResNet-50. The comparative results with existing method reveal that the proposed FB produces significant improvement in accuracy of 90.63% and 90.89% for ResNet-50 classifier.
Calculation Method of System Adjustable Load Considering Renewable Energy Consumption

The coordination control strategy of the source-load-energy storage effectively makes use of adjustable resources, which plays an important role in peak cutting, valley filling, renewable energy consumption, energy efficiency improvement, frequency, and voltage regulation, and other aspects. It supports flexible regulation of the power system. In the case of a small load in the wet season, based on the conventional unit commitment and their minimum output, a proposed calculation method takes the minimum adjustable load required for system configuration as the objective function. The renewable energy consumption constraint and the coordination operation strategy of energy storage are considered. The adjustable load satisfying the abandoned power requirement of renewable energy is calculated by analyzing the whole day participation state and proportion of the adjustable load in system regulation. Finally, a regional power grid is used to verify the effectiveness of the proposed calculation method. The calculation results show that the reasonable configuration of adjustable load can reduce the amount of abandoned power.
Implementation of Lossless Voice Data Communication using Network Streams on Embedded System

Smart home refers to the use of computers and information technology to control home appliances. The smart home system occupies sensors to acquire data for monitoring. One of the most important factors in designing a smart home system was the communication between devices that will be used. It requires high throughput and low latency communication so that monitoring can be done in real time and lossless. The communication network was designed to optimize the stream monitoring for smart home by reviewing the system throughput and latency. Lab-VIEW programming on My-RIO embedded systems was used to acquire accelerometer and voice data readings and send them to personal computer wirelessly. The network communication was designed by implementing network stream protocols between two applications which were planted in the personal computer and My-RIO system. The test results indicate that the network stream protocol did not require normalization of sensor data types while transmitting and receiving. The throughput values were affected by increasing buffer size but on certain conditions saturated throughput were experienced. The value of the latency is always stable with an average value of 13 ms even though the size of the buffer is enlarged.
An Experiment on Simple and Practical Methods of Cluster Labeling for Hierarchically Organized Document Subsets

This paper reports the results of an experiment on cluster labeling for a hierarchical tree of document subsets which were generated by the Hierarchical Multi-way Divisive Clustering (HMDC) algorithm. The data used was a set of 6,374 news articles extracted from the RCV-1 test collection (Reuters Corpus). The tree contained 2,252 clusters (nodes), to which labels were assigned by selecting terms from those included in documents of the target cluster. More specifically, the terms (noun phrases or their components) in the documents were ranked by three well-known weighting methods, and three top ranked terms were used as labels of the cluster. In the experiment, three sets of labels selected by the three methods, respectively, were comparatively assessed by a human reviewer for the set of 1,201 clusters, and the degrees of goodness or badness of these labels were measured by each cluster.
Reconfigurable Signal Processing and DSP Hardware Generator for 5G Transmitters

To impose the reconfigurability and reusability of digital circuits for millimeterwave transmitter architectures, high-speed digital signal processing architectures are explored. The digital front-end of these next-generation transmitters can be implemented up to the maximum operating frequency to meet the requirements of the 5G NR FR2 frequency bands. This paper presents an efficient implementation of a reconfigurable digital signal processor (DSP) that contains programmable multistage multirate filters, operable up to 4 GHz, and a flexible generator for polar, outphasing, and multilevel outphasing modulation. The system achieves an excellent ACLR of 42 dB and EVM degradation of 1.61% with a 7-bit phase signal at a sampling frequency of 4 GHz for outphasing modulation. Digital synthesis of the circuit in a 22 nm FDSOI process results in a core area of 0.12 mm2and an estimated power consumption of 142 mW for a 200 MHz bandwidth 5G NR baseband signal.
Obstacle Detection Using Sensor Fusion and Deep Neural Network for Motion Control of Smart Electric Tractor

The need for obstacle detection is quintessential from the safety point of view for modern smart/autonomous vehicles. The implementation of such technology in farm equipment can lead to further improvements in efficient farming. This necessitates the requirement of a low cost and reliable method for obstacle detection and motion control. To suffice the need, this research work is focused on the development of a perception module using multiple sensors which can act harmoniously in a given scenario. To detect the obstacle, three different sensors are used, providing the distance and feature of the obstacle. The camera is used for object detection and distance measurement using OpenCV deep neural network. As the simultaneous distance measurement is relatively slow and dependent on the environmental conditions pertaining to visibility, a mini Lidar module is used. As the Lidar module has a limited field of view, ultrasonic sensors are used for the detection of obstacles at close range. Data obtained from the system is used to drive commands for the vehicle's motion using a set of actuators controlling the vehicle's motion in terms of acceleration, braking and steering.
Motion Control of a Dexterous Manipulator Using Data Glove

In order to control a dexterous manipulator which is used on humanoid dual-arm robot, a data glove is developed, and its control mode is studied to realize the real-time somatosensory control of the manipulators. The flex sensors are used in data glove to obtain the motion data of human fingers. The data are collected, transmitted and processed by the Arduino Nano controller, the HC-06 Bluetooth module is used for wireless data transmission. For ease control of the dexterous hand, three kinds of grasping modes are defined, and grasping experiments are carried out. The results show that the operator can control the dexterous manipulator well by using data glove, each finger of the dexterous manipulator can be individually controlled, and the proposed control mode is an efficient way to deal with different grasp tasks.
Design of A Variable Stiffness Actuator and Study on Its Variable Stiffness Characteristics

In this paper, the structural design of a variable stiffness actuator (VSA) is proposed, and the variable stiffness characteristics of the VSA are studied. The VSA is compact and can be used for humanoid robots. Firstly, the structure of the VSA is designed. Then the stiffness model of the structure is derived in theory and the dynamic simulation is performed in ADAMS. The stiffness results of dynamic simulation and theoretical calculation are highly consistent, which verified the correctness of each other. Finally, the influence of the curve equation of the worm gear disc on the stiffness of the system is studied: the radius of the curve is a function of the angle, and when the order of the curve equation is higher, the stiffness adjustment range of the system is wider. Under the premise of meeting the same stiffness requirements, when the order of the curve equation increases, the radius of the higher-order curve equation is only half of that of the lower-order curve equation, and a more compact VSA can be obtained. The results are of great significance to the prototype design, that is, without changing the main design dimensions of each component, the stiffness of the system can reach the design value simply by changing the order of the curve equation.
Coherent Magnetization Rotation of a Layered System Observed by Polarized Neutron Scattering under Grazing Incidence Geometry

The in-plane magnetic structure of a layered system composed of polycrystalline grains smaller than the ferromagnetic exchange length was studied to elucidate the mechanism controlling the magnetic properties considerably different from the bulk using polarized neutron scattering under grazing incidence geometry. The measured result, together with quantitative analysis based on the distorted wave Born approximation, showed that the in-plane length of the area with a uniform orientation of moments ranging from 0.5–1.1 μ m was not significantly varied during the process of demagnetization followed by remagnetization. The obtained behavior of moments is in good agreement with the two-dimensional random anisotropy model where coherent magnetization rotation is dominant.
Comparing salience detection algorithms in mammograms

Salience in imaging is defined as the extent to which an object in an image catches the eye of the viewer. Currently, many software packages exist that calculate salience using a wide range of models and implementations. Here we examine four types of salience programs: feature-based programs, convolutional neural networks, principal components analysis programs, and background subtraction programs. In feature-based programs, the software creates a series of maps for individual salience features (e.g., orientation and intensity), and then combines those individual feature maps into an overall map of salience for the entire picture [1] [2] [3]. In other models, convolutional neural networks act as a series of layers, each of which transforms the data and finds the most salient points in an image [6] [9] [10]. In principal components analysis programs, components corresponding to higher eigenvalues are used to separate the background from the salient objects. Lastly, in background subtraction, salient areas are found by comparing the object’s intensity distribution to the background distribution. In total, this paper compares 19 models, including our own algorithm, on a general database of images to determine each model’s accuracy when detecting salience. Additionally, as previous work has shown a correlation between salient points in a mammogram and the presence of a mass in a mammogram, we apply each of these state-of-the-art software packages to a database of mammograms to determine the accuracy of each program when detecting abnormalities in mammograms.
Solar treatments for reducing survival of mountain pine beetle in infested ponderosa and lodgepole pine logs

Negrón, José F. ; Shepperd, Wayne A. ; Mata, Steve A. ; Popp, John B. ; Asherin, Lance A. ; Schoettle, Anna W. ; Schmid, John M. ; David A. Leatherman. 2001. Solar treatments for reducing survival of mountain pine beetle in infested ponderosa and lodgepole pine logs. Res. Pap. RMRS-RP-30. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 11 p. Three experiments were conducted to evaluate the use of solar radiation for reducing survival of mountain pine beetle populations in infested logs. Ponderosa pine logs were used in experiments 1 and 2 and lodgepole pine logs were used in experiment 3. Experiment 1 comprised three treatments: (1) one-layer solar treatment without plastic sheeting and logs rotated one-third of a turn once a week; (2) two-layer solar treatment with plastic sheeting; and (3) two-layer solar treatment without plastic sheeting. For experiment 2, two additional one-layer treatments were added: one-layer treatment with plastic sheeting and no rotation and a one-layer with no plastic sheeting and no rotation. Experiment 3 included all the above-mentioned onelayer treatments only. For all experiments, brood density per 0.05 m (0.5 ft) was estimated before and after treatment and analyzed using repeated measures analysis of variance. Subcortical temperatures were monitored in one replicate of all treatments in all experiments. In experiment 2, phloem moisture was monitored before and after treatment in uninfested logs. All treatments in all experiments caused drastic reductions in brood survival. In experiment 1, the one-layer treatment with the logs rotated once a week significantly reduced brood survival compared to the two-layer without plastic sheeting treatment but was not different from the two-layer with plastic sheeting treatment. There were no differences in brood survival after treatment associated with any treatments in experiments 2 and 3. In all experiments brood survival was consistently reduced in the aspects of the logs exposed to the sun. Maximum temperatures were consistently higher in the treatments with plastic sheeting, the exposed surfaces of the logs to the sun, and the upper layer of logs in the two-layer treatments. No differences were detected in phloem moisture content in uninfested logs before and after treatment in experiment 2, suggesting that heat is directly responsible for the observed reductions in survival. We conclude that solar treatments are an effective alternative for reducing mountain pine beetle survival in infested ponderosa and lodgepole pine logs.
Computer Vision Techniques for Cancerous Cells Analysis in FIB-SEM Images

Recent advances in focused ion beam-scanning electron microscopy (FIB-SEM) has led to unprecedent visualization, analysis, and thus understanding of cancerous cells structures, as well as cell-to-cell interaction in cancerous tissues [1]. If a typical dataset contains hundreds of images (usually up to 1400 images of 6Kx4K pixels with 4nm resolution per pixel) allowing a 3D reconstruction of a tissue fraction, it is not ready for analysis at it is because of the following issues: 1/ misalignment, each consecutive two images are not properly aligned and need registration to preserve the 3D information continuity; 2/ noise, depending on the acquisition settings, the images may contain an important quantity of noise making any further analysis tedious or even impossible; 3/ the structures of interest touch each other or even interlaced, making visualization and spatial analysis impossible.
Comparative Macroscopic and Microscopic Gunflint Use-Wear Analysis

ABSTRACT The present research is focused on a morphological and microscopic comparative analysis of the gunflints of the fur trade component of the Horseshoe Bay site (21CA201), Leech Lake, Cass County, Minnesota. Background information pertaining to the Horseshoe Bay site is followed by the research methodologies utilized in the current analysis of the gunflints. Morphological and microscopic patterns of use wear have identified two different functions for gunflints. The results of the analysis indicate that (1) gunflints can potentially retain use-wear associated ferric depositions for an extended period of time; (2) the ferric depositions retained on archaeologically recovered gunflints display diagnostic striation patterns and microspherule attachment remnants that match replicated samples; (3) gunflints utilized for fire starting in conjunction with a fire steel display morphological characteristics that can be visually identified; and (4) gunflints were utilized for the purposes of fire starting in northern Minnesota during the period circa 1784 to at least 1853.
Changes in Water Surface Area during 1989-2017 in the Huai River Basin using Landsat Data and Google Earth Engine

The dynamics of surface water play a crucial role in the hydrological cycle and are sensitive to climate change and anthropogenic activities, especially for the agricultural zone. As one of the most populous areas in China’s river basins, the surface water in the Huai River Basin has significant impacts on agricultural plants, ecological balance, and socioeconomic development. However, it is unclear how water areas responded to climate change and anthropogenic water exploitation in the past decades. To understand the changes in water surface areas in the Huai River Basin, this study used the available 16,760 scenes Landsat TM, ETM+, and OLI images in this region from 1989 to 2017 and processed the data on the Google Earth Engine (GEE) platform. The vegetation index and water index were used to quantify the spatiotemporal variability of the surface water area changes over the years. The major results include: (1) The maximum area, the average area, and the seasonal variation of surface water in the Huai River Basin showed a downward trend in the past 29 years, and the year-long surface water areas showed a slight upward trend; (2) the surface water area was positively correlated with precipitation (p < 0.05), but was negatively correlated with the temperature and evapotranspiration; (3) the changes of the total area of water bodies were mainly determined by the 216 larger water bodies (>10 km2). Understanding the variations in water body areas and the controlling factors could support the designation and implementation of sustainable water management practices in agricultural, industrial, and domestic usages.
An Improved Faster R-CNN Transmission Line Bolt Defect Detection Method

With the continuous development of deep learning, how to use computer vision technology to accurately locate bolts and identify defects in complex natural backgrounds has become a common problem faced by both academia and industry. Aiming at the problems of slow detection speed and high false detection rate in current bolt defect detection, an improved Faster R-CNN bolt defect detection algorithm for transmission lines is proposed. First, with Faster R-CNN as the basic framework, through the experimental comparison of three different backbone networks, ResNeSt with higher detection accuracy is selected as the backbone network. Second, the feature extraction network and feature pyramid FPN structure are improved. Then, the improved Faster R-CNN model is trained on the transmission line bolt defect dataset. Finally, the application verification is carried out with the inspection on the transmission line above 110kV of a provincial power company. The results show that the method in this paper can assist the inspectors to quickly screen and locate the defective bolts in the high-resolution UAV image, thus greatly improving the inspection efficiency. Check work efficiency.
Quick determination of earthquake source parameters from GPS measurements: a study of suitability for Taiwan

We test the feasibility of GPS-based rapid centroid moment tensor (GPS CMT) methods for Taiwan, one of the most earthquake prone areas in the world. In recent years, Taiwan has become a leading developer of seismometer-based earthquake early warning systems, which have successfully been applied to several large events. The rapid determination of earthquake magnitude and focal mechanism, important for a number of rapid response applications, including tsunami warning, is still challenging because of the limitations of near-field inertial recordings. This instrumental issue can be solved by an entirely different observation system: a GPS network. Taiwan is well posed to take advantage of GPS because in the last decade it has developed a very dense network. Thus, in this research, we explore the suitability of the GPS CMT inversion for Taiwan. We retrospectively investigate six moderate to large (Mw6.0 ∼ 7.0) earthquakes and propose a resolution test for our model, we find that the minimum resolvable earthquake magnitude of this system is ∼Mw5.5 (at 5 km depth). Our tests also suggest that the finite fault complexity, often challenging for the near-field methodology, can be ignored under such good station coverage and thus, can provide a fast and robust solution for large earthquake directly from the near field. Our findings help to understand and quantify how the proposed methodology could be implemented in real time and what its contributions could be to the overall earthquake monitoring system.