Miracle-dz/UniFAR-FTUs huggingface dataset:
Localisation of thin- film resistive sensors for force sensing applications

This paper presents the fabrication and implementation of novel resistive sensors for force-sensing applications. The sensors were developed from specific proportions of graphite and polydimethylsiloxane to form thin-film layers. Localisation was done on the sensors to determine the variation in their responses with respect to different locations and magnitude of the force. The ideology behind these sensors is their uses as tactile sensors for industrial applications and electronic skins for healthcare applications. These sensors showed significant response with a high R2 value for forces ranging from 1 N to 5 N. The podium provided by these sensors could be used as a reference to enhance the ideology on resistive sensing for localisation of the thin-film prototypes.
VSkLCG A Method for Cross-Platform Vulnerability Search in Firmware

Vulnerabilities in firmware will make a system at risk. Because of code reuse, the same vulnerability may occur on different platforms. Therefore, searching vulnerabilities across different platforms is of great significance. Due to the difficulty in obtaining the source code of firmware, there is a need to search vulnerabilities at the binary level. However, the prior methods mainly work at the same platform, which can't be directly extended to the case of cross-platform. In this paper, we propose a multistage method to search cross-platform vulnerabilities in firmware. Given a vulnerable function in a platform, our objective is to find its homologous vulnerability in another platform. To ensure the efficiency, we identify a set of robust numeric features and use the k-Nearest Neighbors (kNN) algorithm to obtain possible vulnerable functions. To improve the accuracy, we adopt the bipartite matching algorithm to calculate the distance between functions based on the local call graphs (LCGs) of functions and the call frequency between functions. We have implemented a prototype of our approach, called VSkLCG, which supports three platforms (ARM, MIPS, x86). The experimental results show that our method can search some vulnerabilities in firmware with a high accuracy while maintaining efficiency.
Real-time Crop Classification Using Edge Computing and Deep Learning

In recent years, edge computing and deep learning have been successfully performed processing and classification tasks in a variety of fields including agriculture. Therefore, this research aims to use unmanned aerial vehicle (UAV) for agriculture applications with integrating edge computing and deep learning techniques. This research experiment was carried out in the NCHU Experimental Farm. The DJI Matrice 100 drone with ASUS Tinker Board S embedded system, which connects a Logitech C925e webcam to capture images are used in this study. The ASUS Tinker Board S runs a folder monitoring program and sends images over the 4G LTE network to the backend server whenever new images are captured and stored. The backend server runs a pre-trained image semantic segmentation model and provides image inference service. The image inference results with the associated segmented image will be sent to the mobile device of the drone controller, and a dynamic flight control action can be triggered. The image semantic segmentation model adopts SegNet network architecture. For a comparison purpose, another network architecture, FCN-AlexNet, was also trained and validated. The preliminary results show SegNet outperformed FCN-AlexNet in image semantic segmentation tasks in terms of the evaluation between training and validation. The average inference speed of the semantic image segmentation model is 0.7s with segmentation identification accuracy is 89%. The promising results shed light on many agriculture applications, such as crop growth condition assessment, fertilizer management, and yield prediction. Additionally, this research provides possible solutions for the labor shortage issue of agriculture which is a common challenge in an aging community like Taiwan and many countries worldwide.
Top-Gate Amorphous Indium-Gallium-Zinc-OxideThin-Film Transistors With Magnesium Metallized Source/Drain Regions

Magnesium (Mg)-induced metallization of amorphous indium-gallium-zinc-oxide (a-IGZO) films is investigated to develop a self-aligned (SA) top-gate (SATG) a-IGZO thin-film transistor (TFT) technology. The high-conductive and SA a-IGZO source/drain (S/D) regions are well realized by a short time of sputtered deposition of Mg onto the a-IGZO film on a heated substrate, followed by the removal of the spare Mg on the surface in hot water. It is shown that the resistivity of the a-IGZO films is lowered to about <inline-formula> <tex-math notation="LaTeX">$4 \times 10^{-{3}}\,\,\Omega $ </tex-math></inline-formula>cm from over <inline-formula> <tex-math notation="LaTeX">$10^{{4}}~\Omega $ </tex-math></inline-formula>cm with a 36-s Mg deposition at <inline-formula> <tex-math notation="LaTeX">$300~^{\circ }\text{C}$ </tex-math></inline-formula>. The metallization effect is believed to be the consequence of a large number of donor-like defects (oxygen vacancies) generated by oxidation–reduction reaction at the interface between the Mg and a-IGZO films. The SATG a-IGZO TFTs fabricated by the proposed technology show excellent electrical characteristics, such as a field-effect mobility of 19.5 cm<inline-formula> <tex-math notation="LaTeX">$^{{2}}\text{V}^{-{1}}\text{s}^{-{1}}$ </tex-math></inline-formula>, a subthreshold swing of 0.19 V/dec, an ON-/ OFF-current ratio of over <inline-formula> <tex-math notation="LaTeX">$10^{{9}}$ </tex-math></inline-formula>, a low S/D series resistance of <inline-formula> <tex-math notation="LaTeX">$2.1~\Omega $ </tex-math></inline-formula>cm, a small channel length shrinking of around <inline-formula> <tex-math notation="LaTeX">$0.1~\mu \text{m}$ </tex-math></inline-formula>, and a high stability against electrical stresses.
Agricultural Product Traceability System Based on Blockchain Technology

The quantity of agricultural products produced in China is huge. How to ensure the quality of agricultural products from farmland to table is a problem that has been studied all the time. From the perspective of decentralization, this paper uses the blockchain technology to combine the characteristics of agricultural products traceability, and the alliance chain hyperledge recology. As the underlying technology of the blockchain, the Fabric1.4. 2 project under the application, the factory, quality inspection, logistics, distribution and supervision as the alliance nodes in the alliance chain, combined with the Internet of Things technology to automatically collect data to achieve agricultural products from planting, processing, quality Traceability of inspection, logistics, distribution and other processes. Through the scanning of the two-dimensional code, the matching of the traceable data and the data uplink are realized, and the products produced are guaranteed to be one yard and one code. Finally, the trace data of the production and circulation process of the product is realized through the scanning of the code of the e-commerce platform of the WeChat mini program.
Development of Fun Hint Game Applications for Special Children on Smart Devices

This paper illustrates the use of Fun Hint Game applications for special children on smart devices. The sample of this experiment were 13 special children from Child Welfare Place with Brain Disabilities Ratchaburi Province, Thailand. The propose of the research were to 1) to design and develop Fun Hint Game application for special children 2) to find the performance of Fun Hint Game applications for special children 3) to compare achievement of students after learning through Fun Hint Game applications for special children on Smart Devices 4) study the level of satisfaction of students towards the Fun Hint Game applications for special children. The results of the research were 1) applications for the special children game on mobile devices were effective for use 2) achievement of students after learning through Fun Hint Game applications for special children higher than before, with statistical significance at the level of.05}{3) the students' satisfaction with the fun hint game for special children on mobile devices was at the highest level ($\overline{x}$ =4.54, S.D.= 0.67)
RGB-D Images for Object Segmentation, Localization and Recognition in Indoor Scenes using Feature Descriptor and Hough Voting

With the development in technology, object localization and recognition systems in RGB and depth have become the essential part of vision systems. There are different ways of objects localization and recognition which segment the whole scene in parts. RGB-D and depth information is best way for the extraction of objects of interest. Researchers and scientists from all our world, continuously trying to improve the vision and detection property of computer systems for improving the people lives. Till now, the computers can sense using sensors and get involved in interesting conversations but lack the capability of understanding a real scene like humans. In our system, we allow the machines to detect and recognize the indoor RGB-d scenes using novel methodology. Inspired by the significance of human-computer interaction, we have presented a technique to recognize and localize the multiple objects present in RGB-D indoor scenes taken from RGB-D object dataset. We have proposed Saliency map based RGB-D object segmentation along with the multiple features and Hough voting to evaluate the performance of our proposed system with other proposed systems. The proposed system should be used in autonomous driving systems, security systems, violence detection, traffic monitoring, games, defense and sports scenes.
Exploiting guard band limits for energy gains in MPSoCs

The critical path delay and, as a consequence, the maximum operating frequency of a digital system are dependent on the supply voltage, so is its power consumption. Typically, voltage guard bands are added in order to improve reliability, at the expense of power efficiency. It has been shown that error detection and correction (EDAC) techniques can be used to mitigate the effects of the reduced safety margins. This Ph.D. project aims to develop a MPSoC capable of self regulate its operating voltage by monitoring the error rate reported by a EDAC system, virtually eliminating voltage safety margins. Literature review and preliminary experiments supports the viability of this approach, motivating further investigation.
Usability of Mobile Applications: A Systematic Literature Study

Since the release of the first mobile devices, the usability of on-board applications has been the concern not only of software vendors but hardware manufacturers as well. The academia community later willingly joined the discussion on usability in terms of theory and empirical measurement, having experience and knowledge in desktop settings. At first sight, such a background should guarantee a solid foundation to conduct research on software usability in a new setting. However, a preliminary study on the subject matter revealed methodological disorder in contemporary literature. As a matter of fact, a need emerged to review existing usability definitions, attributes and measures to recognize all associated aspects. In order to fill this void, we conducted a systematic literature review on usability studies indexed by the Scopus database and devoted to mobile applications. The input volume covers 790 documents from 2001 to 2018. The data analysis shows that the ISO 9241–11 usability definition has been adopted in an unchanged form and popularized as the standard by the HCI community. Secondly, in total, 75 attributes were identified and analysed. The most frequent are efficiency (70%), satisfaction (66%) and effectiveness (58%), which directly originate from the above definition. Subsequently, the less frequent are learnability (45%), memorability (23%), cognitive load (19%) and errors (17%). The last two concern simplicity (13%) and ease of use (9%). Thirdly, in the evaluation of usability, controlled observation and surveys are two major research methods applied, while eye-tracking, thinking aloud and interview are hardly used and serve as complementary to collect additional data. Moreover, usability evaluations are often confused with user experience dimensions, covering not only application quality characteristics, but also user beliefs, emotions and preferences. All these results indicate the need for further research on the usability of mobile applications, aiming to establish a consensus in the theory and practice among all interested parties.
A Transfer k-NN Classifier with the Bagging Method

The k-nearest neighbors algorithm is a simple but an effective method in pattern recognition. The classic k-NN classifier is under the assumption that the training dataset and testing dataset are derived from the same dataset and exhibit the identical distribution. However, transfer learning relaxes these two assumptions and applies the knowledge from the related but different source domain to the target domain. In this paper, a transfer k-NN classification, which can be applied in transfer learning, is proposed. Firstly, the distribution discrepancy between the source domain and the target domain is reduced by reweighting the samples of the source domain. Then, a bagging method with the k-NN algorithm is designed to reduce the influence of the source domain for its massive sample size. Experimental results with the real-world dataset demonstrate that the proposed algorithm is more effective than the classical k-NN and the SVM algorithm.
A New Corner-Reflector Antenna With Tunable Gain Based on Active Frequency Selective Surfaces

A new corner-reflector antenna with a tunable gain based on active frequency selective surfaces (AFSSs) is presented. The proposed design comprises a dipole antenna as a source of the electromagnetic (EM) waves, and three reconfigurable AFSS layers of different size arranged at the same side of the dipole. Each screen consists of two AFSS panels that connected in series and rotated towards the feed to form a V-shaped corner reflector. These AFSS layers are mainly used to control the transmission/ reflection characteristics of the proposed antenna. By applying different combinations for ON/OFF states of diodes, the proposed antenna can adjust its gain value. The antenna performance in terms of reflection coefficient, radiation pattern in the H-plane and gain is analyzed at 5.8 GHz. To validate the concept of the proposed antenna, the prototype of the proposed antenna is fabricated and measured. The measured results show a good agreement with the simulated ones.
Combining Spectral and Texture Features for Estimating Leaf Area Index and Biomass of Maize Using Sentinel-1/2, and Landsat-8 Data

Leaf area index (LAI) and biomass are important indicators that reflect the growth status of maize. The optical vegetation indices and the synthetic-aperture radar (SAR) backscattering coefficient are commonly used to estimate the LAI and biomass. However, previous studies have suggested that spectral features extracted from a single pixel have a poor ability to describe the canopy structure. In this paper, we propose a method for estimating LAI and biomass by combining spectral and texture features. Specifically, LAI, biomass and remote-sensing data were collected from the jointing, trumpet, flowering, and filling stages of maize. Then we formed six remote-sensing feature matrices using the spectral and texture features extracted from the remote sensing data. Principal component analysis (PCA) was used to remove noise and to reduce and integrate the multi-dimensional features. Multiple linear regression (MLR) and support vector regression (SVR) methods were used to build the estimation models. Tenfold cross-validation was adopted to verify the effectiveness of the proposed method. The experimental results show that using the texture features of both optical and SAR data improves the estimation accuracy of LAI and biomass. In particular, SAR texture features greatly improve the estimation accuracy of biomass. The estimation model constructed by combining spectral and texture features of optical and SAR data achieves the best performance (highest coefficient of determination ( $R^{2}$ ) and lowest root mean square error (RMSE)). Specifically, we conclude that the best window sizes for extracting texture features from optical and SAR data are $3\times 3$ and $7 \times 7$ , respectively. SVR is more suitable for estimating the LAI and biomass of maize than MLR. In addition, after adding texture features, we observed a significant improvement in the accuracy of estimation of LAI and biomass for the growth stages, which have a larger variation in the extent of the canopy. Overall, this work shows the potential of combining spectral and texture features for improving the estimation accuracy of LAI and biomass in maize.
An Active Multielectrode Array for Collecting Surface Electromyogram Signals Using a-IGZO TFT Technology on Polyimide Substrate

The surface electromyogram (sEMG) signals produced by living bodies play a significant role in biological applications. However, an active multielectrode array (MEA) having a high spatiotemporal resolution, flexibility, and high gain is still an enormous challenge for accurate sEMG detection. Here, a flexible active MEA based on the diode-connected load inverter is proposed and fabricated for collecting sEMG signals using amorphous indium–gallium–zinc oxide (a-IGZO) thin-film transistors (TFTs) technology on the polyimide (PI) substrate. To obtain the good gain effect and low-noise active MEA, the width–length ratio of the transistors and the suitable impedances are systemically designed. Moreover, the optimized circuit exhibits good bias stability, excellent uniformity in electrical performance, and outstanding mechanical durability, which can ensure reliable sEMG detection. With the combination of the a-IGZO TFTs, the active MEA has an approximate 15-dB signal gain under a low driving voltage of 5 V. Measuring the sEMG of the muscle groups below the thumb with our developed flexible active MEA, the amplitude value of sEMG signals is successfully amplified and the noise fluctuation is obviously reduced. Thus, the active MEA has certain advantages in large-area preparation, stability, flexibility, and high gain, which opens a new avenue for the accurate sEMG signal measurements.
Equivalent Capacitance Guided Dummy Fill Insertion for Timing and Manufacturability

To improve manufacturability, dummy fill insertion is widely adopted for reducing the thickness variation after chemical mechanical polishing. However, inserted metal fills induce significant coupling to nearby signal nets, thus possibly incurring timing degradation. Existing timing-aware fill insertion strategies focus on optimizing induced coupling capacitance instead of resultant equivalent capacitance. Therefore, the impact on timing cannot be fully captured. In contrast, in this paper, we analyze equivalent capacitance friendly regions for dummy fills. The analysis can wisely guide dummy fill insertion to prevent unwanted and unnecessary increase in the resultant equivalent capacitance of timing critical nets. Experimental results based on the ICCAD 2018 CAD Contest benchmark suite show that our solution outperforms the contest winning teams and state-of-the-art work. Moreover, our analysis results are highly correlated to actual equivalent capacitance values and indeed provide accurate guidance for timing-aware dummy fill insertion.
SOC Optimization Based Energy Management Strategy for Hybrid Energy Storage System in Vessel Integrated Power System

Hybrid energy storage system (HESS) consisted of battery and supercapacitor plays an essential role in supporting the normal operation of pulse load in vessel integrated power system (IPS) as well as improving power quality. However, due to the unique properties of the pulse load and diversified operations of the vessel, such advanced power system architectures tend to face greater challenges in optimal power allocation. In order to address the power allocation challenges, a novel optimized state-of-charge (SOC) feedback based energy management strategy is proposed for HESS in IPS to restrain the DC bus voltage fluctuation in this paper. Firstly, considering the operating characteristics of the pulse load in IPS, the optimized SOC of the HESS is introduced to the low-pass filter (LPF) with variable time constant to split the power in the HESS. Secondly, SOC recovery control of the supercapacitor is introduced to the LPF to optimize the size of the HESS as well as prolong the lifetime of the battery. Also, the enforced intervention is introduced to avoid the opposite state of the HESS. The proposed strategy can make full use of the HESS complementary characteristics to compensate the pulse load and optimize the HESS. Finally, the simulation conducted in PSCAD demonstrates the effectiveness of the strategy proposed in pulse load compensation as well as HESS optimization.
Position-Pose Measurement of Noncooperative Targets in Final Approach

Derelict satellites in space not only occupying orbit resource but tending to threaten safety of other normal operating satellites. On-orbit servicing mission including repair, refueling and removal of those satellites are needed urgently. To meet the needs of navigation to derelict satellites, a study of the position-pose measurement methods in final approach of space noncooperative targets is carried out. Combining with the theoretical research and demonstration project progress of the power country in spaceflight, the passive and active measurement methods are introduced and compared. Development trend of multi-sensor fusion based navigation is presented.
NCFET to Rescue Technology Scaling: Opportunities and Challenges

Negative Capacitance Field Effect Transistor (NCFET) is one of the promising emerging technologies that may overcome the fundamental limits of conventional CMOS technology. NCFET features a ferroelectric (FE) layer within the transistor’s gate, which internally amplifies the voltage, allowing NCFET to operate at a lower voltage while sustaining performance at considerable energy savings. In this work, we raise awareness that n- and p-NCFET transistors are asymmetrically affected by the FE layer and show, for the first time, how this asymmetry results in unbalanced circuit performance (e.g., longer fall than rise propagation delay, reduced noise margins). As NCFET are meant to maintain performance while reducing power, we present a solution by scaling the number of fins in n-NCFET to regain symmetry. We optimize iteratively in conjunction with supply voltage scaling to find the minimal energy consumption while maintaining performance. In our first case study, we achieve at least 34% lower power consumption and thus 34% higher energy efficiency as the circuit exhibits identical propagation delay. However, our second case study reveals that NCFETs can consume 3x more power and energy than the FinFET design. In summary, not considering the asymmetry and replacing FinFET with current-matched NCFET results in unreliable circuits (timing violations). This work exemplifies how the power and energy consumption of a NCFET circuit might surpass that of a FinFET, if circuits are designed considering asymmetry and circuit metric matching.