Miracle-dz/UniFAR-FTUs huggingface dataset:
Accurate 3D Finger Knuckle Recognition Using Auto-Generated Similarity Functions

Contactless 3D finger knuckle is an emerging biometric identifier, which can provide a promising alternative for personal identification. To maximize its potential, feature representation and matching are the two critical components towards high performance. A recent pioneering work is limited by its preliminary design of the feature descriptor and the tailor-made similarity function. Although this method demonstrates decent recognition performance, there is room for improvement. This article advances the state-of-the-art method by introducing a new curvature based feature descriptor and a method to compute the similarity functions based on the statistical distribution of the encoded feature space. Our proposed feature representation utilizes an insight in 3D geometry for accurately encoding the curvature information. When computing the similarity between a pair of templates, we compute the similarity function from the probability mass distributions of the encoded feature space. Our proposed approach is scalable to templates with different sizes, and more importantly outperforms the state-of-the-art methods significantly, which is demonstrated in a publicly available database of 3D finger knuckle. In addition, we also demonstrate the generalizability of our approach by evaluating on other publicly available biometric datasets of similar patterns, i.e., 3D palmprint and finger vein.
Enhanced Photodetection Performance in Graphene-Assisted Tunneling Photodetector

The vertical van der Waals heterostructures based on 2-D materials have attracted tremendous attention in optoelectronic devices as they can offer perfect interface without dangling bonds, atomic layer thicknesses, and conveniently tunable energy band alignment. However, the carrier transport mechanism in vertically stacked van der Waals heterostructure photodetectors is usually neglected in regards of photoresponse enhancement strategy, leading to low photoresponsivity and quantum efficiency. Here, we report a vertically stacked tunneling photodetector based on WSe<sub>2</sub>/graphene/WS<sub>2</sub> van der Waals heterostructure. By introducing graphene film into the WSe<sub>2</sub>/WS<sub>2</sub> interface, the interface composition was ameliorated and the Fowler–Nordheim tunneling (FNT) was enhanced with the reduced tunneling barrier height and thickness, caused by the elevated energy level of electrons since strong electron–electron interaction, ultrafast thermalization (~50 fs), and massless Dirac electrons of graphene. Therefore, the device exhibits a high photocurrent/dark current ratio (>10<sup>4</sup>), fast response time (<inline-formula> <tex-math notation="LaTeX">$\sim 300~ \mu \text{s}$ </tex-math></inline-formula>), high detectivity (<inline-formula> <tex-math notation="LaTeX">$\sim 1.58\times 10^{12}$ </tex-math></inline-formula> Jones), and high responsivity (429 mA W<sup>−1</sup>) across a broad spectral range till <inline-formula> <tex-math notation="LaTeX">$1~ \mu \text{m}$ </tex-math></inline-formula> at room temperature. The optimized detectivity and responsivity are about 150 times and 50 times higher than WSe<sub>2</sub>/WS<sub>2</sub> device without graphene, respectively. These results contribute to offer a novel and versatile strategy for overcoming the performance limitation in van der Waals photodetector.
A cell sorting Algorithm for series-parallel configured Lithium ion battery packs in spacecrafts

The Series-parallel (s-p) configured Lithium ion batteries find use in many spacecrafts. Cell selection to make a battery pack involves sorting tested cells to meet screening and matching criteria. Cell capacity, cell resistance, and self-discharge could be used for cell selection. Conventionally, data is linearly sorted into ascending or descending order based on one parameter. Matching criteria are applied to choose cells to be put into strings. Cell sorting using the Genetic Algorithm (GA), involving mixed-integer linear optimization, is proposed in this paper. Cells are arranged randomly to match all of the parameters within a set of tight constraints. A better match for the cells is achieved by multiple iterations. GA Improved Cell Sorting Algorithm (GICSA) is verified with experimental data and has given close to 100% cell yield.
Self-Service, On-Demand Creation of OLAP Cubes over Big Data: a Metadata-Driven Approach

Nowadays, huge amounts of data are continuously created from different sources in different formats, and stored into data lakes for further use. A typical use case is to conduct online analyses in order to gain business insights and make better decisions. However, there are many obstacles to overcome when it comes on analysing Big Data online, such as dealing with schema-free data, conciliating different data formats, managing different locations, and allowing BI professionals and analysts to create their analytical data by themselves. In this paper, we propose some solutions to overcome these obstacles. We propose a data lake metadata model as well as a metadata-driven approach to create OLAP cubes from data lakes on-demand and in a self-service manner. We apply our work to Twitter social network and we present a proof-of-concept dedicated application.
A Comparison of Analog Performance, Linearity, and Distortion Characteristics Between Symmetric InGaAs and Asymmetric InGaAs/InP MOSFETs

In this article, we report an investigation of analog performance, linearity, and harmonic distortion (HD) characteristics for both symmetric and asymmetric InGaAs n-channel MOSFETs at elevated temperatures. Analog performance parameters such as transconductance and voltage gain are found to be better for the asymmetric InGaAs MOSFETs than their symmetric counterparts. The linearity metrics such as <inline-formula> <tex-math notation="LaTeX">${g}_{\text {m2}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${g}_{\text {m3}}$ </tex-math></inline-formula>, voltage intercept points 2 (VIP2), VIP3, IIP3, and third-order intermodulation distortion (IMD3) have been analyzed. Asymmetric devices are found to perform better in terms of linearity. Moreover, distortion is also found to be less for the asymmetric devices than the symmetric ones. A comparison of the linearity and distortion characteristics of InGaAs devices with a similarly sized Si device reveals that, although the Si device performs better in terms of linearity, particularly at elevated temperatures, InGaAs devices have an edge in terms of distortion over the Si device.
A Novel mmWave MIMO-NOMA Scheme Based on Beam Aggregation

Millimeter wave (mmWave) multiple-input and multiple-output (MIMO) technology is one of the key technologies of the fifth generation (5G) wireless communication system. The application of non-orthogonal multiple access (NOMA) to mmWave MIMO system can further improve the throughput and spectrum efficiency. The existing researches on mmWave MIMO-NOMA normally assume that multiple UEs are served by one beam and thus suffers from beam misalignment. In this paper, we propose a novel beam aggregation-based mmWave MIMO-NOMA scheme where multiple UEs are served by a group of beams in a non-orthogonal fashion. Numerical simulation results reveal that our proposed NOMA scheme has significant advantages with respect to the achievable sum-rate and fairness compared with power-domain NOMA.
Dynamic Group Formation with Suitability Constraints in large Social Networks

For people seeking to form a team for a specific purpose, like a side project or study group, challenges quickly arise once they have exhausted their social circle in the search for teammates. In the wake of the current pandemic, meeting new people that are right for a specific team is even more difficult than before due to the lack of in-person events. On social media platforms, users often have large networks of friends but have very few close personal relationships in them. So, posting on those to look for people that are compatible, share the same goal and are interested in the niche group, is being hopeful at best. We present a scalable framework for establishing small online groups that balances two objectives, making the best group recommendations to users and guiding group hosts to the best users for their group. We illustrate this framework using three use cases and evaluate a server-less implementation using a large social media dataset to simulate a production environment.
An MPPT Algorithm for PV Systems Based on a Simplified Photo-Diode Model

A Maximum Power Point Tracking (MPPT) algorithm is proposed based on the assumption that a simplified three-parameter photodiode-based model can provide an excellent approximation of a PV module <inline-formula> <tex-math notation="LaTeX">$i-v $ </tex-math></inline-formula> curve around its maximum power point (MPP). Procedures to obtain the MPP coordinates and the three parameters of the approximated <inline-formula> <tex-math notation="LaTeX">$i-v $ </tex-math></inline-formula> curve from experimental online measurements, analytical and Newton-Raphson iterative calculations are thoroughly described. Initializing the model as well as optimizing it to operate faster by identifying only subsets of the model parameters provides excellent MPPT efficiency in both static and dynamical MPPT situations. The performance of the proposed algorithm has been verified in comparison with other well-known MPPT methods using the software-in-the-loop approach. Next, its performance has been evaluated by using the MATLAB-based hardware-in-the loop experimental setup that provides the required reproducibility of the different synthetic and real irradiance and temperature profiles considered.
Active Bending Mechanism Employing Granular Jamming and Vacuum-Controlled Adaptable Gripper

We propose a bending mechanism in this study capable of wrapping around objects of various shapes and increasing its stiffness simply via the evacuation of internal air. Unlike vacuum splints requiring manual wrapping and pneumatic bending devices based on granular jamming requiring a complicated combination of two separate air control systems, our proposed mechanism can wrap itself around objects using a single air evacuation system. An elastic container enveloping polystyrene foam beads and urethane sponges is employed in this mechanism. The compression of the sponges, caused by the evacuation of internal air, results in bending, while the stiffness of the mechanism increases simultaneously due to granular jamming. On embedding sponges having different stiffnesses, the resulting differences in the onset of sponge shrinkage cause sequential bending, which reduces the gaps between the mechanism and the target object. First, we developed a mattress-shaped bending mechanism that can be used as a vacuum splint and does not need to be manually wrapped around an object. Thereafter, an adaptable gripper was developed using the same bending mechanism. The gripper can wrap around objects having various shapes and increase its stiffness simply by evacuating internal air; it can even lift heavy objects.
A New Architecture for Circulating Current Control in a Multi-port Hybrid Nine-Arm Modular Multilevel Converter

In this paper, a multi-port hybrid nine-arm modular multilevel converter is proposed for integration of an offshore wind farm into the HVDC subsea power transmission system feeding an offshore subsea oil and gas processing load. A detailed analysis of circulating current of the proposed converter is performed and accordingly, a control architecture based on a synchronous rotating reference frame is developed. The proposed control architecture regulates the circulating current at an optimal value in order to achieve a stable and efficient operation of the multi-port hybrid nine-arm modular multilevel converter. The proposed architecture incorporates control of phase angle difference between the source port and load port voltages, which is the key to regulate the circulating current magnitude. A system level simulation model has been developed on PLECS simulation software to demonstrate the performance of the proposed control architecture.
Effect of Cryogrinding on Physico-Chemical Properties of Drugs. I. Theophylline: Evaluation of Particles Sizes and the Degree of Crystallinity, Relation to Dissolution Parameters

An activation of crystalline form of theophylline was carried out by low temperature grinding (at 78 K). From electron microscopy data, there were determined the form, mean linear sizes of particles and then specific surface was calculated. From X-ray data, a fraction of microcrystalline phase in cryogrinded samples was calculated and it was showed that the intense defect formation process takes place up to partial amorphization at final stage of mechanical treatment. By ultra-violet spectroscopy, the solution behaviour of initial (intact) and activated forms of theophylline was studied. The values of solution rate and solubility for activated forms are 12 and 1.5 times greater accordingly then ones for initial form. On the basis of experimentally determined thermodynamic characteristics of solution process for the initial and activated forms, the thermodynamic characteristics of theophylline activation were calculated.
DNN-based self-attitude estimation by learning landscape information

This paper presents DNN (deep neural network) - based self-attitude estimation by learning landscape information. The network predicts the gravity vector in the camera frame. The input of the network is a camera image, the outputs are a mean vector and a covariance matrix of the gravity. It is trained and validated with a dataset of images and correspond gravity vectors. The dataset is collected in a simulator. Using a simulator breaks the limitation of amount of collecting data with ground truth. The validation showed the network can predict the gravity vector from only a single shot image. It also showed the covariance matrix expresses the uncertainty of the prediction.
CAM-FoC: A High Accuracy Lightweight Deep Neural Network for Grip Force Measurement of Elongated Surgical Instrument

Grip force measurement enables better control performance for robot-assisted minimally invasive surgery (RMIS). A deep-learning-based method is proposed to measure the instrument grip force without mounting additional sensors in this article. First, the training trajectory and input data frame are studied. Seven data are derived from the original sensor data, and a binary butterfly optimization algorithm with opposite-based learning (bBOA-OBL) is conducted to form the suitable input data frame. Based on the data frame, a novel convolutional network with an attention mechanism and feedforward of current (CAM-FoC) is proposed to calculate the grip force. The results of the ablation study tell that the master-slave trajectory has the highest accuracy, the optimized input data frame can reduce the error by 17%, and each component of CAM-FoC can enhance the measurement accuracy. Experiments and comparisons are also carried out. The root mean squared error (RMSE) in the experiment is only 0.1233 N and is lower than four other popular methods. In addition, the average computation time is around 2 ms on different platforms. The method manifests higher measurement accuracy than the state-of-the-art and is of acceptable computational complexity. The technology would potentially achieve grip force feedback in clinical usage, which can significantly improve surgery performance. The method could also be used by other robots composed of the cable-pulley mechanism to acquire external forces.
Design of Circular Structured One-dimensional Non-uniform Constellations with Better Performace

Adopting higher modulation order and spacing constellation symbols non-uniformly are two strategies in modern communication systems to meet increasing demand for data volume and to reduce the gap between bit-interleaved coded modulation (BICM) capacity and Shannon limit. This paper proposes a certain circular structured constraint strategy to design one dimensional non-uniform constellations (1D-NUCs) with remarkable performance. This strategy also ensures low demapping complexity (especially for high order NUCs) which benefits applications in power-limited systems. Meanwhile, a computable expression of BICM capacity based on polar coordinates is derived to revise constellation designing scheme with the proposed constraint strategy. Through the revised designing scheme, a set of circular structured 1D-NUCs with order of 1024 are obtained and testified having the ability to provide higher shaping gain than the ones adopted by ATSC 3.0 with low complexity.
Fault Tolerant Control against Actuator Faults Based on Interval Type-2 Fuzzy Sliding Mode Controller for a Quadrotor Aircraft

Fault-tolerant control (FTC) has earned increasing interest in the last few years for its reliability. A fault tolerant control system for operating a quadrotor aircraft in the presence of actuator faults and external disturbances is proposed in this paper. Firstly, the dynamic model of the quadrotor and types of actuator faults are presented. Secondly, an interval type-2- fuzzy sliding mode control (IT2FSMC) is proposed to stabilize the quadrotor if actuator faults occur. Compared to conventional sliding mode control (SMC), The results obtained confirm the validity and capabilities of the proposed FTC. Thirdly, by using the Lyapunov theory, asymptotic stability is confirmed. The efficiency of the proposed FTC is clarified by simulation results.
Fuzzy logic approach for knowledge modeling in an Ontology: A review

Fuzzy logic is an extension of Boolean logic created by Lotfi Zadeh in 1965 based on his mathematical theory of fuzzy sets, which is a generalization of classical set theory. By introducing the notion of degree or possibility, fuzzy logic confers very appreciable flexibility to the reasoning, which uses it, which makes it possible to take into account imprecision and uncertainties. Despite a beginning of reluctance and even rejection of the theory of fuzzy logic, it has been used in many fields. Today, its usefulness and its reputation are no longer to be demonstrated because more than 50 years after its appearance, it has been well adopted by engineers and part of the scientific world. In this paper, we present a state of the art on fuzzy logic and its use in the field of knowledge representation and more specifically in ontology modeling using OWL and SWRL.
Charge-pump Based Enhanced Gain Quasi Z-source Equivalent DC-DC Converter

In this paper, an enhanced gain switching-capacitor based boost DC-DC converter (EGSCBC) exhibiting the voltage transformation ratio better than the conventional Z-source dc-dc boost converter (ZSC) is proposed. Low ripple content in the source current is ensured naturally due to the presence of an inductor. On the basis of time-domain analysis, firstly the converter working principle is explained and then its L/C components design is established. A small-signal analysis is established to highlight the closed-loop regulation and controller design issues. A PID-type controller is designed to maintain constant load voltage. Proposed converter operation and its feasibility is demonstrated both in simulation and experiments. For concept validation a 100 W, 220 V converter with supply voltage of 28 V is made and regulation as well as closed-loop operation is verified.
Repairing 3D Models Obtained From Range Sensors

This paper presents a method to restore 3D models created from range sensors. The approach recovers the 3D information that is lost during the scanning process, usually due to inaccessible zones on the object (occluded areas and crevices). The raw and incomplete 3D data are first projected onto a grid to identify the zones to be repaired. Our algorithm calculates a suitable projection plane for each lost area defined and restores the 2D projected image. Finally, the inverse 2D to 3D transformation is carried out, and the new 3D data are merged with the initial mesh model, providing the completely restored surface. The approach has been tested on a database containing a wide variety of models, yielding excellent results. The experimental section shows that our method works for a large diversity of non-sensed and difficult-to-access zones and provides precise restorations.
High-Performance On-Chip Hot-Pressed NdFeB Hard Magnets for MEMS Applications

In order to advance the potential of thick on-chip hard magnets for the micro-electro-mechanical system (MEMS), we investigate a new silicon molding technique to fabricate dry-packed NdFeB magnets, including a silicon compression tool, which enables the pressing step during silicon-compatible processing. This process delivers samples with a remanence of 0.42 T and an energy product of 38 kJ/m3. Further studies of metal molding show that, for wax-bonding powder-based NdFeB magnets, the optimum fabrication condition is 300 °C and 425 MPa, giving a remanence of 0.54 T and an energy product of 61.7 kJ/m3.
Design of Fine-grained Plant Dataset and A Plant Image Acquisition Tool

Fine-grained plant classification has attracted great interest for its wide application. However, there is currently no suitable fine-grained plant dataset for deep learning. In this paper, we propose a method of constructing fine-grained plant dataset with adequate annotations. the dataset can help the methods to achieve better plant classification performance. Moreover, we develop an acquisition tool for collecting fine-grained plant dataset. The tool can mitigate the problem of collecting plant images in the fields.
Efficiency Analysis of a 7.4 kW Dynamic Wireless Charging System for Electric Vehicle Through GaN Devices

The efficiency analysis is very important aspect which needs to investigate and enhance specially whenever it concerns to the electric vehicles (EVs) where range is a big challenge. Nowadays, the wireless charging scheme for EVs is the most popular technics in which dynamic charging technology provides better solutions to eliminate basic challenges of the static wireless charging system. The dynamic charging system mainly consists of different power converters and coil structure, in which efficiency of the power converters can be enhanced by using new generation wideband semiconductor devices while proper structural arrangement and materials of the coils help in boosting the efficiency of the coil section. In this work, a 7.4 kW dynamic wireless charging system is considered and the loss modeling of each power converters as well as coil section are demonstrated. The loss matrix is plotted with the help of MATLAB coding for two types of semiconductor devices i.e. silicon (Si) and gallium nitride (GaN), along with the output current and frequency. The comparative analysis is presented for both types of devices i.e. Si and GaN for a considered DWC system. Further, efficiency analysis is portrayed to show the impact of GaN devices. It is observed that approx 7 % (average) efficiency is enhanced below 4000 W power and beyond this, approx 3 % (average) efficiency is enhanced in the case of GaN compared to conventional device.