Miracle-dz/UniFAR-FTUs huggingface dataset:
Unrestricted consumption under a deterministic wealth and an Ornstein–Uhlenbeck process as a discount rate

ABSTRACT We consider an individual or household endowed with an initial capital and an income, modeled as a linear function of time. Assuming that the discount rate evolves as an Ornstein–Uhlenbeck process, we target to find an unrestricted consumption strategy such that the value of the expected discounted consumption is maximized. Differently than in the case with restricted consumption rates, we can determine the optimal strategy and the value function.
A Compact Slot MIMO Antenna with Band-Notched Characteristic for UWB Application

In this paper, a very compact slot MIMO antenna with band-notched characteristic for ultra-wideband (UWB) application is presented. With two unsymmetrical dumbbell slot antenna elements, the overall size of this antenna is only $\pmb{24\times 20} \mathbf{mm}^{2}$. By introducing a decoupling slot on the ground plane, not only is the isolation between antenna elements greatly enhanced, the impedance performance is also improved significantly. A narrow line slot is etched into each element to obtain the notched band for blocking WLAN. The simulations are studied and the results show that the impedance bandwidth of the proposed antenna covers all UWB band from 3.1-10.6 GHz except the notched band, while a low mutual coupling of less than -18 dB is achieved at the entire band. Furthermore, the radiation performances and envelope correlation coefficient (ECC) also demonstrate the proposed antenna could be a good candidate for UWB system.
Image Processing Based Indoor Localization System for Assisting Visually Impaired People

Indoor localization or indoor positioning system is a known as a process of detecting position of any object or people inside a building or room by different sensory data collected from different devices using different techniques such as radio waves, magnetic fields, acoustic signals or other procedures. However, lacking of a standard localization system is still a very big concern. Solution of this issue can be very beneficial for people in many cases but it can be especially very beneficial for the visually impaired people. In this paper, an image processing based indoor localization system has been developed using OpenCV and Python by following color detection technique to detect position of the user with maximum accuracy and then location of user is determined by analyzing that location matrix. Location accuracy depends on the size of the matrix and successful identification of target color. Firebase real time database was added to the system which made real time operations between server and the user end device easier. To justify the proposed model, successful experiments were conducted in indoor environments as well and correct result was achieved each time by detecting accurate locations. This will be very advantageous to observe the fully or partially sightless people and guide them towards their destination and also to inspect them for their security purpose.
Generating Expert's Review from the Crowds': Integrating a Multi-Attention Mechanism with Encoder-Decoder Framework

Many consumers resort to others' assessments in product reviews for decision making, while their time is limited to deal with many reviews. Therefore, an expert's review which contains all important features in user-generated reviews, is strongly expected. In this paper, we study "how to generate expert's review from a large number of user-generated reviews (i.e., the crowds). " It can be implemented by text summarization, which mainly has two types of the extractive and the abstractive approaches. However, the former may generate redundant and incoherent summaries, while the latter cannot deal with long sequences. Moreover, both approaches usually neglect the sentiment information. To address the above issues, we propose a novel Expert Review Generation model to integrate a multi-attention mechanism with the encoder-decoder framework. We design a comprehensive preprocess strategy to identify the important sentences while keeping users' sentiment in original reviews, and use them as the input of the encoder-decoder generation model, so as to generate non-redundant and coherent summaries. Experimental results in two real world data sets (Idebate and Rotten Tomatoes) demonstrate that our model performs well in expert review generation.
Improving Large Scale Real-Time Ridesharing with Heuristics for Road Networks

Despite the great potential, ridesharing, especially with dynamic queries, has not been thoughly investigated on large-scale road networks often with many turns and one-way roads. In this paper, we treat one-way roads and viaduct roads of urban road network as heuristic information, and improve the response time of a two-phased ridesharing framework by pre-pruning some drivers to avoid complex shortest path calculation. We evaluate the proposed method using the data sets, which consist of road network and the large-scale trajectory data respectively generated by Brinkhoff road network generator in the city of Jinan, China. Results show that, our algorithm achieves a very high pruning ratio with little response time –only about 40ms in the case of 5000 drivers. It can be concluded that the improved framework is more effective for solving practical application problems.
Mitigation of DC-Link Voltage Oscillations Caused by Resolver Error in an Electric Vehicle Drivetrain

Resolvers are commonly used to measure the rotor position in motor drive applications. However, manufacturing imperfections introduce a position measurement error, which manifests itself as relatively small oscillations primarily at the fundamental and second harmonic frequencies of resolver true electrical position. This affects the field orientation control in machines, leading to oscillations in currents and electromagnetic torque. This paper focuses on the impact of position error in a series-hybrid drivetrain architecture. In this topology, substantial oscillations in dc-link voltage are induced, which are further exacerbated by reducing the dc-link capacitance in a bid to lower the overall inverter size and weight. A novel method to mitigate the aforementioned dc-link oscillations by estimating the position error of any desired harmonic is set forth. The method is validated by simulated and experimental results.
Comparison of Modular Dual 3-phase PM Machines with Overlapping/Non-overlapping Windings

Two modular dual 3-phase PM machines with 42-slots/32-poles (42S/32P) and 192S/32P combinations are compared to show the influence of winding configurations on modular machine performance. The proposed 42S/32P modular machine with redundant teeth for easy modularity adopts non-overlapping (NOLP) winding, while the conventional 192S/32P one uses overlapping (OLP) type. Based on the comparative study with two sets of winding operation, it can be found that two modular machines show similar torque performance with rated currents fed into windings. However, the slightly larger average torque is expected for the proposed modular machine with higher current. Moreover, the torque ripple of the proposed modular machine will not significantly vary with the current. The experiments validate the correctness of the analyses in this paper.
Low-Dimensional Vectors Learning for Influence Maximization

How to model the influence diffusion process accurately, a fundamental problem in influence maximization, is still an open issue. The existing researches mainly adopted pairwise manner to model the influence propagation between uses based on the social network. Thus, these approaches suffer severe over-representing and overfitting problems. This leads to the results of influence probability inaccurately, and further causes the influence maximization problem cannot be solved. This is the main problem we addressed in this paper, and we propose to calculate the influence propagation probability by learning low-dimensional vectors based on the information diffusion network. Our approach needs less parameters, and it can overcome the overfitting problem. Moreover, we propose a novel influence maximization algorithm based on the result of low-dimensional vectors learning. The experimental results illustrate our algorithm performs better than the baselines over the real world dataset.
Hybrid Switched-Capacitor/Switched-Quasi-Z-Source Bidirectional DC–DC Converter With a Wide Voltage Gain Range for Hybrid Energy Sources EVs

In this paper, a hybrid switched-capacitor/switched-quasi-Z-source bidirectional dc–dc converter is proposed for electric vehicles (EVs) with hybrid energy sources, which has a wide voltage gain range in the bidirectional energy flows. Compared with the traditional quasi-Z-source bidirectional dc–dc converter, the proposed converter only changes the position of the main power switch and employs a switched-capacitor cell at the output of the high-voltage side. Therefore, the advantages of the wide voltage gain range and the lower voltage stresses across the power switches can be achieved. The operating principle, the voltage and current stresses across the power switches, and the comparisons with other converters are analyzed in detail. Furthermore, the parameter design of the main components, the dynamic modeling analysis, and the voltage control scheme are also presented. Finally, the experimental results obtained from a 400 W prototype validate the characteristics and the theoretical analysis of the proposed converter.
Indoor Geomagnetic Positioning Based on a Joint Algorithm of Particle Filter and Dynamic Time Warp

The indoor geomagnetic field is affected by the steel structure and other ferromagnetic materials, resulting in the local anomaly of the magnetic field and the indoor geomagnetic field will be specificity. Benefit from this phenomenon, indoor magnetic positioning technology to be achieved. However, in large buildings, the specificity of geomagnetic field will be weakened, which leads to ambiguous positioning results. In response to this phenomenon, this paper presents a path matching based indoor geomagnetic positioning system, by increasing the number of matching features to solve this problem. The system combines Dynamic Time Warp (DTW) algorithm and Particle Filter (PF) algorithm to track the target in the path matching mode. Finally, Measuring robot loaded with magnetic sensor used to verify the results. The results show that the path matching has sufficient number of geomagnetic features to resolve the ambiguity of positioning results under condition of reduced specificity, and the positioning accuracy is better than 1 meter.
Complete Genome Sequence of Aeromonas rivipollensis KN-Mc-11N1, Isolated from a Wild Nutria (Myocastor coypus) in South Korea

We report here the complete genome sequence of Aeromonas rivipollensis KN-Mc-11N1, which was isolated from a wild nutria (Myocastor coypus) in South Korea. Genomic analysis indicated that A. rivipollensis may have zoonotic potential similar to that of other aeromonads, and nutria could be one of the sources of transmission of zoonotic pathogens to humans. ABSTRACT We report here the complete genome sequence of Aeromonas rivipollensis KN-Mc-11N1, which was isolated from a wild nutria (Myocastor coypus) in South Korea. Genomic analysis indicated that A. rivipollensis may have zoonotic potential similar to that of other aeromonads, and nutria could be one of the sources of transmission of zoonotic pathogens to humans.
Randomization in Robot Tasks

This article explores the role of randomization in the solution of robot manipulation tasks. Randomization refers to the ran dom selection and execution of an action from a collection of possible actions. The intention is that this collection contains some actions that are useful for making progress toward ac complishing a task, but that the precise identity of these useful actions is unknown. Randomization offers one approach for ensuring progress in a probabilistic sense. An example of randomization is given by the strategy of shaking a bin containing a part in order to orient the part in a desired stable state with some high probability. Another exam ple consists of using reliable sensory information to bring two parts close together, then relying on short random motions to actually mate the two parts once the part motions lie below the available sensing resolution. Further examples include tapping parts that are tightly wedged, twirling gears before trying to mesh them, and vibrating parts to facilitate a mating operation. Randomization is also useful for mobile robot navigation and as a means of guiding the design process. Randomization is useful in three basic ways. First, random ization can increase the class of solvable tasks. This is because a randomized strategy need not guarantee task success with certainty in a specific number of steps, relying instead on re peated execution of the randomizing actions to accomplish the task in an expected sense. Second. randomization can reduce a strategy's knowledge requirements. This is because randomiza tion can tolerate and circumvent local failures, thereby making a strategy less sensitive to task details. Third, randomization can simplify the planning and execution process. This is be cause a randomized solution may be able to ignore precise prediction of special case scenarios, instead simply ensuring eventual accomplishment of the task independent of the actual scenarios encountered.
Human Action Recognition: A Feature Point Trajectory and Space-Time Interest Point Based Approach

This paper proposes a new recognition algorithm to identify human action captured from unconstrained environments. Our approach considers not only feature point trajectory based de-scriptors but also 3D interest point based descriptors. First, we obtain reliable feature point trajectories through feature track-ing and background trajectory pruning. We then compute a rich set of motion descriptors, which are able to retain local motion information, shape and static appearance information for all reliable trajectories. Finally, we develop an adaptive feature fusion method for selectively combining feature point trajectory based descriptors and 3D interest point based descriptors ac-cording to the presence of camera movement. Extensive experi-ments were conducted to evaluate the effectiveness of the pro-posed algorithm using two benchmark data sets including the UCF Sports dataset and YouTube dataset. We have obtained impressive results for action recognition in the unconstrained environment.
Fine structure of the aggregate silk nodules in the orb-web spider Nephila clavata

ABSTRACT Among the triad spinning units for capture thread producing system in the orb-web spiders, aqueous gluey substances are produced from two pairs of aggregate silk glands (ASG). Although biochemical analysis of glue substance is produced by way of their passage through the ASG, its structural modifications in the nodular area have been nearly neglected till now. This paper focused on identifying the fine structural characteristics of the aggregate nodules in the golden orb-web spider Nephila clavata using both of light and transmission electron microscopes. The ASG in N. clavata is composed of a multi-lobed secretory region and a thick excretory duct surrounded by large irregular nodules. Histological analysis of the nodules demonstrates that the nodule forming cells have extensive membrane-bound tubular system that is continuous with the surface membrane. In particular, the nodule forming cells contain numerous mitochondria and glycogen particles within their cytoplasms, and they are surrounded by the same sheath of thin connectives. As previously described, each gluey droplet is formed of a central glycoprotein mass surrounded by an aqueous covering components, the nodular organization in N. clavata indicates that the extensive membrane system is thought to have a function for gluey silk production in spider. The results of this study also strengthen the premise that spider glues are made of glycoproteins, and the aggregate nodule functions as a key component for the spider web glue production.
A High Performance Slow-Wave Microstrip Line on CMOS Process

A high performance slow-wave microstrip line (S-MSL) structure is presented in this letter based on a 90nm CMOS technology. The ground planes of the S-MSL are composed of metal strips of two different metal layers which are long and thin, arranged in zigzags. Some test structures with different geometries are designed and fabricated using an eight-metal 90nm CMOS process. On-wafer measurements show that the proposed S-MSL demonstrates a better performance when compared to conventional microstrip line (MSL) and slow-wave coplanar waveguide (S-CPW). For one of S-MSLs, high quality factor Q ranges from 5 to 25 between 10 and 40 GHz. High effective dielectric permittivity no less than 28 leads to a very high slow-wave factor and high miniaturization. The wavelength of the measured S-MSL is 1.4mm at 40 GHz, much shorter than the conventional microstrip.
An Efficient Storage Format for Storing Configuration Interaction Sparse Matrices on CPU/GPU

Sparse matrix-vector multiplication (SpMV) can be used to solve diverse-scaled linear systems and eigenvalue problems that exist in numerous and varying scientific applications. One of the scientific applications that SpMV is known as Configuration Interaction (CI). CI is a linear method for solving the nonrelativistic Schrödinger equation for quantum chemical multi-electron systems and it can deal with the ground state as well as multiple excited states. A typical CI sparse matrix requires a significant large matrix for detecting and capturing more electron correlation. In this paper, we have developed a hybrid approach to reduce the space requirement of CI sparse matrices. The proposed model includes a newly-developed hybrid format for storing CI sparse matrices on the CPU/GPU. In addition to the new developed format, the proposed model includes the SpMV kernel for multiplying the CI matrix by vector using the C language and the Compute Unified Device Architecture (CUDA) platform. We have gauged the newly developed model in terms of two primary factors, memory usage and performance.
Numerical Analysis on Distributions of the Magnetic Field and Critical Current Density in the Bitter-Like HTS Magnet

High temperature superconducting (HTS) 2G tape has been extensively applied in the superconducting magnets. This paper presents the numerical analysis the distribution of the magnetic field and critical current density along with the radius in a Bitter-like HTS magnet at liquid nitrogen (77 K). The magnetic field of the Bitter-like HTS magnet was energized by the imposed current. Numerical results show that the magnetic field of the single RE-Ba-Cu-O (RE = rare earth) annular plate decreases along with the radius increasing. The critical current density increases with the radius increasing until the magnetic field reverses.
Stability Analysis of a Droop-Controlled Grid-Connected VSC

In this paper a small signal stability analysis of a reverse droop-controlled grid-connected voltage source converter has been performed. The analysis includes the getting of a state-space representation of the system and the calculation of their participation factors. Special emphasis has been given to the influence of parameters such as the short circuit ratio, the bandwidth of the phase-locked and the constants of the droop controllers on the stability of the system.
A Proposal towards the Design of an Architecture for Evolutionary Visual Software Analytics

The analysis of software systems, their evolution and visualization are dynamic research areas that have produced several promising methods. However, the use of these approaches has not been widely incorporated into practice because of the limited number of full featured open source and commercial tools available, and the absence of training for students and practitioners on their use. This research proposes the design of an architecture according to the results of previous research and the requirements of programmers and project managers of three companies that are sponsoring the project: a large international bank and two software development companies. The design of the architecture takes into account the need for an extensible and scalable architecture to incorporate new and existing methods to retrieve source code from different versioning systems, to carry out the advanced analysis of programs written in different languages, to perform the calculation of software metrics and to make visible the results of the analysis by means of visual representations, incorporated as Eclipse and Visual Studio extensions. The main contribution of this research is the design of an architecture to support the development of a architecture for evolutionary visual software analytics. The results obtained, so far, in the implementation of the architecture and the tests carried out are satisfactory, although, its validation with the partnering companies has not been carried out, yet.
Marchenko Equation for Time Reversal Imaging in an Underwater Acoustic Waveguide

Time reversal (TR) has been used to acoustic imaging to recover the spatial distribution of scatterers or the source location in an underwater acoustic waveguide. This study presents a method based on Marchenko equation, and we focus on achieving acoustic source distribution inside the medium. However, to achieve accurate results for TR imaging, a detailed model of the medium should be known. Otherwise, artifacts can emerge and the results will suffer a lot from model mismatch. Our proposed methodology aims to eliminate the artifacts caused by model mismatch, and to improve the results of imaging weaker sources. To achieve this, reflection data must be acquired from a vertical array and a transducer array is also needed to emit the signal iteratively.
A Novel Phase-lock Loop with Feed-back Repetitive Controller for Robustness to Periodic Disturbance in Three-phase Systems

While power networks evolve towards the new concept of smart grids, with the proliferation of power electronics embedded systems and distributed generation, the insurgence of system unbalance and voltage harmonic distortion, become more and more frequent. Also, often a noisy voltage sampling system can produce offsets in measurements. Such imperfections bring challenges to the phase identification using a traditional phase-lock loop (PLL), utilized in the control of all grid connected converters. However, since the imperfections lead to periodic harmonics in the corresponding dq-axis voltages, the repetitive controller (RC) can be useful for harmonic suppression. This paper presents a three-phase PLL using a feed-back RC. Specially, a novel running mean filter has been added to minimize the interaction between RC and the Proportional-Integral (PI) controller in the PLL. Simulation results show that the proposed PLL can track the phase of the three-phase voltage without being influenced by harmonic distortion.
Visualizing Design Process by Using Lean UX to Improve Interdisciplinary Team's Effectiveness – A Case Study

This is an ongoing project investigating on how to improve interdisciplinary teams to co-work efficiently and effectively. Based on our prior experiment, we found that new formed interdisciplinary teams struggled with poor team communication and coordination which resulting ineffective work progress and may lead to a project failure. In this paper we described such challenges the new formed interdisciplinary teams encountered in an experimental course where undergraduates from design and engineering disciplines collaborate on a project. We then proposed the use of Lean UX methods to visualize their design process so that all members' ideas and the idea exchange process can be "seen". It would help members in the same team getting more familiar with team's pace and well-coordinated with each member and then they may make the most of team effectiveness.