Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multi-Operator Retargeting Scheme for Compressed Videos

This research presents a multi-operator retargeting scheme, in which content-based cropping, seam carving/insertion and scaling are applied sequentially to adjust the video frames to the target resolution. Assuming that the video to be processed is encoded with H.264/AVC, compressed-domain data in the bitstream are utilized to classify video shots into different types for further processing. SLIC superpixels are formed to identify boundaries of objects and a saliency map will determine the visual significance of frame areas for appropriate cropping. A motion feature map is constructed to locate moving objects or contents so that possible distortions on them can be avoided. For static scenes, a local-significance-aware seam carving scheme based on one-dimensional gradients is applied. A SSIM-based blur detection method is also developed to extract sharp foreground objects. The experimental results show that the proposed method performs well in various kinds of video shots.
Deep social collaborative filtering by trust

The primary purpose of recommender system is providing valuable and pertinent information actively according to users' preference. Collaborative filtering (CF) is a successful approach among different recommendation techniques. However, CF-based methods usually suffer from limited performance due to the sparsity of rating data. To address such issues, utilizing auxiliary information such as content information and social networks is a very promising approach. This paper proposes an effective Bayesian hierarchical framework called Deep Trust Recommender (DTR), which aims to improve the quality of recommender systems by integrating user-item rating information and social trust network into the embedding representation. Specifically, we first apply deep learning methods like stacked denoising auto-encoders to learn the approximation representation of the users preference from the users trust network, and then take this representation to train with rating information collaboratively. Extensive experiments on two real-world datasets reveal that our approach performs much better than several widely adopted state-of-the-art recommendation methods.
AText Mining based Reliability Analysis Method in Design Failure Mode and Effect Analysis

Failure Mode and Effects Analysis (FMEA) is one of the basic and the most commonly used techniques in reliability analysis and management. Design FMEA is the application of the FMEA method in product development phase and have shown remarkable results in various engineering design fields. DFMEA reports usually contain a lot of text information about quality and reliability improvement opportunities for new product development. However, it can be very difficult and non-intuitive to fully understand these text information for design improvements. To address this challenge, we propose to apply text mining methods in DFMEA reports to discover the hidden reliability information. Specifically, three types of hidden information are investigated, which include the correlation of the failure related features in the potential failure mode or failure cause, the classification of failure modes and causes, and the optimal set of improvement activities according to the effect and cost metric proposed in this paper. Among them, one feature represents a failure characteristic or a location of the potential failure mode or failure cause (e.g. wear, break, bend, surface, insert, stem). These three pieces of information can be further integrated to product verification and validation process for effective risk identification and mitigation in a more economic and effective way. Finally, we illustrate the application of the text mining methods in DFMEA report for a subsystem in a power generation system within a diesel engine.
An Efficient Greedy Algorithm for finding the Nearest Simultaneous Diagonalizable Family

Diagonalization of given multiple squared matrices by a common similarity transformation is called Simultaneous Diagonalization (SD). The approximate SD problem for finding numerically a similarity matrix which diagonalizes approximately given multiple matrices has been a long standing challenge mainly due to its nonconvexity. In this paper, we propose a new efficient greedy algorithm for finding the nearest simultaneous diagonalizable family from given matrices, and extend an elegant SD approach named the DODO algorithm to the approximate SD problem by using the proposed algorithm as its preprocessing. Numerical experiments show that the DODO algorithm preprocessed the proposed algorithm achieves more accurate estimations of solutions of the approximate SD problem than the existing ones.
Compressive Online Decomposition of Dynamic Signals Via N-ℓ1 Minimization With Clustered Priors

We introduce a compressive online decomposition via solving an ${n}$-$\ell _{1}$ cluster-weighted minimization to decompose a sequence of data vectors into sparse and low-rank components. In contrast to conventional batch Robust Principal Component Analysis (RPCA)—which needs to access full data—our method processes a data vector of the sequence per time instance from a small number of measurements. The $n-\ell _{1}$ cluster-weighted minimization promotes (i) the structure of the sparse components and (ii) their correlation with multiple previously-recovered sparse vectors via clustering and re-weighting iteratively. We establish guarantees on the number of measurements required for successful compressive decomposition under the assumption of slowly-varying low-rank components. Experimental results show that our guarantees are sharp and the proposed algorithm outperforms the state of the art.
Power Factor Calculation Method for the Rectifier Which AC Side Connected CRM LCL Resonant Converter

In order to solve the equivalent inductance calculation problem caused by rectifier which AC side connected LCL resonant converter, a power factor calculation method for the rectifier which AC side connected LCL resonant converter is proposed. Based on the analysis of the working state of the rectifier which connected the critical conduction mode (CRM) LCL resonant converter, a mathematical model of the input voltage and current of the LCL resonant converter is proposed in the form of differential equation. And the fundamental voltage value of the parallel resonant capacitor of the LCL resonant converter is used to approximate its actual voltage value. The proposed method can be used to calculate the power factor of the rectifier which connected CRM LCL resonant converter. And then it can be used to design the CRM LCL resonant converter accurately so that the CRM LCL resonant converter works in a state close to unity power factor. Finally, simulation analysis and experimental verification are carried out. The simulation and experimental results show: the proposed method can be used to calculate the power factor of the rectifier which AC side connected CRM LCL resonant converter.
Simulation of Human Body Exposure to High and Low Frequency Wireless Power Transfer Systems using Simplified Models

In this paper, human body exposure to LF and HF electromagnetic field is analyzed. Antennas and wireless power transfer (WPT) systems are numerically modelled using commercial software FEKO. The analysis is carried out for two simplified models of human body (parallelepiped and cylinder model) exposed to radiation in terms of power transfer efficiency (PTE) and specific absorption rate (SAR)) at frequencies of 13.56 MHz, 6.78 MHz and 100 kHz. It is shown that the SAR in simplified human body model does not exceed the reference limit values prescribed by international guidelines. Used simplified models are validated by comparison with realistic human body model results at 13.56 MHz from literature.
Balanced-to-Unbalanced In-Phase Power Divider

This paper proposes an in-phase balanced-to-unbalanced (BTU) power divider (PD). The proposed PD is of Gysel type, so it can be realized for high power applications as well. Design equations for the proposed PD are derived analytically. Four short circuited parallel coupled lines with floating conductor are used to make circuit compact. To verify the design equations, one prototype for power division ratio 1:2 and one prototype for equal power division at a design frequency 2 GHz are fabricated and tested. Differential return loss of balanced port of both PDs is greater than 15 dB. Return loss of unbalanced ports and isolation between unbalanced ports of both PDs are greater than 15 dB. Common mode suppression is greater than 20 dB. Both PDs show good in-phase characteristic.
A New Space Harmonics Minimization Strategy for Fractional Slot Concentrated Windings

A new winding concept for fractional slot concentrated winding (FSCW) is proposed that can simultaneously cancel both sub and higher order harmonics of stator MMF. The new winding concept proposes two sets of three-phase windings by doubling the number of stator slots connected in wye-delta configuration. These two winding sets are shifted in space with respect to each other and are connected in series. The wye-delta configuration eliminates sub-harmonics and enhances the torque-producing component whereas their relative shifting angle eliminates the dominant higher order harmonics to provide a cleaner and enhanced spectrum. This concept is effective when the stator slot number is multiple of twelve. The application of the proposed winding to a PM machine demonstrated dominant sub and higher order harmonics cancellation, THD reduction, torque ripple reduction, and magnetic loss reduction along with torque density and power factor improvements.
Immersive Exploration of OSGi-Based Software Systems in Virtual Reality

We present an approach for exploring OSGi-based software systems in virtual reality. We employ an island metaphor, which represents every module as a distinct island. The resulting island system is displayed in the confines of a virtual table, where users can explore the software visualization on multiple levels of granularity by performing intuitive navigational tasks. Our approach allows users to get a first overview about the complexity of an OSGi-based software system by interactively exploring its modules as well as the dependencies between them.
A Study of Temporal Stability on Finger-Vein Recognition Accuracy Using a Steady-State Model

Stability has been one of the most fundamental premises in biometric recognition field. In the last few years, a few achievements have been made on proving this theoretical premises concerning fingerprints, palm prints, iris, face, etc. However, none of related academic results have been published on finger-vein recognition so far. In this paper, we try to study on the stability of finger-vein within a designed timespan (four years). In order to achieve this goal, a proper database for stability was collected with all external influences of finger-vein features (acquiring hardware, user behavior and circumstance situation) eliminated. Then, for the first time, we proposed a steady-state model of finger-vein features indicating that each specific finger owns a stable steady-state which all its finger-vein images would properly converging to, regardless of time. Experiments have been conducted on our 5-year/200,000-finger data set. And results from both genuine match and imposter match demonstrate that the model is well supported. This steady-state model is generic, hence providing a common method on how to evaluate the stability of other types of biometric features.
A parallel-res GRU architecture and its application to road network traffic flow forecasting

Gated Recurrent Units (GRU) is an effective architecture on time series analysis. But deeper GRU models are more difficult to train and degrade rapidly. In this paper, we proposed a Parallel-Res GRU architecture for road network traffic flow forecasting. We explicitly reformulate the Parallel-Res Path as learning residual functions with reference to the input layer and output layer, instead of stacked plain GRU layers. And we construct multi-level residual architecture. We provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can improve accuracy from considerably increased depth and reduce the degradation. On UCI's PEM-SF dataset, we construct a 20 layers Parallel-Res GRU model for road network traffic flow forecasting, and the experiments indicate a considerable improvement comparing with normal stacked GRU models.
QoE Degradation Attack in Dynamic Adaptive Streaming Over ICN

The dramatic growth in video demand has motivated content providers (e.g., Netflix and YouTube) to evolve towards Dynamic Adaptive Streaming over HTTP (DASH). However, the rapid growth of multimedia content presents content providers the problem of rapidly expanding the available bandwidth. Therefore, considering the effectiveness of the next generation networking paradigm, i.e., Information Centric Networking (ICN), recently DASH has been introduced to ICN. The inherent features of ICN including efficient content distribution and reduced bandwidth requirements greatly increases the network bandwidth utilization, which smoothly handles the multimedia content delivery. However, we identified that these features of ICN also causes new vulnerabilities in the network. In this paper, we propose a novel attack that exploits the two fundamental ICN characteristics: in-network caching and interest aggregation. We show that an adversary with limited resources is able to disrupt the adaptive behaviour of the DASH streaming control system to degrade the perceived Quality of Experience (QoE) of a benign user. In particular, the proposed attack that shows the vulnerability in ICN-based multimedia streaming, and forces DASH clients to oscillate with the high frequency and amplitude between various resolutions while streaming. We perform extensive simulations on AMuSt-ndnSIM to evaluate the attack performance, that is an increase in the annoyance factor in spatial dimension and the QoE degradation for the honest user. In addition, we propose possible countermeasures to alleviate these attacks.
Is the Optimized FFR Interference Avoidance Scheme Challenging the Future HetNets?

As mobile data demand continues to increase exponentially, networks are evolving via a new paradigm called Heterogeneous Networks (HetNets) that increases the network coverage and capacity, guaranteeing better UE performance. The deployment trend in the next generation systems is then high densification, which yields an Ultra-Dense Network (UDN). However, the Inter-Cell Interference (ICI) is a major challenge in the design and optimization of these networks. The common Fractional Frequency Reuse (FFR) schemes for ICI coordination are considered as one of the most efficient and cost-effective techniques to avoid interference. On the other, the Almost Blank Subframe (ABS) technique is more suitable to HetNets but need strict synchronisation between Macro and Pico nodes and feedback through X2 to set the optimum ABS patterns which is time consuming. In a recent work, we have studied the ABS and power control optimization to jointly maximize the number of satisfied users and minimize the power consumption. By analyzing the simulation results, we noted a similar performance when applying FFR instead of ABS for high density cases. Therefore, in this paper, we present the analysis and simulation results for the deduced optimized FFR scheme that maximizes the number of served users while minimizing the total consumed power. This provides useful insights into the development of optimized FFR techniques for future HetNets.
Network Device Allocation Optimization Using Genetic Algorithms

We present an optimization methodology for a pseudo-adaptive algorithm that assigns IOT devices to a set of networks. The age of The Industrial Internet of Things (IIOT) provides a fantastic opportunity to rethink traditional methods of device assignment amongst heterogeneous network options within an environment. To date, the only way to guarantee performance of a life-safety critical network was to invest in costly fixed and dedicated infrastructure that could not be a shared with non-critical building systems equipment. This paper describes a methodology to tune shared infrastructure communication pathways for reliability approaching fixed infrastructure solutions. The genetic algorithm (GA) developed maximizes devices' and networks' performance while minimizing infrastructure costs. We assume an assessment of each network available to each device in terms of QoS, and our GA running on a central controller at a remote server.
Force control of twisted and coiled polymer actuators via active control of electrical heating and forced convective liquid cooling

ABSTRACT For decades, numerous artificial muscles have been proposed in order to implement beneficial features of biological muscles into robotics. Unfortunately, traditional artificial muscles experienced difficulties in imitating properties of the biological muscles due to mechanical and control issues. Recently, twisted and coiled polymer actuators (TCP) have been shown to produce large mechanical power via thermal stimulations and strong linearity. In this paper, a high-performance TCP thermally cycled by electrical heating and forced convective liquid cooling is designed and associated control algorithms are presented. We elaborate the model of the TCP that is simple, yet provides insight into how the electrical heating and the forced convective liquid cooling contribute to the TCP actuation. The proposed model is verified by experimental studies. Based on the proposed model, we design a feedforward–feedback controller and switching laws, which actively control the TCP in both the heating and cooling cycles. Furthermore, we extend our control methodology to agonist–antagonist TCPs. From the experimental studies, the proposed method is shown to be effective in both single TCP and antagonistic TCPs. GRAPHICAL ABSTRACT
Novel Core Designs to Miniaturise Passive Magnetic Components

Converter sizes are often dominated by passive magnetic components. Passive magnetic component sizes are in turn limited by electromagnetic saturation and thermal limits. This paper covers two modifications to the air gaps of tape wound amorphous magnetic cores, made available by the advancement of additive manufacturing with magnetic materials. These are modifying the width of the core at the air gap and moving the air gap to a different location in the core. The objective was to reduce the effect of fringing flux, and to overcome the issue of a high loss zone and thermal hot spot being generated at the air gap, situated under the windings. These modifications will reduce temperatures and thus allow for smaller components before thermal limits are reached. The changes this causes to inductance, flux density and losses are highlighted and discussed.
Residential Location and Psychological Distance in Americans’ Risk Views and Behavioral Intentions Regarding Zika Virus

Two 2017 experiments with a U.S. national opportunity sample tested effects of location, psychological distance (PD), and exposure to location‐related information on Americans’ Zika risk views and behavioral intentions. Location—distance from mosquito transmission of the virus in Florida and Texas; residence within states with 100+ Zika infections; residence within potential mosquito vector ranges—had small, inconsistent effects. Hazard proximity weakly enhanced personal risk judgments and concern about Zika transmission locally. It also increased psychological proximity, and intentions of mosquito control, avoiding travel to Zika‐infected areas, and practicing safe sex. PD—particularly social and geographical distance, followed by temporal distance, with few effects for uncertainty—modestly and inconsistently decreased risk views and intentions. Exposure to location‐related information from the U.S. Centers for Disease Control and Prevention website—naming states with 100+ Zika cases; maps of potential mosquito vector habitat—increased risk views and psychological closeness, but not intentions; maps had slightly stronger if inconsistent effects versus prevalence information. Structural equation modeling (SEM) of a location > PD > risk views > intention path explained modest variance in intentions. This varied in degree and kind (e.g., which location measures were significant) across behaviors, and between pre‐ and postinformation exposure analyses. These results suggest need for both theoretical and measurement advances regarding effects of location and PD on risk views and behavior. PD mediates location effects on risk views. Online background information, like that used here, will not enhance protective behavior without explicitly focused communication and perhaps higher objective risk.
NF-κB/let-7f-5p/IL-10 pathway involves in wear particle-induced osteolysis by inducing M1 macrophage polarization

ABSTRACT NF-κB signaling pathway shows significant influence on wear particle-induced osteolysis, and this study aims to explore the underlying mechanism and the role of let-7f-5p in this process. A mouse calvarial osteolysis model was constructed with PMMA particles, and the bone marrow-derived macrophages (BMMs) were isolated from the osteolysis area. The expression of miRNA and protein was determined by qRT-PCR and western blot, respectively. The level of cytokines was evaluated with ELISA. Recombinant plasmids were transfected into cells for the endogenous expression of related genes. Dual-luciferase reporter assay was performed to determine the interaction between let-7f-5p and IL-10 in macrophage RAW264.7 cells. M1 macrophage polarization and expression of let-7f-5p were promoted in BMMs of osteolysis mouse model, compared with that in sham group. The expression of let-7f-5p was increased in the process of M1 macrophage polarization that induced by PMMA. Let-7f-5p was involved in M1 polarization in macrophages that treated with PMMA. IL-10 was negatively regulated by let-7f-5p. NF-κB regulated the expression of IL-10 through let-7f-5p. NF-κB participated in the PMMA-induced M1 macrophage polarization through let-7f-5p. Let-7f-5p contributed to PMMA-induced osteolysis by promoting M1 polarization of macrophages. The NF-κB/let-7f-5p/IL-10 pathway induces M1 macrophage polarization, and thus contributing to wear particle-induced osteolysis.
Biomechanical Design and Control of Lower Limb Exoskeleton for Sit-to-Stand and Stand-to-Sit Movements

In this paper, we present design and development phase of lower limb robotic exoskeleton that can assist paralyzed individuals. Motion of the human wearing exoskeleton is introduced by actuators. Both exoskeleton legs are attached to the supporting frame by passive universal joints. The exoskeleton provides 3 DOFs per limb of which two joints are active and one passive. The control actions i.e., sit-to-stand and stand-to-sit movements are triggered using Double Pole Double Throw (DPDT) toggle switch. The control scheme is implement using Switch control method and the feedback is provided by means of current measurement. This assistive device can be utilized for the disabled persons. The simulation results are provided that evaluates the performance of the control actions on exoskeleton.
Bounds of mmWave-Based Ranging and Positioning with Massive Uniform Rectangular Array

This paper aims at investigating the feasibility of ranging and positioning in millimeter (mm)-level accuracy by adopting millimeter-wave and 3D massive antenna array. The agent is equipped with massive phased uniform rectangular array (URA) and multiple anchors are considered in localization networks to pursue a higher accuracy, where a far-field environment is assumed for phased massive URA. Fundamental limits of both time-based ranging and positioning are derived by Crámer-Rao bound (CRB), where the relationship between the fundamental bound of range estimation and that of position estimation is theoretically clarified. Numerical results show that the proposed scenario achieves a precise mm-level accuracy for ranging and positioning.