Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Group-based Influence Maximization Method in Social Networks

Influence maximization is a classic problem studied in social network analysis. This problem is NP-hard and can be solved with a greedy algorithm. However, the method requires tens of thousands of Monte-Carlo simulations, which are very time consuming and not scalable. To improve this method, researchers presented the community-based influence maximization method. However, this method detects communities based on node connections while generally ignores the influence property of nodes. In addition, when computing the influence spread based on community structure, it loses sight of the community size and border nodes. To improve the community-based influence maximization method, this paper first finds groups with similar influence characteristics based on the influence property of nodes. Then influence spread is approximately calculated based on the group structure in which the group size and border nodes are considered. Experiments demonstrate that the group-based influence maximization method in this paper achieves better influence spread than corresponding community-based influence maximization methods with matching running time.
Profiling and Imaging Sonar Fusion Based 3D Normal Distribution Transform Mapping for AUV Application

To expand operation coverage and period of time with low cost, self-localization is needed for long range AUVs. For this, AUVs need to perceive the surrounding environment and localize its position based on the perceived information. The types of sensors that can be used for sensing environment are extremely limited in underwater because of water turbidity and low illuminance. Sonars are a conventional solution for underwater sensing, widely used for sensing underwater environment. Sonars, however, have perceptual ambiguity depending on viewpoint, and the loss of elevation information, which makes difficult to use. One of the ways to solve the difficulties of sonar is to use plenty of data acquired from varied angles and locations. More simple way is to use multiple sonars. In this study, we propose imaging and profiling sonar based 3D mapping. We presented 3D point cloud from two different sonars, and implemented NDT mapping to combine the data set. Considering the motion characteristic of AUV, we derived 4-DOF NDT algorithm and tested it in indoor water tank. As a result, we obtained consistent 3D point cloud map.
A Non-isolated Bidirectional Modular DC-DC Converter with Unipolarand Bipolar Structure for dc Networks Interconnection

In this paper, a novel bidirectional modular dc-dc converter (BMC) with unipolar and bipolar structure for dc networks interconnection is proposed. Compared with traditional dc grid-connecting converters, the proposed converter can realizes high voltage gain with a transformerless structure and reduce the voltage stress across switches. Then, to solve the unbalanced current problem among power units in the BMC, a submodular structure is introduced. The control system was optimized for grid-connection applications by introducing the phase-interval operation between submodules to reduce the current and voltage ripple in both sides. Besides, the control system can provide various control strategies, including output voltage control, voltage gain control and power control to maintain the voltage level or keep a constant voltage gain of the networks and performing precise power control. Finally, simulations of both sub-modular unipolar BMC and bipolar BMC were implemented, and a 1-kW experimental 3-level unipolar prototype was developed.
Analysis of Optimal Operation Conditions for GaN-based Power Converters

The use of Gallium Nitride (GaN) devices allows breaking the performance barriers of conventional silicon-based (Si) low power converters by increasing the operating frequency while reducing system power losses. This paper evaluates the influence of the current ripple, switching frequency and number of GaN devices on the performance of a bi-directional buck converter. Furthermore, hard-switching and soft-switching operation modes are evaluated, identifying the optimal operation conditions for GaN-based power converters. Analytical and simulation models are employed and the obtained results are experimentally validated on a 3 kW GaN-based bi-directional buck converter.
Detection of Vehicles in Multisensor Data via Multibranch Convolutional Neural Networks

Convolutional neural networks, or CNNs, raised the bar for most computer vision problems and have an increasing impact in remote sensing. However, since they usually contain multiple pooling layers, detection of exact borders of small objects at their original resolution remains yet a challenging topic. Additionally, efforts are being made to reduce the amount of training data. In this paper, we investigate the potential of fully convolutional neural networks (FCNs) for individual vehicle detection in combined elevation and optical data using relatively few training samples. By the proposed multibranch CNN, we combine object recognition within a deep learning framework with the object segmentation at a high resolution, for which two CNN branches are employed. Data fusion is accomplished with a pseudo-Siamese approach. The pixelwise classification likelihood, also referred to as heatmap, is harmoniously postprocessed by a vectorization module, which is based on the minimum bounding rectangle (MBR) extraction and allows for delineation of groups of vehicles. Two methods were developed in which MBRs are supported either by pairs of parallel lines or by region growing. Our approach allows efficient training with few training samples, while delivering high-quality detection results and good computational performance. In our detailed evaluation, we investigate the benefits of data fusion and compare our approach to other state-of-the-art networks. Different datasets were used, containing optical images and elevation data, derived either from airborne laser scanning or from photogrammetric reconstruction. The obtained results are very promising with F $_1$ scores up to 97%.
Age-Related Differential Stimulation of Immune Response by Babesia microti and Borrelia burgdorferi During Acute Phase of Infection Affects Disease Severity

Lyme disease is the most prominent tick-borne disease with 300,000 cases estimated by CDC every year while ~2,000 cases of babesiosis occur per year in the United States. Simultaneous infection with Babesia microti and Borrelia burgdorferi are now the most common tick-transmitted coinfections in the U.S.A. , and they are a serious health problem because coinfected patients show more intense and persisting disease symptoms. B. burgdorferi is an extracellular spirochete responsible for systemic Lyme disease while B. microti is a protozoan that infects erythrocytes and causes babesiosis. Immune status and spleen health are important for resolution of babesiosis, which is more severe and even fatal in the elderly and splenectomized patients. Therefore, we investigated the effect of each pathogen on host immune response and consequently on severity of disease manifestations in both young, and 30 weeks old C3H mice. At the acute stage of infection, Th1 polarization in young mice spleen was associated with increased IFN-γ and TNF-α producing T cells and a high Tregs/Th17 ratio. Together, these changes could help in the resolution of both infections in young mice and also prevent fatality by B. microti infection as observed with WA-1 strain of Babesia. In older mature mice, Th2 polarization at acute phase of B. burgdorferi infection could play a more effective role in preventing Lyme disease symptoms. As a result, enhanced B. burgdorferi survival and increased tissue colonization results in severe Lyme arthritis only in young coinfected mice. At 3 weeks post-infection, diminished pathogen-specific antibody production in coinfected young, but not older mice, as compared to mice infected with each pathogen individually may also contribute to increased inflammation observed due to B. burgdorferi infection, thus causing persistent Lyme disease observed in coinfected mice and reported in patients. Thus, higher combined proinflammatory response to B. burgdorferi due to Th1 and Th17 cells likely reduced B. microti parasitemia significantly only in young mice later in infection, while the presence of B. microti reduced humoral immunity later in infection and enhanced tissue colonization by Lyme spirochetes in these mice even at the acute stage, thereby increasing inflammatory arthritis.
Energy Co-ops as a Driver for Bio-Energy Sector Growth in Ukraine

The paper deals with the assessment of economic benefits from biogas projects realization within energy co-operatives in Ukraine. The implemented state support tools for renewable energy growth in Ukraine caused significant disparities in the various renewable energy technologies development, where the bio-energy sector, in particular electricity generation based on animal waste, takes the last position. Based on the analysis, it has been proved that the main barriers for biogas sector development are the need for significant initial investments to construct profitable biogas plants and a large amount of raw materials for their uninterrupted operation. In order to eliminate these barriers, it is proposed to combine the financial and raw material resources of small farms within energy co-operatives. The results of the research prove that the realization such biogas projects makes economic sense and can provide significant financial benefits for the farms’ owners.
Filtering Antenna Based on Substrate Integrated Waveguide and Patch Resonators in LTCC

A filtering antenna is proposed with substrate integrated waveguide and patch resonators in low temperature co-fired ceramic. It is design with the topology of coupled resonators embedded with a lowpass filter. Due to the two 45-degree linearly polarized patches, the measured gain is 7.0 dBi with the 3-dB beamwidth of 48° and the antenna efficiency of about 70% around 28 GHz. The passband bandwidth is over 2.5 GHz. The out-of-band rejection can reach 18 dBc up to 40 GHz. According to the stacked antenna-in-package form, the volume of the overall component is only $12\times 6\times 1.6\ \mathrm{mm}^{3}$.
A Two-Stage AC-DC Converter with $\Delta-\sum$ Configuration for Wide Output Voltage Range Applications

A two-stage AC-DC converter with $\Delta-\Sigma$ configuration is studied for wide output voltage range application. A three-port rectifier (TPR) with two output ports is employed to realize power factor correction and create two paths for input power. One path goes through a LLC resonant converter, the other path goes through an unregulated DC-DC transformer (DCX), The converter improves the efficiency by two ways. First, the TPR itself reduces voltage stress for switches and diodes, which reduces switching loss. Second, the DCX process a part of power which is good for overall efficiency. Dual loop control and dual carrier modulation are used to regulate the TPR. The selection methods of the voltage range of the TPR output is also been discussed to achieve relatively high efficiency under wide output range. Experimental results based on a 1KW prototype are provided to evaluate the effectiveness and advantage of the analyzed method.
Context Combined Cascaded Region Proposal Network with Dual Loss Function for Accurate Car Detection

Car detection in the wild suffers from the problem of high occlusion and complicated scene disturbance. In this paper, we propose a novel Context Combined Cascaded Region Proposal Network (C3RPN) with dual loss function which addresses these problems at three dimensions: (i) we propose a cascaded two-stage region proposal structure that removes the limitation of fixed anchor boxes, (ii) Smooth L1 loss and Intersection over Union (IoU) loss are adopted to optimize the two stages respectively for better convergence and finer proposal regression, (iii) we integrate the complementary information between the proposed area and its context to strengthen the ability of accurate localization. We conduct extensive experiments on KITTI benchmark to prove the effectiveness of C3RPN. Results show that the proposed C3RPN outperforms Faster-RCNN with a large margin of 10.91% relative mAP gain and is robust to occlusion and background variation.
Viability Assessment of a Real-Time Simulation Model for a Residential DC Microgrid Network to Compensate Electricity Disturbances in Puerto Rico

With the passing of hurricanes María and Irma, the island of Puerto Rico was left devastated. This disaster left the electric grid de-energized and millions of people, schools, and hospitals without power. The extended blackout demonstrated a need for energy alternatives that supply power during times of crisis when traditional electricity is not readily available. A system that makes use of renewable energy generation, battery storage and electric vehicle integration can be a feasible alternative during periods when the utility cannot successfully supply power to consumers. In addition, excess power can be supplied to neighboring microgrids. Real-time (RT) simulation tools can demonstrate dynamic operations of these systems. This paper presents a RT simulation model that emulates residential electrification through a microgrid. This dynamic model is a planning tool for microgrid power systems to select designs capable of operation during months-long blackouts.
Cross-Coupling Control in Linear and 2D Arrays

Acoustic cross-coupling between array elements is a well-known cause of variation of the array performance. Cross-coupling prediction and control is an important part of the array design process especially in arrays with low internal acoustic loss level where cross-coupling can strongly affect angular and frequency response of the array. This work presents the results of Finite Element modelling of the angular and frequency behaviour of linear and 2D arrays and describes cross-coupling control techniques that can be used to alter angular and frequency response of linear and 2D arrays with uniform element spacing.
Rate kinematics of in-parallel manipulator systems

The following questions are addressed: how to determine the joint rates and constraints on the end-effector rates and how to know which joint rates are instantaneously inactive and which can be driven independently. The approach is based on the instantaneous properties of series chains as derived from the theory of screw systems. In this framework, those screws that correspond to the joint rates of the constituent series chains are identified. Once the correspondence is determined, the sought-after kinematic properties can be deduced from the vector space properties of these screws. <<ETX>>
Modeling Smart Cyber Physical Systems Based on ModelicaML

Cyber-physical systems are a kind of emerging large-scale distributed systems that are integrations of computation, networking, and physical worlds. Cyber physical systems are increasing scale and complexity with the growing pervasiveness of ICT and the development of the smart worlds such as smart factory, smart robotics, smart grids, smart cities, smart vehicles, smart healthcare systems, and smart homes. The growing interconnection of physical and virtual worlds of complex cyber physical systems, and the development of increasingly sophisticated intelligence techniques, has given rise to the next generation of CPS, that is referred to as smart cyber-physical systems (sCPS) which can efficiently operate, manage and control physical world and virtual world, and offer broad range of novel applications and services. Thus, smart cyber physical systems are complex cyber physical systems endowed with intelligent abilities. The main characteristic of such a new generation of smart cyber physical systems is the ability to interact with the physical worlds and adapt to new working environments through distributed intelligent mechanisms that executing and operating at the unit (single device), cluster (groups of devices) and network level (the network of devices). The properties like uncertainties, safety, reliability, and performance requirement, spatial-temporal requirement, and adaptation ability are very important, modeling smart cyber-physical systems must face these challenges and satisfy these specific requiremnts. In order to specify and model such kind of systems, we propose a new paradigm for specifying and modeling smart cyber physical systems based on software defined approach using Modelicaml. Software defined approach is a new way that help abstract the real world and virtual world with software components, this approach can simplify system specification, modeling and design. The main aim of ModelicaML is to enable an efficient and effective way to use Modelica, UML and SysML models reusing notations that are also used for software modeling based on software defined approach. The effectiveness of the approach is demonstrated with a case study of Vehicular Ad-hoc NETwork.
Managing Lifetime Healthcare Data on the Blockchain

The widespread adoption of fax machines in the 1980s revolutionised everyday communications. It was quickly adopted as the standard form of communication across the globe. Since then, the internet has replaced fax as a truly global form of instant communication. However, the fax machine still reigns as the primary form of communication in a number of industries, healthcare being one of them. This paper presents a system that uses a blockchain and an off-chain centralised data storage to give patients and medical professionals instant access to their medical records from anywhere. By assigning each medical record a pseudo anonymous identifier, a second layer "blockchain" for each user can be created allowing for the rapid collection and querying of data. The off-chain pseudo anonymous data storage allows for the data to remain unencrypted enabling the rapid generation of anonymous medical datasets which can be used for machine learning and data mining on the data, potentially bringing many benefits to the healthcare industry.
A Compact Hybrid-Fed Microstrip Antenna for Harmonics-Based Radar and Sensor Systems

In this letter, we propose and experimentally validate a compact hybrid-fed microstrip antenna for the harmonics-based radar and sensor systems, which receive the fundamental tone and retransmit the modulated second harmonic. The proposed microstrip antenna is based on a simple single-layered and dual-feed structure, consisting of an inner circular patch operating in the TM110 mode (second harmonic; 6 GHz) and an outer split-ring patch operating in the higher order TM210 or TM310 mode (fundamental frequency; 3 GHz). By varying the feed position and the geometry of the split-ring patch, a specific higher order mode can be excited at the fundamental frequency. Moreover, analytical expressions were derived for calculating the antenna's resonant frequencies. Our measurement results show that the maximum realized gain is 1.17 dB at 3 GHz and is 3.33 dB at 6 GHz, with good impedance matching (|S11| < −15 dB) and high isolation (< −20 dB).
Strain Distribution Induced in SOI Photonic Substrate by Through Silicon via Using Advanced Scanning X-Ray Nano-Diffraction

In 3-D integration, dice are vertically interconnected with through silicon via (TSV), which consist of holes etched in a thinned silicon substrate and filled with copper. This process induces thermal strain in surrounding silicon. New trends in 3-D integration imply the fabrication of Si photonic devices like waveguides in silicon-on-insulator (SOI) substrates containing TSVs. Thus, a quantitative analysis of strain in active areas around TSVs is mandatory. In this paper, the strain induced by the TSVs in both the bulk silicon and the SOI layer was investigated by using advanced scanning X-ray nano-diffraction. The crystallographic orientation offset between the separated silicon areas allows decorrelation of the strain in the Si layer of the SOI and Si substrate. Using synchrotron radiation, 2-D quicK continuous mapping of the strain in a region of 50 $ \mu \text{m}\,\, \times $ 50 $ \mu \text{m}$ with 500 nm spatial resolution was performed around a single TSV at room temperature and during in-situ annealing at 460 °C. The strain field induced by the TSV appears negligible in both silicon areas. The effect of in-situ annealing on the strain distribution is surprisingly weak. In the SOI active layer, the strain map mimics the surface pattern generated by the photonic devices processed at high temperature in this thin layer.
Robust Sparse Overlapping Group Lasso for indoor localization

Indoor localization based on Receive Signal Strength Indicator (RSSI) is widely used due to its low infrastructure cost. Unfortunately, RSSI is always fluctuating because of multipath effect, human movement and environmental change, which makes traditional methods get unexpected results. What’s more, state-of-the-art clustering algorithm divides offline radio map into the different non-overlapping group while ignores the fact that different groups should share the same members. In this paper, a novel Robust Sparse Overlapping Group Lasso (RSOGL) algorithm is proposed for indoor localization. The scheme first utilizes similarity between the offline Reference Point (RP) and online Test Point (TP) to obtain overlapping group via Fuzzy C-means (FCM) clustering, and then uses RSOGSL algorithm to reconstruct TP’s fingerprint. Our RSOGL system has been operated in a real environment. Experimental results demonstrate that proposed system outperforms traditional fingerprinting methods.
An Optimized, Multiphase Switched-Capacitor DC-DC Converter with Variable-Gain

A variable-gain, multiphase switched-capacitor DC-DC converter is proposed and implemented as an integrated circuit. The converter utilizes an optimized switching configuration that maximizes the number of attainable ideal conversion ratios for the given number of capacitors, according to the generalized Fibonacci number. This property allows the converter to maintain high efficiency across a wide range of operating conditions. A set of sample switching sequences are provided to generate any attainable ideal conversion ratio, for up to four capacitors. An experimental prototype of the converter is designed and fabricated using $0.35 \ \mathbf{\mu} \mathbf{m}$ CMOS technology to validate the performance.
A Reflected Dual-Band High-Efficiency Polarization Conversion Metasurface

In this paper, a novel dual-band reflective cross polarization converted meta-surface is designed. Its unit cell is composed of three pairs of oblique V-shaped structure mounted on a grounded dielectric substrate. The simulation results show that the incoming linearly-polarized wave will be reflected with its cross-polarized state in the two frequency bands $(\pmb{5.66\sim 9.46\mathrm{GHz},12. 2\sim 13.55\mathrm{GHz})}$ with conversion efficiency higher than 90%. Furthermore, the principle of operation, detailed design are also presented and discussed.