Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Similarity Search for Travel Behavior

To provide travel recommendations and planning in the intelligent transportation system (ITS), we must have the ability to find similar travel patterns among users based on their real mobility traces. To measure the similarity of user’s travel behavior, various methods have been proposed, but they usually only rely on a single attributes-related metric. In comparison, studies of the semantic relationships between travel attributes remain scarce, making it difficult to construct a complete mobility pattern that reveals the relevance between users or groups. In this paper, we introduced the heterogeneous information network to build a weighted travel network with spatial–temporal GPS trajectories. The heterogeneous network allows clustering the similar users based on the connections between different attributes instead of attribute values. On this basis, we defined the meta-paths for travel and used each meta-path to formulate a similarity measure over users by improving existing PathSim (Meta-path-based similarity measures) and SimRank. Next, we aggregated different similarities, where each meta-path was automatically weighted by the learning algorithm to make predictions. The experimental results showed that the recall of the similarity measurement algorithm using multiple meta-paths has improved, which yielded better results than the performance of the algorithm using a single meta-path. The performance of the improved PathSim model under different scales of data was 15% higher than the performance of the improved SimRank model in terms of precision and 21% higher in terms of recall. Due to the area under curve values, our experiments also show that a meta-path combination is more effective than the state-of-the-art approaches and can be efficiently computed.
Decomposing Models Through Dependency Graphs

In Model-Driven Engineering (MDE), models are the primary artifacts of software development life cycles. Being an abstraction of the real systems, models are generally believed to be less complex and better suited for developing, comprehending, communicating, and analyzing systems. However, such an advantage is decreasing with the tendency of models themselves getting more and more complex. In this paper we propose a model decomposition technique for reducing model size and consequently complexity by exploiting the notion of dependency graphs. Compared to its predecessor, this new model decomposition technique is more effective in terms of both the number of derived sub-models (more), the size of sub-models (finer), and the quality of sub-models (better). We demonstrate the improved effectiveness by applying both the previous and the new algorithm to a common example and comparing the results.
Step-by-Step Kinematic Modeling and Control of a Robot with a Free-Floating Base

Motion generation for legged mobile robots, which are characterized by an underactuated free-floating base, has become an important research topic in recent years. Although several research groups have addressed the problem of controlling the base in their own implementations, there is no work that completely describes the framework used to handle it, which makes it complicated for new researchers to find a proper solution. This paper aims at bridging this gap and presents a step-by-step guide to model the effect of the floating base on the kinematics of the robot, and to properly control it to achieve whole-body motion. The proposed framework is generic and can be applied to any legged underactuated robot such as a humanoid robot, a quadruped, an hexapod, amongst others. The results show an example of implementation using the model of a quadruped robot.
A Multi-Mode Biomimetic Wall-Climbing Robot

In this paper, a multi-mode biomimetic wall-climbing robot is represented, which employs spiny wheels, adhesive treads, spiny treads and a suction cup, and it can switch different modes with self-adapting to different terrains. The robot employs spiny wheels and spiny treads while meeting with rough surfaces and employs adhesive treads while encountering smooth surfaces. And a suction cup is applied all the time for assistive adhesive function. The adhesion property of the adhesive materials is analyzed, and their high reliability is proved. Moreover, the prototype of the robot is manufactured, and some experiments are completed.
A SVM and Co-seMLP Integrated Method for Document-Based Question Answering

In this paper, we describe our features and models for Chinese Open-Domain Question Answering DBQA shared task in NLPCC-ICCPOL 2017. After the analysis of task and dataset, 8 features were extracted, and then 4 models were trained. Finally, our model achieves a result, in which MRR score is 0.494292 and MAP score is 0.491736.
Logic-Equations-Based Modulation Technique for Natural Balance Control of an Improved Active-Neutral-Point-Clamped (I-ANPC) Multilevel Converter

Multilevel voltage-source power-converter topologies are used primarily for medium/high-voltage applications including adjustable-speed drives, FACTS devices, HVDC transmission, etc. Active neutral-point-clamped (ANPC) voltage-source converter as a derived topology from NPC family is a well-established configuration for medium-voltage market. This paper explores the Improved-ANPC (I-ANPC) converter and analyzes its major advantage compared with the classical flying-capacitor multilevel topologies. Further, a set of logic-equations are derived for natural balance control of the seventeen-level and twenty-one-level I-ANPC converters. The simulation results are presented to validate the logic-equations-based modulation method for control of the latter I-ANPC multilevel converters.
Volume-Based Large Dynamic Graph Analytics

We present an approach for interactively analyzing large dynamic graphs consisting of several thousand time steps with a particular focus on temporal aspects. we employ a static representation of the time-varying graph based on the concept of space-time cubes, i.e., we create a volumetric representation of the graph by stacking the adjacency matrices of each of its time steps. To achieve an efficient analysis of complex data, we discuss three classes of analytics methods of particular importance in this context: data views, aggregation and filtering, and comparison. For these classes, we present a GPU-based implementation of respective analysis methods that enable the interactive analysis of large graphs. We demonstrate the utility as well as the scalability of our approach by presenting application examples for analyzing different time-varying data sets.
Wideband and High Gain Patch Antenna Loaded with Mushroom-Type Metamaterial

A novel patch antenna loaded with mushroom-type metamaterial is proposed in this paper. The main drawback of patch antenna is narrow impedance bandwidth. The mushroom-type metamaterial is placed along with two radiating edges of the patch and much improvement in impedance matching is achieved on a $1/13\ \lambda_{0}$ -thickness substrate. Simulated results show that impedance bandwidth covers the whole Ku-band, and gains are more than 10 dBi in the operating bandwidth.
Complete Genome Sequence of Megasphaera stantonii AJH120T, Isolated from a Chicken Cecum

A novel bacterium, Megasphaera stantonii (strain AJH120T), was isolated from the cecum of a chicken during a screen for microorganisms using a brain heart infusion (BHI) medium. PacBio and Illumina MiSeq sequencing technologies were used to produce a single contiguous chromosome. ABSTRACT A novel bacterium, Megasphaera stantonii (strain AJH120T), was isolated from the cecum of a chicken during a screen for microorganisms using a brain heart infusion (BHI) medium. PacBio and Illumina MiSeq sequencing technologies were used to produce a single contiguous chromosome. The resulting genome sequence is 2,652,760 bp long with a 52.62% GC content.
Service Oriented Platform for Drones Competition

Drones are facing a huge success. They are available almost anywhere, either online or at a near shop, not only for enthusiasts but also for professionals of many areas, such as agriculture, construction, multimedia and military missions. In the same way, online platforms are growing fast. Many applications that we were used to be installed and ran locally in our devices are now deployed in the internet, with the benefits like high availability, high scalability and high compatibility with almost any laptop, computer, smartphone or tablet. Thus, the high level of interest and utility of drones and the crescent demand of service-oriented platforms surged up to be a great fusion of concepts. Nowadays, training and competition requires users to have their own aircraft(s) and to move, usually, to an arena where they can play with each other. Having it in consideration, in this work it’s proposed a platform that combines real-time online gaming and drones’ training and competition, in which users from around the world can socialize and play together. This paper runs through an overview of the concept, presenting the specifications and the requirements that the platform must meet to accomplish the desired objective. The proposed platform provides access to anyone, anytime, anywhere and with any device. It opens the possibility for users to communicate with each other and to control aircrafts with real-time video transmission, only achievable due to the distributed architecture designed, that minimizes the existence of single points of failure.
Research on Circuit-Level Design of High Performance and Low Power FPGA Interconnect Circuits in 28nm Process

Since the interconnect resources in FPGA cost more than 70% of the chip area, signal delay and power, it plays a crucial role in the implementation of high performance and lower power FPGA to improve performance and reduce power of the interconnect resources. The area, speed and power of the circuit are mutually constrained. Hence, how to design interconnect circuits with better performance and lower power has been a challenge in FPGA design.On the circuit-level design for FPGA interconnect circuits, this paper proposes topology selection strategy and Multi-Vt strategy. The experimental results in 28nm process show that the Decode structure has an optimal DAP (Delay-Power product) when the size of MUX is less than 16, while the 2-level structure has an optimal DAP when the size of MUX is bigger than 16,and pass transistors and NMOS in the first stage of the subsequent buffer are replaced by the ultra-low Vt transistor (ULVT) and low-Vt transistor (LVT) respectively can reduce the PDP(Power-Delay product) of interconnect circuits by 66.6%. Finally, these two strategies are used to optimize 8 types of interconnect circuits, and simulation results show that all the optimization rates of ADP (Area-Delay-Power product) are over 60%.
A histogram based calibration algorithm for MDAC linear and nonlinear errors in pipeline ADCs

In this paper, a histogram based calibration algorithm for pipeline ADC inter-stage linear and nonlinear errors is presented. To calibrate pipeline ADC inter-stage nonlinearities, MDAC transfer function needs to be established for error estimation. The transfer function is established by counting the output codes of a sub-stage to get the decision points. To verify the calibration algorithm, behavior model of pipeline ADC with histogram based calibration is constructed, linear and nonlinear errors are introduced to inter-stage MDAC. Simulation results show that, after calibration, SFDR improves from 60.4 dB to 80.2dB.
Understanding Urban Functionality from POI Space

Urbanization's rapid progress presents an urgent challenge for developing a predictive, quantitative theory to support the comprehensive understanding of the urban built environment. Among, the intertwined relationship between urban functionality and activity diversity has been widely recognized and quantified in terms of the richness of points of interest (POIs). In this research, we provided a novel methodology for revealing the co-occurrences of POIs within the city and the mechanisms of the interplay between them. We built and studied the network of relatedness between POIs, finding that more common POIs are located in a densely connected core whereas rarer and more unique POIs occupy a less-connected periphery. We simulated the diffusion process of the network in different sub-district, finding that common POIs act more on the speed of diffusion, unique POIs act more on the scope of diffusion. This research may help inform stakeholders the proper way of promoting the vitality of the local urban built environment.
Model Order Reduction of Nonlinear Circuit using Proper Orthogonal Decomposition and Nonlinear Autoregressive with eXogenous input (NARX) Neural Network

In this paper, we present a novel model order reduction (MOR) technique based on the proper orthogonal decomposition (POD) and Nonlinear Autoregressive with eXogenous inputs (NARX) neural network. In this proposed method, a set of solutions, referred as snapshots of the original problem are obtained at relatively large intervals. Proper orthogonal decomposition (POD) is used to reduce the order of the nonlinear model using the snapshot. The reduced system is modeled using NARX neural network. On applying the method to nonlinear electrical circuit, the results obtained, verify the validity of the new MOR technique.
Genome Sequence of Bacillus Phage Saddex

The complete genome of Bacillus phage Saddex was determined and annotated in this study. Saddex has distinct sections with similarities to other Bacillus phages, such as Kida, even though these phages were isolated more than 800 km apart by separate laboratories. ABSTRACT The complete genome of Bacillus phage Saddex was determined and annotated in this study. Saddex has distinct sections with similarities to other Bacillus phages, such as Kida, even though these phages were isolated more than 800 km apart by separate laboratories.
Disordered ZnO Nanowires Composited with Photochemically Reduced Graphene Oxide for Enhancement in UV Photoresponse

This article presents a high-performance ultraviolet (UV) photodetector based on one-dimensional (lD) disordered zinc oxide nanowires (ZNWs) composited with reduced graphene oxide (RGO) for improving the photon absorption and suppressing high recombination rate of electron-hole pairs (EHPs) in ZNWs. The RGO/ZNWs composites have been successfully synthetized through UV-assisted photoch. The material characterizations in morphology and Raman scattering verified the formation of graphene sheets attached in ZNWs network and the enhancement of UV absorption due to the introduction of graphene. In comparison with photodetectors based on pure ZNWs, the photodetectors based on RGO/ZNWs composite exhibit stable response to frequency-modulated UV irraddiation and enhanced photoresponse with photocurrent density of 5.87 ma-cm2, on/off current ratio of $3.01\times 10^{4}$, and responsivity of 1.83 A.W-1when a UV irradiation of 3.26 mw-cm−2and 1.0 V bias were used. Theory analysis is also presented to get insight into the inherent mechanisms of separation and transportation of photo-excited carriers in RGO/ZNWs composite.
USBL Positioning System Based Adaptive Kalman Filter in AUV

As an important platform for oceanographic survey, Autonomous Underwater Vehicles (AUV) have been widely applied to many fields such as the ocean research, oil and gas exploitation, fishing and military. The importance of underwater acoustic positioning become more obvious in AUV research missions, ultra short baseline (USBL) because of its lightweight and other advantages with widespread concern. The positioning accuracy of the USBL can be affected by its own or external factors, although a lot of effort has been spent on improving these weaknesses, the efficient and effective method has yet to be developed. A novel positioning system based Adaptive Kalman filter(AKF) is designed for USBL in AUV, AKF can adaptively adjust the measurement covariance matrix and the process noise covariance matrix by utilizing latest measurement data. Experimental results demonstrate that our system outperforms than simple USBL positioning in positioning accuracy.
DLL-Enhanced PLL Frequency Synthesizer with Two Feedback Loops and Body Biasing for Noise Cleaning

This paper presents the relevant aspects of the design of an ultra-low-power frequency synthesizer based on the combination of two feedback loops, a Phase-Locked Loop (PLL) acting together with a Delay-Locked Loop (DLL) to perform fine and coarse tuning of the desired output frequency, respectively. The objective of the circuit is to achieve a power consumption lower than 100 μA to generate a 2.5 GHz output frequency, improving the poor phase-noise of ring oscillators with the usage of the DLL circuit as an auxiliary feedback loop to cancel the phase noise and adjusting the VCO frequency through the body bias feature, available in the 28 nm FDSOI technology from STMicroelectronics.
Uneven-to-Even Power Distribution for Maintaining High Efficiency of Dual-Linearly Polarized Rectenna

The RF-to-dc power conversion efficiency (PCE) of the conventional dual-linearly polarized (DLP) rectenna often suffers from uneven RF power received by two ports of the DLP antenna, which is caused by a tilt angle between the linearly polarized incidence and the two polarizations of the antenna. In this letter, a hybrid coupler is employed to redistribute the uneven power from the DLP antenna to two even power distributions for a successive modified Greinacher charge pump (GCP). Thus, a high RF-to-dc PCE of the modified GCP can be maintained. Both theoretical analysis and experiment validate the proposed power distribution scheme, which maintains a stable high PCE of a DLP rectenna irrespective of polarization tilt angle. The proposed scheme is, thus, suitable for high-efficiency wireless power transfer.
CRNet: Corner Recognition from Trajectories Based on Convolutional and Recurrent Neural Networks

Corner recognition plays an important role in trajectory-route matching for fingerprint crowdsourcing in indoor positioning systems. However, the pose diversity and fake corner problem in most practical scenarios could much degrade the recognition performance. This paper deals with the two problems from a deep learning perspective. We design the CRNet consisting of convolutional and recurrent neural networks, which can recognize a corner from pedestrian movement trajectories directly from raw sensor measurements. Field experiments have validated its effectiveness in terms of much improved precision, recall and F1-measure compared with the state-of-the-art schemes. As the CRNet does not require manual feature extraction, we envision its wide applications in practical corner recognition scenarios.
Localisation Using Undersea Wireless Networks

Underwater navigation for Autonomous Underwater Vehicles (AUVs) is a challenging task, requiring a trade-off between performance, costs and operational time. The project Network Long Base Line (Net-LBL) proposes a system for acoustic-based navigation that relies on the addition of localisation services to underwater networks. The localisation capability is added on top of existing networks, without imposing constraints on their structure or operation. All the nodes can act as transponders of a network baseline, with no need for dedicated instrumentation. This paper evaluates the Net-LBL system using an interval method-based navigation solution in a number of configurations, including the use of TDMA and CSMA MAC protocols, range-only and bearing-only measurements, and with different geometries. Results collected during the NETLBL17b sea trial, held in the Gulf of La Spezia, Italy, are presented and discussed.
Analysis of Store Separation from Weapon Bay of a Blended-Wing-Body Underwater Glider

Based on the kinetic equation and kinematic equation, trajectories of a new blended-wing-body(BWB) underwater glider are simulated with a changing deflection of the center of gravity (CG), which indicates that the glide ratio degrades with the deflection of the center of gravity going larger. Numerical study on the store separation from the weapon bay of a BWB underwater glider, supported by the computational fluid mechanics and the six-degree-of-freedom model, is carried out. The specified separating course and the flow structure of the weapon bay are demonstrated. With the calculated hydrodynamic forces, the kinetic equation and kinematic equation are solved to get the affected trajectories of different attack angles.
Closed-loop Elimination of Low-order Sideband Harmonics in Parallel-Connected Low-Pulse Ratio VSIs

This paper proposes a closed-loop pulse width modulation (PWM) carrier phase shifting method for eliminating the low-order sideband harmonics in parallel-connected low-pulse ratio VSIs. A current sensor is added to measure the THD of total current to adjust the PWM carrier phase of inverters with closed-loop control. First, the low-order sideband harmonics caused by the multiple modulation references are analyzed. Then, the basic idea and the realization of the closed-loop PWM carrier phase shifting method are discussed. Finally, simulations and experimental results verified the proposed method.
Narrowband Filtering Balun Power Divider Based on SIW and CSRRs

A narrowband filtering balun power divider based on substrate integrated waveguide (SIW) and complementary split rings resonators (CSRRs) is proposed in this paper. The middle metal-grand of the SIW filter is used to achieve 180° phase difference. The forward-wave power division propagating below the characteristic cutoff frequency of the waveguide can be easily realized by four complementary split rings resonators. Good in-band performance (amplitude and phase imbalance are less than 0.16 dB and 2°) over the passband are implemented.
Draft Whole-Genome Sequences of 10 Atypical Enteropathogenic Escherichia coli Strains Isolated in Brazil

The number of diarrhea cases caused by atypical enteropathogenic Escherichia coli (aEPEC) has been increasing worldwide. Here, we report the draft whole-genome sequences of 10 aEPEC strains isolated in Brazil. ABSTRACT The number of diarrhea cases caused by atypical enteropathogenic Escherichia coli (aEPEC) has been increasing worldwide. Here, we report the draft whole-genome sequences of 10 aEPEC strains isolated in Brazil. These sequences will provide an important source for future studies concerning aEPEC pathogenicity and genetic markers of potentially virulent strains.
UltraSonic Watch: Seamless Two-Factor Authentication through Ultrasound

Two-factor authentication (2FA) provides an extra layer of security as it requires two pieces of evidence to be provided to an authentication mechanism before granting access to a user. However, people do not prefer 2FA; a reason for this is that 2FA requires performing extra actions. In this late-breaking work, we present UltraSonic Watch which provides a seamless 2FA through ultrasound. We report a small-scale within-subjects study (N=30) which investigates the performance of UltraSonic Watch and the participants' experience (in terms of perception, preference, and willingness to adopt). The results are promising as they revealed that ultrasound can be used to provide an efficient 2FA mechanism, transparent to the users, who are positive in adopting such an approach to increase the security of the authentication process.
Effective Modeling Approach for IaaS Data Center Performance Analysis under Heterogeneous Workload

Heterogeneity prevails not only among physical machines but also among workloads in real IaaS Cloud data centers (CDCs). The heterogeneity makes performance modeling of large and complex IaaS CDCs even more challenging. This paper considers the scenario where the number of virtual CPUs requested by each customer job may be different. We propose a hierarchical stochastic modeling approach applicable to IaaS CDC performance analysis under such a heterogeneous workload. Numerical results obtained from the proposed analytic model are verified through discrete-event simulations under various system parameter settings.