Miracle-dz/UniFAR-FTUs huggingface dataset:
A Framework for Autonomous UAV Swarm Behavior Simulation

In the last several years a large interest in the unmanned aerial vehicles (UAVs) has been seen. This is mostly due to an increase of computational power and decreasing cost of the UAVs itself. One of an intensively researched area is an application of a swarm behavior within team of such UAVs. Simulation tools are one of the means with which quality of solutions in this matter can be measured. In this paper such simulation framework is proposed. The proposed framework is capable of taking under consideration interferences between communicating UAVs, as well as interaction between UAV and surrounding environment. Mathematical models based on which simulation is performed were described, definition of simulation scenario and results of exemplary simulation were also presented.
PLANKTONIC URINARY EPITHELIAL CELL COUNTS AS DISEASE INDICATORS IN OAB

Hypothesis / aims of study The urothelium has been found to be inflamed and infected in a proportion of patients with OAB. Recent studies have shown that the innate immune system dominates the defence of the bladder to such infection. Bacterial components bind to Toll-like receptors (TLR) and thereby activate innate responses. Animal studies identify surface cell shedding as an important component of this immunity. It has already been observed that urothelial hypertrophy and metaplasia are exhibited by patients with OAB in contrast to controls (1)(2). If OAB is associated with bacterial infection, it must feature increased urothelial cell shedding. It has long been demonstrated that urothelial cells can be seen floating in the urine when microscopy is used to examine fresh, unspun specimens for pyuria. They have usually been dismissed as contaminants and annoyances, but far from being irrelevant, the immune reaction confers potential significance. Outside of cytology, data on the pathological implications of urinary urothelial cells are sparse. This was a blinded, prospective, comparative, observational cohort study of patients presenting with, and without, Overactive Bladder (OAB) symptoms. The purpose was to compare urinary planktonic epithelial cell counts with other disease markers, and between patient groups.
Photoplethysmogram-based Cognitive Load Assessment Using Multi-Feature Fusion Model

Cognitive load assessment is crucial for user studies and human--computer interaction designs. As a noninvasive and easy-to-use category of measures, current photoplethysmogram- (PPG) based assessment methods rely on single or small-scale predefined features to recognize responses induced by people’s cognitive load, which are not stable in assessment accuracy. In this study, we propose a machine-learning method by using 46 kinds of PPG features together to improve the measurement accuracy for cognitive load. We test the method on 16 participants through the classical n-back tasks (0-back, 1-back, and 2-back). The accuracy of the machine-learning method in differentiating different levels of cognitive loads induced by task difficulties can reach 100% in 0-back vs. 2-back tasks, which outperformed the traditional HRV-based and single-PPG-feature-based methods by 12--55%. When using “leave-one-participant-out” subject-independent cross validation, 87.5% binary classification accuracy was reached, which is at the state-of-the-art level. The proposed method can also support real-time cognitive load assessment by beat-to-beat classifications with better performance than the traditional single-feature-based real-time evaluation method.
Type-Driven Verification of Non-functional Properties

Energy, Time and Security (ETS) properties of programs are becoming increasingly prioritised by developers, especially where applications are running on ETS sensitive systems, such as embedded devices or the Internet of Things. Moreover, developers currently lack tools and language properties to allow them to reason about ETS. In this paper, we introduce a new contract specification framework, called Drive, which allows a developer to reason about ETS or other non-functional properties of their programs as first-class properties of the language. Furthermore, we introduce a contract specification language, allowing developers to reason about these first-class ETS properties by expressing contracts that are proved correct by an underlying formal type system. Finally, we show our contract framework over a number of representable examples, demonstrating provable worst-case ETS properties.
Design and Application of a Dual Operation Mode Hybrid Mechanism

Serial and parallel configurations are mutually exclusive in performance and structure,this hinders the combination of performance advantages. To solve this problem, a novel hybrid configuration which can realize serial and parallel switching based on a motion bifurcation mechanism is proposed. First, the structure of the new configuration is introduced. Second, the mobility of the reconfigurable arm were analyzed,the mobility characteristic analysis is carried out for the overall manipulator.Then, the specific process of arm mode switching is revealed in order to realize the mode switching control of the arm in the later stage. The mechanism can be applied to both machining and manufacturing robots with a variety of station properties, as well as to the limb structure of multi-habitat bionic robots. In this study, the performance advantages of series and parallel configurations are put into full play, it promotes the practical application of reconfigurable mechanism.
Head Design and Optimization of An Emotionally Interactive Robot for the Treatment of Autism

Emotionally interactive robots with facial expressions have various applications, such as research, education, companion, entertainment, and so on. Apart from this, robots with facial expressions demonstrate unique therapeutic effects via eye contact, facial expression recognition and presentation, especially in the early intervention for autistic children. The present study focuses on the head design of a humanoid robot with facial expressions and demonstrates strong attraction of the emotional robotic head presented in the 20th China Hi-Tech Fair. Feedback of the general public's acceptance of the robotic head during the High-tech Fair, was combined with the special needs in treatment of autism, to optimize the design of a second generation of the robotic head. As a result, the mechanical structures of the key components of the head, including the shell of the head, the eyes, the neck, the tongue, achieved better performance, and fewer motors were used to generate more and reliable facial expressions. TPE material which is environmentally friendly and bio-compatible was used in making a more human-like skin covering the robotic head. The facial expressions of the big six basic emotions presented by the robotic head has been tested by the Face++ software, and the recognition accuracy of some facial expressions exceeded 96%. The contributions of the present study are threefold, first of all, it shows that limited number of motors can generate reliable facial expressions of the basic emotions; second, TPE material is suitable for making human-like skin covering the robotic head; third, it shows the potential of our robotic head to be a practical and clinical rehabilitation platform of training autistic patients to recognize and imitate facial expressions of emotions.
Research on collision avoidance of fixed-wing UAV

In this paper, a hybrid collision avoidance approach, outer planning control and inner emergency control, is designed to solve the problem of avoidance of the non-cooperative target and the cooperative UAVs in the formation. For non-cooperative target, a multi-layer obstacle avoidance model is employed to determine the current situation of the UAV, for which different layer corresponds to different methods. If the UAV is far away from the obstacle, the method of planning control is implemented. A collision cone with a transition domain is introduced to reduce response time and eliminate local minima. If the UAV is closer to the obstacle, an emergency avoidance method is needed to ensure safety. For the cooperative UAVs in the group, we set the avoidance strategy table in advance and select the best response method by optimizing the security value. The feasibility and effectiveness of the proposed strategies are verified by simulations.
Research on Lithium-ion Batteries State of Charge Estimation based on Interactive Multiple-model Cubature Filter

In this paper, an estimator Interactive multi-model cubature kalman filter (IMM- CKF) based on the combination of interactive multi-model algorithm (IMM) and cubature kalman filter (CKF) is applied to estimate the state of charge of lithium-ion battery. Firstly, two multiple models are set up to represent the different degree of parameter shift in the Lithium ion battery. Equivalent circuit methodology is used to construct the non-linear battery models. Secondly, the Interactive Multiple-Model Cubature Kalman Filter (IMM-CKF) and conventional Cubature Kalman Filter is used to estimate SOC of the battery. the numerical simulations and experiments have been done and the results show the effectiveness of interactive multi-model cubature kalman filter and its advantages over conventional methods with respect to estimation errors and variance. Compared with the traditional EKF, UKF and CKF algorithms, the IMM- CKF algorithm is found to yield better SOC estimation accuracy. The added computational cost of new estimator is acceptable.
Poster Abstract: A Fast Consensus-based Time Synchronization Protocol with Virtual Links in WSNs

The main drawback of average consensus-based time synchronization protocols is slow convergence, especially in a sparse network. By increasing the transmission range of nodes, the network becomes strongly connected and achieves faster convergence. However, this is not always a suitable solution. In this poster, a virtual link based time synchronization protocol (VTSP) in WSNs is proposed to improve the convergence speed of consensus-based protocols. The main idea is to increase the connection property of the network by adding virtual links between two-hop neighbors but without increasing the transmission range. Simulation results indicated that the proposed idea can achieve convergence nearly 4 times faster than gradient time synchronization protocol (GTSP)—a well-known consensus-based time synchronization protocol while still has same level of accuracy.
Passing the Baton: Effective hand-off at the bedside

Communication Breakdown is a major factor in 70% of sentinel events in hospitals. Nurses report there is a breakdown of communication during shift reports, with some information not conveyed accurately. Deficient communication during shift report directly affects patient safety, increases risk of falls, decreases patient satisfaction, and decreases teamwork between staff members (Anderson & Mangino, 2006).
Using Overlay Cloud Network to Accelerate Global Communications

The global communication puts a strong demand on the “one global network”. However, the public Internet faces great challenges to achieve this goal due to its inherent mechanisms. In this paper, we propose the global Overlay Cloud Network (OCN), a generic high-quality network built on the global public clouds, to accelerate global communications. We implement the OCN by three key techniques. First, we develop an automated topology planning technique to select the best candidate cloud nodes. Second, we design a novel time-varying routing technique to compute the best routes of OCN. Third, we implement a new dynamic transport layer to provide high-quality data transmission through OCN. We evaluate our prototype of OCN on real public cloud platforms. The results show that OCN substantially outperforms the existing underlay network with the RTT latency decreased by 15.2%, the packet loss rate reduced by 1.9% and throughput improved by 10X.
Demo Abstract: Transparent Remote Connectivity to Bluetooth Low Energy Devices

The evolution of the Internet of Things (IoT) has increased our needs for secure and transparent inter-connectivity between heterogeneous networks. We expect everything to be connected regardless of the access technology. However, an important part of the IoT consists of the short-range wireless communication technologies such as Bluetooth or ZigBee. These are not directly compatible with TCP/IP and so only usable within their physically bounded Wireless Personal Area Network (WPAN). We solve this problem with a new application-agnostic approach called Remote Connection Manager (RCM). RCM raises new opportunities to IoT ecosystems enabling transparent remote communication between an application and a (supposedly) short-range device. We implemented an open-source prototype for Bluetooth Low Energy (BLE) technology to validate our solution and demonstrate the potential of such an original approach.
Retinal vessel segmentation based on Generative Adversarial network and Dilated convolution

Retinal vessel segmentation, which can obtain rich eye information, is an important indicator for examining ophthalmology and cardiovascular diseases. The existing method results in a decrease in resolution due to continuous maximum pooling and downsampling operations, causing the network to lose detail on the image when upsampling and restoring the feature map, ignoring small vessels or allow false positives at terminal branches. In order to better solve these problems, this paper proposes a method for combining dilated convolutions with U-Net networks to detect small vessels. In order to force the generated samples to fit the real sample distribution as much as possible, this paper uses the least squares loss function to replace the Sigmoid cross entropy, which alleviates the problem of gradient disappearance. The experimental results show that the proposed method improves the segmentation accuracy and reduces the loss to a greater extent on the DRIVE and STARE datasets.
Temperature-Dependent Thermal Capacitance Characterization for SOI-MOSFETs

Thermal capacitances are required to describe the fast dynamic thermal behavior in the silicon-on-insulator (SOI) devices. This article presents a physical model based on the ac technique, together with the characteristic thermal frequency determination through the frequency response of the output conductance, for calculating the thermal capacitance of single-finger and multi-finger SOI-MOSFETs. The model accounts for the total gate width and substrate temperature, making evident the augmented thermal coupling when multi-fingers are used. The thermal capacitances and the corresponding time constants, extracted from a variety of gate widths and number of fingers, are correctly predicted up to a substrate temperature of 150 °C.
Automated Assessment of Computer Programming Practices: The 8-Years UNED Experience

The increasing popularity of distance education poses exciting new challenges. In particular, current pedagogical paradigms, such as competency-based education, require students’ continuous evaluation. That is, to master skills, students need to receive constant feedback to guide their experimentation processes. However, teaching teams are usually under-dimensioned to support the large number of students that online courses usually have. This paper presents the approach we have adopted at the National University of Distance Education to overcome this problem for the case of computer programming practices, which complements human evaluation with an automatic assessment system. The paper describes our system and reports its benefits with an empirical study from 2011 to 2018 that involved 14,944 students.
A Low Reverse Recovery Charge Superjunction MOSFET With an Integrated Tunneling Diode

A superjunction MOSFET with an integrated tunneling diode is proposed and investigated by simulations in this article. The tunneling diode comprised the N+ region and the P+ region on the surface of the P-base region is connected in series with the P+/P-pillar/N+ (sub) diode isolated by an oxide layer. The electrons are prevented from injecting into the P-pillar region from both the N-pillar region and the N+ (sub) region, which leads to a low reverse recovery charge in the proposed device. As a result, up to 72.2% and 74.1% reduction in the reverse recovery charge could be achieved when compared with the conventional one at 300 and 400 K, respectively.
Radiated Electromagnetic Bad Gap Antenna for ISM Band in Medical Application

This paper presents a radiated electromagnetic band gap (REBG) antenna at industrial, scientific and medical (ISM) operating band frequency. A microstrip monopole antenna with two electromagnetic band gap (EBG) elements at each side is designed. Subsequently, introducing an additional radiated element at the ground plane of the proposed EBG antenna is also investigated. The proposed antenna is simulated and optimized using CST Microwave studio software. The proposed antenna was also experimentally verified, exhibiting reasonable agreement between the simulation and measurement results. Interestingly, a wider bandwidth and higher gain is attained compared to the antenna without additional radiating element. Owing to its simple structure as well as good performance, the proposed antenna has the potential to be implemented for medical application.
Research on Evaluation Strategy of Development Degree of Military Academies

The evaluation of the development degree of military academies is the core content of the evaluation of military development institutions, and it has a great role in promoting the science, innovation and sustainable development of military academies. Judging the degree of achievement of the quality objectives of military academies, the calculation of the incremental value of military colleges and universities, the calculation of the input and output efficiency of military academies, the benchmarking of the development degree of military academies, and the development degree of military academies The evaluation strategy is carried out to provide some inspiration for the evaluation of colleges and universities.
Non-Blocking In-Network Caching for High-Capacity Content Routers

Unlike IP router's stateless forwarding model, a content router owns a sophisticated data plane, consisting of a three-stage pipeline, namely, FIB, PIT, CS. Generally, a pipeline runs only as fast as its slowest stage. Compared with PIT and FIB, CS design is more challenging because it has more data to read/write, may have more entries in its table to store and lookup, and needs to organize content objects to sustain frequent cache replacement. To address CS's performance issue, we propose a novel mechanism called “NB-Cache” from a network-wide point of view rather than a single router's. In NB-Cache, when packets arrive at a router whose CS is fully loaded, instead of being blocked and waiting for the CS, these packets are forwarded to the next-hop router, whose CS may not be fully loaded. This approach essentially utilizes Content Stores of all the routers along the forwarding path in parallel rather than checking each CS sequentially. Preliminary evaluation shows significant data plane performance improvement as 130% increase in throughput.
A Sparse Manifold Learning Approach to Robust Indoor Positioning Based on Wi-Fi RSS Fingerprinting

The emerging location-based applications depend on the fast and accurate positioning of mobile targets. Wi-Fi received signal strength (RSS) fingerprinting provides a promising solution to localize an object in indoor environments. Among the factors challenging the RSS fingerprinting based algorithms are the site survey cost and the time-varying environment, given the unreliable signal qualities. Here we present a novel approach to indoor object positioning using the manifold assumption on the radio map in RSS-location space. Thinking the measured RSS from one access point (AP) in different locations are randomly drawn from a nonlinear manifold (ground truth), we propose an expectation-maximization (EM) style algorithm to reconstruct the sparse representation of this manifold from the noisy RSS observations. Motivated by the observation that the radio map has a strong local correlation in the RSS-location space, we introduce a multi-scale constrained quadratic programming to approximate the manifold. Within limited iterations, we can estimate the ground truth RSS values and parameters simultaneously. As a result, the learned manifold is exploited to predict the object’s position: we develop a positioning algorithm by minimizing the manifold distortion effort which integrates both measurement error and manifold shape preservation. We conducted extensive simulations and experiments in different settings, testing the datasets collected in a building in the last 8 months. The results showed that the proposed approach was adaptive to the varying environmental noise levels, presenting robust positioning performance.
Context-Aware Service Chaining Framework for Over-the-Top Applications in 5G Networks

As over-the-top (OTT) applications such as videos dominate the global mobile traffic, conventional content delivery techniques such as caching no longer suffice to cope with mobile network users' requirements due to e.g., fluctuating radio conditions. In legacy 4G networks, mobile network operator (MNO) and OTT service providers (OSPs) are logically decoupled from each other, hence preventing them to share necessary context and enable in-network context-aware intelligence. The recently standardized 5G network architecture's softwarized and virtualized nature opens up new opportunities for flexible deployment of MNO- and OSP-operated network functions. In this work, we first extend the current 5G standard to enable third-party stakeholders to deploy their own user-plane functions (UPFs) within the MNO infrastructure. Based on this, we propose a service function chaining (SFC) framework within the 5G core network, which allows MNO to dynamically determine the optimal set of UPFs that each flow should traverse based on their real-time contexts. The proposed framework has been implemented in a testbed network. Through realistic experiments, we demonstrate that UPF deployment strategy plays a crucial rule in the resulting SFC performance, and our proposed scheme can achieve performance that is close to the benchmark. Furthermore, we establish recommendations on best practices of UPF deployment strategies in 5G network.
Docker-based Cloud System for Computer Programming Labs

Recently, the importance of software education has been emphasized all over the world. In Korea, software education has been introduced for elementary schools that have applied for software education since 2015, and software education has been adopted as a regular subject in all elementary schools since 2017. As the importance of the software industry grows, interest in coding education is increasing. In Korea, students must complete 16 hours of instruction in elementary school and 34 hours in middle school from 2019. In Korea, however, there are not enough professional teachers who majored in software, and many schools have poor laboratory environments. For successful software coding education, a basic hands-on environment should be supported. It is also difficult for the teacher to analyze and score all students’ program sources during class. In this paper, we propose a computer labs management system that can be executed within seconds by using images already generated by Docker for software education at school. And we implemented a programming practice management system using Docker. Our system provides the ability for teachers to automatically identify and score students’ source code as they conduct coding training.