Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Spectral-Efficiency of Low-Complexity and Resolution Hybrid Precoding and Combining Transceivers for mmWave MIMO Systems

Millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems will almost certainly use hybrid precoding to realize beamforming with few numbers of RF chains to reduce energy consumption, but require low complexity technique to improve spectral efficiency. While energy-efficient hybrid analog/digital precoders and combiners designs can subdue the high pathloss inherent in mmWave channels, they assume the use of infinite- (or high-) resolution phase shifters to realize the analog precoder and combiner pair which results in high hardware cost and power consumption. One promising solution is to employ the use of low-resolution phase shifters. In this paper, we first diverse the exploration of multiple candidates of array response vectors, to propose low-complexity hybrid precoder and combiner (LcHPC) design via stage-determined matching pursuit (SdMP) namely, LcHPC-SdMP for pursuing better achievable rate for mmWave MIMO systems. We initially decouple the joint optimization over hybrid precoders and combiners into two separate sparse recovery problems. Specifically, LcHPC-SdMP algorithm revises the identification step of orthogonal matching pursuit (OMP) to the selection of multiple “correct” column indices of the matrix of array response vectors, per iteration. Then adds a pruning step –after satisfying a sparsity level condition, to iteratively refine the sparse solution which aids in further accelerating the algorithm, by requiring fewer iterations. We then propose an algorithm which iteratively designs low-resolution (two-bit) hybrid analog-digital precoder and combiner (LrHPC), for pursuing efficiency while maximizing spectral efficiency. Simulation results demonstrate that the proposed LcHPC-SdMP algorithm performs very close to its full-digital precoding and achieves better spectral efficiency over state-of-the-art algorithms with a substantially reduced number of iteration than the recently proposed schemes. In addition, simulation results also reveal that the achievable rate of the proposed LrHPC algorithm is higher than those of the existing algorithms under consideration.
A fuzzy gain scheduling control algorithm for formation flight of multi-UAVs

This paper presents a consensus-based coordination protocol, using a fuzzy logic gain scheduling algorithm, for the formation flight of multiple quadrotors UAVs. The Newton-Euler approach is used to present the equations of motions for the multiple quadrotors UAVs. The formation flight consists of a distributed approach. Real-time experiments are presented in order to test the capabilities of the online tuning of consensus parameters, as well as a comparison with a fixed gain protocol. In effect, the variable gain consensus protocol shows a smoother output while maintaining a robust performance against induced wind gusts, in comparison with fixed gain coordination approach.
Resource Management of LTE-U Systems for Channel Utilization and User Satisfaction

Deploying long term evolution (LTE) system into unlicensed spectrum for offloading faces two challenges: 1) the metrics of instantaneous performance to characterize user satisfaction are no longer applicable due to non-contiguously available channel and 2) in a light traffic scenario, the channel utilization is low due to the added padding bits of simultaneously scheduled users. To tackle these two issues, dynamically configuring channel occupancy duration (COD) and flexibly allocating subcarriers are needed to design for the LTE system operating in unlicensed spectrum (LTE-U system). In this paper, the channel utilization in the COD and a unified user satisfaction are first defined to characterize the performance of LTE-U system. Then, a time–frequency two-dimention optimization problem is formulated to maximize the weighted sum of the two defined performance indexes. To achieve the tradeoff between the two performance indexes, a control factor is introduced. By using Lyapunov optimization and Dinkelback theory, an optimal time–frequency resource management algorithm is developed. The results show that the proposed algorithm outperforms the baselines, as the algorithm can flexibly balance the two performance indexes of the LTE-U system for diverse applications.
Sparse optimal feedback control for continuous-time systems

In this paper, we investigate a sparse optimal control in a feedback framework. We adopt the dynamic programming approach and analyze the optimal control via the value function. Due to the non-smoothness of the $L^{0}$ cost functional, in general, the value function is not differentiable in the domain. Then, we characterize the value function as a viscosity solution to the associated Hamilton-Jacobi-Bellman (HJB) equation. Based on the result, we derive a sufficient and necessary condition for the $L^{0}$ optimality, which immediately gives the optimal feedback map. In addition, we consider the relationship with $L^{1}$ optimal control problem and show an equivalence theorem.
Time-Coordinated Control for Unmanned Aerial Vehicle Swarm Cooperative Attack on Ground-Moving Target

In this paper, cooperative attack control law analysis and design problems for unmanned aerial vehicle (UAV) swarm attack on ground-moving target with time-coordinated strategies are investigated. First, the time-coordinated control problem for a single UAV is formulated, which is the foundation of solving the problem of a single UAV arriving at the desired attack position relative to ground-moving target at a specific terminal time. Then, relative motion between each UAV and ground-moving target is considered as a finite-time time-varying tracking system problem, and the difference between expected output and system output is defined as tracking error vector. The control law is obtained by linear quadratic optimal control theory to minimize the energy cost in the whole process and the tracking error at the terminal time. Besides, time-coordinated function, which is critical to coordinate terminal time among all UAVs in the UAV swarm, is proposed to model time-coordinated strategies. Finally, numerical simulations show that the proposed control law can steer UAV swarm to arrive at the desired attack positions and achieve the time-coordinated strategies effectively.
High Throughput and Low Complexity Implementation for Uplink Scheme of 5G Technology

In order to increase the efficiency of utilizing transmission bandwidth on 5G technology, a non-orthogonal multiple access (NOMA) scheme is emerging on this research topic to support multiple users for uplink transmission. In this paper, we present an Uplink Sparse code multiple access (SCMA) system based on the euclidean distance between received constellation points and the reference constellation points set and the biding relationship of resources. Low-density Parity-check (LDPC) decoding is used for channel coding in our system. In order to speed up processing latency, a 2-level piplined decoder is proposed. Firstly, we have designed and simulated for 6 users-Uplink SCMA system using MATLAB code, then we have implemented the system using Xilinx Generator. The results show that the system not only ensures BER requirements but also significantly reduces hardware resources and increases transmission throughput compared to the reference system.
Research of perspective materials for thin optical films for the mid-IR

The intensive development of the production technology of multilayer interference coatings in the optical range is connected with the use of new unconventional materials. The introduction of unconventional film-forming materials allows expanding the operational spectral band and improving the basic frequency characteristics. The optical properties of the films strongly depend on the method of obtaining the layers, on the process conditions, substrate temperature, deposition rate, residual pressure in the vacuum chamber. Thus, they depend on means of obtaining them and differ from the data available for single crystals or bulk samples. Improving the production quality of optical coatings involves the compilation of a database with the parameters of new materials for films. This article proposes new thin films. Their spectral characteristics were studied. The values of optical constants were obtained: refractive index and absorption coefficient, which determine the optical properties of films and interference coatings.
Adaptive Course Control-Based Trajectory Linearization Control for Uncertain Unmanned Surface Vehicle Under Rudder Saturation

In the presence of the uncertain system dynamics, unknown time-varying disturbances and rudder saturation, this paper develops a novel robust adaptive course control scheme for unmanned surface vehicle (USV). Considering the characteristics of the rudder servo system, a double loop course controller of the practical and concise is proposed by the enhanced trajectory linearization control (TLC) technology. The key features of the developed controller are that, first, the neural networks are employed to online approximate unmodeled dynamics, and adaptive techniques are adopted to deal with completely unknown external disturbances; second, auxiliary systems that are governed by smooth switching functions, are developed in an unprecedented manner to compensate for the saturation constraints on actuators. The main innovation can be summarized as that the TLC technology is applied to the USV motion control field as a new control algorithm, and the enhanced technology based on traditional TLC not only reduces the number of adjustment parameters but also has simple structure and high robustness. Furthermore, a low frequency learning method improves the applicability of the algorithm. The stability analysis is established using the Lyapunov theory. Simulation results and comparison verify the effectiveness of the proposed strategy.
MEAMCP: A Membrane Evolutionary Algorithm for Solving Maximum Clique Problem

The maximum clique problem (MCP) is a classical NP-hard problem in combinatorial optimization, which has important applications in many fields. In this paper, a heuristic algorithm MEAMCP based on Membrane Evolutionary Algorithm (MEA) is proposed to solve MCP. First, we introduce the general structure of MEA, which includes four kinds of membrane operators: selection, division, fusion and cytolysis. MEA evolves the feasible solution population through the membrane operator. Second, MEAMCP is proposed and we discuss how to initialize the population and implement the four kinds of membrane operators. Finally, MEAMCP is tested on DIMACS benchmark datasets and compared with other MCP algorithms. The experiment results demonstrate that MEAMCP has better stability.
Sparse Self-Attention LSTM for Sentiment Lexicon Construction

Sentiment lexicon is a very important resource for opinion mining. Recently, many state-of-the-art works employ deep learning techniques to construct sentiment lexicons. In general, they firstly learn sentiment-aware word embeddings, and then use it as word features to construct sentiment lexicons. However, these methods do not consider the importance of each word to the distinguish of documents’ sentiment polarities. As we know, most words among a document do not contribute to understand documents’ semantic or sentiment. For example, in the tweet It's a good day, but i can't feel it. I'm really unhappy. The words ‘unhappy’, ‘feel’ and ‘can't’ are much more important than the words ‘good’, ‘day’ in predicting the sentiment polarity of this twitter. Meanwhile, many words, such as ‘the’, ‘in’, ‘it’ and ‘I'm’ are uninformative. In this paper, we propose a novel sparse self-attention LSTM (SSALSTM) to efficiently capture the above intuitive facts, and then construct a large scale sentiment lexicons in twitter. In SSALSTM, we use a novel self-attention mechanism to capture the importance of each words to the distinguish of documents’ sentiment polarities. In addition, a $L_1$ regularize is applied in the attentions which can ensure the sparsity characters that most words in a document are semantic and sentiment indistinguishable. Once we learn an efficient sentiment-aware word embedding, we train a classifier which uses sentiment-aware word embedding as features to predict the sentiment polarities of words. Extensive experiments on four publicly available datasets, SemEval 2013–2016, indicate that the sentiment lexicon generated by our proposed model achieves state-of-the-art performance on both supervised and unsupervised sentiment classification tasks.
Multi-node activity recognition based on wireless sensor network in classroom

1This work constructs and discusses a multi-node wireless activity recognition system for teaching environments. The system can collect behavior data simultaneously from multiple users overall wearing the wireless sensor. Behavior data is collected and calculated from users to extract features. The features are then used to do the effective classifier training and recognize different activities. As introduced in classroom teaching, this system can provide high recognition accuracy of the student’s activity and give teachers helpful information to better adjust their course. It is 94.092% in recognition accuracy as being used to recognize five daily activities of learners in classroom education.
Secure and Reliable Decentralized Truth Discovery Using Blockchain

Truth discovery with crowdsourcing has become increasingly popular in recent years by leveraging the wisdom of crowd to solve complex tasks. So far, many existing crowd-sourcing applications utilize a central server for deployment, which collects and processes data from a crowd of workers. However, this kind of centralized model also introduces security concerns, including data privacy, integrity of processed data, and single point of failure. In this paper, we propose a secure decentralized framework for truth discovery with a privacy-preserving and reliable realization. Instead of relying on the central servers (e.g., public cloud servers)to behave correctly, our framework delegates the data aggregation and processing tasks to distributed entities, whose behaviors are enforced and verified by utilizing the emerging blockchain-based smart contract technology. Meanwhile, as the blockchain lacks support for on-chain data confidentiality, we utilize the privacy-preserving solution and integrate it with blockchain for privacy protection. Moreover, given the decentralized nature of our framework, it also overcomes the limitation of single point of failure. We implement a prototype of our framework using Ethereum blockchain and demonstrate its practical performance.
Active set updates in event-triggered networked MPC

We show how to exploit the piecewise affine structure of the optimal control law in networked linear-quadratic MPC. The complete explicit solution is not required in this approach, but the current piece, i.e., the feedback law and its polytope of validity, is computed on demand instead. Assuming such a piece has been determined for the current state, a lean local computational node suffices to check whether future states are still in the current polytope and to evaluate the optimal affine feedback law if that is the case. Whenever the system leaves the current polytope, the local node requests a central, powerful node to determine a new control law and polytope by solving a MPC problem, and to send the resulting law and polytope over the network. In this contribution we extend the approach by not sending the information for a single control law, but for multiple control laws for the predicted system behavior. We show that the number of requests and the amount of transmitted data can be reduced by using active set updates on the local node.
Propagation Modeling for Underwater Magnetic MISO Wireless Power Transfer

In the underwater scenario, the multiple inputs and single output (MISO) technology can greatly enhance the wireless power transfer (WPT) range. In this paper, we investigate the wireless power propagation model for MISO based underwater WPT (UWPT). Experiments are conducted to record the transmission characteristics of the system, using the voltage and phase to model the coupling state of the system. We measure the voltage and phase at different positions in a plane 55mm away from the transmitters, and the experimental results demonstrate that the system has a good transmission performance in most areas of the measurement range. Compared to the experiment with the same setups in the air, the UWPT system can transmit more power and longer distance.
Comparative Study on Energy Efficiency of WSNs and WMSNs for Surveillance Applications

The infrastructure required to deliver various “Internet of Things” (IoT) services is expected to be widely available in the very near future for application areas such as Smart Cities, Smart Homes, Intelligent Transportation and Smart Monitoring in the coming decades. In fact, it is expected that the number of devices connected to the Internet will exceed 50 billion by 2020. It is possible to use these infrastructures for environmental monitoring systems, especially for the early detection and prevention of disasters such as forest fires. Wireless sensors are an essential part of the IoT infrastructure and environmental monitoring/surveillance systems. Wireless sensor networks based on scalar sensors and wireless multimedia sensor networks are widely used for environmental monitoring. Multimedia surveillance systems have better accuracy but a shorter lifetime with multimedia surveillance systems. Therefore, it is necessary to study in detail their energy efficiency to better understand the introduction of more efficient algorithms and architectures. In this study, the lifetimes of the Wireless Sensor Networks(WSNs) and Wireless Multimedia Sensor Networks(WMSNs) are considered in a comparative way. The results are presented for a forest fire detection case study using simulations as well as an example of a test bench to confirm the accuracy of the simulation tool used.
A Predictive DTC-PWM using 12 Vectors for Permanent Magnet Synchronous Motor

In this paper, we propose a Predictive Direct Torque Control - Pulse Width Modulation (PDTC-PWM) control method of PMSM with 12 sectors division and 12 voltage vectors. In the proposed method, a mathematical model was made to calculate the possible voltage vectors from torque and flux errors. These vectors, however, may not satisfy both motor speed and output torque performance due to the counter-electromotive force and decoupling effects. Therefore, the back EMF and decoupling components are also considered to select the appropriate voltage vector to reduce the torque ripple of PMSM. In the 12-sector division method, torque ripple is first estimated and the value is then used to calculate the switching voltage vector and PWM duty ratio according to the switching state of that voltage vector. The simulation result shows that the proposed PDTC-PWM for PMSM using 12 voltage vectors gives excellent control performance with lower voltage and torque ripple through the optimization of the vector selection process.
Investigation on the Compatibility of Transformer Construction Materials with Natural Ester

With the development of high temperature insulation system, natural ester transformers grow rapidly at present. The international standard for the compatibility of transformer construction materials with natural ester are necessary by industry. ANBT NBR 16341, standards in Brazil, identified compatibility of natural ester transformers. However, thermal ageing temperature, 100°C, is too low to identified high temperature insulation system, such as aramid enhanced cellulose with natural ester. In this paper, a series of construction material used in natural ester transformers have been tested, including nitrile rubber, acrylic ester, inner surface varnish, varnish of silicon steel sheet and varnished wire. The natural ester adopted in this paper was FR3. The properties of FR3, rubber and vanished wire were tested before and after 164 hours, 336 hours thermal aging under 130°C. The experimental results indicate that the dielectric strength, dielectric dissipation factor, viscosity and acid value of natural ester, the mass and hardness of rubber are the necessary parameters for evaluating the compatibility of construction materials with natural ester. Meanwhile it is observed that the parameters benchmark of FR3 in ANBT NBR 16341 needed to be justified for overloading transformer. According to the initial test data in this paper, there is big concern for compatibility of the Nitrile rubber and varnished wire with FR3, while acrylic ester, inner surface varnish of transformer and varnish of silicon steel sheet are well compatible with FR3 natural ester. The results in this paper can provide some reference to the revision of the standard for the compatibility of transformer construction materials with natural ester.
VUSphere: Visual Analysis of Video Utilization in Online Distance Education

Online Distance Education (ODE) provides massive course videos of various specialties for students across the country to learn professional knowledge anytime and anywhere. Analyzing the utilization of these videos from user log data can help academics better understand the learning process of students, evaluate the quality of service provided by regional learning centers, and improve the quality of program curriculum in the future. However, due to the lack of comparable indicators, it is a great challenge to discover the utilization patterns of massive videos and analyze the learning process of large-scale student population from learning log data. In this paper, we introduce a visual analytics system, called VUSphere, to explore the video utilization from multiple perspectives with two proposed indicators. This system offers three coordinated views: a spherical layout overview to depict the overall utilization distribution of videos, courses, and students; a detailed statistics view with four panels to present video utilization statistics of each element from multiple perspectives; and a comparison view to examine the differences in individual elements. Based on the real dataset from our ODE school, several patterns related to video utilization and enrollment are found in the case study with our domain experts.
In-Hand Telemanipulation Using a Robotic Hand and Biology-Inspired Haptic Sensing

A new approach to the in-hand manipulation problem, using fuzzy controlled teleoperation and a recently proposed multimodal tactile sensor are presented in this article. Real-time grasping experiments were performed by a fuzzy controlled gripper, with a compliant tactile sensor mounted on the gripper. As a new approach for in-hand manipulation and robot dexterity, a teleoperated thumb performed object rotation while the gripper maintained stable grasping. The data from the experiments were consistent and, thus, provided a substantial tool for in-hand control algorithms.