Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-term Load Forecasting for Distribution Network Using Decomposition with Ensemble prediction

short-term load forecasting (STLF) is helpful to grasp the state of the distribution network system. In order to improve the prediction accuracy and robustness, the paper proposes a hybrid model, including Seasonal-Trend decomposition procedure based on Loess (STL), Long Short-Term Memory neural networks (LSTMs) and XGBoost. First, we use the STL method to decompose the load series to mitigate the impact of data distribution on the prediction model. Then, we choose the LSTM neural network as the learner and design an ensemble prediction model to improve the prediction accuracy and robustness. And XGBoost as the last step of ensemble prediction is adopted to combine with all learners to obtain the ensemble prediction results. The proposed STL-LSTMs-XGBoost is applied on the load data collected from 10kV line in Chongqing distribution network. The experimental results can illustrate the feasibility of the model.
Distributed Consensus of Multi-Agent Via Aperiodic Intermittent Sampled-Data Control*

This paper is concerned with the consensus problem of first-order multi-agent systems with nonlinear dynamics. To avoid the controllers are difficult to keep working continuously and the traditional sampled-data control can only reduce the update frequency of the controller, an aperiodic intermittent sampled-data control strategy is proposed. Based on the theory of algebra graph and matrix analysis, the consensus conditions of network structure, sampling width and communication width are given. The effectiveness of the consensus theory is verified by numerical simulation, and the influence of sampling width and communication width on the consensus is analyzed.
Controlling Smart-City Traffic using Machine Learning

Traffic situation in smart cities is getting worse day by day, which needs optimized control of traffic signals. This paper proposes a complete solution for real-time traffic signal control to reduce traffic congestion. For providing efficient solutions, we develop two machine-learning approaches, namely Edge based Traffic Light Control (ETLC) and Global Traffic Light Control (GTLC). The former approach is used to control traffic congestion for a smaller congested area and latter one provides the solution for the whole city. Both the approaches utilize real-time traffic data, generated from a vehicular traffic simulator, to solve the congestion problem in real-time. The ETLC approach identifies the most congested area through K-Means clustering and applies fuzzy logic for congestion removal. The GTLC approach identifies multiple congested areas using an occupancy threshold and reduces congestion. Our model is flexible to run each approach individually or integrate both the approaches to run sequentially. Comparison of the two approaches shows that the ETLC approach works better than GTLC approach for small areas. However, GTLC gives good results in peak congestions spanning larger areas.
Collaborative space solution and simulation of 7DOF dual-arm rehabilitation robot

Clinical research has proved that bilateral rehabilitation training based on robot-assisted system can effectively improve the rehabilitation effect of patients. The collaborative space of dual-arm robot must be analyzed first when developing rehabilitation training tasks. Aiming at the problem of the collaborative space of the 7 degrees of freedom (DOF) rehabilitation robot, a method combining the Monte Carlo method and the traversal search comparison method is proposed in this paper. Firstly, the kinematics model is established by using the standard Denavit-Hartenberg (DH) method according to the configuration of the manipulator, and then the positive kinematics equation of the manipulator is obtained. Secondly, the Monte Carlo method is used to obtain the workspace of each arm, and the traversal search comparison method is used to obtain the collaborative space of the dual-arm rehabilitation robot. Finally, simulations are performed in the MATLAB toolbox to verify the correctness of the method.
Enabling Sub-5nm CMOS Technology Scaling Thinner and Taller!

Scaling beyond 5nm will bring us into the post FinFET era where new device architectures optimized for CMOS logic scaling will be required. In this paper, the evolution to vertically stacked Nanosheets, Forksheet, and finally CFET are reviewed in conjunction with buried power rails and wrap around contact. Performance and area impact of these architectures are evaluated both at standard cell as well as block level to provide realistic PPA estimate for true technology scaling.
Modeling of the CPS1 for the Frequency Constrained Unit Commitment

Frequency is an important index to reflect stability of the power system. NERC’s Control Performance Standard 1 (CPSI) is to assess control area’s ability in maintaining frequency quality. This paper proposes a stepwise regression method to identify important frequency-control correlation factors for developing a CPSI model. The CPSI model is constructed by the Long Short-Term Memory (LSTM) neural network. The well trained CPSI model is then integrated into a unit commitment (UC) program to realize a CPSI compliant UC (UC-CPSI). The performance of the proposed UC-CPSI is validated by simulation case and is compared with the case without the frequency constrained UC.
Comparative Study and Performance Evaluation of JAG_TDB_CC Concurrency Control Algorithm for Temporal Database

The overall performance of database system can be hinder by uncontrolled concurrency. In multi-user distributed database environment conflicts are normal. Concurrency is undesirable for large time-dependent and time-critical database applications; it must be monitored and managed effectively to ensure consistency of the database system. Uncontrolled concurrency can leave the database in an inconsistent state and can become obstacle in the overall performance of database system. Traditionally time stamps and lock-based approaches are used to address the problem of concurrency. The study showcases the new breed of algorithm known as JAG_TDB_CC concurrency control algorithm, which is a unique blend of a timestamp and lock-based concurrency control mechanisms. This paper shows a comparative study and performance evaluation of the JAG_TDB_CC concurrency control algorithm in comparison to traditional pessimistic and optimistic mechanisms for managing a concurrency for temporary database system using Oracle 12c.
Design of a high outband rejection cross-coupled SIW filter for millimeter wave communications

Substrate integrated waveguide (SIW) technology provides an attractive solution to the integration of planar and nonplanar circuits by using a planar circuit fabrication process. In this paper, a 6-order cross-coupled SIW bandpass filter is designed by coupling matrix synthesis, electromagnetic simulation, coupling matrix extraction and optimization of filter size. The relative bandwith of the filter is 10.5% and the insertion loss is less than 2.65dB in the passband of 24.75GHz-27.5GHz. The transmission zero is introduced by cross-coupling, so that the filter obtains a steep transition band and good sideband suppression characteristics, while having low insertion loss and in-band fluctuation. The filter circuit has a small area and a simple structure, and can be widely applied to the microwave millimeter wave communication system.
Size-Reduced and Broadband Ring Hybrid Coupler with Arbitrary Power Division using Phase Inverters

Novel compact rat-race hybrid-ring coupler with phase inverters of slot-line consisting of microstrip line hybrid ring and slot-line phase inverters are proposed. The features and design criteria of broad-band reverse-phase hybrid ring couplers are presented. Effective bandwidth of a new reverse-phase hybrid ring coupler can be increased by 46% with a return loss of 12dB. In addition, we present a class of microstrip phase inverters and discuss their technical aspects. Experimental results show that the bandwidth of the proposed phase inverter is greater than 100% with insertion loss below 1 dB and phase shift error of less than ± 7°. Measurements confirm that the new microstrip-line hybrid ring coupler provides attractive features. Its isolation is better than 20 dB over a 45% bandwidth attributed to the phase inverter providing almost a 100% bandwidth.
Mechanical Oscillators Based on Superconducting Membranes

Mechanical oscillators can be implemented to store and/or transfer information. In order to couple a mechanical oscillator to a superconducting qubit, we fabricate a superconducting capacitor using the diluted photoresist or electron beam photoresist as a sacrificial layer. The upper plate of the capacitor, a suspended membrane, acts as a mechanical oscillator. We obtain its mechanical resonant frequency and response to the input microwave. Such mechanical oscillator can be used as the capacitor of a superconducting qubit to form a coupled system. Another way to transfer information between a mechanical oscillator and a superconducting qubit is to take advantage of a superconducting microwave resonator such as a coplanar waveguide resonator. In order to control the resonant frequency of the resonators, we introduce a DC voltage bias between the upper and lower plates of the capacitor. We demonstrate the dependence of the resonant frequency on the applied DC voltage.
Research on a Dual-Polarized Antenna Based on an Annular Slot on SICL Resonator and Printed Monopole

This paper proposes an asymmetric structure dual-polarized antenna based on a combination of a circular arc gap and a printed monopole of a dielectric integrated coaxial (SICL) resonant cavity. The dielectric integrated coaxial resonator cavity circular annular gap and printed monopole are both implemented by printed circuit technology, which are isolated from each other in the vertical direction to form two dual-polarized ports. The electromagnetic simulation and optimization of the designed dual-polarized antenna show that the voltage standing wave ratio of the two ports is less than 2 and the port isolation is greater than 20 dB within the working bandwidth. On the two polarization ports, the designed radiation gains of the dual-polarized antenna based on the SICL cavity ring gap and the printed monopole are about 6.3dB and 7.5dB, respectively, and the main radiation direction axis ratio is greater than 40dB. The dual-polarized antenna has a simple structure and low cost, and is suitable for applications such as dual-polarized radar and communication systems.
AudioNet: An Audio Frequency Based Wireless Communication Scheme for Wireless Personal Area Networks

This paper proposes a wireless communication scheme, named AudioNet, which is based on the audio frequency (AF) domain modulation/demodulation techniques for wireless personal area networks (WPAN). The proposed AudioNet includes a transmitter and a receiver. The frequency modulation scheme of the transmitter adopts frequency-shift keying (FSK). The Goertzel's algorithm is used to implement the FSK demodulation in the receiver. As a result, the experimental results showed that the proposed AudioNet can be transmitted the text string messages over audio at 32bps.
Cases and Clusters in Reuse Policies for Decision-Making in Card Games

This work investigates the combination of cases and clusters in the reuse of game actions (e.g., cards played, bets made) recorded in the cases retrieved for a given query in Case-based Reasoning (CBR) card-playing agents. With the support of the K-MEANS clustering algorithm, clustering results detailing problem states/situations and game outcomes relationships recorded in cases from the case base guide the execution of augmented reuse policies. These policies consider the game actions recorded in the retrieved cases in the selection of the clusters to be used. Then, the cases that belong to the selected clusters are used in the determination of which game action is reused as a solution to the current game problem situation. With this two-step reuse process, the proposed policies rely on the majority with clusters, the probability with clusters, the number of points won with clusters and the chance of victory with clusters. To evaluate these proposals, card-playing agents implemented with different reuse policies competed against each other in duplicated game matches where all of them played using the same set of cards.
Affective Multisensorial Books

Affective computing devices have been used in e-learning, game, and movie areas to acquire individuals' affective states. Thus, states like fun, boredom, frustration, and excitement can be detected. Based on these states, many tasks can be executed. For example, if an individual practicing an exercise in an e-learning system is bored, some action can be executed by the system; for example, it could present more challenging tasks. Inspired by the above scenario, the present work proposes the creation of a model based on e-books reading, multisensorial media (MulSeMedia) area, and affective computing area. This model is referred to as Affective Multisensorial Books, and it has two main goals: (i) acquire affective states from users; (ii) produce multisensorial media effects. The main motivation is related to the fact that MulSeMedia can improve Quality of Experience of individuals and affective computing can be used to capture individuals' affective states during reading (e.g., boredom). However, it is important to evaluate if it is possible to detect changes in affective states of individuals in the reading task. In this scenario, this work evaluates if there are statistical differences in the same individual reading two genres of texts. The first one is a drinking fountain guide page, and the second is a poem. The Wilcoxon signed-rank test was used to assess the difference in mean of measurements in Galvanic Skin Response of individuals when reading each of the texts. The analysis indicates a statistically significant difference between the reading of the two texts.
Automatic Identification of Alzheimer's Disease and Epilepsy Based on MRI

Alzheimer's disease (AD) and epilepsy are both common chronic diseases in neurology. A certain proportion of AD patients have been found to have epilepsy complication. Neuroimaging such as structural magnetic resonance imaging (MRI) has been proved to be useful in assessing the pathology of AD and epilepsy. Computer-aided diagnosis (CAD) on automatical MRI identification can be applied to assist physicians in diagnosing both diseases. In this paper, it is investigated that the performance of identification on AD, AD complicated with Epilepsy, and Epilepsy based on different MRI brain tissues and feature extraction methods. 17 AD patients, 17 AD patients complicated with epilepsy, 15 epilepsy patients, and 10 healthy control subjects from West China Hospital, Sichuan University were studied. Several preprocessing steps were performed for each MRI to obtain gray matter (GM) and white matter (WM) tissue voxels. Principal component analysis (PCA) and partial least squares (PLS) were adopted to extract features. Three classes of patients and healthy controls were distinguished separately by support vector machine (SVM). The performance is evaluated by k-fold cross-validation strategy. The approach on combination of GM and WM tissues with PCA archieved the optimal performance, with the accuracy of 87.41%, 83.7%, and 75.2% for AD, AD complicated with epilepsy, and epilepsy identification respectively. Our proposed approach appears to have significant potential as a clinical decision support tool in assisting physicians in their clinical routine.
Compact Side-Edge Frame Printed Fourteen-Element Antenna Array for Triple-Band MIMO Operations in the 5G Smartphone

In this article, a hybrid 14-port antenna array operating in the 3.5/4.9/5.8-GHz (3300-3800/4800-5000/5150-5875 MHz) triple-band for multi-input multi-output (MIMO) operation in the 5G (fifth-generation) smartphone is presented. The proposed hybrid 14-port antenna array consists of two sub- arrays can be used for the $8\times 8$ MIMO in 3.5-GHz band and the $6\times 6$ MIMO in 4.9/5.8-GHz band, respectively. Simulated results show that relative impedance bandwidth of each element and array are all 16%/9%/27% or more for reflection coefficient less than −6 dB (3:1 VSWR) at the center frequency of 3.5/4.9/5.8 GHz, respectively. Besides, desired gain, 3D radiation patterns, total efficiency (more than 40%) are simulated and presented. In addition, good ECC (Envelope Correlation Coefficient) of less than 0.1 for any two antenna elements and acceptable isolation (better than 10.2 dB) are also obtained.
Cooperation Control Between Wireless and Base Stations in Wireless Access Network Consisting of Wireless Networks with Different Coverages

Mobile terminal users prefer WLAN (Wireless LAN) to cellular network because of no connection fee. WLANs are available in some places where many people gather in urban areas, whereas public access network like WLAN should be deployed at a low cost for rural leisure venues and momentary events. In this paper, we propose a wireless access network with larger coverage than WLAN by the cooperation between WLAN and another wireless network with larger coverage. This achieves the wider deployment of such wireless access networks with a smaller number (cost) of base stations. Connection control that decides which wireless network should be used for each wireless station is also proposed to increase the effective network capacity of the wireless access network. Performance evaluations show that the proposal achieves larger effective network capacity compared with greedy connection that all the wireless stations inside the WLAN coverage use the WLAN and the other ones do the other network with larger coverage, respectively.
Does Social Media Affects Users’ Well-Being

Social media platforms are now considered as the most used tools that people used daily. The relationship between social media and well-being is driven by many implicit and explicit factors that are difficult to configure. There is a substantial agreement that using social media platforms have positive effects and dark sides on well-being along with many contradictions. This study is an attempt to understand social media effects on users’ well-being by a novel perception that avoids the linear perspectives of the digital world. This research proposes a digital chaos model to better understanding the full picture of the new chaotic life. This model presents the interplay of dynamic actions and factors between social media platforms and users’ well-being, which are complex, nonlinear and interactive factors.
Analysis of containment control for multi-agent systems based on broadcast gossip algorithm

This paper investigates the containment control problem for multi-agent systems based on the broadcast gossip algorithm, in which only one agent wakes up in the light of the asynchronous time model at each time and sends its information, and one part of the remaining agents get the message to update their states while the other part keep the states unchanged. We equivalently transform the algorithm into a mathematical model with the matrix-vector form, then conduct a detailed theoretical analysis for the mathematical model by utilizing tools including graph theory and stochastic matrix. Then, we establish a necessary and sufficient algebraic graph condition to ensure that every follower gradually enters the convex hull spanned by the leaders. Finally, we give a numerical example to argument the validity of theoretical result.
A Reconfigurable Graphene Reflectarray for Generation of OAM in THz Band

A reconfigurable graphene reflectarray for generation of orbital angular momentum(OAM) vortex wave in THz band is presented. It has a stacked structure consisting of a graphene-based element, a graphene-based frequency selective surface (FSS). By adjusting the electric field, a dynamic change in the complex conductivity of graphene is achieved, which in turn changes the phase and the resonance point of the reflected or transmitted wave at the element. Hence, by suitably choosing the chemical potentials of the graphene and the parameters for each graphene element, the designed reflectarray can produce an OAM vortex wave in 0.8 THz and 1.2 THz, respectively.
The Application of Tobacco Product Quality Prediction Using Ensemble Learning Method

With the rapid development of modern information technology, the tobacco industry has gradually achieved informatization and digitization transformation. A large amount of data is recorded in the production process and those data contains the information and knowledge which can determine the quality of the product. It’s known that the traditional quality test method is not timely and with a large contingency, if the production data can be properly mined and analyzed, the product quality can be predicted in advance. Therefore, based on the mining and analysis of the tobacco production data recorded by the batch management system, this paper proposes a prediction model using ensembled learning algorithm to predict the product quality. The results compare random forest and XGboost method, which shows that the XGboost method has a better performance for quality prediction. This prediction model would be beneficial to guide the future production and improve tobacco product quality.
A Wide-Band Cylindrical Dielectric Resonator Antenna With Artificial Magnetic Conductor Structures

In this paper, a wide-band cylindrical dielectric resonator antenna (CDRA) with artificial magnetic conductor structures (AMCs) is designed. To reduce the influence of AMCs on the radiation field of the CDRA, an AMC cell is also designed. When two orthogonal polarized electromagnetic waves are perpendicularly incident on the AMCs, the proposed AMCs surface can be equivalent to perfect magnetic conductor and perfect electrical conductor, respectively. The matching frequency band for the CDRA with AMC is from 5.04 GHz to 5.81 GHz with an impedance bandwidth of 14.2%. The maximum realized gain of proposed antenna in working band is 6.08 dB at 5.1GHz. The co-to-cross polarization level is 12 dB in the H-plane and 30 dB in the E-plane across the working band.
Tensor Completion using Low-Rank Tensor Train Decomposition by Riemannian optimization

Tensor completion, which recovers missing entries of multiway data, plays an important role in many applications such as image processing, computer vision, machine learning, et al. There into, most of the current methods exploit this technology for image completion applications based on the tensor train (TT) decomposition, which is able to capture hidden information from tensors benefit by its well-balanced multiple matricization scheme. In order to seek a highly accurate solution comparing with traditional linear TT estimation, in this paper, we use Riemannian optimization techniques on TT manifolds to estimate images to be completed. This approach transforms the constrained linear optimization problem in Euclidean space into an unconstrained nonlinear optimization problem in Riemannian manifolds. Experiment results for color images completion show the clear advantage of our method over existed methods.