Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning based Command Pointing direction estimation using a single RGB Camera

Gesture based communication with humanoid robots, especially using hand gestures has universal appeal and could make humanoid robots share home space in a social environment if the technology can be developed in a matured fashion. Till date conventional vision based gesture recognition has had poor success rate since hand engineered features failed to communicate the gesture semantics unambiguously, especially when the gesture is dynamic in nature. This research proposes a deep convolutional neural network based technique that is able to estimate the command direction represented by a finger pointing gesture, with a considerably high accuracy. Moreover, the proposed architecture is able to estimate the direction of finger pointing using only a single two-dimensional RGB image of the hand gesture without using any depth information or stereo-vision techniques making the system computationally and physically less expensive which is particularly suitable for the real time applications such as communicating with the humanoid robots in a home environment.
Adaptive Cross-Cloud Service Composition with the Bidirectional QoS Updates

With the increasing number of cloud services from different providers, service composition across clouds in dynamic environments presents significant challenges. The fact that each of the cloud services has different values of QoS attributes further increases the complexity. Particularly, current approaches cannot efficiently deal with situations when failure between a pair of composed services occurs or the QoS values of the cloud services change in distributed service executions. In this paper, an adaptive cloud service composition in distributed service executions is proposed to improve the traditional Q-learning model and algorithm. It uses a method called the bidirectional QoS updates on composite services which simultaneously considers the QoS update probability and the time cost of selecting the optimal cloud service pairs. The experimental results show that this approach has higher average cumulative rewards and lower average service composition time than the existing approaches.
Text Classification Based on TextCNN for Power Grid User Fault Repairing Information

Aiming at the problem that the fault information submitted by power grid users is difficult to be auto-matically analyzed and dealt with, We proposed a text classification model based on TextCNN (Text Convolutional Neural Network, TCNN) for fault repairing information of Power grid users. First of all, Using CBOW (Continuous Bag-of-Words) to learn the distributed representation of text. Second, The feature of pretrained word vector is learned through the text convolutional neural network model, and k-max pooling is used to further extract the high-level features. Finally, the classification model is obtained by softmax classifier. We use the model to classify and analysis the fault repairing information. Experimental results validate the effectiveness of our approach when compared to the state-of-the-art methods.
Phononic Frequency Combs in Stand-Alone Piezoelectric Resonators

This work reports on the generation and frequency tuning mechanisms of resonant-based phononic frequency combs. The reported mechanical frequency combs are realized in an integrated standalone piezoelectric platform and are excited via non-degenerate parametric pumping. Two flexural resonance modes of a thin Aluminum Nitride (AlN)-on-silicon circular membrane are targeted due to their low onset of nonlinearity and excited simultaneously. When the resonator is pumped with a single tone at a frequency close to the sum of the two mechanical modes, phononic frequency combs are generated close to each mechanical mode, under certain and repeatable pump frequency and power conditions. The phononic combs consist of a set of equally-distanced phase-coherent spectral lines; we demonstrate such combs centered around 6 MHz, with a tunable spacing of around 55 kHz, corresponding to the $u_{11}$ resonance mode of the circular membrane. The center frequency and frequency spacing of the comb can be tuned by tuning the pump frequency and amplitude. We take advantage of the mode coupling between two high-$Q$ resonance modes in the same acoustic cavity, and demonstrate the smallest piezoelectric frequency comb, with a 30 $\mu \mathrm{m}$ diameter circular footprint, which requires a very low threshold power of only −4 dBm to excite a fine-tooth comb.
Highly Reconfigurable Dual-Band Coupler With Independently Tunable Operating Frequencies

To support different standards simultaneously within a wireless communication system, research on dual-/multi-band components has been conducted extensively. However, the operating frequencies of existing works are usually fixed resulting in a low flexibility. To solve this problem, a highly reconfigurable coupler whose two operating frequencies can be controlled independently is proposed for the first time in this paper. Based on the analysis of a basic configuration, the conditions for realizing the desired independent frequency tuning can be obtained. To realize this unique property, varactors loaded coupled line sections are introduced on a conventional branch line coupler. Owing to the symmetrical structure of the proposed coupler, explicit theoretical analysis can be conducted. For demonstration, two reconfigurable couplers are designed, fabricated, and measured. The first coupler can provide frequency tunability from 3.4 to 4.2 GHz at the upper band with the lower band fixed at 2.4 GHz. The other one can not only provide a tunable frequency from 1.3 to 1.6 GHz at the lower band with the higher band fixed at 3.4 GHz, but also give a tunable higher band from 2.9 to 3.4 GHz with the lower band fixed at 1.55 GHz. The measured results agree well with the simulated results, validating the proposed design methodologies.
A Flexible Discontinuous Modulation Scheme With Hybrid Capacitor Voltage Balancing Strategy for Three-Level NPC Traction Inverter

Multilevel inverters are now-a-days being applied in electric vehicles (EV). Considering the dynamic operating conditions of an EV propelled by an induction motor, this paper proposes a flexible discontinuous modulation strategy for three-level neutral-point-clamped (NPC) inverter that can shift modulation pattern seamlessly from sinusoidal pulsewidth modulation (SPWM) to discontinuous PWM (DPWM). The modulation scheme is generalized at each degree of discontinuity to ensure minimum switching losses for variable load power factors. Additionally, a hybrid voltage balancing strategy, which comprises two sets of compensating offset signals with complementary features, has been introduced to mitigate voltage deviation problem at neutral point of the inverter. The unique feature of the proposed hybrid balancing approach is that it generates uniform compensating neutral current regardless of the level of discontinuity. This results in identical and predictable voltage balancing dynamics for the entire modulation transition covering SPWM and DPWM. It has been shown that the proposed hybrid balancing strategy does not lose its unbalance compensation strength even during transition from one modulation pattern to another. The effectiveness of the proposed scheme for wide variations in operating conditions is studied through extensive simulation, and validated in experimentation using a prototype NPC inverter with induction motor loads.
Improving Quality of 3 Phase Supply Generation Using MOSFET and Capacitor Combination for Driving Induction Motors

Four switches, 3-phase inverters (FSTP) plays an important role in transformation. It has been broadly utilized for transformation of DC input to 3-phase AC output. For driving the motors and other high power equipment's, FSTP is more suitable than other conventional methods implemented. The performance of FSTP can be enhanced with certain modification in conventional FSTP. This paper deals with the procedure to optimize the QoS of 3-phase generation using FSTP in combination with capacitor circuitry. In the combined circuit developed, the first 2 phases are generated using conventional FSTP and last phase is generated using the capacitor circuit. The main aim to use capacitor circuitry is to reduce the harmonic content and gets a smoother 3-phase supply at the output. The developed circuit is used to drive 150W, 3-phase induction motor and result obtained shows, 10% improvement in the power efficiency of the motor compared to traditional FSTP circuit.
An Optimal Time Reversal Waveform Based on Sequential Convex Programming for Wireless Power Transmission

Time reversal (TR) is one of the novel techniques on wireless power transmission (WPT), which can enhance transmission efficiency. In this paper, we use TR for WPT and propose a sequential convex programming for TR. We take the non-linear rectenna circuit model into consideration and carry out numerical simulations in a rich multipath environment to compare three waveforms: multi-sine, TR, TR-SCP. The results show that our approach can efficiently adapt to the complex multipath channel and the system model by achieving more output power at the receiver.
Dynamic Assessment of Contact Pressure Changes in the Hip Joint Cartilage During Daily Activities

The contact stresses in the hip joint cartilage are relevant with clinical hip osteoarthritis. Therefore, the objective of this paper is to discover the contact pressure changes in acetabular cartilage during series of dynamic postures such as slow walking, normal walking, fast walking, descending stairs and ascending stairs. Subject-specific anatomical models are built from CT images and kinematical models are constructed using a motion capture system. A two-step adjusted-iterative closest point method is proposed to register the anatomical model with the motion capture recorded kinematical model. After the registration, acetabular cartilage contact pressure is analyzed by a finite element method. According to simulation results, the distribution of walking and stairs movements for contact pressure are mostly uniform during cycle of movement. The peak of contact pressure appears at the heel-strike. The contact area spreads from anterior to superior-posterior and ending at anterior for all the activities. These results provide a basic understanding for the hip contact pressure in cartilage during daily activities and they could be used to analyze the pathologic hips in the clinical research.
Modular Multilevel Converter Based Variable Speed Drive With Reduced Capacitor Ripple Voltage

In recent years, modular multilevel converter (MMC) is considered for medium-voltage variable speed drives (VSD) due to its modularity and higher reliability. However, the major drawback of the MMC-based VSD is the higher capacitor ripple voltage at lower operating speeds. In literature, this ripple voltage is reduced by injecting a high-frequency circulating current into each arm. This additional circulating current increases the overall current rating of the devices, inductors, and capacitors. Alternatively, the capacitor ripple voltage can be reduced at the lower output frequency by reducing the dc-bus voltage. This paper proposes a new configuration using a multipulse diode-bridge rectifier to reduce the dc-bus voltage when the drive is operated at lower speeds. Therefore, the capacitor ripple voltage decreases without injecting any circulating current. In addition, a new technique is proposed to maintain the peak-to-peak value of the submodule capacitor ripple voltage constant at near-zero speed. The proposed converter with 24-pulse rectifier configuration is simulated in MATLAB/Simulink, and the experimental validation is carried out on a prototype with 12-pulse rectifier.
A Novel Wideband Rectifier Design with Two-Stage Matching Network for Ambient Wireless Energy Harvesting

A novel wideband rectifier design is proposed for ambient wireless energy harvesting over the frequency band from 1.5 to 2.5 GHz. The two-stage impedance matching network with two $L$-section networks connected in cascade are introduced to extend the operating bandwidth. The matching network is composed of an inductive section for the high frequency band matching and a high-pass type section for the low frequency band matching. both $L$-section networks consist of chip inductor or chip capacitance and the value of them are optimized to meet the requirement using the advanced design system (ADS) software. Considering average power density of the ambient wireless energy harvesting, Schottky diode SMS7630 is selected in rectifying circuit due to its high detection sensitivity. The results show that the wideband rectifier operated from 1.5 to 2.5 GHz with input power ranging from −10 dBm to 9 dBm, it covers the GSM-1800/4G, UMTS-2100/3G, and WLAN bands. The peak conversion efficiency is 61% at the frequency of 1.5 GHz when the input power is 5.5 dBm. It can maintain a high conversion efficiency (more than 50%) over the frequency band from 1.5 to 2.3 GHz with input power ranging at 6.1 dBm. The structure of the wideband rectifier is simple and easy to manufacture. These advantages make it be applied in the ambient wireless energy harvesting.
Future of Graphene based Interconnecte Technology - A Reality or a Distant Dream

In the era of advanced sub-micron technology, the on-chip interconnect primarily dominates the overall system performance. This paper critically addresses the impact of technology advancement and spacing on crosstalk induced delay and peak noise for copper and multi-layered graphene nanoribbon (MLGNR) based global on-chip interconnects. In order to demonstrate the crosstalk effect, this paper presents the multi-conductor transmission line (MTL) model of MLGNR that can be further simplified to an equivalent single conductor (ESC) model with a negligible tolerance below 0.91% irrespective of interconnect lengths and spacing. Using the proposed ESC model, the crosstalk induced delay and noise are analyzed for a coupled driver-interconnect-load setup. It is observed that the MLGNR possesses a negligible crosstalk effect at an advanced technology node in comparison to Cu interconnects. At 14 nm technology node, the overall crosstalk induced delay of MLGNR can be reduced by 48.1% with respect to Cu in comparison to 32 nm node at global interconnect lengths.
High-Resolution Compact On-Chip Spectrometer Based on an Echelle Grating With Densely Packed Waveguide Array

We design a 121-channel on-chip spectrometer based on an echelle grating with densely packed waveguide array on 220-nm silicon-on-insulator platform. It offers a high spectral resolution of 0.5 nm in a 3 * 3 mm2 footprint, covering a spectral range of 60 nm near the central wavelength of 1550 nm. We fabricate the spectrometer with 20 channels for verification of the design, which is limited by our equipment. The measured crosstalk for the fabricated device is –4.3 dB and can be improved by better fabrication techniques. This spectrometer can be used for lab-on-a-chip spectroscopy applications, such as drug analysis in biotechnological and pharmaceutical research.
Establishing the Stacked Value of Battery Energy Storage in Electric Power Systems

The true value of a battery energy storage system (BESS) can only be established when multiple technically and operationally compatible services rendered by the BESS are ‘stacked’ and valued. This paper makes an attempt towards estimating the stacked value of a BESS providing multiple services such as peak shaving, frequency regulation, and reserve support etc. in an Arizona-based test system. This has been achieved by developing a mixed-integer programming (MIP) based optimization model that captures the operation of the BESS in the test system. The obtained results suggest that BESS with stacked benefits yield significantly more value than BESS delivering a single primary service in isolation.
Fast and Accurate Sea-Land Segmentation based on Improved SeNet and Coastline Database for Large-Scale Image

Sea-land segmentation is an important and key procedure for the ocean target detection. Owing to complex coastline environment, the existing sea-land segmentation algorithms are difficult to extract helpful features while dealing with large-scale satellite remote sensing images. The paper presents a coarse-to-fine sea-land segmentation approach by combining the improved structured edge network (SeNet) and the coastline database. First of all the coarse latitude and longitude of the segmentation points between sea and land is obtained through applying coastline database to remote sensing images. Secondly on the basis of segmentation point, the region around coastline is divided into a group of blocks with 800×800 pixels. Finally SeNet is improved to separate the sea and land of the region. Experiential results on a large data set demonstrated that the proposed method achieved better accuracy and running time than the other methods.
Dimensionality reduction via adjusting data distribution density

Dimensionality reduction is an important processing step for pattern recognition. Designing a new optimization goal is a popular method to improve the effect of the dimensionality decrease method. In this paper, we noted that the distribution density of data was not considered in the most classifiers, which may have a negative impact on the classifier. To overcome the above problem, a new optimization goal is designed under the distribution density of the data. In this optimization goal, the sample with smaller density owns larger impact for the optimization result, and then the density of sample could be adjusted to nearly the same in the low dimensional space. The experiments performed verified the proposed method in terms of classification performance.
A Multi-level Internet Traffic Classifier Using Deep Learning

In the network domain, there is a continuous ongoing evolution in the type of connected devices and the nature of developed applications. This presents the network with varying Quality of Service (QoS) and security requirements. Consequently, there is a need to classify Internet traffic to facilitate its management. Thus, a granular classification based on needs is required, one which relates better to the network requirements of the traffic. In this paper, we apply deep learning to classify traffic requiring different QoS and security policies. We propose a multi-level classification framework applying a new data representation method. A comparison between the proposed data representation method and a previous method is presented. The implementation results show that the proposed data representation model outperforms the previous one and promises to permit the classification of the traffic at different granularity. Recording up to 95% accuracy using only the size, interarrival time, direction, transport protocol of the first 16 packets of each flow, our method can be employed in an online classification platform.
A Compact Millimeter-Wave Array Element Design Combining Integrated Feed and External Taper Slot Structure

A compact composite antenna to obtain high directivity for millimeter-wave communication is proposed. The proposed antenna can be easily integrated with IC with low cost by simply attaching PCB planar tapered slot antenna(TSA)to on-chip antenna, providing increased directivity. Feed slot on TSA receiving electric fields from primary antenna is optimized to obtain good impedance matching and low side-lobe level. Simulated E-plane pattern shows 10.9 dB of directivity which is 7.5 dB higher than stand-alone dipole antenna, while H-plane pattern maintains relatively wider beamwidth characteristic for wide beam-steering range in phase array system.
The Waste Water as a Source of Information for the Urban Agglomerations Management

This paper presents a clear relationship between agglomeration, smart cities and waste management in Slovak republic. The main contribution of this work is to investigate the relationship between smart cities management and the wastewater coming from the households to waste water treatment plant. It has been shown that the gathered information from the waste water is very useful for identifying the locations of pollution caused by medicaments and drugs in a city. We provide a brief overview of smart cities, followed by statistical information about world's population and the population of cities within Slovak republic. Moreover, the key information about the locations and the times of pollution is briefly discussed. Exploiting the network theory and the tree data structure used in this work, enables one to localize the collection points and to create the infrastructure for automatized collection of data. Compared to previous work, we identify the pollution points more effectively and more economically. Therefore, this makes the solution attractive for criminology of drug distribution points in the city. Subsequently, it leads to cleaner, safer and more environmentally friendly cities.
Adaptive Control for Exponential Synchronization of Delayed Memristive Neural Networks

The exponential synchronization is studied in this paper for delayed memristive neural networks (MNNs). A new discontinuous adaptive control scheme is designed, which employs not only the proportional action but also the derivative action. Then, by adopting the adaptive control scheme and constructing an appropriate Lyapunov-Krasovskii functional (LKF), novel synchronization conditions are established. In the end, we use a numerical example to verify the effectiveness of the theory results.
Bi-Directional Indoor VLC system with Backhaul Solution

This paper investigates the performance of a two way decode and forward (DF) relayed Visible light communication (VLC) system with a backhaul solution. The visible light emitting diodes (LEDs) serve for downlink transmission and the infrared LEDs serve for the uplink transmission. In this paper two backhaul solutions are analyzed first being the traditional radio frequency (RF) and the other one being the free space optics (FSO). We derive the closed form expressions of signal to noise (SNR) statistics i.e. Cumulative Distribution Function (CDF) and Probability Density Function (PDF)). We further achieve the expressions for Average Bit Error Rate (ABER) and outage performance.
Time Synchronization Sequence with Weighted Conjugate Symmetry Property for FBMC-OQAM Systems

In this paper we consider the problem of time synchronization sequence design for filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) systems. The subcarrier-filtering operation in FBMC-OQAM systems offers extremely low out-of-band radiations, but it also causes the symbols to overlap, which makes the synchronization sequence design difficult. We propose a new time synchronization sequence scheme which is applicable to the continuous FBM C-OQAM signals transmission scenarios and achieves high spectrum efficiency. Initially, we introduce a method to create a sequence with the property which we call weighted conjugate symmetry property for FBMC-OQAM signals. Furthermore, we give an example of the calculation method to make the training sequence similar to Zadoff-Chu sequence, and also three timing offset estimation algorithms are proposed. Finally, some simulation results are presented and show that the proposed method could achieve good performances in various channel cases.