Miracle-dz/UniFAR-FTUs huggingface dataset:
A 30-40 GHz Continuous Class F−1 Power Amplifier with 35.8% Peak PAE in 65 nm CMOS Technology

This paper presents a continuous-mode inverse Class-F (i.e., Class-F-1) power amplifier design to achieve both high efficiency and wide bandwidth for 5G communications. The proposed fundamental and harmonic matching is achieved using an output transformer with an embedded capacitor for continuous inverse class-F operation. In this way, we can reduce the harmonic load complexity and insertion loss greatly. Therefore, the proposed inverse Class-F PA shows a saturated output power (Psat) of 17.9 dBm, output power bandwidth (30 to 40 GHz) with 33 % peak PAE, and output 1-dB compression point (OP1dB) of 15.0 dBm at 34 GHz. When tested with a single-carrier 64-QAM signal, this PA achieves bandwidth of 400 MHz, 14.1-dBm average output power, and 22.1% average PAE under root-mean-square (rms) error vector magnitude (EVM) −25.1 dB. Among all the published mm-Wave CMOS PAs, this PA shows outstanding large-signal performances and exceptional modulation capability.
Image Segmentation Based Hybrid Watermarking Algorithm for Copyright Protection

Today, most of the information shared across the globe is in multimedia form like audio, video and image. With increased globalization, any type of such information can be broadcasted throughout the world easily and is accessible to multiple users for varied applications. This may lead to fraudulent claiming of data ownership which makes copyright protection a major priority in today's world. Digital Watermarking serves as a prime solution to copyright protection where we embed watermark into digital image which serves as an authenticator. In this paper, we proposed a hybrid algorithm using Image segmentation, SVD (Singular value decomposition), DWT (Discrete wavelet transformation), Homomorphic filtering and RSA encryption technique that helps to overcome various threats. Here, we proposed a new approach of digital watermarking by embedding two segmented watermarks which are obtained using two distinct threshold values on the original watermark. These threshold values are sent as secret keys to the receiver using Diffie-Hellman key exchange algorithm and can be used at the time of copyright verification. This approach of hybrid technique is being tested by applying Gaussian Noise and it gave the best results when compared with the other digital watermarking techniques
Assessment of gait symmetry, torque interaction and muscular response due to the unilateral assistance provided by an active knee orthosis in healthy subjects

Stroke survivors usually present asymmetric gait and mobility impairments as consequence of hemiparesis. In order to alleviate this unilateral loss of mobility and correct this asymmetry, we developed an active knee-orthosis to assist the movement of the impaired leg. The control strategies of the orthosis that we have implemented are based on the kinematics of the healthy leg, by replicating the movement of the healthy one, or by using this movement to synchronize the application of a normalized healthy pattern over the impaired leg. Our main aim is to understand how stroke patient’s gait evolve to adapt to the assistance provided, as a preliminary study, in this paper we describe the effects of the assistance provided in twelve (12) healthy subjects who wore the robotic exoskeleton while they performed overground walking trials. Results indicated that the robot improved the gait symmetry of the users, reducing the spatial and temporal differences between the movements of both legs, without significantly disturbing the stance/swing ratio of the users. In addition, results showed that users tended to respond to this assistance by generating torque in the same direction of the robot action instead of taking advantage of the assistance provided by the exoskeleton. Muscular response of the assisted leg also shows variations according to this torque response, increasing the muscular activity in the 22.7% of cases against the 4% of cases where it was decreased. Finally, we detected changes not only in the assisted leg, but also in the unassisted one, whose muscular activity increased in the 28% of cases against the 1% of cases where it was decreased, showing the effect that the assistance on one leg have over the whole gait dynamics.
Modular Deep Reinforcement Learning for Emergent Locomotion on a Six-Legged Robot

Deep Reinforcement Learning (DRL) approaches have shown tremendous success over the last years in different application areas. But control of robots in real world settings and when facing unpredictable environments has still proven to be a difficult task that requires unreasonable long training times. This has sparked new interest in the organization of animal and human motor control systems and how to transfer these insights into such DRL learning architectures. While a hierarchical organization has now been advocated and introduced into a couple of DRL approaches, we propose decentralization as one further effective organizational principle. As an example we are considering insect locomotion (in particular locomotion of stick insects) which is adaptive and robust even when dealing with unpredictability. The underlying control system is assumed to consist of six individual local control modules that each control the action of a single leg. These local controllers only share limited information with neighboring legs which has shown sufficient to produce robust adaptive walking. In this article, we implement such a decentralized architecture of six local control modules and train it using Deep Reinforcement Learning. This architecture shows faster training times compared to a standard centralized approach and a trend towards more adaptive behavior and better performance when facing uncertain environments.
Study on the Influences of Multiple Parameters With Uncertainty in the Clamp-On Ultrasonic Flowmeter

For a clamp-on ultrasonic flowmeter based on transit-time differential method, the flow rate calculation model with flow velocity correction is established and verified by experiments carried out in a flow standard facility. Based on established flow rate calculation model, a systematic methodology incorporating the parametric uncertainty distribution is proposed to analyze the influences of multiple parameters with uncertainty on measurement error by establishing the sample-based stochastic model. Monte Carlo sampling (MCS) method is used to randomly select the value of each parameter from its prescribed Gaussian distribution and then combining them together as one sample, and the number of selected samples is determined by conducting stochastic convergence analysis of mean value and the standard deviation of input and output parameters. And finally the influence degrees of multiple parameters are analyzed and compared quantitatively on the same dimension to find out which parameters are influential and which are negligible. The results reveal the different influences of multiple parameters with uncertainty, which can be used as reference for performance improvement and measuring error analysis of the clamp-on ultrasonic flowmeter in industrial local measurement.
Cybersecurity Attacks in Vehicular Sensors

Today’s modern vehicles contain anywhere from sixty to one-hundred sensors and exhibit the characteristics of Cyber-Physical-Systems (CPS). There is a high degree of coupling, cohesiveness, and interactions among vehicle’s CPS components (e.g., sensors, devices, systems, systems-of-systems) across sensing, communication, and control layers. Cyber-attacks in the sensing or communication layers can compromise the security of the control layer. This paper provides a detailed review of potential cyber threats related to the sensing layer. Notably, the focus is mainly towards two categories of sensors: vehicle dynamics sensors (e.g., Tire Pressure Monitoring Systems (TPMS), magnetic encoders, and inertial sensors) and environment sensors (e.g., Light Detection and Ranging (LiDAR), ultrasonic, camera, Radio Detection and Ranging (Radar) systems, and Global Positioning System (GPS) units). The paper also offers perspectives through existing countermeasures from literature and stresses the need for data-driven cybersecurity solutions.
Antenna Arrays Calibration Using Recursive Least Squares Adaptive Filtering Algorithms Based on Inverse QR Decomposition

This paper considers the antenna arrays calibration by the using of the Recursive Least Squares (RLS) adaptive filtering algorithms. An algorithm, based on the inverse QR decomposition, has been selected among the diversity of the RLS algorithms. This is caused by its stable operation. Because the algorithm contains the computationally heavy square root operations, a square root free version of the algorithm is also presented. Both versions of the QR RLS algorithms are mathematically identical to each other if they operate in float point arithmetic. The proposed calibration can be used in the antenna arrays with digital beamforming, because the algorithms usage requires the access to the array channel signals. The calibration requires a known training signal, which can be easily provided not only in a laboratory environment, but also in a field operation, if an array is used as a directional antenna of the digital communication system equipment. In the second case, the calibration can be also conducted even in the presence of the interference signal sources. Simulation validates the proposed calibration algorithm, using linear antenna arrays with 4, 8 and 16 antennas with a half wavelength distance between the neighbor antennas. In this simulation, the array channel noise has been varied in 0 … 30 dB range of the Signal-to-Noise Ratio. Two interference sources with the –30 dB Signal-to-Interference Ratio each have been simulated. These sources were located symmetrically relatively the required main lobe direction of the array radiation pattern. A training signal has been simulated as a random one with no specific autocorrelation properties. The signal has been modulated by the Phase Shift Keying (PSK) and the Quadrature Amplitude Modulation.
Therapy with T-FLEX Ankle-Exoskeleton for Motor Recovery: A Case Study with a Stroke Survivor

Stroke is the main neurological condition causing disability worldwide. Physical therapy and robotic devices have been used in rehabilitation to recover lost locomotor functions. Despite the advantages of using robots in rehabilitation scenarios, some joints remain with alterations after therapy processes (e.g., the ankle joint). This paper presents a single case study of a patient with chronic stroke who participated in 18 sessions to assess the effects of T-FLEX in lower limb kinematics, spatiotemporal parameters, and muscular activity. To this end, each session consisted of two modalities: (1) 90-degree knee flexion, and (2) complete knee extension. The results showed improvement in the participant’s spatiotemporal and kinematic parameters, as well as in the foot clearance during the swing phase. Regarding the muscular activity, the first sessions showed considerable increases related to the patient’s inactivity. However, as the experiment proceeded, this value decreased as a consequence of the adaptation to the device. Regarding the electrical activity measured during each session, both muscles (i.e., gastrocnemius and tibialis anterior) tended to increase at the end-stage.
Optimization of Memory Oriented Network-on-Chip for FPGA

In this paper we identify that by the bottleneck link interconnect throughput is limited, tons of files gets created automatically in cache and speed of the network becomes slow down also sometimes system gets hang. Hence we are describing Optimization of cache memory by analyzing the Network on chip (NoC) and field programmable gate array. In this paper with the help of ring topology we are introducing the DWT. Discrete wavelet Transform (DWT) is used to compress the cache memory. By implementing this proposed method System will get faster. Using the terms of FPGA, we believe that our implementation system will provide high gain and less intricacy.
Event-Driven Data Pipeline for Network Management Systems

Developing an event-driven applications for network management systems(NMS) requires data-wrangling operations to be performed in a data pipeline with low latency and high throughput. Data stream processing engines(SPEs) enables the pipeline to feature extract complex data in near real time. We present a low latency and high throughput data pipeline that performs operations such as data cleansing, filtering, aggregations and join of streams on pipeline stages for event-driven machine learning applications. When the data stream has imbalance in arrival of records, a standalone system handle it ineffectively that reduces the performance of data pipeline. In this work, the system powered by SPEs handle the imbalance by scaling out resources and degree of parallelism such that performance is not degraded.
More molecular evidence for interspecific relationships in Liquidambar (Hamamelidaceae)

There are four species of Liquidambar L. (Altingioideae, Ha mamelidaceae). Liquidambar orientalis Miller occurs in western Asia and L. styraciflua L. in Northern and Central America, while L. acalycina Chang and L. formosana Hance are found in south eastern Asia (Bogle 1986). A phylogenetic analysis has recently been conducted based on DNA sequences of the plastid gene matK. (Li et al. 1997a). Li et al. found that the western Asian species L. orientalis is most closely related to the New World species L. styraciflua. This result is consistent with an earlier allozyme study (Hoey and Parks 1991). The finding is significant because it suggests a possible phytogeographical connection be tween the western Eurasian continent and the New World.
Security Assessment in Foggy Era through Analytical Hierarchy Process

Fog Computing provides users with the cloud facilities at the network edge. It may be assumed to be a virtual platform with adequate storage. , computation and processing facilities for latency-sensitive applications. The basic difference lies with the fact that this platform is decentralized in nature. In addition. , the fog systems or devices process data locally. , are conveyable and are capable of being installed on heterogenous hardware. This versatility in its behavior and it being at the network edge turns the attention towards the security of the users sensitive data (in transition or at rest). In this paper. , the authors have emphasized on the security of the fog level in typical Fog- IoT architecture. Various security factors (along with their subfactors) persisting at fog level are identified and discussed in detail. The authors have presented a hierarchy of fog computing security factors that is expected to help in considering security in a systematic and efficient manner. Further. , the authors have also ranked the same through Analytical Hierarchy Process (AHP) and compared the results with Fuzzy-AHP (F-AHP). The results are found to be highly correlated.
A Decision Support System of Selecting Groups (Science/ Business Studies/ Humanities) for Secondary School Students in Bangladesh

As education is the only way to turn a person into human resource, every country tries to give her citizens proper scope of bringing out their inner ability by offering the appropriate education. According to the education system of Bangladesh, an 8th grade completing student has to choose a group (science, Business Studies, humanity) for further studies. This group will be his/her initial highway for higher education. But it is a matter of sorrow that, in Bangladesh this crucial event is done by some rumors and some traditional old school ways, which are mostly wrong and destructive. From the perspective of this country, the only way of choosing those groups is previous result. Of course, result is one of the most important attribute, but it should not be the only thing. Again in this country, Science is thought to be superior than other groups. That's why, parents have the tendency to impose this group to their children without knowing their ability and interest and leads them towards an uncertain future. Therefore, the aim of this paper is to build a model of group selection by analyzing some random attributes of higher level students who have already gone through this event of selecting groups with the help of data mining and some machine learning algorithms, so that a newly 9th grade student could have the proper direction of selecting a group which is best for him/her. For the purpose of experimentation we have used three machine learning algorithms: Naïve Bayes, Sequential Minimal Optimization (SMO) and Random Forest. Among these algorithms Random forest gives the best prediction result with an accuracy of 84.9%.
Research on Mechanisms and Benefits of Electrochemical Energy Storage Participating in Power System Peak Shaving

Electrochemical energy storage is considered to be the best quality participant in the ancillary services market because its power and energy can respond quickly to demand. However, nowadays the trading mechanisms of the ancillary services market are mainly aimed at conventional generators which results in the lack of bidding and settlement mechanisms for energy storage participation in the ancillary services market. In this case, the trading mechanisms of energy storage participating in the peak shaving market is focused on in this paper. Based on the relationship between the charge-discharge depth and its life and the equivalent annual cost, this paper suggests that the energy storage quotation in peak shaving bidding should be various based on the charge-discharge depth zones. Besides, the one-part and two-part settlement methods in the peak shaving market are came up. According to the calculation of the investment cost and peak shaving benefit of electrochemical energy storage, charging and discharging price models suitable for energy storage to participate in peak shaving are proposed. The mentioned methods are verified by a specific case to analyze the cost-effectiveness of electrochemical energy storage in peak shaving.
A 140-GHz 14-dBm Power Amplifier using Power Combiner based on Symmetric Balun in 65-nm Bulk CMOS

This paper proposes a 140-GHz power amplifier (PA) with 14-dBm saturated output power. Our PA uses a symmetric-balun-based power combiner in D-band, which relaxes the impedance matching with the former-stage amplifiers thanks to the balanced input impedance. The PA prototypes have been designed in 65-nm bulk CMOS process. The 2-parallel PA achieves 6.0 dBm OP1dB with measurement, and 11.4 dBm saturated output power is expected with simulation. The performance of the 4-parallel PA is verified with simulation that shows 9.4 dBm OP1dB and 14 dBm saturated output power.
UAV Swarm Intelligence: Recent Advances and Future Trends

The dynamic uncertain environment and complex tasks determine that the unmanned aerial vehicle (UAV) system is bound to develop towards clustering, autonomy, and intelligence. In this article, we present a comprehensive survey of UAV swarm intelligence from the hierarchical framework perspective. Firstly, we review the basics and advances of UAV swarm intelligent technology. Then we look inside to investigate the research work by classifying UAV swarm intelligence research into five layers, i.e., decision-making layer, path planning layer, control layer, communication layer, and application layer. Furthermore, the relationship between each level is explicitly illustrated, and the research trends of each layer are given. Finally, limitations and possible technology trends of swarm intelligence are also covered to enable further research interests. Through this in-depth literature review, we intend to provide novel insights into the latest technologies in UAV swarm intelligence.
Performance Evaluation of Various Beamforming Techniques for Phased Array Antennas

In beamforming, the signals from the particular direction are weighted, whereas signals from other directions are attenuated. In uniform linear array (ULA) of phased array antennas, the beamformer combines the signals linearly from each element of the array and achieves directionality. In uniform planar array (UPA) the antenna elements are arranged in a plane. These antennas can be steered electronically by adjusting the phase and gain. This paper deals with types of beamforming such as conventional, tapered, optimum and adaptive beamforming. In adaptive beamforming, the Sample Matrix Inversion (SMI) method is discussed along with the concept of diagonal loading. The use of diagonal loading reduces the sidelobe level by 12 dB and 25dB in linear and planar array respectively for 100 input training samples.
An Improved Self-Powered H-Bridge Circuit for Voltage Rectification of Piezoelectric Energy Harvesting System

In recent years, piezoelectric materials have been widely investigated for harvesting energy from ambient vibrations. A vibrating piezoelectric device (PD) generates alternating current (AC), which needs to be converted into direct current (DC) for powering electronic devices or for storage. A traditional full-wave bridge rectifier (FBR) interface circuit serves this purpose, but it suffers from high power loss due to the presence of high forward voltage across the diodes. In this article, an improved H-Bridge rectifier circuit is proposed as the AC-DC rectifier circuit to reduce power loss for high frequency and low amplitude application. The performance of the proposed rectifier circuit was experimentally studied, analysed and discussed. Two different testing scenarios for high frequency, namely, varying input power with fixed excitation frequency and varying excitation frequency with fixed input voltage were considered. Applicability of the circuit at low frequency range was also investigated. The outcome shows that the proposed circuit notably increases the voltage and the power produced from the PD when compared to traditional FBR circuits.
Fault analysis of pole-to-pole short-cicuit on the flexible AC-DC hybrid distribution network

The stable operation of the flexible AC-DC hybrid distribution network is inseparable from the support of relay protection technology, while the in-depth analysis of different types of faults will lay the foundation for the selection of relay protection schemes. This paper introduces the current situation of fault analysis of flexible AC-DC Hybrid distribution network, and set up a model of radiated flexible AC-DC hybrid distribution network on PSCAD/EMTDC platform. The pole-to-pole short circuit fault of DC side is deeply studied. Based on the simulation results, the response process of the entire fault as well as the characteristics and trends of transient variables after the fault are studied in-depth, which lays a foundation for the research of the subsequent relay protection method and the configuration of the protection device.