Miracle-dz/UniFAR-FTUs huggingface dataset:
Shared Envelope Tracking for Time-Delayed Power Amplifiers in Phased Array Systems

Analysis shows that multiple time-delayed power amplifiers can share a single envelope tracker and provide a significant improvement over statically supplied amplifiers. Phased arrays are a suitable application of this technique. Our analysis shows a 15 point efficiency improvement over a static supply when amplifying a two-tone signal. We claim that sharing an envelope tracker is justified when $\frac{1}{2} \gg \frac{\Delta f}{f_{0}} \sin(\theta) (N-1$), where $\frac{\Delta f}{f_{0}}$ is the fractional bandwidth of the signal, $\theta$ is the maximum steering angle, and $N$ is the number of elements sharing an envelope tracker. Closed form analytic solutions of a two-tone signal are presented to verify the concept.
Multiple Accelerometers and Magnetometers Joint Calibration and Alignment

In this article, we introduce a computationally efficient algorithm for simultaneous joint calibration and axes alignment of multiple three-axis accelerometers or magnetometers. The proposed algorithm applies to ensembles of sensors of the same type, fixed to the same rigid platform. It compensates for all linear time-invariant distortions, such as scale factor, cross coupling, and offset, including the soft-iron and hard-iron distortions of the magnetometer. It can be implemented in a simple 12-step sequence and provides fast and accurate calibration without requiring any special piece of equipment.
Cooperative UAV Jammer for Enhancing Physical Layer Security: Robust Design for Jamming Power and Trajectory

An unmanned aerial vehicle (UAV)-aided network is becoming a promising application for the future wireless communication due to the flexible deployment and dominant line-of-sight channel. In this paper, we consider the UAV is operated as a cooperative jammer to enhance the physical layer security of the ground legitimated nodes in the presence of an eavesdropper (Eve). Furthermore, we assume that the UAV has imperfect information on the locations of the receiver and Eve due to GPS jamming and covert operation of Eve, respectively. With these uncertainties of the nodes' locations, we formulate a robust joint optimization problem of the UAV's jamming power and trajectory to maximize the average secrecy rate. To handle the non-convexity of the optimization problem, we propose an iterative suboptimal algorithm based on the block coordinate descent method. Simulation results present that the proposed algorithm has outstanding performance in terms of physical layer security compared to other benchmark methods.
Incentive Mechanism with the Caching Strategy for Content Sharing in Vehicular Networks

With the development of cellular vehicle-to- everything(C-V2X) services, content sharing through vehicle-to-vehicle(V2V) communications becomes an effective solution for overburdened vehicular networks. However, due to the different content preferences and limited resources of rational vehicles, vehicle owners are reluctant to participate in content sharing. To address this issue, we first propose a dynamic pricing-based incentive mechanism by jointly considering content information and link status to stimulate content sharing in C-V2X-based vehicular networks. Considering that content sharing among vehicles is supported by vehicle caching, we then propose a caching replacement strategy to further improve the quality of content sharing. Particularly, we employ the multi-factor stock selection model to predict the future revenue of cached contents. We present numerical simulation results to show that the proposed incentive mechanism with the caching strategy can effectively improve the content delivery ratio and hit ratio in vehicular networks.
A Bus Shaped Tri-band Antenna for Sub-6 GHz 5G Wireless Communication on Flexible PET Substrate

The emergence of 5th generation (5G) wireless technology has triggered the need for low-cost, compact, highperformance, and multi-band antennas, especially for flexible and wearable applications. This paper is an effort in this direction, and presents a compact and flexible antenna which operates at 5.3 GHz, 5.6 GHz, and 5.8 GHz. These bands fall in sub-6 GHz band allocated by the Federal Communications Commission (FCC) for potential 5G applications. The flexible antenna is designed on 0.1 mm thick Polyethylene Terephthalate (PET) substrate with loss tangent of 0.002 and relative dielectric constant (Er) of 3. The antenna geometry consists of symmetrical slots based bus-shaped patch which is excited by microstrip line inset feed having an impedance of 50 O. The overall profile of the antenna is 44mm×70mm×0.1mm(LxWxH). Simulations using ANSYS High Frequency Structure Simulator (HFSS) show that the antenna has S11 values of −18.5 dB at 5.3 GHz, −26.76 dB at 5.6 GHz, and −12.79 dB at 5.8 GHz. It has a Voltage Wave Standing Ratio (VSWR) of 1.27 at 5.3 GHz, 1.096 at 5.6 GHz, and 1.59 at 5.8 GHz. The antenna demonstrates gain of 7.8 dB at 5.3 GHz, 5.9 dB at 5.6 GHz, and 4.39 dB at 5.8 GHz. The proposed antenna exhibits a very good radiation efficiency of 86.5%.
Enhancing C-RAN Downlink Performance via Inter-UE D2D Cooperation

Cloud radio access network (C-RAN) is an emerging architecture for achieving high data rate and massive connectivity in future wireless communication systems. To further improve the performance of C-RAN downlink, this work considers the advantages of cooperation among user equipments (UEs). Specifically, it is assumed that the UEs can exchange the downlink received baseband signals via device-to-device (D2D) communication links which are orthogonal to downlink channel. The problem of jointly optimizing the C-RAN downlink and inter-UeD2d communication strategies is tackled with the goal of maximizing the sum-rate of UEs. To address the formulated problem, an iterative algorithm is proposed which attains a suboptimal solution of the problem. Numerical results confirm that the inter-UE D2D cooperation is effective to improve the downlink nerformance of C-RAN systems.
Study on the Integrated Observation Method of Multi Elements of Soil Environment

Among China's meteorological observation items, frozen soil, soil temperature, soil moisture and dry soil layer are elements which related to soil. These items are observed by a variety of single element observation equipments, while the frozen soil and dry soil layer have not yet achieved automatic observation. This paper proposes a multi-element integrated observation method for soil environment. The sensor measures the soil dielectric constant and temperature change through a planar capacitor and a semiconductor temperature measuring element to achieve the measurement of soil moisture and soil temperature. The water-induced freezing phase change causes dielectric The characteristics of the constant change of the constant, establish a mathematical model based on soil dielectric constant and ground temperature to invert frozen soil to achieve accurate measurement of frozen soil; soil moisture combined with soil hydrophysical constants can realize automatic observation of dry soil layers. The experiment shows that the multi-element sensor of soil environment can accurately measure the elements such as soil moisture and frozen soil. The measurement data is consistent with the trend of manual observation, and the automatic observation of frozen soil and dry soil layer is realized.
Dynamic Asset Allocation with Jump-Diffusion Processes

This paper study the problem of optimization and equilibrium. Supposing that risk assets pay continuous dividend regarded as the function of time. It is established that the behavior model of the stock pricing process is jump-diffusion driven by a nonexplosive counting process. We establish the existence of a solution to the optimization problem using the theory of martingales.
Terahertz Wireless CDMA Communication Using Resonant Tunneling Diodes

This paper describes a code division multiple access (CDMA) system operating in the Terahertz (THz) band using resonant tunneling diode (RTD) technology. RTDs are a promising technology enabling the efficient generation and detection of THz-band signals while consuming very low power. Meanwhile, CDMA systems facilitate the transmission of multiple-users signals in low signal to noise ratio (SNR) conditions. The developed THz system consists of real-time CDMA waveform transmission at 3.1 Gchip/s for up to 7 users over a distance of 7.5 cm at 345 GHz with off-line decoding of the digitally-sampled signals. The system employs optical modified prime codes (MPC) with unipolar (0,1) sequences that were originally designed for CDMA optical-fiber networks with simplified detection. Experimental results demonstrate the viability of CDMA transmission using RTDs with chip-level on-off-keying (OOK).
Ameliorating IoT and WSNs via Machine Learning

The dependence of everyday human life on smart devices is exponentially increasing. Wireless Sensor Networks (WSNs) and Internet of Things (IoT) are becoming of momentous importance every day. However, their challenges also increase with their evolution, and the urge for their improvement and continuous enhancement becomes more important. To adapt to such conditions, machine learning techniques are recently employed within WSNs and IoT systems to leverage their potential. This paper presents a survey of the use of machine learning-based algorithms in WSNs and IoT to deem numerous basic operation and performance constraints.
63.2pS at 1.2V dynamic comparator in 65nm CMOS technology

A high speed dynamic comparator is proposed. The speed of the comparator is improved by reducing the voltage of the shared nodes of the input stage and latch stage. The proposed dynamic comparator has been designed and simulated using 65nm CMOS technology. The simulation results show that the proposed comparator achieved 63.2ps delay at 1.2V power supply
Profiling Social Media Campaigns and Political Influence: The Case of Pakistani Politics

Social networking websites have been widely used for political awareness and campaigns. With the increasing reliance of political parties and supporters on social media, interesting patterns can be extracted by analyzing social media profiles. The previous approaches perform political analysis used social media data mainly focused on analyzing only textual data for the two-party system. However, the social media engagement, i.e. posts reaction, of political supporters can be used to identify the most influential political party. Therefore, to explore the content of social media political campaigns and to identify the most influential political party using social engagement in a multi-party system, we extracted Facebook data using Facebook Graph API for the three most popular political parties in Pakistan, i.e. PTI, PML-N and, PPP. The results reported that PTI relies more on the English language when compared with PML-N and PTI. However, video content is most prominently used by all three parties. The ratio of reactions on Facebook posts varies, PTI has received the highest number of “LIKE” and “SHARE”, PML-N, and PPP has received the major number of “HAHA” and “SAD”. PTI appears as the most influential party in comparison with PML-N and PPP. The influence score for each party appeared in accordance with the results of Pakistan's General Elections 2018. Hence, the proposed influence score irrespective of party-system can be used by researchers to improve the accuracy of electoral prediction. The insights highlighted by this study can also be used by political parties to improve their social media campaigns for increasing social influence.
Polarization Insensitive Electromagnetically Induced Transparency in Topological Insulator Metasurface

Electromagnetically induced transparency (EIT) is widely studied in atomic systems and metamaterials. However, there are few studies of EIT on topological insulator (TI). In this paper, the EIT effect is studied in TI which is placed on the dielectric substrate by finite difference time domain (FDTD) method. We discussed the effective permittivity of TI layer on different temperature at terahertz (THz) range. The EIT-like phenomenon can be obtained at transverse electromagnetic (TE) and transverse magnetic (TM) mode. The parameters of dielectric substrate and TI layer are investigated to tune the EIT phenomenon. Moreover, incident angle of electromagnetic (EM) wave is also studied to influence the transmission of the structure. The result was shown the large incident angle and polarization insensitive EIT effect can be realized. The results can provide some potential applications such as terahertz switches, filters and terahertz communications.
Comparative Analysis of TQM and CMMI

It is the consensus of people that improving product quality by improving management, but the management standards adopted in different fields are not the same, which is easy to be confused. As to the current status of different quality management standards and methods used in different business areas, this paper analyzes the development history of the general quality management system in the production field and the core concept of total quality management(TQM), compares it with the CMMI standard of quality management in the system development field, analyzes each other’s strengths and weaknesses, and proposes suggestions for improving the deficiencies of CMMI. Finally, the relationship between TQM, CMMI and system engineering (SE) is analyzed, and concludes that the integration with model-based system engineering(MBSE) will be the new direction of CMMI’s future development.
Mechanism Modeling Considering Cognitive Overload and Cognitive Confusion

System safety, reliability and risk analysis are important tasks that are performed throughout the system lifecycle to ensure the dependability of safety-critical systems [1]. The major safety accidents of Human Machine Systems(HMS) are often caused by the coupling evolution of human, machine and environment in the mission process. The changes of task characteristics, information characteristics and performation shaping factors are related to the historical interaction process of Human Machine Interaction(HMI), which makes human error have obvious path-dependent characteristics. In order to better investigate the influence of path-dependent features on human error, this paper constructs the mechanism mode of HMI between cognitive overload and cognitive confusion from the information level. In addition, the impact of performance shaping factors updates on HMI is also analyzed by qualitative method.
The Role of Apprenticeship in Improving the Livelihood of HIV-PositiveAdolescents Who Prematurely Drop Out of School: The Mildmay UgandaExperience

Objective: HIV and AIDS have adverse effects on the livelihood of adolescents especially when parents die or are poor due to ill health. Mildmay Uganda has an apprenticeship programme that helps such adolescents acquire skills in order to improve their quality of life. The aim of this study was to examine the role of apprenticeship in improving the livelihood of HIV-positive adolescents who prematurely dropped out of school. Methods: A retrospective review of data of all adolescents who had been enrolled on the apprenticeship programme from January 2012 to January 2014 was done to document their progress and any lessons learnt. A vulnerability index tool was used to assess vulnerability levels and at same time to measure the progress and improvement of livelihood. Results: A total of twenty (20) adolescents were enrolled on the apprenticeship programme during the stated period. Sixty percent were male and were in the age range of 17-24 years. Sixteen out of the 20 (80%) were able to use the acquired skills through apprenticeship to improve their livelihood. The other four adolescents completed apprenticeship, but did not practice their acquired skills. One male opted to venture into another business and three females abandoned their vocations when they got married. The vulnerability level assessment outcome showed a graduation from extremely poor to poor. Adolescents were able to meet their basic needs, keep clinic appointments and were emotionally stable by end of period of review. Conclusion: Apprenticeship is one way that can be used successfully to improve the livelihood of adolescents who prematurely drop out of school.
Semi-supervised Multimodal Emotion Recognition with Improved Wasserstein GANs

Automatic emotion recognition has faced the challenge of lacking large-scale human labeled dataset for model learning due to the expensive data annotation cost and inevitable label ambiguity. To tackle such challenge, previous works have explored to transfer emotion label from one modality to the other modality assuming that the supervised annotation does exist in one modality or explored semi-supervised learning strategies to take advantage of large amount of unlabeled data with the focus on a single modality. In this work, we address the multimodal emotion recognition problem with the acoustic and visual modalities and propose a multi-modal network structure of the semi-supervised learning approach with an improved generative adversarial network CT-GAN. Extensive experiments conducted on a multi-modal emotion recognition corpus demonstrate the effectiveness of the proposed approach and prove that utilizing unlabeled data via GANs and combining multi-modalities both benefit the classification performance. We also carry out some detailed analysis experiments such as influence of unlabeled data quantity on recognition performance and impact of different normalization strategies for semi-supervised learning etc.
An Innovative I/O Budgeting Methodology for Hierarchical SoC Development

This paper introduces a new input/output (I/O) budgeting methodology enabling delayed exchange of updated hierarchical blocks at System-on-Chip (SoC) level without risking the timing and tapeout schedule. We propose a “freeze_interface” concept to re-define the timing constraints for each I/O path of a hierarchical block in a more precise and fine-grain way so that block and SoC level development can be completely independent. The timing budgeting methodology has been formulated and demonstrated by experimental results.
Studies of Relationships on Nutrition Knowledge, Nutrition Attitude, and Dietary Behaviors of Staff Nurses

The diet of many nurses does not conform to the recommended daily reference intake. Nurses tend to have numerous meals a day, frequently eat out, and do not exercise regularly; thus, they are likely to develop chronic diseases such as cardiovascular diseases and diabetes. This phenomenon, if being ignored, may have considerably negative effects on the nurses’ health in the long term. This study targeted nurses in a regional hospital in Southern Taiwan and aimed to understand their nutrition knowledge, nutrition attitude, and current dietary behavior and to investigate the factors that influence their dietary behavior. This study conducted a cross-sectional survey of the nurses in a regional hospital in Southern Taiwan from December 1, 2014 to February 28, 2015; 207 valid samples were obtained. The questionnaire of “A Study of Nutrition Knowledge, Attitude to Dietary Behavior among In-Service Student Nurses” was used in the present study. The results indicated that participants attained medium scores for nutrition knowledge and low scores for nutrition attitude and dietary behavior. A stepwise regression analysis revealed a positive correlation between the nutrition attitude and dietary behavior in nurses who did not do shiftwork, who worked in nursing homes or intensive care units, and who regularly read health magazines. The aforementioned variables were significant predictors of dietary behavior (p<0.05), explaining 46.6% of the total variance. In conclusion, the nurses’ nutrition attitude influenced their adoption of healthy dietary behaviors. Thus, hospitals should focus on developing a positive health-oriented attitude among nurses when promoting healthy dietary habits in the workplace.
Virtual-Fixtures for Robotic-Assisted Bi-manual Cutting using Vector-Field Inequalities

Master—slave robotic systems have enabled operators to perform complex tasks with high precision. Some tasks can be further enhanced by adding virtual fixtures, which can guide user motion or constrain it within a safety envelope. In this study, the focus is on the generation of virtual fixtures for robotic-assisted bi-manual cutting, with possible applications in medicine and industry. Two control methods are proposed: forbidden-plane constraints (for increased safety) and an angle-ellipsoid constraint (for increased performance) which guide the user to safe and efficient bi-manual cutting. The proposed methods were evaluated in a user experiment using a pathology grossing master-slave robotic system. The results show that the forbidden-plane constraints enhanced the safety of the task, while the angle-ellipsoid constraint reduced cutting error by more than 58% (p<0.05).
Design of Via-Hole for Dual Layer Butler Matrix

This paper presents a dual layer butler matrix for 5G wireless communication at 28 GHz using via-hole. Via-hole is proposed as the phase shifter connecting dual layer substrate Butler Matrix. In this design, two sides of the substrate are stacked to minimize the occupied area and to eliminate crossover component, resulting in a compact size and a low conductor loss. The two hybrids are designed at the top and bottom substrate with via-holes as the phase shifters and common ground plane at the centre. Phase shifters are designed using via-hole and Butler Matrix strip line is optimized for -45º, +135º, -135º and +45º output phase respectively. Consecutive phase input signal combiner/divider using the proposed Butler Matrix is executed at 28 GHz for fifth generation (5G) wireless connectivity.
Master-Slave Bipedal Walking and Semi-Automatic Standing Up of Humanoid Robots

This paper proposes a bipedal walking method and a standing-up method for master-slave humanoid robots. The methods can be used with a pair of inexpensive master devices, which are 3-DoF haptic devices with some auxiliary buttons. The user’s commands through the master devices are reflected in the motion of the robot’s legs to be able to make the robot locomote stably at the user’s will. During the walking, the height and the attitude of the robot torso are normally maintained constant, but are allowed to vary without affecting the balance when the user intends to make a long stride. The user is also able to take over the control of the robot’s arms. When the robot falls, the proposed method allows the user to use the arms to make the robot stand up, being assisted by a semi-automatic motion planner. The methods have been tested with our interactive/realtime simulation environment.
Underwater Acoustic Detection and Localization with a Convolutional Denoising Autoencoder

Detecting and tracking moving targets is a challenging task, which becomes even harder in underwater scenarios due to the extremely low levels of signal-to-noise ratio associated with common acoustic measures. In the context of continuous marine monitoring, a further challenge is provided by the need to deploy computationally efficient methods that guarantee minimum use of power resources in off-shore monitoring platforms. Here we present a novel approach to accurately detect and track moving targets from the reflections of an active acoustic emitter. Our system is based on a computationally- and energy-efficient deep convolutional denoising autoencoder. System performance is evaluated both on simulated and emulated data, and benchmarked against a probabilistic tracking method based on the Viterbi algorithm.