Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Integral State Feedback Using Coefficient Diagram in Magnetic Levitation System

Magnetic Levitation System or Maglev system is a modern and future technology that has many advantages and applications. Its characteristic is highly nonlinear, fast dynamics, and unstable, so it is challenging to make a suitable controller. The model of the Maglev system is in nonlinear state-space representation, and then feedback linearization is implemented to obtain the linear model system. Then, the integral state feedback control that tuned by the coefficient diagram method is implemented. The robustness of the controller is determined using the coefficient diagram method. The result of the standard coefficient diagram parameter will be compared with the robustness parameter. The open-loop test simulation showed that the maglev system has a nonlinear characteristic. Among all of the uncertainties, the uncertainty of resistance provides the highest nonlinearity, even by the small value of uncertainty. The examination of the mass, inductance, and resistance uncertainties showed that the robustness parameter is able to handle them and to provide a robust controller.
Quantitative Discussion on Sensitivity to Terahertz Waves of Detectors Made of MOSFET and High-Electron Mobility Transistor

A newly developed circuit model is presented to describe detection characteristic of square law detectors made of an FET under non-quasistatic condition. Sensing performance calculated using formulae derived from the model agrees well with results of experiment carried out to detect 1.0 THz waves using InAs-channel high-electron mobility transistor (HEMT). The model predicts that HEMT offers much higher voltage sensitivity to terahertz waves than Si MOSFET even for miniaturized devices.
Modeling and First Characterization of Broad-Spectrum Vibration Rejection of Frequency Modulated Gyroscopes

The work presents a detailed modeling and the first-ever characterization of a frequency modulated (FM) yaw gyroscope in presence of vibrations from low frequency (30 Hz), through the main modes, and up to 40 kHz. The gyroscope two in-plane axes (around 25 kHz) are operated under a Lissajous trajectory (70 Hz period) by an integrated circuit (IC) including oscillators, frequency digitization, and digital demodulation stages. In presence of $2-g_{pk-pk}$ vibrations, no effects are visible across the spectrum apart from the region including the modes. In this range, as predicted by theory, for each axis no effect is observed for accelerations at the axis resonance (< 0.1 dps/g), but a huge effect (tens of dps/g) is visible for accelerations at an offset frequency from resonance corresponding to the mode split.
Low-Cost LWIR-Band CMOS Infrared (CIR) Microbolometers for High Volume Applications

This paper provides an overview of the studies and the current status for the development of a novel, low-cost, and CMOS foundry compatible approach for implementing microbolometers with standard CMOS and simple post-CMOS subtractive MEMS processes. This CMOS infrared detector technology is shortly called as the CMOS IR (CIR) technology, and it can be used to implement Focal Plane Arrays (FPAs) for infrared imaging in the LWIR-band ($8-12\ \mu \mathrm{m}$ wavelength). Post-CMOS processes require only one mask lithography process and simple subtractive etching steps to obtain suspended bulk micromachined microbolometer pixels, where the detector element can be formed with standard CMOS layers and devices such as n-well layers, diodes, polysilicon, and some other CMOS layers and devices. Sensors of various pitch sizes (such as $70\mu \mathrm{m},\ 60\mu \mathrm{m}, 50\mu \mathrm{m}$, and $35\mu \mathrm{m}$) and various FPA formats (such as 160×120, 80×80, and 40×40) have been demonstrated; some of these studies resulted in real commercial products in a VC funded spin-off company. The recent commercial products have a $35\mu \mathrm{m}$ pixel pitch implemented using a $0.18\mu \mathrm{m}$ CMOS process. One of these is a 80×80 microbolometer FPA has a die size of 5.4mmx6. 5 mm and dissipates 20mW; the fabricated sensor is measured to provide NETD values of 163 mK at 17 fps and 71 mK at 4 fps with f/1.0 optics in a dewar, while using only the standard CMOS layers. When this FPA is wafer level vacuum packaged with a silicon cap wafer with one side AR coating, it provides a 112 mK NETD at 4 fps with f/1.1 optics. Another commercial product is the 160×120 FPA, which has a die size of 9.3 mm x 9.1 mm and dissipates less than 50 mW at 30 fps while operating with a 3.3V suppy. The sensor is measured to provide peak NETD values of 161 mK, 117 mK, and 90 mK at 17 fps, 11 fps, and 4 fps, respectively, in a dewar with f/1.0 optics. These performances are more than enough for a number high volume low-cost consumer market applications like advanced presence detection, human counting, smart offices/homes/cities, and other IoT applications. The performances can be improved further by using finer pitch standard CMOS processes as the CIR approach is scalable, allowing to reduce the pixel pitch even further while increasing the array size and/or improving the sensor performance if necessary for automotive, smart phone, and various other low-cost, high volume markets.
A Novel Centrality of Influential Nodes Identification in Complex Networks

Influential nodes identification in complex networks is vital for understanding and controlling the propagation process in complex networks. Some existing centrality measures ignore the impacts of neighbor node. It is well-known that degree is a famous centrality measure for influential nodes identification, and the contributions of neighbors also should be taken into consideration. Furthermore, topological connections among neighbors will affect nodes’ spreading ability, that is, the denser the connections among neighbors, the greater the chance of infection. In this paper, we propose a novel centrality, called DCC, to identify influential nodes by comprehensively considering degree and clustering coefficient as well as neighbors. The weights of degree and clustering coefficient are calculated by entropy technology. To verify the feasibility and effectiveness of DCC, the comparisons between DCC and other centrality measures in four aspects are conducted based on four real networks. The experimental results demonstrate that DCC is more effective in identifying influential nodes.
A Data Infrastructure for Managing Information Obtained from Ambient Assisted Living

The Internet of Things (IoT) is a current paradigm which can be part of several fields of application, and Healthcare is one of the most important. Ambient Assisted Living (AAL) is an important subfield in Healthcare. Also, services demand and network requirements of IoT systems due to the increase of connected devices and data flow overcharges Cloud. Fog Computing represents a new paradigm that lightens the network. Some applications use Fog Computing in order to reduce costs and improve performance of IoT applications. Healthcare is one of them and the implementation of Fog Computing architectures inside those systems is a new trend nowadays. The importance of having a data infrastructure in this kind of IoT systems is evident because of the relevance of the data. In this paper is presented a Data Infrastructure for Managing Information Obtained from Ambient Assisted Living. The model provides the data flow starting in the data reading in the IoT devices and ending in the Cloud by crossing Fog Computing Layer. The model considers communication protocols, security features and relationship between elements which take part in an AAL system. Moreover, the model was developed using Eclipse Modeling Tool and validated in the same tool by using an instantiation of the main classes of the model.
Work-in-Progress: Pricing Mechanism and Workload Scheduling to Optimize Social Welfare and Cost for Fog Computing Systems

Fog computing is a non-trivial extension of cloud computing to overcome many inherent limitations, such as huge network bandwidth and high latency. Fog computing involves a significantly large number of fog instances, unlike few centralized cloud servers. This work is an attempt to address two crucial challenges in fog computing systems in an integrated manner, namely the pricing of the resources and offloading of real-time tasks to appropriate fog instances. We propose an integrated framework to devise the pricing of the resources to maximize the social welfare and an offloading mechanism to minimize the cost of execution of the workloads with the timing constraint.
A 4-GHz Sub-harmonically Injection-Locked Phase-Locked Loop with Self-Calibrated Injection Timing and Pulsewidth

A 4-GHz sub-harmonically injection-locked phase locked loop (ILPLL) with on-chip calibration is presented. The injection timing and pulsewidth of the injected pulse are self-calibrated to achieve a low phase noise. The phase noise of the proposed ILPLL was -110.1 dBc/Hz at 1-MHz offset frequency, while that of the conventional PLL was -104.8 dBc/Hz. The measured reference spur was also reduced from -44.36 dBc to -52.87 dBc with the proposed calibration technique. Fabricated in a 28-nm CMOS process, the proposed ILPLL occupies 0.09 mm2. Operating at 4 GHz, it consumes 11.4 mW from a 1.0-V power supply.
Silicon-Chip Based Electromagnetic Vibration Energy Harvesters Rapidly Fabricated by Wafer-Level Molten Metal Micro-Casting Technique

This paper reports a silicon-chip based electromagnetic vibration energy harvester that is fabricated with a wafer level micro casting technique to form on-chip integrated 3D metal solenoid and magnet sliding channel. The 150-turn solenoid is fabricated by rapidly casting molten ZnA1 alloy (at its low melting point of 380°C) into pre-micromachined silicon mold, where all the coils (wire cross sectional area= $200\mu \mathrm{m}\times 40\mu \mathrm{m}$) in the wafer are formed within 7 minutes. A sliding magnet responding to environmental vibration is put into the channel inside the solenoid to generate electricity. With the wafer-level energy harvester fabrication technique, the size of the harvester chip is as tiny as $10.5\times 2.5\times 1.7\text{mm}$. Test shows that the harvester collects environmental energy high-efficiently within frequency range of 17-47Hz and generates peak power of $16.1\mu\mathrm{W}$ at 37Hz under 6.5g vibration. Compared to either non-MEMS wire-wound electromagnetic harvesters or normal on-chip piezoelectric/electrostatic ones, present on-chip EM harvester shows great improvement in volume power density.
A Novel Bistable Device Driven by Single Actuator via Moment Input

This work presents a novel fully-compliant bistable device that only requires one actuator for switching between its two stable states. The proposed one-actuator bistable device consists of a curved-beam structure and a V-beam actuator. The proposed device, which is driven by a thermal actuator via moment input, is a significantly improved version of our previous work, consumes less die area, is of much less complexity, and does not require latching mechanisms. Characterization of the proposed device of different dimensions was performed and discussed. Preliminary measurement results show that a 50 pulse frequency of 7.5 V with 50% duty cycle applied to the V-beam actuator can continuously switch the device between the two stable states. The maximum switching rate is about 25 Hz.
An Approach of Sensitivity and Metamodel-Based Analyses for SLA Violation Prediction

In support of software development based upon service-oriented architecture (SOA), service providers use quality of service (QoS) to guide their design of services. When the evaluation of QoS considers only influential factors among similar systems in an application domain, as in the approach of collaborative filtering, the results are hardly useful for other applications that involve structural or contextual changes. This paper presents a framework that is capable of identifying influential factors with dominating impacts on the quality of services for quantitative analysis with a fitted model and for objective prediction of services’ performance in new systems. Results from experiments demonstrate that the proposed approach is useful for service providers working on the construction and refinement of services.
Real Time Leak Isolation in Pipelines Based on a Time Delay Neural Network

In this paper, the one leak isolation problem in a water pipeline is tackled using a Time Delay Neural Network. This scheme comes as an alternative to achieve better computing performance since the classical model-based methods usually have high workloads due to the pipe mathematical model complexity compared with the leak dynamics speed. The Neural Network structure could have better time performance exploiting the parallel architecture of some electronics devices like an FPGA.The authors propose a scheme where, due to the difficulty in obtaining training data from a real pipeline, a mathematical model is used to generate synthetic training data. Such training data is obtained using different leak magnitudes and leak positions and it is also corrupted by random noise in order to emulate real data pipe. Finally, to show the potentiality of this method, some results are presented by using real-noisy databases coming from a pipeline prototype.Following the classical leak diagnosis hypothesis, only flow and pressure sensor at both ends of the aqueducts are used for the treatment.
Comparison of Modulation Schemes toward Coverage Area in indoor Visible Light Communication

This paper discusses about the effect of different modulation schemes on the coverage area of an indoor visible light communication. The idea of this research is based on the importance of using modulation techniques as needed. The main subject of this paper is power efficiency of each modulation referring to the coverage area. The modulation techniques used in this paper included On-Off keying Non return to zero (OOK-NRZ), On-Off Keying Return to Zero (OOK-RZ), Direct-current Biased Optical OFDM (DCO-OFDM), and Unipolar OFDM (U-OFDM). This paper presents the result of power efficiency, coverage area and Bit Error Rate performance of each modulation technique. The modulation technique producing the best performance in this paper was U-OFDM that had the highest power efficiency and the widest coverage area.
Banking Queue Waiting Time Prediction based on Predicted Service Time using Support Vector Regression

Prediction using different machine learning approaches have been applied in the last few decades in different areas and research fields. Waiting time is an undeniable fact for every queue and it is very important to develop a system that predicts its duration in real life with minimum error. In this paper we applied several machine learning algorithms and among them we chose Support Vector Regression (SVR) in a real-life Banking queue dataset that contains real-life queues of multiple Banks where we predicted waiting time for everyone in the queue. Moreover, we have compared the result of prediction using SVR with different classifications and clustering methods such as K-nearest-neighbor and K means Clustering. We have shown the feasibility of applying SVR in prediction of waiting time in banking queues of developing countries for everyone, which is applicable, and it performs well in queue analysis.
Optimization of Design Parameters of Microstrip Patch Antenna at 28 GHz and 38 GHz for 5G Applications

This paper has found out optimized value of design parameters of microstrip patch antenna (MPA) at 28 GHz and 38 GHz for 5G applications. Three design parameters namely: substrate element, substrate height and feeding technique have significant effect on antenna performance. If these are not suitably elected, the 5G requirements won't be covered. This work has found out the optimized value of substrate element, substrate height and feeding technique as design parameters for designing MPA at 28 GHz and 38 GHz which fulfill the 5G requirements. In addition, a comparative observation of antenna performance is done among the antennas which are designed based on these three design parameter values. Foam as substrate element, substrate height 0.5 mm and quarter wave transformer feeding technique have been found as the best performance provider at 28 GHz and 38 GHz frequency bands as per 5G requirement. In conclusion, Single element Antenna is designed on 28 GHz and 38 GHz using aforementioned best performance provider design parameter values.
Synthesis and Classification of Heart Sounds Using Multi-component Oscillatory Model

Analysis of heart sounds (HSs) plays a vital role in the early detection and diagnosis of cardiovascular diseases. In this paper, we propose a multi-component oscillatory model for the representation of both normal and pathological heart sound segments. A half-period sine wave is fitted between every two consecutive zero-crossing points to extract parameters for the proposed model. The segment-representation gets improved with the recursive use of multiple half-wave oscillations. The proposed method is tested and validated with the Computing in Cardiology Challenge (CinC) 2016 database, available publicly on the Physionet archive. The efficiency of the model is demonstrated for the synthesis of HS segments. The performance results of synthesis show that the multi-component oscillatory model provides a highly accurate approximation of the original HS segments. Further, the model parameters are employed for the classification of normal and abnormal HS segments. The proposed method achieves a better performance using support vector machine classifier with RBF kernel.
A Comprehensive Survey on VANET Broadcast Protocols

Now a days the emergence of wireless networks and sensors lead the emergence of Internet of Things. The Internet of Things paradigm is now under consideration for developing and improving Intelligent Transportation Systems (ITS). The intelligent transportation systems are mainly focusing on emergency message dissemination as well as general information. For this message dissemination IEEE has approved Wireless Access in Vehicular Environment (WAVE) as the standard. This WAVE supports two MAC layer protocols called IEEE 802.11p and Dedicated Short Range Communication (DSRC). For emergency message transmission, broadcasting is the generally adapted methodology. Due to rebroadcasting of incoming messages by the vehicles, a problem called broadcast storm occurs. To overcome this main issue along with other issues many protocols have been proposed by many researchers in academia and industry. In this paper a comprehensive survey of broadcasting protocols which are developed over the above said MAC protocols are given. This paper also deals with their implementation and limitations of those protocols.
Adaptive Backstepping Design for Stabilizing Synchronverter Control Topology in AC Microgrids

This paper focuses on designing an adaptive Backstepping controller for the nonlinear structure of Synchronverters used for emulating the virtual inertia in AC microgrids. Synchronverter control technique for the inverter-based generation units is a well-known method within the virtual inertia generating approaches, which is introduced briefly. Its nonlinear behaviour leads to probable instability during transients, e.g. microgrid islanding. Adaptive control methods such as Backstepping design can cope with such nonlinear systems and avoid instability. The model of a generation unit controlled by the Synchronverter technique is found and an ancillary adaptive controller is designed to stabilize the unit performance using the Backstepping method. The simulations are done in MATLAB/SIMULINK and the results show the improved performance of the Synchronverter supported by the proposed adaptive controller.
Two-Layer Scaffold Platforms for Drug Screening of Nasopharyngeal Epithelial Cells

A two-layer scaffold platform was designed for drug screening without using fluorescence staining to examine the effectiveness of the tested compounds. Nasopharyngeal epithelial (NP460) cells were used in this work. Typically, NP460 cells could not squeeze into the $10\ \mu \mathrm{m}$ narrow trenches but preferred to migrate on the top ridges. However, NP460 cells could migrate into $10\ \mu \mathrm{m}$ wide trenches after being stimulated by transforming growth factor beta-1 ($\text{TGF}-\beta 1$) as the cells became more active. This double-layer scaffold platform served as a drug screening device by tracking the number of cells migrated into narrow trenches after drug treatment to test and monitor the effectiveness of a compound in a biomimetic microenvironment.
Optoelectronic Enhancement for Piezoresistive Pressure Sensor

Pressure sensing is a critical task of microelectromechanical systems with a wide range of applications. Enhancing the performance such as sensitivity, durability, reliability, linearity and response time of pressure sensors has always been a top priority for researchers and technology developers. This paper demonstrates a new method for enhancing the performance of a piezoresistive pressure sensor. By using light illumination combined with controlling supply current, the performance of a 3C-SiC/Si heterojunction piezoresistive pressure sensor is significantly improved. The sensitivity of the pressure sensor is enhanced a few hundred thousand times under bright condition in comparison with that under dark condition. This enhancement is unprecedented for a micromachined pressure sensor. In addition, the durability, signal to noise ratio and measurement range are substantially improved.
Analysis of the Effects of Decay Coefficient and Time Resolution in SNN Backpropagation

High-performance neural networks operating at low power use spiking neural network (SNN) that are biologically closer than traditional ANN. SNN, unlike ANN, receives a series of binary-coded spike trains as input and updates the membrane potential of the neuron and generates spikes over a period of time specified by the number of spike trains. The function that generates the spike corresponding to the activation function of the ANN is not differentiable, which makes it difficult to apply the backpropagation (BP) algorithm used in the ANN. In order to overcome this problem, studies using numerical approximation of derivatives have been carried out in various ways. However, research on the decay coefficient and the number of spike trains, which are characteristic of SNN neuron, are insufficient. In this paper, we analyze the distribution of spikes and discuss how the decay coefficient characteristics of neurons and the number of spike trains affect network performance.
Capacitive Resonant System to Charge Devices with Metallic Embodiments

Even though wireless power transfer (WPT) is of current interest to researchers and industry, it still strives to become widely accepted. The main reason for this problem is the fact that WPT techniques suffer from alignment constraints. Additionally, they are either not able to transpose a metallic structure, or require multiple pairs of metallic plates aligned. This paper introduces a combination of inductive and capacitive power transfers in order to efficiently allow the charging of a receiver with a metallic embodiment. Furthermore, this new structure allows freedom of positioning the receiver on top of the transmitter. Simulations are performed to infer the system's efficiency versus frequency. Finally, it is demonstrated that the proposed technology can achieve an S21 up to −0.87 dB at 6.78 MHz.