Miracle-dz/UniFAR-FTUs huggingface dataset:
Pre-Corrected Tensor Train Algorithm For Current Flow Modelling in 2D Multi-Conductor Transmission Lines

Pre-corrected Tensor Train (P-TT) fast iterative method is introduced for acceleration of Method of Moments (MoM) solution of the 2D Volume Electric Field Integral Equation (V-EFIE) in magneto-quasi-static regime. The method performs voxelization of the unstructured triangle mesh in MoM discretization through projection of the basis and test functions onto the regular grid of point sources. Subsequently, the Toeplitz matrix governing point-to-point interactions is represented as multi-dimensional tensor and decomposed into the product of smaller dimensional tensors (Tensor Train (TT)). The storage of the TT carriages and vectors pertinent to P-TT requires O(log N) and O(N) memory, respectively. Evaluation of the matrix-vector product requires O(N log N) operations. Resistance and inductance of the circular wire are extracted in broad range of frequencies with proposed P-TT algorithm and compared against analytical values.
FSS Loaded High Gain Antenna Array for C-band Applications

This paper presents a 2:1 Hexagonal shaped microstrip antenna array with FSS as reflector for C-band applications. The proposed antenna has return loss bandwidth of 1.23 GHz (5.25GHz - 6.48GHz) which has applications for 5.5GHz Wimax, 5.8GHz WLAN and Wi-Fiand commercial satellite television transmission above 6GHz. The structure has beensimulated using CST Microwave Studio. High gain of 11.8dB and half power beamwidth of 32.8° has been attained by incorporating FSS as reflector below the antenna array, which also reduces the back radiation due to partial ground structure. The antenna efficiency is 97%.
Big Data Security and Privacy: A Review on Issues, Challenges and Privacy Preserving Methods

In recent years the rapid growth of Internet, IOT and Cloud Computing has led to voluminous data in almost every organization, academics and business area. Big data has rapidly developed into a hot topic that attracts extensive attention from such area around the world. Maintaining the privacy and security of Big Data is a very critical issue. The5V characteristics of big data (Volume, Variety, Velocity, Value and Veracity) alleviate the standard of security required for it. In this research paper, we have emphasized several Big Data security and privacy issues and challenges released by CSA (Cloud Security Alliance) that need to be addressed to make data processing and computing infrastructure more secure as well as possible solutions to address such challenges. This paper also gives insights on overview of big data privacy preserving K-Anonymity technique which aims to protect against leakage of individual’s identity and sensitive information before releasing the dataset during analysis. Finally, this paper overviews big data security solution application and their features provided by the top companies
Three-Dimensional Control of an Iron Ball by Flux-path Control Mechanisms Located around Magnetic Source

Three-dimensional control is achieved in a magnetic suspension system with three flux-path control mechanisms located around a permanent magnet (magnetic source). In the flux-control mechanism, a ferromagnetic control plate is placed beside the magnetic source. The attractive force acting on an iron ball (floator) can be varied by moving the control plate in the vertical direction. The suspension force has two components: vertical and lateral. Therefore, three-dimensional control of the floator can be achieved by moving three control plates individually. Such suspension is realized in the developed experimental apparatus.
A Personal Location Prediction Method Based on Individual Trajectory and Group Trajectory

With the rapid development of communication technology, a large amount of spatiotemporal trajectory data has been produced. One of the critical applications of trajectory data is location prediction that is important for urban traffic planning and location-based services. Although many methods for personal location prediction have been proposed, to the best of our knowledge, some users always have sparse historical trajectory data in practical applications, resulting in poor location prediction precision. Targeting on this challenge, we propose an Individual Trajectory-Group Trajectory (ITGT) location prediction model by utilizing the pattern of group travels. First, the model performs the stay point extraction and conducts the spatial clustering to construct the clustering link. Second, Fano’s inequality and clustering link are used to evaluate the predictability of location. Third, two variable order Markov models, named prediction by partial match (PPM) and probabilistic suffix tree (PST), are adopted to predict the clustering link. Finally, our approach is evaluated by using 608 712 points from 5000 volunteers at Shenzhen, China. The results show that: 1) when using individual trajectory, the PPM individual model is superior to the conventional N-order Markov model and PST individual model; 2) when all group trajectories are used, the PPM group model is not as accurate as the PPM individual model; and 3) when it classifies the group trajectory into different traffic zones, the PPM zone model is better than the PPM group model and the PPM individual model. The prediction precision of 1–3 order PPM zone model is 83.21%, 86.75%, and 87.35%, respectively, which introduces approximately 3% performance gains by utilizing the characters of traffic zone groups.
Modified Fractal-shaped Slotted Patch Antenna with Dipole-shaped Slotted Ground Plane with Enhanced Gain for X-band Applications

This work concentrates on the design and working analysis of a modified fractal-shaped slotted patch antenna with defected ground plane designed for X-band applications. A shorting via at the centre of the slotted fractal patch and a dipole shaped slots at the ground plane have been used in the proposed design to enhance the gain of the antenna. The maximum return loss of 22 dB has been achieved at 11.25 GHz over the frequency range of 10.58-11.37 GHz while the maximum realized gain of 16.98 dB has been obtained at 10.78 GHz. The designed antenna offers broadside radiation characteristics. The proposed antenna can be utilized for X-band applications like defense applications, satellite communication and microimaging in medical analysis for determination of radio waves.
Study on Impact of LC-Filter Parameters Under Variable Loading Conditions of Three-Phase Voltage Source Inverter

This paper studies on the impact of LC filter parameters on the load-side output of three-phase voltage source inverter (VSI) under variable loading conditions. In practice, variable active and reactive load powers have to be met up by VSI based stand-alone system. In this context, the output-side passive parameters of LC filter plays beneficial role for reducing harmonic levels at the load terminals. But, the improper choice of the LC filter parameters can restrict the range of operation of VSI under variable isolated loading conditions. Therefore, this paper focuses on the investigation of the output power limit by the designed values of LC parameters. The influencing factors, design steps of LC filter are presented in the paper to justify the obtained result. The MATLAB-SIMULINK 2014b software is used to study the above said effects.
A Novel Frequency Reconfigurable Slot Antenna using Metasurface

A frequency reconfigurable slot antenna using metasurface is presented in this paper. The proposed structure comprises of a slot antenna and a single layer of metasurface which is optimized to produce frequency reconfigurability. The metasurface consists of a meandered unit cell structure and is positioned periodically along the x-axis and y-axis. The rotation of this metasurface layer w.r. t the slot antenna produces the frequency reconfigurability. Frequency tunability from 1.9 GHz to 2.3 GHz with a wide tuning range of 19% is achieved with the proposed frequency reconfigurable metasurface (FRMS) antenna. The antenna gain varies from 4.5 dBi to 5 dBi in the frequency band of operation.
Design and Comparison of Permanent Magnet Self-Bearing Linear-Rotary Actuators

Linear-rotary actuators (LiRAs) are electric machines that can perform linear and rotary movements. They are used in many different applications, for example, for pick-and-place robots, in packaging or sorting lines, or as gearbox actuators. A linear-rotary movement can be obtained with various combinations of linear and rotary machines, whereas depending on the specifications of the underlying application the most suitable actuator arrangement has to be identified. In order to simplify the selection of the appropriate actuator configuration, this paper first gives an overview of possible realization concepts of linear-rotary actuators, which are also suitable to implement magnetic bearings (MB). Afterwards, fundamental scaling laws concerning achievable axial forces and torques of linear and rotary machines with interior and exterior rotor arrangement are derived, enabling a qualitative comparison in order to figure out the most suitable actuator concept. In this context, it is important that the derivation also considers the machine-internal heat flow and the heat dissipation to the ambient, which finally leads to a maximum current density depending on the selected topology. All findings are verified by finite element method simulations. In order to show the applicability of the derived scaling laws, a design example is discussed.
Smart Speaker: Suspicious Event Detection with Reverse Mode Speakers

Loudspeakers are transducers that convert electrical signals to sounds. However, it is well-known that in reverse mode, they can convert sounds to electrical signals. The paper studies the feasibility of designing an embedded system that detects suspicious events like gunshots or screaming by utilizing the reverse mode of loudspeakers. A proof-of-concept system was introduced, which can record the induced reverse mode signal in the inactive states of a speaker while providing the direct mode functionality in the active states. To examine the impact of the reverse mode’s distorting effects on the event detection accuracy, traditional audio event datasets were transformed into forms as they would have been recorded by speakers. Three different signal processing scenarios were introduced and evaluated by different methods and classifiers. The results suggested that in all three scenarios the reverse mode speakers could be used for event detection.
Android Malware Prediction by Permission Analysis and Data Mining

In recent years, smartphones have brought people’s lives to a new high level. Smartphone applications, or Apps, are accelerating the process with many more functions getting developed, such as browsing the Internet, making payments, taking photos and share. However, the "Apps" are bringing potential vulnerability when they access private information from the phones, and mobile security has never been so much focused on like today. In this paper, we presented a novel Android Permission based malware detection technique. We first gather a huge set of both malware and benign Apps through web clawer and develop a tool to decompile Apps to source code and manifest files automatically. Then permissions with other information are extracted for each App, making up to a raw data set. Afterward, we apply data cleaning, dimension reduction and statical analysis to the raw data set. We find that the distribution of permissions for Apps shares a difference between malware dataset and benign dataset. Finally, we take advantage of machine learning algorithms, including Logistic Regression Model, Tree Model with Ensemble techniques, Neural Network and finally an ensemble model to find patterns and more valuable information. Other models are also discussed. Extended experiments using these various machine learning models are conducted in the end. From the results, we can see that our method generates a good accuracy, F-score and overall performance of malicious App prediction.
Toward Postquantum Security for Embedded Cores

& THE USE OF firmware agents—including their use to define the functionality of embedded cores—has proliferated on computer systems of all scales, especially servers. The agents are often not visible to the operating system as they independently perform configuration, monitoring, and certain control tasks. For example, the baseboard management controller (BMC) on server platforms runs a firmware stack (e.g., OpenBMC (https://github.com/openbmc/ openbmc)), has a network port, some peripherals on external buses (e.g., I2 C’s, SPI, etc.), and storage. The BMC is effectively another full (but scaled-down) computing system on the server of which it is a component. While the BMC can directly affect the operation of a server (e.g., by controlling its power states), it does not interact with the OS. Its behavior is defined completely by its firmware. Improvements in silicon manufacturing processes have reduced the size of these cores to the point where they can be physically embedded within silicon dies of the system components (such as a CPU) on which they operate. In parallel, the volume and importance of their responsibilities have increased, beginning with power management and escalating to security operations that can affect functional safety. Given this, it is critical that they run only signed and authenticated code. One of today’s best practices to authenticate the firmware that runs embedded cores is public key cryptography (digital signatures), which relies on FIPS-140 digital signature algorithms such as RSA and EC-DSA. However, quantum computing will render these algorithms useless since factorizing integers and solving the discrete logarithm problem (i.e., the underlying security problems of RSA and EC-DSA) will be solvable in polynomial time. This implies that increasing RSA/ECC key sizes will be insufficient to defeat a quantum adversary. Prof. Michele Digital Object Identifier 10.1109/MM.2019. 2920203
Exploitting Performance Of Miso Based Non-Orthogonal Multiple Access

This paper examines non-orthogonal multiple access (NOMA) and explores the effect of multiple antenna equipped at base station to serve many users who expect to multiple access to core network. This system model using multiple input single output (MISO) contributes enhancement on the outage performance of two NOMA end-users. We first introduce a simple model of power distribution to NOMA users who use both direct link and relay link to improve quality of transmission. Inspired by NOMA strategy, we then identify signal to noise ratio to discover separated signal for each user, and exact expressions of outage probability are developed in assumption that receiver can eliminate the interference completely with successive interference cancellation. Theoretical and simulation results show that the both suggested models can achieve the remarkable performance improvement of two NOMA users.
Outage Analysis of UAV-based FSO Systems Over Log-Normal Turbulence Channels

Free-space optical (FSO)communication systems have recently attracted an ever increasing popularity for data transfer between unmanned aerial vehicles (UAVs). Although providing wide unlicensed bandwidth, the channel capacity of UAV-based FSO links is negatively affected by atmospheric turbulence-induced fading, pointing errors due to the position and orientation deviations of hovering UAVs along with interruption probability due to the joint effects of angle-of-arrival fluctuations and receiver field-of-view limitations. Due to these undesirable limitations, outage probability is commonly considered as an important metric for performance analysis in FSO links. So, in this paper, we derive the closed-form expression for outage probability of UAV-based FSO links. To confirm the accuracy of the proposed analytical results, we compare these outage rates to those provided by Monte-Carlo simulations.
Operation Mode Comparison of Three 1T2R Parallel Mechanisms Based on Geometric Constraints

this paper attempts to compare operation modes of three one translational and two rotational (1T2R) zero-torsion parallel mechanisms (PMs), 3-PSP PM, 3-RPS PM and 3-SPR PM, using dual quaternions and geometric constraints. At first, the geometric constraints of their limbs are presented based on motion characteristics. Then, constraint equations of these mechanisms are obtained according to dual quaternions in combination with geometric constraints of their limbs. The operation mode analysis of these three mechanisms is thus carried out by prime decompositions. And the kinematic interpretation of their operation modes is presented. Finally, the axodes of 3-PSP PM, 3-RPS PM and 3-SPR PM are drawn to character and compare their operation modes. The results reveal motion characteristics of these mechanisms.
Human Reliability Evaluation through Analysis of Depression Prediction based on Metabolomic Data

Data mining techniques are applied to a broad spectrum of solutions to solve problems through analysis, data acquisition, and prediction. Decision trees are most commonly used for classification and prediction. With the application of fuzzy clustering it is possible to construct a fuzzy decision tree that is more suitable for a prediction on selected data. In this article, we focus on analyzing metabolomics data. This data allows us to detect the depression that has a significant influence on human reliability. The analysis of these metabolomics shows that it is possible to predict the occurrence of depression. These results may improve the treatment and prevention of depression. Further detection of depression in critical domains can increase the precision of Human Reliability Analysis. Early detection of depression can be applied in critical domains such as police officers, firearm licenses, management positions, university students, but also in space ships of human crews.
Review of Dimension Inhomogeneity in Robotics*

Numerous robotic indices have been proposed to evaluate the robot performance and for optimal design of robots. However, due to different units in the output and input of the robotic system, most of these indices are not invariant with respect to changes in the dimensional units. In this paper, the problem of dimensional inhomogeneity in robotics is reviewed and described. The main approaches suggested in the literature for solving unit inconsistency are concluded and some details are given. Finally, it is highlighted that the task-oriented performance index should be carefully designed to be physically consistent, dimensional homogeneous, and frame invariant.
190-GHz G-Band GaN Amplifier MMICs with 40GHz of Bandwidth

We report on three state-of-the-art G-band (140–220GHz) GaN amplifier MMICs. A 4-stage common-source amplifier can provide a small-signal gain of 10dB at 190 GHz with a 3-dB bandwidth of 40GHz (156–196 GHz). A 5-stage common-source MMIC achieves up to 12dB gain at 190GHz with a 36-GHz (157–193 GHz) bandwidth. Additionally, a 2-stage amplifier using inductive degeneration shows 6.3 dB of gain at 179 GHz with a bandwidth of 12GHz (172–184 GHz). At 190 GHz, the 5-stage amplifier can deliver 14.1 dBm (279 mW/mm) of output power at the 1.8-dB gain-compression point with a corresponding power-added efficiency of 1.2%. To the best of our knowledge, these amplifiers show the highest gain above 170GHz among any reported GaN-based MMICs. This is also the first demonstration of multi-stage GaN circuits that can provide gain up to the 200-GHz mark.
Investigation of Compact Power Amplifier Cells at THz Frequencies using InGaAs mHEMT Technology

In this paper a design approach for compact power amplifier cells at frequencies around and above 300 GHz is presented, using a 35nm InGaAs mHEMT technology. Up to 8-finger common-source (CS) and cascode devices are developed based on 2-finger multiport models without feeding structures. Two power amplifier MMICs are presented with more than 15dB measured small-signal gain between 290 –335 GHz. 6.8–8.6-dBm output power is reported for the frequency range of 280–320 GHz, which is state-of-the-art for InGaAs based mHEMT technologies at these frequencies. Due to the compact CS and cascode cells, the required width of the PA core is significantly reduced, achieving high output power levels per required chip width and enabling further parallelization.
Digital Phase Locked Loops for Radio Frequency Synthesis

The demands for an ever higher data rate and a more varied functionality at minimal cost and power consumption have been the driving force behind most innovations in wireless communication systems. Intensive efforts have been made to develop Radio Frequency (RF) Integrated Circuits (ICs) and systems using low-cost Complementary Metal Oxide Semiconductor (CMOS) processes. In radio transceivers for wireless systems, the commonly used frequency synthesizer based on a Phase Locked Loop (PLL) is a crucial building block. In fact, the frequency synthesizer is responsible for the generation of high-purity RF signals utilized to shift up and down in frequency the information content of the transmission, and, as such, determines the performance of the whole transceiver to a large extent, while it is responsible for a large portion of the power consumed and the area occupied by the transceiver.A state-of-the-art PLL must meet stringent requirements on signal purity, while dissipating increasingly lower power to lengthen battery lifetime and being capable of operating at the very low supply voltages required by modern CMOS processes. Furthermore, such a PLL should occupy a small area and coexist with very complex digital systems, which are responsible for the generation of extensive switching noise.With the extraordinary pace of CMOS technology scaling and the attending increase in integration density, conventional analog designs are giving way to digital counterparts, which much better exploit the new silicon ecosystems. The foremost example of this momentous trend is probably the PLL, where the Digital Phase Locked Loop (DPLL) can exploit all the advantages, in terms ofprogrammability, reconfigurability, and adoption of advanced adaptive digital algorithms for the correction of PLL non-idealities, that are beyond the reach of the analog PLL.In this dissertation, several IC design techniques are demonstrated, which improve the DPLL in terms of both overall architecture and individual subblocks. One DPLL has been designed and thoroughly simulated, while one Digitally Controlled Oscillator (DCO) and another DPLL have been designed, simulated, fabricated, and tested, obtaining excellent measured performance (Less)
Anticipatory Approaches for Resource Allocation in LiFi Networks

As a promising solution for future indoor access networks, resource allocation in Visible light communication or LiFi networks is subject to lots of researches. An interesting approach for network algorithm design is to use some knowledge about the future of the network. With this regards, the anticipatory design may improve the performance of the system in terms of delay and throughput. This paper reviews the state-of-the-art anticipatory algorithms proposed in the literature, given different prediction capabilities. The key element that all of these algorithms share is to find an event that correlates the current actions to the performance of the network in the future. Apart from the amount of possible prediction, two main approaches have been proposed for problem formulation. The optimal anticipatory resource allocation problem can be formulated in terms of a T-step look-ahead optimization problem. This approach requires more accurate information about the future of the network and yields higher performance improvements. The objective function can be adjusted to achieve high fairness and throughput or low latency in the system. On the other hand, the resource allocation algorithm can be expressed as a matching problem on a bipartite graph. The partial knowledge of the future can be added to the problem using proper heuristic preference functions.