Miracle-dz/UniFAR-FTUs huggingface dataset:
Small-Signal Analysis of a Hybrid Microgrid With High PV Penetration

This paper presents small signal stability analysis of a hybrid microgrid from three different aspects. First, a generalized droop control of interlinking converter (ILC) is proposed which defines voltage and frequency droops at its terminals to achieve a bidirectional, autonomous power flow between grids. The impact of the droop gains on the stability is discussed and an operational range is defined for a stable system operation. Second, contrary to previous literature which have modeled the ac and dc grids by ideal sources and converters, the ac grid in this scheme is represented as a second-order synchronous generator and the dc grid is modeled as a PV system so as to analyze the dc grid dynamics in detail. It is observed that the dc link capacitor and inductor filter can lead to large system oscillations which can compromise stability. Third, the stability of the hybrid grid is analyzed from the aspect of short circuit ratio (SCR). Both rectifier and inverter mode of operation are used to understand how stability is affected with strength of ac grid. The time-domain simulations in PSCAD are used to confirm the validity of results obtained in frequency domain.
A Model For Enhancing The Structure And Strategy In An E-Learning Environment

In the domain of E-learning, hundreds of dimensions can be taken and predictions can be made based on the browsing history of the users. Nowadays, web-based learning becomes an alternate to face to face education and E-learning becomes an effective tool in the learning process. E-Learning paves way for the learners to interact with the digitally delivered content and services. It focuses on making the learners to become more interested and efficient in their study process. This paper aims at designing strategies that will improvise the structure, assessment criteria and course completion rate in an e-learning environment. To achieve this aim, the following sub-objectives have been framed. The first objective is to provide a well-defined structure of the course whereas the second objective focuses on designing an e-learning system with specific assessment criteria. The third objective aims at achieving high completion rates for the registered students. By framing a defined structure, various assessment criteria can be fixed and calculated for a given student data set. Finally the active participation of enrolled candidates can be examined frequently. Machine Learning algorithms can be used efficiently in order to handle data in large amount.
Comparative Analysis of Power Generation Systems for Renewable Energy Using Electric Energy Storage Devices

In this paper, a comparative analysis of power generation and storage systems for renewable energy using electric energy storage devices was conducted. In this regard, three structures of power generation and storage systems based on a permanent magnet synchronous generator and accumulator battery for renewable energy were investigated and compared. Simulation models of a synchronous generator with permanent magnets and accumulator battery were developed, taking into account the influence of changes in ambient temperature and aging effects. Comparison of the systems was performed on the basic energy characteristics of the input AC-DC converters, output DC-AC converters, and the quality of the generated electric energy was assessed when changing the rotation speed of the generator and state of accumulator battery charge.
Muffin: Minimally-Buffered Zero-Delay Power-Gating Technique in On-Chip Routers

Although conventional Network-on-Chip (NoC) designs provide high bandwidth, many modern applications for many-core architectures have significant periods of low NoC utilization. Highly provisioned NoCs provide the required performance during periods of high activity; yet, large NoC designs come with high power costs. Furthermore, as technology shrinks, the contribution of static power increases. Hence, numerous NoC power-gating techniques have been proposed to alleviate the growing contribution of static power. However, the efficiency of power-gating techniques decreases due to sporadic packet arrivals across a range of injection rates. In this paper, we propose Minimally-Buffered Router Infrastructure (Muffin), which increases the number of traversals that can be made without needing to power on the routers. Empirical results on SPLASH-2 show that, compared to conventional power-gating scheme, Muffin improves static power consumption by an average of 95.4%, while improving the average packet latency by 73.7%.
Joint Reconstruction and Flat-Field Estimation using Support Estimation

Reconstructions from X-ray computed tomography scans often suffer from ring artefacts, caused by non-uniformity in the response of different detector pixels. To reduce these artefacts, flat-fields are obtained and used to normalize each subsequent scan. Any discrepancies between the acquired flat-field and the true flat-field at the time of scanning will still lead to ring artefacts. We propose a novel method in the class of joint reconstruction and estimation algorithms, in which we simultaneously calculate a reconstruction and estimate a flat-field. The proposed method models the reconstruction-estimation problem as a single system of linear equations, which can be solved using fast Krylov methods. Significant reduction of ring artefacts in both simulated and real data is shown.
Close-range Feature-based Head Motion Tracking for MRI and PET-MRI

Optical motion tracking systems are effective in measuring head motion during MRI and PET scans. However, most systems rely on tracking attached markers which can slip or move relative to the head. In this study, we aimed to validate a methodology which uses a stereo-optical camera system to track small feature patches on the forehead. This approach has the advantage that tracked features `native' to the skin can be tracked at very close range (<5cm), making it ideal for use inside an MR scanner bore. 15 volunteers were instructed to perform 6 degree of freedom head motions while simultaneously being tracked by two systems - our feature-based tracking system, and a ground-truth multi-view optical system relying on passive IR-reflective markers attached to the back of the head. Sub-millimeter agreement between the two systems was achieved when head motion was purely rigid. In the case of non-rigid movement of the skin with respect to the head, large spikes in the motion traces derived from the feature-based algorithm were observed. This experiment provides a valuable dataset to benchmark future improvements and optimizations of the feature-based tracking algorithm, such as techniques to handle non-rigid motion.
Top-N-Targets-Balanced Recommendation Based on Attentional Sequence-to-Sequence Learning

User’s behaviors and preferences alter with the temporal evolution dynamically, which leads to low performance, such as the Hit Rate and Normalized Discounted Cumulative Gain (NDCG). Understanding the dynamics of users’ behaviors and preferences can improve the performance of recommendation system. In this paper, we propose a Top-N-targets-balanced recommendation based on attentional sequence-to-sequence (Seq2Seq) learning to capture the users’ transient interests. The attentional Seq2Seq learning is introduced to largely exploit the coherence of users’ sequential behaviors and preferences in the out module of our sequential recommendation. We use two methods to get the Top-N outputs as inputs of the attentional Seq2Seq learning. The direct selection method is choosing the k items with high probability. The simulated generation method is an improvement of the network by simulating the output. We balance the loss between Top-N outputs and the sequence targets to train the neural networks, which include Long Short-Term Memory and attentional Seq2Seq learning. Besides, we modify the recommendation list generation method to further improve the performance. Experimental results demonstrate that our methods outperform existing algorithms including state-of-the-art NCF, ItemPop, ItemKNN, BPR, eAls, and SVD++ on the performance of HR and NDCG. In the best case, the NDCG of our proposal is 14.72% higher than that of NCF.
SPICE Modelling of CNTFET based Neuron Architecture for Low Power and High Speed applications

Very Large-Scale Integration (VLSI) rapidly grew when the Transistor-Transistor Logic (TTL) has much higher power consumption than the Metal-Oxide Semiconductor (MOS) family. The development in the field of electronics have been tremendous since the advent of VLSI. Due to the disadvantages like tunnelling, scaling in Metal Oxide Semiconductor Field Effect Transistors, Carbon nanotubes can be considered as the promising candidate for future devices. Carbon nanotubes are considered as the next generation Field Effect Transistors that can sustain the scalability while increasing its performance. The artificial neural networks are depicted as a structure of interconnected neurons that can figure out values from inputs and are capable of pattern recognition as well as machine learning. The prime aim of this paper is to assimilate techniques that reduce the architecture size using CNTFET technology and decrease the power consumption which leads to higher efficiency and augmented performance of the device. To satisfy the pre-requisites the circuit is designed using 32nm CNTFET technology. The proposed neuron architecture concentrates on the modification of flip flop by replacing the transmission gates with pass transistor by restructuring and reorganisation method to achieve significant delay, power and power delay product utilization. Circuit level simulation for D Flip Flop and neuron Architecture has been performed. The simulation results show that the performance of neuron architecture is improved power by 24.02% with the use of CNTFET, which means the stability is vital than that of MOSFET.
Ultra-wideband SPDT and SP8T Switches using Silicon-Glass PIN Diodes for Microwave Medical Imaging

In microwave medical imaging system, a monostatic radar approach can be used together with Gaussian pulse (with an ultra-wideband (UWB) frequency). In this system, eight antennas can be used for transmitting and receiving the Gaussian pulse signal and controlled by radio frequency (RF) switches. Therefore, this paper presents the performance analysis of three different single pole double throw (SPDT) switch topologies (Design A, B and C) using discrete silicon-glass PIN diodes. Then, the best performance of SPDT switch was built up to be a single pole eight throw (SP8T) switch configuration to connect with eight antennas. As result, Design C showed the highest isolation performance compared to others. Then, based on the SP8T switch of Design C, it resulted that the insertion loss was less than −2 dB and the return loss was more than 10 dB from 1 to 15 GHz. Meanwhile, the isolation bandwidth (at the minimum isolation of −15 dB) was from 1 to 14 GHz (with 13 GHz bandwidth).
Piezoresistive Membrane-type Surface-stress Sensor and Signal Readout Module to Support Research on Odor/Gas Sensing

The development of novel receptor materials for chemical sensors would trigger a breakthrough in the field of odor/gas sensing. To encourage more researchers to start R&Ds on this subject, useful peripheral tools and sensor devices should be available. For this purpose, piezoresistive Membrane-type Surface-stress Sensors (MSS) and a dedicated signal readout module to examine self-prepared chips in an experimental electronic nose system have been developed. These are expected to allow for the researchers to save time on the setup and to concentrate on the pure material explorations instead.
Triangular Antenna Layout Facilitates Deployability of CSI Indoor Localization Systems

Channel state information (CSI) based Wi-Fi localization can achieve admirable decimeter-level accuracy; however, such systems require labor-intensive site survey to calibrate the AP position and the antenna array orientation, which hinders practical large-scale deployment. In this paper, we reveal an interesting finding that the calibration efforts for deploying the CSI localization system can be significantly reduced by simply replacing the ordinary linear antenna layout of the AP with the non-linear layout. In particular, we first present an autonomous self-calibrating method to significantly facilitate site survey for deploying CSI localization systems. Then we propose a systematical evaluation mechanism to show the fundamental reason why linear antenna layout usually leads to serious errors and why non-linear antenna layout is better off. Finally, we build a testbed with COTS devices and conduct comprehensive experiments. Results show that triangular antenna layout can achieve 80% angle of arrival (AoA) measurement error within 9◦ for any direction in contrast to 16◦ based on linear antenna layout. Moreover, we can realize promising localization accuracy as previous works even without labor-intensive site survey, where 80% localization error is within 0.60m.
Beyond Labels: Permissiveness for Dynamic Information Flow Enforcement

Flow-sensitive labels used by dynamic enforcement mechanisms might themselves encode sensitive information, which can leak. Metalabels, employed to represent the sensitivity of labels, exhibit the same problem. This paper derives a new family of enforcers—k-Enf, for 2 ≤ k ≤ ∞—that uses label chains, where each label defines the sensitivity of its predecessor. These enforcers satisfy Block-safe Noninterference (BNI), which proscribes leaks from observing variables, label chains, and blocked executions. Theorems in this paper characterize where longer label chains can improve the permissiveness of dynamic enforcement mechanisms that satisfy BNI. These theorems depend on semantic attributes—k-precise, k-varying, and k-dependent—of such mechanisms, as well as on initialization, threat model, and lattice size.
Exploring the Relation between Monolithic 3D L1 GPU Cache Capacity and Warp Scheduling Efficiency

The warp scheduler plays an important role in the GPU for efficient utilization of hardware resources. However, the efficiency of the warp scheduler is often limited by the L1 cache (especially, L1 data cache) capacity; providing large capacity for an L1 cache is challenging due to the increased latency. In this paper, we adopt Monolithic 3D (M3D) technology to design a large capacity L1 cache for GPU performance enhancement, not deteriorating the latency. Our evaluation results show that the M3D L1 cache improves GPU performance by 2.18~2.24× on average, compared to the 2D conventional L1 cache.
Multi-Objectives Problem For Load Shedding In Micro Grid

The power management in micro grid (MG) is related to the planning of dispatchable sources such as diesel generator or storage devices due to the fluctuation of output power of renewable sources like wind and solar. The aim of the energy management for micro grid in islanded mode is planning of dispatchable source or storage devices and load shedding. This problem will be considered as a multi-objective problem in this paper such as: minimize cost for electricity production, minimize the amount of load to be shed for a day, minimize the shed load for some specific moments. These objectives are usually conflicted. The paper proposed an approach for solving the multi-objective problems, basing on the Particle Swarm Optimization algorithm (PSO) and membership function of fuzzy set. As the illustration, one medium MG is examined with different objective functions.
A Novel Method for High Frequency Battery Impedance Measurements

Electrochemical Impedance Spectroscopy (EIS) is widely used to measure the impedance of lithium-ion (Li-ion) battery cells. The EIS focuses on frequencies from millihertz to kilohertz, since the electrochemical processes do not have shorter time constants. To investigate high frequency phenomena as the electromagnetic compatibility (EMC) of an automotive traction battery, impedance measurements also in the higher megahertz range are necessary. State-of-the-art EIS measurement devices for batteries do not meet the requirements of this application, as they can cause electromagnetic wave reflections and do not provide sufficient calibration techniques. In this paper, we present a method to determine the battery impedance for a wide frequency range from 1 kHz to 300 MHz. Using a vector network analyzer, two-port scattering parameters (S-parameters) of a 18650 Li-ion cylindrical cell are measured with the shunt-through method. The resulting cell impedance is 40 Ωm at 1 kHz and increases to 40 Ω at 300 MHz mainly due to the external inductance of the cell.
Application Specific Architecture for Hardware Accelerating HOG-SVM to Achieve High Throughput on HD Frames

Computer Vision is an emerging field with diverse applications which encompasses many algorithms with heavy computations. Histogram of Oriented Gradients-Support Vector Machine (HOG-SVM) is one such versatile algorithm used for object detection and image classification despite it's heavy computation load. Processing such an algorithm in real time with adequate throughput is a challenging task for a general purpose processor. Moreover, an embedded CPU with very limited processing power could least cater such heavy processing. Therefore our research in general focuses on developing application specific architectures for hardware acceleration of computer vision algorithms. This paper presents a continuation of a series of research to hardware accelerate HOG-SVM algorithm on FPGA. In this paper we mainly present the high performance application specific architecture for hardware acceleration of HOG-SVM which was successful in achieving a high throughput of 240fps on HD frames of size 1920x1080 which is a significant improvement of performance compared to previous research. On the other-hand, both hardware utilization and power consumption are minimized. A mechanism based around Block RAM (BRAM) structures and deep pipelining are used as the key architectural techniques of achieving high performance. The proposed design was deployed on Zynq 7000 FPGA platform which contains a hardwired ARM CPU along with the programmable FPGA fabric. The accelerator is deployed on the FPGA and integrated with the ARM CPU using AXI memory interfaces. A hardware thread model and bare-metal device drivers were developed which encapsulate the behavior of the accelerator as a hardware thread to the applications running on the ARM CPU.
Influence of the Perceived Data Security, Credibility, Trust and Confidence on the Usage Frequency of Internet Services and the Provision of Security Measures

Since internet services are more and more used in the daily private and business life, greater efforts on data security, credibility, confidence and trust regarding the networks, operators, service providers and security measures need to be performed. However, internet users often prefer a better performance and a greater availability of services rather than a higher data security for internet services. To verify if credibility, trust, confidence and data security are really less important in regard to the usage and usage frequency of internet services, the named variables and relations will be analyzed with an adjusted conceptual model based on elements of the Unified Theory of Acceptance and Use of Technology 2. This paper will describe the theoretical approach of the conceptual model and the research hypotheses for the later quantitative analysis.
A 16-Bit 1-MS/s Pseudo-Differential SAR ADC With Digital Calibration and DNL Enhancement Achieving 92 dB SNDR

This paper presents a 16-bit 1 MS/s pseudo-differential Successive-Approximation-Register Analog-to-Digital Converter (SAR ADC) achieving an ENOB of 15-bit. To accommodate the pseudo-differential input, a differential DAC utilizing both monotonic and traditional switching is designed. For both dynamic and static performance improvement, three techniques are proposed. First, a foreground digital self-calibration method is described to eliminate the capacitor mismatch errors. Some of the LSBs capacitors are utilized to measure and calculate the bit weights of other capacitors. Second, a DNL enhancement technique is presented. The fractional value capacitors are used to subtract an analog voltage from the DAC before the conversion is finished, which cancels out the consequent effect when the fractional part of the digital output is discarded before final output. Third, a low-offset low-noise comparator is designed. A reset timer with DAC settling replica is proposed to make the pre-amplifier in the comparator to start to amplify the DAC summing node voltage right after the DAC has fully settled. A prototype ADC is fabricated in a 0.18- $\mu \text{m}$ 5-V CMOS process. It measures a 92.3-dB SNDR and a 107.9-dB SFDR. The DNL and INL are within ±0.3 LSB and ±0.72 LSB, respectively. The overall power consumption, drawn from the 5 V power supply, is 40 mW.
Sustainability and Fog Computing: Applications, Advantages and Challenges

Designing a sustainable society is a key concern of the United Nations’ 2030 Sustainable Development Goals. Sustainable fog computing is the most prominent solution for most problems occurring in cloud data centers, such as latency, security, carbon footprint, electricity consumption and so on. It is an extended design of cloud computing that supports horizontal computing paradigm providing cloud-like services at the edge of user premises. After emerging IoT fog computing has become the first choice of time sensitive applications due to its residing closer to the devices and sensors. In this paper we have introduced fog computing and differentiated it from cloud, furthermore, we have discussed how we can achieve sustainability through fog in several applications areas. Also, we have presented some existing challenges of fog paradigm. Moreover, we have reviewed some existing work about fog computing.
Analytical Design Procedure for Forward Wave Couplers in RGW Technology Based on Hybrid PEC/PMC Waveguide Model

In this paper, a systematic design methodology of a 0dB and a 3dB forward couplers based on the ridge gap waveguide (RGW) technology is presented. This methodology is based on exact theoretical formulations rather than any approximate or empirical equations. The procedure of the proposed design methodology is mainly to build a virtual equivalent waveguide model. This waveguide has two horizontal upper and lower perfect electric conductor (PEC) walls, while the left and the right walls are made of perfect magnetic conductors (PMC). A detailed analysis for this hybrid PEC/PMC waveguide, a common waveguide for coupling, is introduced as the starting phase for designing the RGW couplers. The equivalent RGW coupler that assures the same operation of the hybrid PEC/PMC waveguide at a specific frequency range is deduced based on detailed theoretical aspects. Moreover, a simple analyzing of transitional bends and phase shifters with accurate calculations is presented in this paper, which are the fundamental building blocks of several mmW components such as the six-port junction and the butler matrix. The possibility of tuning the coupler center frequency is introduced without the need of using any nonlinear elements. The resulting RGW couplers are implemented through well-known full wave simulator (Ansoft HFSS), with verification through prototype measurements in order to confirm the validity of the proposed methodology. A good agreement is achieved between measurement and simulation results.