Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Load Analysis During Test Mode for the Network-on-Chip Reused Test Access Mechanisms

On-chip interconnects have been reused for transporting test data to and from different modules of a chip. Similarly, several schemes have been presented to reuse network-on-chip (NoC) as test access mechanism (TAM). There is different load on the on-chip network by different test schemes those result in different energy consumption. Such test schemes are classified in this work, based on the number of input/output access points (IO-APs), number of time slots, and network protocol compliance/defiance. Moreover, the network load is analyzed for different test schemes in term of flit injection rate. The analysis showed that a development in NoC fabric better utilizes the network resources during test operation and reduces network load.
Extended Constant-Q Cepstral Coefficients for Detection of Spoofing Attacks

The constant-Q cepstral coefficients (CQCC) feature is one of the most effective feature in the field of spoof speech detection. The extraction of this feature involves constant-Q transform that captures long range information from the signal. It is followed by uniform resampling of the octave power spectrum to have linear power spectrum from which the CQCC features are obtained. However, we hypothesize that the information obtained from octave power spectrum is complementary with that captured by the linear spectrum. In this regard, we propose to combine the coefficients generated using both linear and octave power spectrum. The combined feature is referred to as extended CQCC (eCQCC) which is hypothesized to have better discriminative information for detection of spoof attacks. The studies for spoof detection are conducted on both synthetic voice and replay based spoofing attacks using ASVspoof 2015 and ASVspoof 2017 Version 2.0 database, respectively. The studies confirm that the proposed eCQCC feature consistently outperforms the baseline CQCC feature in all tasks.
Generation of Correct Word Sequences from Multiple Outputs of a Conventional Automatic Speech Recognizer for Voice-Activated Information Appliances

In information appliances based on speech recognition, users’ spoken queries are converted into text queries using automatic speech recognition (ASR) engines. If the top-1 results of the ASR engines are incorrect, these errors are propagated to the following natural language processing steps. To alleviate this error propagation problem, we propose a post-processing model for revising ASR errors. Based on a sequence-to-sequence neural network, the proposed model generates a correct sentence from multiple candidate sentences returned by an ASR engine. The proposed model does not require any external resources or feature engineering effort, because it uses only syllables as input features. In our experiments with a Korean spoken chatting and FAQ corpus, the proposed model outperformed the previous models.
Electrical Characteristics of Samarium Oxynitride Thin Film on Silicon-Based MOS Device

In this work, metal-oxide-semiconductor (MOS) properties of oxynitrided Sm film on Si in nitrous oxide environment were investigated and trap-assisted tunneling mechanism through the oxide were quantitatively analysed. The effects of oxynitridation temperatures on the capacitance-voltage and leakage current density-electrical field behaviours were reported. It was revealed that sample oxynitrided at $700^{\mathrm {o}}\mathrm {C}$ demonstrated dielectric contant of 13 and the highest electrical breakdown field of 4 MV/cm at the lowest leakage current density of $10^{-7} \mathrm {A}/\mathrm {c}\mathrm {m}^{2}$. This is attributed to the thinnest effective interfacial layers between the oxynitride and the semiconductor, with the lowest effective oxide charge, interface trap density, and total interface trap density. The Fowler-Nordheim tunneling mechanism has been investigated for all samples and the highest value of barrier height extracted between the conduction band edges of oxide and semiconductor was 6.33 eV. This type of oxide could be act as an alternative gate dielectric on Si-based MOS device.
Data Analytics in Text Messages: A Mobile Network Operator Case Study

This paper explores the application of different data mining and machine learning algorithms to propose an effective technique to filter out spam SMSs. Due to high competitive nature of MNO business; filtering spam SMSs will have a great impact on the protection of business and profit making. This is mostly because subscribers refuse to use the services of MNOs that are not vigilant about spam SMSs. Based on the CRISP-DM method which is an open standard process model for data analytics projects, machine learning algorithms and data preparation methods have been conducted on a MNO unstructured dataset to transform characters, delete stop words, extract word stems, roots, N-Grams, and classification. Next, numerical Vector Space Models were created utilizing all four types of word vector creation methods. After producing test and train models with machine learning algorithms; accuracy and error rate, recall, precision and the area under curve for each classification algorithm has been measured. Finally, the Bagging algorithm by implementing Binary Term Occurrence vector space creation method showed the highest efficiency rate which can have the highest application in the big data ecosystem of the industry for spam filtering.
Smokestack: Thwarting DOP Attacks with Runtime Stack Layout Randomization

Memory corruption vulnerabilities in type-unsafe languages are often exploited to perform a control-flow hijacking attack, in which an attacker uses vulnerabilities to corrupt control data in the program to eventually gain control over the execution of the program. However, widespread adoption of control-flow attack defenses such as Control-flow Integrity (CFI) has led attackers to exploit memory errors to corrupt non-control data that can not be detected by these defenses. Non-control data attacks can be used to corrupt security critical data or leak sensitive information. Moreover, recent attacks such as data-oriented programming (DOP) have generalized non-control data attacks to achieve Turing-complete computation capabilities within the programmer-specified control-flow graph, leaving previously proposed control-flow protections unable to stop these attacks.In this paper, we present a stack-layout randomization scheme that can effectively thwart DOP attacks. Our approach, called Smokestack, provides each function invocation with a randomly permuted ordering of the local stack organization. In addition, we utilize true-random value sources combined with disclosure-resistant pseudo-random number generation to ensure that an adversary cannot anticipate a function–s invocation permutation of automatic variables. Our evaluation on SPEC benchmarks and various real-world applications shows that Smokestack can stop DOP attacks with minimal overhead.
Using neural networks to enhance the quality of ROIs for video based remote heart rate measurement from human faces

Classical approaches for measurement of a patients heart rate (HR) inherent several disadvantages like discomfort or irritation of the skin. Therefore, non-invasive and non-obtrusive methods, like video based ones become more and more popular. A majority of the methods described in the past, use video data of human faces. These methods recon minimal changes, invisible for the human eye, in the color spectrum of a persons face to measure the heart activity. It is obvious, that measuring the HR from a persons video data is not a trivial – though a very challenging – task, as seen in the last years. Quality of the results can be improved in multiple ways. Most of the presented approaches using filter methods like independent component analysis (ICA), Blind source separation (BSS) or many others to improve the given data. Because all of these techniques intervene at a relative late point in the algorithm, in this paper another approach is described. By detecting and enhancing the region of interest (ROI) from video data made before, it is possible to improve quality of the given data for the later use in any algorithm. A huge acceleration in processing time is realized. To achieve this the here proposed method using neural networks to detect and improve the ROI from given video data is used. By the later use of ICA the here proposed algorithm is able to measure HR with a very high accuracy. The combination of this two techniques, is able to deal with various situations in different lighting conditions and patients activation level, therefore a better accuracy and an improvement in runtime towards more realistic applications was realized.
Energy-Efficient Downlink Transceiver for Massive Generalized Spatial Modulation MIMO

In this paper, we analyze downlink single-user massive MIMO systems which are equipped with generalized spatial modulation (GSM) over frequency-flat channels. This system activates fewer transmit antennas (in all of available transmit antennas at BS) in each channel use. consequently, power consumption due to RF chains is significantly reduced. In this system, information bits are conveyed through transmit antenna indices in addition to modulation symbols (e.g M-PSK). The sub-optimum receivers for this system, in downlink, suffer from a high bit error probability respect to an optimum ML detector, because of stage-wised detection of activated antenna indices and signal modulation symbols. In this thesis, we first investigate the optimum ML detector and sub-optimum. Then we propose a hybrid detector, which can achieve a near-ML performance, with a much lower complexity. Finally, we extract an union bound for average bit error probability for proposed detector. Also we show that GSM-MIMO outperforms conventional MIMO in point of view of energy efficiency.
22.1 A 769μW Battery-Powered Single-Chip SoC With BLE for Multi-Modal Vital Sign Health Patches

Continuous vital-sign monitoring is of paramount importance in remote heath monitoring or rehabilitation environments for chronic diseases. Medical-grade wireless and wearable bio-sensor systems that can be used at home offer a much more attractive solution than hospital-based monitoring systems. We report an all-in-one battery-powered SoC designed for low-cost single-use health patches (Fig. 22.1.1), allowing continuous monitoring in a home setting to improve patient comfort and reduce cost of care by, e.g., reducing hospital stays. In addition to medical-grade signal quality, low power consumption is key in such a health patch system, to enable a comfortable form factor with miniature battery size and prolong the operational lifetime to at least several weeks.
The improving of biometric image quality compression using Wavelet and SPIHT coding

The important objective of image compression is reducing the quantity of data required by the applying an image encoding. This reduction is needed for transmission or database storage. Our used is based on the Wavelet transform in image compression. It offers ascend to numerous applications in different fields, for example, geophysics, astronomy, media communications, imaging, and video coding. This contribution presents an application in the compression of the biometric image based on the second-generation wavelet with lifting and combined with SPIHT progressive encoder. To study the reliability and performance of these algorithms, we apply them on iris image and use the image quality assessment with full reference (PSNR, MSSIM, VIF) and without reference (NIQE, BLIINDS). The obtained results are very interestingly and encouraging.
Inter-area Oscillation Control Based on Eigensystem Realization Approach

The continuous growth and development of society have a direct correlation to the amount of energy required to satisfy its demand. As consequence, more interconnections of existing electrical networks are required, increasing the complexity on its operation. Thus, larger power systems are prone to experience inter-area oscillations, which are triggered by generators oscillating against each other from different geographic locations. Whether these so called inter-area oscillations are undamped, they could eventually lead to a system collapse. In this work, a Linear Quadratic Gaussian (LQG) control approach to damp inter-area oscillations out, which is coupled with a dynamic eigensystem realization algorithm (ERA), is proposed. Although these two concepts are well documented on the literature, the novelty presented here is its combination resulting on a fast and effective damping controller. The proposed architecture is implemented as a digital Power System Stabilizer (PSS) using the combination of the professional softwares DigSilent PowerFactory and Matlab. The presented controller is validated trough dynamic system simulations on the IEEE benchmark New England model. Additionally, a tutorial to implement the proposed controller is also presented.
Effect of rise time on nanosecond pulsed surface dielectric barrier discharge actuator

Nanosecond pulsed surface dielectric barrier discharge (ns-SDBD) actuator is a novel technology for active flow control due to its high control capability and low power consumption. The electrical, and aerodynamic, characteristics of ns-SDBD actuator with different rise times are investigated by electrical measurement system, Schlieren optical system, and particle image velocimetry (PIV) system. Experimental results show that the short rise time leads to a high current amplitude and a diffuse-like plasma layer. The deposited energy reaches its maximum (9.26 mJ) at a rise time of 50 ns, and then declines, finally, slight changes occur when the rise time is increased from 150 ns to 500 ns. Furthermore, a circular arc wave and a plane wave are produced due to the localized heating. The intensity of the circular arc wave increases when the rise time decreases and the propagation distance of induced pressure waves in the vertical direction increases in a quasi-linear manner. In addition, due to the greater ability to transmit output energy to the surroundings, and the stronger tangential acceleration ability in the case of a short rise time, the area of action for the starting vortex is larger when rise time decreases and two vortexes are formed, which is conducive to mixing with the airflow and improving flow control capability.
A Recommender Systems Based on Similarity Networks: MovieLens Case Study

Recommender systems help consumers to have proper choices regarding personal preferences. Well-known recommender approaches generally benefit from profile similarity, items ratings, behavioral profile or other Hybrid filtering techniques. One of the important drawbacks of previous works is a lack of understanding similarity between users’ opinion and items’ taste beyond considering feature based similarity measure. In this paper, a novel hybrid recommender system proposed by applying network science techniques to overcome those shortages. We build weighted networks corresponding to users’ opinion and items taste for tagging their related groups in order to measure similarity weights between groups of users and items. In the next step, users and items are clustered to similar groups based on individual features. Linear combination of weights generated from the system is used to predict rates for recommended items to users. Experimental results on MovieLens datasets show that the proposed approach improves recommendation performance and agility considerably.
On the implementation of HEVC decoders with high parallelization degree with OpenMP

HEVC is nowadays the de facto video coding standard. In this work, the OpenHEVC open source software has been modified in order to enlarge its interoperability by using OpenMP instead of POSIX threads. This work presents a new proposal on how to handle the parallelization during the decoding process. This solution outperforms the POSIX-based one by at least a 10%, while a higher interoperability degree is provided.
An analytical method for accelerating calculations of the probability of power flows exceeding the tie-lines capacity

The paper presents a new approach for solving a part of adequacy problem- calculating the probability of power flows exceeding the tie-lines capacity The proposed method is based on Lagrange multipliers method applied to random values. Test results have shown a good accuracy of the proposed approach in case of using Monte Carlo simulation technique as a benchmark. The paper points out that the proposed method could significantly reduce the computation burden of Monte Carlo simulation technique and can be used in the solving power system development planning problem.
28.5 Non-Magnetic 60GHz SOI CMOS Circulator Based on Loss/Dispersion-Engineered Switched Bandpass Filters

There has been significant recent research on non-magnetic non-reciprocal components at RF and mm-waves, such as circulators and isolators, based on spatio-temporal modulation [1-3]. Circulators enable simultaneous transmit and receive (STAR) on a shared antenna for applications such as full-duplex wireless communication and FMCW radar. While there has been exciting initial progress, existing architectures do not scale well to mm-waves, whether they are based on switch-based conductivity modulation [1, 2]or varactor-based permittivity modulation [3]. Loss levels increase due to losses in the switches or varactors, isolation is degraded due to reflections produced by parasitics, and power consumption is high due to the relatively high modulation frequencies required. In this work, we present a non-magnetic CMOS 60GHz circulator based on spatiotemporal conductivity modulation (STCM) across a loss/dispersion-engineered bandpass filter. This new architecture improves the insertion loss, isolation, power consumption, and spurious response compared to prior art. The 60GHz circulator achieves 3.6dB/3.1dB insertion loss for TX-to-ANT/ANT-to-RX paths, respectively, TX-to-RX isolation $> 40$dB over 1.3GHz, 3.2dB of ANT-to-RX NF, $> +19.5$dBm TX-to-ANT/ANT-to-RX IP1dBS and spurious tones lower than -30dBc at both ANT and RX ports at a power consumption of 41mW from 1.2V.
Eight-Band Antenna for Full-Screen Metal Frame LTE Mobile Phones

This paper presents an eight-band antenna for full-screen metal frame LTE mobile phones with a size of 142 mm <inline-formula> <tex-math notation="LaTeX">$\times79$ </tex-math></inline-formula> mm <inline-formula> <tex-math notation="LaTeX">$\times7.5$ </tex-math></inline-formula> mm. The proposed antenna mainly consists of two monopole branches, a match circuit, and two ground branches. The two monopole branches and the match circuit are used to cover the lower band (698–960 MHz) and part of the higher band (1710–2690 MHz). One of the two ground branches is used to cover the other part of the higher band, and the other is mainly used to make the lower band matched. The merit of the proposed antenna is that eight bands can be realized under the conditions of an only 2 mm ground clearance and a metal frame; it is very suitable for full-screen metal frame mobile phones. A prototype is manufactured and measured. The measured −6 dB impedance bandwidths are 300 MHz (665–965 MHz) at the lower band and 1190 MHz (1610–2800 MHz) at the higher band. The LTE700, GSM850, GSM900, DCS, PCS, UMTS, LTE2300, and LTE2500 bands are covered. The measured efficiency is bigger than 42%, so it is practical for mobile phone applications.
A SiC BJT-Based Negative Resistance Oscillator for High-Temperature Applications

This brief presents a 59.5 MHz negative resistance oscillator for high-temperature operation. The oscillator employs an in-house 4H-silicon carbide BJT, integrated with the required circuit passives on a low-temperature co-fired ceramic substrate. Measurements show that the oscillator operates from room temperature up to 400 °C. The oscillator delivers an output power of 11.2 dBm into a 50 <inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> load at 25 °C, which decreases to 8.4 dBm at 400 °C. The oscillation frequency varies by 3.3% in the entire temperature range. The oscillator is biased with a collector current of 35 mA from a 12-V supply and has a maximum dc power consumption of 431 mW.
Position Estimation of Moving Objects: Practical Provable Approximation

We consider the problem of matching a pair of point sets, each consists of <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> clusters, where each cluster in the first set is arbitrarily translated with additional noise, resulting in a cluster of the second point set. The goal is to compute <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> translations and a matching that minimizes the sum of squared distances between corresponding pairs of points. This is a fundamental problem for tracking systems (e.g., OptiTrack or Vicon) where the user registers <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> objects (rigid bodies) by attaching a set of markers to each object. Based on the position of these markers in real time, the system estimates the position of the moving objects by simultaneously clustering, matching, and transforming the <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> observed markers to the <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> objects. Similarly, an autonomous robot equipped with a camera may estimate its position by tracking <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> visual features from <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> recognized objects. The result can be used as a seeding clustering for existing algorithms, e.g., to compute the optimal rotation on each cluster. We suggest the first provable algorithm for solving this point matching problem. Unlike common heuristics, it yields a constant factor approximation for the <italic>global optimum</italic> in expected <inline-formula><tex-math notation="LaTeX">$O(n^2\log n)$</tex-math></inline-formula> time. We validate our theoretical results with experimental results using low cost (<inline-formula><tex-math notation="LaTeX">$< \$30$</tex-math></inline-formula>) “toy” quadcopters that are safe and lawful for indoor navigation due to their <inline-formula><tex-math notation="LaTeX">$<200$</tex-math></inline-formula> g weight. Comparisons to existing algorithms and commercial system are provided, together with open source code and a demonstration video.