Miracle-dz/UniFAR-FTUs huggingface dataset:
Security/Timing-Aware Design Space Exploration of CAN FD for Automotive Cyber-Physical Systems

The controller area network with flexible data-rate (CAN FD) is the new generation of the CAN technology to meet the daily increasing bandwidth requirement for automotive cyber-physical systems (ACPS). However, ACPS is a security-critical system, an efficient security/timing-aware design space exploration (DSE) method is required to fully utilize CAN FD's high data phase data rate. In this paper, we propose an AUTOSAR-compliant system model that integrates both timing and security constraint, an integrated mixed-integer linear programming formulation (i-MILP) for the optimal DSE of CAN FD, and a divide-and-conquer approach to the i-MILP (dc-MILP) to address its timing complexity problem. The experiment results show that dc-MILP scales well for industrial-size systems and saves 1.94%–4.76% bandwidth utilization and guarantees the schedulability for more signal sets by comparing with the state-of-the-art algorithm.
Multibeam Digital Array Receiver Using a 16-Point Multiplierless DFT Approximation

An <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>-element array with receivers subject to an <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>-point spatial fast Fourier transform (FFT) leads to <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> directionally orthogonal radio frequency (RF) beams. FFTs are fast algorithms for computing the <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>-point discrete Fourier transform (DFT) at reduced complexity. The brute-force computation of a DFT requires <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(N^{2})$ </tex-math></inline-formula> multiplications while an FFT provides the same computation at <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(N \log N)$ </tex-math></inline-formula> multiplications. The digital chip area and power consumption of the DFT computation are still dominated by the multipliers required by the FFT used. In this paper, an approximation to the 16-point DFT is proposed which maintains mathematical properties close to the ideal 16-point DFT to obtain 16 RF beams by computing an approximate spatial DFT in every clock cycle at significantly lower area and power in the digital realization. The proposed approximation can be implemented using FFT-like fast algorithms that are multiplierless, thereby further reducing the digital chip area and power consumption associated with multiplication in a conventional FFT approach to zero. A 16-beam beamformer employing a 16-element linear array of patch antennas, direct-conversion receivers, and a Xilinx Virtex-6 field-programmable gate array-based real-time digital back-end clocked at 240 MHz are described as an example realization of 16 complex-valued (IQ) receive-mode RF beams, centered at 2.4 GHz with 120 MHz of bandwidth per beam.
Miniaturized Frequency-Selective Rasorber With a Wide Transmission Band Using Circular Spiral Resonator

This paper presents a miniaturized frequency-selective rasorber (FSR) that has a wide transmission band with low insertion loss and a wide absorption band below the transmission band. The FSR is composed of a resistive sheet and a bandpass frequency-selective surface (FSS). The unit cell of the resistive sheet is a resistor-loaded hexagonal metallic loop, each side of which is inserted with a circular spiral resonator (CSR) in the center. The CSR is equivalent to a parallel LC circuit that has a high inductance and low parasitic capacitance. At a high frequency of 10 GHz, the CSR resonates to be infinite impedance, around which a 0.5 dB transmission band of 8.68–11.34 GHz is produced. The bandpass FSS is a triple-layer FSS in which two layers of identical hexagonal patches are coupled through a layer of hexagonal aperture; it has a fast rolloff 0.5 dB transmission band of 8.2–11.33 GHz, which almost coincides with that of the resistive sheet. The 1 dB transmission band of the FSR by placing the resistive sheet on the bandpass FSS is 8.3–11.07 GHz. At low frequency, the FSR performs as an absorber, and the 10 dB absorption band is 2.4–7.1 GHz. In addition, due to its tiny physical sizes of only $1.2\,\,\text {mm}\times 1.6$ mm, the CSR can be viewed as a lumped element circuit with a high inductance, in which the parallel resonance is almost independent to the incident angle. The transmission performance of the FSR has a good independence of polarizations and incident angles. A prototype of the proposed FSR is fabricated and measured to validate the design.
Multivector Sparse Representation for Multispectral Images Using Geometric Algebra

Multispectral images can provide more faithful representations for real scenes than the traditional images and improve the performance of image restoration tasks. In this paper, we propose a novel multivector sparse representation model for multispectral images using geometric algebra (GA), with the truth that GA is now well used in image processing and it gives a formidable way to represent multispectral images. The proposed model represents a multispectral image as a GA multivector by fully considering the spatial and spectral information, where a GA dictionary learning algorithm is presented using the K-GA-singular value decomposition (GASVD) (generalized K-means clustering for GASVD) method. Consequently, with the complete consideration of the relationship between spectral channels in multispectral images, artifacts and blurring effects can be successfully avoided. The experimental results demonstrate that the proposed sparse model surpasses the existing methods for multispectral images reconstruction and denoising tasks by capturing correlations between spectral channels thoroughly and shows its usefulness and effectiveness for multispectral images processing.
Empty SIW Technologies: A Major Step Toward Realizing Low-Cost and Low-Loss Microwave Circuits

Substrate-integrated circuits (SICs) [1] have attracted much attention in the last several years because of their great potential. The first implementation of the concept can be found in [2] as a feeding mechanism for a slot array antenna. Deslandes and Wu [3], [4] used the term substrate-integrated waveguide (SIW) to define this waveguide integrated in a substrate where the lateral walls are synthesized with metallized via holes, and the upper and lower walls are the top and bottom metallization of the substrate.
Appearance of Vacuum Arcs in Axial Magnetic Field and Butt Contacts at Intermediate Frequencies

Intermediate-frequency power technology is widely used in aircraft power-supply systems. This paper studies the appearance and motion of vacuum plasmas in an axial magnetic field (AMF) and butt contacts at 360–800 Hz. Under the influence of an AMF, electrons travel in a cylindrical spiral, which is advantageous for maintaining arc diffusion. The experimental results show that when the contact separation was 3 mm, the vacuum arcs were uniformly distributed and diffused in the AMF contacts. We found that the maximum magnetic pinch pressure in the arc column was approximately <inline-formula> <tex-math notation="LaTeX">$10^{4}$ </tex-math></inline-formula> Pa. However, in butt contacts, the arc was intense and was clearly constricted. The order of magnitudes of the magnetic pinch pressure in the center reached <inline-formula> <tex-math notation="LaTeX">$10^{5}$ </tex-math></inline-formula> Pa at the minimum radius of the arc column around the current peak, which formed a higher pressure gradient that caused the plasma and metal vapor to flow to the lower pressure region and form a plasma jet.
The Eeffects of Anode Foil Transmission Ratio on the Performance of Vircator

Virtual cathode oscillator (Vircator) is an important high power microwave (HPM) source because of its simple structure and no magnetic field is required to maintain its operation. Cathode and anode are the two most important components in vircator. The anode transmission ratio decides the electron number that can cross over to the other side to form vircator oscillation and reflects the late electrons which also contribute to HPM output. In this article we investigate the effects of anode transmission ratio in a X-band vircator with three particle-in-cell (PIC) simulations of 30%, 50%, and 70% anode transmission ratio, and found higher anode transmission ratio leads higher HPM output, less anode collision power loss, and slightly higher drift tube collision power loss, but high anode transmission ratio grid or foil are more difficult to manufacture.
Splashing Characteristics of Microparticles From Electrode Erosion for Copper, Molybdenum, and Tungsten-Copper

Microparticles from electrode erosion would lead field distortion, microdischarge, or impact damage, which are convinced to be mainly responsible for degradation of insulation performance in switches. To investigate the splashing characteristics of microparticles from electrode erosion, this paper performs the discharge experiments between two cylinder electrodes, made of copper, molybdenum, or tungsten-copper. A statistical method based on laser confocal microscopy is introduced to visualize the distribution of microparticles on the electrode surface. Experimental results indicate that the number of microparticles increases and the acceleration tendency gets mild as the discharge shots accumulate. The Cu surface would lead more production of the $> 2~\mu \text{m}$ microparticles than other two materials after hundreds of shots, which would provide an explanation for its relative poor reliability and insulation performance. The electrode surface has formed two distinct zones for distribution of these microparticles: inner zone and outer zone after hundreds of discharge shots. Estimation of inner zone radius and splashing angles of microparticles indicates that the larger the microparticles are, the smaller the angle they would be splashed out with. Finally, the evolution of arc column in the first quarter discharge cycle is captured by a high-speed camera and its relation with the concentration of microparticles is discussed.
Hypoxic cancer–associated fibroblasts increase NCBP2-AS2/HIAR to promote endothelial sprouting through enhanced VEGF signaling

Analysis of the cancer-associated fibroblast secretome identifies an angiogenesis-promoting factor. The secret(ing) life of the tumor stroma The hypoxia that develops in solid tumors leads to the formation of a dysfunctional vasculature that enables cancer cell survival and also prevents efficient chemotherapeutic penetration. Cancer-associated fibroblasts (CAFs) in the tumor stroma release important angiogenic signals; however, the proteins secreted by these cells have generally been characterized at the genome level. Kugeratski et al. analyzed the proteome and secretome of CAFs and found that hypoxia altered the secretome of these cells. The authors identified a previously uncharacterized protein that they renamed HIAR. HIAR was increased in abundance in hypoxic CAFs, promoted the release of the pro-angiogenic factor VEGF from CAFs, and induced VEGF-dependent signaling in endothelial cells. These results provide an overview of the CAF secretome at the protein level and a new potential target for anti-angiogenic therapy. Intratumoral hypoxia causes the formation of dysfunctional blood vessels, which contribute to tumor metastasis and reduce the efficacy of therapeutic treatments. Blood vessels are embedded in the tumor stroma of which cancer-associated fibroblasts (CAFs) constitute a prominent cellular component. We found that hypoxic human mammary CAFs promoted angiogenesis in CAF-endothelial cell cocultures in vitro. Mass spectrometry–based proteomic analysis of the CAF secretome unraveled that hypoxic CAFs contributed to blood vessel abnormalities by altering their secretion of various pro- and anti-angiogenic factors. Hypoxia induced pronounced remodeling of the CAF proteome, including proteins that have not been previously related to this process. Among those, the uncharacterized protein NCBP2-AS2 that we renamed HIAR (hypoxia-induced angiogenesis regulator) was the protein most increased in abundance in hypoxic CAFs. Silencing of HIAR abrogated the pro-angiogenic and pro-migratory function of hypoxic CAFs by decreasing secretion of the pro-angiogenic factor VEGFA and consequently reducing VEGF/VEGFR downstream signaling in the endothelial cells. Our study has identified a regulator of angiogenesis and provides a map of hypoxia-induced molecular alterations in mammary CAFs.
Branched-chain amino acids in disease

Are BCAAs a biomarker, causal agent, or both in cardiometabolic disease? Human proteins are assembled from 20 amino acids, nine of which are considered “essential” because they cannot be synthesized from other metabolites in the human body. Among these are the three branched-chain amino acids (BCAAs): leucine (Leu), isoleucine (Ile), and valine (Val), so named because of their branched rather than linear aliphatic side chains. The food sources most enriched in BCAAs are meat, fish, dairy products, and eggs. BCAAs have been studied for decades as agents for enhancing muscle protein synthesis and mass during exercise training, in syndromes of cachexia (muscle wasting), and in aging. In this context, Leu is known to activate the anabolic signaling molecule mTORC1 (mammalian target of rapamycin complex 1), as well as other factors involved in protein synthesis.
Clinical implications of tumor-intrinsic mechanisms regulating PD-L1

Genetic changes modulate antitumor immune responses through the PD-1/PD-L1 axis, which should be considered when designing combinatory drug regimens. Treatment with immune checkpoint inhibitors targeting programmed death receptor-1 (PD-1) or programmed death ligand-1 (PD-L1) is effective in many cancer types. Tumors harboring specific mutations modulate antitumor immune responses through the PD-1/PD-L1 axis, and this should be taken into account when designing rational combinatory treatments.
Security in the Cloud: an anomaly-based detection framework for the insider threats. (Sécurité dans le cloud: framework de détection de menaces internes basé sur l'analyse d'anomalies)

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Security in the Cloud : an anomaly-based detection framework for the insider threats Pamela Carvallo
Majority problems in distributed systems and clustering in structured graphs

This thesis focuses on the study of various algorithms for Distributed Computing and Machine Learning research areas. More precisely, the work within contains research into various communication protocols in different settings of Distributed Computing, accompanied by relevant analysis on protocol performance in time and space. These protocols are designed to operate in analogous environments using different models for communication, primarily population protocol and random walk variants. In our settings we aim to use as minimal memory as possible, achieving light weight protocols that are powerful in their capabilities and randomized as well as deterministic in nature. We also propose a novel technique of verification which enables multi-step protocols to work in synergy. These protocols generally never terminate, but converge and are difficult to disseminate results throughout the network to be used in dependent processes. With the verification technique proposed, protocols can become adaptive and stacked into a chain of dependent processes. We also provide experimental analysis of a subarea of Machine Learning, unsupervised clustering algorithms. Gaining inspiration from the agglomerative nature and techniques defined in classical hierarchical clustering as well as the Phylogenetic tree building methods, we provide a comprehensive study and evaluation of new method to agglomeratively combine `similar' data into clusters based on the general consensus of taxonomy and evaluation of clustering mechanisms.
A computational model of visual attention

Visual attention is a process by which the Human Visual System (HVS) selects most important information from a scene. Visual attention models are computational or mathematical models developed to predict this information. The performance of the state-of-the-art visual attention models is limited in terms of prediction accuracy and computational complexity. In spite of significant amount of active research in this area, modelling visual attention is still an open research challenge. This thesis proposes a novel computational model of visual attention that achieves higher prediction accuracy with low computational complexity. A new bottom-up visual attention model based on in-focus regions is proposed. To develop the model, an image dataset is created by capturing images with in-focus and out-of-focus regions. The Discrete Cosine Transform (DCT) spectrum of these images is investigated qualitatively and quantitatively to discover the key frequency coefficients that correspond to the in-focus regions. The model detects these key coefficients by formulating a novel relation between the in-focus and out-of-focus regions in the frequency domain. These frequency coefficients are used to detect the salient in-focus regions. The simulation results show that this attention model achieves good prediction accuracy with low complexity. The prediction accuracy of the proposed in-focus visual attention model is further improved by incorporating sensitivity of the HVS towards the image centre and the human faces. Moreover, the computational complexity is further reduced by using Integer Cosine Transform (ICT). The model is parameter tuned using the hill climbing approach to optimise the accuracy. The performance has been analysed qualitatively and quantitatively using two large image datasets with eye tracking fixation ground truth. The results show that the model achieves higher prediction accuracy with a lower computational complexity compared to the state-of-the-art visual attention models. The proposed model is useful in predicting human fixations in computationally constrained environments. Mainly it is useful in applications such as perceptual video coding, image quality assessment, object recognition and image segmentation.
Search-based methods for the sparse signal recovery problem in compressed

The sparse signal recovery, which appears not only in compressed sensing but also in other related problems such as sparse overcomplete representations, denoising, sparse learning, etc. has drawn a large attraction in the last decade. The literature contains a vast number of recovery methods, which have been analysed in theoretical and empirical aspects. This dissertation presents novel search-based sparse signal recovery methods. First, we discuss theoretical analysis of the orthogonal matching pursuit algorithm with more iterations than the number of nonzero elements of the underlying sparse signal. Second, best-first tree search is incorporated for sparse recovery by a novel method, whose tractability follows from the properly defined cost models and pruning techniques. The proposed method is evaluated by both theoretical and empirical analyses, which clearly emphasize the improvements in the recovery accuracy. Next, we introduce an iterative two stage thresholding algorithm, where the forward step adds a larger number of nonzero elements to the sparse representation than the backward one removes. The presented simulation results reveal not only the recovery abilities of the proposed method, but also illustrate optimal choices for the step sizes. Finally, we propose a new mixed integer linear programming formulation for sparse recovery. Due to the equivalency of this formulation to the original problem, the solution is guaranteed to be correct when it can be solved in reasonable time. The simulation results indicate that the solution can be found easily under some reasonable assumptions, especially for signals with constant amplitude nonzero elements.
Automatic Detection and Classification of Neural Signals in Epilepsy

The success of an epilepsy treatment, such as resective surgery, relies heavily on the accurate identification and localization of the brain regions involved in epilepsy for which patients undergo continuous intracranial electroencephalogram (EEG) monitoring. The prolonged EEG recordings are screened for two main biomarkers of epilepsy: seizures and interictal spikes. Visual screening and quantitation of these two biomarkers in voluminous EEG recordings is highly subjective, labor-intensive, tiresome and expensive. This thesis focuses on developing new techniques to detect and classify these events in the EEG to aid the review of prolonged intracranial EEG recordings. It has been observed in the literature that reliable seizure detection can be made by quantifying the evolution of seizure EEG waveforms. This thesis presents three new computationally simple non-patient-specific (NPS) seizure detection systems that quantify the temporal evolution of seizure EEG. The first method is based on the frequency-weighted-energy, the second method on quantifying the EEG waveform sharpness, while the third method mimics EEG experts. The performance of these new methods is compared with that of three state-of-the-art NPS seizure detection systems. The results show that the proposed systems outperform these state-of-the-art systems. Epilepsy therapies are individualized for numerous reasons, and patient-specific (PS) seizure detection techniques are needed not only in the pre-surgical evaluation of prolonged EEG recordings, but also in the emerging neuro-responsive therapies. This thesis proposes a new model-based PS seizure detection system that requires only the knowledge of a template seizure pattern to derive the seizure model consisting of a set of basis functions necessary to utilize the statistically optimal null filters (SONF) for the detection of the subsequent seizures. The results of the performance evaluation show that the proposed system provides improved results compared to the clinically-used PS system. Quantitative analysis of the second biomarker, interictal spikes, may help in the understanding of epileptogenesis, and to identify new epileptic biomarkers and new therapies. However, such an analysis is still done manually in most of the epilepsy centers. This thesis presents an unsupervised spike sorting system that does not require a priori knowledge of the complete spike data.
Identifying shared functionality using latent semantic indexing

There are numerous systems of which parts, at least in the minds of designers, have the same functionality. If the degree of this shared functionality can be measured some how, it would prove to be very valuable. This information can be used to modularize these systems and improve their maintainability. To identify this functionality a technique known as Latent Semantic Indexing (LSI), an information retrieval technique, is proposed. We applied LSI to two systems at Getronics PinkRoccade. Our main conclusion is that we can not recover 100% of the shared functionality automatically, however, the search space can be reduced. This means the experts, recovering the shared functionality, have less documents to evaluate.