Miracle-dz/UniFAR-FTUs huggingface dataset:
A Reevaluation of Why Crypto-detectors Fail: A Systematic Revaluation of Cryptographic Misuse Detection Techniques

The correct use of cryptography is central to ensuring data security in modern software systems. Hence, several academic and commercial static analysis tools have been developed for detecting and mitigating crypto-API misuse. While developers are optimistically adopting these crypto-API misuse detectors (or crypto-detectors) in their software development cycles, this momentum must be accompanied by a rigorous understanding of their effectiveness at finding crypto-API misuse in practice. The original paper presents the MASC framework, which enables a systematic and data-driven evaluation of crypto-detectors using mutation testing. MASC was grounded in a comprehensive view of the problem space by developing a data-driven taxonomy of existing crypto-API misuse, containing 105 misuse cases organized among nine semantic clusters. 12 generalizable usagebased mutation operators were developed and three mutation scopes that can expressively instantiate thousands of compilable variants of the misuse cases for thoroughly evaluating crypto-detectors. Using MASC, nine major crypto-detectors were evaluated and 19 unique, undocumented flaws that severely impact the ability of crypto-detectors to discover misuses in practice were found. For my thesis I built upon this previous research and greatly expanded the MASC framework. MASC was expanded in all areas by adding new functionality, new operators, new misuses, and expanding the taxonomy. In addition, I reevaluated the most up to date versions of the original 9 crypto-detectors and evaluated 5 additional crypto-dectors. On top of this I also doubled the amount of applications I used to evaluate the tools. To analze crypto-dectors I looked at both the 9 crypto-detectors evaluated in the original work and 5 new crypto-detectors. For the original crypto-detectors I evaluated them with the updated MASC against their most up to date versions to determine if old flaws that have previously been fixed have a tendency to reappear. Both old and new crypto-detectors were evaluated with mutated Android and Java applications that were used in the original MASC paper, 15 newly mutated Android and Java applications, and minimal examples of cryptographic misuse.
Binaural Speech Enhancement Based on Deep Attention Layers

Here we describe our submission for the 1st Clarity En-hancement Challenge. The algorithm that we present is based on two conv-TasNets and combines the information contained on each of the listening sides to provide the model with potential binaural cues. This information is combined through intermediate layers that we will refer to as “attention layers”, inspired by the classical attention layers used in sequence to sequence modeling. The implemented model is fed with stereo signals and outputs its de-noised version with 2 ms latency. Results show that attention layers can improve the signal-to-distortion ratio, and could further improve speech intelligibility scores
Taming Dynamically Adaptive Systems with Models and Aspects

Since software systems need to be continuously available under varying conditions, their ability to evolve at runtime is increasingly seen as one key issue. Mod-ern programming frameworks already provide support for dynamic adaptations. However the high-variability of features in Dynamic Adaptive Systems (DAS) introduces an explosion of possible runtime system conﬁgurations (often called modes) and mode transitions. Designing these conﬁgurations and their transitions is tedious and error-prone, making the system feature evolution diﬃcult. While Aspect-Oriented Modeling (AOM) was introduced to improve the modularity of software, this paper presents how an AOM approach can be used to tame the combinatorial explosion of DAS modes. Using AOM techniques, we derive a wide range of modes by weaving aspects into an explicit model re-ﬂecting the runtime system. We use these generated modes to automatically adapt the system. We validate our approach on an adaptive middleware for home-automation currently deployed in Rennes metropolis.
Modelling Rumination as a State-Inference Process

Rumination is a kind of repetitive negative thinking that involves prolonged sampling of negative episodes from one’s past, typically prompted by a present negative experience. We model rumination as an attempt at hidden-state inference, formalized as a partially-observable Markov decision process (POMDP). Using this allegorical model, we demonstrate conditions under which continuous, prolonged collection of samples from memory is the optimal policy. Consistent with phenomenological observations from clinical and experimental work, we show that prolonged sampling (i.e., chronic rumination), formalized as needing to sample more evidence before selecting an action, is required when possible negative outcomes increase in magnitude, when states of the world with negative outcomes are a priori more likely, and when samples are more variable than expected. By demonstrating that prolonged sampling may allow for optimal action selection under certain environmental conditions, we show how rumination may be adaptive for solving particular problems.
An Atomistic Study of the Tensile Deformation of Carbon Nanotube–Polymethylmethacrylate Composites

There has been growing interest in polymer/carbon nanotube (CNT) composites due to an exceptional enhancement in mechanical, structural, thermal, and electronic properties resulting from a small percentage of CNTs. However, the performance of these composites is influenced by the type of polymer used. PMMA is a polymer of particular interest among many other polymers because of its biomaterial applications due to its biocompatibility, non-toxicity, and non-biodegradability. In this research, we utilized a reactive force field to conduct molecular dynamics simulations to investigate changes in the mechanical properties of single-walled carbon nanotube (SWCNT)-reinforced Poly (methyl methacrylate) (PMMA) matrix composites. To explore the potential of SWCNT-reinforced PMMA composites in these applications, we conducted simulations with varying CNT diameters (0.542–1.08 nm), CNT volume fractions (8.1–16.5%), and temperatures (100 K–700 K). We also analyzed the dependence of Young’s modulus and interaction energy with different CNT diameters, along with changes in fracture toughness with varying temperatures. Our findings suggest that incorporating a small amount of SWCNT into the PMMA polymer matrix could significantly enhance the mechanical properties of the resulting composite. It is also found that the double-walled carbon nanotube has roughly twice the tensile strength of SWCNT, while maintaining the same simulation cell dimensions.
CATCHING SPEEDERS VIA MOBILE PHONES AND MACHINE LEARNING: AN OPPORTUNITY TO IMPROVE SPEED ENFORCEMENT

Smartphone cameras and computer vision (CV) can be used to assist public agencies in enforcing traffic laws and improving safety. This paper documents automated enforcement applications around the globe for excessive speed, noise, illegal parking, driving through a red light and other forms of reckless driving, while illuminating how non-stationary, hand-held cameras can be used (as well as the millions of traditional, stationary cameras that already exist alongside roadways). Speeding is a significant cause of car crashes, and despite existing laws and automated speed reduction methods, accidents related to speeding still occur worldwide. While fixed camera surveillance is one automated method for reducing speed, its effectiveness is limited to specific locations. Violators tend to accelerate once they pass these fixed camera sites. To address this issue, a CV technology has been developed using existing open-source methods, which can estimate vehicle speed and identify license plates from mobile phone recordings. This innovation
Eddy‐Mean Flow Interaction With a Multiple Scale Quasi Geostrophic Model

Parameterization of mesoscale eddies in coarse resolution ocean models is necessary to include the effect of eddies on the large‐scale oceanic circulation. We propose to use a multiple‐scale Quasi‐Geostrophic (MSQG) model to capture the eddy dynamics that develop in response to a prescribed large‐scale flow. The MSQG model consists in extending the traditional quasi geostrophic (QG) dynamics to include the effects of a variable Coriolis parameter and variable background stratification. Solutions to this MSQG equation are computed numerically and compared to a full primitive equation model. The large‐scale flow field permits baroclinically unstable QG waves to grow. These instabilities saturate due to non‐linearities and a filtering method is applied to remove large‐scale structures that develop due to the upscale cascade. The resulting eddy field represents a dynamically consistent response to the prescribed background flow, and can be used to rectify the large‐scale dynamics. Comparisons between Gent‐McWilliams eddy parameterization and the present solutions show large regions of agreement, while also indicating areas where the eddies feed back onto the large scale in a manner that the Gent‐McWilliams parameterization cannot capture. Also of interest is the time variability of the eddy feedback which can be used to build stochastic eddy parameterizations.
Resiliency of the Architects in the Academe: A Qualitative Focus on the Virtual Architectural Design (AD) Studio in the Philippines

The widespread impact of COVID-19 greatly affects the deployment of higher education. In the Philippines, with the current physical restrictions, academic institutions have shifted to online learning. However, with limited technological resources compounded by one of the poorest internet connections in Southeast Asia, online learning is a constant challenge to educators in the Philippines. Even more so in architectural design, a studio culture in which creativity and mentorship are the main thrusts. Current literature on online learning in the country is mainly focussed on general subjects. This paper seeks to define the ways in which the architecture studio culture adapted to the challenges of conducting education online. This research employs qualitative methods that focus on the educators’ shift to the online format when it comes to handling architecture studios in the Philippines. In particular, it examines the resiliency and resourcefulness of educators as well as the tools and techniques used. The study hopes to produce a framework for the continued improvement of the online architectural studio that will benefit educators and students alike.
Scaling Properties of Ru, Rh, and Ir for Future Generation Metallization

The downscaling of metal lines in CMOS devices to subnanometer sizes leads to an increase in their resistivity. Thus, the lower electron mean free paths of Ru, Rh, and Ir make them promising materials to replace Cu in conventional interconnected structures with sub-ten-nanometer dimensions. In this study, we investigate their scaling effects on the resistivities of metal lines with thicknesses of 4–32 nm. The resistivities of Ru, Rh, and Ir as-deposited films prepared via sputtering are lower than that of a Cu film with a sub-ten-nanometer thickness. Despite their similar electron mean free paths, the difference in their bulk resistivities lead to Ir and Rh having lower resistivities than Ru, even after annealing at 400 °C. Their resistivities before and after annealing were fitted with equations based on the Fuch–Sondheimer and Mayadas–Shatzkes models, which assess the contributions of surface and grain boundary scatterings, respectively. We determined that grain boundary scatterings have a significant effect on the resistivities of Ru, Ir, and Rh, whereas surface scatterings have a minimal effect. In addition, in the case of Ru, the effect of the surface roughness on the resistivity was also investigated by measuring the resistivity of Ru films deposited by atomic layer deposition. A high surface RMS roughness of 1–2 nm causes a significant increase in the resistivity at thicknesses below 10 nm that cannot be explained by the aforementioned models. These results present multiple points for consideration when applying short mean free path metals to finite size interconnects.
X-ray Lobster Eye all-sky monitor for rocket experiment

This paper presents a Lobster Eye (LE) X-ray telescope developed for the Water Recovery X-ray Rocket (WRX-R) experiment. The primary payload of the rocket experiment is a soft X-ray spectroscope developed by the Pennsylvania State University (PSU), USA. The Czech team participates by hard LE X-ray telescope as a secondary payload. The astrophysical objective of the rocket experiment is the Vela Supernova of size about 8deg x 8deg. In the center of the nebula is a neutron star with a strong magnetic field, roughly the mass of the Sun and a diameter of about 20 kilometers forming the Vela pulsar. The primary objective of WRX-R is the spectral measurement of the outer part of the nebula in soft X-ray and FOV of 3.25deg x 3.25deg. The secondary objective (hard LE X-ray telescope) is the Vela neutron star observation. The hard LE telescope consists of two X-ray telescopes with the Timepix detector. First telescope uses 2D LE Schmidt optics (2DLE- REX) with focal length over 1m and 4 Timepix detectors (2x2 matrix). The telescope FOV is 1.5deg x 1.5deg with spectral range from 3keV to 60keV. The second telescope uses 1D LE Schmidt optics (1D-LE-REX) with focal length of 25 cm and one Timepix detector. The telescope is made as a wide field with FOV 4.5deg x 3.5deg and spectral range from 3keV to 40keV. The rocket experiment serves as a technology demonstration mission for the payloads. The LE X-ray telescopes can be in the future used as all‐sky monitor/surveyor. The astrophysical observation can cover the hard X-ray observation of astrophysical sources in time-domain, the GRBs surveying or the exploration of the gravitational wave sources.
Multi-Scale Factor Analysis of High-Dimensional Functional Connectivity in Brain Networks

We consider challenges in modeling and estimating high-dimensional functional connectivity in brain networks with a large number of nodes arranged in a hierarchical and modular structure. We develop a multi-scale factor analysis (MSFA) model which partitions the massive neuroimaging time series data defined over the brain networks into a finite set of regional clusters. To achieve further dimension reduction, signals in each cluster are represented by a small number of latent factors. The correlation matrix for all nodes in the network can be approximated by lower-dimensional sub-structures derived from the cluster-specific factors. This enables a reliable and computationally efficient multi-scale analysis of both regional and global network connectivity. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to extract the factors. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. Simulation results show that the proposed MSFA estimator improves accuracy of connectivity estimation in high-dimensional settings. When applied to resting-state functional magnetic resonance imaging (fMRI) data, our method identifies modular structure of resting-state networks at multiple scales, revealing interesting connectivity patterns between voxels, regions of interest (ROIs), and functional networks.
Environmental multiway data mining

Among commonly used data mining techniques, few are those which are able to take advantage of the multiway structure of data in the form of a multiway array. In contrast, tensor decomposition techniques specifically look for intricate processes underlying the data, where each of these processes can be used to describe the multilinear structure of the data array. The work reported in the following pages aims at incorporating various external knowledge into the tensor canonical polyadic decomposition, which is usually understood as a blind model. The first two chapters of this manuscript introduce tensor decomposition techniques making use respectively of a mathematical and an application framework. In the third chapter, the many faces of constrained decompositions are explored, including a unifying framework for constrained decomposition, some decomposition algorithms, compression and dictionary-based tensor decomposition. The fourth chapter discusses the inclusion of subject variability modeling when multiple arrays of data are available stemming from one or multiple subjects sharing similarities. State of the art techniques are studied and expressed as particular cases of a more general flexible coupling model later introduced. The chapter ends on a discussion on dimensionality reduction when subject variability is involved, as well as some open problems.
Fuzzy Logic Controller for Half Car Active Suspension System

This work presents the MATLAB/Simulink simulation results of half car active suspension system controlled by the fuzzy logic controller. The half car model consists of one front and rear wheel. Firstly, a mathematical model of the suspension system is developed. Based on the developed mathematical model, the fuzzy logic controller for the system is designed. The input to the controller is the vertical displacement and velocity of the front body of the vehicle. The membership function of these two variables is adjusted accordingly so that the output, i.e., the car body acceleration, the deflection of the wheels and other output are better than that of the passive suspension system. The results clearly show that all of the active suspension system output has improved when compared to that of the passive system.
Predictive values of salivary IL-6 and sFas-dependent apoptosis inhibitor in pathogenesis of oral lichen planus

Introduction: Oral lichen planus (OLP) is a familiar inflammatory disease commonly seen in dental practice. Oral lichen planus’ pathophysiology is not fully understood. Objectives: The current research was aimed to determine the level of IL-6 in the saliva and the apoptosis-related marker soluble Fas (sFas) in OLP patients versus healthy controls before and after triamcinolone acetonide 0.1% in orabase application and to explore their roles in the etiology of OLP and if there is any possible correlation between the two studied markers. Subjects and methods: 30 subjects were allotted into two equal groups. Group I (control): included 15 healthy individuals. Group II (OLP): included 15 patients who were formerly diagnosed with OLP and showed acute exacerbation at time of 1 st examination. Present pain intensity (PPI) and Thongprasom clinical sign scoring were used on group II patients before and 1 month following treatment. Salivary samples for detection of IL-6 and sFas were collected once from group I and twice in group II. Results: OLP group had higher values of IL-6 and sFas in their salivary samples that were statistically superior to those in the control group. In group II, following treatment, a significant reduction of PPI, Thongprasom sign scoring, IL-6 and sFas values was noticed. A weak positive correlation was found between IL-6 and sFas before and after treatment. Conclusion: Salivary IL-6 and sFas concentrations in OLP group were higher than their values in control group and considerably decreased following therapy, confirming their usefulness in OLP diagnosis.
A surface micromachined rotating micro-mirror normal to the substrate

An optical mirror for directing a laser parallel to the substrate surface has been designed and fabricated. The mirror consists of a 214 /spl mu/m/spl times/210 /spl mu/m, 3.5 /spl mu/m thick polysilicon plate, coated with a 0.5 /spl mu/m thick layer of gold. The mirror is connected to the substrate by 3 floating substrate hinges. Using microprobes, the mirror is lifted off of the substrate and up into a latch mechanism. The latch holds the mirror normal to the substrate. The floating substrate hinges are connected to a 200 /spl mu/m diameter circular 2.0 /spl mu/m thick polysilicon plate. This plate is mounted to the substrate via a rotating sliding anchor. The mirror is designed to be driven by an array of thermal actuators.
Religious Moderation Based on Ancient Manuscript in Maros District

The harmony movement in Indonesia has been carried out by the nation's predecessors. The remains of ancient manuscripts in Maros, South Sulawesi, are historical evidence that religious moderation has been practiced. This article aims to examine the practice of religious moderation in the Lontaraq Manuscript of Kassi, Labuang, Pacelle. Through the philological method, this study found the following findings. First, these manuscripts express historical events in the past which have very strong nuances of religious moderation in them. Slavery and extortion were commonplace at that time, but there were breakthroughs or efforts made by Karaeng to abolish slavery and extortion at that time. The breakthrough is through humanity, justice, equality of social strata, and love between the people and the authorities. Equality without caste strata is in line with the justice proclaimed in Religious Moderation. Second, differences in ethnicity, language, and religion become social forces with a culture of mutual respect.
Design of Low Power Arithmetic logic unit using SHE assisted STT / MTJ

: As CMOS technology shrinks to the deep submicron range, increased power dissipation becomes a big issue. Due to its non-volatility, fast speed, great durability, CMOS compatibility, and low power consumption, the Spin transfer torque (STT) switching mechanism based on Magnetic tunnel Junction (MTJ) is widely regarded as one of the most promising spintronic devices for the post-CMOS era. The research presented here proposes a novel Arithmetic Logic Unit (ALU) that makes use of Spin Hall E ff ect (SHE) to aid with STT / MTJ. In this study, we use SHE-assisted STT logic to create a Hybrid Full Adder and three other logics (AND, OR, and XOR). The proposed logics are then used to create an adder circuit, which is used to create an Arithmetic Logic Unit (ALU). A comparison of each of the proposed designs to the DPTL − C 2 MOS − ALU and P-MALU has been performed. The simulation findings show that the proposed designs outperform competing ALU designs, with a 28% reduction in power consumption and a corresponding reduction in latency. For circuit simulation in 45nm technology, the Cadence Virtuoso tool is employed.