Miracle-dz/UniFAR-FTUs huggingface dataset:
A Logic and an Interactive Prover for the Computational Post-Quantum Security of Protocols

We provide the first mechanized post-quantum sound security protocol proofs. We achieve this by developing PQ-BC, a computational first-order logic that is sound with respect to quantum attackers, and corresponding mechanization support in the form of the PQ-SQUIRREL prover. Our work builds on the classical BC logic [7] and its mechanization in the SQUIRREL [5] prover. Our development of PQ-BC requires making the BC logic sound for a single interactive quantum attacker. We implement the PQ-SQuiRREL prover by modifying SQUIRREL, relying on the soundness results of PQ-BC and enforcing a set of syntactic conditions; additionally, we provide new tactics for the logic that extend the tool’s scope. Using PQ-SQUIRREL, we perform several case studies, thereby giving the first mechanical proofs of their computational post-quantum security. These include two generic constructions of KEM based key exchange, two sub-protocols from IKEv1 and IKEv2, and a proposed post-quantum variant of Signal’s X3DH protocol. Additionally, we use PQ-SQuiRREL to prove that several classical SQUIRREL case studies are already post-quantum sound.
Vector-based Dynamic Assessment of Cyber-Security of Critical Infrastructures

The paper encompasses development of existing techniques for assessment of critical cyber-physical systems in conditions of uncertainties and considering transient processes caused by changes in the structure, modes and conditions of their functioning. The goal of the research is to create a mathematical and modeling apparatus capable of solving tasks for cyber-security analysis of complex managed systems of this class with high precision and efficiency.
Early Detection of Casava Plant Leaf Diseases using EfficientNet-B0

Image recognition plays a major role in everyday life applications like medical image analysis, gaming, surveillance and security, industrial automation, and more recently it has gained massive backing in the agricultural industry to identify plant diseases in crops. Plant diseases are a huge problem in agriculture and incorporating machine learning algorithms for their early detection will help better yields and save the farmers from loses. This paper entails the use of such machine learning algorithms to detect leaf diseases in the cassava plant. Cassava is one of the largest sources of carbohydrates for the continent of Africa. It is also very vulnerable to several plant diseases; this in turn threatens the food security of the continent. The present study is based on four of such diseases that affect the cassava yield namely, Cassava Bacterial Blight (CBB), Cassava Brown Streak Disease (CBSD), Cassava Mosaic Disease (CMD), and Cassava Green Mottle (CGM). In this research work, EfficientNet-B0 is proposed for the early detection of these diseases. The EfficientNet-B0 models outperform existing CNNs in terms of accuracy and efficiency while reducing parameter size and FLOPS by an order of magnitude. It is easier to detect disease at an early stage without the assistance of professionals, saving farmers both time and money. And our proposed model gave an accuracy of 92.6%.
Effect of Al-doping in $p$-type $\text{SnO}_{x}$ Thin Film Transistors: Physics and Modeling

In the article, we report the effect of aluminum (Al) doping on the performance enhancement of p-type $\text{SnO}_{x}$ thin film transistors (TFT). To understand the physics of performance enhancement, we have performed the physical modeling of these materials with density-of-state (DOS) model and performed numerical simulations. Computed current-voltage characteristics were compared with results of fabricated 8 nm thin SnO and Al-doped $\text{SnO}_{x}$ TFTs on HfO2/Si substrate. It was observed that the bandgap, field-effect mobility ($\mu_{FE}$) and DOS of SnO are largely affected by Al-doping. An increased $\mu_{FE}\sim 3.5\ cm^{2} V^{-1}s^{-1}$ was observed for $\text{Al}-\text{SnO}_{x}$ TFT.
Can I Borrow Your ATM? Using Virtual Reality for (Simulated) In Situ Authentication Research

In situ evaluations of novel authentication systems, where the system is evaluated in its intended usage context, are often infeasible due to ethical and legal constraints. Consequently, researchers evaluate their authentication systems in the lab, which questions the eco-logical validity. In this work, we explore how VR can overcome the shortcomings of authentication studies conducted in the lab and contribute towards more realistic authentication research. We built a highly realistic automated teller machine (ATM) and a VR replica to investigate through a user study (N=20) the impact of in situ evaluations on an authentication system‘s usability results. We evaluated and compared: Lab studies in the real world, lab studies in VR, in situ studies in the real world, and in situ studies in VR. Our findings highlight 1) VR‘s great potential to circumvent potential restrictions researchers experience when evaluating authentication schemes and 2) the impact of the context on an authentication system‘s usability evaluation results. In situ ATM authentications took longer (+24.71% in the real world, +14.17% in VR) than authentications in a traditional (VR) lab environment and elicited a higher sense of being part of an ATM authentication scenario compared to a real-world and VR-based evaluation in the lab. Our quantitative findings, along with participants‘ qualitative feedback, provide first evidence of increased authentication realism when using VR for in situ authentication research. We provide researchers with a novel research approach to conduct (simulated) in situ authentication re-search, discuss our findings in the light of prior works, and conclude with three key lessons to support researchers in deciding when to use VR for in situ authentication research.
On the Use of Pixelated Plastic Scintillator and Silicon Photomultipliers Array for Coded Aperture Gamma-Neutron Imaging

We report the investigations made on the use of pixelated plastic scintillator (PS) and silicon photomultipliers (SiPMs) array applied to coded aperture gamma-neutron imaging. Specifically, verification of the ability of a multiplexing readout to discriminate and localize neutron interactions was studied. In its intended configuration, the gamma-neutron imager design consists of a coded aperture aligned with a matrix of <inline-formula> <tex-math notation="LaTeX">$12\times12$ </tex-math></inline-formula> PS each coupled to a SiPM. The coded aperture is a rank 7 modified uniformly redundant array (MURA), composed of 1.2 cm of tungsten, with a surface area of 100.4 mm <inline-formula> <tex-math notation="LaTeX">$\times100.4$ </tex-math></inline-formula> mm and placed at 5 cm from the detector. The pixelated PS is composed of polystyrene and standard fluorophores (20 wt% PPO, 0.03 wt% POPOP) loaded with a lithium carboxylate (Li <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>-valerate), which allows the triple discrimination between thermal neutrons, fast neutrons, and photons. Each pixel of PS has a dimension of 3.6 mm <inline-formula> <tex-math notation="LaTeX">$\times3.6$ </tex-math></inline-formula> mm <inline-formula> <tex-math notation="LaTeX">$\times3.6$ </tex-math></inline-formula> mm and they are separated from each other by 0.6 mm of polytetrafluoroethylene (PTFE). The photonic and electronic readout consists of the ArrayC-30035-144P SiPM from SensL, Cork, Ireland, connected to the diode coupled charge division readout from AiT. First, this neutron imager design was modeled and simulated using the MCNP6 Monte Carlo code. The encoding capability, field of view, and spatial resolution of the neutron imager were therefore evaluated by simulation. Then, we detailed the experimental setups implemented to demonstrate the feasibility of coupling pixelated PS to SiPM to localize radioactive sources and showed the results obtained. Finally, based on this position-sensitive gamma-neutron detector, a gamma-neutron imager was prototyped and tested.
A Novel Method for Determining the Electrode Temperature Effect on Post-Arc Breakdown Characteristics

During the post-arc stage of the interruption process, hot gases, high-temperature electrodes, and metallic macroparticles could strictly hinder the recovery of dielectric strength. Despite many studies focusing on the mechanism of the post-arc phenomenon, there is still a lack of comprehension determining the role of electrodes during the breakdown process. In this paper, the electrode temperature after current zero is measured by using the two-color-pyrometry method combined with the narrow band-pass filters and an optical splitting device. Adopting a repetitive pulse power supply, and heating the electrode with a high-power laser, the temperature effect of WCu electrodes on post-arc breakdown voltage in atmospheres is quantitatively determined. Both for the cathode and the anode, the threshold effect of the electrode temperature on the breakdown strength is observed. However, it is found that the cathode temperature has a more pronounced impact on the breakdown voltage compared to the anode temperature; the cathodic critical temperature range for the threshold effect is 1350K-1500K, while the corresponding anodic critical temperature range is 2400K-2500K. By introducing the voltage ratio coefficient of the electrode, we show strong evidence that the higher arc energy could prolong the effect of electrode temperature on the recovery of the post-arc dielectric strength.
Speech Enhancement Using Open-Unmix Music Source Separation Architecture

Speech enhancement using sound source separation finds usefulness in prevention of degradation of the quality of human speech on voice call/video call, voice assistant commands due to background noises. Open-Unmix is popular architecture used by researchers for music source separation. This paper proposes a modified implementation of the Open-Unmix model, to attain the goal of sound source separation for speech enhancement. This paper explains in detail, the custom dataset collection and pre-processing methods to generate the training data. The improved Open-Unmix model is a deep neural network that estimates separation masks in the short-time Fourier transform domain. It is based on three-layer bidirectional long short-term memory (Bi-LSTM) with completely connected encoding and decoding layers. The source to artifact ratio (SAR), scale invariant source to distortion ratio (SI-SDR), short time objective intelligibility (STOI), and source to distortion ratio (SDR) are all popular subjective measures for blind source separation of audio signals used in our overall assessment. Experimental results show that our proposed method can separate noise background signals from human speech and provide enhancement in real environment.
Enhanced Prosthetic Myoelectric Affordable Hand Design of an 1-Open-Source

The need for innovations in developing creative prosthetic hands and terminal systems that take use of the most recent technology advances, to enhance device themes highly functional, robust, aesthetically acceptable, and less costly. This paper presents the design and manufacture technique of a tact hand, an anthropomorphic, open-source (O-S), Myoelectric Prosthetic Hand (MPH) for persons with transradial amputations in emerging state. The design process is based on balancing workability, cost, efficiency, durability, and effectiveness, and then manufacturing using 3D printing technology (3D-P). The findings showed that using lighter and hollow materials instead of rigid injection molded plastic materials reduced fatigue and pain caused by mass distributing to smoother tissues. But create the sensitivity hand system process, predict the sensitivity hand using qualitative and quantifiable events of enactment, and present samples of the usage of this hand to grab domestic things. The validation and findings were determined by comparing them to related studies, such as section four, where the functional usefulness of utilizing the hand to demonstrate a range of household items was discussed. Items like the water bottle and bottle cap, and the use of a 3-jaw chuck, key grip, and tool grip, were all simply understood by the tip. We combine electromyographic pattern recognition for motor control, contact reflexes, and sensory substitution to deliver input to the user. When compared to standard myoelectric prostheses that lack these features, the quality of rotation and other motions has also improved, and using contact reflexes and sensory substitution progresses grasping of delicate objects like an eggshell and a cup of water both with and without visual feedback. It can be shown that average intensity features (AIH) performed better than other feature sets (ACC $\text{AIH}=0.952954668\%, \text{PAIH}=0.966836735\%,\ \text{SAIH}=0.979323844\%$). We label our diagram process, estimate the Sensitivity hand $(\mathrm{S}\_\text{AIH}=0.979323844\%)$ with together qualitative and measurable events of enactment, and show samples of this hand to grip domestic objects.
Effect of turbulence in modeling the reduction of local drag forces in a computational automotive model

In this computational fluid dynamic (CFD) study on vehicle drag forces sheds light on the mathematical algorithms utilized to converge on pertinent data useful in the design and manufacture of automobiles. COSMOS Floworks™ was used to model the virtual vehicle motion involving various governing flow equations with main attention given to turbulent behavior in incompressible fluid flows. The paper highlighted Navier-Stokes considerations in the study and introduced Reynolds Decomposition methods to generate more refined models which in turn give accurate results, such as Reynolds-Averaged Navier– Stokes (RANS) Equations and Large Eddy Simulation (LES) Techniques, introduced using the Einstein Notation. Recent developments in Coherent vortex simulation methods were also briefly discussed. Example modeling and tests were conducted to show automotive design improvements that resulted in a 8.57% improvement in local drag forces (FD) at the rear wheel wells, which effectively reduces the required Horsepower (hp) of the vehicle traveling at a certain speed (7.24 %). Different 3-D Automotive Design Models were examined in the current study, where real life design considerations and design benefits applications were briefly discussed. Furthermore, the paper highlights the need for utilization of both computational and real flow analysis on the car body and future performance relationship with the car’s body weight, material and design. Copyright © 2011 International Energy and Environment Foundation - All rights reserved.
Semiconductor Wafer Map Defect Classification Using Transfer Learning

Semiconductor chip manufacturing is a time consuming and an expensive process. Since the testing process is one of the major contributors to the production cost in IC manufacturing industry, it is quite necessary to detect these wafer map defects during the manufacturing and correctly label them in order to identify the causes of these defects. Through this paper, we present and compare various transfer learning methods that can classify the wafer map with their correct defects. Our experiments compare the performance of various transfer learning based models like VGG19, MobileNet, ResNet, DenseNet on a real-world wafer map dataset WM811K. The dataset consists of eight wafer map defect classes; we have clubbed the defects into four defect classes which will be discussed later in the paper. Through our experiments we have observed that VGG19 has achieved the highest accuracy of 95.56% on the test data.
Use of Electric Arc Furnace Slag for High Strength Concrete Production

In this paper the use of Electric Arc Furnace slag (EAF slag) for the production of High-Performances Concrete (HPC) is explored, as a fully replacement of the natural gravel. Several mixtures were produced, varying the water/cement ratio, the cement and the admixture content, with the aim of reaching a strength class between C50/60 and C60/75, and an S4 consistency class, as defined in EN 206-1. Mechanical properties of EAF concretes were compared with reference conglomerates; a complementary microstructural analysis was performed, with SEM observation after concrete specimens' failure. Results indicate that the use of EAF slag in concrete allows reaching higher compressive strength than with coarse natural aggregates. Lastly, the environmental benefits obtained through the use of recycled aggregates are shown, by means of the application of a Life Cycle Assessment (LCA) tool properly developed for this scope.
Exploring Pseudo-Weight in Augmented Reality Extended Displays

Augmented reality (AR) allows us to wear virtual displays that are registered to our bodies and devices. Such virtually extendable displays, or AR extended displays (AREDs), provide personal display space and are free from physical restrictions. Existing work has explored the new design space to improve user experience and efficiency. Contrary to this direction, we focus on the weight that the user perceives from AREDs, even though they are virtual and have no physical weight. Our user study results show evidence that AREDs can be a source of pseudo-weight, in addition to that of a handheld physical display device. We also systematically evaluate the perceived weight changes depending on the layout and delay in the visualization system. These findings are similar to those in existing pseudo-haptics research. However, we found such behavior in pseudo-weight for a real device and virtual visual stimuli in the air, which differentiates our research from previous work.
Damage Evolution in SAC Solder Alloys

Solder joints in electronic packages often experience fatigue failures due to cyclic mechanical stresses and strains in fluctuating temperature environments. This cyclic loading of the solder is induced by mismatches in coefficients of thermal expansion and elastic modulus, and leads to damage accumulation that contributes to crack initiation, crack propagation, and eventually failure.In this work, we are investigating the accumulation of damage in SAC alloys during isothermal mechanical cycling at room temperature. In the experimental testing, small uniaxial cylindrical samples of SAC305 solder were prepared and reflowed in a reflow oven. These specimens were then mechanically cycled under strain control and several different sets of conditions to induce various levels of damage in the samples. It was found that the total energy dissipation that had occurred in the sample (sum of ΔW for all cycles) could be used as a governing failure variable independent of the damage level applied during each cycle. This has motivated using a scalar damage parameter in the constitutive model for the investigated SAC305 alloy following the basic concepts of continuum damage mechanics. As damage accumulates, the elastic, plastic and creep properties degrade accordingly. The damage law is incorporated into ANSYS UPFs to simulate the stress-strain hysteresis loop in the test. Simulation results show that it can capture the loop area decrease, maximum stress and modulus reduction. The damage model is also used to simulate the progressive failure of a solder sphere under cyclic iso-thermal mechanical load.
Relative Performance Analysis of Different Full Adder Using FINFET Technology

Full Adder (FA) is the very crucial cell of modern electronic processor and its arithmetic logical operations. To design the FA Circuits, the power and delay parameter are most significant consideration. The efficient FA is configured by complementary pass transistor logic, CMOS and transmission gate, etc. As technology goes smaller the Drain Induced Barrier Lowering (DIBL) is becoming a critical factor to design FA circuit. To overcome these issues, FinFET is projected to control on subthreshold conduction and leakage current. The FinFET is a multi-Gate device and can avoid the DIBL problems. In this paper, implemented the different types of high performance Full Adder with FinFET technology. Jyoti Kandpal, Hamed Naseri, Yavar Safaei Mehrabani and Mehedi Hasan projected circuits are implemented by using FinFET technology. All the operation of FA cell is conducted on 1.8 V and compares the performance based on driving capability and Power-delay product (PDP). Enhancing the quality and speed of electronic gadgets can be achieved by increasing the performance of full adder.
Empathic AuRea: Exploring the Effects of an Augmented Reality Cue for Emotional Sharing Across Three Face-to-Face Tasks

The Empathy-Effective Communication hypothesis states the better a speaker can understand their listener’s emotions, the better can they transmit information; and the better a listener can understand the speaker’s emotions, the better can they apprehend the information. Previous emotional sharing systems have managed to create a space of emotional understanding between collaborators on remote locations using bio-sensing, but how a context of face-to-face communication can benefit from biofeedback is still to be studied. This study introduces a new Augmented Reality communication cue from an emotion recognition neural network model, trained using electrocardiogram physiological data (AuRea). The proposed de-sign is meant to facilitate emotional state understanding, increasing cognitive empathy without compromising the existing verbal, non-verbal, and paraverbal communication cues. We conducted a study where pairs of participants (N=12) engaged in three tasks where AuRea was found to positively affect performance and emotional understanding, but negatively affect memorization.
Comparative Study of Various Preprocessing Technique for CNN based Image Fusion

Image fusion is a technique of fusing every possible detail from the images of different modalities or different focuses into a single image so that a viewer can get the maximum quantity of information about the subject in one image. A tremendous effort has been made in this area with handcrafted techniques and later on utilizing deep learning methods. The authors here have endeavored to show the effect of preprocessing on the image fusion utilizing CNN. Three types of filters Gaussian, median and bilateral are employed discretely as a pre-processing step which shows median filter gives the best value of ISSIM in all three datasets (i.e. medical, infrared-visual, and color multi-focus dataset), additionally, Gaussian and bilateral filters gave the second-best values of NMI which denoted maximum quantity of mutual information is recuperated from different modalities.
Computing in Finite Fields

The mathematical apparatus of Galois field theory is used in coding theory, cryptography, stochastic informatics. The paper considers algorithms for multiplying field elements, while paying attention to both table multiplication and multiplication "on the fly"; algorithms for calculating multiplicative inversion. The solution to the problem of finding primitive elements of the field GF (pn) is discussed. The questions of extension of finite fields are considered. Numerical examples of the operation of all considered algorithms are given.