Miracle-dz/UniFAR-FTUs huggingface dataset:
Chip-Underfill Interface Damage Model Under Fatigue Loading after Sustained High-Temperature Exposure

FCBGAs enable advanced safety and control functions on the automotive platform. The substrate and die interfaces in FCBGA packages are reinforced by underfill material. Underfills may be used to protect the chip from shock, vibration, and moisture. Underfills significantly reduce the amount of plastic work during temperature excursions and offer great mechanical support to the solder connections. Additionally, underfills offer FCBGA that are subjected to extremely high thermo-mechanical loads over an extended period of time when employed in underhood electronics. One of the dominant failure modes at chip/UF interfaces has been delamination. In this paper, the Chip-UF interface has been studied under repetitive loads. Bimaterial specimens of Chip/UF interfaces have been fabricated and exposed to high temperatures of 100°C and 150°C for 30, 60, 90, 120, 180, 240, 300, and 360 days. After iso-thermal aging, the samples undergo four-point bend fatigue. The interfacial fracture toughness values have been determined for each of the loading conditions. In fatigue loading, the crack growth rate with respect to the number of fatigue cycles is computed. The interfacial crack growth rate and the stress intensity factor for the interface are related to each other using Paris law. The Paris constants (A, n) are computed from fatigue loading interfaces, which directly represent the evolution of interfacial properties with respect to sustained high-temperature exposure.
Ex pede Herculem: Augmenting Activity Transition Graph for Apps via Graph Convolution Network

Mobile apps are indispensable for people's daily life. With the increase of GUI functions, apps have become more complex and diverse. As the Android app is event-driven, Activity Transition Graph (ATG) becomes an important way of app abstract and graphical user interface (GUI) modeling. Although existing works provide static and dynamic analysis to build ATG for applications, the completeness of ATG obtained is poor due to the low coverage of these techniques. To tackle this challenge, we propose a novel approach, ArchiDroid, to automatically augment the ATG via graph convolution network. It models both the semantics of activities and the graph structure of activity transitions to predict the transition between activities based on the seed ATG extracted by static analysis. The evaluation demonstrates that ArchiDroid can achieve 86% precision and 94% recall in predicting the transition between activities for augmenting ATG. We further apply the augmented ATG in two downstream tasks, i.e., guidance in automated GUI testing and assistance in app function design. Results show that the automated GUI testing tool integrated with ArchiDroid achieves 43% more activity coverage and detects 208% more bugs. Besides, ArchiDroid can predict the missing transition with 85% accuracy in real-world apps for assisting the app function design, and an interview case study further demonstrates its usefulness.
An accurate, CFO-free, phased-based ranging solution using the round-trip CSI

The presence of the carrier frequency offset (CFO) in WiFi systems not only interferes with communication but also hampers the use of the channel state information (CSI) derived from the WiFi signals for ranging. In this paper, we aim to remove the error caused by the CFO and then present an accurate, phased-based ranging solution using the round-trip CSI measurements. Concretely, we first investigate the errors of the CFO that contaminate CSI and model the effects mathematically. Then, we propose the sparse recovery method to estimate the amount of the CFO error and derive a stable calibration parameter based on the linear fitting method to compensate for the CFO error. To validate the proposed method, we finally prototype the ranging system using the software defined radio (SDR) platform. The extensive experimental results show that the ranging accuracy is significantly improved provided that we remove the CFO error with the estimated calibration parameter.
Classification of Respiratory Diseases With Respiratory Sounds With Deep Learning Algorithm

It is crucial to improve access to quality healthcare for the economically underprivileged community in order to ensure that imperative illnesses may be treated quickly. In situations where medical personnel are severely lacking, a simple categorization of respiratory tones using a computerized instrument can be performed to provide a rapid diagnosis for respiratory-related disorders such as Respiratory function. In this paper, it presents Respiratory Specification, an upgraded bi-ResNet deep learning architecture that employs STFT and wavelet extraction of features approaches to boost performance over previous work. The authorized data compared to the global and the "train-and-test" datasets splitting procedure from the ICBHI 2017 challenge to create a fair assessment. As an outcome, able to obtain a productivity of 51.17 percent, which would be the best prediction consequence among all ICBHI 2017 teams participating.
Brauer--Manin obstructions on genus-2 K3 surfaces

We analyze the Brauer--Manin obstruction to rational points on the K3 surfaces over $\mathbb{Q}$ given by double covers of $\mathbb{P}^2$ ramified over a diagonal sextic. After finding an explicit set of generators for the geometric Picard group of such a surface, we find two types of infinite families of counterexamples to the Hasse principle explained by the algebraic Brauer--Manin obstruction. The first type of obstruction comes from a quaternion algebra, and the second type comes from a 3-torsion element of the Brauer group, which gives an affirmative answer to a question asked by Ieronymou and Skorobogatov.
Uncertainty analyses in computational electromagnetism

Uncertainty Analyses provide the quantitative level of confidence that can be held in the results of a measurement or computational simulation. Different Error and Uncertainty Analysis methods are used to estimate the error and uncertainty in the output of Computational Electromagnetic simulations in this thesis. The Uncertainty Analysis methods are compared in terms of their ability to accurately quantify the mean, uncertainty and ninety five per cent confidence intervals in the output of the simulations, as well as in terms of their computational expense. Through this work the Monte Carlo Method, the Method of Moments and the Polynomial Chaos Method are implemented into the Finite Difference Time Domain method. The Monte Carlo Method and the Method of Moments are also implemented into the Intermediate Level Circuit Model. These Uncertainty Analysis methods are applied to a number of specific examples, from simple examples that have analytic solutions, to more realistic and complex Electromagnetic Compatibility scenarios. Performing both Error and Uncertainty Analyses enables an investigation on the relationship between the errors and uncertainties, in the output of simulations, to be conducted. Different Computational Electromagnetic methods are also used in this thesis to determine the differences in the uncertainty in the output of simulations performed using the different methods. In Electromagnetic Compatibility the output of interest is often a curve viewed in the frequency domain. The Feature Selective Validation method is used in this thesis to compare the mean, uncertainty and ninety five percent confidence interval curves formed from the different Uncertainty Analysis methods. Curve Alignment techniques are also used to determine the extent to which the errors and uncertainties in the output curves are amplitude and frequency errors and uncertainties. The results obtained in this thesis show that, of the three uncertainty analysis meth-
Realization and validation of a piezoresistive textile-based insole for gait-related measurements

The measurement of gait-related parameters is required in several application fields, such as experimental biomechanics and robotics. To enhance the wearability, smart textile-based sensors are always more widespread. In this context, we proposed an innovative insoles sensorized with piezoresistive textile able to gather information related to gait phase duration and center of pressure. An experimental protocol involved five healthy people was carried out to validate the gait-related measurements by using two force platforms as reference system. A total of 80 strides has been used for the validation procedure. The on/off status of the piezoresistive sensors placed on toe and heel has been analyzed by applying a threshold-based procedure in order to compute the duration of the stride, as well the stance and swing phase. As for the center of pressure (CoP), the sensor outputs were post-processed to carry put the displacement of the CoP during the stride. The absolute error (AE) and the median absolute error (MAE) have been computed to evaluate the accuracy of the insole to measure the gait events and the gait phase duration in comparison of force platform outputs. Moreover, the correlation between the CoP displacements computed through the two sensor systems was computed, as well the root mean square error (RMSE). The gait phase duration was associated with a MAE lower than 0.05 s both considering the stance and the swing; vice versa a MAE up to 0.16 s was found for the identification of the events. Considering the CoP, the average correlation coefficient was found equal to 0.92; with a RMSE up to 3.2 cm. These findings allow us to assess the ability of the realized insole in the measurement of the gait phases duration; whereas the CoP measurement should be considered viable only if it is sufficient to know the trend of the displacement rather than the accurate value. Considering the achievement, such insole could be used for robotic application when seeking to develop control system for lower limb exoskeleton.
Classification of Amyotrophic Lateral Sclerosis Patients using speech signals

The neurological condition known as Amyotrophic lateral sclerosis (ALS), which progresses and is irreversible, starts with early signs including speech and swallowing difficulties. The early acoustic presentation of speech and voice problems can be difficult to identify for both human experts and automated systems. In order to address this challenge we developed a non-invasive machine learning model for ALS diagnosis, this study proposes a voice assessment approach for an automatic system that can distinguish between healthy individuals and ALS patients. Specifically, our work focuses on analyzing continuous production of the vowel sounds /a/ and /i/using a feature extraction technique known as the wavelet time scattering transform which is not yet explored for ALS disease detection. In order to select the most relevant features from the extracted set of 84 features, we employed a correlation-based feature selection approach, using which we identified features with a correlation coefficient lower than 0.75. The selected features were then subjected to principal component analysis (PCA) to reduce the dimensionality of the dataset, resulting in a final set of 10 features. The resulting PCA-based model achieved an accuracy of 84.2% using support vector machine (SVM) for classification, with a sensitivity and specificity of 77.8% and 90%, respectively.
Enhancing H-Infinity Norm Estimation Using Local LPM/LRM Modeling: Applied to an AVIS

Accurate uncertainty modeling is of key importance in high performance robust control design. The aim of this paper is to develop a new uncertainty modeling procedure that enhances the accuracy of the H∞ norm. A frequency response based approach is adopted. The key novelty of this paper is a new method to address the intergrid error using local parametric modeling methods. These local polynomial and rational models enhance the estimates at the discrete frequency grid. Moreover, the presented methods are shown to enhance the intergrid error estimate. This is illustrated using simulations and experiments on an industrial active vibration isolation system. Compared to the local polynomial models, local rational models are able to handle lightly-damped resonances using far fewer data points.
Print Process Development for Ag-Ink Thermoformable Conductive Traces Utilizing Direct Write technique for In-Mold Printed Electronics

Wire harnesses contribute a significant portion of the weight on the automotive platform. In-mold electronics provide weight reduction pathways by integrating the conductive traces into the automotive interior body panels. Additive print processes provide a method to fabricate circuits through soft tooling using a number of conductive and dielectric materials. However, the print-process recipes and process-property interactions on thermo-formable flexible substrates are scarce. In this paper, a process recipe has been developed by studying different printing and post printing parameters for stretchable conductive silver ink via the direct write technique. Direct write methods have been implemented on the nScrypt platform. A thermo-forming capable high-impact polymer sheet (HIPS) substrate has been used for the study. The printed traces have been sintered post-print. The cross-section of the printed lines has been measured using white-light interferometry. The effect of the process parameters on the printed line resistivity has been studied.
Identification of Students Errors in Solving Indirect Analogical Problems Based on Analogical Reasoning Components

The purpose of this study was to identify students’ errors in solving indirect analogical problems based on analogical reasoning components. Using qualitative design approach, the study was conducted at two schools in two different regions of Nusa Tenggara Barat, Indonesia. The instrument used was analogical problems consisting of two problems where the source problem was symbolic quadratic equation problemand the target problems wastrigonometric equation problem. The findings of this study indicate that students could make error in each of structuring, mapping, applying, or verifying stage. But, errors can occur also in the combination of those anaogical reasoning components, such as structuring-applying.
Novel Dual Band High Gain Antenna Array Using Aperture Coupled Feeding for X-Band Radar

An aperture coupled feeding technique based dual band high gain 4 × 4 microstrip antenna array has been presented here for X-band radar and satellite communication. The designed array consists of three layers which are corporate feed network, 2D array of radiating patches, and coupling apertures on the ground plane. The novelty of the work is the designing of a new asymmetric H-shaped slot for the aperture coupled antenna (ACA) element. The antenna exhibits dual resonances in X-band at frequencies 8.45 and 11.15 GHz, those are altered by changing ACA's physical dimensions. The three layers of the array are printed on two Taconic TLY-5 dielectric materials, which are stacked over each other. The designed array is realized on overall size of 100×100×2.09 mm3 and having return loss bandwidth (BW) of 3.2 % in both bands that covers frequencies 8.53 to 8.81 GHz and 10.8 to 11.15 GHz. In two bands array radiates with gain of 17.1 and 19.34 dBi, and efficiencies of 90.7 % and 94.1 % respectively. The array exhibits considerable low cross-polarization of < - 14.2 dB and <- 36.2 dB at two operating frequencies.
Influence of temperature on the quality of operation of an analog reading system for MEMS structures

This paper presents a static analysis of the properties of the integrated capacitive analog readout circuit for a wide range of operating temperatures. Comparison of identical test-benches for several application-specific integrated circuits (ASICs) is presented and discussed. The comparison was extended by modification of a single test set-up in the form of removing die-package interconnections of the ASIC inputs. Thus, influence of the package and test board gets wholly removed. The performed analysis identifies the temperature-relation of the ASIC operation consistence, including temperature influence on observed signal noise levels. Implications of the presented analyses are discussed along with the possible continuation of practical studies on the thermal dependence of the ASIC operation.
The Function of Crop pest and disease identification based on the improved ConvNeXt Network model

A ConvNeXt-ECA network model based on the improved ConvNeXt network is designed for the problem that the pest identification method based on traditional machine learning and simple neural network is not ideal for crop pest identification with unbalanced data, unclear features and multiple categories. The model is based on the ConvNeXt network model as the backbone network, using migration learning to achieve the sharing of pre-trained weight parameters and combining with the attention mechanism to enhance the feature fusion capability. Finally, 16 plant species with a total of 27 types of diseases were studied with a total of 34,200 images, and the training set, validation set and test set were divided in the ratio of 6:2:2. The model converged significantly faster during the experimental training compared with VGG19, GoogLeNet, ResNet50 and ConvNeXt networks. The experimental results show that the accuracy of the improved ConvNeXt network-based crop pest and disease intelligent recognition model reaches 96.73%, while the ablation experiments demonstrate the improvement of the model performance by the optimization method proposed in this paper.
In-situ Proof-of-Transit for Path-Aware Programmable Networks

This paper presents a scalable and efficient solution for secure network design that involves the selection and verification of network paths. The proposed approach addresses the challenge of extending compliance policies to cover path-aware programmable networks by decoupling the routing/forwarding mechanisms from the Proof-of-Transit (PoT) implementation. Thus, two concepts are bounded: i) a source routing mechanism based on a fixed routeID representing a unique identifier per path, which serves as a key for the PoT lookup table; ii) the “in situ” that allows to collect telemetry information in the packet while the packet traverses a path. The former enables path selection with policy at the edge, while the later allows to perform path verification without extra probe-traffic. A P4 programmable language prototype demonstrates the effectiveness of this approach to protect against deviation attacks with low overhead. The results show a significant reduction in network’s forwarding state for fat-tree topologies depending on the workload per path (flows/path).
Impact of the tropical cyclone Nilam on the vertical distribution of carbon monoxide over Chennai on the Indian peninsula

The present study investigates the impact of tropical cyclone (TC) Nilam on the vertical distribution of carbon monoxide (CO) over Chennai in southern India. Measurements of OZone and water vapour by Airbus In‐service airCraft (MOZAIC) profiles of CO measured during October–November 2012 were analysed. The vertical profiles of CO on 15 October and 2 November were influenced by convective motions with a significant decrease in outgoing long‐wave radiation (OLR) compared to that on normal days of observations. The near‐surface mixing ratios of CO (185 ± 24 ppbv) in convectively influenced conditions were much lower than those measured during normal days (>210 ppbv). The occurrence of minimum CO values at altitudes of 4–6 km coincided with the lowest lapse rate (LR) value of 4–5 °C/km. The uplift of surface air masses led to a large increase in the CO mixing ratio in the free troposphere. The differences in CO between the lower and free troposphere were relatively small (40–50 ppbv) and large (90–100 ppbv) during convective and normal days, respectively. In the lower troposphere, elevated values of CO (>250 ppbv) were measured for lighter wind speeds from the north, while lower values (<150 ppbv) were measured for strong winds from the western sectors. The Model for OZone And Related chemical Tracers (MOZART‐4) and Chemistry Climate Model 2 (CCM2) simulations did not capture the detailed features of the CO profiles. For cyclone‐influenced measurements in the lower troposphere, MOZART‐4 underestimated the CO values by approximately 13%, but CCM2 overestimated the CO values by 70%. In the upper troposphere, MOZART‐4 and CCM2 underestimated the observations by 6–8% and 12–22%, respectively. The mixing scheme of the model and simulated concentrations seem to be the key causes of disagreements. However, the performances of both the MOZART‐4 and CCM2 simulations were better for convection‐free normal days.
The Effect of Errors in Means, Variances, and Covariances on Optimal Portfolio Choice

There is considerable literature on the strengths and limitations of meanvariance analysis. The basic theory and extensions of MV analysis are discussed in Markowitz (1987) and Ziemba and Vickson (1975). Bawa, Brown and Klein (1979) and Michaud (1989) review some of its problems…
The strong decay of higher vector ϒ (11020) state in the framework of non-relativistic quark model

An analytical study of a source of Beauty mesons (B mesons) by the Strong decay of ϒ (11020) is performed to obtain various modes of B mesons. The non-relativistic quark model framework is used to predict the masses of the bottomonium mesons. The strong decay of the ϒ (11020) state is calculated utilizing Quark Pair Creation model. In addition, the branching ratio of the strong decay has been calculated for each decay width and using them to estimate the number of B-meson pairs for each strong decay width. The results show reasonable agreement with recent Particle Data Group data, in particular with the total strong decay width of ϒ (11020). The ϒ (11020) particle is expected to be a good candidate for the conventional ϒ (6S) state and provides both types of strange and non-strange B mesons. We found new conclusions for the strong decay widths of the ϒ (11020) in the relativistic phase space. The strong width of the B ∗ B ∗ channel is predicted to be the highest width by the ratio ( ∼(cid:4) 51%) concerning higher vector ϒ (11020) State. In addition, the speciﬁc B s B ∗ s channel is expected to be the highest width relative to higher ϒ resonances.
Interplanetary Shocks Inducing Magnetospheric Supersubstorms (SML < −2500 nT): Unusual Auroral Morphologies and Energy Flow

We present case studies of two interplanetary shock-induced supersubstorms (SSSs) with extremely high intensities (peak SML −4418 and −2668 nT) and long durations (∼1.7 and ∼3.1 hr). The events occurred on 2005 January 21 and 2010 April 5, respectively. It is shown that these SSSs have a different auroral evolution than a nominal Akasofu-type substorm. The auroras associated with the SSSs did not have the standard midnight onset and following expansion. Instead, at the time of the SML index peak, the midnight sector was generally devoid of intense auroras, while the most intense auroras were located in the premidnight and postmidnight magnetic local times. Precursor energy input through magnetic reconnection was insufficient to balance the large ionospheric energy dissipation during the SSSs. It is argued that besides the release of stored magnetotail energy during the SSSs, these were powered by additional direct driving through both dayside magnetic reconnection and solar wind ram energy.