Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Metal Frame and Adhesive on Thermally-Induced Warpage and Stress of 2.5D Packages: Experimental and Numerical Studies

This paper aims to investigate the thermally induced warpage and stress of 2.5D packages with and without a reinforced metal frame experimentally and numerically. The consistent results between shadow moiré experiment and the finite element method (FEM) show that thermally induced warpage for 2.5D packages can be reduced by using a metal frame. The underfill stresses responsible for interfacial delamination and cracking in this package under thermal cycling are further analyzed using the validated FEM model. The location of underfill singular-feature stress corresponding to the delamination and crack has been identified. The results suggest that the low coefficient of thermal expansion (CTE) of substrate can reduce both package warpage and the underfill stress. And metal frame CTE, more pronounced than its modulus, increases with decreasing package warpage, but with increasing underfill stress. This paper also found that the selection of elastic modulus of metal frame adhesive below 50 MPa can significantly decrease the package warpage. Therefore, the CTE of the metal frame and the modulus of its adhesive are found to play important roles on controlling warpage of the packages and underfill stress, and should be carefully selected for improving both manufacturing and service reliabilities.
A General Class of Bayesian Lower Bounds Tighter than the Weiss-Weinstein Family

In this paper, Bayesian lower bounds (BLBs) are obtained via a general form of the Pythagorean theorem where the inner product derives from the joint or the a-posteriori probability density function (pdf). When joint pdf is considered, the BLBs obtained encompass the Weiss-Weinstein family (WWF). When a-posteriori pdf is considered, by resorting to an embedding between two ad hoc subspaces, it is shown that any “standard” BLBs of the WWF admits a “tighter” form which upper bounds the “standard” form. Interestingly enough, this latter result may explain why the “standard” BLBs of the WWF are not always as tight as expected, as exemplified in the case of the Bayesian Cramer-Rae Bound. As a consequence an updated definition of efficiency is proposed, as well as the introduction of an updated class of efficient estimators.
Asymptotically Throughput Optimal Scheduling for Energy Harvesting Wireless Sensor Networks

In this paper, we investigate a single-hop wireless sensor network in which a fusion center (FC) collects data packets from <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> energy harvesting (EH) sensor nodes. Energy harvested by each node is stored without battery overflow and leakage at that node. The FC schedules <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> nodes over its mutually orthogonal channels to receive data from them in each time slot. The FC knows neither the statistics of EH processes nor the battery states of nodes. The FC solely has information on consequences of previous transmission attempts. We aim for obtaining an efficient and simple policy achieving maximum throughput in this network. The nodes are data backlogged and the data transmission only depends on the harvested energy of the scheduled nodes. A node can transmit data whenever it is scheduled, provided that it has sufficient energy. We propose a simple policy, <italic>uniforming random ordered policy (UROP)</italic>, for the problem. We exhibit that the UROP is nearly throughput-optimal over finite time horizons for a broad class of EH processes. We also prove that for <italic>general</italic> EH processes, UROP achieves <italic>asymptotically optimal throughput</italic> over the infinite time horizon under infinite capacity battery assumption. Numerical results indicate that even with finite-capacity batteries, UROP achieves near-optimal throughput over finite time horizons. We believe that UROP is applicable to much wider area than EH wireless sensor networks.
A Gaussian Process Regression for Natural Gas Consumption Prediction Based on Time Series Data

For several economical, financial and operational reasons, forecasting energy demand becomes a key instrument in energy system management. This paper develops a natural gas forecasting approach, which consists of two major phases: 1) it classifies the natural gas consumption daily pattern sequences into different groups with similar attributes. 2) the design and training of multiple autoregressive Gaussian Process models phase is carried out using the Algerian natural gas market data together with exogenous inputs consisting in weather (temperature) and calendar (day of the week, hour indicator) factors. The main novelty in this work consists of the investigation of multiple different clustering techniques for better analysis and clustering of natural gas consumption data. The impact of the obtained clusters, by each technique, is then summarized and evaluated with respect to the prediction accuracy.
Integrating the aesthetic value of landscapes and biological diversity

As a cultural ecosystem service, the aesthetic value of landscapes contributes to human well-being, but studies linking biodiversity and ecosystem services generally do not account for this particular service. Therefore, congruence between the aesthetic perception of landscapes, ecological value and biodiversity remains poorly understood. Here, we describe the conceptual background, current methodologies and future challenges of assessing landscape aesthetics and its relationship with biodiversity. We highlight the methodological gaps between the assessment of landscape aesthetics, ecological diversity and functioning. We discuss the challenges associated with connecting landscape aesthetics with ecological value, and the scaling issues in the assessment of human aesthetics perception. To better integrate aesthetic value and ecological components of biodiversity, we propose to combine the study of aesthetics and the understanding of ecological function at both the species and landscape levels. Given the urgent need to engage society in conservation efforts, this approach, based on the combination of the aesthetic experience and the recognition of ecological functioning by the general public, will help change our culture of nature and promote ecologically oriented conservation policies.
Sensorless Control of Standalone Brushless Doubly Fed Induction Generator Feeding Unbalanced Loads in a Ship Shaft Power Generation System

The standalone brushless doubly fed induction generator (BDFIG) has demonstrated excellent energy-saving performance in ship shaft power generation applications. As a standalone system, it exhibits unbalanced terminal voltages and poor performance under unbalanced loads. However, the existing control scheme of grid-connected BDFIGs cannot be directly applied to stabilize the amplitude and frequency of terminal voltage when the rotor speed and electrical load vary. This paper presents a new sensorless control scheme for the standalone BDFIG under unbalanced load conditions in the ship shaft power generation system. A second-order generalized integrator-based quadrature signal generator is introduced to realize the rotor speed observer for the standalone BDFIG feeding unbalanced loads. The compensation method of negative-sequence power winding voltage is proposed to eliminate the negative-sequence component of the unbalanced power winding voltage. Comprehensive experiments are carried out on a prototype BDFIG with and without the compensation of negative-sequence power winding voltage. The good performance of the proposed sensorless control scheme is verified by the experimental test results.
Bearing-Only Multi-Target Localization for Wireless Array Networks: A Spatial Sparse Representation Approach

Bearing-only multi-target localization (BOMTL) using multiple sensors is generally required to solve the sophisticated data association problem which determines a designated sensor measurement originated from a particular target. In this paper, a novel spatial sparse representation based BOMTL method is proposed by fully utilizing a wireless array network structure. With array spatial features, the BOMTL problem can be formulated as a binary sparse vector recovery problem using the converted “pseudo-measurements” in frequency domain. The proposed method transforms the source location estimation problem into a spatial sparse representation (SSR) framework, which avoids dealing with the conventional data association. With orthogonal matching pursuit (OMP) exploiting the binary property of the sparse vector to be estimated, we develop a BOMTL-OMP algorithm to reconstruct the sparse vector. The numerical simulations demonstrate the performance of the proposed method.
Multisource I-Vectors Domain Adaptation Using Maximum Mean Discrepancy Based Autoencoders

Like many machine learning tasks, the performance of speaker verification (SV) systems degrades when training and test data come from very different distributions. What's more, both training and test data themselves could be composed of heterogeneous subsets. These multisource mismatches are detrimental to SV performance. This paper proposes incorporating maximum mean discrepancy (MMD) into the loss function of autoencoders to reduce these mismatches. MMD is a nonparametric method for measuring the distance between two probability distributions. With a properly chosen kernel, MMD can match up to infinite moments of data distributions. We generalize MMD to measure the discrepancies of multiple distributions. We call the generalized MMD domainwise MMD. Using domainwise MMD as an objective function, we propose two autoencoders, namely nuisance-attribute autoencoder (NAE) and domain-invariant autoencoder (DAE), for multisource i-vector adaptation. NAE encodes the features that cause most of the multisource mismatch measured by domainwise MMD. DAE directly encodes the features that minimize the multisource mismatch. Using these MMD-based autoencoders as a preprocessing step for PLDA training, we achieve a relative improvement of 19.2% EER on the NIST 2016 SRE compared to PLDA without adaptation. We also found that MMD-based autoencoders are more robust to unseen domains. In the domain robustness experiments, MMD-based autoencoders show 6.8% and 5.2% improvements over IDVC on female and male Cantonese speakers, respectively.
A Mindfulness-Based Intervention: Differential Effects on Affective and Processual Evolution.

OBJECTIVES A 20-minutes-a-day, self-help, mindfulness-based intervention was conducted for 6 weeks with a French community sample. First, the intervention effects on affective and functioning variables were evaluated. Then, a differential approach was used to examine improvement potentiality and the perceived benefits of mindfulness according to the participants' baseline mindfulness competencies. METHOD Participants were non-randomly assigned to a control group on the waiting list (n = 44) or a mindfulness group (n = 47). Self-report measures assessed anxiety, depression, psychological distress, mindfulness, negative self-oriented cognition, and experiential avoidance. RESULTS Improvements in the variables were observed for the mindfulness group but not for the control group, with effect sizes ranging between . 53 and . 88. Low baseline levels of mindfulness predicted greater improvement in mindfulness (r = -0.55, p < .001) than high baseline levels. CONCLUSIONS Mindfulness practice elicited several positive outcomes regarding affective variables, highlighting emotional functioning changes.
Balanced Symmetrical Quasi-Reflectionless Single-and Dual-Band Bandpass Planar Filters

Microwave planar balanced single-/dual-band bandpass filters (BPFs) with symmetrical quasi-reflectionless differential-mode behavior are presented in this letter. They are made up of a direct single-/dual-band BPF branch with virtually short-ended stubs in differential-mode operation, whose input and output accesses are loaded with stub-loaded-type single-/dual-band bandstop filter (BSF) branches that are terminated with a resistor. These BSF branches exhibit a quasi-complementary transfer function with regard to the one of the BPF branch and absorb the differential-mode input-signal energy not transmitted by the filter to achieve quasi-reflectionless capabilities. The theoretical foundations of the proposed balanced quasi-absorptive single-/dual-band BPFs and synthesis examples are given. Furthermore, for experimental-demonstration purposes, microstrip prototypes of 3-GHz second-order single-band and 2.85/3.15-GHz first-order dual-band BPFs are manufactured and characterized.
MASFOG: An Efficient Mutual Authentication Scheme for Fog Computing Architecture

Fog computing is a new paradigm which extends cloud computing services into the edge of the network. Indeed, it aims to pool edge resources in order to deal with cloud's shortcomings such as latency problems. However, this proposal does not ensure the honesty and the good behavior of edge devices. Thus, security places itself as an important challenge in front of this new proposal. Authentication is the entry point of any security system, which makes it an important security service. Traditional authentication schemes endure latency issues and some of them do not satisfy fog-computing requirements such as mutual authentication between end devices and fog servers. Thus, new authentication protocols need to be implemented. In this paper, we propose a new efficient authentication scheme for fog computing architecture. Our scheme ensures mutual authentication and remedies to fog servers' misbehaviors. Moreover, fog servers need to hold only a couple of information to verify the authenticity of every user in the system. Thus, it provides a low overhead in terms of storage capacity. Finally, we show through experimentation the efficiency of our scheme.
A Novel Broadband Microstrip Patch Antenna with Small Ground Plane

A novel broadband microstrip patch antenna with a small ground plane is proposed in this paper. An additional ground radiation mode with low-frequency resonance is introduced by the small ground plane, while the patch radiation mode resonates at high frequency. The radiation patch is loaded with a pair of slots and two rows of shorting pins to obtain broadband matching. A relative bandwidth of 58.8%, from 2.11GHz-3.87GHz, is achieved for a compact size of 0. 41λ0*0. 29λ0*0. 03λ0at center operating frequency. In addition, omnidirectional radiation patterns with low cross-polarization are achieved over the operating band.
New Method for Enhancing Photon Emission Measurements Similar to 2D-Tomography

We present a new experimental method for enhancing quality and accuracy of photon emission measurements (PEM). The technique consists of taking emission images of the device rotated through several different angles. The independent information from several images is then used to numerically calculate an emission pattern, which is superior to just one single PE image. Therefore, the method also allows for spectral photon emission analysis (SPEM) in cases, where emission overlap of neighboring devices prevented SPEM analysis up to this date. This publication gives an overview of the theoretical, experimental and numerical basics of the new method. To give a proof-of-concept we apply the method to a sample case of spectral photon emission and electron temperature analysis of a ring oscillator built in 120nm technology. The obtained results are then compared to data acquired by a conventional measurement on a location of the ring oscillator (RO), where conventional analysis was possible.
Safe Avoidance Path Detection Using Multi Sensor Integration for Small Unmanned Aerial Vehicle

Achieving a robust obstacle detection system that can provide a safe avoidance path system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, a combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle regions and free space regions. This is done through the principal of object size changes and distance relationship in an image perspective. The proposed method was evaluated by conducting experiments in a real complex environment which consist of a textured and textureless obstacle. In the experiment conducted, we successfully detect and create a safe avoidance path for both situations. The textured situation gives a high success rate while textureless situation produces acceptable success rate until 60cm distance.
Correlation Analysis for Exploring Multivariate Data Sets

Correlation analysis is of great significance for exploring the multivariate data sets as it helps researchers toward an in-depth understanding of the complex interactions and relationships among variables. In this paper, we propose a correlation analysis method that identifies salient scalars for multivariate data exploration. We exploit specific mutual information metric to measure the information overlap and analyze the relationships between one scalar and other variables. Moreover, we define the information flow and introduce another metric, influence to quantify the associations among scalars of different variables. Furthermore, we integrate these two information metrics and construct a surprise-influence map for users’ interaction to identify the salient scalars. By investigating the relationships among these salient scalars, we analyze the correlations among variables. We demonstrate the applicability and effectiveness of our proposed method by applying it to different data sets.
Control and Obstacle Avoidance for an UAV Carrying a Load in Forestal Environments

Unmanned aerial vehicles (UAV) provide a wide range of applications, amongst which is load transportation. Aiming at a real application, such as delivery of medical kits for victims in disasters, it is important to include an obstacle avoidance technique in the navigation task, to avoid any obstacle that might appear along the way. Potential fields are a technique that considers objects as identical magnetic poles, such that one of them cannot get close to the other. Also, it is not necessary to create a potential map, since the vehicle can avoid the obstacles as they appear along the UAV navigation, characterizing a local decision making, not a global path-planning. In this work a UAV-cargo system is considered, navigating towards a desired position where the load should be delivered. Euler-Lagrange equations models the UAV-cargo system and its stability is guaranteed by a non-linear controller that rejects load oscillations. In such a case, the load is a modeled disturbance. To deal with obstacle avoidance, a forest-like environment is considered, and the UAV should navigate through the tree trunks till reaching the target position. Finally numerical simulations are presented to demonstrate the system performance.
ACE inhibition for severe bronchopulmonary dysplasia – an approach based on physiology

Premature infants have a high incidence of bronchopulmonary dysplasia (BPD). Systemic hypertension, arterial thickness and stiffness, and increased systemic afterload may all contribute to BPD pathophysiology by altering left ventricular (LV) function and increasing pulmonary venous congestion by lowering end‐diastolic compliance. This case series studied the usefulness of angiotensin‐converting enzyme (ACE) inhibition by measuring clinical and echocardiographic improvements in six consecutive infants with “severe” BPD unresponsive to conventional therapy. The range of gestation and birthweight were 23–29 weeks and 505–814 g, respectively. All required mechanical ventilation (including high‐frequency oscillation) and all but one were administered postnatal corticosteroids. Other treatments including sildenafil and diuretics made no clinical improvements. Captopril was started for systemic hypertension after cardiac and vascular ultrasounds which were repeated 5 weeks later. A significant reduction in oxygen (55 ± 25 to 29 ± 3%, two‐tailed P = 0.03) and ventilator requirements, and improved cardiovascular parameters were noted. This included a trend toward reduction in aorta intima media thickness [840 ± 94 to 740 ± 83 μm, P = 0.07] and an increased pulsatile diameter [36 ± 14 to 63 ± 25 μm, P = 0.04]). Improvements were observed for both systolic (increased LV output, 188 ± 13 to 208 ± 13 mL/kg/min, P = 0.046 and mean velocity of circumferential fiber shortening, 1.6 ± 0.2 to 2.5 ± 0.3 [circ/sec], P = 0.0004) and diastolic (decreased isovolumic relaxation time, 69.6 ± 8.2 to 59.4 ± 5 msec, P = 0.044) function which was accompanied by increased pulmonary vein flow. Right ventricular output increased accompanied by a significant lowering of pulmonary vascular resistance. These findings suggest that improving respiratory and cardiac indices (especially diastolic function) warrants further exploration of ACE inhibition in BPD infants unresponsive to conventional therapy.
A Novel Heterogeneous Wireless Sensor Node Deployment Algorithm With Parameter-Free Configuration

The deployment of wireless sensor nodes affects the WSN performance, such as the sensing coverage, the connectivity between sensor nodes, and the network lifetime. The deployment is much more complicated when the sensor nodes are heterogeneous and there are some environmental obstacles in an area of interest. The deployment of heterogeneous sensor nodes in an area of interest with obstacles is a challenging problem and also proven to be an NP-complete problem. This paper proposes and evaluates a wireless sensor node deployment algorithm, called DeVForce-AP. The proposed algorithm combines the benefits of the two well-known deployment algorithms, Delaunay triangulation method (D) and extended virtual force algorithm (eVForce), with the adaptive parameter (AP) tuning mechanism. The DeVForce-AP attempts to improve the sensing coverage and network lifetime of the heterogeneous wireless sensor node. The practical deployment problems, such as the environmental obstacles, the network connectivity, and the sensing coverage area, have also been addressed. The DeVForce-AP consists of two steps. In the first step, the DeVForce-AP applies the Delaunay triangulation method to find and eliminate the largest coverage hole in the area of interest. In the second step, the DeVForce-AP applies eVForce method to avoid the existence of environmental obstacles and maintain the network connectivity. Moreover, the proposed DeVForce-AP automatically adjusts its parameters to the environmental scenario. Thus, there is no need to configure the parameters of the DeVForce-AP. The simulation results show that the proposed DeVForce-AP outperforms the random deployment, the traditional Delaunay triangulation deployment, and the traditional virtual force deployment methods.