Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy management of a wireless sensor network at application level

Energy is a key resource in Wireless Sensor Networks (WSNs), especially when sensor nodes are powered by batteries. This thesis is investigates how to save energy of the whole WSN, at the application level, thanks to control strategies, in real time and in a dynamic way. The first energy management strategy investigated is based on Model Predictive Control (MPC). The choice of MPC is motivated by the global objectives that are to reduce the energy consumption of the set of sensor nodes while ensuring a given service, named mission, for the sensor network. Moreover, a set of constraints on the binary control variables and on the sensor modes must be fulfilled. The second energy management strategy at the application level is based on a Hybrid Dynamical System (HDS) approach. This choice is motivated by the hybrid inherent nature of the WSN system when energy management is considered. The hybrid nature basically comes from the combination of continuous physical processes, namely, the charge / discharge of the node batteries; while the discrete part is related to the change in the functioning modes and the Unreachable condition of the nodes. The proposed strategies are evaluated and compared in simulation on a realistic test-case. Lastly, they have been implemented on a real test-bench and the results obtained have been discussed.
Real-Time Light-Guided Vocal Fold Injection via the Cricothyroid Membrane in Unilateral Vocal Fold Paralysis: A Human Pilot Study

Objectives. Vocal fold injection (VFI) via the cricothyroid (CT) membrane is used to treat various diseases affecting the vocal folds. The technical challenges of this technique are mainly related to the invisibility of the needle. Real-time light-guided VFI (RL-VFI) was recently developed for injection under simultaneous light guidance in the CT approach. Herein, we present the first clinical trial of RL-VFI, in which we investigated the feasibility and safety of this new technique in unilateral vocal fold paralysis (VFP). Methods. This prospective pilot study enrolled 40 patients, who were treated with RL-VFI for unilateral VFP between September 2020 and August 2021. Adverse events were monitored during the procedure and for 4 weeks postoperatively. The Voice Handicap Index-10, the GRBAS (grade, roughness, breathiness, asthenia, and strain) scale, aerodynamic studies, and acoustic analyses were evaluated to compare the voice improvement after 4 weeks with the baseline values. Results. The needle tip was intuitively identified by the red light. The mean procedure time was 95.6±40.6 seconds for the initial injection, while the additional injection required 79.2±70.5 seconds. The injection was performed under light guidance without additional manipulation after the needle reached the intended point. No acute or delayed adverse events were reported. Among the 40 patients, 36 completed voice analyses after 4 weeks. Subjective and objective voice parameters, including the Voice Handicap Index-10, GRBAS scale, maximum phonation time, mean expiratory airflow, fundamental frequency, jitter, shimmer, and noise-to-harmonics ratio improved significantly after RL-VFI (P<0.05), while the expiratory volume was maintained. Conclusion. RL-VFI is feasible and safe for treating patients with unilateral VFP. This technique is anticipated to improve the precision and safety of the CT approach in the treatment of unilateral VFP. This study provides a rationale for further structured clinical studies.
Uncovering and mitigating unsafe program integrations in Android

Android’s design philosophy encourages the integration of resources and functionalities from multiple parties, even with different levels of trust. Such program integrations, on one hand, connect every party in the Android ecosystem tightly on one single device. On the other hand, they can also pose severe security problems, if the security design of the underlying integration schemes is not well thought-out. This dissertation systematically evaluates the security design of three integration schemes on Android, including framework module, framework proxy and 3rd-party code embedding. With the security risks identified in each scheme, it concludes that program integrations on Android are unsafe. Furthermore, new frameworks have been designed and implemented to detect and mitigate the threats. The evaluation results on the prototypes have demonstrated their effectiveness. UNCOVERING AND MITIGATING UNSAFE PROGRAM INTEGRATIONS IN ANDROID by Xiao, Zhang B.S., University of Science and Technology of China, 2010 Dissertation Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer & Information Science and Engineering Syracuse University May 2016 © Copyright 2016 Xiao, Zhang All Rights Reserved
CT-Net: An Efficient Network for Low-Altitude Object Detection Based on Convolution and Transformer

With the growing popularity of civilian unmanned aerial vehicles (UAVs), unauthorized flights are on the rise accordingly. Therefore, it is critical to detect low-altitude UAVs for protecting personal privacy and public safety. Though substantial progress has been made in UAV detection, the existing detection methods still have problems in balancing the detection accuracy, the model size, and the detection speed. To address these limitations, this article proposes a novel deep learning method named convolution–transformer network (CT-Net). First, the attention-enhanced transformer block (AETB), which builds a feature-enhanced multihead self-attention (FEMSA), is introduced into the backbone of the network to improve the feature extraction ability of the model. Then, a lightweight bottleneck module (LBM) is utilized to control the computation load and reduce the parameters. Finally, we present a directional feature fusion structure (DFFS) to improve the accuracy of detection when processing multiscale objects, especially small-size objects. The proposed scheme achieves 0.966 mAP with the input size of 640 $\times640$ pixels on our low-altitude small-object dataset, and the performance is superior to YOLOv5. Furthermore, the experimental result on MS COCO shows that the CT-Net can outperform the current state-of-the-art detectors by a large margin. Thus, it is feasible to apply CT-Net to low-altitude small-object detection according to the experimental results.
Joint generative and camera-aware clustering for unsupervised domain adaptation on person re-identification

Abstract. Existing supervised person re-identification (Re-ID) methods demonstrate excellent performance. However, their performances suffer degradation when tested on an unseen different distributed domain. Generative adversarial network-based (GAN-based) and clustering- or pseudolabel-based methods are proposed to alleviate this problem. Due to the transfer scheme and the ignorance of correlations between the style-transferred and the original target images, the performance of GAN-based methods is unsatisfactory. We resolve these problems by jointly employing a generative strategy and performing camera-aware clustering for the target domain. Style-transferred images are generated from source cameras to target cameras, and then they are merged into the target domain selectively after exploiting their domain-specific discriminative information. To reduce the noise in generated images, we propose a domain-level boundary separation loss to group the transferred images and push them away from the original target images. The camera-level neighborhood-based clustering is proposed to learn well-clustered features in a camera-aware manner. Extensive experiments on two commonly used person Re-ID datasets demonstrate that our proposed method can achieve state-of-the-art performance.
Optimal Band Selection for Airborne Hyperspectral Imagery to Retrieve a Wide Range of Cyanobacterial Pigment Concentration Using a Data-Driven Approach

Understanding the concentration and distribution of cyanobacteria blooms is an important aspect of managing water quality problems and protecting aquatic ecosystems. Airborne hyperspectral imagery (HSI)—which has high temporal, spatial, and spectral resolutions—is widely used to remotely sense cyanobacteria bloom, and it provides the distribution of the bloom over a wide area. In this study, we determined the input spectral bands that were relevant in effectively estimating the main two pigments (PC, Phycocyanin; Chl-a, Chlorophyll-a) of cyanobacteria by applying data-driven algorithms to HSI and then evaluating the change in the spatio-temporal distribution of cyanobacteria. The input variables for the algorithms consisted of reflectance band ratios associated with the optical properties of PC and Chl-a, which were calculated by the selected hyperspectral bands using a feature selection method. The selected input variable was composed of six reflectance bands (465.7–589.6, 603.6–631.8, 641.2–655.35, 664.8–679.0, 698.0–712.3, and 731.4–784.1 nm). The artificial neural network showed the best results for the estimation of the two pigments with average coefficients of determination 0.80 and 0.74. This study proposes relevant input spectral information and an algorithm that can effectively detect the occurrence of cyanobacteria in the weir pool along the Geum river, South Korea. The algorithm is expected to help establish a preemptive response to the formation of cyanobacterial blooms, and to contribute to the preparation of suitable water quality management plans for freshwater environments.
Structure of the Yeast Cell Wall Integrity Sensor Wsc1 Reveals an Essential Role of Surface-Exposed Aromatic Clusters

In the yeast Saccharomyces cerevisiae and other ascomycetes, the maintenance of cell wall integrity is governed by a family of plasma-membrane spanning sensors that include the Wsc-type proteins. These cell wall proteins apparently sense stress-induced mechanical forces at the cell surface and target the cell wall integrity (CWI) signaling pathway, but the structural base for their sensor function is yet unknown. Here, we solved a high-resolution crystal structure of the extracellular cysteine-rich domain (CRD) of yeast Wsc1, which shows the characteristic PAN/Apple domain fold with two of the four Wsc1 disulfide bridges being conserved in other PAN domain cores. Given the general function of PAN domains in mediating protein–protein and protein–carbohydrate interactions, this finding underpins the importance of Wsc domains in conferring sensing and localization functions. Our Wsc1 CRD structure reveals an unusually high number of surface-exposed aromatic residues that are conserved in other fungal CRDs, and can be arranged into three solvent-exposed clusters. Mutational analysis demonstrates that two of the aromatic clusters are required for conferring S. cerevisiae Wsc1-dependent resistance to the glucan synthase inhibitor caspofungin, and the chitin-binding agents Congo red and Calcofluor white. These findings suggest an essential role of surface-exposed aromatic clusters in fungal Wsc-type sensors that might include an involvement in stress-induced sensor-clustering required to elicit appropriate cellular responses via the downstream CWI pathway.
Chronic pain and long‐term dementia risk in older adults: Results from a 24‐year longitudinal study

Chronic pain (CP) was associated with cognitive impairment in previous studies. However, the longitudinal association between CP and dementia remains under debate. We aimed to assess the prospective link between CP and long‐term dementia risk in a population‐based cohort of older participants, considering covariables linked to CP and cognitive functioning.
Air-gap silicon nitride chirped mirror for few-cycle pulse compression

We propose new design solution for broadband chirped mirrors. It consists in application of silicon nitride with air-gap interlayers. This proposal is the first application of silicon nitride to a chirped mirror, to the best of our knowledge. The proposed material combination allows to realize CMs supplying bandwidth from ultraviolet to near infrared. Using this idea we have made design of silicon nitride - air-gap chirped mirror for compression of few-cycles laser pulses in the near-infrared. Our CM provides high reflectivity and good dispersion properties in the wavelength range 400-1200 nm. Time domain analysis shows that designed CM allows to operate on few-cycles laser pulses. (Received September 14, 2008; accepted September 26, 2008)
Research on the Mechanism of Influencing Factors of the Urban Road Traffic Operation State

Profound understanding of an interaction mechanism among influencing factors in the perspective of urban road traffic operation is of great significance for scientific and effective urban congestion management. In this paper, 6 indicators are proposed for the road traffic operation in the aspects of average speed of road sections, regional traffic index, and number of traffic incidents. Based on this, 4 major influencing factors and 12 measurable subinfluencing factors are proposed according to urban traffic supply and demand, and the SEM (structural equation model) is established to find out their interaction mechanism. And then, several sets of local traffic data collected in Shenzhen are used for model fitting, validation, and path analysis. The mathematical results show that all 6 indicators affiliated to the road traffic operation have a good explanation when it comes to the change of operation status. Among 4 latent variables in the traffic supply and demand aspect, the service equipment operation level and control equipment operation level can positively influence the road traffic operation status, while the urban traffic demand plays a negative role. Complex interactions among four latent variables are further pointed out. Finally, on the basis of the path coefficient relationship among the influencing factors, scientific suggestions and guidance are provided for urban road management control.
A Novel Porous PDMS-AgNWs-PDMS (PAP)-Sponge-Based Capacitive Pressure Sensor

The development of capacitive pressure sensors with low cost, high sensitivity and facile fabrication techniques is desirable for flexible electronics and wearable devices. In this project, a highly sensitive and flexible capacitive pressure sensor was fabricated by sandwiching a porous PAP sponge dielectric layer between two copper electrodes. The porous PAP sponge dielectric layer was fabricated by introducing highly conductive silver nanowires (AgNWs) into the PDMS sponge with 100% sucrose as a template and with a layer of polydimethylsiloxane (PDMS) film coating the surface. The sensitivity of the PAP sponge capacitive pressure sensor was optimized by increasing the load amount of AgNWs. Experimental results demonstrated that when the load amount of AgNWs increased to 150 mg in the PAP sponge, the sensitivity of the sensor was the highest in the low-pressure range of 0–1 kPa, reaching 0.62 kPa−1. At this point, the tensile strength and elongation of sponge were 1.425 MPa and 156.38%, respectively. In addition, the specific surface area of PAP sponge reached 2.0 cm2/g in the range of 0–10 nm pore size, and showed excellent waterproof performance with high elasticity, low hysteresis, light weight, and low density. Furthermore, as an application demonstration, ~110 LED lights were shown to light up when pressed onto the optimized sensor. Hence, this novel porous PAP-sponge-based capacitive pressure sensor has a wide range of potential applications in the field of wearable electronics.
Antibiotics in shallow groundwater underlying urban informal settlements in developing countries: influence of on-site sanitation practices and risk assessment

ABSTRACT This study investigated the influence of on-site sanitation practices (OSS) on antibiotics in shallow groundwater underlying an informal settlement in Kampala City (Uganda) and the resulting antibiotic resistance risks. Ten antibiotics (including sulfonamides, fluoroquinolones, quinolones, penicillins and tetracyclines) were investigated in 17 groundwater sources in relation to physico-chemical and bacteriological water quality parameters. Seven antibiotics were detected, at a maximum total concentration of 1,400 ng/L during the dry season and 730 ng/L during the wet season. A significant positive correlation was observed between sulfathiazole and Escherichia coli (p < 0.001), supported by principal component analysis. Hierarchical cluster analysis showed grouping of antibiotics with parameters usually associated with OSS (E. coli, chlorides, nitrates, sodium and sulphates). Over 65% of the locations presented a high risk for antibiotic resistance during the dry season. This study showed that the population in informal settlements is exposed to a high risk of antibiotic resistance, influenced by OSS.
Pedestrian count estimation using texture feature with spatial distribution

We present a novel pedestrian count estimation approach based on global image descriptors formed from multi-scale texture features that considers spatial distribution. For regions of interest, local texture features are represented based on histograms of multi-scale block local binary pattern, which jointly constitute the feature vector of the whole image. Therefore, to achieve an effective estimation of pedestrian count, principal component analysis is used to reduce the dimension of the global representation features, and a fitting model between image global features and pedestrian count is constructed via support vector regression. The experimental result shows that the proposed method exhibits high accuracy on pedestrian count estimation and can be applied well in the real world.
Mini-trampoline vibration exciter- Force measurements

A mini-trampoline has been previously used as a vibration exciter by Koss, et al for the structural excitation of a foot- bridge. The jumper on the mini-trampoline is “bobbing”, just not lifting off the membrane to provide dynamic force to excite a foot- bridge into vibration in order to determine the stiffness and natural frequency of the bridge. The stiffness and natural frequency were identified as being 10.4 MN/m and 10.6 Hz respectively. Results of bobbing tests are presented to determine the accuracy of using a jumper’s inertial force, mass of person multiplied by the body acceleration at the hip position, as being the transmitted force to the structure on which the mini- trampoline is stationed. The tests consisted of using two people with body masses of 55 kg and 100 kg and only employing three supporting legs that were instrumented to measure force transmitted to the ground. The three measured force signals were summed and analyzed using Matlab® software. A fourth channel was used to measure hip body acceleration for the case of the accelerometer strapped to the hip using a kidney belt. Analyzed data from the tests demonstrate that the first two inertial force harmonic amplitudes, fundamental and first overtone, compare well with the measured transmitted force amplitudes through the three legs for the 50 kg jumper. Comparisons for the 100 kg person were poor. Also, normalized forcefrequency spectra will be presented to estimate what hip body acceleration is required for the jumper to just lift off from the trampoline membrane.
Neural Networks Analysis of Steel Plate Processing Augmented by Multi‐objective Genetic Algorithms

An earlier neural network analysis of processing of steel plates through hot rolling was subjected to a further refined analysis through some flexible neural networks that evolved using a multi‐objective predator‐prey genetic algorithm. The original data set expressing the Yield Strength and Ultimate Tensile Strength of the rolled slabs in terms of a total of 108 process variables were subjected to a systematic pruning through this evolutionary approach, till the nitrogen content of the steel emerged as the most significant input variable. A theoretical explanation is provided for this slightly unexpected result.
Cost-Effective and Selective Fluorescent Chemosensor (Pyr-NH@SiO2 NPs) for Mercury Detection in Seawater

The release of mercury into the environment has adverse effects on humans and aquatic species, even at very low concentrations. Pyrene and its derivatives have interesting fluorescence properties that can be utilized for mercury (Hg2+) ion sensing. Herein, we reported the highly selective pyrene-functionalized silica nanoparticles (Pyr-NH@SiO2 NPs) for chemosensing mercury (Hg2+) ions in a seawater sample. The Pyr-NH@SiO2 NPs were synthesized via a two-step protocol. First, a modified Stöber method was adopted to generate amino-functionalized silica nanoparticles (NH2@SiO2 NPs). Second, 1-pyrenecarboxylic acid was coupled to NH2@SiO2 NPs using a peptide coupling reaction. As-synthesized NH2@SiO2 NPs and Pyr-NH@SiO2 NPs were thoroughly investigated by 1H-NMR, FTIR, XRD, FESEM, EDS, TGA, and BET surface area analysis. The fluorescent properties were examined in deionized water under UV-light illumination. Finally, the developed Pyr-NH@SiO2 NPs were tested as a chemosensor for Hg2+ ions detection in a broad concentration range (0–50 ppm) via photoluminescence (PL) spectroscopy. The chemosensor can selectively detect Hg2+ ions in the presence of ubiquitous ions (Na+, K+, Ca2+, Mg2+, Ba2+, Ag+, and seawater samples). The quenching of fluorescence properties with Hg2+ ions (LOD: 10 ppb) indicates that Pyr-NH@SiO2 NPs can be effectively utilized as a promising chemosensor for mercury ion detection in seawater environments.
EV charging behaviour analysis and modelling based on mobile crowdsensing data

With the growing application of electric vehicles (EVs), it is of great significance to have a deep understanding of EV users driving and charging patterns for charging forecasting. However, the rapid growth scale of EV taxis with charging patterns that are closely coupled with human behaviours of temporal-spatial charging choices was not compatible with most previous coordinated strategies. Unlike the majority of existing approaches, a large volume of second-level EV global positioning system (GPS) data was used to study the behaviour patterns of EV users. In practise, a mobile crowd-sensing system that records GPS data and transmits information to the server was deployed in a fleet of electric-taxi cabs in Shenzhen, China, making it possible to record the exact behaviour of each vehicle. Travelling and charging statuses of EVs were recorded and analysed into different characteristics of behaviour for each user. The load forecast methods proved to be more effective with more knowledge of both history and real-time data.