Miracle-dz/UniFAR-FTUs huggingface dataset:
A topological AUC-based biomarker ensemble method for the complex disease analysis

Complex diseases are affected by many factors, and their pathogenic mechanism is complicated, which brings difficulties to the analysis and treatment of diseases. AUC, the area under the ROC curve, is often used as a gold standard to evaluate the performance of a binary classifier. The existing methods of constructing classifier by optimizing AUC are easy to fall into local optimum, and have high time complexity, which is not suitable for real-time analysis of high-dimensional gene expression data. With the rapid development of high-throughput sequencing technology, feature selection and model estimation become the necessary means to reduce the dimension and complexity of data, and the selected important features have the potential as biomarkers to reveal the pathogenesis of diseases. In this paper, we proposed a topological AUC-based biomarker ensemble method for the complex disease analysis, which uses gene expression data and the topological information derived from the protein-protein interaction network to identify biomarkers. The main contribution is to optimize two objectives simultaneously: maximizing the AUC score and minimizing the number of selected features. We applied the proposed method to analyze two types of problems: 1) prognosis of breast cancer, 2) classification of similar diseases. The results show that our method can effectively identify a small set of biomarkers with the powerful classification ability and the biological interpretability.
Constraint-Based Rerouting mechanism to address Congestion in Software Defined Networks

In this paper, we propose a traffic rerouting mechanism to address congestion in Software-Defined networks. We employ back-tracking and constraint propagation techniques to find alternate paths to reroute multiple active flows simultaneously. Cost function is based on standard deviation of link-loads. We then compare traffic distribution and link utilisation with and without rerouting active flows. We measure and compare network performance using parameters such as total rate of transfer, jitter, and packet loss with that of Shortest Path First with no rerouting. Our proposed solution produces lower jitter, packet drops, and higher transfer rate. We finally conclude the paper by making observations and discussing the scope of the future work.
Harmonic Mitigation in Induction-Motor Drives using Active Filtering Approach

This paper proposes a harmonic mitigation method in open ended induction-motor drive based on active filtering approach. Open ended motor has open stationary windings with two separate inverters feeding from either sides. With half input dc voltage this conventional configuration works as a three-level inverter. In this work, the stator winding is fed from one end by a SVPWM controlled primary voltage source inverter and other end by a secondary voltage source inverter. The secondary voltage source inverter is controlled to produce a voltage which will cancels out the harmonics in the motor phases. It is controlled using a series active filter algorithm to eliminate phase voltage harmonics, thereby reducing the motor losses and improves the efficiency and life span of the motor. The total harmonic distortion of the proposed drive scheme is less compared to conventional three-level open ended motor with additional advantage of no extra switching devices required. The proposed method is validated by simulation results.
ANtarctica: ANalog Thermal Aware, with Reduced Constraint, Technique for Checking & Analysis

With the growing complexity in design requirements and the manufacturing process, more checks are needed to accomplish design tape-out with faster turn-around-time and better quality covering physical, circuit and reliability verification flows. Thermal/power profiling and analysis are examples of verification flows that became more critical for performance, yield and reliability especially when it comes to power consumption, mean-time-to-failure (MTTF) and aging. Commercial thermal/power analysis solutions mainly focus on high-level packaging (e.g. for 3DIC) and low-level back-end layouts on the digital front (e.g. thermal/power analysis such as clock gating) leaving the analog domain in critical condition. The analog sensitivity, matching and reliability requirements raise the need for achieving thermal matching and thermal symmetry while resolving thermal hotspots. This work proposes an electrical-based geometrical flow that aims at performing thermal/power-like analysis early in the design phase. It allows early fixes for issues that are usually detected after electro-thermal simulations or expensive post-silicon analysis. The proposed flow is prototyped to generate heat maps for hotspot identification and thermal symmetry mismatch analysis in addition to an electrical front-end constraint reduction mechanism that optimizes for a full chip processing with reasonable performance.
of the evaporation rate in reservoir partially covered by floating photovoltaic plants

The present study aims to model and analyze the interaction between floating PV systems (FPVs) and the evaporative phenomenon in partially covered reservoirs. The literature provides several numerical models for evaluating the evaporation rate (ER) in free water basins. The input data used in such models are the weather variables (e.g. global irradiance, ambient temperature, wind speed). Otherwise, less investigated is the evaluation of the (ER) in water basin covered by FPV plants. In this study a numerical model is implemented in such a way to quantify the level of daily evaporation considering the different features of the floating PV array (e.g. floating structures, geometry of the deployment of the PV modules) that determine a diverse impact on the water evaporation. The interaction of the floating PV array on the energy balance of the covered part of the basin is taken into account. The results of this study show a decrease of the evaporation rate as function of the features of the FPV plant installed. For a basin with 10.0% of its surface covered with a FPV plant the reduction of the water evaporated ranges from 7.0 to 19.0%.
Topological Data Analysis for Identifying Critical Transitions in Cryptocurrency Time Series

In this study, we investigate financial crashes in the cryptocurrency market including both mini and major crashes for two cryptocurrencies, Bitcoin and Ethereum, during the period that the digital market crashed in 2018. By applying techniques in topological data analysis, we are able to predict financial transitions and explore optimal values of the window size and the dimension of point cloud data to obtain good early warning signals. Our results demonstrate good early warning signals before the financial crashes and also show that the L1-norm and C1 – norm of persistent landscapes peak before the crashes occur.
On Automatic Detection of Central Serous Chorioretinopathy and Central Exudative Chorioretinopathy in Fundus Images

Automatic detection of chorioretinopathy plays an important role in clinical practice, but the detection of a major chorioretinopathy of central serous chorioretinopathy based on fundus photography images has rarely been studied, let alone distinguishing it from another chorioretinopathy of central exudative chorioretinopathy. Due to the high degree of similarity between the two chorioretinopathies on fundus images, it is difficult for the latest automatic methods to accurately distinguish between them. In this study, we design a deep neural network with two branches for different classification tasks, where the first one is to distinguish the normal and abnormal while the other is to classify the two chorioretinopathies. We manage to improve the classification accuracy by combining focal loss and discriminative loss. Extensive experiments are conducted for comparison between our method and other universal classification models using a private retinal fundus dataset. The results demonstrate that our method achieves the best performance with 97.69%, 99.58% and 98.87% on the accuracy, precision and sensitivity, respectively.
Performance Evaluation Index Set of Frequency Control Considering Dynamic Demand Response

Compared with traditional demand response, dynamic demand response (DDR) pays more attention to the dynamic response characteristics of resources. Thus, DDR is a new and valuable kind of frequency control resources. Meanwhile, compared with traditional hydro and thermal power resources, DDR resources can act more rapidly. Therefore, present performance evaluation index sets cannot be used directly considering the influence of DDR. In this paper, a new frequency regulation performance evaluation index set is put forward. Some indexes of this set are designed for the unique characteristics of DDR, i.e., the delay time and interval time indexes. This index set mainly involves two points. The first is control and economic performance. The second is from all frequency control stakeholders. At the same time, we also give a core performance evaluation index set considering practicality. Through the simulation analysis, the proposed indexes can evaluate the dynamic performance of power grid effectively.
Transfer Learning Based on Hybrid Riemannian and Euclidean Space Data Alignment and Subject Selection in Brain-Computer Interfaces

Transfer learning is a promising approach for reducing training time in a brain-computer interface (BCI). However, how to effectively transfer data from previous users to a new user poses a huge challenge. This paper presents a novel transfer learning approach that combines data alignment and source subject selection for motor imagery (MI) based BCIs. The former is achieved by a reference matrix from the regularization of the two reference matrices estimated in Riemannian and Euclidean space respectively, whereas the latter is implemented by a modified sequential forward floating-point search algorithm. The aligned training data from chosen source subjects are used for creating a classification model based on either spatial covariance matrices in Riemannian space or common spatial pattern algorithm in Euclidean space. The proposed algorithms were evaluated on two MI based BCI data sets with different subjects and compared with existing transfer learning algorithms with sole data alignment or subject selection. The experimental results show that the hybrid-space data alignment methods for reducing the differences among subjects significantly outperform two single-space alignment methods, and the source subject selection method can substantially enhance the similarity between source subjects and the target subject. The combination of the two methods achieves superior classification performance compared to either one. The proposed algorithms will greatly facilitate the real-world applications of MI based BCIs.
Inverse Filtering Method of Bare Thermocouple for Transient High-Temperature Test With Improved Deep Belief Network

In this paper, we focus on the inverse filtering method for restoring transient heat conduction processes. First, we address the defects of contact temperature sensor used in transient high temperature test, further we expand the distortion of transient calibration result caused by the lack of dynamic characteristics of bare thermocouple, then the inverse filtering idea is proposed. Second, we propose an improved deep belief network (DBN) to extract the characteristic of thermocouple dynamic nonlinearity on dynamic response signal. The continuous restricted Boltzmann machine (CRBM) is adopted to improve the input layer structure which the input samples can be continuous, and the back propagation (BP) neural network is adopted to realize input-output approximation at output layer. Additionally, dynamic response signal of the thermocouple is obtained through the constructed laser narrow pulse calibration system, and dynamic inverse filtering of thermocouple is realized by using the standard source as the approximation target. The performance of the inverse filtering is analyzed by comparing with the traditional linear least square(LS) method, and it is verified that this method can more accurately approximate the transient high temperature physical process in the calibration environment.
An Efficient Iterated EKF-Based Direct Visual-Inertial Odometry for MAVs Using a Single Plane Primitive

This letter proposes an efficient visual-inertial estimator for aerial robots. The main contribution lies in the direct use of intensity measurements of the latest image frames and key frame via both continuous and regular homographic relations under an assumption of a single planar scene. The filter-based method provides comprehensive estimates of position and attitude with notable efficiency and robustness. The flight evaluation indicates that the incorporation of keyframes significantly minimizes the estimation drift while retaining accurate estimates of flight velocity. Compared to state-of-the-art methods, the proposed work provides rivalling performance at substantially lower computational cost by taking the advantage of the assumed single planar structure.
Modeling of Plasma Streamers Guided by Multi-Ring Electrodes in Atmospheric Pressure Plasma Jets

In atmospheric pressure plasma jets (APPJs), placing ring electrodes on the outer side of the capillary tube is an efficient way to ignite the plasma discharge and simultaneously assist to lead streamer/ionization wave to propagate inside and outside the dielectric tube. The streamer characteristics in APPJs, such as length, shape, and propagation speed inside the tube, heavily depend on the electric field built by the electrodes. To study the streamer propagation characteristics, needle-to-multi-ring electrode configurations are simulated by a 2-D fluid model. By placing a series of ring electrodes, the gradient of potential inside the dielectric tube determines the intensity of discharge, streamer behaviors, and plume formation. Proper arrangement and polarity of ring electrodes are essential for accelerating streamer propagation. By connecting the multi-ring electrode with positive and negative voltage alternatively, it may ignite discharge directly between adjacent ring electrodes, and the discharge mode seems to transform from a streamer discharge to a typical dielectric barrier discharge.
Dynamic Vehicle Routing Problem with Simultaneous Delivery and Pickup: Formulation and Resolution

This article treat a fundamental optimization problem encountered by most distribution companies. The Dynamic Vehicle Routing Problem with Simultaneous Delivery and Pickup (DVRPSDP) is a special variant of the VRP, in which new clients comes when the working day has already begun, and a number of vehicles have started their tours, in a way that each customer requires simultaneous delivery and pickup. These new customers must be included in the planned tours as early as possible with a minimum total travel distance. A rich literature review of the problem is carried out. A mathematical model has been formulated for the DVRPSDP, and it is tested with Cplex to provide optimal solutions for small instances. A memetic algorithm has been used to resolve the problem, the proposed algorithm is a combination of the genetic algorithm with a local search method.
Domain Adaptation for Heart Rate Extraction in the Neonatal Intensive Care Unit

Conventionally, vital sign monitoring for neonatal infants inside the Neonatal Intensive Care Unit is performed via probes affixed to their skin. However, such instruments may cause damage to the epidermis and increase the risk of infection as well as promote discomfort to the infant. As an alternative to traditional means of monitoring heart rate, remote Photoplethysmography techniques have been surging among the scientific community. These techniques have been vastly explored for adult subjects but not for neonatal infants, who would greatly benefit from such applications. This study aims at developing a regular consumer camera-based framework for continuous and contactless extraction of the heart rate in adult subjects in challenging conditions and investigating the tool’s ability to adapt to a new domain which consists of newborn subjects and the real-world conditions of a Neonatal Intensive Care Unit.
Design And Implementation Of Smart Shopping Basket

The purpose of this project is to provide a handsfree and hassle-free shopping experience to the user in the supermarket who suffers from the problems such as having chaotic time moving the baskets, overcrowding at one place for a certain product on sale, theft, spending a very long time standing in the queue in the counter for bill payment, etc. The project follows the user as per the command given in the smartphone application provided along with the smart shopping basket and installed on his phone. Customer will receive the total net amount of the bill he has to pay in the same application. The basket consists of the Bluetooth module to connect with the user’s smartphone through which the basket's movements are commanded over. The basket also avoids coming in contact with any obstacles that it faces by taking deviation while following its user using ultrasonic sensors. Each product the user puts inside the basket is read using RFID technology, where each data is sent to the supermarket's server for a total billing of items the user wishes to buy. The total bill amount is sent to the user installed application so that customer can use any online payment applications available to complete his payment
Customer Stickiness to "Internet +" Environmental Protection Public Welfare Platforms

At present, "Internet +" environmental protection public welfare platforms present a good development trend by bridging the gap between customers and enterprises participating in public welfare. Maintaining customer stickiness to such platforms is the key to promoting the development of environmental protection public welfare undertakings. This is due to the fact that the cost of keeping existing customers is lower than attracting new ones. In addition, high customer stickiness will attract more enterprises to join the platforms carrying out environmental protection public welfare projects. This study aims to examine the factors affecting customer stickiness to environmental protection public welfare platforms from the perspective of users, including trust, satisfaction, flow experience and subjective norms. Drawing on data from 252 questionnaires distributed to customers adopting the platforms, structural equation model was used to test the hypotheses. The research results show that these factors positively influence customer stickiness through the mediation of adoption intention. Moreover, satisfaction positively affects trust and flow experience positively affects satisfaction.
RF Systems Design for Simultaneous Wireless Information and Power Transfer (SWIPT) in Automation and Transportation

This work presents some recent solutions that exploit the wireless power transfer (WPT) technology for energizing moving vehicles and machinery tools. Such technology is currently experiencing unprecedented interests in non-traditional RF/microwave sectors fields, such the industrial automation and the railway transportation safety. Near-field electromagnetic coupling solutions are presented showing that, in order to obtain efficient performances for broad ranges of operating conditions, the nonlinear electromagnetic co-design of the entire WPT system, from the energy source to the receiver load, needs to be carried out. This technology can be combined with wireless data transfer, thus realizing integrated systems able to simultaneously control the energy transfer and the transmission of data. The adopted operating frequencies are in the MHz range, which is only recently considered for this kind of applications. In particular this work focuses on three different systems: the first one demonstrates the constant powering of “on the move” industrial charts at 6.78 MHz, regardless of the relative position of the transmitter and the receiver sub-systems; the second one presents a novel design of a balise transportation system adopting a high efficiency GaN-based transmitter designed to keep its performance over a wide range of loading conditions; the last one consists of the simultaneous wireless power and data transfer, to a rotating machinery tool, automatically controlled by the powering system based on the coexistence of frequency-diverse inductive and capacitive couplings.
Four-Stage Linear Transformer Driver With Sharing Shell: EM Model, Simulation, and Performance

A four-stage fast linear transformer driver (LTD) with sharing shell was constructed as a fundamental component of China’s next-generation Z-pinch driver CZ34. Separate metal rods replaced conventional independent cavity shells for the ease of installation and maintenance. SF6 was utilized for the first time as insulating medium instead of transformer oil. To investigate the electrical performance of the LTD module, a 3-D full-scale electromagnetic model was developed by field-circuit co-simulation method in Computer Simulation Technology Studio Suite. Fundamental discharging brick was modeled as a conductive current path in 3-D model, excitation was employed through exterior circuits coupled to the field model. The applicability of the simulation model was validated by primary experiments. Compared to circuit simulation, the field-circuit co-simulation modeled the impedances of transmission lines and load impedance accurately since specific structures were included. Annular liquid resistor in experiment configurations brought in extra load inductance, which influenced greatly on output voltage fluctuations in each stage due to the mismatch of load impedance. Simulation results were in good agreement with experiments, except that the switch performances were not entirely up to expectations. It was indicated that several switches showed notable delays according to calculations, leading to voltage and current loss in measurements.
Stiffness estimate of information propagation in biological systems modelled as spring networks

We present a mathematical model of the dynamics of a biological network represented as a spring system with n degrees of freedom. The study is inspired by the recent abstraction of a biological network as a system composed of masses (nodes) connected by springs (the arcs between nodes). As a consequence of the mutual interactions between the nodes and/or of stresses deriving from the environmental conditions in which the physical network is immersed, the nodes vibrate around their equilibrium positions. The elastic constant that measures the strength of an ideal spring connecting the vibrating nodes cannot be straightforwardly gauged experimentally, and almost never in the case of large networks whose dynamics has several degrees of freedom. In this study, we show how elastic constants are related to the topology of the network and how they can be derived from the equations of the dynamics at equilibrium. The innovative results of the study are (i) the definition of stiffness vectorial entities as basis of the nullspace of the network incidence matrix, (ii) the introduction of the spring stiffness as an indicator of information propagation between nodes.