Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation Resistance of in Factors Non-Dia during OGTT to betic Subjects Correlate Insulin

The correlation between various factors obtained during oral glucose tolerance tests (OGTT) and insulin sensitivity tests (steady state plasma glucose, SSPG method) were analyzed in non-diabetic subjects by Pearson's simple correlation. Similar data were obtained for normal as well as normal and impaired glucose tolerance (IGT) subjects. Three factors (AUCIo20AUCGo20, AUCIo20 and AUCI , area of under curve (AUC), insulin (I), glucose (G)) were found to have significant correlation (r=0.47-0.54) with SSPG, thus indicating insulin resistance. Those with hyperinsulinemia were noted to have insulin resistance with high precision (98%), but insulin resistant subjects without hyperinsulinemia were all judged to have normal sensitivity. These three factors all had high specificity (98%), but low sensitivity (21-25%) with false negative results being obtained in 75-78%, and false positive results in less than 2%. It was difficult to distinguish positive and negative for the insulin resistance by receiver operating characteristic (ROC) curve of I0G0. The sensitivity of which was 12.8% and specificity 93.8%. By ROC curve, the specificities and sensitivities for the proposed factors, including homeostatic model assessment (HOMA) product (I0G0, Io-12o, Go-120, insulin and glucose at 0-120' during OGTT) ranged from 60 to 70%, which is far from an acceptable level of 90% or more. Therefore, these factors were useful to correlate insulin sensitivity with OGTT results in hyperinsulinemic subjects or in general non-diabetic subjects, but less useful when it came to identifying individual cases with insulin resistance. These parameters should be used only in non-diabetic subjects and their significance is thought to be restricted to cases with hyperinsulinemia.
Performance, Stability, Dynamics, and Control of Airplanes

Performance, Stability, Dynamics and Control of Airplanes provides a comprehensive and integrated overview of several interrelated disciplines involving airplane performance. It contains all necessary background material on aerodynamics, dynamics, and control systems, discussing the fundamental principles with the use of sketches, solved examples, and design exercises. It is an ideal text for upper level undergraduates, graduate students, and professionals. Chapters 1 through 3 present basic principles of aerodynamics, aircraft performance, and static equilibrium and control in steady flight. Chapter 4 deals with aircraft dynamics and decoupled equations for longitudinal and lateral motion, and it introduces the concept of stability derivatives. Chapter 5 discusses design of stability augmentation systems and autopilots. Chapter 6 discusses aircraft response and methods of closed-loop control of aircraft, while Chapters 7 and 8 discuss problems of inertial coupling, aircraft spin, and high angle of attack. The third edition features updates throughout along with a new chapter 9 on stability, control issues, and challenges of unmanned aerial vehicles
Circulation: Cardiovascular Imaging Topic Review Circulation: Cardiovascular Imaging Editors’ Picks

The following articles are being highlighted as part of Circulation: Cardiovascular Imaging’s Topic Review. This series will summarize the most important manuscripts, as selected by the editors, that have been published in the Circulation portfolio. The studies included in this article represent the most significant research in the area of congenital heart disease. (Circ Cardiovasc Imaging. 2012;5:e1-e9.)
Calculation of sound pressure level of marine propeller in low frequency

The research performed in this paper is carried out to calculate the sound pressure level of the marine propeller by Reynolds-Averaged Navier–Stokes solver in low frequencies band. Noise is generated by the induced trailing vortex wake and induced pressure pulses. The two-step Fflowcs Williams and Hawkings equations are used to calculate hydrodynamic pressure and its performance as well as sound pressure level at various points around the propeller. The directivity patterns of this propeller and accurate explanation of component propeller noise are discussed. Comparison of the numerical results shows good agreement with the experimental data.
An Improved Grey Model and Scenario Analysis for Carbon Intensity Forecasting in the Pearl River Delta Region of China

In this paper, an improved grey model and scenario analysis, GA-GM(1,N) is proposed to forecast the carbon intensity in the Pearl River Delta (PRD) region, one of the most developed regions in China. Moreover, to show the advantage and feasibility of the proposed model, the forecasting results of the GA-GM(1,N) model are compared with that of a single-variable grey model (GM (1,1)) and a multivariable form (GM(1,N)). Data from one sample period (2005–2012) are used to develop the models, and data from another sample period (2013–2015) are used to test them. The mean absolute percentage error (MAPE) is applied to measure the accuracy of prediction. The results show that, of the three models, GA-GM(1,N) produces the best carbon intensity forecasts, with MAPEs of 0.4–1.4% and 0.04–0.4% in the development and testing periods respectively. This indicates that the optimization of the genetic algorithm is effective. The realization of carbon reduction targets in different cities is also explored by combining grey models with scenario analysis. Only Guangzhou could achieve its reduction target under all scenarios, and it can serve as a reference for other cities. Policy recommendations are provided based on these results.
I DPID It My Way! A Covert Timing Channel in Software-Defined Networks

Software-defined networking is considered a promising new paradigm, enabling more reliable and formally verifiable communication networks. However, this paper shows that the separation of the control plane from the data plane, which lies at the heart of Software-Defined Networks (SDNs), can be exploited for covert channels based on SDN Teleportation, even when the data planes are physically disconnected.This paper describes the theoretical model and design of our covert timing channel based on SDN Teleportation. We implement our covert channel using a popular SDN switch, Open vSwitch, and a popular SDN controller, ONOS. Our evaluation of the prototype shows that even under load at the controller, throughput rates of 20 bits per second are possible, with a communication accuracy of approximately 90%. We also discuss techniques to increase the throughput further.
Compact Two-Sided Krylov Methods for Nonlinear Eigenvalue Problems

We describe a generalization of the compact rational Krylov (CORK) methods for polynomial and rational eigenvalue problems that usually, but not necessarily, come from polynomial or rational approximations of genuinely nonlinear eigenvalue problems. CORK is a family of one-sided methods that reformulates the polynomial or rational eigenproblem as a generalized eigenvalue problem. By exploiting the Kronecker structure of the associated pencil, it constructs a right Krylov subspace in compact form and thereby avoids the high memory and orthogonalization costs that are usually associated with linearizations of high degree matrix polynomials. CORK approximates eigenvalues and their corresponding right eigenvectors but is not suitable in its current form for the computation of left eigenvectors. Our generalization of the CORK method is based on a class of Kronecker structured pencils that include as special cases the CORK pencils, the transposes of CORK pencils, and the symmetrically structured linearizations .
Construction of Time-Space Radio Environment Database using HMM for Cooperative Sensing

In recent years, many researchers focus on a measurement-based radio environment database (RED) that utilizes the actual received signal power obtained by spectrum sensing as an enabler for an efficient frequency sharing. In this paper, in an environment where multiple transmitters are switched ON/OFF, each sensor is distributed in the environment by cooperative sensing and acquires time series data. Moreover, each sensor learns using the Hidden Markov Model (HMM) on the acquired time series data, thereby estimating the parameter of the receivable transmitter. After collecting estimation results by HMM in each sensor, we propose to use sensor selection for estimation of time parameters (channel occupancy rate, average ON/OFF interval) and multiple imputation for estimation of spatial parameters (pathloss exponent, transmit power). By the proposed method, it is possible to construct a highly accurate time–space RED. The simulation results confirm the effectiveness of the proposed method.
High gain low profile wideband dual-layered substrate microstrip antenna based on multiple parasitic elements

In this paper, a high gain broadband low profile microstrip antenna with the dual-layered substrate and four parasitic metal elements is presented. The proposed microstrip antenna is mainly composed of four parts: four circular parasitic metal patches with dual arced breaches, a rectangular metal patch sandwiched between substrates, a square ground plane, and two-square substrates. The circular parasitic elements are the main radiation structure and determine the characteristics of the proposed antenna are closely related to the parasitic elements. The proposed antenna has been fabricated for experimental measurement. The reflection coefficient, radiation pattern, radiation efficiency, and gain have been studied in detail. The simulated and measured impedance bandwidth is 27.0% (3.30–4.33 GHz), the maximum realized peak gain reaches up to 6.52 dBi at the frequency of 3.65 GHz. The radiation pattern has a single peak which is perpendicular to the surface of the substrate. The proposed antenna is suitable to be applied in the 5G mobile or WiMAX wireless communication. Dual antenna with a pair of parasitic elements has been investigated numerically to explain the principle of the proposed antenna.
Software Defined Internet of Things: Cyber Antifragility and Vulnerability Forecast

The authors use the definition of a synergetic approach to obtain the effect of combining different concepts of cyber systems. The cyber antifragility of the result of this approach is substantiated. As an example, software-defined networking (SDN) and Internet of Things (IoT) are explored. In conclusion, the SDIoT vulnerability forecast is introduced.
A Robust Traffic Video Stabilization Method Assisted by Foreground Feature Trajectories

This paper considers stabilizing traffic videos recorded by vehicle-mounted cameras. Compared with videos recorded by handheld cameras, traffic videos suffer from more challenges, such as dynamic scenes, dominant foreground objects, and significant parallax. As conventional video stabilization methods usually estimate a homography only from background feature trajectories and warp frames with that homography, they may not obtain enough number of background feature trajectories, especially in the existence of large moving vehicles or strong parallax, and cannot obtain a precise homography to stabilize videos. To resolve this issue, this paper proposes a novel method that makes use of foreground feature trajectories to assist background feature trajectories in stabilizing traffic videos. More specifically, the stabilized views of foreground trajectories are obtained through solving a spatial–temporal optimization. Then, background feature trajectories, together with foreground feature trajectories and their stabilized views, are used to compute the desired homography, which is implemented to stabilize videos. To further improve the stabilization performance, this paper proposes a block-based strategy, which divides each frame into a few equal blocks and attempts to maintain the balance of the numbers of feature trajectories of blocks by evenly extracting feature points and compensating discontinuous feature trajectories if necessary. The experimental results confirm that the proposed method is superior to several state-of-the-art methods in stabilizing traffic videos, especially when there are large moving objects and/or parallax.
A Comprehensive Security Analysis of a SCADA Protocol: From OSINT to Mitigation

It is an established fact that the security of Industrial Automation and Control Systems (IACS) strongly depends on the robustness of the underlying supervisory control and data acquisition (SCADA) network protocols (among other factors). This becomes especially evident when considering the extent to which certain protocols, designed with poor or nonexistent security mechanisms, have led to a considerable number of past incident reports affecting critical infrastructures and essential services. Considering the current situation, it is rather obvious why the proper auditing and analysis of SCADA protocols are considered as key when it comes to design and/or protect IACS infrastructures. However, while the security of some protocols, such as Modbus or DNP3, has already been extensively analyzed, the same cannot be said for other protocols and technologies being used in the same domain that have not received the same amount of attention. In this paper, we provide a comprehensive security analysis of the PCOM SCADA protocol, including a dissection of PCOM, a demonstration of several attacks scenarios on PCOM-based systems, and also an analysis of possible mitigation strategies against these potential attacks. Moreover, this paper also describes a number of open-source tools that we developed for further analysis and research of PCOM security aspects, including a PCOM Wireshark dissector, a Nmap NSE PCOM scan, multiple Metasploit PCOM modules, a set of Snort PCOM rules, and several network traffic datasets containing multiple samples of different types of PCOM operations.
Image Inpainting Based on Generative Adversarial Networks

Image inpainting has a good application value in image editing, however, traditional image inpainting techniques cannot complete semantic repair in the case of insufficient sample resources. Deep learning neural network have powerful learning capabilities and can extract high-level semantic features. These features can be used to semantically fill missing regions. Ideal image restoration needs to maintain structural consistency and texture clarity. In this paper, using the GAN network structure, we propose a inpainting method which constrains the repair process using the neighborhood loss function and gradient loss. The experimental results show that the repair results can maintain the global consistency of the structure and the clarity of the local texture. It shows that adding gradient loss constraint can further improve the quality of repair.
Environmental parameters monitoring using a single mode-bare core multimode-single mode optical fiber sensor

We report a single mode-bare core multimode-single mode (SBMS) optical fiber sensor, for environmental parameters in-situ monitoring. Compared with the reflection structure and the transmission structure of the SBMS optical fiber sensors, we found that the repeatability and stability results of the reflection structure were much better than that of the transmission structure’s. The principle of this experimental design is based on the optical fiber which can be transmitted by the outside temperature modulation. Because the parameters of the light transmitted in the single mode-multimode single mode (SMS) fiber structure are subject to the change of the external physical factors, this type of fiber optic temperature sensor is made by multiple modes of transmission in a multimode fiber. As the light source transmits a distance in the multimode fiber, it will change greatly, making the input light and the final output light produce a great difference. While the length of the bare core multimode fiber was around 8.1cm, the temperature cross-sensitivity of the device had good linearity and was around 0.009075nm/°C , from 50 °C to 350 °C. Furthermore, the increased temperature curve was almost coincided with the decreased temperature curve.
Waveguide-Integrated Graphene Photodetector with a Bragg Reflector on Silicon

A silicon-based waveguide-integrated graphene photodetector with an asymmetric metallization scheme is demonstrated. A Bragg reflector is introduced to shorten the length of the light absorption section. High responsivity of ∼0.2 mA W−1 at 1550nm under zero bias and broadband photoresponse are observed.
Toward a Lightweight Intrusion Detection System for the Internet of Things

Integration of the Internet into the entities of the different domains of human society (such as smart homes, health care, smart grids, manufacturing processes, product supply chains, and environmental monitoring) is emerging as a new paradigm called the Internet of Things (IoT). However, the ubiquitous and wide-range IoT networks make them prone to cyberattacks. One of the main types of attack is a denial of service (DoS), where the attacker floods the network with a large volume of data to prevent nodes from using the services. An intrusion detection mechanism is considered a chief source of protection for information and communications technology. However, conventional intrusion detection methods need to be modified and improved for application to the IoT owing to certain limitations, such as resource-constrained devices, the limited memory and battery capacity of nodes, and specific protocol stacks. In this paper, we develop a lightweight attack detection strategy utilizing a supervised machine learning-based support vector machine (SVM) to detect an adversary attempting to inject unnecessary data into the IoT network. The simulation results show that the proposed SVM-based classifier, aided by a combination of two or three incomplex features, can perform satisfactorily in terms of classification accuracy and detection time.
Empirical Analysis for the Heat Exchange Effectiveness of a Thermoelectric Liquid Cooling and Heating Unit

This study aims to estimate the performance of thermoelectric module (TEM) heat pump for simultaneous liquid cooling and heating and propose empirical models for predicting the heat exchange effectiveness. The experiments were conducted to investigate and collect the performance data of TEM heat pump where the working fluid was water. A total of 57 sets of experimental data were statistically analyzed to estimate the effects of each independent variable on the heat exchange effectiveness using analysis of variance (ANOVA). To develop the empirical model, the six design parameters were measured: the number of transfer units (NTU) of the heat exchangers (i.e., water blocks), the inlet water temperatures and temperatures of water blocks at the cold and hot sides of the TEM. As a result, two polynomial equations predicting heat exchange effectiveness at the cold and hot sides of the TEM heat pump were derived as a function of the six selected design parameters. Also, the proposed models and theoretical model of conventional condenser and evaporator for heat exchange effectiveness were compared with the additional measurement data to validate the reliability of the proposed models. Consequently, two conclusions have been made: (1) the possibility of using the TEM heat pump for simultaneous cooling and heating was examined with the maximum temperature difference of 30 °C between cold and hot side of TEM, and (2) it is revealed that TEM heat pump has difference with the conventional evaporator and condenser from the comparison results between the proposed models and theoretical model due to the heat conduction and Joule effect in TEM.
Association Optimization in Wi-Fi Networks based on the Channel Busy Time Estimation

With the centralized management paradigm offered by the recent IEEE 802.11 products, it is now easier and more efficient to optimize associations between access points (APs) and stations. Most of the optimization approaches consider a saturated network. Even if such traffic conditions are rare, the optimization of the association step under this assumption has the benefit to fairly share the bandwidth between stations. Nevertheless, traffic demands may be very different from one station to another and it may be more useful to optimize associations according to the stations’ demands. In this paper, we propose an optimization of the association step based on the stations’ throughputs and the channel busy time fraction (BTF). The latter is defined as the proportion of time the channel is sensed busy by an AP. Associations are optimized in order to minimize the greatest BTF in the network. This original approach allows the Wi-Fi manager/controller to unload the most congested AP, increase the throughput for most of the stations, and offer more bandwidth to stations that need it. We present a local search technique that finds local optima to this optimization problem. This heuristic relies on an analytical model that predicts BTF for any configuration. The model is based on a Markov network and a Wi-Fi conflict graph. NS-3 simulations including a large set of scenarios highlight the benefits of our approach and its ability to improve the performance in congested and non-congested Wi-Fi networks.
Translating Sentences Using RDF Graphs

This research article deals with translating a sentence from one language toanother. Our motive is to provide a technique that converts web-pages from one language to another automatically using Resource Description Framework (RDF) graphs. We particularly focus on making translation independent of human interference. Therefore, this research paper presents a framework and provides its implementationfor converting English sentences to Hindi using RDF and Pythonprogramming language. As a result of our research work, we successfullytranslatedour sample sentences present in English to Hindi.
Exact Task Execution in Highly Under-Actuated Soft Limbs: An Operational Space Based Approach

Recently, the development of soft robots is imposing a change of prospective in several aspects of design and control, moving the robotic field closer to the natural world. Soft robots, like many animals, are often built of continuously deformable elements, and are consequently characterized by a highly under-actuated input space. In this letter we prove that given a generic nonlinear task to be accomplished by a soft robot—as e.g., the positioning of its end effector in space—a linear actuation space with the size of the task itself is already sufficient to achieve the goal. We then introduce the dynamically consistent projector into synergistic space, which can be used to convert controllers designed in operational space, to work in the under-actuated case. This enables a direct translation of control strategies from classic to soft robotics. Leveraging on this result, we present the first dynamic feedback controller for trunk-like soft robots taking in account nonconstant deformations of the soft body. We present simulations showing that using this controller it is possible to track a prescribed dynamic evolution of the robot's tip with zero error at steady state, both in planar and 3-D case with gravity.
An Experimental Study on the Use of Visual Texture for Wood Identification Using a Novel Convolutional Neural Network Layer

We describe a novel approach to transform the input layer of a convolutional neural network (CNN) so that textural properties and relational pixel properties are captured directly. We test this approach by using wood texture for wood identification. We compare our results with our dataset against another approach using CNN and obtained better results. This approach can be used for detecting textures in general.