Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation of IR smoke screen based on physical model

Infrared smoke screen plays an important role in modern battlefield simulation. We put the velocity, concentration, temperature, pressure and obstacles on 3D grids in smoke screen. To enrich the characteristics of smoke screen, we simplified and improved the Navier-Stokes equations. And we add smoke screen curl constraining force, gravity, buoyancy to truly represent the turbulent effect of smoke screen. In terms of smoke screen rendering, we consider the influence of atmospheric transmittance and atmospheric path radiation on smoke infrared simulation to make the imaging effect more realistic. At the same time we use the CUDA parallel computing platform, which greatly reduces the calculation time, to improve the real-time performance further.
IoT-PEN: A Penetration Testing Framework for IoT

With the horizon of 5th generation wireless systems (5G), Internet of Things (IoT) is expected to take the major portion of computing. The lack of inbuilt security and security protocols in cheap IoT devices give privilege to an attacker to exploit these device's vulnerabilities and break into the target device. IoT network security was initially perceived from the perspective of a single, or a few attacks surface only. However, attacks like Mirai, Wannacry, Stuxnet, etc. show that a cyber attack often comprises of a series of attacks on vulnerabilities of victim devices to reach the target device. Penetration testing is generally used to identify the vulnerabilities/ possible attacks on traditional systems periodically. A timely fix of these vulnerabilities can avoid future attacks. Traditional penetration testing methods focus on isolated and manual testing of a host that fails to detect attacks involving multi-hosts and multi-stages.In this paper, we introduced first-of-its-kind, IoT-PEN, a Penetration Testing Framework for IoT. The framework consists of server-client architecture with "a system with resources" as server and all "IoT nodes" as clients. IoT-PEN is an end-to-end, scalable, flexible, and automatic penetration testing framework for IoT. IoT-PEN seeks to discover all possible ways an attacker can breach the target system using target-graphs. It constructs prerequisite and postconditions for each vulnerability using the National Vulnerability Database (NVD). We also demonstrated that even if an individual system is secure under some threat model, the attacker can use a kill-chain (a sequence of exploitation of multiple vulnerabilities on different hosts) to reach the target system.
World malaria report 2011

The World Health Organization (WHO) World Malaria Report 2021 < https://www.who. int/publications/i/item/9789240040496 > estimates that there were 241 million malaria cases, including 627,000 deaths, worldwide in 2020, which represents around 14 million more cases, and 69,000 more deaths, than 2019. Approximately two-thirds of these additional deaths were linked to disruptions in the provision of malaria prevention, diagnosis and treatment during the COVID-19 pandemic. Sub-Saharan Africa continues to carry the heaviest malaria burden, accounting for about 95% of all cases and 96% of all deaths in 2020, with around 80% of deaths in the region among children under five years old. Since 2015, the baseline date for the WHO's global malaria strategy, registered increases in malaria deaths were reported in 24 countries. In the 11 countries that carry the highest burden of malaria worldwide, cases increased from 150 million in 2015 to 163 million cases in 2020, and malaria deaths increased from 390,000 to 444,600 over that same period. As in previous years, the report includes an up-to-date assessment on the burden of malaria at global, regional, and country levels, and tracks investment in malaria programmes and research, as well as detailing progress across the four intervention areas of prevention, diagnosis, treatment and surveillance. There are also dedicated chapters on malaria elimination and key threats, such as insecticide and drug resistance.
Robust GaN Limiting LNA for C-Ku Band T/R Modules

In this contribution a robust limiting-LNA for next generation Electronic Warfare T/R modules is presented. The proposed circuit relies on a balanced design technique and exploits ad hoc biasing circuit scheme to control output power compression characteristic. The proposed MMIC features a 3.5 x 2 mm2 outline and operates in the 5 ÷18 GHz band with an average noise figure of 3.5 dB and an associated gain of 13 dB; output power is clamped around 15 dBm up to 4W of input excitation, while guaranteeing a minimum OP1 dB of 10 dBm.
Impact on V2V VoIP Traffic between to ProSe-enabled End-points while Switching between Infrastructure Mode and Direct Mode

Device-to-device (D2D) communication or Proximity Service (ProSe) is a proposed technique to increase the network capacity in a dense 5G network. This enables a base station (aka eNB) to perform in-band offloading of traffic between two ProSe enabled user equipments (UEs) so that the UEs can communicate directly over a side-link (SL) channel switching from conventional Infrastructure Mode (IM). However, such a mode-switching during an ongoing session may potentially degrade the Quality of Experience (QoE) for the end-consumer due to possible loss of packets in flight during the mode-switching instance. This paper presents, based on simulation of realistic conditions, a unique observation on how mode-switching affects a voice over IP (VoIP) session between two moving vehicles crossing each other from a distance. Observations reveal how a potential smart mode-switching decision, combining application context and instantaneous channel parameters, can improve performance both in terms of QoE as well as network capacity. To best of our understanding, this paper is a stepping stone towards a generic predictive model based scheduling policy to intelligently trigger mode-switch keeping the application context in consideration.
Supervised Aspect Category Detection of Co-occurrence Data using Conditional Random Fields

Customer’s sentiments on products and services are recognized by the internet through consumer reviews. But, to make a purchase decision one cannot identify all the data and make a fair evaluation of a product or resource. Hence, all reviews are summarized using a text processing framework. In this paper, we work on identifying the aspect categories in the review sentences. We have built Conditional Random Field based system for category detection and summarization to achieve the Aspect Based Sentiment Analysis(ABSA) task on Restaurant review dataset. Implicit aspect in product review sentences is a difficult task. In the proposed system explicit as well as implicit aspects are extracted to identify the aspect category.
Research of Time-domain Model of Microwave Radiation Field Measurement System Based on Scatter Parameters Transient Analysis

The microwave pulse transmission among the radiation field measurement system is transient. It's difficult to give expression to the transmission at math. So, the pulse usually is regarded as single frequency continuous wave, that makes some errors. Based on scatter parameters transient analysis, this article used band-limited scatter parameters of devices in the system to get these devices' impulse response and then accomplished X-band microwave radiation field measurement system's time domain model. The simulation results show that the time domain model can accurately calculate pulse transmission characteristics among the measurement system such as reflection, superposition, and delay. In addition, the direct measurements' probability distribution in the microwave radiation field measurement system were brought in the time domain models based on monte-carlo method. That can not only get a value of uncertainty but also get the probability distribution of radiation field power density. It's an available way to evaluate the uncertainty of microwave radiation field measurement.
Robust Beam Tracking with Extended Kalman Filtering for Mobile Millimeter Wave Communications

Millimeter wave (mmWave) combined with beam-forming technology is an attractive option for meeting the explosive growth of wireless data traffic. However, in a mobile communication scenario, slight misalignment between the transmit and receive beams may lead to a significant degradation of the received signal quality. This paper proposes a joint optimization of the mean square error (MSE) and extended Kalman filter (EKF) robust beam tracking algorithm to maintain the communication link. First, the initial channel state information is obtained via the two-dimensional MUSIC method. Then, the channel complex gain and beam angle are predicted with EKF algorithm from the received signal. Finally, we adopt the minimum mean square error (MMSE) criterion to perform iteratively optimization procedure to eliminate the estimation errors caused by the linear approximation of EKF. Simulation results show that the proposed algorithm can reduce the angle tracking error rates and improve the link maintenance time compared with existing angle tracking algorithms.
Modeling and Simulation of Aluminium Nitride-Based Piezoelectric Micromachined Ultrasonic Transducer for Ultrasound Imaging

In this work, a PMUT based on Pt/AlN/Pt/TiO2/SiO2/Si structure with square suspended membrane is proposed and modeled by performing finite element method (FEM) software COMSOL. The vibration mode, resonant frequency and effective electro-mechanical coupling coefficient (keff2) of the proposed AlN-based PMUT are analyzed. It is shown that the (0,1) resonant mode of PMUT reaches up to 25.73 MHz when the AlN thickness is 1μm. Moreover, the influences on the sensitivity of geometric parameters, i.e., the side length and thickness of top electrode, and the thickness of AlN thin film, are investigated. Maximum transmitting and receiving sensitivity of 32.79 pm/V and 0.478mV/kPa, respectively, are obtainable with optimum geometric parameters. Investigation results demonstrate that by optimizing the structure of the proposed AlN-based PMUT, keff2 and sensitivity are significantly improved, which is beneficial for meets the requirement for application of high resolution ultrasound imaging.
Pricing Mechanism for Virtualized Heterogeneous Resources in Wireless Network Virtualization

Virtualized resource in the wireless network enables to share the physical resource efficiently to increase the resource utilization. In the wireless network virtualization, an infrastructure provider (InP) and mobile virtual network operator (MVNO) can design a pricing scheme for the network resource to maximize their revenue and network resource sharing. Previous works have been proposed pricing mechanisms for virtualized resource sharing and allocation as an optimal solution. However, previous works mainly focus on a single type of virtualized resource. Thus, in this paper, we propose a pricing mechanism for multiple types of virtualized resources that include communication and caching resources in the wireless network. To do this, we formulate an optimization problem by considering social welfare among the MVNOs and show that this problem is NP-hard. Therefore, to solve the formulated problem, we propose an auction-based solution approach. The auction allows placing multiple MVNOs together in the same competitive market of virtualized heterogeneous resources. In our auction approach, first, InP decides and announces the reservation price to the mobile virtual network operator which covers capital expenditures (CAPEX) and Operating Expenditure (OPEX). Second, depending on resource demand to satisfy users’ requests, mobile virtual network operators determine and submit the bidding value to InP. Finally, InP evaluates bidding values from MVNOs to select the winning MVNOs and decide the optimal price for virtualized heterogeneous resources. The performance of the proposed algorithm shows that our approach can guarantee social welfare maximization.
Efficient Plane Extraction Based on Hierarchical Clustering

Plane extraction is a crucial task for many applications such as robot navigation, SLAM (simultaneous localization and mapping) and so on. Although there exists several of plane segmentation methods based on RANSAC (Random Sample Consensus), Hough transform, region growing etc. Some of these methods may not guarantee speed performance for computer vision tasks with real-time requirements. In order to improve the efficiency of the plane extraction algorithm, we propose a method based on agglomerative hierarchical clustering in this paper. Our method extracts planar surfaces in organized point clouds obtained from RGB-D sensors such as Microsoft Kinect in real time. We first divide point clouds into several groups of points as nodes. Those nodes represent point sets while the edges of the nodes represent neighborhoods. Next, we find nodes with the smallest plane fitting MSE (mean squared error) as initial nodes, and then perform agglomerative hierarchical clustering to merge nodes that belong to the same plane. We stop the step once the MSE is larger than the given threshold. Weoptimize the boundary of the extracted planes at last. We evaluate our method using the public TUM and SegComp datasets. Experiments show that the proposed approach can detect planar surfaces efficiently and correctly compared with other state-of-art methods.
Performance Optimization of Dual supply voltage level shifter using FINFET and CNTFET at 32nm technology

With bulk CMOS technology scaling below 100 nm, there is significant increase of leakage power in that. Multigate FET like FINFET and CNTFET (carbon Nano tube field effect transistor) are the devices to replace that because of improved drive strength and short channel behavior. This paper represents dual supply voltage level shifter which is capable of converting low input of voltage to high level. This proposes a comparative study of voltage level shifter at 32nm technology node of MOSFET, FINFET and CNTFET. Simulations results tells us that there is notable improvement at frequency 0.5Mz in average power and PDP of 7.50E-07 W and 3.57E-14 in FINFET and 9.58E-07 W and 2.45E − 14 in case of CNTFET with comparison of MOSFET.
Free Vibration of Functionally Graded One-Dimensional Hexagonal Piezoelectric Quasicrystal Sandwich Plates

A one-dimensional (1D) quasicrystal (QC) [1] refers to a three-dimensional structure with atomic arrangement quasi-periodically in one direction and periodically in the plane perpendicular to that direction [2] , [3] . Functionally graded martial (FGM) [4] – [10] composite piezoelectric QCs and other materials expand the application of QCs [11] – [13] .
Precise Indoor Pressure Positioning System Based on LabVIEW

Using a single positioning technology for indoor positioning systems may cause drawbacks, such as low robustness, low positioning accuracy, and long response time, therefore, a four-point pressure location model is proposed in this paper. Furthermore. we designed an indoor pressure positioning system using LabVIEW, Bluetooth, data acquisition card, SolidWorks, and a 3D Printer to perform a simulation, and solved the problem of locating the blind-area in this model. The comprehensive application of various positioning technologies and the consideration in locating the blind-area resulted in precise positioning. Our experimental results show that the absolute error of the indoor positioning system is within 1 cm. We proposed an accurate and easy to operate indoor positioning method, which makes up for the lack of indoor positioning in accuracy, practicality. and price.
Model-Based Generalization Under Parameter Uncertainty Using Path Integral Control

This letter addresses the problem of robot interaction in complex environments where online control and adaptation is necessary. By expanding the sample space in the free energy formulation of path integral control, we derive a natural extension to the path integral control that embeds uncertainty into action and provides robustness for model-based robot planning. Our algorithm is applied to a diverse set of tasks using different robots and validate our results in simulation and real-world experiments. We further show that our method is capable of running in real-time without loss of performance. Videos of the experiments as well as additional implementation details can be found at https://sites.google. com/view/emppi.
Webpages Classification Based on Deep Belief Network Using Images and Text Information

In this paper, Deep Belief Network(DBN) is used for drug-related webpages classification. HTML parsing is used to extract image-label text and body text, FOCARSS method is used to choose effective images. text representation is generated by BOW model, images representation is generated by BOF model. We concatenate images and text representation to generate final representation. It is shown that DBN’s classification accuracy is higher than BPNN’s classification accuracy, and better than that of single-modal information.
Simultaneous Wireless Information and Power Transfer in 5G Mobile Networks: A Survey

The fifth generation (5G) mobile networks are growing vigorously. As one of the most promising technologies of 5G, millimeter-wave (mmWave) communication can provide us with multi-Gbps transmission rate. However, the ultra-high transmission rate greatly increases the power consumption of wireless devices. People begin to pay attention to the lifetime of battery-powered devices when pursuing higher quality of service (QoS) of communication. Investigating an environment friendly and energy efficiency transmission technology in 5G mobile networks is an urgent task. Simultaneous wireless information and power transfer (SWIPT) is an innovative candidate, and an effective solution to ease the contradiction between high transmission rate and long lifetime of battery-powered devices. But the propagation features of mmWave bring new challenges to SWIPT system. This paper presents an updated literature survey on the application of SWIPT technology in 5G mobile networks. Specifically, we give an overview of SWIPT technology, not only including the typical structure, but also the classical radio frequency (RF) signal resource allocation structures and the rate-energy (R-E) tradeoff of information and energy allocation. Then, we summarize the recent advances on SWIPT technology in 5G mobile networks and explore them in various scenarios of 5G. Finally, the SWIPT-enabled mmWave network is mainly discussed according to the development of SWIPT, the propagation features of mmWave and the general structure of SWIPT-enabled mmWave network. Moreover, we put forward several potential future research directions and practical challenges.
Using MTD and SDN-based Honeypots to Defend DDoS Attacks in IoT

With the rapid development of Internet of Things (IoT), distributed denial of service (DDoS) attacks become the important security threat of the IoT. Characteristics of IoT, such as large quantities and simple function, which have easily caused the IoT devices or servers to be attacked and be turned into botnets for launching DDoS attacks. In this paper, we use software-defined networking (SDN) to develop moving target defense (MTD) architecture that increases uncertainty because of ever changing attack surface. In addition, we deploy SDN-based honeypots to mimic IoT devices, luring attackers and malwares. Finally, experimental results show that combination of MTD and SDN-based honeypots can effectively hide network asset from scanner and defend against DDoS attacks in IoT.
On Fast Channel Switching With a Parallel Multiple Channels Streaming in P2P Systems

A long start-up delay of a channel in IP-Based TV systems can degrade viewers’ quality of experience significantly. By leveraging the peer-to-peer (P2P) architecture, we present a novel architecture for Internet TV systems that can shorten the start-up delay caused by channel switching, called multiple channels streaming (MCS). The MCS is a stream comprised of multiple parallel channels selected from all channels that work within a single channel streaming. Although some overhead traffic is involved by the MCS from a conventional perspective, it can alleviate start-up delay for viewers in a P2P video system. For each peer, the most important problem is to dynamically determine how many and which channels should be selected into the MCS. We propose a proper solution to this problem and analyze how much delay time can be reduced by the limited increase in overhead traffic in P2P systems.
Bend Loss Properties of the Octagonal-core and Nodeless Large-mode-area Anti-resonant Hollow-core Fibers

We report the results of the numerical and experimental comparison of bend loss properties for two different silica-based anti-resonant hollow-core fibers (AR-HCFs) at the wavelength of 2.25 μm with the mode area larger than 1000 μm2. The first fiber has a negative curvature of the core-cladding boundary formed by eight touching trapezoidal capillaries and the second one has the nodeless structure designed by six non-touching round capillaries.
High-gain V - band Dielectric Lens Antenna for Communication and Direction Finding Systems

A highly-directional spherical lens antenna system operating from 40 GHz to 50 GHz (V band) is proposed. The antenna consists of a Luneburg inspired lens, which is fed by a 16-element array of septum horns with circular aperture. The septum horn antenna with circular aperture has a rotationally symmetric radiation pattern with the ability to generate both righthanded and left-handed circular polarizations. A single septum horn antenna has a gain of 8 dBi with −13 dB side lobe level (SLL). The return loss of each septum horn antenna is below −10 dB over the entire frequency range of operation. Using a lens together with a 16-element array of septum horns makes it permissible to increase the overall gain to 26 dBi and simultaneously decrease the SLL to −21 dB. The proposed system can be used for direction finding and satellite communications in the V band. The design procedure together with the simulated results with CST software are presented in this paper.
A Comparative Study of Coarse to Dense 3D Indoor Scene Registration Algorithms

3D alignment has become a very important part of 3D scanning technology. For instance, we can divide the alignment process into four steps: key point detection, key point description, initial pose estimation, and alignment refinement. Researchers have contributed several approaches to the literature for each step, which suggests a natural need for a comparative study for an educated more appropriate choice. In this work, we propose a description and an evaluation of the different methods used for 3D registration with special focus on RGB-D data to find the best combinations that permit a complete and more accurate 3D reconstruction of indoor scenes with cheap depth cameras.