Miracle-dz/UniFAR-FTUs huggingface dataset:
Security at the Physical Layer Over GG Fading and mEGG Turbulence Induced RF-UOWC Mixed System

With the rapid evolution of communication technologies, high-speed optical wireless applications under the water surface as a replacement or complementary to the conventional radio frequency (RF) and acoustic technologies are attracting significant attention from the researchers. Since underwater turbulence (UWT) is an inevitable impediment for a long distance underwater optical wireless communication (UOWC) link, mixed RF-UOWC is being considered as a more feasible solution by the research community. This article deals with the secrecy performance of a variable gain relay-based mixed dual-hop RF-UOWC framework under the intercepting attempt of a potential eavesdropper. The RF link undergoes Generalized Gamma (GG) fading distribution, whereas the UOWC link is subjected to mixture Exponential Generalized Gamma (mEGG) distribution. The eavesdropper is capable of wiretapping via a RF link that also experiences the GG fading. The secrecy analysis incorporates the derivations of closed-form expressions for strictly positive secrecy capacity, average secrecy capacity, and exact as well as lower bound of secrecy outage probability in terms of univariate and bivariate Meijer’s $G$ and Fox’s $H$ functions. Based on these expressions, impacts of heterodyne and intensity modulation/direct detection techniques along with weak, moderate, and severe UWT conditions due to air bubbles, temperature, and salinity gradients are quantified. To the best of authors’ knowledge, the proposed model is the first of its kind that addresses the secrecy analysis of a temperature gradient RF-UOWC system along with air bubbles, as opposed to the existing models that considered thermally uniform scenarios only. Finally, the derived expressions are verified via Monte-Carlo simulations.
AI Traffic Control System Based on Deepstream and IoT Using NVIDIA Jetson Nano

With the rapid growth of population and economic development, the number of vehicles is increasing day by day. Which leads to traffic congestion. In certain time slots of the day, it becomes unbearable. So, it has become very difficult to control the traffic and maintain traffic law and order traditionally. Thus, it creates a demand for an improved and optimized traffic management system. Fixed timers or manual control are being used in conventional ways of traffic control, which has been proven ineffective to mitigate this situation. In this paper, a completely new system has been introduced to solve the problem of traffic congestion. Which will monitor vehicle traffic in real-time and the system is smart enough to detect traffic conditions and provide decisions depending on the situation. Besides that, the system is designed in a such way, that can also detect the number plate of those vehicles which violate the traffic rules. Advanced features have been added to inform law enforcement agencies about that number plate and send a confirmation message to the driver mentioning the amount of penalty. Throughout the paper, attempts have been made to represent this system’s advancement and efficiency over the existing manual traffic control system.
Sparsely Discretized Refracting Dielectric Huygens’ Metasurface at 28 GHz

We report a sparsely discretized refracting dielectric Huygens’ metasurface comprising only two meta-atoms per period. The proposed metasurface is termed as bipartite dielectric Huygens’ metasurface (Bi-DHMS), which dramatically simplifies the design and pave the way towards efficient electromagnetic (EM) wave manipulation. Such sparse discretization reduces inter-element mutual coupling, leading to efficient, cost-effective, and robust metasurface design. Through full-wave Floquet simulations at 28 GHz, we have demonstrated that a judiciously designed Bi-DHMS can refract an incoming electromagnetic wave from 15 deg to -45 deg, where more than 80% of the total transmitted power is coupled to the desired Floquet space harmonic.
Modelling of Tunable CPW Structure Dielectric Phase Shifters

The high performance phase shifter is of significant interest in the modern communication system. New type coplanar waveguide (CPW) structure dielectrics phase shifters are reported; the microwave characteristics of the devices are systematically studied by the FEA method basing on HFSS (ANSYS Electronics®). It is found that the proposed phase shifters can operate over 10 GHz. The influence of active varactor area, dielectric thickness and the matching of pads are analyzed. The tuning effects of the phase shifters are also investigated by changing the relative permittivity $(\varepsilon_{r})$ of the dielectric layer. In order to increase the absolute phase shifting angle, assorted structures with multiple varactors are designed. By increasing the number of varactors, the phase angle shifting of the devices can be multiplied, but the insertion loss of the phase shifters will also increase. The proposed structures are compact and easy to fabricate, which can be used for the rapidly developing microwave industry.
A Model of Information Circulation and Transmission Network of Grid Cells in Entorhinal Cortex and Place Cells in the Hippocampus of Rat

Biological studies have found that the grid cells in the entorhinal cortex of the rat brain structure and the place cells in the hippocampus structure have a mutual input and output cyclic relationship in the process of information transmission, from entorhinal cortex-hippocampus information transfer loop. The traditional neural network model from grid cells to place cells is not enough to satisfy the information transmission relationships, ignores the information transfer from place cells to grid cells, to solve this problem, a neural network model based on grid cells in entorhinal cortex and place cells in hippocampus information transfer loop is proposed. The simulation results show that the model can simulate the firing characteristics of place cells and grid cells.
A Methodology to Determine Test Scenarios for Sensor Constellation Evaluations

This paper proposes a methodology for determining strategically bundled relevant test scenarios for the simulation- based evaluation of sensor constellations. This is achieved by gogri identification of important use cases for the autonomous driving operation, (b) the conversion of these use cases into Regions of Interests (ROIs) around the vehicle along with (c) a definition of a critical index (CI) for each of these regions and (d) a procedure to derive crucial scenarios and (e) categorise them into scenario families. The derived test scenarios help to optimise the field of view of the sensor constellation for the most important regions around the ego vehicle. The novelty lies in its independence from traditional methods of deriving test scenarios and its capability of providing targeted feedback to improve the sensor constellation at the identified pain points. The test scenario families can reduce the development time of highly automated vehicles by providing virtual testing of the sensor constellation performance in the vehicle concept phase.
A Multi-Level Convolution Pyramid Semantic Fusion Framework for High-Resolution Remote Sensing Image Scene Classification and Annotation

High spatial resolution (HSR) imagery scene classification has become a hot research topic in remote sensing. Scene classification method based on the handcrafted features, such as the bag-of-visual-words (BoVW) model, describes an image by extracting local features of the scene and mapping them to the dictionary space, but usually uses a shallow structure and loses the spatial distribution characteristics of the scene. The method based on deep learning extracts hierarchical features to describe the scene, which can maintain the spatial position information well. However, deep features in different levels have scale recognition restrictions for multi-scale ground objects, and cannot understand complex scenes well. In this paper, the multi-level convolutional pyramid semantic fusion (MCPSF) framework is proposed for HSR imagery scene classification. Differing from previous scene classification methods, which integrate the feature of different levels directly, of which the fusion features have large differences in both sparsity and eigenvalue magnitude, MCPSF integrates multi-level semantic features extracted by BoVW model and convolutional neural network (CNN) model. In MCPSF, two convolution pyramid feature expression strategies are proposed to enhance the ability of capturing multi-scale land objects, i.e., local and convolutional pyramid based BoVW (LCPB) model and local and convolutional pyramid based pooling-stretched (LCPP) model. The effectiveness of the proposed method is verified on 21-class UC Merced (UCM) dataset and 30-class Aerial Image Dataset (AID). The framework was also transferred toa case study of scene annotation in Wuhan. The proposed framework significantly improves the performance when compared with other state-of-the-art methods.
Research on Electrical Characteristics of Insulating Silicone Oil Based on Polarization-Depolarization Current Method

The DC conductivity and 0.1Hz dielectric loss factor of insulating silicone oil with different water content were measured by polarization-depolarization current method. The influence of water content in insulating silicone oil on polarization-depolarization current curve is analyzed, and the reason why the DC conductivity and 0.1 Hz dielectric loss factor of insulating silicone oil increase with increasing water content is given. Measured 15s and 60s insulation resistance and power frequency dielectric loss factor, the results show that with the increase of water content in insulating silicone oil, the trend of 15 s and 60 s insulation resistance is opposite to that of DC conductivity, the trend of power frequency dielectric loss factor is the same as that of 0.1Hz dielectric loss factor, the effectiveness of the polarization-depolarization current method in detecting DC conductivity and 0.1 Hz dielectric loss factor of insulating silicone oil is verified.
Cage Solitons

The theoretical framework of the Haus master equation of passive mode-locking is revisited. Reformulating the equation in the frequency domain as coupled ordinary differential equations, the complete set of fundamental soliton solutions is surveyed. For large values of anomalous dispersion, this leads to the well known bell-shaped solutions originally found by inverse scattering. Closer to zero dispersion, mode-locked spectra are affected by the available gain bandwidth, and solitons with Bessel-like temporal profiles are found. These spectrally caged solitons match previously unexplained pulse characterization measurements of few-cycle oscillators and mode-locked fiber lasers in the normal dispersion regime. Moreover, the frequency domain formalism suggests that a phase lock between the modes can even be established in the absence of saturable absorption. This finding may explain numerous mysterious experimental reports of mode-locking or comb formation in passive microring resonators and semiconductor lasers. Therefore our frequency-domain approach sheds new light into soliton physics from a completely different perspective.
Evaluation of Measurement Space Representations of Deep Multi-Modal Object Detection for Extended Object Tracking in Autonomous Driving

The perception ability of automated systems such as autonomous cars plays an outstanding role for safe and reliable functionality. With the continuously growing accuracy of deep neural networks for object detection on one side and the investigation of appropriate space representations for object tracking on the other side both essential perception parts received special research attention within the last years. However, early fusion of multiple sensors turns the determination of suitable measurement spaces into a complex and not trivial task. In this paper, we propose the use of a deep multi-modal object detection network for the early fusion of LiDAR and camera data to serve as a measurement source for an extended object tracking algorithm on Lie groups. We develop an extended Kalman filter and model the state space as the direct product Aff(2) × ℝ6 incorporating second- and third-order dynamics. We compare the tracking performance of different measurement space representations-SO(2) × ℝ4, SO(2)2 × ℝ3 and Aff(2)-to evaluate, how our object detection network encapsulates the measurement parameters and the associated uncertainties. With our results, we show that the lowest tracking errors in the case of single object tracking are obtained by representing the measurement space by the affine group. Thus, we assume that our proposed object detection network captures the intrinsic relationships between the measurement parameters, especially between position and orientation.
6LoWPAN Based Futuristic Smart Architecture for Home Automation

IPv6 over Low Power Wireless Personal Area Network (6LoWPAN) is an emerging area of research. It helps to extend network architecture for Wireless Sensor Network (WSN) which allows end-to-end connectivity between a 6LoWPAN node and any IP devices of the network. To make a low powered mesh network, 6LoWPAN is a promising solution on a simple embedded system. It’s target is to carry IPv6 packets efficiently within a small link layer of IEEE 802.15. 4 frame. Currently the absence of IP address hinders the process of accessing sensors directly. To overcome the problem, IP supporting sensors are necessary. According to 6LoWPAN technology each sensor will have a unique IPv6 address that will be auto-configured. So, the user can easily access the sensors data directly from the Internet without any gateway. In our proposed home automation, we have implemented it through COOJA simulator which is basically designed for wireless sensor network. It is exceptionally helpful for performing various and versatile tasks. It works in framework Contiki. In this proposed system a Contiki-based 6LoWPAN gateway is designed to interconnect with 6LoWPAN nodes through the Internet. Our home automation has found a better end to end communication, mobility, scalability and lower overhead which makes the system more convenient compare to other technology based automated system.
Detection of Microconidia in Microscopy Images of Fusarium oxysporum f. sp. cubense Using Image Processing Techniques and Neural Networks

Fusarium oxysporum f. sp. cubense (Foc) is a soilborne fungus and the causative agent of the deadly Fusarium wilt disease in banana plants. Left alone, the fungus is able to survive for years and infect multiple plants through the soil. External symptoms only manifest in late stages of infection, with the destruction of all plants within a 7.5 meter radius of the diseased through burning being the only way to eradicate the fungus. Foc Tropical Race 4 (TR4) is capable of infecting the widely used Cavendish cultivars, threatening global banana production. It is imperative then that Foc be detected as soon as possible. To achieve this, the study endeavors to detect microconidia, a reproductive structure of the Foc species, in microscopy images of stained soil specimen under three microscopy configurations using image processing techniques and convolutional neural networks (CNNs). The networks were built using the ResNet-50 architecture, and results were validated via Gradient-weighted class activation mapping (Grad-CAM). The network classifying fluorescent images achieved the highest accuracy with 95.24 %, followed by bright field images with 94.94%, all (bright field, dark field, and fluorescent) images with 93.75 %, and lastly, dark field images with 92.86%. Grad-CAM results indicate the networks are able to identify Foc structures and correctly distinguish clean from Foe-infected images. This study contributes towards the early detection of Foc, and is a step toward mitigating the threat it presents.
Rethink the IoU-based loss functions for bounding box regression

The $\ell_{\mathrm{n}}-$norm loss is widely used as the bounding box regression loss function in the existing object detectors, but Intersection over Union (IoU) is used to evaluate the accuracy of the bounding box locating. There is no inevitable correlation between low $\ell_{\mathrm{n}}-$norm loss and high IoU, so IoU-based loss functions represented by Io$\mathrm{U}^{+}$1, Generalized IoU(GIoU), Distance IoU(DIoU) and Complete IoU(CIoU) appeared. Based on the simulation experiment of bounding box regression, we point out that the existing IoU-based loss functions have the problems of slow convergence speed, large training error, and poor training result. From the specific bounding box regression process, the causes of the problems are explored, and a new loss function LIoU combining smooth $\ell_{1}-$norm loss and IoU is proposed. The experimental results on the two-stage object detectors Faster R-CNN, Mask R-CNN and the single-stage object detector RetinaNet consistently show that LIoU gets rid of the problems of the existing IoU-based loss functions and can further improve the performance of the object detectors. The source code and model training weights are open source on https://github.com/iamRyanChiaLIoU.1IoU+ refers to the IoU-based loss function used in UnitBox [1].
A 0.7-V Clock-gating Cell with Power Gating Technology and 1.56-pA Sleep Power

In digital circuits, dynamic power consumption caused by clock switching occupies a large part of the total power consumption. Dynamic power consumption can be effectively reduced by using clock-gating technology. In this work, a clockgating cell is proposed with sleeping mechanism under 0.7 V supply. Power gating is used to decrease the static power. The proposed cell can be used in circuit with frequency up to 1MHz typically. Compared to existing design, this work stands out for lower leakage current of 1.56 pA, which is suitable for circuits in low frequency where low power standard cell library is required.
Kinetics and Selectivity of the Fischer–Tropsch Synthesis: A Literature Review

A critical review of the kinetics and selectivity of the Fischer–Tropsch synthesis (FTS) is given. The focus is on reaction mechanisms and kinetics of the water–gas shift and Fischer–Tropsch (FT) reactions. New developments in the product selectivity as well as the overall kinetics are reviewed. It is concluded that the development of rate equations for the FTS should be based on realistic mechanistic schemes. Qualitatively, there is agreement that the product distribution is affected by the occurrence of secondary reactions (hydrogenation, isomerization, reinsertion, and hydrogenolysis). At high CO and H2O pressures, the most important secondary reaction is readsorption of olefins, resulting in initiation of chain growth processes. Secondary hydrogenation of α-olefins may occur and depends on the catalytic system and the process conditions. The rates of the secondary reactions increase exponentially with chain length. Much controversy exists about whether these chain-length dependencies stem from differe.
Optimization of the conductivity of microwave components printed by inkjet on polymeric substrates by photonic sintering

In this work, using a Drop on demand (DOD) inkjet printer, microwave resonators are printed on a polymer (polyimide) substrate with silver nanoparticle ink. To improve the electrical conductivity of the metallic deposit, two strategies are presented using sintering with pulsed light (IPL) over a broad spectrum of 190-1100 nm. The conductivity measured is improved from 50 to 138% for resonators working in range of 7-21 GHz.
Effect of pH on distribution and adhesion of Staphylococcus aureus to glass

The adhesion of Staphylococcus aureus ATCC 25923 to glass at different pH values was investigated using scanning electron microscopy (SEM) and image analysis with the Mathlab® program. The images obtained by SEM show that the adhesion behaviour of Staphylococcus aureus ATCC 25923 depends on the pH of the suspending medium. At highly acidic (pH 2, pH 3) and alkaline pH, the cells deposited in aggregate forms, while at pH 5 the aggregation phenomenon was absent. The quantitative adhesion (number of adhering cells to glass surface) showed that cells adhered strongly in the pH range 4 to 6 and weakly at highly acidic (pH 2, pH 3) and alkaline pH. Moreover, the surface properties of the cells were characterized by the microbial adhesion to solvents (MATS) method. A good correlation was obtained between physicochemical properties (hydrophobicity or electron donor electron acceptor character) of Staphylococcus aureus ATCC 25923 and the number of adhering cells to glass. These results show that the adhesion of Staphylococcus aureus ATCC 25923 to glass is controlled by both acid–base and hydrophobic interactions.
How Successful Has the UN Been in Maintaining International Peace and Security?

This year, the United Nations (UN) is celebrating its 75th year. Born out of war, the UN has sought to curtail plagues of a past characterized by two world wars. Based on the idea of liberal institutionalism where multilateral institutions are to facilitate inter-state cooperation, the UN intended to bring the major military powers together with the main task of maintaining international peace and security (Weiss 2018: 174, Hanhimaki 2015: 18). This has, however, been fraught with difficulties that this essay will address along with the challenges and opportunities with different peace and security initiatives, in an attempt to evaluate the UN’s success in its main task. It will specifically focus on peace operations, nuclear disarmament and humanitarian intervention, some of the main areas through which the UN is maintaining international peace and security (UN 2020a). As one main actor in global governance, I conclude that the real success of the UN has been in its role as a normative power, guiding the global understanding of acceptable behavior.
Laboratory Prediction of Soluble Compounds before Soil Recycling of Wastes

Abstract One of the best alternatives to waste disposal is through the soil-plant system as a fertilizer. Based on contrasting properties, different wastes can be co-recycled in order to take simultaneously the best profit and minimize environmental pollution. To predict the release of available nutrients and potentially toxic elements, before land application of two wastes (sewage sludge and fly ash), a laboratory experiment had been conducted using leaching and incubation of soil-waste mixtures. Loading rates of 500 t ha−1 of fly ash increased soluble compounds in soil solution, and the sewage sludge N-mineralization was inhibited. The proposed method could give an estimation for soluble elements and mineralizable-N compounds, avoiding undesirable land consequences of waste recycling.