Miracle-dz/UniFAR-FTUs huggingface dataset:
Blockchain-Based Safety Management System for the Grain Supply Chain

In recent years, various food-safety issues have aroused public concern regarding safety in the food supply chain. Since grains are closely linked to human life and health, it is necessary to effectively manage information in the grain supply chain. The grain supply chain is characterized by a long life cycle, complex links, various hazards, and heterogeneous information sources. Problems with traditional traceability systems include easy data tampering, difficult hazardous-material information management, the “information isolated island” problem, and low traceability efficiency in the whole supply chain. Blockchain is a distributed computing paradigm characterized by decentralization, network-wide recording, security, and reliability. As such, it can reduce administrative costs and improve the efficiency of information management. Based on literature research and a field investigation of wheat-processing enterprises in Shandong Province, We analyze the operation process of grain supply chain. This study, therefore, proposed a new system architecture in the entire grain supply chain based on blockchain technology and designed a multimode storage mechanism that combines chain storage. This prototype system was tested and verified using actual cases and application scenarios. Compared to traditional systems, the proposed system is characterized by data security and reliability, information interconnection and intercommunication, real-time sharing of hazardous-material information, and dynamic and credible whole-process tracing. As such, this system is highly significant and has reference value for guaranteeing food quality and safety-process traceability.
Propagating Asymptotic-Estimated Gradients for Low Bitwidth Quantized Neural Networks

The quantized neural networks (QNNs) can be useful for neural network acceleration and compression, but during the training process they pose a challenge: how to propagate the gradient of loss function through the graph flow with a derivative of 0 almost everywhere. In response to this non-differentiable situation, we propose a novel Asymptotic-Quantized Estimator (AQE) to estimate the gradient. In particular, during back-propagation, the graph that relates inputs to output remains smoothness and differentiability. At the end of training, the weights and activations have been quantized to low-precision because of the asymptotic behaviour of AQE. Meanwhile, we propose a M-bit Inputs and N-bit Weights Network (MINW-Net) trained by AQE, a quantized neural network with 1–3 bits weights and activations. In the inference phase, we can use XNOR or SHIFT operations instead of convolution operations to accelerate the MINW-Net. Our experiments on CIFAR datasets demonstrate that our AQE is well defined, and the QNNs with AQE perform better than that with Straight-Through Estimator (STE). For example, in the case of the same ConvNet that has 1-bit weights and activations, our MINW-Net with AQE can achieve a prediction accuracy 1.5% higher than the Binarized Neural Network (BNN) with STE. The MINW-Net, which is trained from scratch by AQE, can achieve comparable classification accuracy as 32-bit counterparts on CIFAR test sets. Extensive experimental results on ImageNet dataset show great superiority of the proposed AQE and our MINW-Net achieves comparable results with other state-of-the-art QNNs.
Thermal Simulations of a UV LED module with nanosilver sintered die attach process on graphene-coated copper substrates

The industrial market has been growing for high-power ultraviolet (UV) LEDs in curing, water purifying, and other applications that required high light output. As a rule of thumb, LED lumen output usually drops 0.3–0.5% for each 1°C increase in temperature while operating within the typical working temperature range. Such requirements for high-power UV LED modules indicate that innovative materials and processes for module packaging are needed to reduce thermal conductivity and to ensure high reliability.In this work, UVA (wavelengths between 365–405nm) LEDs were chosen, since the increasing usage in curing equipment for drying paints, adhesives, and other curable materials. In order to reduce the thermal conductivity of UVA LED packages, a high power UV Chip on Board (COB) based LED module was simulated. Compared with traditional modules using silver-filled adhesive and metal-core printed circuit boards(MCPCB) substrate, the novel high power UV COB based module was using nano-silver material for die attach process. Such silver sintering method is emerging for high power electronics applications. Such substrate is then sintered on copper heatsink which is covered by a thin layer of graphene, for better thermal management. Such novel structure was investigated using ABAQUS software and the Heat Transfer Module. The simulation is intended to first check how much thermal conductivity reduce caused by nanosilver sinter die attach process. Secondly, the simulation will also investigate the graphene influence on the copper heatsink. Results from the simulation will show the typical structural function of a 200W LED module with reduced thermal resistance up to 7%. The module temperature with edge-to-center temperature difference will also be checked as a standard to compare the heat dissipation capacity. Besides, the simulation will provide temperatures in various parts of the LED module in steady-state conditions, as an indication for reliability.
Study on the Variation Law of Sensitivity of Hydrophone Under the Condition of Acoustic Baffle

Aiming at the influence of anti-acoustic baffle on the acoustic characteristics of hydrophone, the sound field model of hydrophone under the influence of anti-acoustic baffle is established by using finite element software, and the sensitivity variation law is analyzed. The simulation results show that the anti-acoustic baffle and the hydrophone can be placed at 45°, and the former can increase the sensitivity of the latter by 6dB in a certain frequency range. This frequency range varies with the change in the anti-sound coefficient of the baffle and the distance between the hydrophone and the baffle. The research results have guiding significance for designing high-sensitivity hydrophones in the future.
Field Measurement and Empirical Models for Radio Signal Propagation Prediction in Baghdad

Mobile communications businesses have grown rapidly through recent years. In front of this development, quality of services may consider as a big challenge. Accordingly, the need for optimization in all mobile networks’ aspects is essential. The optimization starts from good planning which provides a good coverage area and hence the best signal quality. An important factor that playing the fundamental’s role in characterizing accurately the environment is the appropriate propagation model. In this work, an empirical model is being selected to characterize two regions, urban and suburban areas. The selected model will be adapted to analyze the performance of 2G and 3G mobile networks that are currently operated in Baghdad city. An extensive drive and walk test are conducted to collect the field measurement data. After comparative analyses between the simulated and the measured data, the results clarify that; Cost231-Hata model is the most suitable propagation model for the 2G network in all environment. Cost231-Hata model achieves the least Root Mean Squared Error (RMSE) equals to 3.37dB and 2.24dB for urban and suburban respectively. For the 3G network, Cost231-Hata model achieves the least RMSE equals to 8.17dB in an urban environment, while the ITU model is determined to be the suitable model for the suburban environment with RMSE equals to 4.45dB.
Development of a Remote Tracking Security Box with Multi-Factor Authentication System Incorporates with a Biometric Sensing Device

In this paper, a security box is designed for safe transportation of important and confidential documents. Most often it is necessary to convey confidential documents from one locus to another and these are being unveiled by the unbidden characters. Again the documents are sometimes not reached in the appointed destination. In this proposed system, the state and the location of the security box is continuously monitored from a base station. Again the implementation of multi-factor authentication (MFA) method for confirming one’s identity ensures the security of documents. The box is equipped with a biometric fingerprint sensor and a keypad for entering the passcode. An onboard display shows the current status of the box. In case of the accidental and unwanted opening of the box, a feedback system is provided for notifying the base station. Analyzing and mitigating the risks associated with the system security makes it reliable. The system performance exhibited in this paper validates the reliability of the security box.
A wideband 1-bit Reflective Metasurface Based on Linear Polarizer

This paper presents a novel wideband high-gain 1-bit reflective metasurface for 5G millimeter wave system. The metasurface unit cell is based on a wideband linear polarizer, which consists of a single-layer substrate with top polarization rotating patch (PRP) and bottom metallic ground. The proposed unit cell and its mirror image can maintain a stable 180° phase difference over a wide bandwidth of18–36 GHz. Thus, 1-bit phase quantization is obtained by using this property. Based on the linear polarizer, a single 1-bit reflectarray is designed and simulated. The simulated results show that focused pencil beam with high gain is successfully generated by the proposed metasurface and the maximum gain reaches to 21.62 dBi with 18.86% 1-dB gain bandwidth and 34.1% 3-dB gain bandwidth, respectively.
Stress Tester and Network Emulator in Apache JMeter

Cyber-attacks hit us every day and threat to individuals as well as businesses sphere. This paper describes Denial-of-service (DoS) attacks which are the common types of cyber-attacks. A denial-of-service attack floods online systems with traffic to exhaust resources and bandwidth. As a result, the system is unable to fulfil legitimate requests. Attackers can also use multiple compromised devices to launch this attack. This is known as a distributed-denial-of-service (DDoS) attack. The paper deals with developing of universal stress tester and network emulator based on open source project Apache JMeter. New modules developed for DoS attacks and network traffic generator into Apache JMeter will be described in this paper. The modules can test a network infrastructure and network parameters. First part of the paper contains a comparison of tools for stress testing and network emulators, description of common (D)DoS attacks and specification of transmission parameters of data networks. Recently common attacks, such HTTP Flood (Hypertext Transfer Protocol), SYN Flood, ICMP Flood (Internet Control Message Protocol), NTP (Network Time Protocol) Flood, UDP (User Datagram Protocol) Flood, DNS Server Flood (Domain Name Server), DNS Amplification, Slowloris, are described in second part of the paper.
Automated Health Care Analysis using Network Structure and Sprial Analysis

As bio and health technology continues to grow rapidly and become more and more ubiquitous, the need to pay attention to health concerns and the quality of medical care has increased. The first step in a healthcare analysis that will tackle these concerns is to analyze data from people who are interested in the health sectors via individual or group interviews. However, the traditional approach to this kind of health care analysis is based on person to person conversations followed by an expert’s decision, this has inherent limitations in terms of data scalability and the bias from experts’ prior knowledge. In this paper, we propose an Automated HealthCare Analysis (AHCA) approach using network structures and spiral analysis. AHCA generates network structures from real world datasets (health care interview results from real people) and specifies important keywords and their properties in terms of network structure. Then AHCA evaluates the impact on these keywords by removing the keywords iteratively. In this paper, an application of AHCA is designed, evaluated and analyzed for possible use as a new framework by using real world data.
Smart Center for Asset Management: Transformation to intelligent maintenance through digitalization

This document describes the stages of maintenance transformation by initiating its steps towards the non-interruptive predictive maintenance considered as Intelligent Maintenance, through the integration, aggregating and connecting of information for decision making with a holistic and asset-centered view. It is proposed that the relevant information of the assets be consolidated and displayed in the Smart Center for Asset Management, based on the proven and stable models developed in recent years in the ISA group. Among them are the equipment condition assessment (automatic diagnostic algorithms), health indexes, remaining life, assets criticality, presence of combustible gases, SF6 gas emission, assets geographic location, online monitoring, offline maintenance tests analytics, total asset costs and operational asset performance.
Proactive Controller Assignment Schemes in SDN For Fast Recovery

A sizeable software defined network with a single controller responsible for all forwarding elements is potentially failure-prone and inadequate for dynamic network loads. To this end, having multiple controllers improves resilience and distributes network control overhead. However, when there is a disruption in the control plane, a rapid and performant controller-switch assignment is critical, which is a challenging technical question. In this work, we propose a proactive switch assignment approach in case of controller failures using a genetic algorithm based heuristic that considers controller load distribution, reassignment cost and probability of failure. Moreover, we compare the performance of our scheme with random and greedy algorithms. Experiment results show that our proposed PREFCP framework has better performance in terms of probability of failure and controller load distribution.
Dynamics of High Peak Power Pulses near $1.9\ \mu \mathrm{m}$ in a Standard Single-mode Telecom Fiber

The higher-order solitons are the soliton pulses with the energy higher than that of the fundamental soliton. Although the higher-order solitons' temporal and spectral shapes are not constant, such pulses reproduce their shapes after a soliton period. Previous research assumed that higher-order solitons and high peak power pulses could be obtained in femtosecond Tm-doped all-fiber lasers. For many of these works, the higher-order dispersion and nonlinear effects lead to a pulse break up and higher-order solitons are not able to reproduce their shape during the propagation in the fiber. Such effects as stimulated Raman scattering, self-steepening and higher-order dispersion appear in the cases of a propagation of high energy pulses and can lead not only to a spectral broadening, but also to a soliton fission. That is why it is important to model pulse dynamics in the external fiber and carefully conduct the measurements of the pulse parameters, especially autocorrelation trace and spectrum, while registration of higherorder solitons. In this work, we study the propagation of higher-order solitons assuming the presence of higher-order effects and their absence near $1.9\ \mu \mathrm{m}$ in the SMF-28 fiber, as it's a common waveguide for pulse parameter measurements.
Occupational Therapy Interventions for Adults at the End of Life: A Systematic Review of Dignity Therapy

ABSTRACT The objectives of this study were to determine the effects of dignity therapy, a psychological intervention for individuals with terminal illness, and to explore whether this is an appropriate occupational therapy intervention. A literature search produced 10 dignity therapy studies for review. Four reported positive effects (decreased anxiety, depression, suffering), one reported negative effects (decreased quality of life, increased depression), and five reported no effects. With its client-centered and occupation-based approach, dignity therapy aligns with the values of occupational therapy. Practitioners should explore dignity therapy as an intervention and direct future research toward examining its efficacy as part of a holistic treatment plan.
Role imunosupresivní terapie ve vztahu k výskytu nádorových onemocnění po orgánové transplantaci

Organova transplantace, lecebna metoda schopna nahradit funkci devastovaneho organu a poskytnout tak zachranu života, respektive podstatně zvýsit jeho kvalitu, s sebou zaroveň nese řadu imunologických i neimunologických rizik, ktere mohou vest k zavažným komplikacim. Stale vice diskutovanou otazkou je vysoka incidence nadorových onemocněni u transplantovaných pacientů, ktera býva davana do souvislosti s nutným potlacenim imunitni odpovědi organizmu. Cilem naseho přispěvku je poskytnout zakladni charakteristiky role vybraných imunosupresiv v procesu vzniku a progrese nadorových onemocněni po organových transplantacich. Upozorňujeme na specifika ucinků mTOR inhibitorů a jejich možný benefit v managementu potransplantacnich malignit.
Cyclostationary Source Separation Based on Electrornagnetic Measurements in the Near-field of PCB

Characterization of stochastic unintentional electromagnetic radiations in the near field region of digital devices allows to simulate statistical characteristics of electromagnetic fields emitted to the surrounding space inside enclosures of digital devices. The near-field measurements by magnetic probes allow extracting the correlation characteristics of the stochastic process. Cyclic averaging with known cyclic frequency extracts the spatial positions containing the random signals with the defined cyclostationary properties. This allows separating random signals with different cyclic frequencies and also exclude the existing stationary noise from the obtained characteristics. Experimental validation of the proposed methodology for the stochastic cyclostationary sources separation was realized based on scanning system and digital oscilloscope.
Design of Bandpass Filters Based on Metamaterials

We will focus on the design of a bandpass filter based on complementary ring-shaped resonators. This structure is intended to operate in the band [0.5–3] GHz. The substrate used at a relative dielectric constant of $\varepsilon \mathbf {r} =2.2$, tangential losses tan ($\delta $) $=0.0009$ and a thickness of h $=0.508$ mm.
A Dielectric-horn Integrated Resonator Antenna for Point-to-point Wireless Communications

The upcoming early 5G communication network is going to be strongly based on wireless backhaul, midhaul and fronthaul radio links. Indeed, this application will allow, for mm-wave frequency ranges like 24, 28 and 39 GHz, a very large bandwidth to ensure high data rates avoiding any expensive fiber installation between the increasing number of radio base stations. This scenario opens to new opportunities for antenna designers since the wavelength reduction leads to more compact radiating structures. In this context, materials play a key role in this technology especially for what concerns high-performance low losses dielectric materials. In this paper, the design and electromagnetic analysis of a dielectric resonator antenna (DRA) are presented. The aim is to propose a 5G-ready antenna for point-to-point (PtP) links in the 28 GHz band. To this end, a novel design to boost the boresight gain of a cylindrical dielectric resonator antenna (CDRA) keeping sidelobes level (SLLs) below −10dB (relative to the peak gain) for both E- and H-planes is presented. Numerical results show that a fractional bandwidth of 14% with a peak realized gain of 13.2 dBi and a total efficiency greater than 80% is obtained.
An IMU/Sonar-based Extended Kalman Filter for Mini-UAV Localization in Indoor Environment

Micro Aerial Vehicles (MAV) have been seen rapid progress in the indoor entertaining, security monitoring, as well as search and rescue activities. The indoor localization with lightweight sensors in a Global Positioning System (GPS-denied) environment is a challenging topic for MAVs autonomous flight and path planning. This paper proposes a novel indoor localization approach relying on only the IMU and four ultrasonic sensors. Four mutually perpendicular installed ultrasonic sensors are used to provide distances of each direction. A prior map and an improved multiple rays model are constructed to approximate the measurement of the ultrasonic sensor. A fast algorithm to calculate the Jacobian matrix of the measurement function is given, then an Extended Kalman Filter (EKF) is conducted to fuse the information from IMU and the sonar sensor. The proposed algorithm is validated by the simulation and the results indicate good localization performance and robustness against compass measurement noise.
Regional Variability of Raindrop Size Distributions in Indonesia as Inferred from Principal Component Analysis

Distribution of precipitation in Indonesia is very unique due to a complex interaction between local factors such as complex shape, geography, and orientation of the island coastlines and global scale atmospheric circulations. Raindrop size distribution (DSD) which has important implications for remote sensing and several numerical modeling applications may also vary considerably across the region. This work provides new insights into precipitation microphysics in Indonesia as inferred from principal component analysis (PCA) with 7 attributes. The PCA is used to classify raindrop size distribution data collected through a network of the Particle Size and Velocity (Parsivel) optical disdrometer along equatorial Indonesia. The Par-sivel were installed at Manado (Sulawesi) and Biak (Papua). In addition to the aforementioned sites, we have been conducting DSD observations at Padang, Sicincin, Kototabang (Sumatra) and Pontianak (Kalimantan). We divided the data into 6 DSD groups indicating six unique DSD characteristics. It was found the percentage of DSD in group V (large Do and low Nw) at Kototabang, Sicincin, Padang and Pontianak is larger than that at Manado and Biak. On the other hand, the percentage of data point in group IV (small Do and large Nw) and VI (small Do and very large Nw) at Manado and Biak is smaller than other locations.
Fast and Reliable Offloading via Deep Reinforcement Learning for Mobile Edge Video Computing

In this paper, we propose an adaptive video streaming method which is inspired by deep reinforcement learning in mobile edge computing systems for autonomous driving applications. In fast moving autonomous driving applications, it is challenge to design fast and reliable video streaming (those are obtained by vision-based autonomous vehicles) task offloading. This paper handles this issue inspired by deep Q-network (DQN) which is one of the most well-known deep reinforcement learning algorithms.