Miracle-dz/UniFAR-FTUs huggingface dataset:
Building a Best-in-Class De-identification Tool for Electronic Medical Records Through Ensemble Learning

The natural language portions of an electronic health record (EHR) communicate critical information about disease and treatment progression. However, the presence of personally identifying information in this data constrains its broad reuse. In the United States, the Health Insurance Portability and Accountability Act of 1996 (HIPAA) provides a de-identification standard for the removal of protected health information (PHI). Despite continuous improvements in methods for the automated detection of PHI over time, the residual identifiers in clinical notes continue to pose significant challenges - often requiring manual validation and correction that is not scalable to generate the amount of data needed for modern machine learning tools. In this paper, we describe an automated de-identification system that employs an ensemble architecture, incorporating attention-based deep learning models and rule based methods, supported by heuristics for detecting PHI in EHR data. Upon detection of PHI, the system transforms these detected identifiers into plausible, though fictional, surrogates to further obfuscate any leaked identifier. We evaluated the system with a publicly available dataset of 515 notes from the I2B2 2014 de-identification challenge and a dataset of 10,000 notes from the Mayo Clinic. We compared our approach with other existing tools considered best-in-class. The results indicated a recall of 0.992 and 0.994 and a precision of 0.979 and 0.967 on the I2B2 and the Mayo Clinic data, respectively.
Genetic optimization of short block-length PAC codes for high capacity PHz communications

With the ongoing deployment of 5G cellular networks, the research and development of 6G technologies have recently triggered. The current studies begin to explore the higher frequency bands, such as Terahertz (THz) and Petahertz (PHz). In order to meet the requirements PHz communications, we focus on the novel coding schemes with short block-length and high code rate. Last year, Arikan proposed new concatenated codes called polarization-adjusted convolutional (PAC) codes. Under the Fano decoding, the performance of PAC codes with short block-length can approach Polyanskiy-Poor-Verdu (PPV) bound. In order to reduce complexity, list decoding of PAC codes is proposed. However, there is no general construction method for PAC codes with different block-lengths and code rates. In order to obtain an effective solution of PAC codes construction with higher code rates and longer lengths, we propose a genetic algorithm (GenAlg) based optimization scheme of PAC codes evaluated by list decoding. The simulation results show that a (512, 256) PAC code optimized by the proposed GenAlg scheme can achieve a noticeable performance gain of 0.25 dB at block error rate (BLER) of 10−3, when compared to the PAC code constructed by Gaussian approximation (GA). A (256,192) PAC code constructed by our scheme can lend to a coding gain of 0.3 dB at BLER of 10−2 when compared to the PAC code constructed by Gaussian approximation (GA).
Host−Guest Energy Transfer: Semiconducting Polymer Nanoparticles and Au Nanoparticles

Here, we demonstrate the energy transfer from the semiconducting polymer nanoparticles, poly(N-vinylcarbazole) (PVK), (2-(4-biphenylyl)-5-(4-tert-butylphenyl)-1,3,4-oxadiazole) (PBD), and a mixture of PVK and PBD blended polymer nanoparticles, to Au nanoparticles using steady-state and time-resolved photoluminescence spectroscopies. The PL quenching values are 65, 30, 57, and 53% for PVK, PBD, and 5 and 10 wt % PBD-doped PVK nanoparticles, respectively. The PL quenching and shortening of the decay time in the presence of Au nanoparticles suggest the energy transfer from polymer nanoparticles to Au nanoparticles. The increase of nonradiative rates in the presence of Au nanoparticles reveals the nonradiative resonance energy transfer from polymer nanoparticles to Au nanoparticles. The calculated energy transfers are 80.8, 72.3, and 77.07%, respectively, for pure PVK, 5 wt % PBD-doped PVK, and 10 wt % PBD-doped PVK nanoparticles. Using Forster resonance energy transfer and surface energy transfer methods, we.
Single multimode fiber focused spot scanning based on a liquid crystal spatial light modulator

At present, there are some problems in the digital scanning imaging methods of multimode optical fiber, such as poor quality of focused spot, large amount of calculation and long time in the forming process of focused spot. In order to solve the above problems, a parallel phase compensation method based on liquid crystal spatial light modulator (LCSLM) is proposed to achieve fast point-focused scanning of multimode fiber (MMF). The parallel algorithm, which includes the two processes of collecting online specklegrams and calculating offline phase masks, calculates the compensation phase masks so that the phase masks can be loaded on SLM in turn to generate a series of focused spots at different predefined positions, which greatly saves time. Experiments demonstrate that this method doesn’t need many iterations, and the phase compensation mask used for focusing spot at a predefined position on the MMF output facet can be obtained by using a two-step phase-shifting technique, and a series of phase compensation masks can be quickly obtained by using the parallel method, so as to form focused spots at different predefined positions. Experimentally, we obtained 100 focused spots, the average focused efficiency was 30.12%, the average focused diameter was 2. 3382μμm, and the quality of the focused spot was improved compared with previous reports.
Research on intelligent network control mechanism and protocol verification of spatial information network

With the increase of the number of satellite systems and the diversity of satellite loads, the satellite networks present obvious heterogeneity. The centralized management and control characteristics of SDN provide ideas for the unified management of satellite heterogeneous network resources, and the programmable control plane also provides the possibility of dynamic reconfiguration of satellite networks. It is necessary to explore a centralized network architecture based on SDN, so as to manage and control the satellites better. Moreover, an emulation platform has been designed with respect to verifying the feasibility of our network paradigm. Firstly, this paper analyzes the development status of satellite network management and control and the exploration of SDN in terms of satellite network management and control. Secondly, this paper points out some challenges in the application of SDN in satellite network management and control. Thirdly, this paper also proposes a SDN-based satellite network management and control architecture, and proposes a hardware emulation platform based on OpenFlow switches. Finally, this paper adopts a programming method to simulate the satellite network scenario, completes the load migration of burst traffic when the link utilization rate exceeds 80%, and proves the feasibility of using SDN to control the satellite network.
Chromatic dispersion monitoring for coherent optical communications using artificial neural network

With the development of coherent optical communication systems, the optical communication networks are becoming more dynamic and complex. The optical signals in communication networks are vulnerable to various impairments. Therefore, optical performance monitoring (OPM) is essential for optical networks, which ensures the robustness of the networks. Real-time chromatic dispersion (CD) monitoring is the basis for the compensation of CD induced transmission impairment. Therefore, to enable the high quality-of-service of reliable optical networks, it is essential to implement accurate CD monitoring for fiber optical transmission link. In this paper, we present a blind CD estimation method in conjunction with artificial neural network (ANN) for polarization division multiplexing (PDM) coherent optical communication systems. The CD monitoring range is set from 1340ps/nm to 9380ps/nm with step of 1340ps/nm. We experimentally demonstrate the proposed method in PDM quadrature phase-shift keying (QPSK), PDM 16 quadrature amplitude modulation (16-QAM) and PDM 64-QAM systems. The experiment results in our scheme show that CD values can be estimated successfully. The root-mean-square errors (RMSEs) of CD monitoring for 112Gbps PDM QPSK, 112Gbps PDM 16-QAM and 120Gbps PDM 64-QAM are 3.79ps/nm, 7.57ps/nm and 9.68ps/nm respectively.
Error Bounds on the Loggamma Function Amenable to Interval Arithmetic

Unlike other common transcendental functions such as log and sine, James Stirling's convergent series for the loggamma (“logΓ”) function suggests no obvious method by which to ascertain meaningful bounds on the error due to truncation after a particular number of terms. (“Convergent” refers to the fact that his original formula appeared to converge, but ultimately diverged.) As such, it remains an anathema to the interval arithmetic algorithms which underlie our confidence in its various numerical applications. Certain error bounds do exist in the literature, but involve branches and procedurally generated rationals which defy straightforward implementation via interval arithmetic. In order to ameliorate this situation, we derive error bounds on the loggamma function which are readily amenable to such methods.
The ADAPT’s Submissions to the WMT20 Biomedical Translation Task

This paper describes the ADAPT Centre’s submissions to the WMT20 Biomedical Translation Shared Task for English-to-Basque. We present the machine translation (MT) systems that were built to translate scientific abstracts and terms from biomedical terminologies, and using the state-of-the-art neural MT (NMT) model: Transformer. In order to improve our baseline NMT system, we employ a number of methods, e.g. “pseudo” parallel data selection, monolingual data selection for synthetic corpus creation, mining monolingual sentences for adapting our NMT systems to this task, hyperparameters search for Transformer in lowresource scenarios. Our experiments show that systematic addition of the aforementioned techniques to the baseline yields an excellent performance in the English-to-Basque translation task.
Research on the single event effect of CCD analog front-end for satellite-borne directional polarization camera

The directional polarimetric camera (DPC) is a satellite sensor with the aim to observe the polarization and directionality of the earth’s reflectance, developed by Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences. The analog front-end signal processor is the key to realize the conversion from the analog input signal of the front-end CCD image to the digital processing signal of the back-end. Its performance directly determines the image quality of the instrument. In this paper, the single particle locking effect of the CCD analog front-end signal processor of the Directional Polarization camera after being irradiated by high-energy particles is studied, the test scheme and the test system composition of the single particle locking effect are introduced, and the dynamic working current of the device and the change rule of the dynamic output digital code signal and other parameters are analyzed. The experimental results show that when the LET threshold of high-energy particles is greater than 13.4 MeV•cm2•mg-1, the dynamic working current of the analog front-end signal processor increases significantly, the dynamic output digital code cannot change with the change of the input signal, and single particle locking occurs in the chip. These research results provide significant reference data for in-depth study of single particle locking protection of analog front-end signal processor in space application environment.
AlGaAs Bragg reflection waveguide design optimization for photon pair generation

AlGaAs is one of the most promising integrated quantum photonics material. It has second order nonlinear coefficient which could support spontaneous down conversion (SPDC) process. The phase matching requirement could be achieve by specific designed Bragg reflection waveguide (BRW). In this paper, AlGaAs BRW was designed and simulated. Wavelength relationship of type II SPDC’ three photons were calculated. Epitaxy thickness and composition variation effects were also calculated.
Efficient inverted polymer solar cells using low-temperature zinc oxide interlayer processed from aqueous solution

In this work, an aqueous solution method that entails processing at low temperatures is utilized to deposit a ZnO interlayer in poly(3-hexylthiophene-2,5-diyl):[6,6]-phenyl C61 butyric acid methyl ester-based inverted polymer solar cells (PSCs). The effect of ZnO annealing temperature from 50 to 150 °C on PSC performance is systemically studied and it is found that the transition point is approximately 80 °C. When the ZnO annealing temperature is higher than 80 °C, PSCs show similar current density–voltage (J–V) characteristics and achieve a power conversion efficiency higher than 3.5%. Transmittance spectrum, PL spectrum, and surface morphology studies show that an annealing temperature above 80 °C is sufficient for ZnO to achieve a relatively good quality, and that a higher temperature only slightly improves ZnO quality, which is confirmed from statistical results. Furthermore, flexible PSCs based on PET substrates show a comparable power conversion efficiency and good flexibility.
Photoacoustic detection of glucose for the milk-glucose mixed solution

In this study, the glucose was detected by using the photoacoustic spectroscopy method for the milk-glucose mixed solutions. To achieve the purpose, a kind of photoacoustic detection system of glucose was established by using the OPO pulsed laser. Meanwhile, a focused ultrasonic detector with central echo frequency of 2.5MHz was used to capture the photoacoustic signals of glucose. And a kind of custom-built cycling sub-system used to analogy the flow system of pure blood in the vessel of human being. In experiments, a series of mixed solutions with different concentrations of milk and glucose were prepared and excitated by the pulsed laser beam with the wavelength of 1064nm and the output energy about 1mJ. The time-resolved photoacoustic signals, the peak-to-peak values and peak-point times for the mixed solutions with different concentrations were all obtained. Experimental results show that with the increase of the concentration of milk and glucose, the peak times decrease, i.e., the ultrasonic velocity increases. For the mixed solutions with fixed concentration of milk but different concentrations of glucose, the photoacoustic peak-to-peak values of glucose increases with the increase of the glucose concentration. However, for the mixed solutions with fixed concentration of glucose but different concentrations of milk, the photoacoustic peak-to-peak value of glucose decreases with the increase of milk concentration. The results can be interpreted by the reason that the light absorbance of glucose is decreased by the increase of the milk concentration due to the increase of the light-scattering effect in the turbid solutions. The prediction models of glucose were built for the different mixed solution for the milk and glucose. Then, the prediction correlation coefficients and root-mean-square error (RMSE) values were also gotten. Results show the correlation coefficient can reach 0.986 in the milk-glucose mixed solutions, and the smallest RMSE value is about 18.24mg/dl .
HDecoder: a hardware LDPC decoder using high level synthesis for phase modulated collinear holographic storage

Phase-modulated collinear holographic storage is promising high storage density at cost of high raw bit error rate. We first performed a simulation to analyze the bit-error-rate characteristics of phase-modulated collinear holographic storage under different noise intensity. To ensure high storage capacity with acceptable user biterror-rate, LDPC (Low Density Parity Check Code) is introduced to ensure data reliability. We further analyze the LDPC code error correction performance under different factors and determine the appropriate hardware parameters for the LDPC decoder. Finally, we use High Level Synthesis to fast implement and optimize an LDPC FPGA-based hardware decoder, named as HDecoder. HDecoder achieves 204Mbps decoding throughput, 150x and 4850x higher than CPU-based software decoder and the HLS-based vanilla hardware decoder. Compare to HLS-based vanilla LDPC decoder, HDecoder consumes 55x lower hardware resource per Mbps.
Design of diffractive optical element for ultra-thin deep ultraviolet imaging system

Optical imaging systems operating in the deep ultraviolet (UV) waveband have many applications in nanofabrication, medical and cellular imaging. However, Current deep UV optical systems are large form factors and complications since they usually base on the refractive lens and the limitation of available materials in deep UV waveband. The main reason is that chromatic and thermal aberration of the refractive lens is challenging to correct under limited available materials. In this paper, we proposed to use a single diffractive optical element (DOE) to construct a lightweight and ultra-thin UV imaging system. The achromatic realize base on the end-to-end design of the DOE and the following image processing algorithm. The athermalization achieves due to the inherent small thermal aberration of DOE. We design a DOE with a focal length of 50 mm, F-number of 4, and effective thickness of only 1μm for deep UV application. Simulation results show it realized excellent deep UV imaging performance over the waveband of 240 nm ~ 280 nm and working temperature range of - 40 °C ~ + 80 °C.
Applying Machine Learning to the Task of Generating Search Queries

In this paper we research two modifications of recurrent neural networks – Long Short-Term Memory networks and networks with Gated Recurrent Unit with the addition of an attention mechanism to both networks, as well as the Transformer model in the task of generating queries to search engines. GPT-2 by OpenAI was used as the Transformer, which was trained on user queries. Latent-semantic analysis was carried out to identify semantic similarities between the corpus of user queries and queries generated by neural networks. The corpus was converted into a bag of words format, the TFIDF model was applied to it, and a singular value decomposition was performed. Semantic similarity was calculated based on the cosine measure. Also, for a more complete evaluation of the applicability of the models to the task, an expert analysis was carried out to assess the coherence of words in artificially created queries.
Interactive Parallelization of C Programs in SAPFOR

SAPFOR (System For Automated Parallelization) is a software development suite that is focused on cost reduction of manual program parallelization. SAPFOR produces parallel programs according to the high-level DVMH parallel programming model. SAPFOR relies on an implicitly parallel programming model, so it includes an automatic parallelizing compiler. On the other hand, it allows the user to guide parallelization. The system provides the user with a set of source-to-source transformations which can be performed in an automatic way. The user may also assert some implicit program properties useful for parallelization. This paper presents the interactive subsystem of SAPFOR and discusses how it supports iterative parallelization. We advocate the use of the client-server model to organize the interaction with the user. We also present the data transfer optimization technique the automatic parallelizing compiler implements. This technique reduces communication overhead when GPU is used to execute a parallel program. We guide SAPFOR to perform semi-automatic parallelization of the NAS Parallel Benchmarks 3.3. 1. The paper evaluates the performance of parallel versions that SAPFOR builds automatically and compares it with the performance of manually written versions.
Numerical Optimization of Non-Conflict Aircraft Flow Merging (short paper)

Nowadays, aircraft move along routes consisting of horizontal tunnels and vertical flight levels. With that, the routes can split or join. At the point of route joining, a problem of aircraft flows merging appears. Such a problem is highly important near airports, where the air traffic is very dense. The main demand for aircraft flows merge is the presence of the minimal safe time interval between arrival instants at the merge point. There are two main tools for changing arrival instant of an aircraft to a checkpoint. The first of them is control of the aircraft velocity, which allows to obtain relatively small changes of the arrival instant both to earlier or later times. To get larger delays one uses the second tool, delay schemes. As a result of designing system of delay schemes for a certain airport, one has information about possible acceleration and deceleration of aircraft moving along each route. Further on the basis of this information, it is necessary to study capabilities of the constructed system for formation of safe aircraft flows merge. In the paper, a formalization is set forth for the problem of optimal formation of aircraft arrival schedule under the present delay scheme system as a finite-dimensional optimization problem. Also, the authors consider applicability of different methods for search of multivariable function extrema to this problem. Results of numerical computations are discussed.
Steinmetz: Toward Automatic Decomposition of Monolithic Software Into Microservices

Industry is adopting the microservices paradigm for greenﬁeld development as well as for migrating monolithic software. However, the latter approach involves signiﬁcant manual work, speciﬁcally in the early stages of the decomposition process, when determining boundaries between the services. We devise a methodology to automatically generate microservice candidate recommendations for any given monolithic software. We leverage three coupling dimensions: static, semantic, and evolutionary. For each dimension, we calculate a weighted graph. We aggregate the three dimensions into a single graph that we cluster into microservice candidate recommendations. We evaluate our methodology using several established metrics as well as our PoC implementation, Steinmetz 1 . Preliminary re-sults are encouraging: the methodology works as expected, there are clear results regarding feasibility of metrics to assess the quality of microservice candidate recommendations, and we are able to identify the best suitable graph clustering algorithm.
"Is anybody there?": exploring the use and difficulties of Brazilians with conversational systems

Conversational Systems (CSs) are increasingly being used and receiving investments. However, these systems can present problems that discourage users from using them. This paper aims to verify the opinions of Brazilian users and ex-users of CSs about the use of these systems and their possible difficulties. We conducted an online survey with several questions about the use of CSs and obtained 113 respondents from different knowledge areas, such as law, agronomy, health, computing, among others. Results reveal some issues in the Brazilian context that negatively influence the use of CSs, such as accent, lack of support for the Portuguese language, and internet access problems. Despite this, results show that respondents consider CSs easy to use and satisfactory. We hope our results can contribute to improving these systems for the Brazilian context, providing insights for the exploration of new strategies for designers and developers.