Miracle-dz/UniFAR-FTUs huggingface dataset:
Effort-Aware Neural Automatic Post-Editing

For this round of the WMT 2019 APE shared task, our submission focuses on addressing the “over-correction” problem in APE. Over-correction occurs when the APE system tends to rephrase an already correct MT output, and the resulting sentence is penalized by a reference-based evaluation against human post-edits. Our intuition is that this problem can be prevented by informing the system about the predicted quality of the MT output or, in other terms, the expected amount of needed corrections. For this purpose, following the common approach in multilingual NMT, we prepend a special token to the beginning of both the source text and the MT output indicating the required amount of post-editing. Following the best submissions to the WMT 2018 APE shared task, our backbone architecture is based on multi-source Transformer to encode both the MT output and the corresponding source text. We participated both in the English-German and English-Russian subtasks. In the first subtask, our best submission improved the original MT output quality up to +0.98 BLEU and -0.47 TER. In the second subtask, where the higher quality of the MT output increases the risk of over-correction, none of our submitted runs was able to improve the MT output.
Smart Maintenance Model for Operational Planning of Static Synchronous Compensators

This paper proposes an innovative smart maintenance (SM) model for scheduling proactive preventive maintenance of static synchronous compensators (STATCOMs). The approach is primarily useful for optimal operational planning of STATCOMs to maximize net benefit that comes from the difference between the power losses reduction savings and the cost of STATCOM’s acquisition and maintenance. The SM model incorporates: 1. Markov chains to describe STATCOM reliability with aging features; and 2. Type I restoration factor to describe the impact of maintenance over component’s virtual age. The optimization problem is solved using the Accelerated Quantum Particle Swarm Optimization (AQPSO), which involves three stages. The first stage determines the optimum number, size, and placement of the STATCOMs. The second stage set the effective maintenance plan. The last stage governs the best operation of the STATCOMs. The results show the efficacy of the proposed model, opening a new pathway to future applications in smart grids.
Optimization of Cryogenic Deep Reactive Ion Etching Process for On-Chip Energy Storage

In this paper we optimize cryogenic deep reactive ion etching processes to achieve the best aspect ratios of holes in a silicon substrate that is supposed to be used for fabrication of on-chip energy storage. By optimizing capacitively coupled plasma source power and oxygen flow, aspect ratio of 28:1 for holes of 2 μm in diameter was achieved. Bottling effect was suppressed by tuning capacitively coupled plasma, inductively coupled plasma sources and process pressure at the same time. The smoothness and purity of the hole walls are other parameters we investigate using atomic force microscopy and X-ray photoelectron spectroscopy.
Demystifying IoT Security: An Exhaustive Survey on IoT Vulnerabilities and a First Empirical Look on Internet-Scale IoT Exploitations

The security issue impacting the Internet-of-Things (IoT) paradigm has recently attracted significant attention from the research community. To this end, several surveys were put forward addressing various IoT-centric topics, including intrusion detection systems, threat modeling, and emerging technologies. In contrast, in this paper, we exclusively focus on the ever-evolving IoT vulnerabilities. In this context, we initially provide a comprehensive classification of state-of-the-art surveys, which address various dimensions of the IoT paradigm. This aims at facilitating IoT research endeavors by amalgamating, comparing, and contrasting dispersed research contributions. Subsequently, we provide a unique taxonomy, which sheds the light on IoT vulnerabilities, their attack vectors, impacts on numerous security objectives, attacks which exploit such vulnerabilities, corresponding remediation methodologies and currently offered operational cyber security capabilities to infer and monitor such weaknesses. This aims at providing the reader with a multidimensional research perspective related to IoT vulnerabilities, including their technical details and consequences, which is postulated to be leveraged for remediation objectives. Additionally, motivated by the lack of empirical (and malicious) data related to the IoT paradigm, this paper also presents a first look on Internet-scale IoT exploitations by drawing upon more than 1.2 GB of macroscopic, passive measurements’ data. This aims at practically highlighting the severity of the IoT problem, while providing operational situational awareness capabilities, which undoubtedly would aid in the mitigation task, at large. Insightful findings, inferences and outcomes in addition to open challenges and research problems are also disclosed in this paper, which we hope would pave the way for future research endeavors addressing theoretical and empirical aspects related to the imperative topic of IoT security.
eTranslation’s Submissions to the WMT 2019 News Translation Task

This paper describes the submissions of the eTranslation team to the WMT 2019 news translation shared task. The systems have been developed with the aim of identifying and following rather than establishing best practices, under the constraints imposed by a low resource training and decoding environment normally used for our production systems. Thus most of the findings and results are transferable to systems used in the eTranslation service. Evaluations suggest that this approach is able to produce decent models with good performance and speed without the overhead of using prohibitively deep and complex architectures.
Adaptive Patterning of Optical and Electrical Fan-Out for Photonic Chip Packaging

Packaging and assembly challenges for photonic chips still need to be addressed in order to enable rapid deployment in mass-market production. Integration and assembly solutions that not only enable ease of packaging but also allow a dense co-integration of the electronic and photonic ICs are essential. In that context, we demonstrate an adaptive patterning of both optical and electrical fan-out for face-up electronic-photonic integration. For the optical fan-out, we developed an approach based on adiabatic optical coupling between single-mode polymer waveguides and silicon waveguides on a silicon photonic chip. The polymer waveguides were directly patterned on the silicon photonic chip by direct-write lithography (DWL). The electrical interconnects between a photonic chip and electronic IC are realized by employing high-speed silver interconnects using aerosol-jet printing (AJP), as a promising alternative for the traditional bond-wires. Furthermore, a direct comparison between the AJP interconnects and the conventional bondwires is established. Finally, an NRZ optical transmitter has been successfully demonstrated based on the AJP interconnection and clear open eye diagrams were obtained at 56 Gb/s.
Machine Translation with parfda, Moses, kenlm, nplm, and PRO

We build parfda Moses statistical machine translation (SMT) models for most language pairs in the news translation task. We experiment with a hybrid approach using neural language models integrated into Moses. We obtain the constrained data statistics on the machine translation task, the coverage of the test sets, and the upper bounds on the translation results. We also contribute a new testsuite for the German-English language pair and a new automated key phrase extraction technique for the evaluation of the testsuite translations.
In-Memory Computing: Advances and prospects

High-dimensionality matrix-vector multiplication (MVM) is a dominant kernel in signal-processing and machine-learning computations that are being deployed in a range of energy- and throughput-constrained applications. In-memory computing (IMC) exploits the structural alignment between a dense 2D array of bit cells and the dataflow in MVM, enabling opportunities to address computational energy and throughput. Recent prototypes have demonstrated the potential for 10 × benefits in both metrics. However, fitting computation within an array of constrained bit-cell circuits imposes a number of challenges, including the need for analog computation, efficient interfacing with conventional digital accelerators (enabling the required programmability), and efficient virtualization of the hardware to map software. This article provides an overview of the fundamentals of IMC to better explain these challenges and then identifies promising paths forward among the wide range of emerging research.
A Quasi-Dynamic Tool for Validation of Power System Restoration Strategies at Distribution Level

a quasi-dynamic tool suitable for validation of power system restoration (PSR) strategies at distribution level is proposed. The tool contains detailed models of loads and renewable energy source (RES)-based generation units from normal to PSR conditions. The models are utilized as back-ends of static and dynamic calculation modules. The static calculation module aims to run power flow calculation periodically in time intervals of a few seconds, while in the meantime, the dynamic module calculates the dynamic network frequency with a few millisecond resolution. The tool is capable of investigating the frequency stability degree of any Build-Up PSR strategy at distribution level (but not limited to that) both statically and dynamically in reasonable computation time.
Epoxy Composites with Surface Modified Silicon Carbide Filler for High Temperature Molding Compounds

With the rapid development of high power, high frequency and high-density electronics, heat management of the package has attracted intensive attention. Thermal conductivity is becoming an increasingly important parameter in the evaluation of packaging materials like EMCs. However, for polymer in encapsulation materials such as epoxy, their low thermal conductivity due to the phonon scattering issue greatly limits their ability in heat dissipation. Therefore, it is worthwhile to study the modification of filler system for the improvement of thermal conductivity of EMCs, since filler occupies 70-90 % of the weight in EMCs. In this work, SiC particles are coated with silane and rubberized layers for molding compounds as a modified filler. The effects of treated SiC filler on thermal conductivity and toughness in epoxy composite are studied at low filler loading.
A Method for Sizing Centralised Energy Storage Systems Using Standard Patterns

Low Voltage (LV) distribution networks with high penetration levels of photovoltaics have to tackle various challenges such as overvoltages, voltage fluctuations, reverse power flows, and non-coincident demand and local generation. Energy Storage Systems (ESS) can help to ease these issues, if sized properly. This paper proposes a two-step methodology for sizing centralised ESS in LV networks. In the first step, a reoccurring daily pattern is detected using symbolic aggregated approximation (SAX) from the data measured at a German grid. Afterwards, high- and low-frequency components of the power signal are separated using a low-pass filter and then used for sizing different types of ESS. The effect of data resolution on the sizing outcomes is also investigated. The performance of the method was investigated using the full data set. It is concluded that ESS with the characteristics derived using this methodology can effectively be used for peak shaving, power smoothing and load balancing.
Stochastic Energy and Reserve Market in a Microgrid Environment

The continuous proliferation of distributed energy resources (DER), mainly from renewable energy sources (RES) is changing the operational planning of distribution grids. Microgrids (MGs) as a small part of distribution grids are characterized by their ability to partially/fully self-producing their energy needs, and for the ability to trade different energy products (e.g. energy and reserve). This paper, addresses the energy and reserve market problem within the MG environment considering the RES uncertain production. Thus, a two-stage stochastic programming was modelled, minimizing the energy and reserve costs of the MG operator. A DC Optimal Power Flow (OPF) was incorporated to mitigate potential congestion that may occur in the MG. The assessment of the model is carried out through a test case based on actual generation data, considering a 37-bus distribution grid. The performance and accuracy of the model is determined based on the expected value of perfect information (EVPI) and value of stochastic solution (VSS).
Study of BEOL Failure Mode in Flip Chip Packages at High Temperature Conditions

As copper pillar bumps have been widely used in flip chip packages to meet the performance demand for denser IO bump and finer pitch, chip-package interaction (CPI) has been critical to achieving high yield rate and package reliability. With the increasing requirement for advanced technology nodes in high-performance devices, low-K (LK), extreme low-K (ELK) and ultralow-K (ULK) dielectric materials have been introduced in Back-End-Of-Line (BEOL) interconnects of silicon process. However, this poses a significant challenge for copper pillar bump interconnects in flip-chip packages since copper pillar is much stiffer than solder bump. During the cooling stage of chip attach reflow, a high stress could be induced in the fragile dielectric materials due to the thermal mismatch between the chip and substrate without any underfill protection right after chip attach. Intensive work has been studied to mitigate the CPI stress caused by the reflow process, such as package design optimization, cooling rate control, and assembly jig implementation, etc. Besides the BEOL dielectric delamination during chip attach, it was observed that the chip level LK/ELK failure could also occur even for assembled packages which already passed final test. It could happen during reliability tests or SMT process when packages go through a high temperature condition. This work presents a study of this failure mode and related mechanical mechanism. Flip chip using copper pillar bumps were tested in MSL 3 conditions to detect the failure mode. A multi-scale finite element model was developed to evaluate the CPI stress under different package conditions to understand the failure mechanism. First, a global model was built to include the bump array with individual bumps; then a detailed local bump model at fine scale with layered BEOL and copper pillar structure was built at the possible failed bump location to simulate stress on the dielectric layers. The simulation results have a good correlation with the test results to interpret the failure mode. The major factors impacting this failure mode include underfill material properties, polyimide opening (PIO), die thickness, UBM size, etc. are also studied. The simulation demonstrates the impact of package design associated with this failure mode.
Auto-LEE: A Novel Autonomous Lower Extremity Exoskeleton for Walking Assistance

Wearable exoskeletons have been proven to be efficacious in aiding walking for individuals suffering from lower limb mobility disorder. However, the application of most existing devices is limited to inconvenience of usage, e.g., complicated training and unnatural gait. This paper presents a novel autonomous lower extremity exoskeleton, Auto-LEE, for the purpose of improving the practicality of walking assistive devices as well as simplifying their application process. The developed exoskeleton consists of two robotic legs, and each of them has 5 active degrees-of-freedom (DOFs) to independently control the rotations of hip, knee and ankle joints in the sagittal and coronal planes, which enables the device to possess self-balancing ability and flexible gait. The modular design concept is introduced into the structure and hardware development of Auto-LEE, making it more convenient to be assembled and maintained. In order to validate the self-balancing walking ability, virtual prototype simulation and preliminary experiment on flat terrain are implemented.
Using the Ecovat system to supply the heat demand of a neighbourhood

In this paper we present a demand side management control approach for a neighbourhood, which includes a seasonal thermal storage, called the Ecovat system. The Ecovat system is used to satisfy the heat demand of this neighbourhood instead of gas boilers, which are currently used in most Dutch houses for this purpose. We observe that an Ecovat system is capable of supplying the heat demand of such a neighbourhood throughout the year, even if the heat demand is unexpectedly high, for example due to a harsh winter. As benefits we observe an 86.8 to 91.8% reduction in electricity fed back to the grid as well as a reduction in the amount of CO2 emitted yearly by 91.4 up to 138.8 ton, when using an Ecovat system instead of gas boilers to satisfy the heat demand of the neighbourhood.
RRT*-smooth Algorithm Applied to Motion Planning of Concentric Tube Robots

Concentric tube robots have broad prospects for the development of minimally invasive surgery. Concentric tubes consist of super-elastic nickel-titanium alloys, so they can exhibit different shapes when they are relatively rotated or translated. Moreover, compared to traditional robots, concentric tube robots are smaller and more flexible, they can work in tight spaces or complicated environments consequently. In this paper, for the application of concentric tube robot with dominant stiffness, the forward kinematics calculation formula and the detailed inverse kinematics geometry method are given. In addition, RRT*-smooth algorithm is proposed after smoothing twice based on RRT*, and compared with other motion planning algorithms. Experiments show that it can quickly plan a shortest path while guaranteeing collision-free.
Obstacle Avoidance Method of Robot Based on Admittance Control

Instead of traditional ranging radar and camera, Kinect was used to ensure the robot can avoid obstacles in the process of movement. And an obstacle avoidance method of robot was proposed based on admittance control. The relative distance between the robot and human hand was real-time measured by Kinect sensor and converted into a virtual force, acting as an input of the admittance controller to control the next moment speed of the controller to avoid obstacles. Then a modification algorithm for the robot's speed direction was added on the basis of admittance control, when the operator's arm is moving at a high speed, to control the robot's avoid obstacles urgently. At the same time, a method of singular transition to the joint space was proposed to solve the problem that once the robot encountering strange points in Cartesian space it will out of control. Finally, a physical experiment platform based on Kinect sensor and UR robot was set up to conduct dynamic and static obstacle avoidance experiments. The results verified the effectiveness of the proposed method.
A Highly Linear 28GHz 16-Element Phased-Array Receiver with Wide Gain Control for 5G NR Application

This paper presents a 28GHz 16-element phased-array receiver in a 28nm bulk RF CMOS process targeting 5G NR application. The receiver implements a high-gain low-NF LNA, a linearity enhanced RF amplifier with post-distortion, and RF/IF step attenuators for a wide gain range and fine gain step control. Thereby, the presented receiver demonstrated a system NF of 3.5dB, a gain control range of 50dB (1dB step), and an EVM of - 37.7/-43.1dB with 5G NR 800/100MHz signals while consuming a low power of 0.54W (equivalent to 33.5mW per channel).
Impact Analysis of V2G Services on EV Battery Degradation -A Review

Due to their promising feature in reducing greenhouse gas emissions, electric vehicles (EVs) have received overwhelming support in recent decades. One of the compelling ideas is that EVs serve as distributed energy storage and provide ancillary services to the electricity grid. From the concept to deployment, thorough research is required from the respective of technology, economics and policy. This paper gives a review of research works in terms of vehicle-to-grid (V2G) impacts on battery degradation. Battery degradation mechanisms and main stress factors are briefly summarized. Commonly used degradation models, classified as theoretical models, empirical models and semi-empirical models are reviewed in terms of mathematical expressions, advantages and disadvantages. Suitable applications of different models are highlighted. Based on the review of studies on V2G impacts on battery degradation, conclusions from current research and remarks for future work are given in this paper.
APE through Neural and Statistical MT with Augmented Data. ADAPT/DCU Submission to the WMT 2019 APE Shared Task

Automatic post-editing (APE) can be reduced to a machine translation (MT) task, where the source is the output of a specific MT system and the target is its post-edited variant. However, this approach does not consider context information that can be found in the original source of the MT system. Thus a better approach is to employ multi-source MT, where two input sequences are considered – the one being the original source and the other being the MT output. Extra context information can be introduced in the form of extra tokens that identify certain global property of a group of segments, added as a prefix or a suffix to each segment. Successfully applied in domain adaptation of MT as well as on APE, this technique deserves further attention. In this work we investigate multi-source neural APE (or NPE) systems with training data which has been augmented with two types of extra context tokens. We experiment with authentic and synthetic data provided by WMT 2019 and submit our results to the APE shared task. We also experiment with using statistical machine translation (SMT) methods for APE. While our systems score bellow the baseline, we consider this work a step towards understanding the added value of extra context in the case of APE.
Wideband Low-Profile Ka-Band Microstrip Antenna with Low Cross Polarization Using Asymmetry AMC Structure

In this work, a 28GHz microstrip antenna based on an asymmetric artificial magnetic conductor structure is proposed, which takes the features of low profile, high bandwidth, high gain, and low cross-polarization level. The principle that the AMC structure servers as a reflection plane of the microstrip antenna to widen bandwidth is deeply investigated. The mechanism of the H-plane cross-polarization level deterioration when the symmetric AMC structure is applied to the microstrip antenna is analyzed for the first time. The asymmetric AMC cell provides a 0° reflection phase for the E-plane horizontal electric field and a 180° reflection phase for the H-plane horizontal electric field. Therefore, it is used as a reflection plane to achieve both large bandwidth and low cross-polarization level. The simulation results demonstrate that the proposed antenna with 0. 056λ0 substrate thickness realizes the high bandwidth of 23% and low H-plane cross-polarization level of less than -20dB in band. The radiation efficiency is up to 97.6% at 27GHz while peak gain reaches to 10.1dBi at 31.2GHz.