Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-Agnostic Metalearning-Based Text-Driven Visual Navigation Model for Unfamiliar Tasks

As vision and language processing techniques have made great progress, mapless-visual navigation is occupying uppermost position in domestic robot field. However, most current end-to-end navigation models tend to be strictly trained and tested on identical datasets with stationary structure, which leads to great performance degradation when dealing with unseen targets and environments. Since the targets of same category could possess quite diverse features, generalization ability of these models is also limited by their visualized task description. In this article we propose a model-agnostic metalearning based text-driven visual navigation model to achieve generalization to untrained tasks. Based on meta-reinforcement learning approach, the agent is capable of accumulating navigation experience from existing targets and environments. When applied to finding a new object or exploring in a new scene, the agent will quickly learn how to fulfill this unfamiliar task through relatively few recursive trials. To improve learning efficiency and accuracy, we introduce fully convolutional instance-aware semantic segmentation and Word2vec into our DRL network to respectively extract visual and semantic features according to object class, creating more direct and concise linkage between targets and their surroundings. Several experiments have been conducted on realistic dataset Matterport3D to evaluate its target-driven navigation performance and generalization ability. The results demonstrate that our adaptive navigation model could navigate to text-defined targets and achieve fast adaption to untrained tasks, outperforming other state-of-the-art navigation approaches.
Machine-Learning based Traffic Forecasting for Resource Management in C-RAN

The assumption of a fixed computational capacity at the Baseband Unit (BBU) pools in a Cloud Radio Access Network (C-RAN) deployment results in underutilized resources or unsatisfied users depending on traffic requirements. In this paper a new strategy to predict the required resources based on Machine Learning techniques is proposed and analysed. Support Vector Machine (SVM), Time-Delay Neural Network (TDNN), and Long Short-Term Memory (LSTM) have been tested and compared to select the best predicting approach. Instead of using a regular synthetic scenario a realistic dense cell deployment over Vienna city is used to validate the results. Authors show that the proposed solution reduces the unused resources average by 96 %.
All-Optical 2 $ \times $ 2-Bit Multiplier at 40 Gb/s Based on Canonical Logic Units-based Programmable Logic Array (CLUs-PLA)

Multiplication is an important function of logic operation, and all-optical high-speed multiplication logic operation will lay the foundation for future high-speed optical computing and optical logic processing chip. In this article, by introducing the structure of canonical logic units-based programmable logic array (CLUs-PLA), we propose a scheme to realize all-optical 2 × 2-bit multiplier. In our scheme, different types of CLUs are generated using bidirectional multichannel four-wave mixing (FWM), then the results of multiplier at the operation of 40 Gb/s can be obtained by simple power coupling of corresponding CLUs. Eye diagrams of logic results are widely open, and the extinction ratios are more than 9.4 dB. Comparing with multiplier based on traditional hierarchical computing, multiplier based on parallel computing in our scheme can reduce the number of AND gate by 4, and avoid further deterioration of signal quality due to three-order cascade of AND gate. Moreover, the scheme has the potential to realize m × n-bit ($m + n \leq 9$, m and n are positive integers) multiplier at higher operation rate in the integrated platform, paving the way towards multi-bit high-speed compact complex logic devices for future high-performance optical computing and optical logic processing chip.
Fuzzy Logic Classifier and Conditional Responses Algorithm for Gestural Input Game

This paper presents hand gesture classification using fuzzy logic, with an application to the Rock-Paper-Scissors game. It includes a comparison between a simple threshold classifier and the Fuzzy Logic classifier. The real-time gesture recognition is implemented for the Leap Motion input device. Although the human’s game gesture pattern may seem random, some recent work suggests how it is possible to predict an opponent’s gesture, from a previous gesture, with better-than-random success. Based on this, we designed a conditional-response algorithm making the behavior of the virtual player more similar to a real human. Using networking tools, we enable game play remotely against other players. The game was experimentally evaluated with eleven players, reaching an average online classification accuracy of 97.35% for hand pattern recognition. The evaluation metrics are represented in confusion matrices.
Silage of Prickly Pears (Opuntia spp.) Juice By-Products

Simple Summary The cactus pear plant is a Cactaceae which originates from the Americas and is highly resistant to arid and hot environments. The plant is used as animal feedstuff in regions characterized by a lack of nutrient resources. In Italy, the fruits are known as prickly pears are usually eaten fresh by humans, and more recently have also started to be transformed into fruit juice. Various by-products (i.e., peel, pulp, and seeds) derived from the extraction of fruit juice are used for livestock feed due to their high amounts of fermentable structural carbohydrates. However, some of these by-products are difficult to conserve due to their high fermentability. The aim of the present study was to produce micro-silages of prickly pear by-products with different level of wheat straw (0, 5, and 10% as fed) and evaluate their chemical characteristics and fermentation kinetics using the in vitro gas production technique. Both chemical parameters (higher crude protein and lower neutral detergent fibre) and in vitro fermentation data demonstrated that the silage obtained with 5% of straw as the best-preserved (lower pH and ammonia nitrogen concentration). Abstract Cactus pear cladodes are used as forage in the most arid regions. In Italy, the human consumption of prickly pear fruits and juice is gradually increasing for their numerous health benefits. In manufacturing plants that produce prickly pear juice, several by-products (prickly pear by-products PPB) are obtained. Despite their interesting nutritional characteristics, PPB are not very usable because of their poor shelf-life which is related to their high moisture and sugar content. The aim of this study was to verify the efficacy of ensilage to preserve PPB and to compare different inclusion levels (0, 5, and 10% as fed) of wheat straw. For each treatment, four under vacuum micro-silos were prepared and, after 35 days of storage, the state of preservation was evaluated. Subsequently, the aliquots were analyzed for chemical composition and incubated with bovine rumen fluid to evaluate the fermentation kinetics. The PPB 5% of straw showed significant lower pH and ammonia nitrogen concentration, indicating a better preservation process. Moreover, PPB 5% of straw showed better nutritional parameters (higher crude protein and lower Neutral Detergent Fibre) and fermentation characteristics (higher degradability and VFA volatile fatty acids production) when compared with the other PPB silages. Ensilage with straw represents a suitable storage technique to preserve the nutritional characteristics of PPB.
A Low loss feed line for patch antenna based on silicon in millimeter-wave applications

Silicon substrate plays an important role in 3D package integration due to the precise wiring process and low CTE of materials. However, the high loss of silicon limits its application in millimeter-wave field. In this paper, a low loss feed line comprised of CPW(coplanar waveguide) with shield line and S-COV(silicon-core coaxial via) is proposed and applied to stimulate a millimeter-wave patch antenna. The proposed feed line process is also presented, which is simple, compatible with conventional semiconductor processes and time-saving compared with a traditional TSV. Simulation results show that the feed line has similar electrical characteristics as the ordinary feed solution based on organic substrate, even though this path is through common low resistance silicon substrate. In well-matched condition, the measured insertion loss of the feed line is -0.3 dB at 80 GHz. The antenna fed by this structure has small performance reduction, revealing its feasibility in vertical antenna feed or even 3D integration in millimeter-wave applications.
Rotation-Invariant Wafer Map Pattern Classification With Convolutional Neural Networks

The enhancement of production yield is a continuous challenge in semiconductor manufacturing. Analyzing the spatial defect patterns of previously processed wafers is a key step in identifying the root causes of yield degradation. Predictive modeling approaches have been successful in automated wafer map pattern classification. The classification performance depends significantly on the quantity and diversity of data that can be acquired, which are often limited in practice. In this study, we demonstrate that rotation-based data augmentation can effectively improve wafer map pattern classification when training data are scarce. As rotation is a label-preserving transformation for wafer maps, we construct a convolutional neural network with rotation-augmented training data to render the classification invariant with respect to rotation. This enables us to provide consistent predictions for rotational variations of new wafer maps, thereby achieving higher classification performance. The effectiveness of our method is verified based on real-word data from a semiconductor manufacturer.
Designing a Serious Game for Myoelectric Prosthesis Control

As an amputee, learning how to control a myoelectric prosthesis is a difficult task. One of the main issues with conventional, highly repetitive, rehabilitation methods is the lack of engagement and motivation of the patients that often leads to high rejection rates of the prosthetic device. This work proposes and implements a novel serious game design, improving previous work, as music-based app. The prototype was evaluated by seven able-bodied participants with regard system usability and engagement. Results suggest positive outcomes in motivation, but room for improvement in system usability
Predicting 30-day mortality using point-of-care testing; an external validation and derivation study

Background Early risk stratification for guiding treatment priority in the emergency department (ED) is becoming increasingly important. Existing prediction models typically use demographics, vital signs and laboratory parameters. Laboratory-based models require blood testing, which may cause substantial delay. However, these delays can be prevented by the use of point-of-care testing (POCT), where results are readily available. We aimed to externally validate a laboratory-based model for mortality and subsequently assessed whether a POCT model yields comparable performance. Methods All adult patients visiting the ED of a university hospital between January 1st, 2012 and December 31st, 2016 were retrospectively reviewed for inclusion. Primary outcome was defined as 30-day mortality after ED presentation. We externally validated one existing prediction model including age, glucose, urea, sodium, haemoglobin, platelet count and white blood cell count. We assessed the predictive performance by discrimination, expressed as Area under the Curve (AUC). We compared the existing model to an equivalent model using predictors that are available with POCT (i.e. glucose, urea, sodium and haemoglobin). Additionally, we internally validated these models with bootstrapping. Results We included 34,437 patients of whom 1,942 (5.6%) died within 30 days. The AUC of the laboratory-based model was 0.794. We refitted this model to our ED population and found an AUC of 0.812, which decreased only slightly to 0.790 with only POCT parameters. Conclusions Our POCT-model performs similar to existing laboratory-based models in identifying patients at high risk for mortality, with results available within minutes. Although the model needs further validation and evaluation, it shows the potential of POCT for early risk stratification in the ED.
Hierarchical Blockchain Topologies for Quality Control in Food Supply Chains

The use of blockchains to improve product quality and safety control in food supply chains through transparent, trusted, and secure end-to-end traceability frameworks, has received increased attention in the last few years. The use of blockchains, though, does not come at no cost. Poor design of blockchain-based applications can lead to prohibitive costs, intolerable delays, and nonscalable systems. In this work we explore different architectures for blockchain-based traceability and quality control of produce, proposing, evaluating, and comparing four different scenarios. Our evaluation uses public and private Ethereum instances, and assesses the considered architectures in terms of cost and overall throughput.
Towards a Modular and Customisable Model-Based Architecture for Autonomous Drones

In the domain of autonomous unmanned vehicles, some design patterns emerge from various distinct software designs. These patterns are the result of the search for modularity and, in consequence, customisation. They point to the possibility of a more general architecture and design process that are able to comply to at least most of design requirements made for unmanned vehicles, including regulatory ones. This paper explores the possibility of proposing this modular and customisable architecture as a simpler approach to responding to design requirements.
On the Impact of Normalized Interference Threshold for Topological Interference Management

This paper presents a new formulation to build an interference topology for the multi-user unicast Topological Interference Management (TIM) based wireless network problem. Based on our interference topology formulation, we are able to evaluate the achievable rate’s theoretical limit, in the asymptotic signal to noise ratio (SNR) regime, for the underlying wireless network and not just for its topological interference representation. This new formulation allows us to cope with the finite SNR regime and not just with the asymptotic SNR regime with the Degrees of Freedom (DoF) analysis. A new SNR independent interference threshold parameter is proposed and we evaluate the achievable symmetric rates of the wireless network in both the finite SNR regime and the asymptotic SNR regime. Finally, we present outer bound solutions on the new normalized interference threshold parameter for interference topologies with half-DoF-feasibility, considering both an orthogonal resource allocation and Interference Alignment (IA). These bounds specify if a given half-DoF-feasible interference topology can be, in terms of the achievable rate, the best topology or not. Using this result, we limit the search space in the normalized interference threshold parameter range, to find half-DoF-feasible interference topologies having the possibility to be the best topologies in terms of the achievable rate.
Active Learning in Online Computer Systems Course

Active learning has been proven to improve students learning outcomes effectively. An online active learning pedagogy model is designed and applied in online Computer Systems course this Spring. The model includes five cycle phases which cover online feedback between students and instructor before class, active discussion in the online class, and asynchronous interaction after class in the virtual education environment. Based on the data from students’ questionnaires and the test score ratio shows the active learning pedagogy model is efficient for online education.
SDN-based multi-controller optimization deployment strategy for satellite network

Due to the network topology high dynamic changes, the number of ground users and the impact of uneven traffic, the load difference between SDN-based satellite network controllers varies widely, which will cause network performance such as network delay and throughput to drop dramatically. Aiming at the above problems, a multi-controller optimized deployment strategy of satellite network based on SDN was proposed. First, the controller's load state is divided into four types: overload state, high load state, normal state, and idle state; second, when a controller in the network is idle, the switch under its jurisdiction is migrated to the adjacent low load controller and turn off the controller to reduce waste of resources. When the controller is in a high-load state and an overload state, consider both the controller and the switch, and migrate the high-load switch to the adjacent low-load controller. Balance the load between controllers, improve network performance, and improve network performance and network security. Simulation results show that the method has an average throughput improvement of 2.7% and a delay reduction of 3.1% compared with MCDALB and SDCLB methods.
Making More Extensive and Efficient Typo-Tolerant Password Checkers

As passwords remain the main online authentication method, focus has shifted from naive entropy to how usability improvements can increase security. Chatterjee et al. recently introduced the first two typo-tolerant password checkers, their second being usable in practice while being able to correct up to 32% of typos, with no real security cost. We propose an alternative framework which corrects up to 57% of typos without affecting user experience, at no computational cost to the server.
Flexible planar supercapacitors by straightforward filtration and laser processing steps

There is ever increasing demand for flexible energy storage devices due to the development of wearable electronics and other small electronic devices. The electrode flexibility is best provided by a special set of nanomaterials, but the required methodology typically consists of multiple steps and are designed just for the specific materials. Here, a facile and scalable method of making flexible and mechanically robust planar supercapacitors with interdigital electrode structure made of commercial carbon nanomaterials and silver nanowires is presented. The capacitor structure is achieved with vacuum filtration through a micropatterned contact mask and finished with simple laser processing steps. A maximum specific capacitance of 4 F cm−3 was measured with cyclic voltammetry at scan rate of 5 mV s−1. The reliability and charge transfer properties of devices were further investigated with galvanostatic charge-discharge measurements and electrochemical impedance spectroscopy, respectively. Furthermore, mechanical bending tests confirmed the devices have excellent mechanical integrity, and the deformations have no adverse effects on the electrochemical charge-discharge behavior and stability.
Investigating the Failure Mechanism of Short-Circuit Tests in 1.2-kV SiC JBS-Integrated MOSFETs

In this article, the failure mechanism of a 1.2-kV monolithic junction barrier-controlled Schottky diode integrated silicon carbide metal–oxide–semiconductor field-effect transistor (JMOS) under short-circuit (SC) tests has been investigated by an experimental validation and simulation analysis. As a new type of device, JMOS has superior performance and chip area efficiency. However, the SC ruggedness of the JMOS needs further investigation. When comparing vertical double-diffused metal–oxide–semiconductor field-effect transistor (VDMOS) and JMOS devices in the SC test study, the leakage current of the JMOS is much higher than that of a common VDMOS. During the SC test, the JMOS drain current cannot be successfully suppressed after gate turn-off, and the thermionic emission current due to heat generation in the Schottky barrier diode (SBD) region continues flowing into the n-drift region. The SBD thermionic emission current is rapidly increased by the increasing lattice temperature, which can reach over 1600 K. Eventually, the JMOS undergoes thermal runaway due to positive electrothermal feedback. A mechanistic study was set up to analyze the relationship between the SC limit and the leakage current in the SBD region of the heated materials. Finally, the key to improve the SC ruggedness of the JMOS is decreasing the leakage current in the SBD region.
Theoretical Investigation of the thermodynamic stability and Density of States in α-(Co, Cu)Sn3

With the development of electronic packaging, the performance of microchip is crucial for the reliability of solder joints. The α-CoSn3 with some performance have been studied by researchers continuously. However, there is a little study on doping α-(Co, Cu)Sn3 that Cu is regard as a common element of electronic packaging. In this paper, different concentrations of Cu (0~9.375 at.%) were used to replace the Co atoms in α-CoSn3 intermetallic(IMC). The thermodynamic stability and electronic structure of α-(Co, Cu)Sn3 were calculated by the first-principles. The results show that the formation enthalpy and cohesive energy of α-(Co1-x, Cux)Sn3 (x=0~0.375) are negative values, means the α-(Co, Cu)Sn3 configurations can be formed and exist stably. With the increasing of Cu atoms, the formation enthalpy and cohesive energy increased, the formation of α-(Co, Cu)Sn3 became difficult and unstable configurations. By analyzing the density of states(DOS) , the increasing of Cu atoms make the main peak deviate from Fermi level gradually and form two main peaks under Fermi level. Besides, the increase of Cu concentrations decreases NEF, indicating the bonding is weakened.
Gate-Length Dependence of Vertical GaSb Nanowire p-MOSFETs on Si

The effect of gate-length variation on key transistor metrics for vertical nanowire p-type GaSb metal–oxide–semiconductor field-effect transistors (MOSFETs) are demonstrated using a gate-last process. The new fabrication method enables short gate-lengths (<inline-formula> <tex-math notation="LaTeX">${L}_{g} =40$ </tex-math></inline-formula> nm) and allows for selective digital etching of the channel region. Extraction of material properties as well as contact resistance are obtained by systematically varying the gate-length. The fabricated transistors show excellent modulation properties with a maximum <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}} =700$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">${V}_{GS} = -0.5$ </tex-math></inline-formula> V) as well as peak transconductance of <inline-formula> <tex-math notation="LaTeX">$50~\mu \text{S}/\mu \text{m}$ </tex-math></inline-formula> with a linear subthreshold swing of 224 mV/dec.
CHOCSLAT: Chinese Healthcare-Oriented Computerised Speech & Language Assessment Tools

This paper describes an on-going project to develop diagnostic profiling tools for healthcare professionals to identify potential speech and language developmental problems of Chinese-speaking children. The tools aim to provide a technical advance in helping children who may have speech impairment or language delay. The project is currently being carried out as a collaboration with Chinese healthcare professionals, and a multidisciplinary team including applied linguists, speech and language pathologists, and computer scientists (staff and students) at the first Sino-foreign higher education institution in China, University of Nottingham Ningbo China (UNNC). The paper presents the background, development, and current state of the project. Challenges to project completion, including difficulties encountered due to the Covid-19 outbreak and subsequent world-wide emergency and lock-down are also discussed.