Miracle-dz/UniFAR-FTUs huggingface dataset:
SNP analyses and acoustic tagging reveal multiple origins and widespread dispersal of invasive brown trout in the Falkland Islands

Biological invasions are important causes of biodiversity loss, particularly in remote islands. Brown trout (Salmo trutta) have been widely introduced throughout the Southern Hemisphere, impacting endangered native fauna, particularly galaxiid fishes, through predation and competition. However, due to their importance for sport fishing and aquaculture farming, attempts to curtail the impacts of invasive salmonids have generally been met with limited support and the best prospects for protecting native galaxiids is to predict where and how salmonids might disperse. We analysed 266 invasive brown trout from 14 rivers and ponds across the Falkland Islands as well as 32 trout from three potential source populations, using a panel of 592 single nucleotide polymorphisms (SNPs) and acoustic tagging, to ascertain their origins and current patterns of dispersal. We identified four genetically distinct clusters with high levels of genetic diversity and low admixture, likely reflecting the different origins of the invasive brown trout populations. Our analysis suggests that many trout populations in the Falklands may have originated from one of the donor populations analysed (River Wey). The highest genetic diversity was observed in the rivers with the greatest number of introductions and diverse origins, while the lowest diversity corresponded to a location without documented introductions, likely colonized by natural dispersal. High levels of gene flow indicated widespread migration of brown trout across the Falkland Islands, likely aided by anadromous dispersal. This is supported by data from acoustically tagged fish, three of which were detected frequently moving between two rivers ~26 km apart. Our results suggest that, without containment measures, brown trout may invade the last remaining refuges for the native endangered Aplochiton spp. We provide new insights into the origin and dispersal of invasive brown trout in the Falkland Islands that can pave the way for a targeted approach to limit their impact on native fish fauna.
Spatial Skyline Queries on Triangulated Irregular Networks

A spatial skyline query is a query to find a set of data points that are not spatially dominated by other data points, given a set of data points P and query points Q in a multidimensional space. The query enumerates the skyline points based on distance in a multidimensional space. However, existing spatial skyline queries can lead to large errors with actual travel distances in geo-spaces because the query is based on the Euclidean distance. We propose a spatial skyline query on triangulated irregular networks (TINs), which are frequently used to represent the surfaces of terrain. We define a new spatial skyline query based on more accurate travel distances considering the TIN distance instead of the Euclidean distance. We also propose an efficient solution method using indexes to find nearest-neighbor points in TIN space and reduce the numbers of unnecessary data points and TIN vertices. The proposed method achieves a computational complexity of O(|P′||Q|N′2 + |P′|2|Q|), where P′ and N′ are the reduced sets of data points and number of TIN vertices, respectively, based on the range of query points. The proposed method can process a query faster than the naive method with Θ(|P||Q|N2 + |P|2|Q|), where N is the number of TIN vertices. Moreover, experiments verify that the proposed method is faster than the naive method by using a spatial index to reduce the numbers of unnecessary data points and TIN vertices.
Pressure active disturbance rejection five-mode switching control based on pneumatic high speed on/off valves

In this paper, an active disturbance rejection five-mode switching (ADR-FMS) controller is designed in order to solve the problem of low pressure control accuracy, which is caused by the nonlinearity and the susceptibility to external interference of the high speed on/off valve. Through real-time compensation of nonlinearity and various external disturbances, the pressure control accuracy is effectively improved. Moreover, a five-mode switching controller (FMSC) is designed to ensure rapid response of the pressure and avoid frequent switching of the valve. Finally, it is verified that the ADR-FMS controller is better than the PID controller through experiments, the pressure steady-state error is reduced by 10kPa when tracking the step signal, and the pressure tracking error is reduced by 33kPa when tracking a 1Hz sine signal.
Geolocating Traffic Signs using Large Imagery Datasets

Maintaining a database with the type, location, and direction of traffic signs is a labor-intensive part of asset management for many road authorities. Today there are high-quality cameras in cell-phones that can add location (EXIF) metadata to the images. This makes it efficient and cheap to collect large geo-located imagery datasets. Detecting traffic signs from imagery is also much simpler today due to the availability of several high-quality open-source object-detection solutions. In this paper, we use the detection of traffic signs to find both the location and the direction of physical traffic signs. Five approaches to cluster the detections are presented. An extensive experimental evaluation shows that it is important to consider both the location and the direction. The evaluation is done on a novel dataset with 21,565 images that is available free for download. This includes the ground-truth location of 277 traffic signs and all source code. The conclusion is that traffic signs are detected with an F1 score of 0.8889, a location accuracy of 5.097-meter (MAE), and a direction accuracy of ± 11.375°(MAE). Only data from two trips are needed to get these results.
Research on 3D Reverse Technology Based on Monocular Image Sequence

A solution to improve the FAST feature point detection algorithm susceptible to image noise interference is proposed. Eight directions are derived from the selected point to solve the gray level mutations in these eight directions, and based on this, it is judged whether the point is a feature point. And take the maximum value suppression for the dense area of feature points, and solve the maximum value of the sum of gray changes in all directions as the judgment condition to screen the feature points. A new feature point matching scheme is proposed, where the Hamming distance between feature points within the target image is derived by the BruteForce algorithm. If the Hamming distance between the first few target points and the original feature point is less than a certain threshold, it will be substituted into the original image to solve the problem. The Hamming distance between the feature points of the original image is selected as the correct matching point. Finally, the principle of region growth is introduced to the MC algorithm, which saves the amount of calculation and improves the generation accuracy.
Express: applications of dynamically typed Haskell expressions

This paper presents Express, a library for manipulating dynamically typed Haskell expressions involving function application and variables. Express works as a wrapper around the Data.Dynamic module and provides additional features such as: explicit encoding of function applicaion thus delayed application between values, support for variable placeholders and expression matching. This paper shows these additions make this library useful in generating program specifications, automated testing and program synthesis.
Initialization Improvement and Map Reuse Based on ORBSLAM3

Monocular initialization has always been a critical issue in the research of visual SLAM. In the research of monocular initialization, ORBSLAM3, the state-of-the-art system at present, proposes a monocular-inertial initialization algorithm based on maximum a posteriori estimation. The initialization of this algorithm requires sufficient motion excitation, takes up memory, and is time-consuming. In response to this problem, considering the low cost of the wheel encoder and the strong complementarity between camera and IMU, we propose an initialization algorithm that integrates the wheel encoder, camera, and IMU. This algorithm can quickly and accurately initialize the scale of the camera and speed up the initialization of the gravity direction and IMU bias. Besides, we propose a minimum storage map reuse algorithm based on ORBSALM3, which can realize map storage, map reloading, and relocation on the reloaded map while occupying a small memory. Experimental results show that compared with ORBSLAM3, the initialization algorithm we proposed effectively improves the initialization speed and accuracy of the system. The new map reuse algorithm takes up a small system memory to achieve map reloading and relocation.
DiLOS: adding performance to paging-based memory disaggregation

Memory disaggregation places computing and memory in physically separate nodes and achieves improved memory utilization in datacenters. Kernel-based approaches for memory disaggregation offer transparent virtual memory by using paging schemes but suffer from expensive page fault handling. As an alternative, library-based approaches incorporate application semantics to memory disaggregation and can even eliminate page fault handling on its data path. However, its lack of compatibility harms generality and obstruct wide adoption. This paper revisits the paging-based approaches and challenges their performance. We posit that the page fault overhead is not a fundamental limitation. We propose DiLOS, a new memory disaggregating unikernel, that delivers both performance and generality. The key insight of DiLOS to overcome performance drawbacks while maintaining generality lies in the design of a fast, lightweight page fault handler on top of the unikernel's simple execution model. Since each unikernel serves a single application, it also opens room for extra optimization via app-aware prefetching. DiLOS outperforms a recent library-based system (AIFM) by 1.52× and 1.31× when the cache size is 12.5% and 100% of the total working set, respectively. Compared to the state-of-the-art paging-based system (Fastswap), DiLOS with a general-purpose prefetcher achieves up to 2.2× higher performance in real-world workload. An app-aware prefetcher further improves the throughput of Redis in-memory database up to 27%.
Co-designed mini-games for children with severe visual impairment

Digital games can be designed and used to improve many specific skills, related to both cognitive and sensory-motor goals. A set of novel mini-games explicitly aimed to children with severe visual impairments are presented. The games are played by moving within the range of a large-scale interactive environment, i.e. a floor portion placed under a motion capture system which allows the tracking of one or more people. It is then possible to link the players movements to audio and graphic output, producing meaningful interactions. The games are the results of a design process that involved computer engineers and a multidisciplinary therapy team from the R. Hollman Foundation (Padova, Italy). A set of guidelines useful to designers and developers are presented as a result of the co-design process.
Boosting coverage-based fault localization via graph-based representation learning

Coverage-based fault localization has been extensively studied in the literature due to its effectiveness and lightweightness for real-world systems. However, existing techniques often utilize coverage in an oversimplified way by abstracting detailed coverage into numbers of tests or boolean vectors, thus limiting their effectiveness in practice. In this work, we present a novel coverage-based fault localization technique, GRACE, which fully utilizes detailed coverage information with graph-based representation learning. Our intuition is that coverage can be regarded as connective relationships between tests and program entities, which can be inherently and integrally represented by a graph structure: with tests and program entities as nodes, while with coverage and code structures as edges. Therefore, we first propose a novel graph-based representation to reserve all detailed coverage information and fine-grained code structures into one graph. Then we leverage Gated Graph Neural Network to learn valuable features from the graph-based coverage representation and rank program entities in a listwise way. Our evaluation on the widely used benchmark Defects4J (V1.2.0) shows that GRACE significantly outperforms state-of-the-art coverage-based fault localization: GRACE localizes 195 bugs within Top-1 whereas the best compared technique can at most localize 166 bugs within Top-1. We further investigate the impact of each GRACE component and find that they all positively contribute to GRACE. In addition, our results also demonstrate that GRACE has learnt essential features from coverage, which are complementary to various information used in existing learning-based fault localization. Finally, we evaluate GRACE in the cross-project prediction scenario on extra 226 bugs from Defects4J (V2.0.0), and find that GRACE consistently outperforms state-of-the-art coverage-based techniques.
Improving GHC Haskell NUMA profiling

As the number of cores increases Non-Uniform Memory Access (NUMA) is becoming increasingly prevalent in general purpose machines. Effectively exploiting NUMA can significantly reduce memory access latency and thus runtime by 10-20%, and profiling provides information on how to optimise. Language-level NUMA profilers are rare, and mostly profile conventional languages executing on Virtual Machines. Here we profile, and develop new NUMA profilers for, a functional language executing on a runtime system. We start by using existing OS and language level tools to systematically profile 8 benchmarks from the GHC Haskell nofib suite on a typical NUMA server (8 regions, 64 cores). We propose a new metric: NUMA access rate that allows us to compare the load placed on the memory system by different programs, and use it to contrast the benchmarks. We demonstrate significant differences in NUMA usage between computational and data-intensive benchmarks, e.g. local memory access rates of 23% and 30% respectively. We show that small changes to coordination behaviour can significantly alter NUMA usage, and for the first time quantify the effectiveness of the GHC 8.2 NUMA adaption. We identify information not available from existing profilers and extend both the numaprof profiler, and the GHC runtime system to obtain three new NUMA profiles: OS thread allocation locality, GC count (per region and generation) and GC thread locality. The new profiles not only provide a deeper understanding of program memory usage, they also suggest ways that GHC can be adapted to better exploit NUMA architectures.
Automated code transformation for context propagation in Go

Microservices architecture, which is increasingly being adopted by large technology companies, can accelerate development and deployment of backend code by partitioning a monolithic infrastructure into independent components. At the same time, microservices often compose into massively distributed systems, where analyzing the behavior of an individual service may not be enough to diagnose a performance regression or find a point of failure. Instead, a more global view of the entire computation may be required, where some form of global context is used to trace relevant information flowing through the system. In the Go language, the recommended method of propagating this tracing context through service’s code is to pass it as the first parameter to all functions on call paths where the context is used. This kind of code transformation, in addition to modifying function calls and function signatures, may involve modifications to other language constructs – performing it manually can be very tedious, particularly for large existing services. In this paper we describe an automated code transformation tool supporting this style of context propagation. We describe the design and implementation of the tool and, based on a case study using real production services, demonstrate that the tool can on average eliminate 94% of manual effort required to propagate tracing context through the code of a given service.
UQCom: underwater safety communication based on 3D blue-green QR arrays

Underwater team members use gestures to exchange information with each other while working, but the way of using gestures to transform information is limited, fixed and prone to lead to ambiguity. If the transformed information is inaccurate or even wrong, it will definitely interfere with collaboration between underwater team members. In our poster, we present the design, implementation and evaluation of UQCom, a novel underwater secure communication method using 3D blue-green QR arrays based on image enhancement technology, to solve the problem mentioned above. We apply blue-green QR codes to underwater short range communication and utilize underwater image enhancement technology to address the unique issues in underwater environments such as turbid water and image distortion. A 3D QR displaying scheme is proposed to improve communication rate. UQCom can also ensure communication security via encryption algorithm. Extensive experiments with two commercial off-the-shelf (COTS) smartphones conducted in indoors and outdoors demonstrate that UQCom can achieve real-time and robust short range communication in underwater environments.
Resilient Team Formation with Stabilisability of Agent Networks for Task Allocation

Team formation (TF) faces the problem of defining teams of agents able to accomplish a set of tasks. Resilience on TF problems aims to provide robustness and adaptability to unforeseen events involving agent deletion. However, agents are unaware of the inherent social welfare in these teams. This article tackles the problem of how teams can minimise their effort in terms of organisation and communication considering these dynamics. Our main contribution is twofold: first, we introduce the Stabilisable Team Formation (STF) as a generalisation of current resilient TF model, where a team is stabilisable if it possesses and preserves its inter-agent organisation from a graph-based perspective. Second, our experiments show that stabilisability is able to reduce the exponential execution time in several units of magnitude with the most restrictive configurations, proving that communication effort in subsequent task allocation problems are relaxed compared with current resilient teams. To do so, we developed SBB-ST, a branch-and-bound algorithm based on Distributed Constrained Optimisation Problems (DCOP) to compute teams. Results evidence that STF improves their predecessors, extends the resilience to subsequent task allocation problems represented as DCOP, and evidence how Stabilisability contributes to resilient TF problems by anticipating decisions for saving resources and minimising the effort on team organisation in dynamic scenarios.
MidifilePerformer: a case study for chronologies

This article discusses the internal architecture of the MidifilePerformer application. This software allows a user to follow a score described in the MIDI format at its own pace and with its own accentuation. MidifilePerformer allows for a wide variety of style and interpretation to be applied to the vast number of MIDI files found on the Internet. We present here the algorithms enabling the association between the commands made by the performer, via a MIDI or alpha-numeric keyboard, and the notes appearing in the score. We will show that these algorithms define a notion of expressiveness which extends the possibilities of interpretation while maintaining the simplicity of the gesture.
Micogito: a Serious Gamebook Based on Daily Life Scenarios to Cognitively Stimulate Older Adults

With the increase in the number of people aged 60 years and older, it becomes essential to promote active ageing. Adequate cognitive training activity can preserve older adults' health conditions, allowing them to live autonomously longer. However, older people often have difficulties with the use of digital technologies and risk being excluded from these. For this reason, this work proposes a solution that introduces older adults to new technologies while maintaining a familiar appearance to them. The solution proposed is Micogito, a web serious game that exploits the book metaphor for cognitive stimulation of older adults. It supports tasks which replicate daily living activities, and has been conceived, and designed to stimulate the most implicated cognitive functions in ageing and particularly in mild cognitive impairment. In its design and implementation, guidelines useful to make web applications accessible and usable for the target users were considered. We also report on a first user test with older adults, to assess the effectiveness of this approach, which provided useful and encouraging feedback, and discuss some lessons learnt.
Research on Grain Yield Prediction Model Based on Contribution Multiplier and Bidirectional LSTM Neural Network

It is extremely difficult to predict grain yield because of several influencing factors and the uncertainty and nonlinearity among them. In order to improve the prediction accuracy of grain yield, one new prediction model is proposed based on bidirectional LSTM Neural Network. Firstly, the correlation coefficients between the grain yield and each influencing factor are computed and sorted, thereby the main influencing factors are chosen; then one contribution multiplier is defined and weighted with the corresponding influence factor by the correlation coefficient; finally, the weighted factors and the historical grain yield will be imputed to bidirectional LSTM neural network and the future grain yield can be obtained. The simulation analysis has shown the contribution multiplier can change the difference among the main influence factors, and compared with the traditional prediction methods as ARIMA, SVR, RF, LSTM, the proposed prediction model can realize the medium and short-term prediction of grain yield with the higher accuracy.
Research and Application of Intelligent Order Making System for Electric Power Customer Service

Electric power is the most important energy power in production and life, and electric power customer service is the window of external service communication for electric power enterprises. The customer service center of State Grid Co., Ltd. is responsible for accepting the demands of more than 1 billion customers in provinces and municipalities within the power supply scope of the company, such as electricity business consultation, fault report, complaints, reports and opinions. The accepted contents will be transferred to the follow-up processing personnel in the form of work orders, and the number of documents made is huge. At present, after a customer calls 95598, the customer service specialist needs to record the customer's personal information and his or her demands while answering the phone. In order to reduce the working pressure of customer service specialists, improve the quality and efficiency of work, and achieve the purpose of reducing cost and increasing efficiency, this paper proposes an automatic order making method, which can help achieve the loading of work orders by classifying the businesses of service dialogues, and then realizes the generation of work orders through the slot filling method of work order elements. The method proposed in this paper significantly improves the accuracy of business classification, and finally achieves 75.5% accuracy of production work order, which is helpful to simplify the service process of front-line personnel and save work costs.