Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Placer for Analog Circuits Using Integer Linear Programming Warm Started by Graph Drawing

: Due to its diversity, the physical design of the Analog and Mixed-Signal Integrated Circuits is not as automated as the physical design of digital Integrated Circuits. The placement process is one of the critical steps of the physical design, and automating it would significantly shorten the design time. We formulate the placement process using an Integer Linear Programming approach, with features to support a specific semiconductor technology. We include an enumeration of possible variants of the circuit’s topological structures, which are afterward considered during optimization. We use the Gurobi solver to minimize both the approximate wire length and the placement area. The results were evaluated by layout design experts and compared with manual designs. We also utilize a graph drawing-based method to generate an initial feasible solution to warm start the Integer Linear Programming solver, which noticeably improves the performance and shortens the computation time (5x to 15x), and makes the approach applicable even for larger problem instances containing 100 independent elements. Experiments performed on real-life industrial problem instances show that our graph drawing-enhanced approach can produce high-quality placement in a much shorter time than the designers need.
Assessing the Impact of Attacks on Connected and Autonomous Vehicles in Vehicular Ad Hoc Networks

: The transportation sector is evolving rapidly towards more sustainable and safer solutions with the idea of Connected and Autonomous Vehicles (CAVs) based upon Vehicular Ad-hoc Network technology. The biggest challenge for CAVs is the security threats due to their open nature and internet connections, opening a wide range of vulnerabilities. In this research, the impact of four cyber security attacks (Distributed Denial of Service (DDoS), Man-in-the-Middle (MITM), Blackhole and Grayhole) is quantified in terms of network and transportation performance metrics. The map is setup based on a busy urban area in a UK city, and a combination of OMNeT++, Sumo and Veins software tools are used for modelling and simulating the attacks on the network. The simulation is performed with and without the attacks for an accident scenario. MITM is found to have maximum impact severity on the transportation operational efficiency and safety of the CAV network. The dynamic rerouting algorithm of the network is identified as the most vulnerable attack vector, experiencing maximum impact from all the attacks. A maximum packet loss of 82% is achieved by a DDoS attack. These insights showcased the importance of analysing the impacts of security attacks on the transportation efficiency of the CAV network, which is vital for building reliable and safer next-generation mobility systems.
Recent Advances in Statistical Mixture Models: Challenges and Applications

: This paper discusses current advances in mixture models, as well as modern approaches and tools that make use of mixture models. In particular, the contribution of mixture-based modeling in various area of researches is discussed. It exposes many challenging issues, especially the way of selecting the optimal model, estimating the parameters of each component, and so on. Some of newly emerging mixture model-based methods that can be applied successfully are also cited. Moreover, an overview of latest developments as well as open problems and potential research directions are discussed. This study aims to demonstrate that mixture models may be consistently proposed as a powerful tool for carrying out a variety of difficult real-life tasks. This survey can be the starting point for beginners as it allows them to better understand the current state of knowledge and assists them to develop and evaluate their own frameworks.
Query Log Analysis for SQL Injection Detection

: Nowadays, more and more services are dependent on the use of resources hosted on the web. The realization of operations such as access to the account bank, credit card operations, among other operations, is something increasingly common in current times, demonstrating not only human dependence on the internet connection, as well as the need to adapt the web resources to the daily life of society. As a result of this growing dependency, web resources now provide a greater amount of conﬁdential information, making the risk of a cyberattack and information leaking grow considerably. In the web context, one of the most well-known attacks is SQL injection that allows the attacker to exploit, through the injection of malicious queries, access to conﬁdential information. This paper suggests a solution for the detection of SQL injection via web resources, using the analysis of the logs of the executed queries.
Distinct Role of a Spring Atmospheric Circulation Mode in the Arctic Sea Ice Decline in Summer

A distinguishing feature of Arctic sea ice is the rapid declining in the Pacific Arctic Sector (PAS) in recent years. The atmospheric variability during spring (March‐May) plays a critical role in determining the sea ice extent (SIE) during the following summer. The summertime (June‐August) SIE reduction in the eastern part of PAS, including the East Siberian Sea and the Laptev Sea, is strongly related to the first two leading atmospheric circulation modes in spring, the Arctic Oscillation and the Arctic Dipole, retrieved from empirical orthogonal function analysis. Here, we show that the third leading mode of atmospheric circulation in spring, namely the Barents‐Beaufort Oscillation (BBO), can also change the summer SIE, especially on the western regime of the PAS across the Beaufort and Chukchi Seas. We find that a positive phase of springtime BBO (i.e., BBO+), relative to the BBO−, acts to decrease sea ice thickness via advection and generate sea ice deformation through divergence and shear processes, thereby preconditioning for a rapid sea ice loss within the PAS in the following summer. Furthermore, the occurrence of BBO is state‐dependent and potentially modulated by the phase shift of the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). Since the mid‐1990s, the AMO (PDO) index has changed from a dominant negative (positive) to a positive (negative) phase. These phase shifts in AMO and PDO would have contributed to the subsequently increased appearance of anomalous BBO+ after 2000 and enhanced the summertime sea ice loss in the western regions of the PAS in recent years.
Unsupervised Tree Detection and Counting via Region-Based Circle Fitting

: Automatic tree detection and counting is a very important task for many areas such as environmental protection, agricultural planning, crop yield estimation and monitoring of replanted forest areas. This paper presents an unsupervised method for tree detection from high resolution UAV imagery based on a modified version of the Decremental Ellipse Fitting Algorithm DEFA . The proposed Decremental Circle Fitting Algorithm ( DCFA ) works similarly to DEFA with the main difference that DCFA uses circles instead of ellipses. According to DCFA , the skeleton of the 2D shape is calculated first, followed by the initialization of the circle hypotheses and the application of the Gaussian Mixture Model Expectation Maximization algorithm. Finally, model evaluation is performed based on the Akaike Information Criterion. The DCFA method was tested on the Acacia-6 dataset, which depicts six months acacia trees, collected with Unmanned Aerial Vehicles in Southeast Asia and it exhibits high performance compared with the state-of-the art unsupervised and supervised methods.
EvLiDAR-Flow: Attention-Guided Fusion Between Point Clouds and Events for Scene Flow Estimation

: In this paper, we propose the fusion of event streams and point clouds for scene ﬂow estimation. Bio-inspired event cameras offer signiﬁcantly lower latency and higher dynamic ranges than regular RGB cameras, and are therefore appropriate for recording high-speed motions. However, events do not provide depth information, which makes them unsuitable for scene ﬂow (3D) estimation. On the other hand, LiDAR-based approaches are well suited to scene ﬂow estimation due to the high precision of LiDAR measurements for outdoor scenes (e.g. autonomous vehicle applications) but they fail in the presence of unstructured regions (e.g. ground surface, grass, walls, etc.). We propose our EvLiDAR-Flow, a neural network architecture equipped with an attention module for bi-directional feature fusion between an event (2D) branch and a point cloud (3D) branch. This kind of fusion helps to overcome the lack of depth information in events while enabling the LiDAR-based scene ﬂow branch to beneﬁt from the rich motion information encoded by events. We validate the proposed EvLiDAR-Flow by showing that it performs signiﬁcantly better and is robust to the presence of ground points, in comparison to a state-of-the-art LiDAR-only scene ﬂow estimation method.
Isolating the singular term of the green's function in the vicinity of the corner formulated by two intersecting waveguides

A bent waveguide comprised of two vertically intersected unequal parallel‐plate structures is excited by an elementary singular source located into the corner cavity.The electric field, equaling the Green's function, is computed in each region by considering a common singular quantity, the necessary image terms corresponding to infinite planes and a sum describing the mode matching procedure along the separating boundaries. The final form could be used effectively in implementing the scattering integral equations, due to the isolation of the irregular term that can be handled properly. Several graphs representing the variations of the Green's functions and the propagating powers with respect to the oscillating frequency are shown and discussed. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:16–23, 2013;X View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27227
A Wearable Device Application for Human-Object Interactions Detection

: Over the past ten years, wearable technologies have continued to evolve. In the development of wearable technology, smart glasses for augmented and mixed reality are becoming particularly prominent. We believe that it is crucial to incorporate artificial intelligence algorithms that can understand real-world human behavior into these devices if we want them to be able to properly mix the real and virtual worlds and give assistance to the users. In this paper, we present an application for smart glasses that provides assistance to workers in an industrial site recognizing human-object interactions. We propose a system that utilizes a 2D object detector to locate and identify the objects in the scene and classic mixed reality features like plane detector, virtual object anchoring, and hand pose estimation to predict the interaction between a person and the objects placed on a working area in order to avoid the 3D object annotation and detection problem. We have also performed a user study with 25 volunteers who have been asked to complete a questionnaire after using the application to assess the usability and functionality of the developed application.
Generating strange magnetic and dielectric interactions: Classical molecules and particle foams

When a soft magnetic particle suspension is subjected to a vertical uniaxial magnetic field the particles polarize, the positive dipolar interactions causing particle chain formation. If instead an audio-frequency rotating magnetic field is applied in a horizontal plane, the particles experience an average interaction that to first order is a negative dipolar interaction, causing particle sheet formation in the biaxial field plane. When a vertical uniaxial field and a horizontal biaxial field are simultaneously applied with the field amplitudes balanced, the positive and negative dipolar interactions cancel to first order, and one might expect no dipolar interactions at all. But in this balanced triaxial field an isotropic second-order dipolar interaction of surprising magnitude remains. This triaxial interaction can be attractive or repulsive, and exhibits strong many-body interactions that lead to a variety of unexpected effects, including stable clusters with molecular geometries, the emergence of a particle foam, and the production of vortices in the fluid. By manipulating the triaxial field, a variety of particle structures can be made that cannot be produced by any other known means.
Experimental evidence of fast reconnection via trapped electron motion

Magnetic reconnection in collisionless magnetohydrodynamic plasmas is studied under controlled conditions in toroidal X-line configurations formed in the center of the Versatile Toroidal Facility [J. Egedal , Rev. Sci. Instrum. 71, 3351 (2000)]. Profiles of key parameters are measured during driven reconnection pulses in the reproducible plasma discharges. The experimental results prove to be highly sensitive to the boundary conditions applied. In the configuration with "open" boundaries reconnection is fast; the measured current densities are about three orders of magnitude below those predicted based on classical Spitzer resistivity. These small current densities are consistent with the electrons following toroidally trapped orbits. Further, the size of the electron diffusion region scales with the drift orbit width of the trapped electrons. Experiments conducted with "closed" boundaries yield significantly different results. In this configuration the electrons are not trapped toroidally and large current densities are permitted to develop. These currents reduce significantly the reconnection rate in the closed configurations. (C) 2004 American Institute of Physics.
Evaluating the Impact of Low-Light Image Enhancement Methods on Runner Re-Identification in the Wild

: Person re-identification (ReID) is a trending topic in computer vision. Significant developments have been achieved, but most rely on datasets with subjects captured statically within a short period of time in rather good lighting conditions. In the wild scenarios, such as long-distance races that involve widely varying lighting conditions, from full daylight to night, present a considerable challenge. This issue cannot be addressed by increasing the exposure time on the capture device, as the runners’ motion will lead to blurred images, hampering any ReID attempts. In this paper, we survey some low-light image enhancement methods. Our results show that including an image processing step in a ReID pipeline before extracting the distinctive body appearance features from the subjects can provide significant performance improvements.
Alternative Geometric Determination of Altazimuthal‐Distance Covariance Matrices

Conventional equations for determining the variance‐covariance matrix of vertical angles, geodetic azimuths and distances are based on the standard law of propagation of covariance using the Jacobian matrix of the corresponding functional relationships. A conceptually simpler geometric approach exclusively dependent on the notion of rotation matrices is presented here. The method completely avoids the cumbersome requirement of taking partial derivatives of non‐linear expressions. As an added advantage the method contributes to clarify several points related to dimensional transformations between linear and angular units.
Flow downstream of the heliospheric terminal shock - The magnetic field on the heliopause

Modeling the kinematic magnetic field in the solar wind beyond the terminal shock shows that a ridge of magnetic pressure is produced just inside the heliopause. This ridge has its maximum amplitude in the plane defined by the solar rotation axis and the heliotail and decreases to zero amplitude in the solar equatorial plane. The ridge is sufficiently large that it will cause the layer immediately inside the heliopause to thicken, pushing the heliopause outward and slightly affecting its position relative to the terminal shock. However, the ridge is far too thin to cause an important change in the distance of the terminal shock from the Sun. The kinematic assumption prevents us from estimating the actual magnitude of the ridge, but we show that these conclusions are a simple consequence of geometrical arguments for incompressible, steady, laminar flows. Moreover, the heliopause magnetic field originates on the terminal shock near the substagnation point. Consequently, the heliospheric current sheet field reversals are painted onto the inside surface of the heliopause. Alternate magnetic polarity strips will be oppositely directed relative to the interstellar magnetic field, implying that reconnection inevitably occurs on a fine scale near the nose of the heliosphere. This suggests that the heliopause is a leaky, diffuse surface.
Blood, Education and Economic Development: How the 19th Century Wars in Latin America Foiled its Economic Development

In this paper, we hypothesize that the prolonged wars in Latin America during most of the 19 th century hindered human capital development and delayed economic progress well into the 20 th century. Collecting novel data for the seven largest Latin American economies over the period 1820-2016, we show that the extraordinarily large share of military expenditure in total spending crowded out investment in education and R&D, which in turn had persistent effects on economic development
Closing the Achievement Gap: An Analysis of Equity-Based Educational Interventions

The ongoing differences in academic performance and outcomes between student groups represents a significant problem for educators worldwide. As a possible remedy, equity-based educational interventions have been receiving more and more attention for their focus on removing the structural impediments that contribute to the achievement gap. The purpose of this research is to analyze how well equity-based educational interventions reduce the gap in academic performance. The research technique included both a literature review and case studies of three schools that had already implemented equity-based educational interventions. Schools were chosen as case studies because of their track records of success in reducing the achievement gap through the implementation of various equity-based initiatives. When implemented with fidelity and supported by good leadership and a positive school culture, the results of this study demonstrate that equity-based educational interventions can be beneficial in reducing the achievement gap. Significant gains in student achievement and school atmosphere, as well as improved participation and engagement from traditionally underrepresented student populations, were observed in the case study schools. A lack of resources and support, resistance to change, and the complexity of tackling structural disparities were all highlighted as obstacles to the successful implementation of equity-based interventions in the study. These results stress the importance of continuing to work for equity-based interventions and to guarantee that all children have access to the tools and opportunity they need to achieve.
Reverse innovations bridging the gap between entrepreneurial orientation and international performance

PurposeThis paper aims to elucidate the relationship between entrepreneurial orientation, reverse innovation and international performance of emerging economy multinational enterprises (EMNEs). Design/methodology/approachThe authors analyze archival data of Chinese limited companies between 2010 and 2016, including 11,230 firm-year observations about 1708 firms. In order to test the study’s mediation hypotheses, the authors apply an ordinary least square (OLS) regression.FindingsThe authors find evidence that the entrepreneurial orientation of EMNEs has a positive effect on reverse innovations. Furthermore, the authors find positive effects of reverse innovation on the international performance of EMNEs. This pattern of results suggests that the relationship between entrepreneurial orientation and international performance is partially mediated by reverse innovation.Practical implicationsThe study’s findings help managers in EMNEs to promote reverse innovation by building and using their entrepreneurial orientation. It also helps them to set out and gauge the chances of success of their internationalization strategies. The findings also hold relevance for firms in developed economies as well, as they may understand which emerging economy competitors stand to threaten their positions.Originality/valueThe strategic role of reverse innovations – i.e. clean slate, super value and technologically advanced products originating from emerging markets – has generated considerable research attention. It is clear that reverse innovations impact the international performance of EMNEs. Yet how entrepreneurial orientation influences international performance is still underexplored. Thus, the current study clarifies the mechanism by examining and testing the mediating role of reverse innovation among the entrepreneurial orientation–international performance link.
Metric-Based Few-Shot Learning for Pollen Grain Image Classification

: Pollen is an important substance produced by seed plants. They contain the male gametes which are necessary for fertilization and the reproduction of flowering plants. The scientific study of pollen, palynology, plays a crucial role in a number of disciplines, such as allergology, ecology, forensics, as well as food-production. Current trends in climate research indicate an increasing importance of palynology, partly due to a projected rise in allergies. Pollen detection and classification in microscopic images via deep neural networks has been studied and researched, however, pollen data is often sparse or imbalanced, especially when compared to the number of plant species, which is estimated to be between 330,000 and 450,000, of which only a small percentage is investigated. In this work, we present a solution that does not require a large number of data samples by employing Few-Shot Learning. Our work shows, that by utilizing Prototypical Networks, an average classification accuracy of 90% can be achieved on state-of-the-art pollen data sets. The results can be further improved by fine-tuning the net, achieving up to 98% accuracy on novel classes. To our best knowledge, this is the first attempt at applying Few-Shot Learning in the field of pollen analysis.
Shaping the Huara Intrusive Complex in the Hyperarid Atacama Desert—Erosional Near‐Stasis Contrasting High Topographic Gradients

The Atacama Desert is one of the driest and oldest deserts on Earth, with extremely low precipitation rates (<2 mm/yr). Mostly abiotic hyperarid environmental conditions prevail, and surface processes act at extremely low rates over the long‐term. To gain knowledge about the rate of surface processes and age of landscapes in desert environments, terrestrial cosmogenic nuclide derived erosion rate estimates can be used. Within the Huara Intrusive Complex, situated in the hyperarid core of the Atacama Desert, basin‐averaged bedrock erosion rates from channel sediments are extremely low, that is, less than 1 m/Myr. Such low rates indicate that fluvial processes operate very slowly or are almost absent. Bedrock erosion rates of channel knickpoints, however, reveal one to two orders of magnitude higher erosion rates (2–12 m/Myr). Erosion rates are remarkably low when compared to the steep surrounding topography. Tectonic uplift creates higher gravitational potentials for surface processes, controlling the overall erosion rate capacity. However, erosion itself is taking place by local precipitation capable of exceeding thresholds for surface activity. In the Atacama Desert, this happens only due to rare severe precipitation events, explaining the extremely low erosion rates. The efficiency of these events is modulated by local intrinsic processes and conditions, such as high infiltration capacities of Atacama soils and/or large channel boulder accumulations. Due to the virtual absence of these precipitation events capable of erosion, the landscape appears to be in hibernation.