Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Level Domain Adaptive Learning for Cross-Domain Detection

In recent years, object detection has shown impressive results using supervised deep learning, but it remains challenging in a cross-domain environment. The variations of illumination, style, scale, and appearance in different domains can seriously affect the performance of detection models. Previous works use adversarial training to align global features across the domain shift and to achieve image information transfer. However, such methods do not effectively match the distribution of local features, resulting in limited improvement in cross-domain object detection. To solve this problem, we propose a multi-level domain adaptive model to simultaneously align the distributions of local-level features and global-level features. We evaluate our method with multiple experiments, including adverse weather adaptation, synthetic data adaptation, and cross camera adaptation. In most object categories, the proposed method achieves superior performance against state-of-the-art techniques, which demonstrates the effectiveness and robustness of our method.
Improving Sketches for Similarity Search

Prace se zabyva tzv. sketches. Sketch je bitova reprezentace objektu reprezentujici jeho relativni polohu v prostoru. V praci navrhujeme definici vlastnosti sketchu, ktere maji zlepsit jejich vyuziti v podobnostnim vyhledavani. Tyto vlastnosti testujeme a potvrzujeme zvyseni­ kvality vyhledavani pri jejich splneni.
OGLE-2015-BLG-1649Lb: A Gas Giant Planet around a Low-mass Dwarf

We report the discovery of an exoplanet from the analysis of the gravitational microlensing event OGLE-2015-BLG-1649 that challenges the core accretion model of planet formation and appears to support the disk instability model. The planet/host-star mass ratio is q = 7.2 × 10−3 and the projected separation normalized to the angular Einstein radius is s = 0.9. We conducted high-resolution follow-up observations using the Infrared Camera and Spectrograph (IRCS) camera on the Subaru telescope and are able to place an upper limit on the lens flux. From these measurements we are able to exclude all host stars greater than or equal in mass to a G-type dwarf. We conducted a Bayesian analysis with these new flux constraints included as priors resulting in estimates of the masses of the host star and planet. These are ML = 0.34 ± 0.19 M⊙ and , respectively. The distance to the system is . The projected star–planet separation is . The estimated relative lens-source proper motion, ∼7.1 mas yr−1, is fairly high and thus the lens can be better constrained if additional follow-up observations are conducted several years after the event.
High-order symplectic integrators for planetary dynamics and their implementation in rebound

Direct N-body simulations and symplectic integrators are effective tools to study the long-term evolution of planetary systems. The Wisdom–Holman (WH) integrator in particular has been used extensively in planetary dynamics as it allows for large time-steps at good accuracy. One can extend the WH method to achieve even higher accuracy using several different approaches. In this paper, we survey integrators developed by Wisdom et al., Laskar & Robutel, and Blanes et al. Since some of these methods are harder to implement and not as readily available to astronomers compared to the standard WH method, they are not used as often. This is somewhat unfortunate given that in typical simulations it is possible to improve the accuracy by up to six orders of magnitude (! ) compared to the standard WH method without the need for any additional force evaluations. To change this, we implement a variety of high-order symplectic methods in the freely available N-body integrator rebound. In this paper, we catalogue these methods, discuss their differences, describe their error scalings, and benchmark their speed using our implementations.
Multiple Human Association between Top and Horizontal Views by Matching Subjects' Spatial Distributions

Video surveillance can be significantly enhanced by using both top-view data, e.g., those from drone-mounted cameras in the air, and horizontal-view data, e.g., those from wearable cameras on the ground. Collaborative analysis of different-view data can facilitate various kinds of applications, such as human tracking, person identification, and human activity recognition. However, for such collaborative analysis, the first step is to associate people, referred to as subjects in this paper, across these two views. This is a very challenging problem due to large human-appearance difference between top and horizontal views. In this paper, we present a new approach to address this problem by exploring and matching the subjects' spatial distributions between the two views. More specifically, on the top-view image, we model and match subjects' relative positions to the horizontal-view camera in both views and define a matching cost to decide the actual location of horizontal-view camera and its view angle in the top-view image. We collect a new dataset consisting of top-view and horizontal-view image pairs for performance evaluation and the experimental results show the effectiveness of the proposed method.
Vehicular Multi-object Tracking with Persistent Detector Failures

Autonomous vehicles often perceive the environment by feeding sensor data to a learned detector algorithm, then feeding detections to a multi-object tracker that models object motions over time. Probabilistic models of multi-object trackers typically assume that errors in the detector algorithm occur randomly over time. We instead assume that undetected objects and false detections will persist in certain conditions, and modify the tracking framework to account for them. The modifications are tested with a novel lidar-based vehicle detector, and shown to enable real-time detection and tracking without specialized computing hardware.
Exploiting weak ties in trust-based recommender systems using regular equivalence

User-based Collaborative Filtering (CF) is one of the most popular approaches to create recommender systems. CF, however, suffers from data sparsity and the cold-start problem since users often rate only a small fraction of available items. One solution is to incorporate additional information into the recommendation process such as explicit trust scores that are assigned by users to others or implicit trust relationships that result from social connections between users. Such relationships typically form a very sparse trust network, which can be utilized to generate recommendations for users based on people they trust. In our work, we explore the use of regular equivalence applied to a trust network to generate a similarity matrix that is used for selecting k-nearest neighbors used for item recommendation. Two vertices in a network are regularly equivalent if their neighbors are themselves equivalent and by using the iterative approach of calculating regular equivalence, we can study the impact of strong and weak ties on item recommendation. We evaluate our approach on cold-start users on a dataset crawled from Epinions and find that by using weak ties in addition to strong ties, we can improve the performance of a trust-based recommender in terms of recommendation accuracy.
Lazy Stream Programming in Prolog

In recent years, stream processing has become a prominent approach for incrementally handling large amounts of data, with special support and libraries in many programming languages. Unfortunately, support in Prolog has so far been lacking and most existing approaches are ad-hoc. To remedy this situation, we present {\em lazy stream generators} as a unified Prolog interface for stateful computations on both finite and infinite sequences of data that are produced incrementally through I/O and/or algorithmically. We expose stream generators to the application programmer in two ways: 1) through an abstract sequence manipulation API, convenient for defining custom generators, and 2) as idiomatic lazy lists, compatible with many existing list predicates. We define an algebra of stream generator operations that extends Prolog via an embedded language interpreter, provides a compact notation for composing generators and supports moving between the two isomorphic representations. As a special instance, we introduce answer stream generators that encapsulate the work of coroutining first-class logic engines and support interoperation between forward recursive {\em AND-streams} and backtracking-generated {\em OR-streams}. Keywords: lazy stream generators, lazy lists, first-class logic engines, stream combinators, AND-stream / OR-stream interoperation, Prolog extensions
UGAN: Untraceable GAN for Multi-Domain Face Translation

The multi-domain image-to-image translation is a challenging task where the goal is to translate an image into multiple different domains. The target-only characteristics are desired for translated images, while the source-only characteristics should be erased. However, recent methods often suffer from retaining the characteristics of the source domain, which are incompatible with the target domain. To address this issue, we propose a method called Untraceable GAN, which has a novel source classifier to differentiate which domain an image is translated from, and determines whether the translated image still retains the characteristics of the source domain. Furthermore, we take the prototype of the target domain as the guidance for the translator to effectively synthesize the target-only characteristics. The translator is learned to synthesize the target-only characteristics and make the source domain untraceable for the discriminator, so that the source-only characteristics are erased. Finally, extensive experiments on three face editing tasks, including face aging, makeup, and expression editing, show that the proposed UGAN can produce superior results over the state-of-the-art models. The source code will be released.
New class of solutions to Laplace equation: Regularized multipoles of negative orders

We introduce a new class of solutions to Laplace equation, dubbed logopoles, and use them to derive a new relation between solutions in prolate spheroidal and spherical coordinates. The main novelty is that it involves spherical harmonics of the second kind, which have rarely been considered in physical problems because they are singular on the entire z axis. Logopoles, in contrast, have a finite line singularity like solid spheroidal harmonics, but are also closely related to solid spherical harmonics and can be viewed as an extension of the standard multipole ladder toward the negative multipolar orders. These new solutions may prove a fruitful alternative to either spherical or spheroidal harmonics in physical problems.
Local characteristics and tangency of vector-valued martingales

This paper is devoted to tangent martingales in Banach spaces. We provide the definition of tangency through local characteristics, basic $L^p$- and $\phi$-estimates, a precise construction of a decoupled tangent martingale, new estimates for vector-valued stochastic integrals, and several other claims concerning tangent martingales and local characteristics in infinite dimensions. This work extends various real-valued and vector-valued results in this direction e.g. due to Grigelionis, Hitczenko, Jacod, Kallenberg, Kwapien, McConnell, and Woyczynski. The vast majority of the assertions presented in the paper is done under the sufficient and necessary UMD assumption on the corresponding Banach space.
Data Dissemination Techniques in Mobile Computing Environment

Generally, data is broadcasted through high downlink channel capacity. The capacity of this channel is very large when compared to the uplink channel capacity. This method is best suited for mobile computing environment. Here the server continuously broadcast and the client listens and downloads the required data. In this scenario, when the client requests the required data, it should be able to access within a minimum time. So, the primary goal of mobile computing is to achieve minimum access time. This paper discusses various research concepts where the readers can proceed with the research work.
Tight Approximation for Variants of Directed Steiner Tree via State-Tree Decomposition and Linear Programming Rounding

Directed Steiner Tree (DST) is a central problem in combinatorial optimization and theoretical computer science. Recently, Grandoni, Laekhanukit and Li and independently Ghuge and Nagarajan gave quasi-polynomial time $O(\log^2k/\log \log k)$-approximation algorithms for the problem, which is tight under popular complexity assumptions. In this paper, we show a general framework that achieves $O(\log n \log k)$-approximation for many variants of DST. We show that if the problem has the property that the validity of the tree and its cost can be checked and computed using a bottom-to-top procedure, then the general framework can be used to produce a small-cost {multi-tree}: a tree that may contain multiple copies of a vertex or an edge. Using the framework, we show that two prominent variants of DST, namely Length-Bounded DST (LB-DST) and Buy-at-Bulk DST with Concave Cost Functions (BaB-DST-Concave), admit $O(\log n \log k)$-approximation algorithms. In the Length-Bounded Directed Steiner Tree (LB-DST) problem, there are bounds on lengths of paths from the root to vertices in the output tree. In the Buy-at-Bulk DST problem with Concave Functions (BaB-DST-Concave), each terminal needs to receive a flow from the root and the cost of each edge is a concave function on the total amount of flow that it carries. Our results almost match the best known $O(\log ^2k/\log \log k)$ algorithm that have recently been discovered by Ghuge and Nagarajan. Another variant that fits into the framework is the Degree-Bounded DST (DB-DST) problem. In this problem, we are additionally given a degree bound $d_v$ on each vertex $v \in V$, which imposes the constraint that $v$ is allowed to have at most $d_v$ children in the output tree. In this case, our framework gives an $O(\log^3n \log k, \log n\log k)$-bicritiera approximation, which is the first non-trivial result for the problem.
Entanglement area law for shallow and deep quantum neural network states

A study of the artificial neural network representation of quantum many-body states is presented. The locality and entanglement properties of states for shallow and deep quantum neural networks are investigated in detail. By introducing the notion of local quasi-product states, for which the locally connected shallow feed-forward neural network states and restricted Boltzmann machine states are special cases, we show that Rényi entanglement entropies of all these states obey the entanglement area law. Besides, we also investigate the entanglement features of deep Boltzmann machine states and show that locality constraints imposed on the neural networks make the states obey the entanglement area law. Finally, as an application, we apply the notion of Rényi entanglement entropy to understand the power of neural networks, and show that image classification problems can be efficiently solved must obey the area law.
Marbled Murrelet (Brachyramphus marmoratus)

The Marbled Murrelet, Brachyramphus marmoratus, is a member of the auk family (Alcidae). No subspecies are recognized in North America (AOU 1997). Some intraspecific morphological and molecular variation has been found among populations of Marbled Murrelets (reviewed in Burger 2002). The small population in the western Aleutian Islands, Alaska, shows some genetic differences from the rest of the North American population, but samples from British Columbia, southeastern Alaska, Washington, and Oregon showed no consistent genetic differences or evidence of subspecies.
Modeling and Forecasting Day-Ahead Hourly Electricity Prices: A Review

Electricity markets around the world are being transformed from a highly Government regulated and controlled markets into deregulated markets. Today, electricity trading has transformed from primarily being a technical business, to one in which the product is treated in the same way as any other commodity. The main objective of deregulation is to introduce competition in the power industry and provide more choices to market participants in the way they trade electricity and ancillary services. In the framework of competitive electricity markets, power producers and consumers need accurate price forecasting tools because price forecasts embody crucial information for producers and consumers when planning bidding strategies in order to maximize their benefits and utilities. A Generator/firm/Individual Power Producer (IPP) which is able to forecast prices correctly can adjust its own production schedule accordingly and hence maximize its profits. But one has to bear in mind that electricity is a very unique commodity that cannot be economically stored and the end user demand shows strong seasonality. This current study reviews literature pertaining to short term electricity price modeling and forecasting and gives direction for future researchers.Keywords: Electricity, Price, Market, Modeling, Forecasting
CROSSOVER TO MEMORY EXPANSION WITH ADESTO ECOXiP AND NXP ’ S i . MX RT CROSSOVER PROCESSORS

With 8.4 billion connected “things” having shipped in 2017, the internet of tomorrow is clearly upon us. We have entered a new age of human to machine interactions where technology is guiding many aspects of our lives. For a variety of end devices such as wearables, home monitoring nodes and industrial controllers, the capabilities of the embedded processor play a vital role in addressing the insatiable demand for a higher order of functionality. This has led to industry focus on machine learning enabled by vision and audio processing to bring the computation needed to make decisions at the edge node. These capabilities require elevated levels of processing performance and memory space for MCUs. The push for processing has led to a new breed of semiconductor device which does not fit into a traditional definition of a microcontroller. The ‘Crossover Processor’ integrates attributes of a microprocessor such as higher CPU speeds, multimedia interfaces and expandable memory into a microcontroller form factor built for cost effectiveness and fastest development time. This new crossover processor class of device provides embedded developers the ability to solve many problems in today’s fast-moving technology markets.
Systematic Review of Research Trends in Robotics Education for Young Children

This study conducted a systematic and thematic review on existing literature in robotics education using robotics kits (not social robots) for young children (Pre-K and kindergarten through 5th grade). This study investigated: (1) the definition of robotics education; (2) thematic patterns of key findings; and (3) theoretical and methodological traits. The results of the review present a limitation of previous research in that it has focused on robotics education only as an instrumental means to support other subjects or STEM education. This study identifies that the findings of the existing research are weighted toward outcome-focused research. Lastly, this study addresses the fact that most of the existing studies used constructivist and constructionist frameworks not only to design and implement robotics curricula but also to analyze young children’s engagement in robotics education. Relying on the findings of the review, this study suggests clarifying and specifying robotics-intensified knowledge, skills, and attitudes in defining robotics education in connection to computer science education. In addition, this study concludes that research agendas need to be diversified and the diversity of research participants needs to be broadened. To do this, this study suggests employing social and cultural theoretical frameworks and critical analytical lenses by considering children’s historical, cultural, social, and institutional contexts in understanding young children’s engagement in robotics education.
OPTIONS FOR STABILISING RIPARIAN ESTUARINE ZONES

This paper deals with the issues and practical considerations of providing stability to eroding river banks located in estuarine settings. The adaptation in recent years of traditional ‘hard engineering’ solutions in order to provide increases in habitat and environmental values, has led to a range of options being trialled and adopted. The Soil Conservation Service (SCS) has been involved with the design and implementation of these options in the Hunter and Wallis Lakes catchments including rock fillets, saltmarsh benches, stable grade beaches and log crib walls. An evaluation of the effectiveness of these solutions in comparison with traditional rock revetment has been made with conclusions based on pre-determined goals of stability and post construction mangrove and saltmarsh recruitment. The function and application of these options has also been assessed based on: • Desired outcome – stability, revegetation or both? • Function over time – will structure dilapidation reduce function or is there inherent resilience? ; • Monitoring and evaluation. The successful implementation of the options discussed has also been considered and is dependent on adequate site survey, an attention to detail during construction and identifying outcome(s) of proposed works
TRANSPARENCY FOR OFDM EXPERIMENTATION

Many developments in communications systems begin as a theoretical model and then analyzed in a simulation environment such as Matlab. Often, these simulations do not provide the complexity of a real implementation where one must deal with real circuitry and channels. The open source GNU Radio platform offers an easy transition between the theoretical models and an affordable solution to test the models under real-world conditions. We present the concept of GNU Radio for this purpose here by discussing and analyzing a flexible OFDM transceiver. This design offers research and development of different methods of OFDM symbol transmission, reception, and synchronization. These concepts are currently being applied to develop waveforms such as WiMAX.
Optimizing the African VLBI Network for Astronomy and Geodesy

The African VLBI Network will be a pan-African network of radio telescopes comprised of converted redundant satellite Earth-station antennas and new purpose-built radio telescopes. The first of these antennas, in Ghana, is currently being converted to a radio telescope and current funding is estimated to permit the conversion of two more antennas in Africa. These antennas will initially be equipped with a 5-GHz and 6.7-GHz receiver and the next receiver likely to be fitted is a 1.4–1.7-GHz receiver. While it would be advantageous for the AVN antennas to be able to participate also in geodetic and astrometric VLBI observations, there is no funding currently for this. In this paper we re-visit the scientific justifications for the AVN in an attempt to optimize the AVN for each science case, both astronomical and geodetic.