State recommendations on approaches to LANDSAT

The feasibility of continuing the LANDSAT program is contingent upon the success of the technology transfer process to state and local governments. The focus of these concerns can be generally expressed in terms of these issue areas: (1) user needs, in terms of awareness, technical capabilities, and training; (2) product availability and pricing; and (3) roles and communication links, in terms of federal and state governments, the private sector, and the universities. The perspective of the states on these issues are classified. Where possible, alternative strategies for accomplishing the satellite technology transfer for effective state implementation are suggested. Those suggestions are based on the recommendations offered by the state and local user community

An Analysis of the Current United States and State of Washington\u27s Mental Health Policies Serving Children and Families

Due to continued fragmentation and gaps in mental health services and the increase in the prevalence of mental health problems for children, youth, and their families, these populations remain underserved. In 2003, the federal New Freedom Commission (Commission) responded by publishing policies to address these concerns. As directed in 2005, the Substance Abuse and Mental Health Services Administration (SAMHSA) funded planning incentive grants to states to transform their delivery of care. The study reviewed the federal policy, specifically the recommendations of the Commission’s Subcommittee on Children and Families, and Washington State’s policy and implementation actions of its five-year SAMHSA incentive grant. The method included searching, reviewing, and analyzing the literature on the topic published sinceapproximately 2002. The analysis distilled the recommended determinants in children’s mental health care transformation: prevention, early intervention, and screening in child welfare (juvenile justice and foster care) strategies; evidence-based practices; geographic disparities; workforce barriers; cultural competence aspirations; and consumer, schoolbased mental health, and primary care providers’ role expectations. Despite innumerable studies, policies and services remain fragmented with gaps. The following topics from the outcome data require continuing attention: increasing the 2 cultural competency of professional services that are efficacious, and designing and promulgating measures for evidence-based practice specific to children. Three themes emerged regarding how to serve children’s mental health needs in Washington State in a more efficacious manner. Within the penumbras of cultural competency and outcome-based measures, constructs for evidence-based practice for children need to be age-developmentally appropriate. Simultaneously, both the family role and venues of service delivery need to be considered, e.g., schools, out-of-home placement, and clinics. Access to mental health care through schools and primary care providers needs to be collaborative with behavioral health professionals. School policy needs to link students’ attendance and achievement with their physical and behavioral health. Training for the mental health workforce requires increased cultural competency. Rural mental health care requires incentives to train and retain a workforce reflective of the demographics, particularly in the areas populated by persons of color. Also, the number of prescribers needs to increase through certification of nurse practitioners and psychologists

Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting

For person re-identification, existing deep networks often focus on representation learning. However, without transfer learning, the learned model is fixed as is, which is not adaptable for handling various unseen scenarios. In this paper, beyond representation learning, we consider how to formulate person image matching directly in deep feature maps. We treat image matching as finding local correspondences in feature maps, and construct query-adaptive convolution kernels on the fly to achieve local matching. In this way, the matching process and results are interpretable, and this explicit matching is more generalizable than representation features to unseen scenarios, such as unknown misalignments, pose or viewpoint changes. To facilitate end-to-end training of this architecture, we further build a class memory module to cache feature maps of the most recent samples of each class, so as to compute image matching losses for metric learning. Through direct cross-dataset evaluation, the proposed Query-Adaptive Convolution (QAConv) method gains large improvements over popular learning methods (about 10%+ mAP), and achieves comparable results to many transfer learning methods. Besides, a model-free temporal cooccurrence based score weighting method called TLift is proposed, which improves the performance to a further extent, achieving state-of-the-art results in cross-dataset person re-identification. Code is available at https://github.com/ShengcaiLiao/QAConv.Comment: This is the ECCV 2020 version, including the appendi

Beyond single-photon localization at the edge of a Photonic Band Gap

We study spontaneous emission in an atomic ladder system, with both transitions coupled near-resonantly to the edge of a photonic band gap continuum. The problem is solved through a recently developed technique and leads to the formation of a ``two-photon+atom'' bound state with fractional population trapping in both upper states. In the long-time limit, the atom can be found excited in a superposition of the upper states and a ``direct'' two-photon process coexists with the stepwise one. The sensitivity of the effect to the particular form of the density of states is also explored.Comment: to appear in Physical Review

Product recognition in store shelves as a sub-graph isomorphism problem

The arrangement of products in store shelves is carefully planned to maximize sales and keep customers happy. However, verifying compliance of real shelves to the ideal layout is a costly task routinely performed by the store personnel. In this paper, we propose a computer vision pipeline to recognize products on shelves and verify compliance to the planned layout. We deploy local invariant features together with a novel formulation of the product recognition problem as a sub-graph isomorphism between the items appearing in the given image and the ideal layout. This allows for auto-localizing the given image within the aisle or store and improving recognition dramatically.Comment: Slightly extended version of the paper accepted at ICIAP 2017. More information @project_page --> http://vision.disi.unibo.it/index.php?option=com_content&view=article&id=111&catid=7

Angular variation of the magnetoresistance of the superconducting ferromagnet UCoGe

We report a magnetoresistance study of the superconducting ferromagnet UCoGe. The data, taken on single-crystalline samples, show a pronounced structure at $B^* = 8.5$~T for a field applied along the ordered moment $m_0$. Angle dependent measurements reveal this field-induced phenomenon has an uniaxial anisotropy. Magnetoresistance measurements under pressure show a rapid increase of $B^*$ to 12.8~T at 1.0~GPa. We discuss $B^*$ in terms of a field induced polarization change. Upper critical field measurements corroborate the unusual S-shaped $B_{c2}(T)$-curve for a field along the $b$-axis of the orthorhombic unit cell.Comment: 6 pages, 5 figures; accepted for publication in Phys. Rev.

A Preliminary Study of Image Analysis for Parasite Detection on Honey Bees

International Conference Image Analysis and Recognition (ICIAR 2018, Póvoa de Varzim, Portugal

Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database

In this paper we present a novel architecture for storing visual data. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing such data requires a set of tools and frameworks such as SQL database management systems and service-oriented frameworks. The proposed solution is based on a multi-layer architecture, which allows to replace any component without recompilation of other components. The approach contains five components, i.e. Model, Base Engine, Concrete Engine, CBIR service and Presentation. They were based on two well-known design patterns: Dependency Injection and Inverse of Control. For experimental purposes we implemented the SURF local interest point detector as a feature extractor and $K$-means clustering as indexer. The presented architecture is intended for content-based retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan