nils-herrmann/clean_scirepeval huggingface dataset:
Deep learning based supervised hashing for efficient image retrieval
Venue: 2016 IEEE International Conference on Multimedia and Expo (ICME)

Due to its storage and search efficiency, hashing has attracted great attentions in large scale vision problems such as image retrieval and recognition. This paper presents a novel Deep Learning based Supervised Hashing (DLSH) method by using a deep neural network to better capture the semantic structure of nonlinear and complex data. We consider learning a nonlinear embedding that simultaneously preserves semantic information and produces nearby binary codes for semantically similar data. Specifically, our hashing model is trained to maximize the similarity measure of neighbor pairs while preserving the relative similarity of non neighbor pairs with a relaxed empirical penalty in the binary space. An effective regularizer for minimizing the quantization loss between the learned embedding and the binary codes is also considered in the optimization to generate better hash code quality. Experimental results have demonstrated the proposed method outperforms the state of the art methods.
YFCC100M HybridNet fc6 Deep Features for Content Based Image Retrieval
Venue: MMCommons ACM Multimedia

This paper presents a corpus of deep features extracted from the YFCC100M images considering the fc6 hidden layer activation of the HybridNet deep convolutional neural network. For a set of random selected queries we made available k NN results obtained sequentially scanning the entire set features comparing both using the Euclidean and Hamming Distance on a binarized version of the features. This set of results is ground truth for evaluating Content Based Image Retrieval (CBIR) systems that use approximate similarity search methods for efficient and scalable indexing. Moreover, we present experimental results obtained indexing this corpus with two distinct approaches: the Metric Inverted File and the Lucene Quantization. These two CBIR systems are public available online allowing real time search using both internal and external queries.
Deep Aggregation of Local 3D Geometric Features for 3D Model Retrieval
Venue: BMVC

Aggregation of local features is a well studied approach for image as well as 3D model retrieval (3DMR) A carefully designed local 3D geometric feature is able to describe detailed local geometry of 3D model, often with invariance to geometric transformations that include 3D rotation of local 3D regions. For efficient 3DMR, these local features are aggregated into a feature per 3D model. A recent alternative, end toend 3D Deep Convolutional Neural Network (3D DCNN) [7][33] has achieved accuracy superior to the abovementioned aggregation of local features approach. However, current 3D DCNN based methods have weaknesses; they lack invariance against 3D rotation, and they often miss detailed geometrical features due to their quantization of shapes into coarse voxels in applying 3D DCNN. In this paper, we propose a novel deep neural network for 3DMR called Deep Local feature Aggregation Network (DLAN) that combines extraction of rotation invariant 3D local features and their aggregation in a single deep architecture. The DLAN describes local 3D regions of a 3D model by using a set of 3D geometric features invariant to local rotation. The DLAN then aggregates the set of features into a (global) rotation invariant and compact feature per 3D model. Experimental evaluation shows that the DLAN outperforms the existing deep learning based 3DMR algorithms.
Understanding Customer Experience Throughout the Customer Journey

Understanding customer experience and the customer journey over time is critical for firms. Customers now interact with firms through myriad touch points in multiple channels and media, and customer experiences are more social in nature. These changes require firms to integrate multiple business functions, and even external partners, in creating and delivering positive customer experiences. In this article, the authors aim to develop a stronger understanding of customer experience and the customer journey in this era of increasingly complex customer behavior. To achieve this goal, they examine existing definitions and conceptualizations of customer experience as a construct and provide a historical perspective of the roots of customer experience within marketing. Next, they attempt to bring together what is currently known about customer experience, customer journeys, and customer experience management. Finally, they identify critical areas for future research on this important topic.
Prison Rape Reform: Perspectives from Women with Life Sentences on the Impact of a Class Action Lawsuit

Sexual abuse by correctional staff against prisoners violates multiple international human rights standards yet, despite federal policy efforts, remains a concern in the USA. Prisoners who are victims of custodial sexual abuse have used legal remedies, such as class action lawsuits, to acknowledge their individual experiences of victimization and to gain effective remedies, as outlined in human rights law, such as injunctive relief (e.g. institutional changes) This study explores women's perceptions of outcomes from a class action lawsuit regarding sexual abuse during imprisonment by correctional officers. This lawsuit spanned 15 years and included over 800 women. The incarcerated women serving life sentences who participated in this class action lawsuit were well positioned to describe the kinds of changes that did and did not occur in the prison as a result of the lawsuit. Therefore, incarcerated women serving life sentences were asked to participate in semi structured interviews to elicit individual and system level outcomes from their involvement in the class action lawsuit. In terms of individual level outcomes, women described two key themes of financial outcomes and meaningful participation in the lawsuit as a change effort. For prison level changes, two themes emerged around the role of safety mechanisms in the prison and the hostile environment perpetuated by correctional officers as a result of the lawsuit. These findings offer descriptive information regarding how women in prison experience legal remedies for sexual victimization, in particular a form of "third victimization." Likewise, they are informative for future social work policy and practice efforts to address this often neglected, but concerning, human rights violation within prisons.
Exploring Options Including Class Action to Transform Military Mental Healthcare and End the Generational Cycle of Preventable Wartime Behavioral Health Crises

This article examines three major options for transforming military mental healthcare in order to end the pattern of self inflicted and largely preventable wartime behavioral health crises plaguing American veterans, their families, and broader society since the turn of the twentieth century. Evidence is provided that the first option of maintaining the status quo consisting of internal incremental changes has proven largely ineffectual in addressing the broader issues responsible for perpetuating wartime crises. The second option describes necessary transformative changes required to end the cycle of mental health neglect and preventable crises. However, there are no signs that responsible government agencies are inclined to compel the military to overhaul its system. Lastly, we offer a legal analysis for an unprecedented class action against the Department of Defense to effect change. After reviewing the history of tort law and the US military's immunity from the Feres Doctrine, we examine legal precedents both domestic and aboard. Legal strategies are described in detail from a landmark class action by British soldiers against the Ministry of Defense (MoD) or Multiple Claimants v. MoD (2003) who sued for failure to properly identify and treat predictable war stress injury like post traumatic stress disorder. The successful claims from individual military plaintiffs have been instrumental in compelling the MoD to implement necessary reforms of its mental health services and possibly end their cycle of neglect and preventable wartime crises. If successful, the proposed American class action will establish a critical precedent to elevate the importance of mental healthcare on equal footing with physical medicine both within and outside of the military.
Simultaneous Hand Eye and Robot World Calibration by Solving the $AX=YB$ Problem Without Correspondence
Venue: IEEE Robotics and Automation Letters

Calibration is often an important and necessary step in the use of image guided systems. In the case of the <inline formula> <tex math notation="LaTeX"$AX=YB$/tex math>/inline formula> problem, the relative hand eye <inline formula> <tex math notation="LaTeX"$X$/tex math>/inline formula> and robot world <inline formula> <tex math notation="LaTeX"$Y$/tex math>/inline formula> transformations must be determined to provide accurate data for use in control. As an added difficulty, the exact correspondence between the streams of sensor data <inline formula> <tex math notation="LaTeX"$A$/tex math>/inline formula>'s and <inline formula> <tex math notation="LaTeX"$B$/tex math>/inline formula>'s) is typically unknown due to asynchrony in sampling rates and processing time. One common scenario is a constant shift between the two data streams. Therefore, in this paper, we present a probabilistic method to simultaneously solve for <inline formula> <tex math notation="LaTeX"$X$/tex math>/inline formula> and <inline formula> <tex math notation="LaTeX"$Y$/tex math>/inline formula> without <italic>a priori</italic> knowledge of the correspondence between the streams of <inline formula> <tex math notation="LaTeX"$A$/tex math>/inline formula>'s and <inline formula> <tex math notation="LaTeX"$B$/tex math>/inline formula>'s. We begin by discussing probability density functions on <inline formula> <tex math notation="LaTeX"$SE(3)/tex math>/inline formula> and then use Euclidean group invariants to obtain an exact solution for <inline formula> <tex math notation="LaTeX"$X$/tex math>/inline formula> and <inline formula> <tex math notation="LaTeX"$Y$/tex math>/inline formula> We then present a method to simultaneously recover <inline formula> <tex math notation="LaTeX"$X$/tex math>/inline formula> and <inline formula> <tex math notation="LaTeX"$Y$/tex math>/inline formula> and the correspondence between temporally shifted data sets using a correlation method. Following this, we show how to solve the problem in the case when the data are completely scrambled, corresponding to a complete loss of temporal information. Finally, we numerically simulated the proposed method with asynchronous data and noise added to the stream of <inline formula> <tex math notation="LaTeX"$B$/tex math>/inline formula>'s to verify its efficiency and robustness.
Simultaneous Calibration of Hand Eye Relationship, Robot World Relationship and Robot Geometric Parameters with Stereo Vision
Venue: ICCSIP

Robot world calibration and hand eye calibration are fundamental steps for robots equipped with cameras. This problem is described as solving "AX YB" equation. However, this problem usually interacts with robot calibration, because robot geometric parameters are not very precise. Therefore, we propose a novel calibration method which can calibrate hand eye relationship, robot world relationship and robot geometric parameters simultaneously. This method considers hand eye relationship and robot world relationship as another two axes of robot arm. Modified D H convention is used to describe robot position and orientation and stereo cameras are used to measure positioning errors. In order to improve calibration accuracy, least square method is introduced to solve calibration equations. Simulation and implement prove that this overall calibration method is feasible.
Multimodal Indexing and Information Retrieval System Based on Mammographic Image Analysis: Gabor Model in Digital Learning

In this chapter, we propose a new indexing approach on medical "image scanner" databases combining the analysis process of the texture characteristics with the descriptive information. The proposed model is based on the digital image components using the characteristics vector. This vector represents the morphological processing result on image texture. It is linked to image semantic attributes using the annotations of medical professionals. Our application context is based on "Mammographic Image Analysis" (MIAS) in databases. The first aspect concerning the morphology processing on images called the "numerical signature" vector. In this approach, the texture analysis of the image is based on the Gabor Wavelets (or Filters) Theory. In offline processing for each image in MIAS databases, the Gabor Wavelets determine all numerical signatures: image characteristics as multi index vectors. In online, the query processing by image in real time defines the query signature (or image query vectors) and determines all similarities by multi index matching with images in databases. The similarities are built between the image query and images in MIAS databases using the same Gabors' algorithms implementation. In order to evaluate the robustness of our system (based on multi index, semantic attributes, query and information retrieval by image) we experiment with a controlled database of 320 mammographies. The efficient results show a set of successful criteria in image representations based on the Gabor's Wavelets, semantic attributes and significant ratios in the system recall and precision. The objective is to design an intelligent application to assist medical professionals in the decision making on tumor dignosis based on mammography scanner. Multimodal Indexing and Information Retrieval System Based on Mammographic Image Analysis: Gabor Model in Digital Learning
Specificites de la biochimie clinique geriatrique

Resume Dans cette revue, sont abordees les particularites biochimiques de la biologie clinique geriatrique bilan hydro electrolytique (ionogramme plasmatique et urinaire) et acido basique (gazometrie) marqueurs de la fonction renale et estimation du DFG (debit de filtration glomerulaire) endocrinologie (diabete, thyroide et autres glandes) denutrition (proteines, lipides et carences vitaminiques) metabolisme osseux, systeme cardio vasculaire (bilan lipidique, troponine et BNP) inflammation, marqueurs tumoraux, fonction hepatique et maladies neurodegeneratives. Les points suivants sont traites le vieillissement physiologique et pathologique, les intervalles de reference et les valeurs seuil des parametres biochimiques ainsi que certaines difficultes dans l'interpretation des bilans biochimiques. Pour illustrer notre propos, les resultats de certains travaux realises au sein du laboratoire de biochimie de l'hopital geriatrique Charles Foix (IVRY, 94) sont donnes. Au plan bibliographique, les references les plus recentes sont privilegiees et nous avons signale egalement les aspects specifiquement geriatriques des recommandations de la Haute Autorite de Sante (HAS)
Understanding the role of Indigenous community participation in Indigenous prenatal and infant toddler health promotion programs in Canada: A realist review.
Venue: Social science medicine

Striking disparities in Indigenous maternal child health outcomes persist in relatively affluent nations such as Canada, despite significant health promotion investments. The aims of this review were two fold: 1. To identify Indigenous prenatal and infant toddler health promotion programs in Canada that demonstrate positive impacts on prenatal or child health outcomes. 2. To understand how, why, for which outcomes, and in what contexts Indigenous prenatal and infant toddler health promotion programs in Canada positively impact Indigenous health and wellbeing.  We systematically searched computerized databases and identified non indexed reports using key informants. Included literature evaluated a prenatal or child health promoting program intervention in an Indigenous population in Canada. We used realist methods to investigate how, for whom, and in what circumstances programs worked. We developed and appraised the evidence for a middle range theory of Indigenous community investment ownership activation as an explanation for program success.  Seventeen articles and six reports describing twenty programs met final inclusion criteria. Program evidence of local Indigenous community investment, community perception of the program as intrinsic (mechanism of community ownership) and high levels of sustained community participation and leadership (community activation) was linked to positive program change across a diverse range of outcomes including: birth outcomes; access to pre and postnatal care; prenatal street drug use; breast feeding; dental health; infant nutrition; child development; and child exposure to Indigenous languages and culture.  These findings demonstrate Indigenous community investment ownership activation as an important pathway for success in Indigenous prenatal and infant toddler health programs.
Synergism of Alkaline Extract of the Leaves of Sasa senanensis Rehder and Antiviral Agents.
Venue: In vivo

Previous studies have shown a much greater antiviral activity of alkaline extract of the leaves of Sasa senanensis Rehder (SE) against human immunodeficiency virus (HIV) compared to lignin precursors, tannins and flavonoids, suggesting its possible application to oral diseases. Systematic comparative study with herpes simplex virus (HSV) has been limited compared to that with HIV. In the present study, we investigated whether combination of SE with other popular antiviral agents further enhances their individual activity.  Cell viability of mock infected, HIV infected and HSV infected cells was determined by the 3 (4,5 dimethylthiazol 2 yl) 2,5 diphenyltetrazolium bromide (MTT) method. The antiviral activity was evaluated by the selectivity index, defined as the ratio of 50% cytotoxic concentration to 50% effective concentration. Synergy between SE and antiviral agents was evaluated by MacSynerg and CompuSyn software.  SE showed potent anti HIV activity, although its activity was two orders lower than that of azidothymidine, 2',3' dideoxycytidine dextran sulfate and curdlan sulfate. Combination of SE with these antiviral agents produced synergistic effects. Using a newly established MTT assay system for anti HSV activity, SE and acyclovir were found to have synergistic anti HSV activity.  The present study suggests the possible efficacy of the clinical application of SE combined with antiviral agents.
Dynamic Modeling of Spherical 5R Parallel Mechanism for Spherical Plain Bearing Running in Equipment

Spherical plain bearing plays a significant role in the national defense military, aerospace, robotics and other cutting edge fields. Running in test should be conducted prior to use which can significantly reduce friction coefficient, minimize torque ripple, improve reliability and increase lifecycle. Based on the requirement for spherical plain bearing running in equipment, this paper conducts the feasibility analysis of application of spherical 5R parallel mechanism in spherical plain bearing running in equipment. According to the geometric constraint conditions, a simple kinematic model is derived. Then the dynamic model is established based on the Lagrange method. Combining with a specific prototype, the reachable workspace and kinematic characteristics are analyzed, and the effective inertia varying with the configurations of mechanism is also discussed. Finally, dynamic simulation is implemented to verify the correctness of the dynamic model by using ADAMS software. The derived model can provide theoretical basis in dynamic optimal design, driving unit lectotype and control model establishment.
Cutting performance of CBN and diamond tools in dry turning of cemented carbide

This research deals with the hard turning of cemented carbide with CBN and diamond tools, and focuses on the tool performance, mainly tool wear with respect to cutting force and cutting temperature. The internal turning tests without cutting fluid are executed with the vertical machining center. Seven types of tool materials: SC, CVD SC, two PCDs, BL NPD (Binderless nano polycrystalline diamond) and CBN: are selected for cutting three grades of cemented carbides WC having the different Co binder content (12% 20% and 25% Attrition has been found to be the main tool wear mechanism for all tools with slight adhesion of the workpiece binder on the tool face. In cutting of softest carbide WC m (25% Co) the polycrystalline CBN tool has the lowest tool wear than any other PCD tools. In turning of harder carbides WC d (20% Co) and WC t (12% Co) both polycrystalline CBN and PCD cannot be used continuously due to their low hardness, and BL NPD, SC and CVD SC tools are applicable. And the BL NPD tool has the best cutting performance with less flank wear. As for WC d, extremely stable cutting can be done with BL NPD where the principal cutting force is kept almost constant at 40 N. Only BL NPD tool can continue to turn the hardest WC t. In spite of turning hard materials, the tool temperatures measured are relatively low below 450degC due to the high thermal conductivities of tool materials. However, cutting temperature is directly related to the tool wear and cutting force rather than thermal conductivity of tool in turning of WC m and WC t.
Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring
Venue: Mob. Networks Appl.

Traditional wearable devices have various shortcomings, such as uncomfortableness for long term wearing, and insufficient accuracy, etc. Thus, health monitoring through traditional wearable devices is hard to be sustainable. In order to obtain healthcare big data by sustainable health monitoring, we design "Smart Clothing" facilitating unobtrusive collection of various physiological indicators of human body. To provide pervasive intelligence for smart clothing system, mobile healthcare cloud platform is constructed by the use of mobile internet, cloud computing and big data analytics. This paper introduces design details, key technologies and practical implementation methods of smart clothing system. Typical applications powered by smart clothing and big data clouds are presented, such as medical emergency response, emotion care, disease diagnosis, and real time tactile interaction. Especially, electrocardiograph signals collected by smart clothing are used for mood monitoring and emotion detection. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make smart clothing ubiquitous for a wide range of applications.