nils-herrmann/clean_scirepeval huggingface dataset:
Blurred target tracking by Blur driven Tracker
Venue: 2011 International Conference on Computer Vision
Year: 2011

Visual tracking plays an important role in many computer vision tasks. A common assumption in previous methods is that the video frames are blur free. In reality, motion blurs are pervasive in the real videos. In this paper we present a novel BLUr driven Tracker (BLUT) framework for tracking motion blurred targets. BLUT actively uses the information from blurs without performing debluring. Specifically, we integrate the tracking problem with the motion from blur problem under a unified sparse approximation framework. We further use the motion information inferred by blurs to guide the sampling process in the particle filter based tracking. To evaluate our method, we have collected a large number of video sequences with significatcant motion blurs and compared BLUT with state of the art trackers. Experimental results show that, while many previous methods are sensitive to motion blurs, BLUT can robustly and reliably track severely blurred targets.
Urban Ecological Corridor Network Construction: An Integration of the Least Cost Path Model and the InVEST Model
Venue: ISPRS Int. J. Geo Inf.
Year: 2020

Under the background of urban expansion, ecological protection cannot be delayed. The construction of ecological networks is of considerable significance to ecosystem services. However, in the process of constructing a corridor network, there is no uniform standard for the selection of ecological sources and the determination of cost factors. The InVEST model is an effective complement to ecosystem service assessment for sensitively measuring external threats and their threat intensity. Therefore, taking Wuhan as an example, we combined InVEST and the least cost path model (LCP) to construct a multi target corridor network with comprehensive cost factors for birds and small terrestrial mammals. The results showed that: (1) The InVEST model provided a reliable basis for ecological source screening by demonstrating the distribution of habitat quality. (2) The corridor with a length of 12 25 km presented a "U" shape, and the impact of urbanization on small terrestrial mammals was more significant than that of birds. (3) The integrated network pattern proposed by the "point line plane" principle would provide a reference for urban ecological construction and sustainable development.
Social Attentional Memory Network: Modeling Aspect and Friend Level Differences in Recommendation
Venue: WSDM
Year: 2019

Social connections are known to be helpful for modeling users' potential preferences and improving the performance of recommender systems. However, in social aware recommendations, there are two issues which influence the inference of users' preferences, and haven't been well studied in most existing methods: First, the preferences of a user may only partially match that of his friends in certain aspects, especially when considering a user with diverse interests. Second, for an individual, the influence strength of his friends might be different, as not all friends are equally helpful for modeling his preferences in the system. To address the above issues, in this paper, we propose a novel Social Attentional Memory Network (SAMN) for social aware recommendation. Specifically, we first design an attention based memory module to learn user friend relation vectors, which can capture the varying aspect attentions that a user share with his different friends. Then we build a friend level attention component to adaptively select informative friends for user modeling. The two components are fused together to mutually enhance each other and lead to a finer extended model. Experimental results on three publicly available datasets show that the proposed SAMN model consistently and significantly outperforms the state of the art recommendation methods. Furthermore, qualitative studies have been made to explore what the proposed attention based memory module and friend level attention have learnt, which provide insights into the model's learning process.
Using Anisotropic Diffusion for Efficient Extraction of Sensor Noise in Camera Identification
Venue: Journal of forensic sciences
Year: 2012

Each digital camera has an intrinsic fingerprint that is unique to each camera. This device fingerprint can be extracted from an image and can be compared with a reference device fingerprint to determine the device origin. The complexity of the filters proposed to accomplish this is increasing. In this note, we use a relatively simple algorithm to extract the sensor noise from images. It has the advantages of being easy to implement and parallelize, and working faster than the wavelet filter that is common for this application. In addition, we compare the performance with a simple median filter and assess whether a previously proposed fingerprint enhancement technique improves results. Experiments are performed on approximately 7500 images originating from 69 cameras, and the results are compared with this often used wavelet filter. Despite the simplicity of the proposed method, the performance exceeds the common wavelet filter and reduces the time needed for the extraction.
L'estime de soi chez des etudiants dyslexiques en premiere annee d'universite.
Year: 2020

De nombreuses etudes ont ete realisees sur l'estime de soi des eleves dyslexiques. Mais tres peu ont ete elaborees avec des etudiants dyslexiques. Pourtant, le passage en etudes superieures est un stade important ou de nombreuses mutations apparaissent, en particulier sur le plan de l'autonomie. C'est aussi un moment ou l'estime de soi se consolide avant le passage vers le monde adulte (Rodriguez Tome, 1997) Des recherches ont conclu que la dimension d'estime de soi scolaire differencie systematiquement les eleves dyslexiques des eleves sans trouble (Leonova et Grilo, 2009) L'objectif de ce memoire se propose d'etudier l'estime de soi chez les etudiants dyslexiques en premiere annee d'universite. Aussi, nous savons que la dyslexie est un trouble de la lecture et de l'ecriture specifique et durable. La dyslexie est reconnue comme un trouble specifique de l'apprentissage (TSA) et trouble dys L'estime de soi est un sujet tres controverse et a amene beaucoup de chercheurs a s'y interesser. L'estime de soi se construit tout au long de la vie. La question de l'estime de soi se pose donc desormais dans tous les domaines et a toutes les etapes de la vie y compris dans le domaine scolaire et plus particulierement au regard de la reussite et/ ou de l'echec scolaire des jeunes. Dans cette recherche, nous tenterons de savoir comment est l'estime de soi d'un etudiant dyslexique pendant la premiere annee d'universite, si son estime de soi scolaire est preponderante dans son estime de soi globale, le role d'autrui sur leur estime de soi et enfin l'effet des notes sur celle ci. Nous avons constitue un echantillon de 3 etudiantes dyslexiques en premiere annee a l'universite Jean Jaures de Toulouse. Les resultats nous revelent que les etudiants dyslexiques ont une estime de soi fragilisee par le vecu scolaire. Cette estime de soi est aussi instable et diminue lorsque les etudiants dyslexiques recoivent des mauvaises notes et lorsqu'ils se sentent juger par autrui.
Current Multistage Drug Delivery Systems Based on the Tumor Microenvironment
Venue: Theranostics
Year: 2017

The development of traditional tumor targeted drug delivery systems based on EPR effect and receptor mediated endocytosis is very challenging probably because of the biological complexity of tumors as well as the limitations in the design of the functional nano sized delivery systems. Recently, multistage drug delivery systems (Ms DDS) triggered by various specific tumor microenvironment stimuli have emerged for tumor therapy and imaging. In response to the differences in the physiological blood circulation, tumor microenvironment, and intracellular environment, Ms DDS can change their physicochemical properties (such as size, hydrophobicity, or zeta potential) to achieve deeper tumor penetration, enhanced cellular uptake, timely drug release, as well as effective endosomal escape. Based on these mechanisms, Ms DDS could deliver maximum quantity of drugs to the therapeutic targets including tumor tissues, cells, and subcellular organelles and eventually exhibit the highest therapeutic efficacy. In this review, we expatiate on various responsive modes triggered by the tumor microenvironment stimuli, introduce recent advances in multistage nanoparticle systems, especially the multi stimuli responsive delivery systems, and discuss their functions, effects, and prospects.
Human Machine Reconfigurations: Plans and Situated Actions
Year: 2006

Acknowledgements Introduction 1. Readings and responses 2. Preface to the 1st edition 3. Introduction to the 1st edition 4. Interactive artifacts 5. Plans 6. Situated actions 7. Communicative resources 8. . Human machine communication 10. Conclusion to the 1st edition 11. Plans, scripts and other ordering devices 12. Agencies at the interface 13. Figuring the human in AI and robotics 14. Demystifications and re enchantments of the human like machine 15. Reconfigurations Notes References.
Evaluation of Deep Learning Models for Ear Recognition Against Image Distortions
Venue: 2019 European Intelligence and Security Informatics Conference (EISIC)
Year: 2019

Automated human authentication is becoming increasingly popular on a variety of daily activities, ranging from surveillance to commercial related applications. While there are many biometric modalities that can be used, ear recognition has earned its value if and when available to be captured. Ears demonstrate specific advantages over other competitors in an effort to identify cooperative and non cooperative individuals in either controlled or challenging environments. The performance of ear recognition systems can be impacted by several factors, including standoff distance, ear pose angle, and ear image quality. While all three factors can degrade ear recognition performance, here we focus on the latter two using real data, and assess the standoff distance factor by synthetically generating blurry and noisy images to simulate longer distance ear images. Thus, in this work we are inspired by various studies in the literature that discuss the how and why challenging biometric images of different modalities impact the associated biometric system recognition. Specifically, we focus on how different ear image distortions and yaw pose angles affect the performance of various deep learning based ear recognition models. Our contributions are threefold. Firstly, we are using challenging ear dataset, with a wide range of yaw pose angles, to evaluate the ear recognition performance of various original ear matching approaches. Secondly, by examining multiple convolutional neural network (CNN) architectures and employing multiple techniques for the learning process, we determine the most efficient CNN based ear recognition approach. Thirdly, we investigated the impact on performance of a set of ear recognition CNN models in the presence of multiple image degradation factors, including variations of blurriness, additive noise, brightness and contrast.
GUIDED BONE REGENERATION (GBR) USING COLLAGEN MEMBRANE BARRIER TECHNIQUE FOR PRESERVATION OF THE ALVEOLAR BONE FOLLOWING TOOTH EXTRACTION
Year: 2018

Alveolar ridge resorption is a phenomenon observed following the removal of the teeth in an otherwise healthy individual. The conditions appears to be progressive and irreversible, resulting in a host of esthetic and functional problems. Post extraction bone loss is accelerated in the first 6 months, followed by a gradual modelling( changes in size and shape) and remodeling (turn over existing bone) of the remaining bone as 40% of the alveolar height and 60% of the alveolar width lost in the first 6 months. Current methods used to prevent ridge resorption include placement of particulate autografts, allografts, alloplasts and xenografts. These biomaterials present advantages and disadvantages and depending on their structure and biochemical composition, may be resorbabale and nonresorbabale. Guided bone regeneration(GBR) is a technique in which bone growth is enhanced by maintaining the space and preventing soft tissue in growth in the area utilizing either a resorbable or non resorbable barrier membrane. GBR has become a predictable surgical technique to enhance ne bone formation in alveolar ridge augmentation, even though it is being highly technique sensitive and requires high surgical skill. The main surgical goal in application of GBR is protecting the space for bone regeneration underneath the membrane barrier, permitting blood clot stability and migration of osteogenic cells, and excludes soft tissue penetration. A wide variety of barrier membrane has been used in numerous studies over the years, eg, expanded poly tetrafluoroethylene (ePTFE collagen, polyglycolic acid and polygalactin 910. The aim of our present study is to determine the effectiveness of bone graft material and collagen membrane in preserving the dimesions of extraction sockets in ridge preservation groups during 6 month healing period compare to tooth extraction alone group.
ENTROPiA: Towards Infinite Surface Haptic Displays in Virtual Reality Using Encountered Type Rotating Props
Venue: IEEE Transactions on Visualization and Computer Graphics
Year: 2021

In this article, we propose an approach towards an infinite surface haptic display. Our approach, named ENcountered Type ROtating Prop Approach (ENTROPiA) is based on a cylindrical spinning prop attached to a robot's end effector serving as an encountered type haptic display (ETHD) This type of haptic display permits the users to have an unconstrained, free hand contact with a surface being provided by a robotic device for the users' to encounter a surface to be touched. In our approach, the sensation of touching a virtual surface is given by an interaction technique that couples with the sliding movement of the prop under the users' finger by tracking their hand location and establishing a path to be explored. This approach enables large motion for a larger surface rendering, permits to render multi textured haptic feedback, and leverages the ETHD approach introducing large motion and sliding/friction sensations. As a part of our contribution, a proof of concept was designed for illustrating our approach. A user study was conducted to assess the perception of our approach showing a significant performance for rendering the sensation of touching a large flat surface. Our approach could be used to render large haptic surfaces in applications such as rapid prototyping for automobile design.
Dispositif d'administration de medicament par voie nasale
Year: 2012

La presente invention se rapporte a un dispositif d'administration de compose destine a administrer un jet derive d'un agent propulseur et une formulation de medicament. La formulation de medicament est produite sous une forme medicamenteuse intranasale ayant la forme d'une poudre, d'une suspension, d'une dispersion ou d'un liquide. La forme medicamenteuse intranasale propulsee est deposee dans la region olfactive de la cavite nasale. Le medicament depose dans la region olfactive est administre au cerveau, ce qui evite la barriere hemato encephalique. L'agent propulseur hydrofluoroalcane provenant d'une canette sous pression est oriente vers un diffuseur et une chambre qui contient le medicament ou la forme medicamenteuse intranasale se trouve sous forme d'alcool. La forme medicamenteuse intranasale sous forme d'alcool passe a travers une buse, ce qui permet d'administrer un jet a la region olfactive d'une cavite nasale de l'utilisateur.
High level semantic photographic composition analysis and understanding with deep neural networks
Venue: 2017 IEEE International Conference on Multimedia Expo Workshops (ICMEW)
Year: 2017

In order to take better photos, it is a fundamental step for the beginners of photography to learn basic photo composition rules. However, there are no tools developed to help beginners analyze the composition rules in given photos. Thus, in this study we developed a system with the capability to identify 12 common composition rules in a photo. It should be noted that some of the 12 common composition rules have not been considered by the previous studies, and this deficit gives this study its significance and appropriateness. In particular, we utilized deep neural networks (DNN) to extract high level semantic features for facilitating the further analysis of photo composition rules. In order to train the DNN model, our research team constructed a dataset, which is collected from some famous photo websites, such as DPChallenge, Flicker, and Unsplash. All the collected photos were later labelled with 12 composition rules by a wide range of raters recruited from Amazon Mechanical Turk (AMT) Two DNN architectures (AlexNet and GoogLeNet) were then employed to build our system based on the collected dataset. The representative features of each composition rule were further visualized in our system. The results showed the feasibility of the proposed system and revealed the possibility of using this system to assist potential users to improve their photographical skills and expertise.
A Method to Implement Interprofessional Simulations into Established Curriculum: Process and Survey of Student Responses for Nursing, Radiologic Science, and Respiratory Care.
Venue: Journal of allied health
Year: 2019

Interprofessional education (IPE) among healthcare students of different programs provides a foundation for learning how to work effectively as a team. Combining IPE and simulation gives students the chance to interact with each other while caring for a patient in a safe setting. Adding IPE to established curriculum for healthcare disciplines poses significant challenges: synchronizing student schedules, low student and faculty buy in, lack of administrative support, outdated equipment and technology, and inadequate space. This paper describes a process of incorporating IPE simulations into established curricula for nursing, radiologic science, and respiratory care students. Following the simulations, students (n=98) were asked to respond to their experience via survey questionnaire. The results suggested that IPE simulation activities were effective and enjoyable learning opportunities that meet the IPE core competencies of improving teamwork, communication, mutual respect of values and ethics, and learning of others' roles and responsibilities. In conclusion, when a structured framework for IPE is lacking, it still appears to be a meaningful learning activity and worth the efforts of interdisciplinary faculty.
Phased array antenna metamaterial based design operating in millimeter wave for 5G mobile networks
Venue: 2016 IEEE Student Conference on Research and Development (SCOReD)
Year: 2016

In the following couple of years, an alternative for the 4G and its derivatives like the LTE A is inventible. The demands and challenges must be envisaged and addressed to meet the desired objectives of the upcoming 5G mobile networks which are resembled by significant increasing in capacity, improved data rate, low latency, and better quality of service. To achieve these objectives, radical enhancements and improvements have to be made in cellular network architecture and the antenna configuration that is used for this purpose. This paper presents the results of a 5G cellular network phased array antenna with millimeter wave beamforming at 28Hz. A microstrip structured antenna on a metamaterial substrate that performs as a leaky wave, in which, it has a composite cascaded right left handed transmission line configuration 32 unit cells. The main beam is tuned via varicaps with gain changing between 5dB to 6dB during scanning.
ROS Are Good.
Venue: Trends in plant science
Year: 2017

Reactive oxygen species (ROS) are thought to play a dual role in plant biology. They are required for many important signaling reactions, but are also toxic byproducts of aerobic metabolism. Recent studies revealed that ROS are necessary for the progression of several basic biological processes including cellular proliferation and differentiation. Moreover, cell death that was previously thought to be the outcome of ROS directly killing cells by oxidation, in other words via oxidative stress is now considered to be the result of ROS triggering a physiological or programmed pathway for cell death. This Opinion focuses on the possibility that ROS are beneficial to plants, supporting cellular proliferation, physiological function, and viability, and that maintaining a basal level of ROS in cells is essential for life.
Exosomes Released by Bone Marrow Mesenchymal Stem Cells Attenuate Lung Injury Induced by Intestinal Ischemia Reperfusion via the TLR4/NF kB Pathway
Venue: International journal of medical sciences
Year: 2019

Acute lung injury (ALI) is a primary component of multiple organ dysfunction syndromes triggered by intestinal ischemia reperfusion (IIR) which results in high mortality. Existing treatment options remain unsatisfactory. Mesenchymal stem cells (MSCs) have shown considerable promise as a biological therapy for ALI in preclinical studies. However, there are many limitations to stem cell treatment. This study aimed to investigate whether MSC derived exosomes, a non cellular alternative, are able to act in a protective capacity similar to that of MSCs for ALI triggered by IIR in a rat model and to explore the underlying mechanisms.  The IIR model involved occlusion of the superior mesenteric artery of a rat for 75 min then reperfusion for 20 h. Rats then received an intravenous injection of either bone marrow derived MSCs or MSC derived exosomes. Pathologic alteration of lung tissue, levels of pro inflammatory cytokines, apoptotic proteins and TLR4/NF kB signaling were measured to evaluate the therapeutic effect of treatment with either MSCs or exosomes.  Manifestations of acute lung injury after IIR were observed as edema and hemorrhage of alveoli and mesenchyme, and inflammatory cell infiltration. MSCs and MSC derived exosomes both attenuated IIR induced lung damage by decreased apoptosis and inflammation accompanied by down regulation of TLR4 and NF kB expression.  MSC derived exosomes provide protection similar to that of MSCs against IIR induced ALI via inhibition of TLR4/NF kB signaling, suggesting that a potential strategy against IIR mediated acute lung injury could be therapy with exosomes as a non cellular alternative to MSC transplantation.