Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive browsing of 3D environment over the Internet

In this paper, we describe a system for wandering in a realistic environment over the Internet. The environment is captured by the concentric mosaic, compressed via the reference block coder (RBC), and accessed and delivered over the Internet through the virtual media (Vmedia) access protocol. Capturing the environment through the concentric mosaic is easy. We mount a camera at the end of a level beam, and shoot images as the beam rotates. The huge dataset of the concentric mosaic is then compressed through the RBC, which is specifically designed for both high compression efficiency and just-in-time (JIT) rendering. Through the JIT rendering function, only a portion of the RBC bitstream is accessed, decoded and rendered for each virtual view. A multimedia communication protocol -- the Vmedia protocol, is then proposed to deliver the compressed concentric mosaic data over the Internet. Only the bitstream segments corresponding to the current view are streamed over the Internet. Moreover, the delivered bitstream segments are managed by a local Vmedia cache so that frequently used bitstream segments need not be streamed over the Internet repeatedly, and the Vmedia is able to handle a RBC bitstream larger than its memory capacity. A Vmedia concentric mosaic interactive browser is developed where the user can freely wander in a realistic environment, e.g., rotate around, walk forward/backward and sidestep, even under a tight bandwidth of 33.6 kbps.
Lack of association between ipratropium bromide and mortality in elderly patients with chronic obstructive airway disease

BACKGROUND Ipratropium is commonly used for the management of elderly patients with obstructive airway disease. However, a recent report suggested that its use might be associated with a significant increase in mortality. A study was therefore conducted to compare all-cause mortality rates between users and non-users of ipratropium in elderly patients with either asthma or chronic obstructive pulmonary disease (COPD). METHODS A retrospective cohort study was performed using linked data from the Canadian Institute for Health Information, the Ontario Drug Benefit Program, the Ontario Health Insurance Plan, and the Ontario Registered Persons database. A total of 32 393 patients were identified who were aged 65 years or older and who had been discharged from hospital with asthma or COPD between 1 April 1992 and 31 March 1997. All-cause mortality rates were compared between those treated and those not treated with ipratropium following discharge from hospital. RESULTS In total, 49% of patients received ipratropium within 90 days of discharge. After adjusting for age, sex, comorbidity, use of health services, and other airway medications there was no significant association in patients with COPD between the use of ipratropium and mortality (relative risk (RR) 1.03; 95% confidence interval (CI) 0.98 to 1.08). In patients with asthma, however, there was a slight increase in the relative risk of mortality associated with the use of ipratropium (RR 1.24; 95% CI 1.11 to 1.39). A dose-response increase in the mortality rate was not observed with increasing use of ipratropium in either COPD or asthma. CONCLUSIONS The use of ipratropium in patients with COPD was not associated with an increase in mortality. However, in asthma there was a small increase in the mortality rate. Since asthmatic patients who received ipratropium had greater use of other airway medications and health services, the difference in mortality rate between users and non-users may be a reflection of unmeasured differences in asthma severity.
Multi-Camera Scene Flow by Tracking 3-D Points and Surfels

Scene flow represents the 3-D motion of points in the scene, just as optical flow is related to their 2-D motion in the images. As opposed to classical methods which compute scene flow from optical flow, we propose to compute it by tracking 3-D points and surface elements (surfels) in a multi-camera setup (at least two cameras are needed). Two methods are proposed: in the first one, the translation of each 3-D point is found by matching the neighborhoods of its 2-D projections in each camera between two time steps; in the second one, the full pose of a surfel is recovered by matching the image of its projection with a texture template attached to the surfel, and visibility changes caused by occlusion or rotation of surfels are handled. Both methods detect lost or untrackable points and surfels. They were designed for real-time execution and can be used for fast extraction of scene flow from multi-camera sequences.
An improved association method of SLAM based on ant colony algorithm

A new data association algorithm based on ACA (ant colony algorithm) is proposed to solve the data to deal with the data association problem for SLAM (simultaneous localization and mapping). Using the advantages of ACA in resolving the problem of combination and optimization, the problem of data association was transformed into combinational optimization problem and the ACA together with JML (joint maximum likelihood) theory was used to associate the measurements and features. The detailed approach was given and the algorithm model was constructed. At last, the presented algorithm was tested under certain simulation environment. The results show the superiority of the presented method in data association of SLAM. It reduces computation cost and maintains better association efficiency and it is an available method to deal with the problem on data association of SLAM.
Hidden Voice Commands: Attacks and Defenses on the VCS of Autonomous Driving Cars

Autonomous driving is becoming one of the most popular applications of AI. Meanwhile, the advances in deep learning have promoted the rapid development of the voice controllable systems (VCSs), which have almost reached the maturity stage. Before autonomous driving cars reach the highest level of automation, intelligent voice interaction remains the primary approach for human-vehicle interaction. Recent works show that such intelligent systems are vulnerable to hidden voice commands that are unnoticed or unintelligible to humans. In particular, an adversary utilizing hidden voice commands is able to control autonomous driving cars. For example, malicious voice commands embedded into the sound of online shared videos can stealthily control the vehicle when people watch the videos in the car. In this article, we investigate the potential perniciousness of hidden voice commands on the VCS of autonomous driving cars, and then discuss feasible defense strategies. We finally propose a pop-noisebased general defense strategy that can resist various kinds of attacks.
Improving user experience by infusing web technologies into desktops

Modern applications are able to adapt their architecture dynamically in order to tackle requirements, correctives and context changes. Such dynamism is often an echo of complexity and is not well supported by traditional client and user software stacks making complex the design, implementation and maintenance of the end user interface. Meanwhile, the web has seen the emergence of user interface technologies (e.g. HTML5, CSS3, JavaScript) widely adopted by developers to create highly flexible user interfaces. However, such clients are intrinsically bound to run on a web browser which is out of the control of the application. In this paper, we present ChameRIA, an application framework where a browser engine is reified as a component within the framework, thus allowing for better control over the rendering engine. We describe how we preserve a clear separation of concerns between the user interface and the application logic while maintaining coherence between them. We discuss how ChameRIA has been successfully used in two projects: a DRM document reader and a valve control application.
Model-Based Methodology for Validation of Traffic Flow Detectors by Minimizing Human Bias in Video Data Processing

This paper provides a model-based method for analysis and hypothesis testing for paired data where one source of data has to be validated against another source of data that contains subjective and dynamic errors. This study deals with human-observed flow counts collected from traffic videos of freeway cameras. The available videos are mainly used for the purpose of manual observation by transportation personnel in case of emergency. This amounts to a varying inconsistency of the quality of the videos, which presents an additional challenge when analyzing the data. Video processing cannot be performed due to the mentioned issues with regard to the video quality. The processing has to be manually performed by humans who unfortunately have an inherent bias. If the video data have to be used for validating flow detector sensors, then a technique that performs validation with subjective and dynamic erroneous data as a result of the human bias is needed. This paper presents a methodology to deal with this issue. It is based on statistical testing with heteroscedasticity, which is demonstrated through a case study using data from traffic flow detectors and traffic cameras installed on highways in the Southern Nevada Region. A model for the relationship between the video ratings and the distribution of the human errors is developed taking into consideration the human bias. A method for identification of faulty detectors is also demonstrated based on the developed technique.
BlobMaker: Free-Form Modelling with Variational Implicit Surfaces

We present BlobMaker, a program for modelling surfaces using variational implicit surfaces. Our approach uses variational implicit surfaces as a geometrical representation for free-form shapes. We have implemented new modelling operations to support stroke (pen-based) input. To this end, we have built a complete modeller application using variational implicit surfaces. Users can create and manipulate shapes using sketches on a perspective or parallel view. The main operations are inflate, which creates 3D forms from a 2D stroke, merge, which creates a 3D shape from two blobs and oversketch, which allows users to redefine shapes using a single stroke to change their boundaries or to modify a surface by an implicit extrusion. We compare these techniques with those of other approaches published. Finally, we describe their implementation in BlobMaker. We have provided additional features such as copying, picking and dragging to offer a natural user interface suitable for free-form modelling.
A Fault Model Framework for Quality Assurance

This Ph.D thesis proposes a testing methodology based on fault models with an encompassing fault model lifecycle framework. Fault models have superior fault detection ability w.r. t. Random testing by capturing what "usually goes wrong". Turning them operational yields the (semi-)automatic generation of test cases directly targeting the captured faults/failures. Each operationalization requires an initial effort for fault/failure description and creation of a test case generator, which is possibly domain-/test level-/application-specific. To allow planning and controlling this effort in practice, a fault model lifecycle frame-work is proposed capturing the testing methodology. It allows tailoring itself to processes used in organizations and integration into existing quality assurance activities. The contribution of this Ph.D thesis is testing methodology based on fault models to generate test cases and a lifecycle framework for its real-world application in organizations.
Fusion in the Context of Information Theory

ion of the flow of information in the system. In a distributed network of sensors, the sensing system may be comprised of multiple sensors that are physically disjoint or distributed in time or space, and that work cooperatively. Compared to a single sensor platform, a network has the advantages of diversity (different sensors offer complementary 3.9. FUSION IN THE CONTEXT OF INFORMATION THEORY 5 viewpoints), and redundancy (reliability and increased resolution of the measured quantity) [24]. In fact, it has been rigorously established from the theory of distributed detection that higher reliability and lower probability of detection error can be achieved when observation data from multiple, distributed sources is intelligently fused in a decision making algorithm, rather than using a single observation data set [44]. Intuitively, any practical sensing device has limitations on its sensing capabilities (e.g. resolution, bandwidth, efficiency, etc.). Thus, descriptions built on the data sensed by a single device are only approximations of the true state of nature. Such approximations are often made worse by incomplete knowledge and understanding of the environment that is being sensed and its interaction with the sensor. These uncertainties, coupled with the practical reality of occasional sensor failure greatly compromises reliability and reduces confidence in sensor measurements. Also, the spatial and physical limitations of sensor devices often means that only partial information can be provided by a single sensor. A network of sensors overcomes many of the shortcomings of a single sensor. However new problems in efficient information management arise. These may be categorized into two broad areas [30]: 1. Data Fusion: This is the problem of combining diverse and sometimes conflicting information provided by sensors in a multi-sensor system, in a consistent and coherent manner. The objective is to infer the relevant states of the system that is being observed or activity being performed. 2. Resource Administration: This relates to the task of optimally configuring, coordinating and utilizing the available sensor resources, often in a dynamic, adaptive environment. The objective is to ensure efficient use of the sensor platform for the task at hand. In comparison to lumped-parameter sensor systems (Figure 3.9.1), the issues mentioned Efficiency, in this context, is very general and can refer to power, bandwidth, overhead, throughput, or a variety of other performance metrics, depending upon the particular application. 6 CHAPTER 3. INFORMATION FUSION above for multi-sensor systems can be diagrammed as shown in Figure 3.9. 2 [24].
PTEN interacts with the transcription machinery on chromatin and regulates RNA polymerase II-mediated transcription

Abstract Regulation of RNA polymerase II (RNAPII)-mediated transcription controls cellular phenotypes such as cancer. Phosphatase and tensin homologue deleted on chromosome ten (PTEN), one of the most commonly altered tumor suppressors in cancer, affects transcription via its role in antagonizing the PI3K/AKT signaling pathway. Using co-immunoprecipitations and proximal ligation assays we provide evidence that PTEN interacts with AFF4, RNAPII, CDK9, cyclin T1, XPB and CDK7. Using ChIP-seq, we show that PTEN co-localizes with RNAPII and binds to chromatin in promoter and putative enhancer regions identified by histone modifications. Furthermore, we show that loss of PTEN affects RNAPII occupancy in gene bodies and further correlates with gene expression changes. Interestingly, PTEN binds to promoters and negatively regulates the expression of genes involved in transcription including AFF4 and POL2RA, which encodes a subunit of RNAPII. Loss of PTEN also increased cells’ sensitivity to transcription inhibition via small molecules, which could provide a strategy to target PTEN-deficient cancers. Overall, our work describes a previously unappreciated role of nuclear PTEN, which by interacting with the transcription machinery in the context of chromatin exerts an additional layer of regulatory control on RNAPII-mediated transcription.
Wearable computing for patients with coronary diseases

Cardiovascular diseases are killing more and more people around the world, striking rich and poor alike. The World Health Organization identifies these diseases as challenges to population health and well being and calls it a global epidemic. These diseases can seriously affect the life of both the patient and family. In tandem with a strategy to provide information and education to individuals at risk, Information and Communication Technologies can be a valuable tool to address the challenges posed by this global epidemic. The HEARTRONIC project is developing an innovative system for prevention and early warning by continuous monitoring the heart conditions. This system is wearable by the patient, monitors and analyzes the heart beat, and in the event of results that could predict a heart attack or stroke an alert message is sent to a server and them relayed to the responsible healthcare professional. The system uses EGC processing for automatic detection of abnormal functioning. First response actions are taken but the healthcare professionals are always in the control loop and can cancel or impose actions other than the ones decided by the system. System integration is starting and first trials are planned. Besides validating systems functionalities, these trials will allow to calibrate the sensitivity of the algorithms: high sensitivity may cause numerous false positives, while low sensitivity may result in misdiagnosis of potentially life threatening conditions.
Study of Query Expansion Techniques and Their Application in the Biomedical Information Retrieval

Information Retrieval focuses on finding documents whose content matches with a user query from a large document collection. As formulating well-designed queries is difficult for most users, it is necessary to use query expansion to retrieve relevant information. Query expansion techniques are widely applied for improving the efficiency of the textual information retrieval systems. These techniques help to overcome vocabulary mismatch issues by expanding the original query with additional relevant terms and reweighting the terms in the expanded query. In this paper, different text preprocessing and query expansion approaches are combined to improve the documents initially retrieved by a query in a scientific documental database. A corpus belonging to MEDLINE, called Cystic Fibrosis, is used as a knowledge source. Experimental results show that the proposed combinations of techniques greatly enhance the efficiency obtained by traditional queries.
Goal and action inference for helpful robots using self as simulator

New applications are bringing robots into environments where they will have the opportunity to cooperate with humans as capable partners. A crucial element of cooperation is the ability to infer actions and goals of another by observing them. The ability to understand the intention being enacted by another is very important for anticipating the needs of and providing timely assistance to them. This thesis presents an approach to building a robot that is capable of action and goal inference that is based on the concept of Simulation Theory (a dominant theory in philosophy for how people do this). Simulation Theory argues that we exploit our own psychological responses in order to simulate others' minds to infer their mental states. With respect to action recognition and goal inference this implies that the ability to perform an action helps one to recognize when the same action is performed by others. It further implies that a robot could leverage its own action/goal representation to infer goals of others based on their actions. This implementation addresses the task of acquiring perceptual data about the physical motion of another agent and the context in which is it performed and mapping it onto the robot's own perceptual and movement repertoire. This implementation then addresses how to achieve the simulation to recognize the actions and infer the goals of the observed agent based on this movement and perceptual data. I demonstrate this skill by having the robot exhibit behaviors that address the inferred goal being enacted by the human. In principle this approach could be extended to not only infer the intentions of others, but other mental states as well (motivations, emotions, desires, beliefs, etc.). The main contribution of this work is a plausible working model of simulation theory (informed by scientific studies of autism, imitation, and the development of theory of other minds) that is able to infer the intention behind observable action and its effects. This is an important step towards building robots that can begin to understand human behavior in terms of the mental states that generate it, rather than only upon observable surface behavior. This understanding is key for cooperating with robots instead of using them as tools. Thesis Supervisor: Cynthia Breazeal Title: Assistant Professor of Media Arts and Sciences
A Latent Topic Extracting Method based on Events in a Document and its Application

Recently, several latent topic analysis methods such as LSI, pLSI, and LDA have been widely used for text analysis. However, those methods basically assign topics to words, but do not account for the events in a document. With this background, in this paper, we propose a latent topic extracting method which assigns topics to events. We also show that our proposed method is useful to generate a document summary based on a latent topic.
Ear Pinna : a privileged DNA electroporation site for inducing strong Th1 immune responses

DNA vaccination appears a very attractive approach for inducing immune responses towards the encoded anti- gen, but studies in large animals and in humans revealed weaknesses of such responses. In this study, we evaluated a new approach based on a new device combining DNA vaccination with electroporation (EP) at the ear pinna site. Under opti- mal EP conditions, the expression of the DNA encoded antigen and the induced immune responses were considerably in- creased. Very interestingly, DNA vaccination using EP at the ear pinna induced much stronger cellular immune responses than at the flank skin although antigen expression was similar at both sites. As compared to vaccination at the ear pinna without EP, IFN-￻ but not IL-4 production by splenocytes from immunized mice was significantly enhanced. In contrast, IL-4 but not IFN-￻ production was increased by EP at the flank skin. The vaccination site of the ear pinna combined with EP route even provided therapeutic effects in a mouse tumor model. In conclusion, this study highlights the ear pinna as a privileged site for the induction of strong Th1 polarized cellular im- munity against a defined antigen when combining DNA vaccination with EP.
On the massive star content of the nearby dwarf irregular Wolf-Rayet galaxy IC 4662 ⋆

Aims. We investigate the massive stellar content of the nearby dwarf irregular Wolf-Rayet galaxy IC 4662, and consider its global star forming properties in the context of other metal-poor galaxies, namely the SMC, IC 10 and NGC 1569. Methods. Very Large Telescope/FORS2 imaging and spectroscopy plus archival Hubble Space Telescope/ACS imaging datasets permit us to spatially identify the location, number and probable subtypes of Wolf-Rayet stars within this galaxy. We also investigate suggestions that a significant fraction of the ionizing photons of the two giant H ii regions A1 and A2 lie deeply embedded within these regions. Results. Wolf-Rayet stars are associated with a number of sources within IC 4662-A1 and A2, plus a third compact H ii region to the north west of A1 (A1-NW). Several sources appear to be isolated, single (or binary) luminous nitrogen sequence WR stars, while extended sources are clusters whose masses exceed the Orion Nebula Cluster by, at most, a factor of two. IC 4662 lacks optically visible young massive, compact clusters that are common in other nearby dwarf irregular galaxies. A comparison between radio and Hα-derived ionizing fluxes of A1 and A2 suggests that 30–50% of their total Lyman continuum fluxes lie deeply embedded within these regions. Conclusions. The star formation surface density of IC 4662 is insufficient for this galaxy to qualify as a starburst galaxy, based upon its photometric radius, R25. If instead, we were to adopt the V-band scale length RD from Hunter & Elmegreen, IC 4662 would c) – – .