Miracle-dz/UniFAR-FTUs huggingface dataset:
Crosstalk: A Scalable Cross-Protocol Monitoring System for Anomaly Detection

Monitoring is crucial both to the correct operation of a network and to the services that run on it. Operators perform monitoring for various purposes, including traffic engineering, quality of service, security and detection of faults and mis-configurations. However, the relentless growth of IP traffic volume renders real-time monitoring and analysis of data a very challenging problem. In this paper we introduce Crosstalk, a scalable and efficient distributed monitoring architecture that uses cross-protocol correlation to detect network anomalies. While applicable to a wide range of applications such as botnet detection, spam mitigation and mis-configurations, we pick a point in this application space, concentrating on VoIP attacks. We present extensive simulation results based both on generated calls and on millions of Call Data Records (CDRs) from a large VoIP operator to show our approach's performance and effectiveness.
A Satisfactory-Oriented Approach to Multi-Evaluator Single-Layer Evaluation System with Linguistic Truth-Value

In this paper, a general satisfaction-based approach with linguistic truth-value to multi-evaluator single-layer evaluation system is presented. In this approach, user can give evaluation value for every criterion in natural language. And all evaluation value given by evaluator will be transformed to linguistic truth-value based on satisfaction. In the final aggregation process, different important coefficient which comes from both evaluation criteria and evaluators will be included in the final evaluation results.
Significant prognostic impact of improvement in ventriculo-arterial coupling induced by dobutamine stress on cardiovascular outcome for patients with dilated cardiomyopathy.

AIMS The purpose of this study was to investigate the prognostic impact of the changes in ventriculo-arterial (VA) coupling during dobutamine stress on the cardiovascular events for patients with dilated cardiomyopathy (DCM). METHODS AND RESULTS For this study, 89 DCM patients with ejection fractions of 32 ± 10% and 30 normal controls were recruited. Ees was estimated with the non-invasive single-beat method using three-dimensional echocardiography at rest and during dobutamine stress (20 μg/kg/min). Effective arterial elastance (Ea) was calculated as left ventricular (LV) end-systolic pressure divided by stroke volume, and VA coupling was calculated as Ea/Ees. Event-free survival was then tracked for 32 months. At baseline, VA coupling was far from optimal in patients with DCM compared with controls (Ea/Ees: 2.49 ± 1.02 vs. 1.04 ± 0.21, P < 0.001). During the follow-up period, 22 patients developed adverse cardiovascular events. During dobutamine stress, VA coupling was significantly improved in patients without cardiovascular events (from 2.47 ± 1.09 to 1.59 ± 0.68, P < 0.001), but remained unchanged in those with cardiovascular events. A multivariate Cox proportional-hazards analysis revealed that age, NYHA functional class (>II), and the change in VA coupling during dobutamine stress were the independent determinants of cardiovascular events (P < 0.05, <0.01, and <0.001, respectively). When patients were divided into two subgroups based on the finding of receiver operating characteristic curve analysis, patients with good VA coupling reserve (cut-off: change in VA coupling> 0.29) showed significantly favourable event-free survival than those with poor VA coupling reserve (P < 0.001). CONCLUSIONS Improvement in VA coupling during dobutamine stress is an important determinant of cardiovascular outcome for patients with DCM.
View-dependent control of elastic rod simulation for 3D character animation

This paper presents view-dependent control of elastic rod simulation for 3D character animation. Elastic rod simulation is often used in character animation to generate motion of passively deforming body parts such as hair, ear, and whiskers. Our goal is to allow artistic control of the simulation in a view-dependent way, for example to move a hair strand so that it does not hide the eye regardless of the view direction. To achieve this goal, the artist defines several example rest poses of the rod in preparation, each of which is associated with a particular view direction. In run time, the system computes the current rest pose by blending the example rest poses associated with the view directions near the current view direction, and then pulls the pose to the current rest pose. Technical contribution is in the formulation of example-based rod simulation using view direction as an input, and an algorithm to suppress undesirable increase of momentum caused by dynamically changing rest poses.
security 2011 ( CSS ’ 2011 ) Text-based CAPTCHA Strengths and Weaknesses

We carry out a systematic study of existing visual CAPTCHAs based on distorted characters that are augmented with anti-segmentation techniques. Applying a systematic evaluation methodology to 15 current CAPTCHA schemes from popular web sites , we find that 13 are vulnerable to automated attacks. Based on this evaluation, we identify a series of recommendations for CAPTCHA designers and attackers, and possible future directions for producing more reliable human/computer distinguishers.
Providing Useful Information for Passengers Based on TTF Model

Taxis are an important part of public transportation in nowadays. Taking a vacant taxi has become a difficult problem due to the imbalance between demand and supply of taxi service. People want to know where is better to wait for a vacant taxi in order to save their time in the fast-paced city life. Helpful information could be provided to the passengers by mining the historical GPS traces generated by taxis. In this paper, we propose a model based on taxi traffic flow (TTF) model to measure the difficulty of taking a vacant taxi on the road segments nearby. Furthermore, we calculate probability and expected waiting time of taking a vacant taxi based on TTF model. Afterwards, we detect the hotspots on the road segments expecting to offer more available information. Our research is based on the real historical taxi GPS data generated by 12000 taxis in Beijing. We conduct experiments to validate our model eventually and the experimental results are in line with the actual situation well relatively.
Large-Scale Image Retrieval Using Local Binary Patterns and Iterative Quantization

Hashing algorithm is an efficient approximate searching algorithm for large-scale image retrieval. Learning binary code is a key step to improve its performance and it is still an ongoing challenge. The inputs of Hashing affects its performance. This paper proposes a method to improve the efficiency of learning binary code by improving the suitableness of the Hashing algorithms inputs by employing local binary patterns in extracting image features. This approach results in more compact code, less memory and computational requirement and higher performance. The reasons behind these achievements are the binary nature and high efficiency in feature generation of local binary pattern. The performance analysis consists of using CIFAR-10 and precision vs. recall rate as dataset and evaluation criteria respectively. The simulations compare the new algorithm with three state of the art and along the line algorithms from three points of view; the hashing code size, memory space and computational cost, and the results demonstrate the effectiveness of the new approach.
Identification and characterisation of regionally enriched cortex genes in the rat brain

2012 2 If the human brain were so simple that we could understand it, we would be so simple that we couldn't. Acknowledgements Many colleagues have contributed to the fulfilment of this thesis, and I thank you all. First and foremost, I would like to express my sincere gratitude to my supervisor Prof. Vidar M. Steen. Thank you for including me in your group, for sharing your profound knowledge of the field and for giving me freedom to explore different aspects of the project. And most of all, thank you for your never-ending enthusiasm and encouragement! I am also very grateful to my co-supervisors Dr. Le Hellard and Dr. Bjarte Håvik. Christine-you made the foundation that this thesis is based upon, and none of this work would have been possible without you. Thank you for including me in the project and for your invaluable input on manuscripts and this thesis. Stephanie-I thank you for introducing me to the world of genetics and for sharing your expertise with me. I am very thankful for your endless patience and support. I am also indebted to Bjarte, who through his laboratory know-how, great ideas and invaluable discussions strongly contributed to the success of this work. I would like to thank all the co-authors for their contributions to the papers included in this work. In addition, a special thanks to Dr. Jean M. Hebert at the Albert Einstein College of Medicine for welcoming me in his group, and Dr. Marie Fernandes for teaching me their methods. I also thank Dr. Jonathan Soule for his technical input and valuable discussions. I am so happy to be a part of the Martens group, and I thank both present and former members for making it fun to go to work every day! I especially thank Dr. Silje Skrede, Dr. soon-to-be Teresa Osland and Dr. to-be Carla Fernandes Neto for our shared joys (and minor depressions) during this joint PhD run. Also, a special thanks to Dr. Andrea Christoforou for all the invaluable help and guidance through the jungle of SNPs and P-values! I also thank Marianne Naevdal for your excellent technical assistance. And to all my co-workers at MGM-thank you for creating a 5 great working environment! I am also thankful for the technical and infrastructure support provided by the Center for Medical Genetics and Molecular Medicine. Bergithe, I am so grateful for the friendship we share. …
Decentralized view prediction for global content placement

A large portion of today's Internet traffic originates from streaming and video services. Storing, indexing, and serving these videos is a daily engineering challenge that requires increasing amounts of efforts and infrastructures. One promising direction to improve video services consists in predicting at upload time where and when a new video might be viewed, thereby optimizing placement and caching decisions. Implementing such a prediction service in a scalable manner poses significant technical challenges. In this paper, we address these challenges in the context of a decentralized storage system consisting of set-top boxes or end nodes. Specifically, we propose a novel data placement algorithm that exploits information about the tags associated with existing content, such as videos, and uses it to infer the number of views that newly uploaded content will have in each country.
Attribute Grammar-Based Event Recognition and Anomaly Detection

We propose to use attribute grammars for recognizing normal events and detecting abnormal events in a video. Attribute grammars can describe constraints on features (attributes) in addition to the syntactic structure of the input. Events are recognized using an extension of the Earley parser that handles attributes and concurrent event threads. Abnormal events are detected when the input does not follow syntax of the grammar or the attributes do not satisfy the constraints in the attribute grammar to some degree. We demonstrate the effectiveness of our method for the task of recognizing normal events and detecting anomalies in a parking lot.
Toward seamless human-robot handovers

A handover is a complex collaboration, where actors coordinate in time and space to transfer control of an object. This coordination comprises two processes: the physical process of moving to get close enough to transfer the object, and the cognitive process of exchanging information to guide the transfer. Despite this complexity, we humans are capable of performing handovers seamlessly in a wide variety of situations, even when unexpected. This suggests a common procedure that guides all handover interactions. Our goal is to codify that procedure. To that end, we first study how people hand over objects to each other in order to understand their coordination process and the signals and cues that they use and observe with their partners. Based on these studies, we propose a coordination structure for human-robot handovers that considers the physical and social-cognitive aspects of the interaction separately. This handover structure describes how people approach, reach out their hands, and transfer objects while simultaneously coordinating the what, when, and where of handovers: to agree that the handover will happen (and with what object), to establish the timing of the handover, and to decide the configuration at which the handover will occur. We experimentally evaluate human-robot handover behaviors that exploit this structure and offer design implications for seamless human-robot handover interactions.
A VS-IMM algorithm for maneuvering target tracking

Tracking of highly maneuvering targets with unknown behavior is a difficult problem in state estimation. This paper presents an adaptive interacting multiple model algorithm (IMM) utilizing adaptive turn rate models to track a maneuvering target. The turn rate is calculated at each step form the estimator of velocity and the radius of curvature of the trajectory of the target by using Least Square (LS) and curve fitting theory. Simulation in different scenario proves that the turn-rate estimation techniques in this adaptive framework can significantly solve the problem of tracking maneuvering targets.
Toward Self-Manageable and Adaptive Industrial Cyber-Physical Systems With Knowledge-Driven Autonomic Service Management

An increasingly important goal of industrial automation systems is to continuously optimize physical resource utilization such as materials. Distributed automation is seen as one enabling technology for achieving this goal, in which networking controller nodes collaborate in a peer-to-peer way to form a new paradigm, namely industrial cyber-physical systems (iCPS). In order to achieve rapid response to changes from both high-level control systems and plant environment, the proposed self-manageable agent relies on the use of the service-oriented architecture (SOA) that improves flexibility and interoperability. It is enhanced by the autonomic service management (ASM) to implement software modifications in a fully automatic manner, thus achieving self-manageable and adaptive iCPS. The architecture design of the ASM is provided and integration with SOA-based execution environment is illustrated. Preliminary tests on self-management are completed using a case study of an airport baggage handling system.
A survey of covert channels and countermeasures in computer network protocols

Covert channels are used for the secret transfer of information. Encryption only protects communication from being decoded by unauthorised parties, whereas covert channels aim to hide the very existence of the communication. Initially, covert channels were identified as a security threat on monolithic systems i.e. mainframes. More recently focus has shifted towards covert channels in computer network protocols. The huge amount of data and vast number of different protocols in the Internet seems ideal as a high-bandwidth vehicle for covert communication. This article is a survey of the existing techniques for creating covert channels in widely deployed network and application protocols. We also give an overview of common methods for their detection, elimination, and capacity limitation, required to improve security in future computer networks.
How DOCSIS Protocol Solves Asymmetric Bandwidth Issue in Cable Network

Since the high bandwidth and popular usage are the characteristics of cable network, it becomes one of the main solutions for residential network. The cable network is a kind of asymmetric bandwidth architecture, which generates certain performance issues. This article first discusses the issues stemmed from asymmetric bandwidth. It then briefly introduces Data over Cable Service Interface Specifications (DOCSIS) protocol, the most popular standard for cable network today. The rest of the article discusses the operations and mechanisms in DOCSIS protocol that solve those performance issues and other possible improvements in cable network.
State-of-the-Art: DTM Generation Using Airborne LIDAR Data

Digital terrain model (DTM) generation is the fundamental application of airborne Lidar data. In past decades, a large body of studies has been conducted to present and experiment a variety of DTM generation methods. Although great progress has been made, DTM generation, especially DTM generation in specific terrain situations, remains challenging. This research introduces the general principles of DTM generation and reviews diverse mainstream DTM generation methods. In accordance with the filtering strategy, these methods are classified into six categories: surface-based adjustment; morphology-based filtering, triangulated irregular network (TIN)-based refinement, segmentation and classification, statistical analysis and multi-scale comparison. Typical methods for each category are briefly introduced and the merits and limitations of each category are discussed accordingly. Despite different categories of filtering strategies, these DTM generation methods present similar difficulties when implemented in sharply changing terrain, areas with dense non-ground features and complicated landscapes. This paper suggests that the fusion of multi-sources and integration of different methods can be effective ways for improving the performance of DTM generation.
What are Dynamic Capabilities and are They a Useful Construct in Strategic Management?

The dynamic capability perspective extends the resource-based view argument by addressing how valuable, rare, difficult to imitate and imperfectly substitutable resources can be created and how the current stock of valuable resources can be refreshed in changing environments. The concept of dynamic capabilities emerged in the 1990s, and the field has advanced considerably since. This paper presents a review as well as a synthesis of the extant literature. This synthesis first highlights, that dynamic capabilities are shaped by enabling and inhibiting variables within and outside the firm, including the perceptions and motivations of managers; secondly, it identifies processes that create dynamic capabilities; and thirdly, it explains that dynamic capabilities do not automatically lead to performance improvements. Finally, the paper addresses some areas of confusion and contradiction that hamper the development of the literature.
Cloud Password Manager Using Privacy-Preserved Biometrics

Using one password for all web services is not secure because the leakage of the password compromises all the web services accounts, while using independent passwords for different web services is inconvenient for the identity claimant to memorize. A password manager is used to address this security-convenience dilemma by storing and retrieving multiple existing passwords using one master password. On the other hand, a password manager liberates human brain by enabling people to generate strong passwords without worry about memorizing them. While a password manager provides a convenient and secure way to managing multiple passwords, it centralizes the passwords storage and shifts the risk of passwords leakage from distributed service providers to a software or token authenticated by a single master password. Concerned about this one master password based security, biometrics could be used as a second factor for authentication by verifying the ownership of the master password. However, biometrics based authentication is more privacy concerned than a non-biometric password manager. In this paper we propose a cloud password manager scheme exploiting privacy enhanced biometrics, which achieves both security and convenience in a privacy-enhanced way. The proposed password manager scheme relies on a cloud service to synchronize all local password manager clients in an encrypted form, which is efficient to deploy the updates and secure against untrusted cloud service providers.
Projected inverse dynamics control and optimal control for robots in contact with the environment: A comparison

This paper addresses the problem of constrained motion for a manipulator performing a task while in contact with the environment, and investigates two force control frameworks, one based on projected inverse dynamics, and one based on optimal control. Firstly, we propose a control method based on projected inverse dynamics, which directly exploits the contact constraints to minimise the instantaneous joint torques needed to perform a task. Secondly, we propose an optimal control strategy which provides a tool to minimise the joint torques over an interval of time. We show how contact constraints can be used as optimisation constraints in the definition of the problem, and how to formulate the optimal control problem directly using projected dynamics. Initially we explore a positional control problem, where the robot is required to follow a desired path, and show that both of the proposed methods can satisfy the positional task while significantly reducing the joint torques as compared to simple kinematic control and also classical inverse dynamics control. We also show that the proposed optimal control method outperforms the pure projected inverse dynamics method in terms of minimising the required joint torques. We then show how each method can be extended to follow a desired path while also exerting a desired contact force. Again, the method incorporating optimal control is shown to satisfy the task requirements with significantly smaller commanded torques than the pure projected inverse dynamics method. To confirm the analysis, and demonstrate proof of concept, we present the results of empirical experiments with a simulated 3-degree-of-freedom planar manipulator which is constrained to move while in contact with a rigid surface.
慢性腰痛の新たな治療戦略 — Cognitive Functional Therapy の紹介—

Low back pain is a significant problem in the world and in Japan. It is understood that about 70% of non-specific low back pain improves in 4-6 weeks, but the remaining 30% becomes chronic. It is widely known that psychosocial factors, in addi-tion to structural and functional problems, are responsible for the chronicity and delayed improvement of non-specific low back pain. Therefore, it is necessary to consider non-specific low back pain based on a biopsychosocial model. In addition, the concepts of classification and stratified care have been developed to identify the direction of specific interventions by grouping low back pain according to its characteristics, rather than considering it as a single condition. Physical therapy management for non-specific low back pain based on the biopsychosocial model requires different strategies depending on the duration of the disease, and more multifaceted strategies are needed in the chronic phase. In recent years, a new intervention called Cognitive Functional Therapy, which is a multifaceted intervention method consisting of the three components of “Making Sense of Pain,” “Exposure with Control,” and “Lifestyle Change,” has been proposed. Since 80% of low back pain is non-specific that does not require surgery, the evolution of physical therapy will help to decrease the number of low back pain patients.
Individualized service selection with ontologies and rules

An extension of the HTN-DL web service model is presented, including rules for web service behavior and compliance validation against customer requests. The intention is to overcome the limitations of HTN-DL and OWL-S in covering business constraints in service selection and also the limitation of preconditions. The proposed approach validates a web service obtained through HTN-DL planning, for compliance to customer constraints. A proof of concept implementation shows the workings of our conceptualization.