ppxscal/embedding_network huggingface dataset:
Modeling and parameter estimation of spacecraft fuel slosh mode
Authors: Keith Schlee, Sathya Gangadharan, James Ristow, Carl Hubert, James Sudermann, Charles Walker
Venue: Proceedings of the 37th conference on Winter simulation (2005)

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. Its rate of growth is characterized by the Nutation Time Constant (NTC). For analytical prediction of the NTC this fuel slosh is often modeled using simple mechanical analogs such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The current research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics based computer simulation of the experimental setup.
A case study on the application of UML in legacy development
Authors: Bente Anda, Kai Hansen
Venue: Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering (2006)

Model-driven development with UML is becoming a de facto standard in industry, but although much of today's software development is about enhancing existing systems, there is no welldefined process for model-driven development in the context of legacy systems. To ensure the relevance of research on modeldriven development with UML, there is a need for studies of actual use of UML in software development companies. As part of a software process initiative, we conducted a case study in a large development project where some of the development teams enhanced existing components, while other teams developed software from scratch. The results from this case study showed that those who applied UML in modelling and enhancing legacy software experienced more challenges and fewer benefits from the use of UML than did the developers who modelled and developed new software. Overall our results show a need for better methodological support on applying UML in legacy development.
k-Approximating Circuits
Authors: Marco Cadoli Francesco M. Donini Paolo Liberatore Marco Schaerf
Venue: IEEE Transactions on Computers (2006)

In this paper, we define and study the k-approximating circuits. A circuit accepting a given set of inputs A is k-approximated by accepting inputs that differ from one of A by at most k bits. We show that the existence of polynomial-size k-approximating circuits depends on the relation between k and the number of inputs.
Dynamics Based Robust Motion Segmentation
Authors: Roberto Lublinerman, Mario Sznaier, Octavia Camps
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In this paper we consider the problem of segmenting multiple rigid motions using multi-frame point correspondence data. The main idea of the method is to group points according to the complexity of the model required to explain their relative motion. Intuitively, this formalizes the idea that points on the same rigid share more modes of motion (for instance a common translation or rotation) than points on different objects, leading to less complex models. By exploiting results from systems theory, the problem of estimating the complexity of the underlying model is reduced to simply computing the rank of a matrix constructed from the correspondence data. This leads to a simple segmentation algorithm, computationally no more expensive than a sequence of SVDs. Since the proposed method exploits both spatial and temporal constraints, is less sensitive to the effect of noise or outliers than approaches that rely solely on factorizations of the measurements matrix. In addition, the method can also naturally handle "degenerate cases", e.g. cases where the objects partially share motion modes. These results are illustrated using several examples involving both degenerate and non-degenerate cases.
It's the End of the Tube as We Know It
Authors: Michael Macedonia
Venue: Computer (2006)

The CRT king is dead; long live the LCD king.
A Tangible Interface for Hands-on Learning
Authors: Satoshi Yonemoto, Takahiro Yotsumoto, Rin-ichiro Taniguchi
Venue: Proceedings of the conference on Information Visualization (2006)

In this paper, we describe a tangible interface for Hands-on Learning using physical-tangible objects ( pattern blocks). A computer recognizes the states of the user-handled objects in real time and it gives the users advice to execute learning tasks if necessary. In our approach, a pattern block is employed as a primitive piece. It helps the users to do direct manipulation in real environments, while displayed events in virtual environments help them to support the learning tasks. Concretely, we have developed the interaction system can support Hands-on Math activities.
Schedulability Analysis of Petri Nets Based on Structural Properties
Authors: Cong Liu, Alex Kondratyev, Yosinori Watanabe, Alberto Sangiovanni-Vincentelli, Jorg Desel
Venue: Proceedings of the Sixth International Conference on Application of Concurrency to System Design (2006)

A schedule of a Petri Net (PN) represents a set of firing sequences that can be infinitely repeated within a bounded state space, regardless of the outcomes of the nondeterministic choices. Schedulability analysis for a given PN answers the question whether a schedule exists in the reachability space of this net. This paper suggests a novel approach for schedulability analysis based solely on PN structure. It shows that unschedulability can be caused by a structural relation among transitions modelling nondeterministic choices. A method based on linear programming for checking this relation is proposed. This paper also presents a necessary condition for schedulability based on the rank of the incidence matrix of the underlying PN. These results shed a light on the sources of unschedulability often found in PN models of embedded multimedia systems.
Balance-Based Energy-Efficient Communication Protocols forWireless Sensor Networks
Authors: Yu Wang, Hongyi Wu, Ravi Nelavelli, Nian-Feng Tzeng
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

Energy efficiency is a critical design issue in wireless sensor networks, where each sensor node relies on its limited battery power for data acquisition, processing, transmission, and reception. In this paper, we propose several energy-efficient communication schemes based on power control and load balancing, aiming at even distribution of the residual energy of the sensors and thus prolonging the lifetime of overall wireless sensor networks. More specifically, an Integer Linear Programming (ILP) algorithm and a Distributed Energy Efficient Routing (DEER) protocol are proposed for time-driven sensor networks. A Residual Energy-based Traffic Splitting (RETS) protocol is introduced for event-driven sensor networks. We have carried out extensive simulations to evaluate the proposed protocols. Our simulation results show that most heuristic approaches yield network lifetimes far smaller than the upper bound obtained from the ILP algorithm. The proposed DEER and RETS approaches can effectively distribute energy consumption evenly among the sensor nodes to prolong the network lifetime by up to 200% or more, when compared with other approaches in the literature.
Combination Artificial Ant Clustering and K-PSO Clustering Approach to Network Security Model
Authors: Surat Srinoy, Werasak Kurutach
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

A Computer system now operate in an environment of near ubiquitous connectivity, whether tethered to an Ethernet cable or connected via wireless technology. While the availability of always on communication has created countless new opportunities for web based businesses, information sharing, and coordination, it has also created new opportunities for those that seek to illegally disrupt, subvert, or attack these activities. We present natural based data mining algorithm approach to data clustering. Artificial ant clustering algorithm is used to initially create raw clusters and then these clusters are refined using k-mean particle swarm optimization (KPSO). KPSO that has been developed as evolutionary-based clustering technique. The algorithm uses hybridization the k-means algorithm and PSO principle to find good partitions of the data. Certain unnecessary complications of the original algorithm are discussed and means of overcoming these complexities are proposed. We propose k-means particle swarm optimization clustering algorithm in the second stage for refinement mean of overcoming these complexities is proposed. Our approach allows us to recognize not only known attacks but also to detect suspicious activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining-(KDDCup 1999.
A tunable hybrid memory allocator
Authors: Yusuf Hasan, J. Morris Chang
Venue: Journal of Systems and Software (2006)

Dynamic memory management can make up to 60% of total program execution time. Object oriented languages such as C++ can use 20 times more memory than procedural languages like C. Bad memory management causes severe waste of memory, several times that actually needed, in programs. It can also cause degradation in performance. Many widely used allocators waste memory and/or CPU time. Since computer memory is an expensive and limited resource its efficient utilization is necessary. There cannot exist a memory allocator that will deliver best performance and least memory consumption for all programs and therefore easily tunable allocators are required. General purpose allocators that come with operating systems give less than optimal performance or memory consumption. An allocator with a few tunable parameters can be tailored to a program's needs for optimal performance and memory consumption. Our tunable hybrid allocator design shows 11-54% better performance and nearly equal memory consumption when compared to the well known Doug Lea allocator in seven benchmark programs.
Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers
Authors: Jamie A. Ward, Paul Lukowicz, Gerhard Troster, Thad E. Starner
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

In order to provide relevant information to mobile users, such as workers engaging in the manual tasks of maintenance and assembly, a wearable computer requires information about the user's specific activities. This work focuses on the recognition of activities that are characterized by a hand motion and an accompanying sound. Suitable activities can be found in assembly and maintenance work. Here, we provide an initial exploration into the problem domain of continuous activity recognition using on-body sensing. We use a mock "wood workshop” assembly task to ground our investigation. We describe a method for the continuous recognition of activities (sawing, hammering, filing, drilling, grinding, sanding, opening a drawer, tightening a vise, and turning a screwdriver) using microphones and three-axis accelerometers mounted at two positions on the user's arms. Potentially "interesting” activities are segmented from continuous streams of data using an analysis of the sound intensity detected at the two different locations. Activity classification is then performed on these detected segments using linear discriminant analysis (LDA) on the sound channel and hidden Markov models (HMMs) on the acceleration data. Four different methods at classifier fusion are compared for improving these classifications. Using user-dependent training, we obtain continuous average recall and precision rates (for positive activities) of 78 percent and 74 percent, respectively. Using user-independent training (leave-one-out across five users), we obtain recall rates of 66 percent and precision rates of 63 percent. In isolation, these activities were recognized with accuracies of 98 percent, 87 percent, and 95 percent for the user-dependent, user-independent, and user-adapted cases, respectively.
Performance evaluation of a streaming based protocol for 3D virtual environment exploration on mobile devices
Authors: Azzedine Boukerche, Richard Werner Nelem Pazzi
Venue: Proceedings of the 9th ACM international symposium on Modeling analysis and simulation of wireless and mobile systems (2006)

With the recent advances of mobile computing devices with communication capabilities, virtual environment walkthrough and real-time streaming movie playback for mobile devices has opened a new class of 3D virtual environment exploration based applications such as virtual guides and malls, online gaming, training and monitoring, just to name a few. The challenge lies in how to provide a rich and detailed 3D virtual environment on thin mobile devices that are known for their lack of proper resources to process large scale 3D geometric data. In this paper, we focus on defining a new approach to remote rendering and interactive visualization of 3D virtual environments on thin mobile devices such as PDAs and cell phones. To this end, we propose efficient end-to-end streaming and rate control protocols to support the requirements of bandwidth-demanding multimedia systems. The main purpose of our proposed rate control scheme is to achieve both high end-to-end throughput and low frame rate ºuctuation in order to adapt data traffic to the frequent changes of the bandwidth and error rate, mainly due to the nature of wireless networks. We discuss the design of our proposed streaming and rate control algorithms, and report on the their performance evaluation using an extensive set of simulation experiments.
Utilizing node's selfishness for providing complete anonymity in peer-to-peer based grids
Authors: Rohit Gupta, Souvik Ray, Arun K. Somani, Zhao Zhang
Venue: Multiagent and Grid Systems (2006)

In this paper, a novel protocol for providing both client and server anonymity in peer-to-peer (P2P) based grids is presented. The protocol assumes individual nodes or users to be utility maximizing agents, and relies on an auction mechanism for trading of resources among them. The resources here can refer to data files, storage capacity, or computation power (i.e., CPU cycles) etc. The protocol is inherently anonymous, light-weight, and incentive-compatible. Incentive compatibility implies that the protocol takes into account the selfishness of users; as would be seen the utilities of users are maximized by truthfully following the protocol steps. Moreover, if the protocol is truthfully followed by the users, anonymity to both the clients and servers of all the transactions are guaranteed. Furthermore, unlike other schemes, the proposed protocol does not rely on any trusted centralized entity or require specialized encryptions to be performed by the users. Thus, the protocol incurs very low overhead on the system and is light-weight. In brief, the proposed protocol provides efficient and natural means to provide anonymity in P2P based grids, and is easily deployable in a large un-trusted Internet-scale setting.
A Powerful Approach for Effective Finding of Significantly Differentially Expressed Genes
Authors: Osman Abul, Reda Alhajj, Faruk Polat
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2006)

The problem of identifying significantly differentially expressed genes for replicated microarray experiments is accepted as significant and has been tackled by several researchers. Patterns from Gene Expression (PaGE) and q-values are two of the well-known approaches developed to handle this problem. This paper proposes a powerful approach to handle this problem. We first propose a method for estimating the prior probabilities used in the first version of the PaGE algorithm. This way, the problem definition of PaGE stays intact and we just estimate the needed prior probabilities. Our estimation method is similar to Storey's estimator without being its direct extension. Then, we modify the problem formulation to find significantly differentially expressed genes and present an efficient method for finding them. This formulation increases the power by directly incorporating Storey's estimator. We report the preliminary results on the BRCA data set to demonstrate the applicability and effectiveness of our approach.
WhoPay: A Scalable and Anonymous Payment System for Peer-to-Peer Environments
Authors: Kai Wei, Alan J. Smith, Yih-Farn Robin Chen, Binh Vo
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

An electronic payment system ideally should provide security, anonymity, fairness, transferability and scalability. Existing payment schemes often lack either anonymity or scalability. In this paper we propose WhoPay, a peer-topeer payment system that provides all the above properties. For anonymity, we represent coins with public keys; for scalability, we distribute coin transfer load across all peers, rather than rely on a central entity such as the broker. This basic version of WhoPay is as secure and scalable as existing peer-to-peer payment schemes, while providing a much higher level of user anonymity. We also introduce the idea of real-time double spending detection by making use of distributed hash tables (DHT). Simulation results show that the majority of the system load is handled by the peers under typical peer availability, indicating that WhoPay should scale well.
Color Image Segmentation that Preserves Boundary by using Mean Shift Algorithm and Region Merging Method
Authors: Nae-Joung Kwak, Dong-Jin Kwon, Young-Gil Kim, Jae-Hyeong Ahn
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

Mean shift algorithm is a nonparametric statistical method for seeking the main modes of a point sample distribution. This process achieves a high quality, discontinuity preserving spatial filtering. For the segmentation task, the convergence points sufficiently close in the joint domain are fused to obtain the homogeneous regions in the image. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for oversegmented images. The proposed method converts an over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the proposed method use by region merging constraints to decide whether regions is merged or not. After then, we merge the regions in RGB color space for nonprocessed regions in HSI color space. Experimental results show the proposed method is superior to conventional methods in region's segmentation results.
3D Human Motion Analysis in Monocular Video Techniques and Challenges
Authors: Cristian Sminchisescu
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

Human motion and action analysis in video is an actively growing field with a broad spectrum of applications including video browsing and indexing, entertainment, virtual reality, human-computer interaction and surveillance. However, human motion analysis systems face important scientific and computational challenges. The proportions of the human body vary across individuals due to gender, weight, age or race. Aside from this variability, any single human body has many degrees of freedom due to articulation and the individual limbs are deformable due to muscle and clothing. Finally many realworld scenes involve multiple interacting humans occluded by each other or by other objects, and the scene conditions may also vary due to the camera motion or lighting changes. These factors make accurate 3D human models difficult to build and difficult to reconstruct reliably from 'flat' 2D images. During this talk I will discuss learning and inference algorithms for estimating 3D human motion in monocular video. While the problem has been traditionally approached using the powerful machinery of generative models, operating in an analysis by synthesis loop, the main emphasis of this talk will be on an emerging class of complementary discriminative temporal estimation models. These can be viewed as upside down, bottom-up versions of classical temporal models used with Kalman filtering or particle filtering. But instead of inverting a generative imaging model, we will learn to cooperatively predict complex, feedforward 2D-to-3D mappings, using Conditional Bayesian Mixtures of Experts. These are embedded in a probabilistic temporal framework in order to enforce dynamic constraints and allow a principled propagation of uncertainty. We call the resulting model BM3E (a Conditional Bayesian Mixture of Experts Markov Model). During the talk, I will discuss how inference can be restricted, for efficiency, to low-dimensional non-linear state spaces, and how the framework can be extended in order to deal with clutter and occlusion. I will also discuss the relative advantages of generative and initialize and recover from failure.
A Query-Based Medical Information Summarization System Using Ontology Knowledge
Authors: Ping Chen, Rakesh Verma
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

As huge amounts of knowledge are created rapidly, effective information access becomes an important issue. Especially for critical domains, such as medical and financial areas, efficient retrieval of concise and relevant information is highly desired. In this paper we propose a new user query based text summarization technique that makes use of Unified Medical Language System, an ontology knowledge source from National Library of Medicine. We compare our method with keyword-only approach, and our ontologybased method performs clearly better. Our method also shows potential to be used in other information retrieval areas.
An approach to detection ontology changes
Authors: Michal Tury, Mária Bieliková
Venue: Workshop proceedings of the sixth international conference on Web engineering (2006)

Ontologies change and evolve both on the level of schema and individuals in order to meet requirements of changing world. Changes involve adding, deleting and modifying elements in the ontology both on structural (schema related) and content (individuals related) levels. The changes can lead to incorrect conclusions and can cause malfunction of systems, which use ontology data. In this paper we describe a proposal of the method for automated detection of currentness of presented data, including meta-data, which are represented by an ontology. Method comes out from a detection of changes between different versions of the ontology. Besides identifying modifications in the ontology, the purpose of the method lies also in identifying equivalent elements, thanks to which we are able to track information sources over time. We describe possibilities of automated identification of changes between ontologies using heuristic methods and their realization as a software tool called OntoDiff for comparing ontologies.