ppxscal/embedding_network huggingface dataset:
Landmark-Based Pedestrian Navigation with Enhanced Spatial Reasoning
Authors: Harlan Hile, Radek Grzeszczuk, Alan Liu, Ramakrishna Vedantham, Jana Košecka, Gaetano Borriello
Venue: Proceedings of the 7th International Conference on Pervasive Computing (2009)

Computer vision techniques can enhance landmark-based navigation by better utilizing online photo collections. We use spatial reasoning to compute camera poses, which are then registered to the world using GPS information extracted from the image tags. Computed camera pose is used to augment the images with navigational arrows that fit the environment. We develop a system to use high-level reasoning to influence the selection of landmarks along a navigation path, and lower-level reasoning to select appropriate images of those landmarks. We also utilize an image matching pipeline based on robust local descriptors to give users of the system the ability to capture an image and receive navigational instructions overlaid on their current context. These enhancements to our previous navigation system produce a more natural navigation plan and more understandable images in a fully automatic way.
Visual interaction design for tools to think with: interactive systems for designing linear information
Authors: Yasuhiro Yamamoto, Kumiyo Nakakoji, Atsushi Aoki
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

We have developed a series of tools, which use spatial positioning of objects as a means of externalizations in designing linear information. They include a tool for collage-style writing, a tool for notes summarization, a tool for multimedia data analysis, and a tool for movie editing. With these tools, linear information design is viewed as a concurrent process of framing parts and determining the order of the parts. In designing these tools, visual interaction design has been a center of our project. Our design priority has been put in minimizing the user's cognitive load in creating and modifying parts in a space, and manipulating them in the space. This paper first presents a brief philosophy underneath the system development, and describes interaction techniques used in the tools, such as how a user distinguishes objects positioned in the space, how a user resizes the space by dragging objects toward one of its edges, and how a user sees a trajectory of the objects the user is moving in the space.
Short term load forecasting in Greek intercontinental power system using ANNs: a study for input variables
Authors: G. J. Tsekouras, F. D. Kanellos, V. T. Kontargyri, C. D. Tsirekis, I. S. Karanasiou, Ch. N. Elias, A. D. Salis, P. A. Kontaxis, N. E. Mastorakis
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

The scopus of this paper is to compare the performance of different structures of Artificial Neural Networks (ANNs) regarding the input variables used for short-term forecasting of the next day load in intercontinental Greek power system. The input variables can be: (a) historical loads, (b) weather related temperatures, (c) hour and day indicators, in two ways: (i) selfsame, (ii) compressed using the Principal Components Analysis (PCA). The training algorithm is the scaled conjugate gradient algorithm, for which a calibration process is conducted regarding the crucial parameters values, such as the number of neurons, the kind of activation functions, etc. The performance of each structure is evaluated by the Mean Absolute Percentage Error (MAPE) between the experimental and estimated values of the hourly load demand of the next day for the evaluation set in order to specify the optimal ANN. Finally the load demand for the next day of the test set (with the historical data of the current year) is estimated using the best ANN structure, so that the verification of behaviour of ANN load prediction techniques was demonstrated.
Stage: Python with Actors
Authors: John Ayres, Susan Eisenbach
Venue: Proceedings of the 2009 ICSE Workshop on Multicore Software Engineering (2009)

Programmers hoping to exploit multi-core processors must split their applications into threads suitable for independent, concurrent execution. The lock-based concurrency of many existing languages is clumsy and error prone - a barrier to writing fast and correct concurrent code.
Necessary and sufficient global optimality conditions for NLP reformulations of linear SDP problems
Authors: Luigi Grippo, Laura Palagi, Veronica Piccialli
Venue: Journal of Global Optimization (2009)

In this paper we consider the standard linear SDP problem, and its low rank nonlinear programming reformulation, based on a Gramian representation of a positive semidefinite matrix. For this nonconvex quadratic problem with quadratic equality constraints, we give necessary and sufficient conditions of global optimality expressed in terms of the Lagrangian function.
Domain decomposition based $${\mathcal H}$$-LU preconditioning
Authors: Lars Grasedyck, Ronald Kriemann, Sabine Le Borne
Venue: Numerische Mathematik (2009)

Hierarchical matrices provide a data-sparse way to approximate fully populated matrices. The two basic steps in the construction of an $${{\mathcal H}}$$-matrix are (a) the hierarchical construction of a matrix block partition, and (b) the blockwise approximation of matrix data by low rank matrices. In this paper, we develop a new approach to construct the necessary partition based on domain decomposition. Compared to standard geometric bisection based $${{\mathcal H}}$$-matrices, this new approach yields $${\mathcal H}$$-LU factorizations of finite element stiffness matrices with significantly improved storage and computational complexity requirements. These rigorously proven and numerically verified improvements result from an $${\mathcal H}$$-matrix block structure which is naturally suited for parallelization and in which large subblocks of the stiffness matrix remain zero in an LU factorization. We provide numerical results in which a domain decomposition based $${{\mathcal H}}$$-LU factorization is used as a preconditioner in the iterative solution of the discrete (three-dimensional) convection-diffusion equation.
Collaborative haptic environment assessment
Authors: Felix G. Hamza-Lup, Benjamin M. Lambeth, James LaPlant
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

Collaborative virtual environments (CVE) allow users from different geographical locations to execute a shared task by acting upon the same entities in the virtual world. Most of these environments rely on visual and auditory senses. The advances in haptic technology have opened a path for the sense of touch to be integrated into CVE. The main issue in a haptic CVE is maintaining state consistency despite the existence of network delays. We focus this research on studying the effects of network latency on task performance and we report our preliminary results.
Peculiar behaviors of flexible chainlike walkers
Authors: Takashi Mashiko
Venue: Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control (2008)

To study the behaviors of many-body systems of deformable self-driven objects, several versions of the "flexible chainlike walker" (FCW) model are proposed and investigated by numerical simulations on a square lattice. It is shown that the "original" FCWs aggregate spontaneously and irreversibly, where no adherence is assumed, triggered by "mutual locking". This is in complete contrast to established aggregation models, where adherence is indispensable, and exemplifies the significance of the deformability of self-driven objects. The behaviors of the "smart" FCWs, which have higher ability of moving, are similar to those of the original FCWs. This suggests that the spontaneous, irreversible aggregation is a robust feature peculiar to a many-body system of deformable self-driven objects. On the other hand, the "double-headed" FCWs do not undergo the mutual locking and the resultant irreversible aggregation, unlike the original and the smart FCWs. This indicates that "bidirectionality" prevents deformable self-driven objects from aggregating.
A hybrid multi-group approach for privacy-preserving data mining
Authors: Zhouxuan Teng, Wenliang Du
Venue: Knowledge and Information Systems (2009)

In this paper, we propose a hybrid multi-group approach for privacy preserving data mining. We make two contributions in this paper. First, we propose a hybrid approach. Previous work has used either the randomization approach or the secure multi-party computation (SMC) approach. However, these two approaches have complementary features: the randomization approach is much more efficient but less accurate, while the SMC approach is less efficient but more accurate. We propose a novel hybrid approach, which takes advantage of the strength of both approaches to balance the accuracy and efficiency constraints. Compared to the two existing approaches, our proposed approach can achieve much better accuracy than randomization approach and much reduced computation cost than SMC approach. We also propose a multi-group scheme that makes it flexible for the data miner to control the balance between data mining accuracy and privacy. This scheme is motivated by the fact that existing randomization schemes that randomize data at individual attribute level can produce insufficient accuracy when the number of dimensions is high. We partition attributes into groups, and develop a scheme to conduct group-based randomization to achieve better data mining accuracy. To demonstrate the effectiveness of the proposed general schemes, we have implemented them for the ID3 decision tree algorithm and association rule mining problem and we also present experimental results.
Visualization Techniques for Program ComprehensionA Literature Review
Authors: François Lemieux, Martin Salois
Venue: Proceeding of the 2006 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fifth SoMeT_06 (2006)

Understanding software is getting more complex as programs are getting ever bigger. Many believe that the key to this problem is better visualization. The objective of this document is to provide an as thorough as possible overview of this field. This is the starting point for further research and development in this critical area. Over 140 papers and nearly as many tools were reviewed for this purpose. This document presents the most relevant and significant ones. It also tries to identify the essential requirements of a software visualization component.
Measurement and Modeling of Silicon Heterostructure Devices, 1st edition
Authors: John D. Cressler
Venue:  (2007)

When you see a nicely presented set of data, the natural response is: How did they do that; what tricks did they use; and how can I do that for myself? Alas, usually, you must simply keep wondering, since such tricks-of- the-trade are usually held close to the vest and rarely divulged. Shamefully ignored in the technical literature, measurement and modeling of high-speed semiconductor devices is a fine art. Robust measuring and modeling at the levels of performance found in modern SiGe devices requires extreme dexterity in the laboratory to obtain reliable data, and then a valid model to fit that data. Drawn from the comprehensive and well-reviewed Silicon Heterostructure Handbook, this volume focuses on measurement and modeling of high-speed silicon heterostructure devices. The chapter authors provide experience-based tricks-of-the-trade and the subtle nuances of measuring and modeling advanced devices, making this an important reference for the semiconductor industry. It includes easy-to-reference appendices covering topics such as the properties of silicon and germanium, the generalized Moll-Ross relations, the integral charge-control model, and sample SiGe HBT compact model parameters. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Applying active measurement in the rate adaptation for 802.11 wireless networks
Authors: Shaohe Lv, Xiaodong Wang, Xingming Zhou
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Rate Adaptation (RA) is a mechanism to choose transmission rate based on the dynamic channel quality in wireless networks. The adaptation algorithm run solely at the sender side in 802.11 networks is studied. The key insight is the inference discrepancy in inferring the relative order of the expected performance of candidate rate, which argues that one can not always reach the correct order based on the channel state information collected exclusively by the sender itself. The consequence is wrong rate decision and significant performance loss. Therefore, a new RA structure is proposed to mitigate such effect by a novel component, rate testing. By embracing the active measurement, a lightweight and effective testing mechanism SFB, short frame burst, is proposed to detect and filter out the unsuitable transmission rate. Finally, an active measurement-based rate adaptation mechanism (AMRA) is designed and implemented. The experiments show that AMRA outperforms many other well-known RA solutions in most scenarios.
Pattern Recognition and Neural Networks, 1st edition
Authors: Brian D. Ripley
Venue:  (2008)

This book uses tools from statistical decision theory and computational learning theory to create a rigorous foundation for the theory of neural networks. On the theoretical side, Pattern Recognition and Neural Networks emphasizes probability and statistics. Almost all the results have proofs that are often original. On the application side, the emphasis is on pattern recognition. Most of the examples are from real world problems. In addition to the more common types of networks, the book has chapters on decision trees and belief networks from the machine-learning field. This book is intended for use in graduate courses that teach statistics and engineering. A strong background in statistics is needed to fully appreciate the theoretical developments and proofs. However, undergraduate-level linear algebra, calculus, and probability knowledge is sufficient to follow the book.
An interactive parallel coordinates technique applied to a tropical cyclone climate analysis
Authors: Chad A. Steed, Patrick J. Fitzpatrick, T. J. Jankun-Kelly, Amber N. Yancey, J. Edward Swan II
Venue: Computers Geosciences (2009)

A highly interactive visual analysis system is presented that is based on an enhanced variant of parallel coordinates - a multivariate information visualization technique. The system combines many variations of previously described visual interaction techniques such as dynamic axis scaling, conjunctive visual queries, statistical indicators, and aerial perspective shading. The system capabilities are demonstrated on a hurricane climate data set. This climate study corroborates the notion that enhanced visual analysis with parallel coordinates provides a deeper understanding when used in conjunction with traditional multiple regression analysis.
Preemption point selection for improved memory hierarchy management
Authors: Hyacinthe Kocou Aboudja
Venue:  (2008)

The gap in access time between Central Processing Unit (CPU) and the main memory has continued to increase drastically due to advances in technology especially in the silicon material industry. Cache memory has been used in systems to reduce that gap and to increase performance attributes, mainly speed. However because of the drawbacks it introduces, cache memory hinders its primary goal of improvement.The main goal of this dissertation is to contribute to a reduction in the drawbacks of cache memory on systems. This dissertation presents and improves a technique, the Preferred Preemption Point Technique, to increase performance, predictability and stability of cache-based real-time systems. This technique consists of monitoring the cache content during the course of a running task to select the best point where the cost of preemption will be minimum. This improvement leads to a reduction in resource contention.To reach this goal in the present study, a cache simulator has been used as a platform. It has been augmented to have useful features for cache memory such as interconnection between levels in the multi-level cache hierarchy. The state of each line in the cache is monitored to decide on the cost-effective selection of preemption points. This process is followed by a performance evaluation of the system.Time-critical systems used in security, medical equipment, hazardous environments, flight control, radar systems, and telecommunication will benefit from the current study.The performance analysis of the results of the simulation showed an improvement of up to and over 20% in some cases. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A modified pulse coupled neural network for shortest-path problem
Authors: Xiaobin Wang, Hong Qu, Zhang Yi
Venue: Neurocomputing (2009)

Shortest-path problem is well-known optimization problem and has been studied by many authors in recent years. Typically it is solved by using the famous Dijkstra's algorithm, which would quickly provide a global optimization solution in most instances. However, as the problem scale increases, this method is inefficient and may consume a considerable amount of CPU time. Neural networks, which are massively parallel models, can solve this question easily. This paper presents a novel biological neural network based algorithm for the finding of the shortest path in large scale systems. The start neuron fires first, and then the firing event spreads out through the lateral connections among the neurons, like the propagation of a wave. Then the generated spiking wave spreads at a constant speed so that the time of travel between two neurons is proportional to the path length between them. The computational complexity of the algorithm is only related to the length of the shortest path, and independent of the number of existing paths in the graph. Simulation results show that the proposed method is more efficient than Dijkstra's in the larger scale systems.
Link quality prediction for wireless devices with multiple radios
Authors: Qiuyi Duan, Lei Wang, Charles D. Knutson, Daniel Zappala
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Communication between wireless devices ought to be as simple as possible; they should be able to seamlessly switch between different radios and network stacks on the fly in order to better serve the user. To make this a possibility, we consider the challenging problem of predicting link quality in a changing mobile environment. In this paper we present an algorithm that uses Weighted Least Squares Regression to predict whether a given link can meet application requirements in terms of throughput, delay, and jitter. We use a simulation study to demonstrate that our algorithm is able to predict link quality accurately and stably in a frequently changing mobile environment. The prediction algorithm is more accurate than several alternative algorithms, and the overhead caused by the link measurements is negligible in terms of throughput and power consumption.
Combinatorial Auctions and Knapsack Problems - An Analysis of Optimization Methods
Authors: Jella Pfeiffer
Venue:  (2007)

With the rapid diffusion of the internet, different kinds of market designs for e-commerce have emerged. Among these, combinatorial auctions (CAs) have gained increased interest as they permit bidders to express their valuations more easily. For applying a CA in real world scenarios, fast algorithms are needed to compute the optimal allocation of the offered goods. Although much research has dealt with this so-called Winner Determination Problem (WDP), only recently has its equivalence to the well-studied multi-dimensional knapsack problem (MDKP) been noticed. Therefore, there is a lack of research which compares approaches for solving MDKP and WDP problems. With this work, the author, Jella Pfeiffer, provides the missing integrative step, aiming at a more intense understanding and a mutual inspiration of both research areas. She examines structural differences of test instances from both domains, compares the performance of different algorithms, and alludes to a successful search behavior of non-exact but fast algorithms. The book addresses readers interested in electronic market design and algorithms solving complex combinatorial optimization problems.
Low-energy fault-tolerant bounded-hop broadcast in wireless networks
Authors: Hanan Shpungin, Michael Segal
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

This paper studies asymmetric power assignments in wireless ad hoc networks. The temporary, unfixed physical topology of wireless ad hoc networks is determined by the distribution of the wireless nodes as well as the transmission power (range) assignment of each node. We consider the problem of bounded-hop broadcast under k-fault resilience criterion for linear and planar layout of nodes. The topology that results from our power assignment allows a broadcast operation from a wireless node r to any other node in at most h hops and is k-fault resistant. We develop simple approximation algorithms for the two cases and obtain the following approximation ratios: linear case--O(k); planar case--we first prove a factor of O(k3), which is later decreased toO(k2) by a finer analysis. Finally, we show a trivial power assignment with a cost O(h) times the optimum. To the best of our knowledge, these are the first nontrivial results for this problem.
Stability regions of two-way relaying with network coding
Authors: Ertugrul Necdet Ciftcioglu, Aylin Yener, Randall Berry
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

We consider a pair of nodes with stochastic traffic flows who wish to communicate in a bi-directional communication scenario using intermediate relays in two-hop fashion. Intermediate relays are capable of XOR network coding. Transmission scheduling is done by tailoring the backpressure algorithm to the problem at hand. Two main alternatives for network operation are either to have queues at the relays (hop-by-hop scheduling) or no queues at the relays (immediate forwarding). In this two-way network with stochastic flows, we formulate and show that the resulting stability regions of these two approaches are identical.
An Adaline-Based Location Algorithm for Wireless Sensor Network
Authors: Fengjun Shang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Localization is used in location-aware applications such as navigation, autonomous robotic movement, and asset tracking to position a moving object on a coordinate system. In this paper, we present an improved DV-Hop algorithm based on Adaline(adaptive linear neuron) and DV-Hop, called ADV-Hop. The algorithm makes three major contributions to the localization problem in the wireless sensor networks(WSNs). First, we present a practical, fast and easy-to-use localization scheme with relatively high accuracy and low cost for WSNs. Second, the proposed algorithm improves location accuracy than the DV-Hop algorithm. Third, we explored the influence of anchor nodes on localization performance of the ADV-Hop algorithm. The proposed method can improve location accuracy and coverage without increasing hardware cost of sensor node. Simulation results show that the performance of this algorithm is superior to the original DV-Hop algorithm. Compared with DV-Hop, it is more available for WSNs.