ppxscal/embedding_network huggingface dataset:
The 2005 DARPA Grand Challenge: The Great Robot Race, 1st edition
Authors: Martin Buehler, Karl Iagnemma, Sanjiv Singh
Venue: Springer Tracts In Advanced Robotics (2007)

The DARPA Grand Challenge was a landmark in the field of robotics: a race by autonomous vehicles through 132 miles of rough, cross-country Nevada terrain that showcased exciting and unprecedented capabilities in robotic perception, navigation, and control. The event took place in October 2005, and drew teams of competitors from academia and industry, and many garage hobbyists. This book presents fifteen technical papers that are written at a level that makes them easily accessible to a broad technical audience, describing the technology behind most of the robotic vehicles that participated in this famous race. The papers describe each team's driverless vehicle, race strategy, and insights. As a whole, they present the state of the art in autonomous vehicle technology, and offer a glimpse of future technology for tomorrows driverless cars. This book will serve as an authoritative, archival source for the DARPA Grand Challenge and a must have for robotics students and researchers, since it describes the state of the art in perception, planning and control.
Scatter Difference NAP for SVM Speaker Recognition
Authors: Brendan Baker, Robbie Vogt, Mitchell Mclaren, Sridha Sridharan
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

This paper presents Scatter Difference Nuisance Attribute Projection (SD-NAP) as an enhancement to NAP for SVM-based speaker verification. While standard NAP may inadvertently remove desirable speaker variability, SD-NAP explicitly de-emphasises this variability by incorporating a weighted version of the between-class scatter into the NAP optimisation criterion. Experimental evaluation of SD-NAP with a variety of SVM systems on the 2006 and 2008 NIST SRE corpora demonstrate that SD-NAP provides improved verification performance over standard NAP in most cases, particularly at the EER operating point.
OpenTag: Privacy Protection for RFID
Authors: Henry Holtzman, Sanghoon Lee, Daniel Shen
Venue: IEEE Pervasive Computing (2009)

Radio frequency identification (RFID) is widely used to identify goods in the supply chain and is increasingly implemented in individual manufactured goods at the retail level. This is a positive trend for pervasive computing; ubiquitous, machine-readable tagging of objects has proven valuable—yet elusive—in the past. With the proliferation of RFID tagged objects, however, comes the possibility of privacy loss. OpenTag was designed to prototype new privacy enhancing algorithms for RFID. Its tags are programmable and work in several modes, including EPC mode, where they're fully compatible with EPCglobal's dominant supply-chain RFID standard. OpenTags can also operate in private mode, frequently altering their IDs so that only authorized readers can predict them, as well as in invisible mode, where they stop responding to readers entirely. Designed for cradle-to-grave object tagging, OpenTags easily and appropriately transition between their various modes.
Thermohaline fields monitoring model
Authors: Peep Miidla, Kalev Rannat
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

In this paper a model of thermohaline field turbulent energy evolution caused by double diffusion effects, is under consideration. The model itself is a system of three nonlinear partial differential equations for environment's temperature, salinity and turbulence kinetic energy, where unknown functions depend on time and on one only, vertical space state variable. The numerical implementation of the model is given, also the computational stability criteria. The numerical realisation of the model bases on implicit difference method, on the uniform rectangular time-space grid and Newton iteration method. The numerical stability criterion of the algorithm for the model's approximated solution is estimated by the maximum values of the solutions of system components.
Recent advances in data engineering and management
Authors: Zeljko Panian
Venue: Proceedings of the 8th Wseas international conference on Telecommunications and informatics (2009)

To increase the value of data as a business asset, companies and government organizations need to establish standards, policies, and processes for the usage, development, engineering and management of data, to create the right organizational structure, and to develop the supporting technology infrastructure. As a practice with roots in corporate and information technology (IT) governance, data governance emerged. Data governance can be defined as the processes, policies, standards, organization, and technologies required to manage and ensure the availability, accessibility, quality, consistency, auditability, and security of data in an organization.
A case study of behavior-driven conjoint analysis on Yahoo!: front page today module
Authors: Wei Chu, Seung-Taek Park, Todd Beaupre, Nitin Motgi, Amit Phadke, Seinjuti Chakraborty, Joe Zachariah
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Conjoint analysis is one of the most popular market research methodologies for assessing how customers with heterogeneous preferences appraise various objective characteristics in products or services, which provides critical inputs for many marketing decisions, e.g. optimal design of new products and target market selection. Nowadays it becomes practical in e-commercial applications to collect millions of samples quickly. However, the large-scale data sets make traditional conjoint analysis coupled with sophisticated Monte Carlo simulation for parameter estimation computationally prohibitive. In this paper, we report a successful large-scale case study of conjoint analysis on click through stream in a real-world application at Yahoo!. We consider identifying users' heterogenous preferences from millions of click/view events and building predictive models to classify new users into segments of distinct behavior pattern. A scalable conjoint analysis technique, known as tensor segmentation, is developed by utilizing logistic tensor regression in standard partworth framework for solutions. In offline analysis on the samples collected from a random bucket of Yahoo! Front Page Today Module, we compare tensor segmentation against other segmentation schemes using demographic information, and study user preferences on article content within tensor segments. Our knowledge acquired in the segmentation results also provides assistance to editors in content management and user targeting. The usefulness of our approach is further verified by the observations in a bucket test launched in Dec. 2008.
A relation metadata extension for SCORM Content Aggregation Model
Authors: Eric Jui-Lin Lu, Chin-Ju Hsieh
Venue: Computer Standards Interfaces (2009)

To increase the interchangeability and reusability of learning objects, Advanced Distributed Learning Initiative suggested a set of metadata in SCORM Content Aggregation Model to describe learning objects and express relationships between learning objects. However, the suggested relations defined in the metadata of the SCORM CAM are limited. To resolve the problem, new relations were proposed by researchers. Unfortunately, some of the relations are redundant and even inappropriate. In addition, the usability of these relations has never been formally studied. Therefore, in this paper, we summarized and analyzed existing relations, removed duplicated relations, and developed a new relation metadata extension for SCORM CAM. Also, we surveyed 145 students in attempt to understand whether or not the proposed relations can increase their learning effectiveness. The results of the survey showed that learners agreed that the proposed relations are helpful.
A lab course for discrete mathematics
Authors: Ben Setzer
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

We describe a mathematics course designed for Computer Science majors in which they investigate large scale examples based in discrete mathematics. This course was developed in response to the need to strengthen the theoretical content of the Computer Science curriculum. The design of this course supports better learning and using good programming practice.
Leakage reduction, delay compensation using partition-based tunable body-biasing techniques
Authors: Po-Yuan Chen, Chiao-Chen Fang, Tingting Hwang, Hsi-Pin Ma
Venue: ACM Transactions on Design Automation of Electronic Systems (TODAES) (2009)

In recent years, fabrication technology of CMOS has scaled to nanometer dimensions. As scaling progresses, several new challenges follow. Among them, the most noticeable two are process variations and leakage current of the circuit. To tackle the problems of process variations and leakage current, an effective way is to use a body-biasing technique. In substance, using the RBB technique can minimize leakage current but increase the delay of a gate. Contrary to RBB, the FBB technique decreases the delay but increases leakage current of a gate. In the previous work, a single body-biasing is applied to the whole circuit. In a slow circuit, since the FBB is applied to the whole circuit, the leakage current of all gates in the circuit increases dramatically. On the other hand, in a fast circuit, RBB is applied to decrease the leakage current. However, without violating the timing specification, the value of body-biasing is restricted by the critical paths, and the saving of leakage current is limited. In this article, we propose a design flow to partition the circuit into subcircuits so that each subcircuit can be applied its individual RBB or FBB. Experiments show that our method is able to save leakage current from 42&percnt; to 47&percnt; as compared to designs not using a body-biasing technique. Under process variations, our method can save 42&percnt; to 49&percnt; leakage on fast circuits and 20&percnt; to 35&percnt; on slow circuits.
e-Work based collaborative optimization approach for strategic logistic network design problem
Authors: Pablo A. Miranda, Rodrigo A. Garrido, José A. Ceroni
Venue: Computers and Industrial Engineering (2009)

We propose a collaborative e-Work based optimization approach for assisting the strategic logistic network design problem, which considers fleet design and customer clustering decisions. Normally, fleet design and customer clustering decisions are made by mid-level logistics managers while network design decision is made independently by high-level logistics managers. In the proposed approach, strategic distribution network design is modeled as a Facility Location Problem, considering long term inventory control decisions. On the other hand, tactical fleet design and customer clustering decisions are modeled based on a Hub and Spoke cost structure. An e-Work based heuristic approach is proposed to solve collaboratively the network design problem at strategic and tactical levels. The collaborative solution approach results from a particular sequential decomposition of the problem, similarly to traditional location-allocation heuristics, modeling an information sharing strategy between decision makers involved at each organizational level. A numerical application of the approach with real data based instances shows significant benefits, when compared to a non-collaborative independent optimization, where the hierarchical levels share no dynamic information and base their decisions on static and independent optimization models. These results show evidence of the advantage of the e-collaborative approach to deal with logistic decisions at different hierarchical levels, organizational units, or companies, compared to non-integrated non-linear mixed integer programming models.
A Broadcasting Method considering Battery Lifetime and Distance between Nodes in MANET
Authors: Daisuke Kasamatsu, Norihiko Shinomiya, Tadashi Ohta
Venue: Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems Workshops (2009)

This paper proposes a broadcasting method considering the residual battery lifetime of each node and distance between relay nodes in MANET (Mobile Ad-hoc Networks). In the method, broadcasting packets are sent with high reachability, low network load and low broadcasting latency to a whole network. So far, many broadcasting methods have been proposed. But, since most methods do not take into consideration the residual battery lifetime of each node, there is a possibility that reachability decreases with time lapse. As a method which considers the residual battery lifetime of each node, FBC (Fair Battery Consumption) has been proposed. However, there is a possibility that the number of dead nodes rapidly increases because the difference between the residual battery lifetimes of each node decreases with time lapse. By simulation, the proposed method is compared with existing methods and the effectiveness of the proposed method was confirmed.
Design of an Environment for Developing Presentation Skills
Authors: Kazuhisa Seta, Mitsuru Ikeda
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Presentation plays an important role in transmitting one's opinion and encouraging collaborative knowledge creation and decision-making processes. A key to producing persuasive presentation materials is to perform meta-cognitive activities well, but that is difficult for novice learners of presentation tasks. Furthermore, from the system-development viewpoint, it is difficult to develop a learning system with which learners can develop their presentation skills effectively because the cognitive activities in presentation task are typically not clarified. In this paper, we first present a cognitive model of the user who performs presentation task. We then overview two kinds of designed environments based on that model: one is for producing presentation materials that encourage learners to perform meta-cognitive activities; the other is a collaborative learning environment in presentation rehearsal, which encourages the transfer of context-dependent meta-cognitive knowledge among learning partners.
Why are we still here?: experiences of successful women in computing
Authors: Hannah M. Dee, Karen E. Petrie, Roger D. Boyle, Reena Pau
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

This paper describes a study into the attitudes and experiences of women at three distinct stages of the career pipeline: undergraduate, graduate student, and staff. Computing has often been likened to a "leaky pipeline" for women, so this work aims to consider various aspects of the student experience from the perspective of those who have in some sense succeeded and got at least as far as studying the subject at degree level. Through concentrating on the opinions and experiences of women who have persisted (and in some sense, done well) in computing, the authors hope to accentuate the positive: rather than work out what makes women drop out of computing, we instead consider what makes them stay.
Parameter-uniform hybrid numerical scheme for time-dependent convection-dominated initial-boundary-value problems
Authors: Kaushik Mukherjee, Srinivasan Natesan
Venue: Computing (2009)

In this paper, we propose a numerical scheme which is almost second-order spatial accurate for a one-dimensional singularly perturbed parabolic convection-diffusion problem exhibiting a regular boundary layer. The proposed numerical scheme consists of classical backward-Euler method for the time discretization and a hybrid finite difference scheme for the spatial discretization. We analyze the scheme on a piecewise-uniform Shishkin mesh for the spatial discretization to establish uniform convergence with respect to the perturbation parameter. Numerical results are presented to validate the theoretical results.
An evaporation mechanism for dynamic and noisy multimodal optimization
Authors: Jose Luis Fernandez-Marquez, Josep Lluis Arcos
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

Dealing with imprecise information is a common characteristic in real-world problems. Specifically, when the source of the information are physical sensors, a level of noise in the evaluation has to be assumed. Particle Swarm Optimization is a technique that presented a good behavior when dealing with noisy fitness functions. Nevertheless, the problem is still open. In this paper we propose the use of the evaporation mechanism for managing with dynamic multi-modal optimization problems that are subject to noisy fitness functions. We will show how the evaporation mechanism does not require the detection of environment changes and how can be used for improving the performance of PSO algorithms working in noisy environments.
Distributed Computation of Likelihood Maps for Target Tracking
Authors: Jonathan Gallagher, Randolph Moses, Emre Ertin
Venue: Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems (2009)

Using the Bayesian framework of measurement likelihood, sensor data can be combined in a rigorous manner to produce a concise summary of knowledge of a target's location in the state-space. This framework allows sensor data to be fused across time, space and sensor modality. When target motion and sensor measurements are modeled correctly, these "likelihood maps" contain all the relevant information for making inferences about the underlying target state. By combining all data without thresholding for detections, targets with low signal to noise ratio (SNR) can be detected where standard detection algorithms may fail. As the calculation cost of computing likelihood maps over the entire state space is prohibitively high for most practical applications, we propose an approximation which is computed in a distributed fashion, locally at each sensor node. We analyze this approximation, and give cases where it agrees with the centrally calculated likelihood map. Detection and tracking examples using measured data from multi-modal sensors (Radar, EO, Seismic) are presented.
Simulation of turning process of AISI 1045 and carbide tool using finite element method
Authors: A. G. Jaharah, Y. Hendri, C. H. Che Hassan, R. Ramli, Z. Yaakob
Venue: Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics (2008)

In recent years, the applications of finite element method (FEM) in metal cutting operations have proved to be effective in studying the cutting process and chip formation. The simulation results is useful for both researchers and machine tool makers in optimising the cutting parameters and designing new tools. This paper present the application of Finite element method (FEM) in simulating the effect of cutting tool geometries and cutting speed on the effective stress and temperature changes in turning AISI 1045.The tool geometries studied were various rake (α) and clearance (β) in the range of -5° to 5°, and 5° to 9° for α and β respectively, for cutting speed in the range of 100-300 m/min, at constant feed rate of 0.35 mm/rev and depth of cut of 0.18 mm. The effect of cutting speed on turning process was studied for cutting speed in the range of 100-450 m/min, while the feed rate and depth of cut were kept constant at 0.35 mm/rev and 0.3 mm respectively. The simulation simulation results show that the effective stress and cutting temperature on the cutting edge were between 1710Pa to 2040MPa and 880°C to 2080°C respectively while varying the tool geometries. The simulation results also show that by increasing the cutting speed causes a decrease in effective-stress and increase the temperature of the chip formed to certain extend.
Transmission Network Planning Based on Multi-objective Evolutionary Algorithm of Transportation Theory
Authors: Huang Ping, Zhang Yao, Li Pengcheng, Li Kangshun
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Power network planning is a discrete, nonlinear and multi-object mixed integer program problem, and is quite difficult to solve. In this paper, a Multi-objective Problem Evolutionary Algorithm, MOPEA, for solving power network planning is presented according to the principle of particle trajectories, minimum energy principle and the law of entropy increasing in phase space of particles based on transportation theory and this algorithm can solve complex optimization problems to obtain the global optimal solution. By means of a DC load flow model, the network takes into account of construction cost, operation cost and cost of losses. After running a simulation computation of Garver-6 node system, the results are: Compared with the results of single objective genetic algorithm and NSGA-II algorithm, MOPEA obtains the lowest costs of total planning scheme, and the planning schemes can highly improve the economic efficiency of power transmission network planning.
Test collection selection and gold standard generation for a multiply-annotated opinion corpus
Authors: Lun-Wei Ku, Yong-Shen Lo, Hsin-Hsi Chen
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

Opinion analysis is an important research topic in recent years. However, there are no common methods to create evaluation corpora. This paper introduces a method for developing opinion corpora involving multiple annotators. The characteristics of the created corpus are discussed, and the methodologies to select more consistent testing collections and their corresponding gold standards are proposed. Under the gold standards, an opinion extraction system is evaluated. The experiment results show some interesting phenomena.
Norms with deadlines in Dynamic Deontic Logic
Authors: Robert Demolombe, Philippe Bretier, Vincent Louis
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

In this paper we extend the logical framework defined by K. Segerberg about norms and actions to norms that refer to deadlines. We also characterize the circumstances where these norms are violated.
Case study of virtual organization learning and knowledge testing environments
Authors: Kazys Baniulis, Bronius Tamulynas, Nerijus Aukstakalnis
Venue: Proceeding of the 2005 conference on Towards the Learning Grid: Advances in Human Learning Services (2005)

The proposed web-based knowledge assessment is based on flexible educational model and allows to implement adaptive control of learning process as well as to implement knowledge testing environment according to the requirements of student's knowledge level, his personal abilities and subject learning history. The learner knowledge model can be constructed as a subgraph of the global knowledge domain graph. The paper presents the architecture of student self-evaluation and on-line assessment system TestTool. The system is explored as an assessment engine capable to support and improve the individualized intelligent self-instructional mode of learning, grounded on the Grid distributed service architecture.
Integration of Gd silicate/TiN gate stacks into SOI n-MOSFETs
Authors: M. Schmidt, A. Stefani, H. D. B. Gottlob, H. Kurz
Venue: Microelectronic Engineering (2009)

In this work we describe the gate first integration of gadolinium silicate (GdSiO) high-k dielectrics and metal gate electrodes into SOI n-MOSFETs. Fully functional devices are achieved and compared to reference devices with standard SiO"2. Analysis of electron transport in these gate stacks is performed by specific MOSFET test structures that enable extraction of intrinsic inversion channel mobility. Attractive peak mobilities of 170cm^2/Vs have been found for GdSiO.