ppxscal/embedding_network huggingface dataset:
A penalized likelihood based pattern classification algorithm
Authors: Amir F. Atiya, Ahmed Al-Ani
Venue: Pattern Recognition (2009)

Penalized likelihood is a general approach whereby an objective function is defined, consisting of the log likelihood of the data minus some term penalizing non-smooth solutions. Subsequently, this objective function is maximized, yielding a solution that achieves some sort of trade-off between the faithfulness and the smoothness of the fit. Most work on that topic focused on the regression problem, and there has been little work on the classification problem. In this paper we propose a new classification method using the concept of penalized likelihood (for the two class case). By proposing a novel penalty term based on the K-nearest neighbors, simple analytical derivations have led to an algorithm that is proved to converge to the global optimum. Moreover, this algorithm is very simple to implement and converges typically in two or three iterations. We also introduced two variants of the method by distance-weighting the K-nearest neighbor contributions, and by tackling the unbalanced class patterns situation. We performed extensive experiments to compare the proposed method to several well-known classification methods. These simulations reveal that the proposed method achieves one of the top ranks in classification performance and with a fairly small computation time.
Principles of Mobile Computing and Communications, 1st edition
Authors: Mazliza Othman
Venue:  (2007)

Assuming only a basic knowledge of communication networks, Principles of Mobile Computing and Communications provides an understanding of wireless networks and relevant standards, highlighting issues that are unique to the mobile computing environment and exploring the differences between conventional and mobile applications. This book covers wireless network standards for cellular networks, WLANs, WPANs, wireless sensor networks, MANETs, and mobile IPs. It discusses location identification techniques as well as location systems. It also explores the issue of security in wireless networks and presents case studies to illustrate the requirements for developing mobile applications. A Web site provides ancillary material for classroom use. 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
Computer Games as Intelligent Learning Environments: A River Ecosystem Adventure
Authors: Jason Tan, Chris Beers, Ruchi Gupta, Gautam Biswas
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

Our goal in this work has been to bring together the entertaining and flow characteristics of video game environments with proven learning theories to advance the state of the art in intelligent learning environments. We have designed and implemented an educational game, a river adventure. The adventure game design integrates the Neverwinter Nights game engine with our teachable agents system, Betty's Brain. The implementation links the game interface and the game engine with the existing Betty's Brain system and the river ecosystem simulation using a controller written in Java. After preliminary testing, we will run a complete study with the system in a middle school classroom in Fall 2005.
Evaluating SoC Network Performance in MPEG-4 Encoder
Authors: Ari Kulmala, Erno Salminen, Marko Hännikäinen, Timo D. Hämäläinen
Venue: Journal of Signal Processing Systems (2009)

This paper shows how a bus topology performs as a System-on-Chip (SoC) interconnection. We measure and analyze Heterogeneous IP Block Interconnection (HIBI) bus for a multiple clock domain, Multiprocessor System-on-Chip (MPSoC) with an MPEG-4 video encoding application on FPGA. The studied MPSoC contains up to 22 IP blocks: 11 soft processors, 8 hardware accelerators and three other components. A novel approach of frequency scaling is used to isolate the impact of various architecture components. The system is benchmarked in various configurations. For example, HIBI is run at 100× speed with respect to processors to resemble ideal interconnection. Based on the measurements with up to 16.9frames/s CIF (352 × 288) encoding speed, estimation for HDTV resolution video encoder is presented. The required optimizations are discussed. Finally, it is shown that 25frames/s 1280 × 720 video encoder needs 55 MHz HIBI but 670 MHz general-purpose soft RISC processors. In practice, the processing performance has to be boosted by implementing hardware acceleration and improving memory hierarchy. Clearly, HIBI is not the limiting factor.
Estimation of erosion in tectonically active orogenies. Example from the Bhotekoshi catchment, Himalaya (Nepal)
Authors: C. Andermann, R. Gloaguen
Venue: International Journal of Remote Sensing (2009)

The inaccessibility of active orogens such as the Himalayas renders detailed field studies on a large scale impossible. The integrative application of several remote sensing techniques in combination with ground truth information provides an alternative to assess the acting processes during erosion in tectonically active orogens. This study was carried out in the catchment area of the Bhotekoshi River, which drains both the Tibetan Plateau and the Himalayan Range. On the basis of stereogrammetric digital elevation models (DEMs) extracted from ASTER data and from aerial photographs, in combination with multispectral analysis, it is possible to appraise the nature of erosive processes. River networks are extracted from DEMs and their gradient, channel densities and flow path geometries are calculated and integrated in the erosion estimation model. In this study a modified Revised Universal Soil Loss Equation (RUSLE) and the Vegetation cover-Surface material and Drainage density (VSD) index have been tested for their suitability in the Himalayas. Using classifications methods-Maximum Likelihood (MLC), Support Vector Machines (SVM) and Object Based (OBC)-precise land use mapping can be carried out and affiliated with typical erosion rates. Long-term total erosion has been estimated using power law stream analysis. We show that the erosion models tested here underestimate erosion in tectonically active regions.
L1-norm Regularization Based Nonlinear Integrals
Authors: Jinfeng Wang, Kinhong Lee, Kwongsak Leung
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Since Nonlinear Integrals, such as the Choquet Integral and Sugeno Integrals, were proposed, how to get the Fuzzy Measure and confirm the unique solution became the hard problems. Some researchers can obtain the optimal solution for Fuzzy Measure using soft computing tools. When the Nonlinear Integrals can be transformed to a linear equation with regards to Fuzzy Measure by Prof. Wang, we can apply the L1-norm regularization method to solve the linear equation system for one dataset and find a solution with the fewest nonzero values. The solution with the fewest nonzero can show the degree of contribution of some features or their combinations for decision. The experimental results show that the L1-norm regularization is helpful to the classifier based on Nonlinear Integrals. It can not only reduce the complexity of Nonlinear Integral but also keep the good performance of the model based on Nonlinear Integral. Meanwhile, we can dig out and understand the affection and meaning of the Fuzzy Measure better.
Understanding E-Learners' Characteristics and Performance in Online Courses
Authors: Rowena Santiago, Minoru Nakayama
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Learner characteristics have been identified to have a significant influence on student performance in online learning environments. This paper describes the results of a project that surveyed the motivation, personality and thinking styles of e-learners and explored any significant relationship(s) they may have on student performance.
Retrieval of sea ice thickness distribution in the seasonal ice zone from airborne L-band SAR
Authors: T. Toyota, K. Nakamura, S. Uto, K. I. Ohshima, N. Ebuchi
Venue: International Journal of Remote Sensing (2009)

Although satellite data are known to be useful for obtaining ice thickness distribution for perennial sea ice or in stable thin sea ice areas, their use in the seasonal sea ice zone (SIZ) is still unresolved. In this study, we approached the problem of ice thickness retrieval by using L-band Synthetic Aperture Radar (SAR). In the SIZ, ice thickness growth is closely related to ridging activity and therefore we expected surface roughness to be correlated to ice thickness. L-band SAR is suitable for detecting such surface roughness and should be a useful tool for obtaining ice thickness distribution. To verify this correlation, we conducted shipborne electromagnetic (EM) inductive sounding and supersonic profiling observations with an icebreaker, coordinated with airborne L-band SAR observations in the southern Sea of Okhotsk in February 2005. The surface elevation was estimated by representing the ship's motion with a low-pass filter. Backscattering coefficients correlated well with ice thickness and surface roughness, defined by the standard deviation of the surface elevation. This result sheds light on the possibility of determining ice thickness distribution in the SIZ.
Predicting the location of mobile users: a machine learning approach
Authors: Theodoros Anagnostopoulos, Christos Anagnostopoulos, Stathes Hadjiefthymiades, Miltos Kyriakakos, Alexandros Kalousis
Venue: Proceedings of the 2009 international conference on Pervasive services (2009)

Mobile context-aware applications experience a constantly changing environment with increased dynamicity. In order to work efficiently, the location of mobile users needs to be predicted and properly exploited by mobile applications. We propose a spatial context model, which deals with the location prediction of mobile users. Such model is used for the classification of the users' trajectories through Machine Learning (ML) algorithms. Predicting spatial context is treated through supervised learning. We evaluate our model in terms of prediction accuracy w.r.t. specific prediction parameters. The proposed model is also compared with other ML algorithms for location prediction. Our findings are very promising for the efficient operation of mobile context-aware applications.
Scaling up data intensive scientific applications to campus grids
Authors: Douglas Thain
Venue: Proceedings of the 1st ACM workshop on Large-Scale system and application performance (2009)

A campus grid aggregates computing and storage capacity from many clusters, desktops, and servers to provide a cost-effective large scale computing facility for an entire institution. Many universities today operate campus grids on the scale of thousands to tens of thousands of nodes. However, the people that might derive the most benefit from campus grids are generally accustomed to using single computers or conventional clusters. Making the jump from a single cluster to a campus grid can be very challenging, because the user or programmer must contend with a host of performance and reliability challenges that only arise in large scale systems. To solve this problem, we advocate the use of high level abstractions. An abstraction is a framework that represents a very narrow category of problems, but is both robust and scalable across very large problem sizes. We have developed a suite of abstractions and deployed them on campus grids at the University of Notre Dame, Purdue University, and the University of Wisconsin to attack large scale problems in fields such as biometrics, bioinformatics, data mining, and economics. With this approach, we have enabled end users to efficiently harness hundreds to thousands of CPUs without requiring them to learn a radically new programming model.
Derivational relations in Czech WordNet
Authors: Karel Pala, Dana Hlaváčková
Venue: Proceedings of the Workshop on Balto-Slavonic Natural Language Processing: Information Extraction and Enabling Technologies (2007)

In the paper we describe enriching Czech WordNet with the derivational relations that in highly inflectional languages like Czech form typical derivational nests (or subnets). Derivational relations are mostly of semantic nature and their regularity in Czech allows us to add them to the WordNet almost automatically. For this purpose we have used the derivational version of morphological analyzer Ajka that is able to handle the basic and most productive derivational relations in Czech. Using a special derivational interface developed in our NLP Lab we have explored the semantic nature of the selected noun derivational suffixes and established a set of the semantically labeled derivational relations -- presently 14. We have added them to the Czech WordNet and in this way enriched it with approx. 30 000 new Czech synsets. A similar enrichment for Princeton WordNet has been reported in its recently released version 3.0, we will comment on the partial similarities and differences.
The Gilgamesh MIND Processor-in-Memory Architecture for Petaflops-Scale Computing
Authors: Thomas Sterling
Venue: Proceedings of the 4th International Symposium on High Performance Computing (2009)

Implicit in the evolution of current technology and high-end system evolution is the anticipated achievement of the implementation of computers capable of a peak performance of 1 Petaflops by the year 2010. This is consistent with both the semiconductor industry's roadmap of basic device technology development and an extrapolation of the TOP-500 list of the world's fastest computers according to the Linpack benchmark. But if contemporary experiences with today's largest systems hold true for their descendents at the end of the decade, then they will be very expensive (> $100M), consume too much power (> 3 Mwatts), take up too much floor space (> 10,000 square feet), deliver very low efficiency (< 10%), and are too difficult to program. Also important is the likely degradation of reliability due to the multiplicative factors of MTBF and scale of components. Even if these systems do manage to drag the community to the edge of Petaflops, there is no basis of confidence to assume that they will provide the foundation for systems across the next decade that will transition across the trans-Petaflops performance regime. It has become increasingly clear that an alternative model of system architecture may be required for future generation high-end computers.
Technology to Aid Aging in Place- New Opportunities and Challenges
Authors: Lalatendu Satpathy, Anijo Mathew
Venue:  (2007)

With cheaper and more ubiquitous computing, "smart" spaces and responsive environments are increasingly becoming plausible and affordable. Can the profession of architecture respond to current computing technologies? Most critics agree that one of the first (most important) problems that "smart" homes will help to address is that of spiraling costs of elderly healthcare and care giving. But what is the problem with healthcare? Will the technologies that are designed for the urban home work in a rural setting? This book addresses the above questions through research of current problems and models of rural healthcare and through a documentation of existing studies and a focus group study at Meridian, MS. The book also examines the role of architecture (and architects) in the context of ubiquitous computing and "smart" spaces in rural areas.
New inexact implicit method for general mixed quasi variational inequalities
Authors: Abdellah Bnouhachem, Muhammad Aslam Noor
Venue: Journal of Global Optimization (2009)

In this paper, we suggest and analyze a new self-adaptive inexact implicit method with a variable parameter for general mixed quasi variational inequalities, where the skew-symmetry of the nonlinear bifunction plays a crucial part in the convergence analysis of this method. We use a self-adaptive technique to adjust parameter ¿ at each iteration. The global convergence of the proposed method is proved under some mild conditions. Preliminary numerical results indicate that the self-adaptive adjustment rule is necessary in practice.
Digital signature and hash function irregularity
Authors: Milan Tuba
Venue: Proceedings of the 8th Wseas international conference on Telecommunications and informatics (2009)

Use of computer networks is expanding in many important areas such as e-government, e-business, e-learning etc. In any such communications network it is crucial to be able to authenticate both the contents and the origin of a message. Digital signatures (based on public key schemas) are used for authentication and ideally they should provide the same guarantees as a handwritten signatures: unforgeability (only the author of a message should be able to sign his name to a message), undeniability (the author of a message should not be able to deny he signed it at a later stage) and authentication (the signature should allow the contents of the message to be authenticated). In order to provide message authentication the signature must depend on the contents of the message being signed. Two major problems with the public key-based signature schemes are that they are existentially forgeable and if the message is long then the signature will take a long time to compute. To overcome both of these problems hash functions that map a (possibly lengthy) message M to a small digest h(M) are used. Among other desirable properties (the length of h(M) should be small, the function h should be a publicly known one-way function, it should destroy algebraic relationships between messages and signatures), an interesting one is that it should be 'collision-resistant', that is it should be difficult to find two messages with the same hash value. To find a collision the birthday attack is used, which shows that attacker may not need to examine too many messages before he finds a collision. If attacker generates random messages and computes their hash values then with probability at least ½ he finds a collision after generating √(2|R|) messages, where |R| is the total number of possible hash values for the corresponding hash function. The real situation is even worse. In previous estimates it is always assumed that the hash function is regular, meaning that all points in the range have the same number of pre-images under h. If h is not regular, fewer trials are required. Here we examine different types of irregularity of the hash function and the quantitative changes in the required number of trials to find a collision.
The impact of process choice in high maturity environments: An empirical analysis
Authors: Narayan Ramasubbu, Rajesh Krishna Balan
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

We present the results of a three year field study of the software development process choices made by project teams at two leading offshore vendors. In particular, we focus on the performance implications of project teams that chose to augment structured, plan-driven processes to implement the CMM level-5 Key Process Areas (KPAs) with agile methods. Our analysis of 112 software projects reveals that the decision to augment the firm-recommended, plan-driven approach with improvised, agile methods was significantly affected by the extent of client knowledge and involvement, the newness of technology, and the project size. Furthermore this decision had a significant and mostly positive impact on project performance indicators such as reuse, rework, defect density, and productivity
Towards a Complex Automata Multiscale Model of In-Stent Restenosis
Authors: Alfonso Caiazzo, David Evans, Jean-Luc Falcone, Jan Hegewald, Eric Lorenz, Bernd Stahl, Dinan Wang, Jörg Bernsdorf, Bastien Chopard, Julian Gunn, Rod Hose, Manfred Krafczyk, Patricia Lawford, Rod Smallwood, Dawn Walker, Alfons G. Hoekstra
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale problem involving a large number of processes. We describe a Complex Automata Model for in-stent restenosis, coupling a bulk flow, drug diffusion, and smooth muscle cell model, all operating on different time scales. Details of the single scale models and of the coupling interfaces are described, together with first simulation results, obtained with a dedicated software environment for Complex Automata simulations. The results show that the model can reproduce growth trends observed in experimental studies.
Visualization by Linear Projections as Information Retrieval
Authors: Jaakko Peltonen
Venue: Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps (2009)

We apply a recent formalization of visualization as information retrieval to linear projections. We introduce a method that optimizes a linear projection for an information retrieval task: retrieving neighbors of input samples based on their low-dimensional visualization coordinates only. The simple linear projection makes the method easy to interpret, while the visualization task is made well-defined by the novel information retrieval criterion. The method has a further advantage: it projects input features, but the input neighborhoods it preserves can be given separately from the input features, e.g. by external data of sample similarities. Thus the visualization can reveal the relationship between data features and complicated data similarities. We further extend the method to kernel-based projections.
An SLA-based resource virtualization approach for on-demand service provision
Authors: Attila Kertesz, Gabor Kecskemeti, Ivona Brandic
Venue: Proceedings of the 3rd international workshop on Virtualization technologies in distributed computing (2009)

Cloud computing is a newly emerged research infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business processes and virtualization. In this paper we present an architecture for SLA-based resource virtualization that provides an extensive solution for executing user applications in Clouds. This work represents the first attempt to combine SLA-based resource negotiations with virtualized resources in terms of on-demand service provision resulting in a holistic virtualization approach. The architecture description focuses on three topics: agreement negotiation, service brokering and deployment using virtualization. The contribution is also demonstrated with a real-world case study.
Performance analysis of mobile IP registration protocols
Authors: S. Rathi, K. Thanushkodi
Venue: WSEAS Transactions on Computers (2009)

Mobile IPv6 will be an integral part of the next generation Internet protocol. The importance of mobility in the Internet gets keep on increasing. Current specification of Mobile IPv6 does not provide proper support for security in the mobile network and there are other problems associated with it. This paper is concerned with security aspects of the Registration protocols in Mobile IP. Providing security in Mobile IP registration is highly important. The registration part must be guarded against any malicious attacks that might try to take illegitimate advantage from any participating principal. This paper deals with the performance analysis of various protocols available for Mobile IP registration. The parameters considered for comparison are: Data confidentiality, Authentication, Attack prevention, Registration delay and Computational complexity. This paper aims to determine the protocol which outperforms others when the parameters mentioned above are taken into consideration.