ppxscal/embedding_network huggingface dataset:
A novel neural network model upon biological and electrical perceptions
Authors: Saki Yatano, Atsushi Fukasawa, Yumi Takizawa
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

Modeling of a neural network (NN) is presented. This study is targeted to compose a highly capable processor. Proposed model is based on knowledge of biological and artificial NN developed until nowadays. An advantage of the proposed model is forward and reverses couplings with positive and negative signs for synaptic coupling of neurons. Neurons are connected mutually and allocated multiple accesses, total large numbers of neurons are included in the NN is the second advantage. The other point is that operation of NN is done with timing is synchronously. The size of NN is far large than ever proposed. The proposed model is applied for the analysis of time-space data analysis. This scheme was found sufficiently useful to solve the problem which was impossible to be solved.
Hypercalculia for the mind emulation
Authors: Alexis Lemaire, Francis Rousseaux
Venue: AI Society (2009)

By imitating the high-speed computational behavior of a machine through a consciousness of the future, we suggest a reverse artificial intelligence in an attempt to achieve the computational whole mind emulation of high level thoughts. The methodology, using such reverse artificial intelligence which we run with control on the mind instead of a machine, is disclosed. We then generalize this ability to enable the proposed mind emulation through high-speed mental computation processes. We suggest a set of theoretical and empirical principles and methods for the mind transfer, which leads to an almost unlimited potential for the human beings and society. In this paper, we present the most basic case of experimenting with the inactive behaviors, then a new hypothesis.
Bringing your dead links back to life: a comprehensive approach and lessons learned
Authors: Atsuyuki Morishima, Akiyoshi Nakamizo, Toshinari Iida, Shigeo Sugimoto, Hiroyuki Kitagawa
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

This paper presents an experimental study of the automatic correction of broken (dead) Web links focusing, in particular, on links broken by the relocation ofWeb pages. Our first contribution is that we developed an algorithm that incorporates a comprehensive set of heuristics, some of which are novel, in a single unified framework. The second contribution is that we conducted a relatively large-scale experiment, and analysis of our results revealed the characteristics of the problem of finding movedWeb pages. We demonstrated empirically that the problem of searching for moved pages is different from typical information retrieval problems. First, it is impossible to identify the final destination until the page is moved, so the index-server approach is not necessarily effective. Secondly, there is a large bias about where the new address is likely to be and crawler-based solutions can be effectively implemented, avoiding the need to search the entire Web. We analyzed the experimental results in detail to show how important each heuristic is in real Web settings, and conducted statistical analyses to show that our algorithm succeeds in correctly finding new links for more than 70% of broken links at 95% confidence level.
IT LAw - an ISEB Foundation, 1st edition
Authors: John Antell, Jonathan Exell, Jon Fell
Venue:  (2007)

IT professionals not only need to know the technology, they should also be aware of how the law applies to the technology. This is a guide to the main aspects of Law that an IT professional is most likely to come up against. In an increasingly digital society, computer law has an ever widening impact. This book gives the reader a thorough introduction to increasingly important areas such as corporate governance, data protection, computer misuse, digital rights management and intellectual property law. This is a textbook for the 'ISEB Foundation Certificate in IT Law'.
On the design and optimization of symmetric low swing to high swing level converter for on-chip interconnects
Authors: José C. García, Juan A. Montiel-Nelson, Saeid Nooshabadi
Venue: Analog Integrated Circuits and Signal Processing (2009)

This paper reports a series of symmetric high performance, low to full swing level converters (udld1-converter to udld5-converter) for recovering signal levels at the receiver end of the global interconnects with large capacitive loads. The proposed udld5-converter provides a matching receiver for the up-down low swing voltage driver (UDLD) signaling style for driving the global interconnect lines. When implemented on 0.13 μm CMOS 1.2 V technology, the udld5-converter performs 16% faster, reduces the energy per switching event by 4%, the energy-delay product by 19%, and the active area by 10%, when compared with a counterpart up low swing voltage driver (ULD) level converter (uld-converter). The proposed level converter receivers, each provide a different performance energy saving trade off. The paper also provides comparative performance evaluation of the various proposed level converters and uld-converter.
Web Page Clustering via Partition Adaptive Affinity Propagation
Authors: Changyin Sun, Yifan Wang, Haina Zhao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Clustering techniques have been applied to categorize documents on Web and extract knowledge from Web. In this paper, we introduce a novel clustering method into Web page clustering, which is an extension of affinity propagation (AP). This method is called partition adaptive affinity propagation (PAAP), which can automatically rerun AP procedure to yield optimal clustering results and eliminate number oscillations if they occur. Experiments are carried out to compare PAAP with K-means and AP on ten different Web page data sets. The results verify that PAAP can find better clusters when compared with similar methods. And the results also demonstrate that PAAP is robust and effective when clustering Web pages.
Build Your Own PC Do-It-Yourself For Dummies
Authors: Mark L. Chambers
Venue: For Dummies (2009)

If youve dreamed about having a customized multimedia PC or one tricked out for your favorite games, build your own and make your dreams come true! Build Your Own PC Do-It-Yourself For Dummies makes it easy. Not only is building your own PC a really rewarding project, it can also save you a nice chunk of cash. This step-by-step guide helps you decide what you need, teaches you what all those computer terms mean, and tells you exactly how to put the pieces together. It shows you: What tools you need (not as many as you might think!) All about operating systems How to install CD and DVD drives The scoop on sound and video, and how to put a sound system together from start to finish How to connect a monitor and install a modem All about setting up and configuring the hard drive Secrets for securing your system, and more Included is a bonus DVD showing you how to install the motherboard, CPU, RAM, ports, hard drive, video and sound cards, a DVD drive, and more. With Build Your Own PC Do-It-Yourself For Dummies, you can have the computer you want plus the satisfaction of doing it yourself!
A case study on compiler optimizations for the Intel® Core™ 2 duo processor
Authors: Aart J. C. Bik, David L. Kreitzer, Xinmin Tian
Venue: International Journal of Parallel Programming (2008)

The complexity of modern processors poses increasingly more difficult challenges to software optimization. Modern optimizing compilers have become essential tools for leveraging the power of recent processors by means of high-level optimizations to exploit multi-core platforms and single-instruction-multiple-data (SIMD) instructions, as well as advanced code generation to deal with microarchitectural performance aspects. Using the Intel®Core™2 Duo processor and Intel Fortran/C++ compiler as a case study, this paper gives a detailed account of the sort of optimizations required to obtain high performance on modern processors.
Multi-core parallelization in Clojure: a case study
Authors: Johann M. Kraus, Hans A. Kestler
Venue: Proceedings of the 6th European Lisp Workshop (2009)

In recent years, the demand for computational power in data mining applications has increased due to rapidly growing data sets. As a consequence, standard algorithms need to be parallelized for fast processing of the generated data sets. Unfortunately, most approaches for parallelizing algorithms require a careful software design and a deep knowledge about thread-safe programming. As a consequence they are hardly applicable for rapid prototyping of new algorithms. We outline the process of multi-core parallelization using Clojure, a new functional programming language utilizing the Java Virtual Machine (JVM) that does not require knowledge of thread-safe programming. We provide some benchmark results for our multi-core algorithm to demonstrate its computational power. The rationale behind Clojure is combining the industry-standard JVM with functional programming, immutable data structures, and a built-in concurrency support via software transactional memory. This makes it a suitable tool for parallelization and rapid prototyping in many areas. In this case study we present a multi-core parallel implementation of the k-means cluster algorithm. The multi-core algorithm shows an increase in computation speed up to a factor of 10 compared to R or network based parallelization.
Assessing the efficacy of a mixed-modal auditory display system for enhancing auditory sensation
Authors: Si-Jung Kim, Jennifer Thangjitham, Woodrow Winchester
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

This paper presents the design and evaluation of a new type of mixed-modal auditory display for enhancing auditory sensation. The purpose of this study is to determine whether or not a light apparatus in which LED lights are installed in front of a speaker panel and alternating lights based on sound frequency and intensity can support user awareness of the auditory source. Five different auditory sources were used, and a user study with 20 participants revealed that all auditory sources were better recognized when listened to with the light apparatus. The music and the emergency alert auditory source were best represented by the light apparatus. The experiment showed synchronized visual and audio representation enhanced the user's auditory sensation. Findings suggest that the light apparatus could be useful when auditory signal displays are not universally applicable because people who suffer from hearing loss are unable to use them effectively. It is expected that the result of this study could contribute to the design of hearing aids, emergency alarm device/mechanisms, communication trust or other assistive technologies that seek to provide context to received data.
Automated Design Space Exploration for DSP Applications
Authors: Ramsey Hourani, Ravi Jenkal, W. Rhett Davis, Winser Alexander
Venue: Journal of Signal Processing Systems (2009)

We present a performance analysis framework that efficiently generates and analyzes hardware designs for computationally intensive signal processing applications. Our framework synthesizes designs from a high level of abstraction into well-constructed and recognizable hardware structures that perform well in terms of area, throughput and power dissipation. Cost functions provided by our framework allow the user to reduce the design space to a set of efficient hardware implementations that meet performance constraints. We utilize our framework to estimate hardware performance using a set of pre-synthesized mathematical cores which expedites the synthesis process by approximately 14 fold. This reduces the architectural generation and hardware synthesis process from days to several hours for complex designs. Our work aims at performing hardware optimizations at the architectural and arithmetic levels, relieving the user from manually describing the designs at the register transfer level and iteratively varying the hardware structures. We illustrate the efficiency and accuracy of our framework by generating finite impulse response filter structures used in several signal processing applications such as adaptive equalizers and quadrature mirror filters. The results show that hardware filter structures generated by our framework can achieve, on average, a 3 fold increase in power efficiency when compared to manually constructed designs.
Model-guided autotuning of high-productivity languages for petascale computing
Authors: Hans Zima, Mary Hall, Chun Chen, Jaqueline Chame
Venue: Proceedings of the 18th ACM international symposium on High performance distributed computing (2009)

addresses the enormous complexity of mapping applications to current and future highly parallel platforms - including scalable architectures consisting of tens of thousands of nodes, many-core devices with tens to hundreds of cores, and hierarchical systems providing multi-level parallelism. At systems of these scales, for many important algorithms, performance is dominated by the time required to move data across the levels of the memory hierarchy. As a consequence, locality awareness of algorithms and the efficient management of communication are essential requirements for obtaining scalable parallel performance, and are of particular concern for applications characterized by irregular memory access patterns. We describe the design of a programming system that focuses on productivity of application programmers in expressing locality-aware algorithms for high-end architectures, which are then automatically tuned for performance. The approach combines the successes of two novel concepts for managing locality: high-level specification of user-defined data distributions and model-guided autotuning for data locality. The resulting combined system provides a powerful general mechanism for the specification of data distributions, which can express domain-specific knowledge, and facilitates automatic tuning of a distribution to access patterns in algorithms and its application to different levels of a memory hierarchy. Because there is a clean separation between the specification of a data distribution and the algorithms in which it is used, these can be written separately and composed together to quickly develop new applications that can be tuned in the context of their data set and execution environment. We address key issues for a range of codes that include LU Decomposition, Sparse Matrix-Vector Multiply and Knowledge Discovery. The knowledge discovery algorithms, in particular, stress the proposed language and compiler technology and provide a forcing function for developing tools that address inherent challenges of irregular applications.}
Empirically building and evaluating a probabilistic model of user affect
Authors: Cristina Conati, Heather Maclaren
Venue: User Modeling and User-Adapted Interaction (2009)

We present a probabilistic model of user affect designed to allow an intelligent agent to recognise multiple user emotions during the interaction with an educational computer game. Our model is based on a probabilistic framework that deals with the high level of uncertainty involved in recognizing a variety of user emotions by combining in a Dynamic Bayesian Network information on both the causes and effects of emotional reactions. The part of the framework that reasons from causes to emotions (diagnostic model) implements a theoretical model of affect, the OCC model, which accounts for how emotions are caused by one's appraisal of the current context in terms of one's goals and preferences. The advantage of using the OCC model is that it provides an affective agent with explicit information not only on which emotions a user feels but also why, thus increasing the agent's capability to effectively respond to the users' emotions. The challenge is that building the model requires having mechanisms to assess user goals and how the environment fits them, a form of plan recognition. In this paper, we illustrate how we built the predictive part of the affective model by combining general theories with empirical studies to adapt the theories to our target application domain. We then present results on the model's accuracy, showing that the model achieves good accuracy on several of the target emotions. We also discuss the model's limitations, to open the ground for the next stage of the work, i.e., complementing the model with diagnostic information.
Estimating myocardial motion by 4D image warping
Authors: Hari Sundar, Harold Litt, Dinggang Shen
Venue: Pattern Recognition (2009)

A method for spatio-temporally smooth and consistent estimation of cardiac motion from MR cine sequences is proposed. Myocardial motion is estimated within a four-dimensional (4D) registration framework, in which all three-dimensional (3D) images obtained at different cardiac phases are simultaneously registered. This facilitates spatio-temporally consistent estimation of motion as opposed to other registration-based algorithms which estimate the motion by sequentially registering one frame to another. To facilitate image matching, an attribute vector (AV) is constructed for each point in the image, and is intended to serve as a ''morphological signature'' of that point. The AV includes intensity, boundary, and geometric moment invariants (GMIs). Hierarchical registration of two image sequences is achieved by using the most distinctive points for initial registration of two sequences and gradually adding less-distinctive points to refine the registration. Experimental results on real data demonstrate good performance of the proposed method for cardiac image registration and motion estimation. The motion estimation is validated via comparisons with motion estimates obtained from MR images with myocardial tagging.
The Oea framework for class-based object-oriented style JavaScript for web programming
Authors: Musbah Sh. Sagar, David A. Duce, Muhammad Younas
Venue: Computer Standards Interfaces (2009)

In this paper we reflect on the differences between prototype-based and class-based programming languages and we introduce a new approach, called the Oea framework, that will allow JavaScript developers to write programs using a class-based style, which we assert is easy to use, has a syntax style that resembles that of the Java class-based approach and has high performance and reliability. We present a survey of the most widely used class-based techniques for JavaScript describing their methods and highlighting their shortcomings and compare the new approach with this earlier work. The approach has been developed in the context of a framework for developing Web applications using Scalable Vector Graphics (SVG), JavaScript and the Resource Description Framework (RDF) which involved the construction of substantial libraries and other code using the approach.
Sybil-resilient online content voting
Authors: Nguyen Tran, Bonan Min, Jinyang Li, Lakshminarayanan Subramanian
Venue: Proceedings of the 6th USENIX symposium on Networked systems design and implementation (2009)

Obtaining user opinion (using votes) is essential to ranking user-generated online content. However, any content voting system is susceptible to the Sybil attack where adversaries can out-vote real users by creating many Sybil identities. In this paper, we present SumUp, a Sybilresilient vote aggregation system that leverages the trust network among users to defend against Sybil attacks. SumUp uses the technique of adaptive vote flow aggregation to limit the number of bogus votes cast by adversaries to no more than the number of attack edges in the trust network (with high probability). Using user feed-back on votes, SumUp further restricts the voting power of adversaries who continuously misbehave to below the number of their attack edges. Using detailed evaluation of several existing social networks (YouTube, Flickr), we show SumUp's ability to handle Sybil attacks. By applying SumUp on the voting trace of Digg, a popular news voting site, we have found strong evidence of attack on many articles marked "popular" by Digg.
Virtual craniofacial reconstruction using computer vision, graph theory and geometric constraints
Authors: Ananda S. Chowdhury, Suchendra M. Bhandarkar, Robert W. Robinson, Jack C. Yu
Venue: Pattern Recognition Letters (2009)

A novel solution to the problem of virtual craniofacial reconstruction using computer vision, graph theory and geometric constraints is proposed. Virtual craniofacial reconstruction is modeled along the lines of the well-known problem of rigid surface registration. The Iterative Closest Point (ICP) algorithm is first employed with the closest set computation performed using the Maximum Cardinality Minimum Weight (MCMW) bipartite graph matching algorithm. Next, the bounding boxes of the fracture surfaces, treated as cycle graphs, are employed to generate multiple candidate solutions based on the concept of graph automorphism. The best candidate solution is selected by exploiting local and global geometric constraints. Finally, the initialization of the ICP algorithm with the best candidate solution is shown to improve surface reconstruction accuracy and speed of convergence. Experimental results on Computed Tomography (CT) scans of real patients are presented.
Sequencing and Counting with the multicost-regular Constraint
Authors: Julien Menana, Sophie Demassey
Venue: Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2009)

This paper introduces a global constraint encapsulating a regular constraint together with several cumulative costs. It is motivated in the context of personnel scheduling problems, where a schedule meets patterns and occurrence requirements which are intricately bound. The optimization problem underlying the multicost-regular constraint is NP-hard but it admits an efficient Lagrangian relaxation. Hence, we propose a filtering based on this relaxation. The expressiveness and the efficiency of this new constraint is experimented on personnel scheduling benchmark instances with standard work regulations. The comparative empirical results show how multicost-regular can significantly outperform a decomposed model with regular and global-cardinality constraints.
Display and analysis of historical and instrumental seismological data pertaining to India and adjoining regions, using the Java-based software application-'Kampan 2006'
Authors: Naveenchandra N. Srivastava, Nisha K. Dharwa, Adhisha K. Shukla, Mausami H. Thakkar, Uday J. Barad, A. R. Dasgupta
Venue: Computers Geosciences (2009)

The seismological records of past events provide insight into the seismic activities in an area. They help in preparing long-term plans to manage earthquake disasters. We present a system to display and analyse historical seismological data using the Java-based software application Kampan 2006. This interactive multi-purpose tool can display and analyse seismological data with a simple click of the mouse. The design and development of Kampan 2006 strictly followed the concepts of software engineering. We used the programming capabilities of Java to the fullest extent in developing Kampan 2006.
Structuring and Merging Distributed Content
Authors: Luca Stefanutti, Dietrich Albert, Cord Hockemeyer
Venue: Proceeding of the 2005 conference on Towards the Learning Grid: Advances in Human Learning Services (2005)

A flexible approach for structuring and merging distributed learning object is presented. At the basis of this approach there is a formal representation of a learning object, called attribute structure. Attribute structures are labeled directed graphs representing structured information on the learning objects. When two or more learning objects are merged, the corresponding attribute structures are unified, and the unified structure is attached to the resulting learning object.