ppxscal/embedding_network huggingface dataset:
The Best of MAKE
Authors: Mark Frauenfelder, Gareth Branwyn
Venue: Make 75 Projects From The Pages Of Make (2007)

After two years, MAKE has become one of most celebrated new magazines to hit the newsstands, and certainly one of the hottest reads. If you're just catching on to the MAKE phenomenon and wonder what you've missed, this book contains the best DIY projects from the magazine's first ten volumes -- a surefire collection of fun and challenging activities going back to MAKE's launch in early 2005. Find out why MAKE has attracted a passionate following of tech and DIY enthusiasts worldwide with one million web site visitors and a quarter of a million magazine readers. And why our podcasts consistently rank in the top-25 for computers and technology. With the Best of MAKE, you'll share the curiosity, zeal, and energy of Makers -- the citizen scientists, circuit benders, homemakers, students, automotive enthusiasts, roboticists, software developers, musicians, hackers, hobbyists, and crafters -- through this unique and inspiring assortment of DIY projects chosen by the magazine's editors. Learn to: Hack your gadgets and toys Program micontrollers to sense and react to things Take flight with rockets, planes, and other projectiles Make music from the most surprising of things Find new ways to take photos and make video Outfit yourself with the coolest tools Put together by popular demand, the Best of MAKE is the perfect gift for any maker, including current subscribers who missed early volumes of the magazine. Do you or someone you know have a passion for the magic of tinkering, hacking, and creation? Do you enjoy finding imaginative and unexpected uses for the technology and materials in your life? Then get on board with the Best of MAKE!
Pairwise sequence alignment algorithms: a survey
Authors: Waqar Haque, Alex Aravind, Bharath Reddy
Venue: Proceedings of the 2009 conference on Information Science, Technology and Applications (2009)

Pairwise sequence alignment is a fundamental compute-intensive problem in bioinformatics that has helped researchers analyse biological sequences. The analysis has helped biologists detect pathogens, develop drugs, and identify common genes. The biological sequence database has been growing rapidly due to new sequences being discovered. This has brought many new challenges including sequence database searching and aligning long sequences. To solve these problems, many sequence alignment algorithms have been developed. These algorithms employ various techniques to efficiently find optimal or nearly-optimal alignments. In this paper, we present the popular past and recent work on both local and global pairwise sequence alignment algorithms. In addition to identifying the techniques used, the advantages and limitations of the algorithms are also presented.
Cryptology as College Outreach to Young Teens
Authors: David E. Boliver
Venue: Cryptologia (2009)

During the last decade, the author has been privileged to run 8 years of Summer academies serving students aged 13-15 and focused on elementary cryptology as a hook for involving them in preparation for a future college career in the STEM (science, technology, engineering, or mathematical) disciplines. Students have been highly enthusiastic about this program and it has often had over 100 applicants for 60 spaces. These students learn the meaning of number congruences, and how to solve them algebraically. They use this knowledge to encrypt and decrypt messages using both the Euler Phi-function and the Chinese Remainder Theorem. They also prepare extensive reviews of possible collegiate futures for themselves, including both academic and financial planning for those futures. We will show how other campuses can implement similar programs to engender an increased supply of students who are appreciative users of mathematics. We also comment on the positive career effect on undergraduate mathematics teaching majors employed as staff.
Verification of authentication protocols for epistemic goals via SAT compilation
Authors: Kai-Le Su, Qing-Liang Chen, Abdul Sattar, Wei-Ya Yue, Guan-Feng Lv, Xi-Zhong Zheng
Venue: Journal of Computer Science and Technology (2006)

This paper introduces a new methodology that uses knowledge structures, a specific form of Kripke semantics for epistemic logic, to analyze communication protocols over hostile networks. The paper particularly focuses on automatic verification of authentication protocols. Our approach is based on the actual definitions of a protocol, not on some difficult-to-establish justifications. The proposed methodology is different from many previous approaches to automatic verification of security protocols in that it is justification-oriented instead of falsification-oriented, i.e., finding bugs in a protocol. The main idea is based on observations: separating a principal executing a run of protocol from the role in the protocol, and inferring a principal's knowledge from the local observations of the principal. And we show analytically and empirically that this model can be easily reduced to Satisfiability (SAT) problem and efficiently implemented by a modern SAT solver.
How Do We More Greatly Ensure Responsible AGI?
Authors: Eiezer Yudkowsky, Jeff Medina, Karl H. Pribram, Ari Heljakka, Hugo de Garis, Stephan Vladimir Bugaj
Venue: Proceeding of the 2007 conference on Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the AGI Workshop 2006 (2007)

At the end of the 2006 AGI Workshop, a number of presenters were invited to participate in a panel discussion on the theme “How Do We More Greatly Ensure Responsible AGI?” This chapter presents a record of that dialogue, including audience participation, lightly edited by the presenters themselves for greater readability.
Structure-Based Partitioning of Large Ontologies
Authors: Heiner Stuckenschmidt, Anne Schlicht
Venue: Modular Ontologies: Concepts, Theories and Techniques for Knowledge Modularization (2009)

In this chapter we describe a method for structure-based ontology partitioning and its implementation that is practically applicable to very large ontologies. We show that a modularization based on structural properties of the ontology only already results in modules that intuitively make sense. The method was used for creating an overview graph for ontologies and for extracting key topics from an ontology that correspond to topics selected by human experts. Because the optimal modularization of an ontology greatly depends on the application it is used for, we implemented the partitioning algorithm in a way that allows for adaption to different requirements. Furthermore this adaption can be performed automatically by specifying requirements of the application.
A sequential algorithm for biological event detection using statistical nonstationarity
Authors: John Dicecco
Venue:  (2008)

High dimension complex dynamical systems, such as those found in physiological processes, produce time series which are often accompanied by nonstationarity. In many cases, the nonstationarity is caused by a physiologically significant event such as the prelude to ventricular fibrillation in cardiac arrest or the change of stasis by introducing pharmaceuticals. A need exists to be able to detect and monitor this change. Most conventional attempts at addressing this problem involve segmenting the time series and evaluating the statistics of the segments. The difficulty with this approach is that the nature of the nonstationarity can be transient, such that it is bounded by two, or more, regions of stationarity. This oscillation may continue for a significant portion of the time series. This research will address the underlying statistical justification for asserting stationarity and linearity as well as the use of segmentation time series analysis techniques. 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
Monitoring of landscape change for waste land rehabilitation in Haizhou opencast coal mine
Authors: Yingyi Chen, Daoliang Li
Venue: WSEAS Transactions on Information Science and Applications (2009)

Land rehabilitation is being carried out throughout the whole country. But in many areas, the main purpose of land rehabilitation is to increase the overall cultivated land area which neglects the eco-construction. Important tasks of modern landscape ecology are to monitor and assess natural resources, to examine the impacts and effects of human intervention and, last but not least, to observe the state of the environment over long periods of time. The objective of this research was to create a method for land rehabilitation project using landscape ecology by combining Geographical Information Systems (GIS) and Landscape Ecology Analysis (LEA). GIS technologies were developed for the digital preparation and analysis of historical maps, and subsequent digital land use mapping. The landscape spatial pattern and influence on landscape were expressed by dominance index, contagion index, cohesion index, etc. Applying those landscape ecology indexes landscape spatial pattern influence caused by the land development and rehabilitation planning of Haizhou coal mine waste area was studied by comparing landscape characteristics between those before and after planning implementation. The analysis of the structural landscape changes proved to be an important aspect.
Trust and Satisfaction, Two Stepping Stones for Successful E-Commerce Relationships: A Longitudinal Exploration
Authors: Dan J. Kim, Donald L. Ferrin, H. Raghav Rao
Venue: Information Systems Research (2009)

Trust and satisfaction are essential ingredients for successful business relationships in business-to-consumer electronic commerce. Yet there is little research on trust and satisfaction in e-commerce that takes a longitudinal approach. Drawing on three primary bodies of literature, the theory of reasoned action, the extended valence framework, and expectation-confirmation theory, this study synthesizes a model of consumer trust and satisfaction in the context of e-commerce. The model considers not only how consumers formulate their prepurchase decisions, but also how they form their long-term relationships with the same website vendor by comparing their prepurchase expectations to their actual purchase outcome. The results indicate that trust directly and indirectly affects a consumer's purchase decision in combination with perceived risk and perceived benefit, and also that trust has a longer term impact on consumer e-loyalty through satisfaction. Thus, this study extends our understanding of consumer Internet transaction behavior as a three-fold (prepurchase, purchase, and postpurchase) process, and it recognizes the crucial, multiple roles that trust plays in this process. Implications for theory and practice as well as limitations and future directions are discussed.
Simultaneous genes and training samples selection by modified particle swarm optimization for gene expression data classification
Authors: Qi Shen, Zhen Mei, Bao-Xian Ye
Venue: Computers in Biology and Medicine (2009)

Gene expression datasets is a means to classify and predict the diagnostic categories of a patient. Informative genes and representative samples selection are two important aspects for reducing gene expression data. Identifying and pruning redundant genes and samples simultaneously can improve the performance of classification and circumvent the local optima problem. In the present paper, the modified particle swarm optimization was applied to selecting optimal genes and samples simultaneously and support vector machine was used as an objective function to determine the optimum set of genes and samples. To evaluate the performance of the new proposed method, it was applied to three publicly available microarray datasets. It has been demonstrated that the proposed method for gene and sample selection is a useful tool for mining high dimension data.
Face recognition across pose: A review
Authors: Xiaozheng Zhang, Yongsheng Gao
Venue: Pattern Recognition (2009)

One of the major challenges encountered by current face recognition techniques lies in the difficulties of handling varying poses, i.e., recognition of faces in arbitrary in-depth rotations. The face image differences caused by rotations are often larger than the inter-person differences used in distinguishing identities. Face recognition across pose, on the other hand, has great potentials in many applications dealing with uncooperative subjects, in which the full power of face recognition being a passive biometric technique can be implemented and utilised. Extensive efforts have been put into the research toward pose-invariant face recognition in recent years and many prominent approaches have been proposed. However, several issues in face recognition across pose still remain open, such as lack of understanding about subspaces of pose variant images, problem intractability in 3D face modelling, complex face surface reflection mechanism, etc. This paper provides a critical survey of researches on image-based face recognition across pose. The existing techniques are comprehensively reviewed and discussed. They are classified into different categories according to their methodologies in handling pose variations. Their strategies, advantages/disadvantages and performances are elaborated. By generalising different tactics in handling pose variations and evaluating their performances, several promising directions for future research have been suggested.
Distributed control systems with incomplete and uncertain information
Authors: Kendall E. Nygard
Venue:  (2008)

Scientific and engineering advances in wireless communication, sensors, propulsion, and other areas are rapidly making it possible to develop unmanned air vehicles (UAVs) with sophisticated capabilities. UAVs have come to the forefront as tools for airborne reconnaissance to search for, detect, and destroy enemy targets in relatively complex environments. They potentially reduce risk to human life, are cost effective, and are superior to manned aircraft for certain types of missions. It is desirable for UAVs to have a high level of intelligent autonomy to carry out mission tasks with little external supervision and control. This raises important issues involving tradeoffs between centralized control and the associated potential to optimize mission plans, and decentralized control with great robustness and the potential to adapt to changing conditions. UAV capabilities have been extended several ways through armament (e.g., Hellfire missiles on Predator UAVs), increased endurance and altitude (e.g., Global Hawk), and greater autonomy. Some known barriers to full-scale implementation of UAVs are increased communication and control requirements as well as increased platform and system complexity. One of the key problems is how UAV systems can handle incomplete and uncertain information in dynamic environments. Especially when the system is composed of heterogeneous and distributed UAVs, the overall system complexity is increased under such conditions. Presented through the use of published papers, this dissertation lays the groundwork for the study of methodologies for handling incomplete and uncertain information for distributed control systems. An agent-based simulation framework is built to investigate mathematical approaches (optimization) and emergent intelligence approaches. The first paper provides a mathematical approach for systems of UAVs to handle incomplete and uncertain information. The second paper describes an emergent intelligence approach for UAVs, again in handling incomplete and uncertain information. The third paper combines mathematical and emergent intelligence approaches.
Employment Horizon and the Choice of Performance Measures: Empirical Evidence from Annual Bonus Plans of Loss-Making Entities
Authors: Michal Matějka, Kenneth A. Merchant, Wim A. Van der Stede
Venue: Management Science (2009)

We examine the extent to which employment horizon concerns affect the relative emphasis on financial versus nonfinancial performance measures in annual bonus plans. We argue that managers of loss-making firms are likely to voluntarily or forcibly depart in the near future and, consequently, have a shorter employment horizon. Loss-making firms then need to increase the emphasis on forward-looking nonfinancial performance measures to motivate long-term effort of their managers. Thus, we hypothesize that the emphasis on nonfinancial performance measures is greater in loss making than in profitable firms even after controlling for the informativeness of earnings. We find consistent support for our hypothesis using different (archival, survey, and field) data sources and various proxies for short employment horizon and the emphasis on nonfinancial performance measures.
Do developers search for source code examples using multiple facts?
Authors: Reid Holmes
Venue: Proceedings of the 2009 ICSE Workshop on Search-Driven Development-Users, Infrastructure, Tools and Evaluation (2009)

In this paper we examine the search behaviours of developers using the Strathcona source code example recommendation system over the period of three years. In particular, we investigate the number of query facts software engineers included in their queries as they searched for source code examples. We found that in practice developers predominantly searched with multiple search facts and tended to constrain their queries by iteratively adding more facts as needed. Our experience with this data suggest that example search tools should both support searching with multiple facts as well and facilitate the construction of multi-fact queries.
A Design for Library Marketing System and Its Possible Applications
Authors: Toshiro Minami
Venue: Knowledge Acquisition: Approaches, Algorithms and Applications: Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, Hanoi, Vietnam, December 15-16, 2008, Revised Selected Papers (2009)

Library marketing system is a system that helps with improving patrons' convenience and library management based on the data in libraries by analyzing them with data mining methods, including statistical ones. In this paper we present a design of such a system which deals with usage data of materials and extracts knowledge and tips that are useful, for example, for better arrangements of bookshelves and for providing patrons with information which will attract the patrons. Two methods are proposed for collecting usage data from bookshelves; one is with RFID and the other is with two-dimensional code, such as the QR code that is very popularly used in mobile phones. By combining several analysis methods, we can construct a library marketing system, which will give benefits to library management and patron services.
Learning teamwork skills in university programming courses
Authors: Pilar Sancho-Thomas, Rubén Fuentes-Fernández, Baltasar Fernández-Manjón
Venue: Computers Education (2009)

University courses about computer programming usually seek to provide students not only with technical knowledge, but also with the skills required to work in real-life software projects. Nowadays, the development of software applications requires the coordinated efforts of the members of one or more teams. Therefore, it is important for software professionals to master the sort of skills that assure the success of teamwork, such as communication, leadership, negotiation, or team management. However, these abilities are difficult to teach, one of the reasons being that they require true commitment from the students. However, today students are taking a more and more passive role in their own education, two of the more evident consequences being the increase in dropout rates and the decrease in marks obtained in exams. The NUCLEO e-learning framework has been designed to promote the effective acquisition of teamwork skills and, at the same time, to promote the more active participation of the students in their own learning process. NUCLEO adopts a socio-constructivist pedagogical approach that pursues the development of communities of practice for Problem Based Learning. Our research has rooted the design decisions of NUCLEO in the analysis of its socio-cultural environment with Activity Theory, which considers conflicts within groups as the impetus of their evolution and the forges of their environments. This paper presents the analysis of the main features of NUCLEO according to Activity Theory, as well as the experimental results obtained with the framework in three different case studies in university courses.
Harmony - Advance Reservations in Heterogeneous Multi-domain Environments
Authors: Alexander Willner, Christoph Barz, Joan Antoni Garcia Espin, Jordi Ferrer Riera, Sergi Figuerola, Peter Martini
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

Grid computing aims at offering standardized access to heterogeneous and distributed resources for scientific communities. In order to ensure certain quality of service requirements, the interconnecting networks have also be considered as Grid resources and must be taken into account for the co-scheduling process. However, most current systems do not support co-allocation of heterogeneous network resource provisioning systems and malleable advance reservations in multi-domain, multi-technology, and multi-vendor environments. Our approach, called Harmony, provides a functional service plane to unify the underlying network management systems and supports advanced reservation capabilities to utilize the available capacity and network resources in an efficient manner. The developed prototype has been demonstrated on numerous conferences and a preliminary performance evaluation of the current implementation is given.
Digital Master
Authors: Gary Singh
Venue: IEEE Computer Graphics and Applications (2009)

Randy Kochis enjoys the freedom of correcting gaffes, improvising, and the overall process of trial and error in digital art. He uses Photoshop, layering filter effects so that he gets more intricate patterns, depth, color, and shadows.
Siberian silkmoth outbreak pattern analysis based on SPOT VEGETATION data
Authors: V. I. Kharuk, K. J. Ranson, S. T. Im
Venue: International Journal of Remote Sensing (2009)

The spatial pattern of Siberian silkmoth outbreak in south Siberian mountains was analysed based on SPOT VEGETATION data. A digital elevation model (DEM) was also used to relate outbreak area dynamics with topographic elements (elevation, azimuth and slope steepness). To avoid bias of spatial pattern data, areas with a given damage category and with given azimuth, slope steepness and elevation were referenced to the areas with similar parameters within the entire study area. The outbreak began between the elevations of ∼430-480 m and on south-west slopes with steepness