ppxscal/embedding_network huggingface dataset:
php/architect's Guide to Date and Time Programming
Authors: Derick Rethans
Venue:  (2009)

If your development involves working with dates and times, then this book is a must-have. In this book, Derick Rethans (contributor to PHP's core date extension and well-known PHP expert) explores in great detail the subtle nuances of working with dates and times. Frequently PHP developers encounter unexpected results that adversely affect their software and web applications. This book will undoubtedly help them tackle those issues. This book covers a variety of areas including: history of calendars and time standards, giving the reader a better understanding of how date/time concepts evolved into the way they are today parsing date/time strings and the potential pitfalls a developer can encounter timezones, the quirks inherent in them, and how your application can handle these quirks formatting and representing times and dates correctly and dealing with the DateTime Object manipulating and working with past, future and recurring dates obtaining dates when timestamps aren't available format specifiers upgrading the master timezone database What are PHP experts saying about this book? "Complex date and time programming isn't just for international applications. Even in the US, we have to deal with up to nine different time zones, and shifting between these can be difficult. Derick is one of the most knowledgeable people I know when it comes to date and time programming. I have turned to him countless times for help, and now he brings that depth of knowledge to this book. If you need to parse dates and times, shift between time zones, or manipulate dates and times in your applications then this book is for you." - Ben Ramsey "If you ever have to deal with parsing or formatting timestamps, or dealing with timezones this is the definite reference to make your time related PHP coding tasks fast and simple!" -Elizabeth Marie Smith This is the most comprehensive book on date/time data for PHP available, and one that any PHP developer can't do without. 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
Novel Architectures: Solving Computational Problems with GPU Computing
Authors: Jonathan Cohen, Michael Garland
Venue: IEEE Design Test (2009)

Modern GPUs are massively parallel microprocessors that can deliver very high performance for the parallel computations common in science and engineering.
Extended Hidden Vector State Parser
Authors: Jan Švec, Filip Jurčíček
Venue: Proceedings of the 12th International Conference on Text, Speech and Dialogue (2009)

The key component of a spoken dialogue system is a spoken understanding module. There are many approaches to the understanding module design and one of the most perspective is a statistical based semantic parsing. This paper presents a combination of a set of modifications of the hidden vector state (HVS) parser which is a very popular method for the statistical semantic parsing. This paper describes the combination of three modifications of the basic HVS parser and proves that these changes are almost independent. The proposed changes to the HVS parser form the extended hidden vector state parser (EHVS). The performance of the parser increases from 47.7% to 63.1% under the exact match between the reference and the hypothesis semantic trees evaluated using Human-Human Train Timetable corpus. In spite of increased performance, the complexity of the EHVS parser increases only linearly. Therefore the EHVS parser preserves simplicity and robustness of the baseline HVS parser.
Game Balance Principles in MMORPG with Pet System
Authors: Linlin Shui, Guangzheng Fei, Guoyu Sun, Chi Wa Leong
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

This paper proposes a series of pet system design principles which can guarantee the game balance while successfully maintaining attractiveness to game players.
Stochastically evaluating the validity of partial parse trees in incremental parsing
Authors: Yoshihide Kato, Shigeki Matsubara, Yasuyoshi Inagaki
Venue: Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together (2004)

This paper proposes a method for evaluating the validity of partial parse trees constructed in incremental parsing. Our method is based on stochastic incremental parsing, and it incrementally evaluates the validity for each partial parse tree on a word-by-word basis. In our method, incremental parser returns partial parse trees at the point where the validity for the partial parse tree becomes greater than a threshold. Our technique is effective for improving the accuracy of incremental parsing.
Evaluation of User Interface Design and Input Methods for Applications on Mobile Touch Screen Devices
Authors: Florence Balagtas-Fernandez, Jenny Forrai, Heinrich Hussmann
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

With the advent of touch screen phones, good UI design and simplified input methods for applications running on such devices are important factors that contribute to its popularity and success. The goal of this research is to evaluate different user interface designs and input methods for mobile phones with touch screen capability. In order to do this, two prototypes of a simple social networking application were implemented using a G1 phone that runs the Android platform. A user study has been conducted to compare different input techniques and UI designs and evaluate their usability.
Multi-scale personalization for voice search applications
Authors: Daniel Bolaños, Geoffrey Zweig, Patrick Nguyen
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

Voice Search applications provide a very convenient and direct access to a broad variety of services and information. However, due to the vast amount of information available and the open nature of the spoken queries, these applications still suffer from recognition errors. This paper explores the utilization of personalization features for the post-processing of recognition results in the form of n-best lists. Personalization is carried out from three different angles: short-term, long-term and Web-based, and a large variety of features are proposed for use in a log-linear classification framework. Experimental results on data obtained from a commercially deployed Voice Search system show that the combination of the proposed features leads to a substantial sentence error rate reduction. In addition, it is shown that personalization features which are very different in nature can successfully complement each other.
An Initialization Method for Clustering High-Dimensional Data
Authors: Luying Chen, Lifei Chen, Qingshan Jiang, Beizhan Wang, Liang Shi
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In iterative refinement clustering algorithms, such as the various types of K-Means algorithms, the clustering results are very sensitive to the initial cluster centers. Conventional initialization methods tend to loss effectiveness due to the so-called "curse of dimensionality" when clustering high-dimensional data. In this paper, a local density based method is proposed to search for initial cluster centers on high-dimensional data. We define the probability density of a point as the amount of its highly similar neighborhoods with weight coefficient. Points with high density neighborhoods and low similarity are chosen as the initial cluster centers. Experimental results on real world datasets show the effectiveness of the proposed method
A Storage Scheme of Native XML Database Supporting Efficient Updates
Authors: Chenying Wang, Xiaojie Yuan, Shitao Yu, Hua Ning, Huibin Zhang
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

XML storage schemes have become an important research topic in the XML data management field. Several alternatives to manage XML documents exist, ranging from file systems over relational or other database systems to native XML database systems. This paper presents a novel storage scheme, which directly stores XML nodes as records into a paged file to build up the persistent document object model.The model retains the original tree structure of XML data, and then the updating algorithm is proposed for dynamic maintenance of the physical persistent storage. Finally several query experimental results are reported to demonstrate the superiority of our storage scheme.
A Modified Fuzzy C-means Algorithm in Remote Sensing Image Segmentation
Authors: Du Gen-yuan, Miao Fang, Tian Sheng-li, Liu Ye
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

Fuzzy C-Means (FCM) algorithm has good clustering efficiency, for which it is widely used in the field of image segmentation. However, problems such as weak robustness of distance measure, the number of initial clustering to be given in advance and not considering local image feature still exist. In essence, FCM is a local search algorithm. Improper selection of initial value will lead to the need for more iterations and convergence to local optimal solution. By combining evolving clustering (ECM) with FCM algorithm, a new method of remote sensing image segmentation is put forward. By using FCM algorithm to solve the choice of ECM's initialization clustering centers and using FCM to optimize the obtained centers, fuzzy clustering is completed. And by converting fuzzy into a certainty classification, clustering segmentation is realized. The algorithm is typical of relatively less iterations of convergence to global optimum, good stability and robustness. Experiment results show that it helps to produce better segmentation effect and improve the efficiency of remote sensing image segmentation.
Extracting influential nodes for information diffusion on a social network
Authors: Masahiro Kimura, Kazumi Saito, Ryohei Nakano
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We consider the combinatorial optimization problem of finding the most influential nodes on a large-scale social network for two widely-used fundamental stochastic diffusion models. It was shown that a natural greedy strategy can give a good approximate solution to this optimization problem. However, a conventional method under the greedy algorithm needs a large amount of computation, since it estimates the marginal gains for the expected number of nodes influenced by a set of nodes by simulating the random process of each model many times. In this paper, we propose a method of efficiently estimating all those quantities on the basis of bond percolation and graph theory, and apply it to approximately solving the optimization problem under the greedy algorithm. Using real-world large-scale networks including blog networks, we experimentally demonstrate that the proposed method can outperform the conventional method, and achieve a large reduction in computational cost.
Innovation Networks: A Report on Creating a Specialist Professional Social Network, Offline and Online, to Foster Innovation in the New Media Sector
Authors: Bob Cotton
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

This paper is a report on the building of an online professional social network (http://nm-x.com) supported by a programme of live events, focused on innovation in the digital media content-design and development sector in London, late 2006-present. Starting with a summary of the state of the digital media design and development sector in this period, the Creative London strategy and the development team, the Report then focuses on the interface design issues, the creation of nm-x, and the supporting programme of live events. A reflective conclusion summarises the development and poses some questions and feedback that may be useful for others developing similar projects. A new contribution, a `Connections Module' (allowing semantic links between nodes) is made to Drupal.
Use and acquisition of semantic language model
Authors: Kuansan Wang, Ye-Yi Wang, Alex Acero
Venue: Demonstration Papers at HLT-NAACL 2004 on XX (2004)

Semantic language model is a technique that utilizes the semantic structure of an utterance to better rank the likelihood of words composing the sentence. When used in a conversational system, one can dynamically integrate the dialog state and domain semantics into the semantic language model to better guide the speech recognizer executing the decoding process. We describe one such application that employs semantic language model to cope with spontaneous speech in a robust manner. The semantic language model, though can be manually crafted without data, can benefit significantly from data driven machine learning techniques. An example based approach is also described here to demonstrate a viable approach.
Ensemble Methods of Face Recognition Based on Bit-plane Decomposition
Authors: Kai Li, Lingxiao Wang
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Face recognition has become one of the latest research subjects of pattern recognition and image processing. Although many face recognition techniques have been proposed and many achievements have been obtained, we can’t get high recognition rate due to the changes of face expression, location, direction and light. In this paper we study human face recognition based on ensemble techniques. In order to improve diversity of component classifiers, the idea of bit-plane decomposition is used and moving window classifier is used as a basic individual classifier. The quantized pattern representations’ layers are used jointly to make a decision. And we mainly study several fused methods which include product, sum, majority vote, max, min and median rules. Experiments results with face images databases show that fusion of multiple classifiers has good classification performance. Moreover, we compare different multiple classifier schemes with other human face recognition methods.
Clustering search algorithm for the capacitated centered clustering problem
Authors: Antonio Augusto Chaves, Luiz Antonio Nogueira Lorena
Venue: Computers and Operations Research (2010)

The capacitated centered clustering problem (CCCP) consists in partitioning a set of n points into p disjoint clusters with a known capacity. Each cluster is specified by a centroid. The objective is to minimize the total dissimilarity within each cluster, such that a given capacity limit of the cluster is not exceeded. This paper presents a solution procedure for the CCCP, using the hybrid metaheuristic clustering search (CS), whose main idea is to identify promising areas of the search space by generating solutions through a metaheuristic and clustering them into groups that are then further explored with local search heuristics. Computational results in test problems of the literature show that the CS found a significant number of new best-known solutions in reasonable computational times.
The Comparative Empirical Analysis of China and India's Use of FDI and the Implications for China
Authors: Liu Ting, Chen Chong-xian
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

The economic developments of China and India, two largest developing countries in the world, have been very impressive recently, but FDI policies and real FDI inflows in two countries are different. This article compares the main factors that cause the great differences in using FDI between China and India by empirical methods. The empirical results indicate that the larger domestic market size and more friendly FDI strategies make China much more attractive than India. With the increasing wages in China, the cost oriented FDI would be greatly affected. As FDI inflows in India mainly go to the service departments, the impact would be smaller. China has lost its advantages in low cost industries, it should change its ways of using FDI.
Quality Skyline in Sensor Database
Authors: Tian Yang, Zaifei Liao, Xinjie Lu, Hongan Wang
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

Data quality of sensor database is very important in industrial applications. An appropriate time period can improve the quality of result of high-level applications. In this paper we present a quality assessment and then give an algorithm to detect a quality skyline in a sensor dataset with stationary assumption. This algorithm returns an appropriate length of time period that query with a longer time period will get a result with stationary data quality.
Cost-Sensitive Support Vector Machine Based on Weighted Attribute
Authors: Dai Yuanhong, Chen Hongchang, Peng Tao
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

In practice it is existed a matter in classified problem. The problem can be described as that the different sort has different wrong classified cost. In this paper we propose a Cost-sensitive SVM approach based on weighted attribute. The approach first calculates the weightiness of feature attributes corresponded to the classification attribute, then calculates the corresponding weightiness of attribute for all sample. In the end the samples are used for Cost-sensitive SVM training and testing. The experimental results show that the approach can improve the classification precision of the cost sensitive samples, and also the use of feature attribute increases the integer classified capability of the classifier. The approach has important realistic significance of unbalanced wrong-classification cost in classified problem.
Combinable Tabs: An Interactive Method of Information Comparison Using a Combinable Tabbed Document Interface
Authors: Gonglue Jiang, Chen Zhao, Matthew R. Scott, Fang Zou
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I (2009)

The Tabbed Document Interface ("TDI") of today's web browsers is widely considered to be a usability improvement over the previously predominate Single Document Interface ("SDI"). TDI styled interfaces however, especially in mashups or other overlays of different information sets, suffer from a key usability limitation: they cannot show two or more tabbed documents simultaneously. Users are left with the task of quickly switching between tabs when trying to visually compare content. Our contribution is centered on intuitively enabling the comparison of tabbed content via what we coined a Combinable Tabbed Document Interface ("CTDI"). This interface extends TDI to allow tabs to be dragged and dropped onto one another to form a "master tab" whose data page renders a "side by side" view of its combined "sub tabs". The combined view will revert to the previous form when closing the master tab. It's a novel solution for those websites that needs to compare information, such as e-commerce sites, online dictionaries, etc. To test the effectiveness of CTDI, we developed an online dictionary called "Engkoo" which puts the concept to practice.
Exploratory Software Testing: Tips, Tricks, Tours, and Techniques to Guide Test Design, 1st edition
Authors: James A. Whittaker
Venue:  (2009)

How to Find and Fix the Killer Software Bugs that Evade Conventional Testing In Exploratory Software Testing, renowned software testing expert James Whittaker reveals the real causes of todays most serious, well-hidden software bugs--and introduces powerful new exploratory techniques for finding and correcting them. Drawing on nearly two decades of experience working at the cutting edge of testing with Google, Microsoft, and other top software organizations, Whittaker introduces innovative new processes for manual testing that are repeatable, prescriptive, teachable, and extremely effective. Whittaker defines both in-the-small techniques for individual testers and in-the-large techniques to supercharge test teams. He also introduces a hybrid strategy for injecting exploratory concepts into traditional scripted testing. Youll learn when to use each, and how to use them all successfully. Concise, entertaining, and actionable, this book introduces robust techniques that have been used extensively by real testers on shipping software, illuminating their actual experiences with these techniques, and the results theyve achieved. Writing for testers, QA specialists, developers, program managers, and architects alike, Whittaker answers crucial questions such as: Why do some bugs remain invisible to automated testing--and how can I uncover them? What techniques will help me consistently discover and eliminate show stopper bugs? How do I make manual testing more effective--and less boring and unpleasant? Whats the most effective high-level test strategy for each project? Which inputs should I test when I cant test them all? Which test cases will provide the best feature coverage? How can I get better results by combining exploratory testing with traditional script or scenario-based testing? How do I reflect feedback from the development process, such as code changes?
Fault Attacks on RSA Signatures with Partially Unknown Messages
Authors: Jean-Sébastien Coron, Antoine Joux, Ilya Kizhvatov, David Naccache, Pascal Paillier
Venue: Proceedings of the 11th International Workshop on Cryptographic Hardware and Embedded Systems (2009)

Fault attacks exploit hardware malfunctions to recover secrets from embedded electronic devices. In the late 90's, Boneh, DeMillo and Lipton [6] introduced fault-based attacks on crt-rsa. These attacks factor the signer's modulus when the message padding function is deterministic. However, the attack does not apply when the message is partially unknown, for example when it contains some randomness which is recovered only when verifying a correct signature.In this paper we successfully extends rsa fault attacks to a large class of partially known message configurations. The new attacks rely on Coppersmith's algorithm for finding small roots of multivariate polynomial equations. We illustrate the approach by successfully attacking several randomized versions of the iso/iec 9796-2 encoding standard. Practical experiments show that a 2048-bit modulus can be factored in less than a minute given one faulty signature containing 160 random bits and an unknown 160-bit message digest.