ppxscal/embedding_network huggingface dataset:
Middle school use of automated writing evaluation: a multi-site case study
Authors: Mark Warschauer
Venue:  (2008)

This dissertation addresses classroom use of automated writing evaluation (AWE), software that uses artificial intelligence to automate essay scoring and feedback. The leading AWE products are delivered over the World Wide Web to educational institutions and individuals from upper elementary to university levels, and at least one of vendor claims over one million students are now using its AWE system.Proponents claim that AWE alleviates a longstanding need to improve writing instruction by greatly increasing writing practice and students' motivation to write. Critics claim that it diminishes the role of teachers and warps students' notions of good writing. In order to examine these and other claims, and to understand AWE in the context of research on writing instruction, writing assessment, and the diffusion of educational technologies, I employed a mixed-mode multi-level case study in eight middle schools in two Southern California school districts. Data collection included interviews of teachers and district administrators, classroom observations, surveys of teachers and students, sample essays, administrator reports of AWE use, and students' scores on the English Language Arts portion of the California State Test.Although teachers reported that students wrote more and the software made teaching easier, use of the software was moderate overall. Usage patterns were shaped by peer support, professional training, institutional attitudes and policies, the availability and reliability of computer hardware and networks, and teachers' prior beliefs and instructional practices. Findings are analyzed in terms of Rogers's (2003) theory of the diffusion of innovations and Kling's (1999) theory of socio-technical configurations, and recommendations are made for educators, researchers, and AWE developers.
Constrained coalitional games: formal framework, properties, and complexity results
Authors: Gianluigi Greco, Enrico Malizia, Luigi Palopoli, Francesco Scarcello
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

A general approach to define constrained coalitional games is proposed, i.e., TU games where additional, application-oriented constraints are imposed on the possible outcomes. It is observed that constrained games are succinct NonTransferable (NTU) specifications, which yet retain (some of) the nice properties of the underlying TU games. In fact, a clear picture about the preservation properties of TU solution concepts is depicted, and a thorough analysis is eventually carried out, to assess the impact of issuing constraints on the computational complexity of these solution concepts.
Adsorption equilibria of propane on activated carbon and molecular sieves
Authors: Z. Yaakob, S. K. Kamarudin, I. Kamaruzaman, A. Ibrahim
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

Data of adsorption isotherm of propane on activated carbon (AC), molecular sieve carbon (MSC), MS13X and MS5A at 303K, 328K and 353K are acquired using constant volumetric method. Isosteric heats can be obtained indirectly from the isotherms using the Clausius-Clapeyron equation. The data is then fitted to several conventional and new models using regression method which is done at all three temperatures simultaneously. A new version of Clausius-Clapeyron equation is used to validate the range of temperatures of the isotherms in order to use it to obtain the isosteric heats. Models are fitted into both the adsorption isotherms and isosteric heats of adsorption data. While each model has only marginal differences between each other for the goodness-of-fit for the isotherms are, the representation of isosteric heats differentiate the models from each other.
Studies and experiments related to modular structure robot
Authors: Nicu Bîzdoaca, Anca Petrisor, Sonia Degeratu, Elvira Bîzdoaca, Cristian Vladu
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

The modularity of robotic subsystems is a big opportunity for robotics to compel recognition on the market as a viable and efficient alternative, thanks to the development of standardized modulus, especially, but also because of the robots' features-such as productivity and flexibility. The idea of this proposal roots in the structure of a personal computer. The winding and the upgrade of a pc is an extremely simple and quick process thanks to the standardization of the functional modulus. Extrapolating this idea to robots, and to robotic systems, in general, it is necessary the conceiving of a modular system, as far back as in the primary design phase. The modular system should be conceived as intelligent structures with a high degree of sensorial, communicational, functional and control autonomy. These elements are presented and experimented with functional models, for validation. The conclusions are formulated and future directions are targeted.
Automatic Creation of a Countermeasure Plan against Process Delay Based on Fast-Tracking
Authors: Rihito Yaegashi, Daisuke Kinoshita, Yuichiro Hayashi, Keiichi Nakamura, Hiroaki Hashiura, Seiichi Komiya
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

Recently, some techniques for a very short-period software development which is called “Agile” have been proposed. In order to avoid risks, it has been considered as a taboo that the Post-work is started before the Pre-work is completed. However, we might have to break a taboo to recover a process delay. Therefore, this paper proposes a method to make a successful schedule plan automatically. The process delay can be recovered by breaking the taboo. This paper also proposes a method which is able to make a countermeasure plan automatically against a process delay by means of 'Fast-Tracking', and finally proves that our method is effective in a software project management by showing an example of the system.
On selecting the best transmission mode for WiFi devices
Authors: Mohammad Hossein Manshaei, Mathieu Lacage, Ceilidh Hoffmann, Thierry Turletti
Venue: Wireless Communications Mobile Computing (2009)

The design of efficient IEEE 802.11 physical (PHY) rate adaptation algorithms is a challenging research topic and usually the issues surrounding their implementations on real 802.11 devices are not disclosed. In this paper, we identify and evaluate the key parameters to design such algorithms. We then present a survey on existing PHY rate adaptation mechanisms and discuss their advantages and drawbacks. We also propose three new 802.11 PHY rate adaptation mechanisms, named adaptive auto rate fallback (AARF), closed loop adaptive rate allocation (CLARA), and adaptive multi-rate retry (AMRR). AARF, proposed for low-latency systems, has low complexity and obtains similar performance than RBAR in stationary and non-fading wireless channels. CLARA is a culmination of the best attributes of the transmitter-based ARF and RBAR control mechanisms with additional practical features such as adaptive fragmentation to improve multipath-fading channel sensing and to provide feedback control signaling. AMRR is designed for high-latency systems; it has been implemented and evaluated on an AR5212-based device. Experimentation results show more than 20&percnt; performance improvement in throughput over the default algorithm implemented in the AR5212 MADWIFI driver. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Microsoft SQL Server 2008 Reporting Services Step by Step
Authors: Stacia Misner
Venue:  (2009)

Teach yourself to design, create, view, and manage SQL Server 2008 reports one step at a time. You ll begin by building a solid foundation with the tools and techniques for using SQL Server Reporting Services, mastering the fundamentals of installing and working with reports. Next, you ll design and develop reports progressively adding calculations, interactivity, queries, charts, and models. You ll then deploy and administer reports to the reporting server. Finally, you ll learn to use Reporting Services as a development platform. Once you ve completed each lesson, you can hone your skills using the practice exercises from the companion CD. Plus, you can review and download code samples illustrating the author s own, professional techniques direct from the companion Web site.
The difficulties of taxonomic name extraction and a solution
Authors: Guido Sautter, Klemens Böhm
Venue: Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis (2006)

In modern biology, digitization of biosystematics publications is an important task. Extraction of taxonomic names from such documents is one of its major issues. This is because these names identify the various genera and species. This article reports on our experiences with learning techniques for this particular task. We say why established Named-Entity Recognition techniques are somewhat difficult to use in our context. One reason is that we have only very little training data available. Our experiments show that a combining approach that relies on regular expressions, heuristics, and word-level language recognition achieves very high precision and recall and allows to cope with those difficulties.
A gradient-based combined method for the computation of fingerprints' orientation field
Authors: Yuan Mei, Huaijiang Sun, Deshen Xia
Venue: Image and Vision Computing (2009)

Estimation of fingerprint orientation fields is an essential module in automatic fingerprint recognition system. Many algorithms based on gradient have been proposed, but their results are unsatisfactory, especially for poor image. In this paper, a gradient-based combined method for the computation of fingerprints' orientation field has been proposed. In our method, we first calculate the first level orientation fields with three different size blocks; and then combine these first level orientation fields together to form the second level orientation field; finally, use the iteration based method to predict orientation. All experiments show that, compared to the prior works, our method is more robust against noise while preserving the accuracy and is capable of predicting.
Interactive plan hints for query optimization
Authors: Nicolas Bruno, Surajit Chaudhuri, Ravishankar Ramamurthy
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Commercial database systems expose query hints to fix poor plans produced by the query optimizer. However, current query hints are not flexible enough to deal with a variety of non-trivial scenarios, and can be at times cumbersome for DBAs to interact with. In this demonstration we present a framework that enables visual specification of hints to influence the optimizer to pick better plans. Our framework goes considerably beyond existing hinting mechanisms and significantly improves the usability of such functionality.
Fast approximate spectral clustering
Authors: Donghui Yan, Ling Huang, Michael I. Jordan
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-scale problems due to its computational complexity of O(n3) in general, with n the number of data points. We extend the range of spectral clustering by developing a general framework for fast approximate spectral clustering in which a distortion-minimizing local transformation is first applied to the data. This framework is based on a theoretical analysis that provides a statistical characterization of the effect of local distortion on the mis-clustering rate. We develop two concrete instances of our general framework, one based on local k-means clustering (KASP) and one based on random projection trees (RASP). Extensive experiments show that these algorithms can achieve significant speedups with little degradation in clustering accuracy. Specifically, our algorithms outperform k-means by a large margin in terms of accuracy, and run several times faster than approximate spectral clustering based on the Nystrom method, with comparable accuracy and significantly smaller memory footprint. Remarkably, our algorithms make it possible for a single machine to spectral cluster data sets with a million observations within several minutes.
Revisiting the Performance of Short TCP Transfers
Authors: Aymen Hafsaoui, Denis Collange, Guillaume Urvoy-Keller
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

Performance of short TCP transfers, e.g., Web browsing, has a direct impact on the way users perceive the health of their Internet access. It is a common belief that TCP performs better with large than with short transfers, as the latters are more likely to time-out and their duration is dominated by the RTT.In this paper, we revisit the performance of short TCP transfers. We highlight the interplay between TCP and the application on top. We show that while losses can have a detrimental impact on short TCP transfers, the application significantly affects the transfer time of almost all short - and even long - flows in a variety of way. Indeed, the application can induce extremely large tear-down times and it can also slow the rate of actual TCP transfers or affect the ability of TCP to recover using Fast Retransmit/Fast Recovery. We illustrate our findings using several traces from realistic networks including DSL, wireless hotspot and a research lab traffic.
Approximability and Fixed-Parameter Tractability for the Exemplar Genomic Distance Problems
Authors: Binhai Zhu
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

In this paper, we present a survey of the approximability and fixed-parameter tractability results for some Exemplar Genomic Distance problems. We mainly focus on three problems: the exemplar breakpoint distance problem and its complement (i.e., the exemplar non-breaking similarity or the exemplar adjacency number problem), and the maximal strip recovery (MSR) problem. The following results hold for the simplest case between only two genomes (genomic maps) ${\cal G}$ and ${\cal H}$, each containing only one sequence of genes (gene markers), possibly with repetitions. 1 For the general Exemplar Breakpoint Distance problem, it was shown that deciding if the optimal solution value of some given instance is zero is NP-hard. This implies that the problem does not admit any approximation, neither any FPT algorithm, unless P=NP. In fact, this result holds even when a gene appears in ${\cal G}$ (${\cal H}$) at most two times. 1 For the Exemplar Non-breaking Similarity problem, it was shown that the problem is linearly reducible from Independent Set. Hence, it does not admit any factor-O(n ¿ ) approximation unless P=NP and it is W[1]-complete (loosely speaking, there is no way to obtain an O(n o(k)) time exact algorithm unless FPT=W[1], here k is the optimal solution value of the problem). 1 For the MSR problem, after quite a lot of struggle, we recently showed that the problem is NP-complete. On the other hand, the problem was previously known to have a factor-4 approximation and we showed recently that it admits a simple FPT algorithm which runs in O(22.73k n + n 2) time, where k is the optimal solution value of the problem. 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
Transmission power selection for ad hoc networks
Authors: Jianping He, Jiahai Yang, Changqing An, Xuenong Li
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

In wireless ad hoc networks, as an important technology, power control is widely used to increase energy efficiency and improve network throughput. Power control is composed of two components: one component handles the problems caused by asymmetric channel; the other component is responsible for selecting transmission power. In this paper, we focus on transmission power selection for ad hoc networks using 802.11 DCF MAC protocol. In this paper, we model the network with power control in joint with PHY layer and MAC layer. Then we prove that in considering the noise, interference from other nodes and packet length, it is NP-hard to obtain the optimal transmission power for every node even if it knows the complete knowledge of the network. After that, we propose two heuristic transmission power selection algorithms, one for energy-oriented power control and the other for throughput-oriented power control, which are time efficiency and able to improve the network performance largely. Finally, we evaluate our algorithms under different topologies and in different packet size. The results show that our algorithms can improve the network performance largely when compared with 802.11 and traditional power control algorithms.
Extending the loop language with higher-order procedural variables
Authors: Tristan Crolard, Emmanuel Polonowski, Pierre Valarcher
Venue: ACM Transactions on Computational Logic (TOCL) (2009)

We extend Meyer and Ritchie's Loop language with higher-order procedures and procedural variables and we show that the resulting programming language (called Loop&omega;) is a natural imperative counterpart of G&ouml;del System T. The argument is two-fold: (1) we define a translation of the Loop&omega; language into System T and we prove that this translation actually provides a lock-step simulation, (2) using a converse translation, we show that Loop&omega; is expressive enough to encode any term of System T. Moreover, we define the &ldquo;iteration rank&rdquo; of a Loop&omega; program, which corresponds to the classical notion of &ldquo;recursion rank&rdquo; in System T, and we show that both translations preserve ranks. Two applications of these results in the area of implicit complexity are described.
Deadline fault tolerance in a networked real-time system
Authors: Peng Wen, Yan Li
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

This paper applies a well-developed algorithm in real-time computing to a networked real-time system, and model the system as a periodic real-time computing one. In this model, each process is named as a task and implemented in two versions: the primary and the alternate. The primaries might fail but the alternates are guaranteed. A scheduling algorithm manages to execute all primaries if possible. Otherwise it guarantees the executing of each task either the primary or the alternate before their deadlines. The algorithm is verified in simulation. The result shows that in cases with high failure probability, the low priority tasks have a lower completion rates. In cases with low failure probability, both high priority and low priority tasks can be completed very well.
A monospectral approach for fMRI analysis using Kohonen self-organised networks and objective dialectical classifiers
Authors: Wellington P. Dos Santos, Francisco M. De Assis, Ricardo E. De Souza, Ana Cristina T. Albuquerque, Maria Lucia B. Simas
Venue: International Journal of Innovative Computing and Applications (2008)

One of the major challenges at the field of cognitive sciences is mapping the regions of the brain responsible for the motor and behavioural functions. The acquisition of functional magnetic resonance images is an important non-invasive technique to study the neural activity in the human brain. The dialectical conception of reality is a kind of philosophical investigative method for analysing processes present in nature and in human societies. The dialectical method is a tool for studying systems by considering the dynamics of their contradictions, as dynamic processes with intertwined phases of evolution and revolutionary crisis. It has inspired us to conceive a dialectical classifier able to solve classification problems. This work presents a new approach for the detection of activated brain regions: the composition and analysis of synthetic multi and monospectral images using statistical methods and proposing a non-parametrical method based on Kohonen self-organised networks and in objective dialectical classifiers.
Synthesis of strategies for non-zero-sum repeated games
Authors: Dana Nau
Venue:  (2008)

There are numerous applications that involve two or more self-interested autonomous agents that repeatedly interact with each other in order to achieve a goal or maximize their utilities. This dissertation focuses on the problem of how to identify and exploit useful structures in agents&rsquo; behavior for the construction of good strategies for agents in multi-agent environments, particularly non-zero-sum repeated games.This dissertation makes four contributions to the study of this problem. First, this thesis describes a way to take a set of interaction traces produced by different pairs of players in a two-player repeated game, and then find the best way to combine them into a strategy. The strategy can then be incorporated into an existing agent, as an enhancement of the agent's original strategy. In cross-validated experiments involving 126 agents for the Iterated Prisoner's Dilemma, Iterated Chicken Game, and Iterated Battle of the Sexes, my technique was able to make improvement to the performance of nearly all of the agents. Second, this thesis investigates the issue of uncertainty about goals when a goal-based agent situated in a nondeterministic environment. The results of this investigation include the necessary and sufficiency conditions for such guarantee, and an algorithm for synthesizing a strategy from interaction traces that maximizes the probability of success of an agent even when no strategy can assure the success of the agent. Third, this thesis introduces a technique, Symbolic Noise Detection (SND), for detecting noise (i.e., mistakes or miscommunications) among agents in repeated games. The idea is that if we can build a model of the other agent&rsquo;s behavior, we can use this model to detect and correct actions that have been affected by noise. In the 20th Anniversary Iterated Prisoner&rsquo;s Dilemma competition, the SND agent placed third in the &ldquo;noise&rdquo; category, and was the best performer among programs that had no "slave" programs feeding points to them. Fourth, the thesis presents a generalization of SND that can be wrapped around any existing strategy. Finally, the thesis includes a general framework for synthesizing strategies from experience for repeated games in both noisy and noisy-free environments.
Multi-Agent Collaboration: A Satellite Constellation Case
Authors: Grégory Bonnet, Catherine Tessier
Venue: Proceeding of the 2008 conference on STAIRS 2008: Proceedings of the Fourth Starting AI Researchers' Symposium (2008)

Physical agents such as robots are generally constrained in their communication capabilities. In a multi-agent system composed of physical agents, these constraints have a strong influence on the organization and the coordination mechanisms. Our multi-agent system is a satellite constellation, for which we propose a collaboration method based on incremental coalition formation in order to optimize individual plans and satisfy collective objectives. This involves a communication protocol and two coordination mechanisms: (1) an incentive to join coalitions and (2) coalition minimization. Results on a simulated satellite constellation are presented and discussed.