ppxscal/embedding_network huggingface dataset:
Analysis of routing metrics for providing better link utilization in WiMAX using soft computing
Authors: Arianit Maraj
Venue: Proceedings of the 8th WSEAS international conference on Electronics, hardware, wireless and optical communication (2009)

Quality of service is a challenging problem in networks that offer multimedia services. WiMAX technology is able to offer multimedia services. Network quality of service for offering multimedia services depends on link utilization: better link utilization improves quality of service in a network. For satisfying QoS requirements in WiMAX technology we should take into consideration the most important metrics that affect directly to the QoS. In this paper we will consider four metrics: required recourses, buffer size packet queues, delay and losses. Those metrics affect directly in link utilization. It is very difficult job to consider three or more metrics simultaneously, but using soft computing this is possible. Fuzzy logic is the main branch of soft computing. We will use intelligent controlling techniques that are based on fuzzy logic for solving different problems in aspect of link utilization. The aim is to obtain better values of link utilization using different rules from Rule Editor and using appropriate defuzzification method. We will use MATLAB software for designing fuzzy logic controller. With MATLAB software we will see which rule (from Rule Editor) and which defuzzication method gives better results in aspect of link utilization.
Conversations in developer communities: a preliminary analysis of the yahoo! pipes community
Authors: M. Cameron Jones, Elizabeth F. Churchill
Venue: Proceedings of the fourth international conference on Communities and technologies (2009)

In this paper we describe several issues end-users may face when developing web mashup applications in visual language tools like Yahoo! Pipes. We explore how these problems manifest themselves in the conversations users have in the associated discussion forums, and examine the community practices and processes at work in collaborative debugging, and problem solving. We have noticed two valences of engagement in the community: core and peripheral. Core engagement involves active question asking and answering and contribution of example content. Peripheral engagement refers to those who read but don't post, and those who post legitimate questions and content, but whose posts receive no response. We consider what the characteristics are of each of these groups, why there is such a strong divide, and how the periphery functions in the community process.
Data clustering and fuzzy neural network for sales forecasting: A case study in printed circuit board industry
Authors: Pei-Chann Chang, Chen-Hao Liu, Chin-Yuan Fan
Venue: Knowledge-Based Systems (2009)

In order to obtain a better control of market trend and profit for the company, timely identification of sales is very important for businesses. Upward and downward trends in sales signify new market trends and understanding of sales trends is important for marketing as well as for customer retention. This research develops a hybrid model by integrating K-mean cluster and fuzzy neural network (KFNN) to forecast the future sales of a printed circuit board factory. Based on the K-mean clustering technique, the historical data can be classified into different clusters. The accuracy of the forecasted model can be further improved by referring the new data to be forecasted from a more focused region, i.e., a smaller region after clustering. Numerical data of various affecting factors and actual demand of the past 5 years of the printed circuit board (PCB) factory are collected and input into the hybrid model for future monthly sales forecasted. The experimental results derived from the proposed model show the effectiveness of the hybrid model when compared with other approaches.
Swarm intelligence based tuning of extended Kalman filter for manoeuvring target tracking
Authors: Ravi Kumar Jatoth, T. Kishore Kumar
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

Kalman filter is a well known adaptive filtering Algorithm, widely used for target tracking applications. When the system model and measurements are non linear, variation of Kalman filter like extended Kalman filter (EKF) is used. For obtaining reliable estimate of the target state, filter has to be tuned before the operation (off line). Tuning an EKF is the process of estimation of the noise covariance matrices from process data [1]. In practical applications, due to unavailable measurements of the process noise and high dimensionality of the problem tuning of the filter is left for engineering intuition. In this paper, tuning of the EKF is investigated using Particle Swarm Optimization (PSO). The simulation results show the superiority of the PSO tuned EKF over the conventional EKF.
Positive and negative verbal feedback for Intelligent Tutoring Systems
Authors: Barbara di Eugenio, Xin Lu, Trina C. Kershaw, Andrew Corrigan-Halpern, Stellan Ohlsson
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

We built three different versions of an ITS on a letter pattern extrapolation task: in one version, students only receive color-coded feedback; in the second, they receive verbal feedback messages when they perform correct actions, and in the third, when they make a mistake. We found that time on task and number of errors are predictive of performance on the post-test rather than the type of feedback.
Learning Optimal Compact Codebook for Efficient Object Categorization
Authors: Teng Li, Tao Mei, In So Kweon
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Representation of images using the distribution of local features on a visual codebook is an effective method for object categorization. Typically, discriminative capability of the codebook can lead to a better performance. However, conventional methods usually use clustering algorithms to learn codebooks without considering this. This paper presents a novel approach of learning optimal compact codebooks by selecting a subset of discriminative codes from a large codebook. Firstly, the Gaussian models of object categories based on a single code are learned from the distribution of local features within each image. Then two discriminative criteria, i.e. likelihood ratio and Fisher, are introduced to evaluate how each code contributes to the categorization. We evaluate the optimal codebooks constructed by these two criteria on Caltech-4 dataset, and report superior performance of object categorization compared with traditional K-means method with the same size of codebook.
Reactive NUCA: near-optimal block placement and replication in distributed caches
Authors: Nikos Hardavellas, Michael Ferdman, Babak Falsafi, Anastasia Ailamaki
Venue: Proceedings of the 36th annual international symposium on Computer architecture (2009)

Increases in on-chip communication delay and the large working sets of server and scientific workloads complicate the design of the on-chip last-level cache for multicore processors. The large working sets favor a shared cache design that maximizes the aggregate cache capacity and minimizes off-chip memory requests. At the same time, the growing on-chip communication delay favors core-private caches that replicate data to minimize delays on global wires. Recent hybrid proposals offer lower average latency than conventional designs, but they address the placement requirements of only a subset of the data accessed by the application, require complex lookup and coherence mechanisms that increase latency, or fail to scale to high core counts. In this work, we observe that the cache access patterns of a range of server and scientific workloads can be classified into distinct classes, where each class is amenable to different block placement policies. Based on this observation, we propose Reactive NUCA (R-NUCA), a distributed cache design which reacts to the class of each cache access and places blocks at the appropriate location in the cache. R-NUCA cooperates with the operating system to support intelligent placement, migration, and replication without the overhead of an explicit coherence mechanism for the on-chip last-level cache. In a range of server, scientific, and multiprogrammed workloads, R-NUCA matches the performance of the best cache design for each workload, improving performance by 14% on average over competing designs and by 32% at best, while achieving performance within 5% of an ideal cache design.
Ofdm interference mitigation algorithms with application to dvb-h
Authors: Naofal Al-Dhahir
Venue:  (2008)

Orthogonal frequency-division multiplexing (OFDM) has gained an increased popularity over the last few years and has been adopted as the modulation scheme of choice for beyond 3G mobile communication systems. This is mainly due to its high robustness to time dispersion effects and its low implementation complexity. DVB-H is the latest development within the set of Digital Video Broadcasting (DVB) standards that use OFDM as a modulation scheme. DVB-H is required to operate under high mobility conditions resulting in significant Inter-Carrier Interference (ICI). Under these conditions, the conventional one-tap per subcarrier channel estimation and equalization scheme is suboptimal since it does not account for ICI effects due to channel time-variation within an OFDM symbol. To mitigate ICI, we propose in this dissertation a simplified hybrid frequency/time-domain channel estimation algorithm. In addition, we design a reduced-complexity Q-tap frequency-domain equalizer (FEQ) and enhance its performance by integrating it with joint channel and data estimation and an ICI-mitigating pilot/data placement scheme. We also investigate differential OFDM detection as a low-complexity alternative for coherent detection and test its performance in the presence of Doppler for DVB-H system. Furthermore, we extend our approach to multiple-input multiple-out (MIMO) OFDM systems. We design a novel embedded space-frequency block code (SFBC)-OFDM scheme that performs well under high Doppler. We also propose a novel standard-conformable Cyclic Delay Diversity (CDD) scheme and its associated channel estimation scheme for comb-type OFDM transmissions, which achieves the Cramer-Rao lower bound on channel estimation mean square error.
Practical Reasoning and Proposing: Tools for e-Democracy
Authors: Douglas Walton
Venue: Proceeding of the 2005 conference on Legal Knowledge and Information Systems: JURIX 2005: The Eighteenth Annual Conference (2005)

It is shown how two tools developed in argumentation theory are useful for AI systems for electronic democracy [2,3] and more generally for formal dialogue systems representing deliberation. The novel part of this analysis is that it represents the speech of proposing as a small dialogue exchange in which one party practically reasons with another, based on premises that both are committed to, as collaborative participants in a deliberation dialogue. The structure of practical reasoning as a type of argument as analyzed in [6] is brought to bear, to bring out special features of the speech act of proposing that make it a nice fit with the formal framework for deliberation dialogue constructed by [4].
Accurate loop self inductance bound for efficient inductance screening
Authors: Mosin Mondal, Yehia Massoud
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2006)

An analytical model for the upper bound of loop self inductance has been developed that is applicable to a wide range of layout geometries commonly encountered in high performance integrated circuits. We demonstrate that the existing analytical models can significantly underestimate the value of loop self inductance producing optimistic results. When compared with field solver results, the developed model shows an average error of 2%. A speedup of more than three orders of magnitude is obtained enabling our model to be fit for applications in inductance screening, inductance aware physical synthesis and prelayout inductance estimation.
Robust web extraction: an approach based on a probabilistic tree-edit model
Authors: Nilesh Dalvi, Philip Bohannon, Fei Sha
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

On script-generated web sites, many documents share common HTML tree structure, allowing wrappers to effectively extract information of interest. Of course, the scripts and thus the tree structure evolve over time, causing wrappers to break repeatedly, and resulting in a high cost of maintaining wrappers. In this paper, we explore a novel approach: we use temporal snapshots of web pages to develop a tree-edit model of HTML, and use this model to improve wrapper construction. We view the changes to the tree structure as suppositions of a series of edit operations: deleting nodes, inserting nodes and substituting labels of nodes. The tree structures evolve by choosing these edit operations stochastically. Our model is attractive in that the probability that a source tree has evolved into a target tree can be estimated efficiently--in quadratic time in the size of the trees--making it a potentially useful tool for a variety of tree-evolution problems. We give an algorithm to learn the probabilistic model from training examples consisting of pairs of trees, and apply this algorithm to collections of web-page snapshots to derive HTML-specific tree edit models. Finally, we describe a novel wrapper-construction framework that takes the tree-edit model into account, and compare the quality of resulting wrappers to that of traditional wrappers on synthetic and real HTML document examples.
Retrieving broken web links using an approach based on contextual information
Authors: Juan Martinez-Romo, Lourdes Araujo
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

In this short note we present a recommendation system for automatic retrieval of broken Web links using an approach based on contextual information. We extract information from the context of a link such as the anchor text, the content of the page containing the link, and a combination of the cache page in some search engine and web archive, if it exists. Then the selected information is processed and submitted to a search engine. We propose an algorithm based on information retrieval techniques to select the most relevant information and to rank the candidate pages provided for the search engine, in order to help the user to find the best replacement. To test the different methods, we have also defined a methodology which does not require the user judgements, what increases the objectivity of the results.
Annotating and learning compound noun semantics
Authors: Diarmuid Ó Séaghdha
Venue: Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop (2007)

There is little consensus on a standard experimental design for the compound interpretation task. This paper introduces well-motivated general desiderata for semantic annotation schemes, and describes such a scheme for in-context compound annotation accompanied by detailed publicly available guidelines. Classification experiments on an open-text dataset compare favourably with previously reported results and provide a solid baseline for future research.
Real Estate v2.0: A Professional's Guide to Dynamic Websites, Blogs, and Podcasts
Authors: Danielle Babb, Alex Lazo
Venue:  (2007)

The second version of the Internet, known in geek terms as Web 2.0, has created opportunities for organizations to expand the capability of offering services for their clients using only online tools. Web 2.0 includes the use of podcasts, blogs, and dynamic web sites. One industry that is sure to take advantage of the new online collaboration tools that Web 2.0 provides is real estate. One of the last markets to be radically changed by technology due to its complexity and the exceedingly large number of players involved in each transaction is quickly catching up with other industries such as travel and online stock trading. Many tools are available for real estate professionals to help them list and sell more homes and to provide better service to their clients. If they dont adopt many of these tools, they threaten their business for the long term. Authors Dani Babb and Alex Lazo point out that there are ways for professionals to overcome these obstacles, including the expanded use of technology. This book explores some of the ways to do that using dynamic and useful tools online.
STFLS: A Heuristic Method for Static and Transportation Facility Location Allocation in Large Spatial Datasets
Authors: Wei Gu, Xin Wang, Liqiang Geng
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

This paper solves a static and transportation facility location allocation problem defined as follows: given a set of locations Loc and a set of demand objects D located in Loc, the goal is to allocate a set of static facilities S and a set of transportation facilities T to the locations in Loc, which minimizes both the average travelling distance from D to S and the maximum transportation travelling distance between D and S through T. The problem is challenging because two types of facilities are involved and cooperate with each other. In this paper, we propose a static and transportation facility location allocation algorithm, called STFLS, to solve the problem. The method uses two steps of searching for static facility and transportation facility locations Experiments demonstrate the efficiency and practicality of the algorithm.
Student learning through situated use of three-dimensional modeling and animation software in a high school art class
Authors: Kerry Freedman
Venue:  (2008)

In the United States today, students in some secondary art programs are beginning to utilize professional grade 3-D modeling and animation software to create original works of visual art. Teachers creating and teaching such courses have almost no pedagogical guidance available to them in the art education literature or from the literature of other fields such as computer science. This study addresses this deficiency by investigating student learning in one public school secondary digital art classroom utilizing the Maya 3-D modeling and animation software to create original animations. Drawing on Constructivist and Postmodern art education theories, this pragmatically designed thematic case study examines the learning outcomes of five groups of students working collaboratively for one semester to create 3-D digital animations.In response to the first research question, the influences of visual culture on student attitudes and motivations were examined. This study found that student experiences with popular visual culture motivated and guided their efforts in the course, and participation in the course likewise affected how they view 3-D computer graphics in popular visual culture. In response to the second research question, the types and qualities of student learning in art were explored. This study found that in addition to technical learning about computer technology and the Maya software, students demonstrated meaningful learning in critical, formal, and expressive areas of art, as well as learning to sustain inquiry in a difficult project. Responding to the third research question, this study examined the modalities that enabled student learning of the Maya software. Findings included both details about student inductive and collaborative learning during creation and student development of strategies for utilizing learning resources based on probabilities of success and time management. This study responded to the fourth research question by utilizing empirical means to test students for cognitive benefits of participation in the course, but could not conclusively identify any.This study shows how students construct meaningful knowledge about art in the digital technology art classroom through interactions with visual culture outside the classroom. The study concludes with practical applications and suggestions for future research.
Mechatronics and Machine Vision in Practice, 1st edition
Authors: John Billingsley, Robin Bradbeer
Venue:  (2007)

From grading and preparing harvested vegetables to the tactile probing of a patients innermost recesses, mechatronics has become part of our way of life. The addition of senses and computing intelligence to blend with mechanical actuation gives rise to a breed of new machines with all the best attributes of a robot. Here we find educational robots competing under water and dancing on land. Surgical robots drill precision holes in the skull while others direct radiation treatment or extract blood from an umbilical cord. Machine vision manages beer kegs and automated paint spraying, while controlling feral animals and the watering of cotton crops. Although there is no shortage of theoretical and technical detail in these chapters, they have the common theme that they describe work that has been applied in practice. They are vital reading both for students of mechatronics and for engineers harnessing its power to create new products.
Parallel Preprocessing for Classification Problems in Knowledge Discovery Systems
Authors: N. R. Akchurina, V. N. Vagin
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

A new algorithm for solving the actual problem in machine learning of joint preprocessing of qualitative and quantitative attributes with missing values is proposed. A parallel version of the algorithm developed by the authors is also presented. In thorough tests on 55 databases from the UC Irvine Repository specially designed from real databases of various fields for testing and comparing generalization algorithms, usage of the proposed algorithms has allowed to increase the classification accuracy (the main criterion of learning process) of the well-known classification algorithms: ID3, C4.5, Naïve Bayes, table majority, instance based algorithm almost in all the cases. In case of resources being available the parallel version of the algorithm allows to speed up preprocessing efficiently.
QoS based scheduling in the downlink of multi-user wireless systems (extended)
Authors: Feng Wang, Jian Pu, Mounir Hamdi
Venue: Computer Communications (2009)

Frame aggregation is a MAC-layer technology proposed in 802.11n WLAN. The base station can serve two or more users in one frame simultaneously, which can improve MAC-layer efficiency by reducing the transmission time for preamble and frame headers, and the random backoff period for successive frame transmissions. This fact enables us to design a more QoS-aware scheduler from the MAC layer. In this paper, we first formulate the scheduling problem with frame aggregation into a knapsack problem that is shown NP hard. Then we propose a simple approximation algorithm (LUUF) based on the unit urgency concept. Our analysis shows that the complexity of LUUF is O(nlogn) and it achieves an approximation ratio of F^'/F"m"a"x. We then show that in practice the complexity can be further reduced to O(n) and the approximation ratio can be made very near to 1, which makes LUUF a promising candidate for wireless systems that support frame aggregation. We also conduct simulations comparing LUUF with the widely used Round-Robin scheduler and find that LUUF can significantly improve the quality of service for various numbers of users and different maximum aggregation frame sizes.