ppxscal/embedding_network huggingface dataset:
Adaptive subcarrier allocation and bit loading for voice-data transmission in multiuser OFDM systems
Authors: Hua Zhang, Guoan Bi, Liren Zhang
Venue: Wireless Communications Mobile Computing (2009)

A new algorithm of adaptive subcarrier allocation and bit loading (A-SABL) is proposed for simultaneous voice and data transmission in multiuser OFDM systems. The algorithm takes advantage of the frequency diversity and the voice-data transmission requirements to dynamically assign the number of subcarriers and bits-per symbol on each subcarrier for each user in a single cell. Due to the strict delay requirement of voice service, the subcarriers with low channel gains are assigned for voice transmission with a small number of bits per symbol to guarantee its required bit-error-rate (BER) and transmission rate. Based on the remaining subcarriers with high channel gains and the transmission power, the throughput of data transmission is then maximized by loading as many bits as possible on each subcarrier to achieve the required transmission bit rate and BER. Theoretical analysis and simulation on the proposed algorithm show that a better performance is obtained than previously reported schemes. Copyright &copy; 2008 John Wiley & Sons, Ltd.
On the practical complexity of solving the maximum weighted independent set problem for optimal scheduling in wireless networks
Authors: Peng Wang, Stephan Bohacek
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

It is well known that the maximum weighted independent set (MWIS) problem is NP-complete. Moreover, optimal scheduling in wireless networks requires solving a MWIS problem. Consequently, it is widely believed that optimal scheduling cannot be solved in practical networks. However, there are many cases where there is a significant difference between worst-case complexity and practical complexity. This paper examines the practical complexity of the MWIS problem through extensive computational experimentation. In all, over 10000 topologies are examined. It is found that the MWIS problem can be solved quickly, for example, for a 2048 node topology, it can be solved in approximately one second. Moreover, it appears that the average computational complexity grows polynomially with the number of nodes and linearly with the mean degree of the conflict graph.
Reordering Sparsification of Kernel Machines in Approximate Policy Iteration
Authors: Chunming Liu, Jinze Song, Xin Xu, Pengcheng Zhang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Approximate policy iteration (API), which includes least-squares policy iteration (LSPI) and its kernelized version (KLSPI), has received increasing attention due to their good convergence and generalization abilities in solving difficult reinforcement learning problems. However, the sparsification of feature vectors, especially the kernel-based features, greatly influences the performance of API methods. In this paper, a novel reordering sparsification method is proposed for sparsifiying kernel machines in API. In this method, a greedy strategy is adopted, which adds the sample with the maximal squared approximation error to the kernel dictionary, so that the samples are reordered to improve the performance of kernel sparsification. Experimental results on the learning control of an inverted pendulum verify that by using the proposed algorithm, the size of the kernel dictionary is smaller than that of the previous sequential sparsification algorithm with the same level of sparsity, and the performance of the control policies learned by KLSPI can also be improved.
Cor-Split: Defending Privacy in Data Re-publication from Historical Correlations and Compromised Tuples
Authors: Daniele Riboni, Claudio Bettini
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

Several approaches have been proposed for privacy preserving data publication. In this paper we consider the important case in which a certain view over a dynamic dataset has to be released a number of times during its history. The insufficiency of techniques used for one-shot publication in the case of subsequent releases has been previously recognized, and some new approaches have been proposed. Our research shows that relevant privacy threats, not recognized by previous proposals, can occur in practice. In particular, we show the cascading effects that a single (or a few) compromised tuples can have in data re-publication when coupled with the ability of an adversary to recognize historical correlations among released tuples. A theoretical study of the threats leads us to a defense algorithm, implemented as a significant extension of the m-invariance technique. Extensive experiments using publicly available datasets show that the proposed technique preserves the utility of published data and effectively protects from the identified privacy threats.
Plenary lecture 10: multi-key search algorithms - a new paradigm in algorithm design
Authors: Ahmed Tarek
Venue: Proceedings of the 15th american conference on Applied mathematics (2009)

This talk is a consolidated representation of my recent research findings. Search algorithms are fundamental to the computing sciences with intensive database applications. So far, a significant amount of efforts has been set forth to improving the computer-based search strategies. Multi-element search techniques are relatively new in computer science. I have introduced this concept at the 8th World Multi-Conference on Systemics, Cybernetics and Informatics back in 2004. The multiple key search algorithms may effectively be combined with the traditional concepts prevailing in the data structure literature to optimize the computer-based resource requirements for certain applications. Further research in this area has appeared to be appealing in integrating these concepts with the traditional designs prevailing in the algorithmic. Among the most useful search algorithms, interpolation search uses the concept of projection for equally separated elements inside a given list. An extended multiple key interpolation search algorithm is developed and implemented, which has time and computational memory requirements much less than the other algorithms in this class with multiple key search criteria and equally separated list of elements. The idea of Block Search is to subdivide a given list of sorted elements into equally sized blocks, and then restrict the search effort into one of these blocks. The concept pertaining to multiple search elements fits nicely with the idea prevailing in Block Search. This hybrid algorithm has the best performance whenever an element to search for exists at each division point of each independent block within the current tier. In that event, the time required by the new algorithm is linear, and proportional to the number of elements to look for. It is also possible to sub-divide each independent block into multiple numbers of sub-blocks and then reapply the multiple element block search strategy to each independent block containing a number of sub-blocks. Though this increases the complexity of algorithm design, but due to the improved efficiency, the algorithm will require substantially less computational resources. The optimum number of tiers for the computational resources requirements is also investigated. The basic binary search technique may be combined with the multi-tier multiple key block search strategy.
Human Pose Estimation with Rotated Geometric Blur
Authors: Bo Chen, Nhan Nguyen, Greg Mori
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

We consider the problem of estimating the pose of a human figure in a single image. Our method uses an exemplar-matching framework, where a test image is matched to a database of exemplars upon which body joint positions have been marked. We find the best matching exemplar for a test image by employing a variant of an existing deformable template matching framework. A hierarchical correspondence process is developed to improve the efficiency of the existing framework. Quantitative results on the CMU MoBo dataset verify the effectiveness of our approach.
A hybrid multicast connectivity solution for multi-party collaborative environments
Authors: Namgon Kim, Jongwon Kim, Thomas D. Uram
Venue: Multimedia Tools and Applications (2009)

In multi-party collaborative environments, a group of users can share multiple media streams via IP multicasting. However, despite of the efficiency of IP multicast, it is not widely available and alternative application-layer multicast approaches are introduced. Application-layer multicast is advantageous, however, it incurs additional processing delays. In this paper, we present a new hybrid-style application-layer multicast solution that satisfies both network efficiency and easy deployment. We achieve this goal by connecting multicast islands through UDP tunnels employing UMTP (UDP multicast tunneling protocol). We also design a MPROBE protocol to remove multicast loop among multicast island in real Internet. We verify the feasibility of the proposed solution by implementing a prototype tool, AG Connector, that works on Access Grid multi-party collaborative environment.
B-Fabric: An Open Source Life Sciences Data Management System
Authors: Can Türker, Fuat Akal, Dieter Joho, Ralph Schlapbach
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

The advances in information technology boosted life sciences research towards systems biology which aims at studying complex interactions in biological systems in an integrative way. Steadily improving high-throughput instruments (genome sequencers, mass spectrometers etc.) and analysis software produce large amounts of experimental data. In this paper, we report on experiences with developing and running a life sciences data management system in a productive environment.
Students create game-based online learning environment that teaches Java programing
Authors: Joe Shanahan
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

This paper examines current Massively Multiplayer Online Role Playing Games (MMORPGs) and their educational value. It provides details of a project at Auburn University where students are attempting to create an Educational MMORPG that teaches Java programming. The game allows students to play the role of a computer scientist, and use programming skills to interact with in-game objects. Throughout the paper are examples of why Java is an excellent choice for MMORPG development. This paper also serves as a jump-start for other students who are interested in creating an Educational MMORPG.
Learning in Planning with Temporally Extended Goals and Uncontrollable Events
Authors: André A. Ciré, Adi Botea
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution plan. This paper introduces a planning model that combines temporally extended goals and uncontrollable events. The planning task is to reach a state such that all event sequences generated from that state satisfy the problem's temporally extended goal. A real-life application that motivates this work is to use planning to configure a system in such a way that its subsequent, non-deterministic internal evolution (nominal behavior) is guaranteed to satisfy a condition expressed in temporal logic. A solving architecture is presented that combines planning, model checking and learning. An online learning process incrementally discovers information about the problem instance at hand. The learned information is useful both to guide the search in planning and to safely avoid unnecessary calls to the model checking module. A detailed experimental analysis of the approach presented in this paper is included. The new method for online learning is shown to greatly improve the system performance.
Two Stage Knowledge Discovery for Spatio-temporal Radio-emission Data
Authors: Matthias Haringer, Lothar Hotz, Vera Kamp
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In this paper, we introduce a method to examine and interpret spatio-temporal radio emission datasets. The goal is to find communication patterns in the data in respect to spatial, temporal, and frequency based attributes. The chosen approach is a combination of two different AI-methods. First a clustering algorithm groups spatially close data points to potential emitters. In a second step a model-based constraint solving technique is applied to find relationships between the identified emitters. The used models describe rules of the communications that are to be found. This guarantees a flexible search for different kinds of communication.
Selective Ensemble Algorithms of Support Vector Machines Based on Constraint Projection
Authors: Lei Wang, Yong Yang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

This paper proposes two novel ensemble algorithms for training support vector machines based on constraint projection technique and selective ensemble strategy. Firstly, projective matrices are determined upon randomly selected must-link and cannot-link constraint sets, with which original training samples are transformed into different representation spaces to train a group of base classifiers. Then, two selective ensemble techniques are used to learn the best weighting vector for combining them, namely genetic optimization and minimizing deviation errors respectively. Experiments on UCI datasets show that both proposed algorithms improve the generalization performance of support vector machines significantly, which are much better than classical ensemble algorithms, such as Bagging, Boosting, feature Bagging and LoBag.
Sole versus dual sourcing under order dependent lead times and prices
Authors: Mohsen S. Sajadieh, Kourosh Eshghi
Venue: Computers and Operations Research (2009)

In this paper, we consider a dual-sourcing model with constant demand and stochastic lead times. Two suppliers may be different in terms of purchasing prices and lead-time parameters. The ordering takes place when the inventory level depletes to a reorder level, and the order is split among two suppliers. Unlike previous works in the order splitting literature, the supply lead time between vendor and buyer as well as unit purchasing prices is considered to be order quantity dependent. The proposed model finds out the optimal reorder point, order quantity and splitting proportion, using a solution procedure. Numerical results show that neglecting the relationship between ordering batch size and lead times is a shortcoming that hides one of order splitting advantages. Moreover, connecting unit prices to order quantity can decrease the percentage saving from dual sourcing compared to sole sourcing. Furthermore, sensitivity analysis shows some managerial insights.
On the complexity of paths avoiding forbidden pairs
Authors: Petr Kolman, Ondřej Pangrác
Venue: Discrete Applied Mathematics (2009)

Given a graph G=(V,E), two fixed vertices s,t@?V and a set F of pairs of vertices (called forbidden pairs), the problem of a path avoiding forbidden pairs is to find a path from s to t that contains at most one vertex from each pair in F. The problem is known to be NP-complete in general and a few restricted versions of the problem are known to be in P. We study the complexity of the problem for directed acyclic graphs with respect to the structure of the forbidden pairs. We write x@?y if and only if there exists a path from x to y and we assume, without loss of generality, that for every forbidden pair (x,y)@?F we have x@?y. The forbidden pairs have a halving structure if no two pairs (u,v),(x,y)@?F satisfy v@?x or v=x and they have a hierarchical structure if no two pairs (u,v),(x,y)@?F satisfy u@?x@?v@?y. We show that the PAFP problem is NP-hard even if the forbidden pairs have the halving structure and we provide a surprisingly simple and efficient algorithm for the PAFP problem with the hierarchical structure.
Plenary lecture V: nonlinear optimization models and solving algorithms based on appropriate neural networks
Authors: Nicolae Popoviciu
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

This work contains a complete set of algorithms for several quadratic and nonlinear optimization problems. The problem constraints are very differently. For each type of constraint an appropriate algorithm is given. The algorithms for linear bound constraints and nonlinear optimization are based on neural networks and uses a system of differential equations. In order to reduce the sensitivity and round off errors a preconditioning method is used. A great number of numerical applications illustrates the algorithms. We use the square matrices M of the type n × n or rectangular matrices M of type m × n. All the used vectors are column vectors i.e. x,c,d,p,r,u,v,w and denote, for example, x = xn×1 or x ∈ Rn, x = (xi). The letter T means the transposition. Here we enumerate several nonlinear optimization models and mention the appropriate algorithms to solve them. There are a lot of quadratic optimization (QO) models (or quadratic programming (QP) models) and nonlinear optimization models (NO) and here we mention several of them. We denote by θ the null vector of an appropriate space, let us say Rn and x ∈ Rn is the unknown vector of the any optimization problem.
An assured environment for collaborative engineering using web services
Authors: David Golby, Michael Wilson, Lutz Schubert, Christian Geuer-Pollmann
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

This paper describes an application of the TrustCoM environment to support secure contract based collaboration between companies using managed web services. The application scenario describes a consortium of engineering companies that seek to upgrade a customer's fleet of aircraft to provide in-flight internet capabilities. The environment supports the consortium to collaborate so as to take advantage of the market opportunity. In order to reduce the risks of collaboration, the environment provides assurances of the past performance of consortium members, of the current performance of each member to meet their contract and service level agreements, and the secure control of access to resources. As a result of a member's performance, the consortium dynamically reconfigures itself and initiates a collaborative business process that enlists new members to join and contribute to the negotiations with the customer.
A probabilistic model for web usage mining
Authors: Nicoleta David, Lucian Patrascu, Adela Sasu, Daniela Damian
Venue: Proceedings of the 8th Wseas international conference on Telecommunications and informatics (2009)

In this paper we propose the DTTS method for determining the typical trails in a web site. We use a probabilistic model for a web site and we use the entropy of a Markov chain in order to compute the length of the typical trails.
Digital Video Database: Supporting Student Teachers' Learning about Teaching during Teaching Practice
Authors: Winnie So, Vincent Hung, Walker Yip
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

This article introduces the setting-up of an online digital video database by the teacher education institute. An investigation into the application of the online digital videos database to support student teachers learning to teach during their teaching practice period is discussed, which includes the details of trimming the videos of teaching practice into learning objects for peer evaluation in order to construct good teaching & learning practices for sharing. Analysis of peer evaluation and feedbacks in the discussion forum among three student teachers involved in this study was conducted to gain a better understanding of the learning objects chosen as good practices of teaching and the nature of suggestions given. The focus group discussion afterwards provided evidences of student teachers' learning in the process of sharing learning objects on the online digital video database.
Choosing Reading Passages for Vocabulary Learning by Topic to Increase Intrinsic Motivation
Authors: Michael Heilman, Alan Juffs, Maxine Eskenazi
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Intrinsic motivation has been shown in previous research to lead to better learning. In order to increase intrinsic motivation, REAP, a tutoring system for ESL vocabulary was enhanced to prefer practice readings that match personal interests. In a randomized experiment, students receiving personalized readings indicated higher levels of interest in post-reading questionnaires. Additionally, overall post-test scores were higher (but not significantly) for students with interest-matched practice readings than for students using a previous version of REAP that did not match topics to student interests.
The Name-Your-Own-Price Channel in the Travel Industry: An Analytical Exploration
Authors: Tuo Wang, Esther Gal-Or, Rabikar Chatterjee
Venue: Management Science (2009)

Name-your-own-price (NYOP) retailers, such as Priceline, offer an alternative distribution channel for service providers in the travel industry such as airlines, hotels, and car rental companies. Our research employs an analytical model to identify and understand key trade-offs driving the decision by a service provider to employ an NYOP channel, assuming that such a channel is available. This decision requires the existence of forces that counteract the adverse consequences of cannibalization of sales through traditional posted-price channels. Our analysis provides some insight into these forces. Contracting with the NYOP retailer facilitates market segmentation and price discrimination, and allows for disposal of excess capacity after meeting business travel demand. However, the cost of this flexibility is that the service provider can no longer credibly precommit to maintaining high prices when there is unsold capacity. Also, when contracting with an independent retailer, the service provider is unable to extract the entire revenue generated from NYOP consumers. A key insight from our model is that the rationale for contracting with an NYOP retailer is driven by the uncertainty in business travel demand, not the expectation of excess capacity. Indeed, all else equal, the larger the capacity, the less likely it is that contracting with an NYOP retailer is the right decision on the part of the service provider.