ppxscal/embedding_network huggingface dataset:
Enhancing and Relaxing Competitive Units for Feature Discovery
Authors: Ryotaro Kamimura
Venue: Neural Processing Letters (2009)

In this paper, we propose a new information-theoretic method called enhancement and relaxation to discover main features in input patterns. We have so far shown that competitive learning is a process of mutual information maximization between input patterns and connection weights. However, because mutual information is an average over all input patterns and competitive units, it is not adequate for discovering detailed information on the roles of elements in a network. To extract information on the roles of elements in a networks, we enhance or relax competitive units through the elements. Mutual information should be changed by these processes. The change in information is called enhanced information. The enhanced information can be used to discover features in input patterns, because the information includes detailed information on elements in a network. We applied the method to the symmetry data, the well-known Iris problem and the OECD countries classification. In all cases, we succeeded in extracting the main features in input patterns.
No i-Sums for Nissim (and Shalom)
Authors: Itamar Francez
Venue: Languages: From Formal to Natural: Essays Dedicated to Nissim Francez on the Occasion of His 65th Birthday (2009)

Lappin and Francez (1994) present a theory of donkey anaphora which, they claim, captures both their existential and their universal readings, while maintaining a uniform representation of donkey pronouns. This paper shows that their analysis does not in fact assign the correct truth conditions to donkey sentences and so does not account correctly for the distribution of readings. An alternative analysis is proposed which retains LF's uniform representation for donkey pronouns, but abandons their analysis in terms of i-sums and the corollary derivation of universal readings by means of a maximality constraint. On the proposed analysis, donkey pronouns are uniformly represented with free variables over (Skolemized) choice functions, as in Chierchia's (1992) E-type analysis. The quantification associated with them is inferred quantification over choice functions. Universal readings arise as in Chierchia (1992) when all possible values for the free variable in the representation of a donkey pronoun are salient. For existential readings, a pragmatic account in the spirit of LF's analysis in terms of a cardinality constraint is maintained.
A Fixed-Parameter Enumeration Algorithm for the Weighted FVS Problem
Authors: Jianxin Wang, Guohong Jiang
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

In this paper, we present a fixed-parameter enumeration algorithm for the feedback vertex set problem by using the branch-and-search method. The algorithm transforms the feedback vertex set problem to the feedback edge set problem with specific conditions. Then it enumerates the z minimum-weight feedback edge sets by enumerating the z maximum-weight forests. As a result, we show the problem of enumerating the z minimum-weight feedback vertex sets of size k is solvable in time $\mathcal {O}(5^{k}kn^{2}+(5^{k}+3^{k}z)n^{2}\log n)$.
Constraint-based dynamic programming for decentralized POMDPs with structured interactions
Authors: Akshat Kumar, Shlomo Zilberstein
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Decentralized partially observable MDPs (DEC-POMDPs) provide a rich framework for modeling decision making by a team of agents. Despite rapid progress in this area, the limited scalability of solution techniques has restricted the applicability of the model. To overcome this computational barrier, research has focused on restricted classes of DEC-POMDPs, which are easier to solve yet rich enough to capture many practical problems. We present CBDP, an efficient and scalable point-based dynamic programming algorithm for one such model called ND-POMDP (Network Distributed POMDP). Specifically, CBDP provides magnitudes of speedup in the policy computation and generates better quality solution for all test instances. It has linear complexity in the number of agents and horizon length. Furthermore, the complexity per horizon for the examined class of problems is exponential only in a small parameter that depends upon the interaction among the agents, achieving significant scalability for large, loosely coupled multi-agent systems. The efficiency of CBDP lies in exploiting the structure of interactions using constraint networks. These results extend significantly the effectiveness of decision-theoretic planning in multi-agent settings.
Rule-based OWL Ontology Reasoning Using Dynamic ABOX Entailments
Authors: Georgios Meditskos, Nick Bassiliades
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In the rule-based OWL reasoning paradigm, ontologies are mapped into an internal rule engine representation format and rules are applied, such as TBOX and ABOX OWL entailment rules, in order to deduce new knowledge. In this paper we briefly introduce the notion of dynamically generating ABOX entailment rules in order to enhance the ABOX reasoning performance of a rule engine. The proposed methodology is still based on entailments rules for reasoning, using generic TBOX entailments for handling OWL semantics about concepts and roles, and dynamic ABox entailments for handling ontology instances.
Forming text in PDAs for special education students
Authors: Ümit Girgin, H. Ferhan Odabasi, M. Cem Girgin
Venue: Proceedings of the 8th WSEAS international conference on Electronics, hardware, wireless and optical communication (2009)

Use of mobile technologies in education has given way to new learning environments and thus to new learning opportunities. There are fields like special education which benefit from the flexible structure of mobile technologies. This study explains the process of forming text within a PDA project carried out with special education students.
Optimization of production plan through simulation techniques
Authors: G. Caputo, M. Gallo, G. Guizzi
Venue: WSEAS Transactions on Information Science and Applications (2009)

The production costs reduction in a highly competitive environment is a critical success factor. In particular, in fields where outsourcing is used frequently and the impact of the material costs is high, a significant cost reduction can be achieved making more efficient value chain. Moreover, the use of outsourcing is a way to adjust production capacity depending on demand. Therefore the coordination and planning of the various rings of the chain and the estimate of the productive capability of the various production units become fundamental for a coherent evaluation of promised delivery times. More and more frequently and in greater detail the Companies at the "end of the network" require, through capacity assessment a verification of the available productive capacity of the manufacturing units, both from a quality and quantity point of view, that each single firm can dedicate to a certain type of production. In this paper it is presented a simulation model that allows the elaboration of an operative plan of production through the verification of finite capacity scheduling of resources. The model tends to minimize costs of stocking and set-up, considering other production costs as constant. The simulation is a technique that allows the checking with better precision of the use of the resources with variation of the ties. This approach lead to a high performing instrument in the field of the advanced planning and scheduling through analysis of the various possible views. The auxiliary use of the optimizing tool available in the ARENA software allows an optimal solution, confirming the validity of the study of new applications of the simulative instrument for the verification of productive capacity in the short term.
Generalization analysis of listwise learning-to-rank algorithms
Authors: Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

This paper presents a theoretical framework for ranking, and demonstrates how to perform generalization analysis of listwise ranking algorithms using the framework. Many learning-to-rank algorithms have been proposed in recent years. Among them, the listwise approach has shown higher empirical ranking performance when compared to the other approaches. However, there is no theoretical study on the listwise approach as far as we know. In this paper, we propose a theoretical framework for ranking, which can naturally describe various listwise learning-to-rank algorithms. With this framework, we prove a theorem which gives a generalization bound of a listwise ranking algorithm, on the basis of Rademacher Average of the class of compound functions. The compound functions take listwise loss functions as outer functions and ranking models as inner functions. We then compute the Rademacher Averages for existing listwise algorithms of ListMLE, ListNet, and RankCosine. We also discuss the tightness of the bounds in different situations with regard to the list length and transformation function.
Supporting co-evolution of users and systems by the recognition of interaction patterns
Authors: Stefano Arondi, Pietro Baroni, Daniela Fogli, Piero Mussio
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

This paper presents an approach to support the designer of Visual Interactive Systems (VISs) in adapting a VIS to the evolution of its users. This process is called co-evolution of users and systems. The approach is based on the identification of the patterns of interaction between the user and an interactive system and on their use for the evolution of the system to facilitate novel usages introduced by the user. The approach is focused on WIMP systems and is based on the recently introduced PCL (Pictorial Computing Laboratory) model of interaction, within which we provide a novel definition of interaction pattern. The proposal assumes that the VIS is observed by an external system called SIC (Supporting Interaction Co-evolution), which is in charge of recording the interactions between the user and the VIS and of analyzing the relevant interaction patterns. In particular, SIC exploits a UML-based statechart specification of the VIS in order to associate observed user activities with the states of the interactive process. This information provides a useful basis for a variety of pattern recognition techniques. Two techniques called usual state and recurrent sequence recognition are illustrated and the results of a first experiment are discussed.
Statistical classification of Search Engines interrogated by the Meta-Search System
Authors: Katarzyna Wegrzyn-Wolska
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

This paper describes the work carried out to classify Search Engines used by the Meta Search System. This classification is used to choose automatically a set of Search Engines according to the category of the query. It surveys problems relating to Web information retrieval with Meta-Search techniques and, in particular, the different methods of classification and selection of queried Search Engines. It presents the results of the experiments performed to evaluate and classify the Search Engine used.
Real-Time Model-Based Hand Localization for Unsupervised Palmar Image Acquisition
Authors: Ivan Fratric, Slobodan Ribaric
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Unsupervised and touchless image acquisition are two problems that have recently emerged in biometric systems based on hand features. We have developed a real-time model-based hand localization system for palmar image acquisition and ROI extraction. The system operates on video sequences and produces a set of palmprint regions of interest (ROIs) for each sequence. Hand candidates are first located using Viola-Jones approach and then the best candidate is selected using model-fitting approach. Experimental results demonstrate the feasibility of the system for unsupervised palmar image acquisition in terms of speed and localization accuracy.
Cryptanalysis of an image encryption scheme based on a compound chaotic sequence
Authors: Chengqing Li, Shujun Li, Guanrong Chen, Wolfgang A. Halang
Venue: Image and Vision Computing (2009)

Recently, an image encryption scheme based on a compound chaotic sequence was proposed. In this paper, the security of the scheme is studied and the following problems are found: (1) a differential chosen-plaintext attack can break the scheme with only three chosen plain-images; (2) there is a number of weak keys and some equivalent keys for encryption; (3) the scheme is not sensitive to the changes of plain-images; and (4) the compound chaotic sequence does not work as a good random number source.
Microsoft Dynamics AX Interview Questions: Unofficial Microsoft Dynamics AX Axapta Certification Review
Venue:  (2007)

The Ultimate Reference & Learning Guide for Microsoft Dynamics AX Consultants, Administrators, and Developers Over 150 Certification Questions, Answers, and Explanations It's clear that Microsoft Dynamics is the future for cost effective ERP, but few resources exist for the professional consultant seeking quick insight to the software package. Appropriate for all levels of Dynamics proficiency, over 150 Questions, Answers, and Explanations guide you through your learning process. From helping you to assess your Dynamics AX skills to evaluating candidates for a job, Microsoft Dynamix AX Interview Questions will help you understand what you really need to know, and what you can safely ignore. The book is organized around implementation issues, functional design, and audit and security. Each question includes everything you need to know to master the interview or properly evaluate a candidate. More than just a rehash of Microsoft documentation and sales presentations, each question is based on project knowledge and experience gained on successful high-profile Dynamics implementations. Key certification and interview topics include: Software Installation and Configuration, Programming in X++, Logistics, Distribution, BOM setup, Design, performance tuning, audit and security, and Database Monitoring 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
A hardware platform for efficient worm outbreak detection
Authors: Miad Faezipour, Mehrdad Nourani, Rina Panigrahy
Venue: ACM Transactions on Design Automation of Electronic Systems (TODAES) (2009)

Network Intrusion Detection Systems (NIDS) monitor network traffic to detect attacks or unauthorized activities. Traditional NIDSes search for patterns that match typical network compromise or remote hacking attempts. However, newer networking applications require finding the frequently repeated strings in a packet stream for further investigation of potential attack attempts. Finding frequently repeated strings within a given time frame of the packet stream has been quite efficient to detect polymorphic worm outbreaks. A novel real-time worm outbreak detection system using two-phase hashing and monitoring repeated common substrings is proposed in this article. We use the concept of shared counters to minimize the memory cost while efficiently sifting through suspicious strings. The worm outbreak system has been prototyped on Altera Stratix FPGA. We have tested the system for various settings and packet stream sizes. Experimental results verify that our system can support line speed of gigabit-rates with negligible false positive and negative rates.
BEWARE: Background traffic-aware rate adaptation for IEEE 802.11
Authors: Shao-Cheng Wang, Ahmed Helmy
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

IEEE 802.11-based devices employ rate adaptation algorithms to dynamically switch data rates to accommodate the fluctuating wireless channel conditions. Many studies observed that, when there are other stations transmitting in the network, existing rate adaptation performance degrades significantly due to the inability of differentiating losses between wireless noise and contention collisions. Previous studies proposed to exploit optional RTS frames to isolate the wireless losses from collision losses, and thus improve rate adaptation performance. In this paper, we conduct a systematic evaluation on the effectiveness of various existing rate adaptation algorithms and related proposals for loss differentiations, with multiple stations transmitting background traffic in the network. Our main contributions are two-fold. Firstly, we observe that existing RTS-based loss differentiation schemes do not perform well in all background traffic scenarios. In addition, our study reveals that RTSbased loss differentiation schemes can mislead the rate adaptation algorithms to persist on using similar data rate combinations regardless of background traffic level, thus result in performance penalty in certain scenarios. The fundamental challenge is that a good rate adaptation algorithm must dynamically adjust the rate selection decision objectives with respect to different background traffic levels. Secondly, we design a new Background traffic aware rate adaptation algorithm (BEWARE) that addresses the above challenge. BEWARE uses a mathematical model to calculate on-the-fly the expected packet transmission time based on current wireless channel and background traffic conditions. Our simulation results show that BEWARE outperforms other rate adaptation algorithms without RTS loss differentiation by up to 250% and with RTS by up to 25% in throughput.
Dynamic Task and Data Placement over NUMA Architectures: An OpenMP Runtime Perspective
Authors: François Broquedis, Nathalie Furmento, Brice Goglin, Raymond Namyst, Pierre-André Wacrenier
Venue: Proceedings of the 5th International Workshop on OpenMP: Evolving OpenMP in an Age of Extreme Parallelism (2009)

Exploiting the full computational power of current hierarchical multiprocessor machines requires a very careful distribution of threads and data among the underlying non-uniform architecture so as to avoid memory access penalties. Directive-based programming languages such as OpenMPprovide programmers with an easy way to structure the parallelism of their application and to transmit this information to the runtime system.Our runtime, which is based on a multi-level thread scheduler combined with a NUMA-aware memory manager, converts this information into "scheduling hints" to solve thread/memory affinity issues. It enables dynamic load distribution guided by application structure and hardware topology, thus helping to achieve performance portability. First experiments show that mixed solutions (migrating threads and data) outperform next-touch-based data distribution policies and open possibilities for new optimizations.
Ontology-based natural language query processing for the biological domain
Authors: Jisheng Liang, Thien Nguyen, Krzysztof Koperski, Giovanni Marchisio
Venue: Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis (2006)

This paper describes a natural language query engine that enables users to search for entities, relationships, and events that are extracted from biological literature. The query interpretation is guided by a domain ontology, which provides a mapping between linguistic structures and domain conceptual relations. We focus on the usability of the natural language interface to users who are used to keyword-based information retrieval. Preliminary evaluation of our approach using the GENIA corpus and ontology shows promising results.
Plenary lecture XIII: probabilistic-fuzzy inference procedures for knowledge-based systems
Authors: Anna Walaszek-Babiszewska
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

Knowledge-based systems (KBS) are computer systems using methods and techniques of artificial intelligence. The main components of the systems are the knowledge base and the inference procedure. Such systems are capable of supporting human decisions in many fields of activities, as: control, prediction, diagnosis and many others. In this work we present the general methods of creating the probabilistic-fuzzy knowledge base and the inference procedure. A structure of the reason-result fuzzy model is predefined according to expert's experiences, at the beginning of the task. Sets of numerical data, collected in real systems are used to compute empirical probability distributions of linguistic variables of the knowledge representation. The calculated probabilities of fuzzy events have been included into inference procedures. Models and inference procedures for exemplary tasks are presented.
Performance-driven interface contract enforcement for scientific components
Authors: Premkumar T. Devanbu
Venue:  (2008)

Performance-driven interface contract enforcement research aims to improve the quality of programs built from plug-and-play scientific components. Interface contracts make the obligations on the caller and all implementations of the specified methods explicit. Runtime contract enforcement is a well-known technique for enhancing testing and debugging. However, checking all of the associated constraints during deployment is generally considered too costly from a performance stand point. Previous solutions enforced subsets of constraints without explicit consideration of their performance implications. Hence, this research measures the impacts of different interface contract sampling strategies and compares results with new techniques driven by execution time estimates. Results from three studies indicate automatically adjusting the level of checking based on performance constraints improves the likelihood of detecting contract violations under certain circumstances. Specifically, performance-driven enforcement is better suited to programs exercising constraints whose costs are at most moderately expensive relative to normal program execution.
Efficient Iris Spoof Detection via Boosted Local Binary Patterns
Authors: Zhaofeng He, Zhenan Sun, Tieniu Tan, Zhuoshi Wei
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Recently, spoof detection has become an important and challenging topic in iris recognition. Based on the textural differences between the counterfeit iris images and the live iris images, we propose an efficient method to tackle this problem. Firstly, the normalized iris image is divided into sub-regions according to the properties of iris textures. Local binary patterns (LBP) are then adopted for texture representation of each sub-region. Finally, Adaboost learning is performed to select the most discriminative LBP features for spoof detection. In particular, a kernel density estimation scheme is proposed to complement the insufficiency of counterfeit iris images during Adaboost training. The comparison experiments indicate that the proposed method outperforms state-of-the-art methods in both accuracy and speed.
Business Process Analysis using Reference Model
Authors: Shinobu Saito, Shuichiro Yamamoto
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

Reference models are used to analyze and improve business processes. But it is not clear to use reference models effectively. We will propose a business process analysis method using reference model. So the decomposition checkpoints are proposed to clarify the problems in business processes. Then case studies are also presented.