ppxscal/embedding_network huggingface dataset:
Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS
Authors: Neşe Yalçın Seçme, Ali Bayrakdaroğlu, Cengiz Kahraman
Venue: Expert Systems with Applications: An International Journal (2009)

The performance evaluation of banks has important results for creditors, investors and stakeholders since it determines banks' capabilities to compete in the sector and has a critical importance for the development of the sector. The aim of this study is to propose a fuzzy multi-criteria decision model to evaluate the performances of banks.The largest five commercial banks of Turkish Banking Sector are examined and these banks are evaluated in terms of several financial and non-financial indicators. Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) methods are integrated in the proposed model. After the weights for a number of criteria are determined based on the opinions of experts using the FAHP method, these weights are input to the TOPSIS method to rank the banks. The results show that not only financial performance but also non-financial performance should be taken into account in a competitive environment.
Controlled operation of variable speed driven permanent magnet synchronous generator for wind energy conversion systems
Authors: Rajveer Mittal, K. S. Sandhu, D. K. Jain
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

The introduction of distributed generation through renewable sources of energy has opened a challenging area for power engineers. As these sources are intermittent in nature, variable speed electric generators are employed for harnessing electrical energy from these sources. However, power electronic control is required to connect these sources to the existing grid. The grid interconnection issues are to be dealt with before connecting these to the local grid. Power conditioners using self commutating devices are necessary to have grid friendly inverters. In this paper, the MATLAB based simulation studies have been done to realize a grid friendly inverter system for harnessing energy from a variable speed wind energy system. The system is designed for low harmonic injection into the grid and fast control of voltage so as to meet the IEEE standard-1547 requirements.
Designing a Multi-Agent system to simulate scenarios for decision-making in river basin systems
Authors: Thania Rendón-Sallard, Miquel Sànchez-Marrè, Montserrat Aulinas, Joaquim Comas
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

Environmental problems tend to be very intricate, thus traditional software approaches cannot cope with this complexity when developing an environmental system. Multi-Agent systems (MAS) have the ability to deal with complex problems, thus we propose the development of a MAS for supporting the decision-making in a river basin system. With this proposal, we intend to provide feasible solutions at catchment scale throughout modelling and simulation of different scenarios in a river basin system.
Adaptive Physical Design for Curated Archives
Authors: Tanu Malik, Xiaodan Wang, Debabrata Dash, Amitabh Chaudhary, Anastasia Ailamaki, Randal Burns
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

We introduce AdaptPD, an automated physical design tool that improves database performance by continuously monitoring changes in the workload and adapting the physical design to suit the incoming workload. Current physical design tools are offline and require specification of a representative workload. AdaptPD is "always on" and incorporates online algorithms which profile the incoming workload to calculate the relative benefit of transitioning to an alternative design. Efficient query and transition cost estimation modules allow AdaptPD to quickly decide between various design configurations. We evaluate AdaptPD with the SkyServer Astronomy database using queries submitted by SkyServer's users. Experiments show that AdaptPD adapts to changes in the workload, improves query performance substantially over offline tools, and introduces minor computational overhead.
What's happening?: promoting community awareness through opportunistic, peripheral interfaces
Authors: Qiang Alex Zhao, John T. Stasko
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

Maintaining an awareness of information about one's own community and its members is viewed as being important, but is becoming more challenging today as people are overwhelmed by so many different forms of information. This paper describes the "What's Happening" suite of tools for helping convey relevant and interesting community information to people in a manner that is minimally distracting and disruptive, with little or no user set-up and interaction. The tools are more lightweight than e-mail and Usenet news, and opportunistic in providing information to people when they are not deeply focused on some other task.
Real-time haptic display of fluids
Authors: Mauricio Vines, Javier Mora, Won-Sook Lee
Venue: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering (2009)

We present a novel interactive computer system based on integrating fluid simulation and haptic force feedback. Our system allows the user to interact with a fluid simulation in real time, producing flows and allowing the user to feel the fluid properties such as viscosity and velocity. Differently from solid or deformable objects found in most haptic applications, we interact with a pool of liquid where the shape cannot be defined using conventional polygons. We base our approach on the Navier-Stokes equation and a mass-spring system to represent the fluid surface. We solve the problems associated to real time rendering of haptic forces.
Modelling Judicial Context in Argumentation Frameworks
Authors: Adam Wyner, Trevor Bench-Capon
Venue: Proceeding of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008 (2008)

Much work using argumentation frameworks treats arguments as entirely abstract, related by a uniform attack relation which always succeeds unless the attacker can itself be defeated. However, this does not seem adequate for legal argumentation. Some proposals have suggested regulating attack relations using preferences or values on arguments and which filter the attack relation, so that some attacks fail and so can be removed from the framework. This does not, however, capture a central feature of legal reasoning: how a decision with respect to the same facts and legal reasoning varies as the judicial context varies. Nor does it capture related context dependent features of legal reasoning, such as how an audience can prefer or value an argument, yet be constrained by precedent or authority not to accept it. Nor does it explain how certain types of attack may not be allowed in a particular procedural context. For this reason, evaluation of the status of arguments within a given framework must be allowed to depend not only on the attack relations along with the preference or value of arguments, but also on the nature of the attacks and the context in which they are made. We present a means to represent these features, enabling us to account for a number of factors currently considered to be beyond the remit of formal argumentation frameworks. We give three examples of the use of approach: appealing a case, overruling a precedent, and rehearing of a case as a civil rather than criminal proceeding.
Probabilistic fuzzy systems in value-at-risk estimation
Authors: R. J. Almeida, U. Kaymak
Venue: International Journal of Intelligent Systems in Accounting and Finance Management (2009)

Value-at-risk (VaR) is a popular measure for quantifying the market risk that a financial institution faces into a single number. Owing to the complexity of financial markets, the risks associated with a portfolio varies over time. Consequently, advanced methods of VaR estimation use parametric conditional models of portfolio volatility (e.g. generalized autoregressive heteroscedasticity (GARCH) models) to adapt risk estimation to changing market conditions. However, more flexible semi-parametric methods that adapt to the highly flexible underlying data distribution are better suited for accurate VaR estimation. In this paper, we consider VaR estimation by using probabilistic fuzzy systems (PFSs). A PFS is a semi-parametric method that combines a linguistic description of the system behaviour with statistical properties of the data. Therefore, they provide the potential to adapt estimations of probability density to the linguistic framework of the modeller. We study two approaches to designing probabilistic fuzzy VaR models and compare their performances with the performance of a GARCH model. It is found that statistical back testing always accepts PFS models after tuning, whereas GARCH models may be rejected. Copyright &copy; 2009 John Wiley & Sons, Ltd.
Constructing Passwords from Biometrical Data
Authors: Vladimir B. Balakirsky, Anahit R. Ghazaryan, A. J. Vinck
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

We propose a probabilistic model for constructing passwords on the basis of outcomes of biometrical measurements. An algorithm for the transformation of biometrical data to passwords is given. The performance of the authentication scheme is evaluated by the compression factor, the false acceptance/rejection rates, the probability distribution over the set of passwords, and the probability of a correct guess of the input biometrical data mapped to the known password. An application of the results to DNA measurements is presented.
Technology transfer decision support in requirements engineering research: a systematic review of REj
Authors: Martin Ivarsson, Tony Gorschek
Venue: Requirements Engineering (2009)

One of the main goals of an applied research field such as requirements engineering is the transfer of research results to industrial use. To promote industrial adoption of technologies developed in academia, researchers need to provide tangible evidence of the advantages of using them. This can be done through industry validation, enabling researchers to test and validate technologies in a real setting with real users and applications. The evidence obtained, together with detailed information on how the validation was conducted, offers rich decision support material for industrial practitioners seeking to adopt new technologies. This paper presents a comprehensive systematic literature review of all papers published in the Requirements Engineering journal containing any type of technology evaluation. The aim is to gauge the support for technology transfer, i.e., to what degree industrial practitioners can use the reporting of technology evaluations in the journal as decision support for adopting the technologies in industrial practice. Findings show that very few evaluations offer full technology transfer support, i.e., have a realistic scale, application or subjects. The major improvement potential concerning support for technology transfer is found to be the subjects used in the evaluations. Attaining company support, including support for using practitioners as subjects, is vital for technology transfer and for researchers seeking to validate technologies.
The optimisation of the single surface mount device placement machine in printed circuit board assembly: a survey
Authors: Masri Ayob, Graham Kendall
Venue: International Journal of Systems Science (2009)

This article surveys research on the single surface mount device (SMD) placement machine optimisation problem. We classify the optimisation problem into five sub-problems: feeder setup, component placement sequencing, nozzle optimisation, component retrieval plan and motion control; and analyse issues relevant to each of these. One of the aims of this article is to provide guidance to other researchers and gain a deeper understanding of the various optimisation issues that arise in this domain. This could lead to the design of improved heuristics, which are more appropriate to the real-world scheduling problem of the SMD placement machine.
Leakage-Aware Multiprocessor Scheduling
Authors: Pepijn Langen, Ben Juurlink
Venue: Journal of Signal Processing Systems (2009)

When peak performance is unnecessary, Dynamic Voltage Scaling (DVS) can be used to reduce the dynamic power consumption of embedded multiprocessors. In future technologies, however, static power consumption due to leakage current is expected to increase significantly. Then it will be more effective to limit the number of processors employed (i.e., turn some of them off), or to use a combination of DVS and processor shutdown. In this paper, leakage-aware scheduling heuristics are presented that determine the best trade-off between these three techniques: DVS, processor shutdown, and finding the optimal number of processors. Experimental results obtained using a public benchmark set of task graphs and real parallel applications show that our approach reduces the total energy consumption by up to 46% for tight deadlines (1.5× the critical path length) and by up to 73% for loose deadlines (8× the critical path length) compared to an approach that only employs DVS. We also compare the energy consumed by our scheduling algorithms to two absolute lower bounds, one for the case where all processors continuously run at the same frequency, and one for the case where the processors can run at different frequencies and these frequencies may change over time. The results show that the energy reduction achieved by our best approach is close to these theoretical limits.
A Bag of Words Approach for 3D Object Categorization
Authors: Roberto Toldo, Umberto Castellani, Andrea Fusiello
Venue: Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques (2009)

In this paper we propose a novel framework for 3D object categorization. The object is modeled it in terms of its sub-parts as an histogram of 3D visual word occurrences. We introduce an effective method for hierarchical 3D object segmentation driven by the minima rule that combines spectral clustering --- for the selection of seed-regions --- with region growing based on fast marching. The front propagation is driven by local geometry features, namely the Shape Index. Finally, after the coding of each object according to the Bag-of-Words paradigm, a Support Vector Machine is learnt to classify different objects categories. Several examples on two different datasets are shown which evidence the effectiveness of the proposed framework.
Learning equilibria in repeated congestion games
Authors: Moshe Tennenholtz, Aviv Zohar
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

While the class of congestion games has been thoroughly studied in the multi-agent systems literature, settings with incomplete information have received relatively little attention. In this paper we consider a setting in which the cost functions of resources in the congestion game are initially unknown. The agents gather information about these cost functions through repeated interaction, and observations of costs they incur. In this context we consider the following requirement: the agents' algorithms should themselves be in equilibrium, regardless of the actual cost functions and should lead to an efficient outcome. We prove that this requirement is achievable for a broad class of games: repeated symmetric congestion games. Our results are applicable even when agents are somewhat limited in their capacity to monitor the actions of their counterparts, or when they are unable to determine the exact cost they incur from every resource. On the other hand, we show that there exist asymmetric congestion games for which no such equilibrium can be found, not even an inefficient one. Finally we consider equilibria with resistance to the deviation of more than one player and show that these do not exist even in repeated resource selection games.
The software agent paradigm as a powerful simulation tools to support modelling of complex systems: the cases of consumer markets and telecom architectures
Authors: Filippo Neri
Venue: Proceedings of the 7th WSEAS international conference on System science and simulation in engineering (2008)

In the talk we will describe how the software agent paradigm can be a powerful and versatile simulation tool to model and study complex systems, allowing to fast prototype approximate solutions to difficult problems and to easily select which ones to take forward at the deployment stage. To support our position, we will introduce two different domains: consumer decisions in fast moving consumers goods and mobile telecom network management applications.
Language Processing in Human Brain
Authors: Alexander Borzenko
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

Human brain is exceptionally complex and simple at the same time. Its extremely composite biological structure results itself in human everyday behavior that many people might consider rather simple than complex. In our research we will concentrate on the ways how a human brain can processes English and other human natural languages because taken in general sense the ability to speak English or other human languages is only serious distinguishing feature that rises humans over the rest of the world making a human an intellectual being. On the purpose of our research we consider natural language as naturally formed symbolic system completely independent of these symbols' physical nature that is a little more general than a common natural language definition. The principles of natural language processing in human brain are most important for us if we want to build equally powerful artificial general intelligence. We start with the features of human brain neurons and neural networks, and step by step create a computer model of human brain networks that is able to process and generate a reasonable speech. We can't give a detailed explanation of human brain functionality in this short article. Moreover, it is not our goal, and such research is not complete yet. The main result of our research is revealing the principles how tiny single neurons working together can produce intellectual-like behaviour that exhibits itself in proper speech comprehension and generation in accordance with current context.
Learning Nonverbal Emotion Interaction In 3D Intelligent Virtual Environment For Children
Authors: Zhen Liu
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Nonverbal emotion interaction is very important for children, learning nonverbal emotion interaction by computer technology is an interesting subject. In a certain intelligent virtual environment (IVE), multi virtual characters interact with emotion and construct an virtual society. Modeling nonverbal social interaction is very important for constructing believable virtual characters. Nonverbal social interaction is a direct communication manner for virtual characters in an IVE. A cognitive architecture of virtual character is presented in this paper, the architecture outlines high-level knowledge of virtual characters in IVE, some new concepts on nonverbal social interaction is set up. A virtual character has the ability of social interaction with other virtual characters by cognitive architecture.
An HTN Planning Approach for Power System Scheduling Using SHOP2
Authors: Jingge Song, Jianzhong Cha
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

HTN Planning is an efficient approach in real-world planning problem solving. Operating order synthesis (OOS) is an important application area of AI techniques in power system scheduling in China. An HTN Planning approach is proposed for OOS based on SHOP2 methodology and planner. In this approach, power system model is constructed hierarchically in three levels. Based on different levels of system model, three types of task are identified and task decomposition strategies are proposed respectively. An example is presented and some issues are discussed.
Case-based adaptation for product formulation
Authors: D. Segura Velandia, A. A. West, C. J. Hinde
Venue: International Journal of Computer Integrated Manufacturing (2008)

The fact that case-based reasoning (CBR) adaptation in design domains is knowledge-intensive is one of the major factors that has limited the industrial application of CBR systems. Nevertheless, inductive techniques can ease the adaptation knowledge acquisition bottleneck by enabling useful knowledge to be elicited from the case-base (CB). Application of neural networks that use the knowledge available in the CB to (i) generate a desired mapping from differences between a query and retrieved cases, (ii) to minimise those differences and hence (iii) to adapt retrieved cases so that an optimal solution to a query is found is studied in this paper. This adaptation method is suitable for CBR systems that use numerical-valued attributes for describing a case.
Groovy Neural Networks
Authors: Axel Tidemann, Yiannis Demiris
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

The drum machine has been an important tool in music production for decades. However, its flawless way of playing drum patterns is often perceived as mechanical and rigid, far from the groove provided by a human drummer. This paper presents research towards enhancing the drum machine with learning capabilities. The drum machine learns user-specific variations (i.e. the groove) from human drummers, and stores the groove as attractors in Echo State Networks (ESNs). The ESNs are purely generative (i.e. not driven by an input signal) and the output is used by the drum machine to imitate the playing style of human drummers, making it a cost-effective way of achieving life-like drums.
The role of perceived user-interface design in continued usage intention of self-paced e-learning tools
Authors: Vincent Cho, T.C. Edwin Cheng, W.M. Jennifer Lai
Venue: Computers Education (2009)

While past studies on user-interface design focused on a particular system or application using the experimental approach, we propose a theoretical model to assess the impact of perceived user-interface design (PUID) on continued usage intention (CUI) of self-paced e-learning tools in general. We argue that the impact of PUID is mediated by two variables, namely perceived functionality (PF) and perceived system support (PSS), which influence perceived usefulness (PU) and perceived ease of use (PEOU), respectively. We empirically validated the model using data collected from a survey administered to university students in Hong Kong. We found that most hypotheses are valid and PUID is an important antecedent of CUI of a self-paced e-learning tool. We also showed that PU and user satisfaction (USat) are two essential predictors of CUI. However, the impact of PEOU on CUI is indirect via PU as a mediator. Our findings enrich the theory on the continued usage of technology, and provide e-learning developers with managerial insights on how to entice learners to continue using their e-learning tools.