Issue 4 • Nov 2001
Predictive and reactive approaches to the train-scheduling problem: a knowledge management perspectivePublication Year: 2001, Page(s):476 - 484
Cited by: Papers (14) | Patents (1)
Predictive and reactive train scheduling are tactical and operational decision making, respectively, under constraints (e.g. resource capacity, managerial objectives) and under uncertainty (e.g. imprecise data and information, unforeseen events). Predictive scheduling produces timetables taking into account the market demand and resource utilization levels. Reactive scheduling challenges disruptio... View full abstract»
Cited by: Papers (16)
Knowledge discovery and data mining commonly rely on finding salient patterns of association from a vast amount of data. Traditional citation analysis of scientific literature draws insights from strong citation patterns. Latent domain knowledge, in contrast to the mainstream domain knowledge, often consists of highly relevant but relatively infrequently cited scientific works. Visualizing latent ... View full abstract»
DNA sequence classification via an expectation maximization algorithm and neural networks: a case studyPublication Year: 2001, Page(s):468 - 475
Cited by: Papers (22) | Patents (2)
Presents new techniques for biosequence classification, with a focus on recognizing E. Coli promoters in DNA. Specifically, given an unlabeled DNA sequence S, we want to determine whether or not S is an E. Coli promoter. We use an expectation maximization (EM) algorithm to locate the -35 and -10 binding sites in an E. Coli promoter sequence. The EM algorithm differs from previously published EM al... View full abstract»
Cited by: Papers (9)
We discuss stages of autonomy determination for software agents that manage and manipulate knowledge in organizations that house other software agents and human knowledge workers. We suggest recognition of potential autonomies in the belief-desire-intention (BDI) paradigm and actual reasoning about autonomy choice decision theoretically. We show how agents might revise their autonomies in light of... View full abstract»
Cited by: Papers (4)
To reduce the amount of computation in a full search (FS) algorithm for fast motion estimation, we propose a novel and fast FS motion estimation algorithm. The computational reduction without any degradation in the predicted image comes from fast elimination of impossible motion vectors. We obtain faster elimination of inappropriate motion vectors using efficient matching units from localization o... View full abstract»
Cited by: Papers (8)
One of the major obstacles to using organizational data for mining and knowledge discovery is that, in most cases, it is not amenable for mining in its natural form. Using a data set from a large tertiary-care hospital, we provide strong empirical evidence that data enhancement by the introduction of new attributes, along with judicious aggregation of existing attributes, results in higher-quality... View full abstract»
Cited by: Papers (287) | Patents (2)
We introduce Learn++, an algorithm for incremental training of neural network (NN) pattern classifiers. The proposed algorithm enables supervised NN paradigms, such as the multilayer perceptron (MLP), to accommodate new data, including examples that correspond to previously unseen classes. Furthermore, the algorithm does not require access to previously used data during subsequent incremental lear... View full abstract»
Cited by: Papers (12)
Classification of the electroencephalogram (EEG) during motor imagery of the left or right hand can be performed using a classifier comprising two hidden Markov models (HMMs) describing the spatio-temporal patterns related to the imagination. Due to the known asymmetries during motor imagery of rightand left-hand movement, an HMM-based classifier allowing asymmetrical structures is introduced. The... View full abstract»
Cited by: Papers (12) | Patents (2)
Presents the cognizant enterprise maturity model (CEMM). The model provides tripartite usage of calibration, capability assessment and maturity advancement. The entry point is an organizational and departmental profiler that provides relevance measures based on fuzzy multicriteria group decision-making capabilities to key maturity areas (KMAs) identified for the five-level maturity model. These re... View full abstract»
Cited by: Papers (6) | Patents (3)
When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies and heterogeneity of representations, problems arise in combining multiple domains when the domains are merged. The knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. This h... View full abstract»
Cited by: Papers (22)
A radial basis function (RBF) neural network (NN) is proposed to develop a rainfall-runoff model for three-hour-ahead flood forecasting. For faster training speed, the RBF NN employs a hybrid two-stage learning scheme. During the first stage, unsupervised learning, fuzzy min-max clustering is introduced to determine the characteristics of the nonlinear RBFs. In the second stage, supervised learnin... View full abstract»
Cited by: Papers (46)
We present a tutorial on knowledge management (KM) and a roadmap of this special issue around the knowledge life-cycle. Knowledge management is a discipline that provides a strategy, process and technology to share and leverage information and expertise that increases our level of understanding, to more effectively solve problems and make decisions. We address three key views: (1) codification (ta... View full abstract»
Cited by: Papers (75)
Research in the information processing, situated learning and social network traditions has consistently demonstrated the importance of social networks for acquiring information. However, we know little about how organizational relationships established by a relative position in a formal structure or social relationships established by interpersonal processes influence who is sought out for variou... View full abstract»
Aims & Scope
This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Human-Machine Systems.
Overview, tutorial and application papers concerning all areas of interest to the SMC Society: systems engineering, human factors and human machine systems, and cybernetics and computational intelligence.
Authors should submit human-machine systems papers to the IEEE Transactions on Human-Machine Systems.
Authors should submit systems engineering papers to the IEEE Transactions on Systems, Man and Cybernetics: Systems.
Authors should submit cybernetics papers to the IEEE Transactions on Cybernetics.
Authors should submit social system papers to the IEEE Transactions on Computational Social Systems.
Meet Our Editors
Dr. Vladimir Marik
(until 31 December 2012)