Oded Maimon

Tel Aviv University, Industrial Engineering, Faculty Member

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Papers by Oded Maimon

Fractal geometry statistical process control for non-linear pattern-based processes

Iie Transactions, Jan 7, 2013

We suggest a new statistical process control (SPC) approach for data-rich environments. The propo... more We suggest a new statistical process control (SPC) approach for data-rich environments. The proposed approach is based on the theory of fractal geometry. In particular, we develop a monitoring scheme which is based on fractal representation of the monitored data at each stage, to account for online changes in monitored processes. The proposed Fractal-SPC enables a dynamic inspection of non-linear

A distributed genetic algorithm for neural network design and training

Optimal dynamic load distribution in a class of flow-type flexible manufacturing systems

European Journal of Operational Research, Nov 6, 1991

This paper studies optimal dynamic load-distribution among parallel single-stage stations in flex... more This paper studies optimal dynamic load-distribution among parallel single-stage stations in flexible manufacturing systems and characterizes the form of the optimal policies as a function of the system state. Each work station maintains its own buffer and has independent input and output processes. At each decision epoch, a central Work-In-Process controller redistributes and routes jobs among all stations to minimize the total expected operating cost of the network system. The optimal policy for the system prescribes how many jobs will be sent to (taken from) each station so that optimal load balancing among all stations is implemented. The model takes into account holding and shortage costs for all the stations, which are assumed to be convex increasing functions, and routing costs as well. It is proved that the optimal action (number of jobs to be received) for a station is monotonically decreasing, as the number of jobs at the station grows, and is monotonically increasing, as the number of jobs at any other station grows. The resultant properties of the optimal policies for the model give fundamental guidelines on how optimal routing can be done among parallel stations by generalizing from a single-stage situation. Finally, a numerical example is presented to display the analytically proven properties of the optimal policies.

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Segmentation of Continuous Data Streams Based on a Change Detection Methodology

Advanced Information and Knowledge Processing, 2000

Most data mining algorithms assume that the historic data are the best estimator of what will hap... more Most data mining algorithms assume that the historic data are the best estimator of what will happen in the future. As more data are accumulated in a database, one should examine whether the new data agrees with the model induced from previous instances. The problem of recognizing the change of the underlying model is known as a change detection problem.

Information-Theoretic Fuzzy Approach to Knowledge Discovery in Databases

1 Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel, e-mail: maim... more

Communications: A Proof of the Complexity of Design

Kybernetes, 1992

Probabilistic sequential methodology for designing a factorial system with multiple responses

Int J Prod Res, 1999

This paper addresses the problem of optimizing a factorial system with multiple responses. A heur... more This paper addresses the problem of optimizing a factorial system with multiple responses. A heuristic termed probabilistic sequential methodology (PSM) is proposed. The PSM identi® es those designs that maximize the likelihood of satisfying a given set of functional requirements. It is based on sequential experimentation, statistical inference and a probabilistic local search. The PSM comprises three main steps: (1) screening and estimating the main location and dispersion e ects by applying fractional factorial experiments (FFE) techniques; (2) based on these e ects, establishing probabilistic measures for di erent combinations of factorlevels; and (3) constructing a set of candidate designs from which the best solution is selected by applying a heuristic local search. The PSM is attractive when the exact analytic relationship between factor-level combinations and the system's responses is unknown; when the system involves qualitative factors; and when the number of experiments is limited. The PSM is illustrated by a detailed case study of a Flexible Manufacturing Cell (FMC) design. ) is applied as a screening process and used to optimize qualitative factors. Second, the RSM is applied in order to ® ne-tune the quantitative and continuous factors, since RSM`cannot perform optimization for qualitative factors' . Shang' s use of the RSM approach requires a large number of experiments. In the case study provided, approximately 200 simulation-runs are performed to propose the best design with respect to a single performance measure. Such an extensive experimentation is suitable only when the cost per experiment is su ciently low.

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Fuzzy Approach to Data Reliability

Studies in Fuzziness and Soft Computing, 2000

A novel, fuzzy approach to deal with reliability of attribute values in a relational database is ... more A novel, fuzzy approach to deal with reliability of attribute values in a relational database is presented. The degree of reliability is defined as a fuzzy measure of certainty that the data is correct from user's point of view. The relation scheme is partitioned into a subset of input (completely reliable) and a subset of target (partially reliable) attributes. An information theoretic connectionist network is constructed to evaluate the information content of links between input and target attributes. The network connection weights are used to calculate the reliability degrees of target attribute values. The method is applied to a real-world database, which includes partially reliable information. This work aims at improving reliability of data in a relational database by developing a framework for evaluating and representing reliability of attribute values in database tuples.

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Anytime Algorithm for Feature Selection

Lecture Notes in Computer Science, 2001

Feature selection is used to improve performance of learning algorithms by finding a minimal subs... more Feature selection is used to improve performance of learning algorithms by finding a minimal subset of relevant features. Since the process of feature selection is computationally intensive, a trade-off between the quality of the selected subset and the computation time is required. In this paper, we are presenting a novel, anytime algorithm for feature selection, which gradually improves the quality of results by increasing the computation time. The algorithm is interruptible, i.e., it can be stopped at any time and provide a partial subset of selected features. The quality of results is monitored by a new measure: fuzzy information gain. The algorithm performance is evaluated on several benchmark datasets.

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Corrigendum To (quote)The Design Process: Properties, Paradigms, And Structure(quote)

Adaptive Learning for Successful Flexible Manufacturing Cell Design: A Case Study

Applied Optimization, 1998

Improving Stability of Decision Trees

International Journal of Pattern Recognition and Artificial Intelligence, 2002

Decision-tree algorithms are known to be unstable: small variations in the training set can resul... more

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Creating a Consistent 3-D Virtual Last for Problems in the Shoe Industry

Applied Optimization, 1998

Context-sensitive medical information retrieval

Studies in health technology and informatics, 2004

Substantial medical data such as pathology reports, operative reports, discharge summaries, and r... more Substantial medical data such as pathology reports, operative reports, discharge summaries, and radiology reports are stored in textual form. Databases containing free-text medical narratives often need to be searched to find relevant information for clinical and research purposes. Terms that appear in these documents tend to appear in different contexts. The con-text of negation, a negative finding, is of special importance, since many of the most frequently described findings are those denied by the patient or subsequently "ruled out." Hence, when searching free-text narratives for patients with a certain medical condition, if negation is not taken into account, many of the retrieved documents will be irrelevant. The purpose of this work is to develop a methodology for automated learning of negative context patterns in medical narratives and test the effect of context identification on the performance of medical information retrieval. The algorithm presented significantl...

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Neighborhood Evaluation in Recommender Systems Using the Realization Based Entropy Approach

International Journal of Business Analytics, 2014

Unsupervised zoning of scientific articles using huffman trees

2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, 2008

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Analysis and Control of Flexible Multi-Robot Operations

Concurrent Logic Programming for Multiple Robots

Concluding Reflections

A System Performance Scale for Engineering Team Decision-Making

Oded Maimon

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