Fuzzy functions with LSE

“Fuzzy Functions” are proposed to be determined by the least squares estimation (LSE) technique for the development of fuzzy system models. These functions, “Fuzzy Functions with LSE” are proposed as alternate representation and reasoning schemas to the fuzzy rule base approaches. These “Fuzzy Functions” can be more easily obtained and implemented by those who are not familiar with an in-depth knowledge of fuzzy theory. Working knowledge of a fuzzy clustering algorithm such as FCM or its variations would be sufficient to obtain membership values of input vectors. The membership values together with scalar input variables are then used by the LSE technique to determine “Fuzzy Functions” for each cluster identified by FCM. These functions are different from “Fuzzy Rule Base” approaches as well as “Fuzzy Regression” approaches. Various transformations of the membership values are included as new variables in addition to original selected scalar input variables; and at times, a logistic transformation of non-scalar original selected input variables may also be included as a new variable. A comparison of “Fuzzy Functions-LSE” with Ordinary Least Squares Estimation (OLSE)” approach show that “Fuzzy Function-LSE” provide better results in the order of 10% or better with respect to RMSE measure for both training and test cases of data sets.     

Speech enhancement based on undecimated wavelet packet-perceptual filterbanks and MMSE–STSA estimation in various noise environments

In this paper, we proposed a new speech enhancement system, which integrates a perceptual filterbank and minimum mean square error–short time spectral amplitude (MMSE–STSA) estimation, modified according to speech presence uncertainty. The perceptual filterbank was designed by adjusting undecimated wavelet packet decomposition (UWPD) tree, according to critical bands of psycho-acoustic model of human auditory system. The MMSE–STSA estimation (modified according to speech presence uncertainty) was used for estimation of speech in undecimated wavelet packet domain. The perceptual filterbank provides a good auditory representation (sufficient frequency resolution), good perceptual quality of speech and low computational load. The MMSE–STSA estimator is based on a priori SNR estimation. A priori SNR estimation, which is a key parameter in MMSE–STSA estimator, was performed by using “decision directed method.” The “decision directed method” provides a trade off between noise reduction and signal distortion when correctly tuned. The experiments were conducted for various noise types. The results of proposed method were compared with those of other popular methods, Wiener estimation and MMSE–log spectral amplitude (MMSE–LSA) estimation in frequency domain. To test the performance of the proposed speech enhancement system, three objective quality measurement tests (SNR, segSNR and Itakura–Saito distance (ISd)) were conducted for various noise types and SNRs. Experimental results and objective quality measurement test results proved the performance of proposed speech enhancement system. The proposed speech enhancement system provided sufficient noise reduction and good intelligibility and perceptual quality, without causing considerable signal distortion and musical background noise.     

Integrating artificial neural networks with rule-based expert systems

The Rule-Based (RB) and the Artificial Neural Network (ANN) approaches to expert systems development have each demonstrated some specific advantages and disadvantages. These two approaches can be integrated to exploit the advantages and minimize the disadvantages of each method used alone. An RB/ANN integrated approach is proposed to facilitate the development of an expert system which provides a “high-performance” knowledge-based network, an explanation facility, and an input/output facility. In this case study an expert system designed to assist managers in forecasting the performance of stock prices is developed to demonstrate the advantages of this integrated approach and how it can enhance support for managerial decision making.     

Control design for recycled, multi unit processes

An integrated multi-unit chemical plant presents a challenging control design problem due to the existence of recycling streams. In this paper, we develop a framework for analyzing the effects of recycling dynamics on closed-loop performance from which a systematic design of a decentralized control system for a recycled, multi-unit plant is established. In the proposed approach, the recycled streams are treated as unmodelled dynamics of the “unit” model so that their effects on closed-loop stability and performance can be analyzed using the robust control theory. As a result, two measures are produced: (1) the ν-gap metric, which quantifies the strength of recycling effects, and (2) the maximum stability margin of “unit” controller, which represents the ability of the “unit” controller to compensate for such effects. A simple rule for the “unit” control design is then established using the combined two measures in order to guarantee the attainment of good overall closed-loop performances. As illustrated by several design examples, the controllability of a recycled, multi unit process under a decentralized “unit” controller can be determined without requiring any detailed design of the “unit” controller because the simple rule is calculated from the open-loop information only.     

Robot planning system

The paper discusses the development of a computer-aided robot planning system. The proposed methodical procedure is based on the steps of “Manufacturing Systems Analysis, Determination of Basic Data, Documentation of Information, System Layout Planning and Evaluation, Decision on Economic Feasibility, Final Detailing of the Planned System and Planning of the Systems Installation”, which are described in detail. Further software modules, corresponding to the phases in the planning procedure, as well as the data flow requirements, are presented.     

Teaching programming: A spiral approach to syntax and semantics

Coupling the recently proposed syntactic/semantic model of programmer behavior [1] with classic educational psychological theories yields new insights to teaching programming to novices. These new insights should make programming education more natural to students. alleviate “computer shock” (the analog of “math anxiety” [2]) and promote the development of widespread “computer literacy”.The spiral approach is the parallel acquisition of syntactic and semantic knowledge in a sequence which provokes student interest by using meaningful examples, builds on previous knowledge, is in harmony with the student's cognitive skills, provides reinforcement of recently acquired material and develops confidence through successful accomplishment of increasingly difficult tasks. The relationship of structured programming and flowcharts to the spiral approach is discussed.     

Globally stable PID-like control of mechanical systems

Decoupled PID control with actuator constraints and velocity measurement or estimation achieves global asymptotic stability of the desired configuration, if there is some friction in the controlled mechanical system and the signals to be integrated are limited accordingly. Stability analysis using the direct Lyapunov method and Gershgorin's “circle theorem” gives these limits and physically meaningful lower bounds on position control gains. A simple procedure is proposed for selecting the design parameters and determining the gains of the controllers.     

Guidelines for the development of e-learning systems by means of proactive questions

The current development approaches for e-learning systems fail to explain in a clear and consistent way the pedagogical principles that support them. Moreover, decisions with regard to the structuration of each component proposed by these approaches are mainly taken by the designer/developer. As a result, the ensuing e-learning systems reflect “common sense” rather than a theoretically informed and systematic design.The present paper proposes a global architecture model for any e-learning system whose blocks are extracted from the analysis of the main approaches that currently guide the development of these kinds of systems. We use Kipling’s famous questions to define and structure the blocks of the proposed model, and we base the answers to these questions on two disciplines that are closed to e-learning: presential education (i.e., its pedagogical theories) and knowledge management.     

Implementation of higher-order asymptotics to S-plus

Higher-order asymptotics is an active area of development in theoretical statistics. However, most existing work in higher-order asymptotics is directed to the theoretical aspects. This paper attempts to incorporate higher-order inference procedures to S-plus, a widely used software in statistics. Algorithm is developed in the settings of generalized linear models and nonlinear regression models. The proposed algorithm generalizes the standard S-plus functions “glim” and “nls” in the sense that both the first-order and higher-order p-values are provided, and its manipulation is straightforward.     

Realization of STEP-NC enabled machining

A STEP-compliant CNC machine tool that demonstrated a G-code free machining scenario is presented. The aim of this research is to showcase the advantages of, and evaluate, STEP-NC—a new NC data model—by implementing it in a legacy CNC system. The work consists of two parts: retrofitting an existing CNC machine and the development of a STEP-compliant NC Converter called STEPcNC. The CompuCam's motion control system is used for retrofitting the machine, which is programmable using its own motion control language—6K Motion Control language and capable of interfacing with other CAPP/CAM programs through languages such as Visual Basic, Visual C++ and Delphi. STEPcNC can understand and process STEP-NC codes, and interface with the CNC controller through a Human Machine Interface. It makes use of STEP-NC information such as “Workplan”, “Workingstep”, machining strategy, machining features and cutting tools that is present in a STEP-NC file. Hence, the system is truly feature-based. The Application Interpreted Model of STEP-NC has been used.     

Dynamic learning from multiple examples for semantic object segmentation and search

We present a novel “dynamic learning” approach for an intelligent image database system to automatically improve object segmentation and labeling without user intervention, as new examples become available, for object-based indexing. The proposed approach is an extension of our earlier work on “learning by example,” which addressed labeling of similar objects in a set of database images based on a single example. The proposed dynamic learning procedure utilizes multiple example object templates to improve the accuracy of existing object segmentations and labels. Multiple example templates may be images of the same object from different viewing angles, or images of related objects. This paper also introduces a new shape similarity metric called normalized area of symmetric differences (NASD), which has desired properties for use in the proposed “dynamic learning” scheme, and is more robust against boundary noise that results from automatic image segmentation. Performance of the dynamic learning procedures has been demonstrated by experimental results.     

Input-to-state stabilization for nonlinear dual-rate sampled-data systems via approximate discrete-time model

The problem of state feedback stabilization of nonlinear sampled-data systems is considered under the “low measurement rate” constraint. A dual-rate control scheme is proposed that utilizes a numerical integration scheme to approximately predict the current state. Given an approximate discrete-time model of a sampled nonlinear plant and given a family of controllers that stabilizes the plant model in input-to-state sense, we show that under some standard assumptions the closed loop dual-rate sampled data system is input-to-state stable in the semiglobal practical sense.     

Network flow control under capacity constraints: A case study

In this paper, we demonstrate how tools from nonlinear system theory can play an important role in tackling “hard nonlinearities” and “unknown disturbances” in network flow control problems. Specifically, a nonlinear control law is presented for a communication network buffer management model under physical constraints. Explicit conditions are identified under which the problem of asymptotic regulation of a class of networks against unknown inter-node traffic is solvable, in the presence of control input and state saturation. The conditions include a Lipschitz-type condition and a “PE” condition. Under these conditions, we achieve either asymptotic or practical regulation for a single-node system. We also propose a decentralized, discontinuous control law to achieve (global) asymptotic regulation of large-scale networks. Our main result on controlling large-scale networks is based on an interesting extension of the well-known Young's inequality for the case with saturation nonlinearities. We present computer simulations to illustrate the effectiveness of the proposed flow control schemes.     

Beyond RACF: Extending user authentication controls

A discussion on passwords and user i.d.s as the central point for security control is presented, with recommendations for stricter control, and identifying weaknesses in this approach. Use of “tokens” for authentication is discussed, concentrating on currently available devices, including IBM's TSS. The impact of authentication on the US NCSC standards (the “Orange Book”) and the proposed ITSEC standards are considered.     

Expressing Priorities and External Probabilities in Process Algebra via Mixed Open/Closed Systems

Defining operational semantics for a process algebra is often based either on labeled transition systems that account for interaction with a context or on the so-called reduction semantics: we assume to have a representation of the whole system and we compute unlabeled reduction transitions (leading to a distribution over states in the probabilistic case). In this paper we consider mixed models with states where the system is still open (towards interaction with a context) and states where the system is already closed. The idea is that (open) parts of a system “P” can be closed via an operator “P↑G” that turns already synchronized actions whose “handle” is specified inside “G” into prioritized reduction transitions (and, therefore, states performing them into closed states). We show that we can use the operator “P↑G” to express multi-level priorities and external probabilistic choices (by assigning weights to handles inside G), and that, by considering reduction transitions as the only unobservable τ transitions, the proposed technique is compatible, for process algebra with general recursion, with both standard (probabilistic) observational congruence and a notion of equivalence which aggregates reduction transitions in a (much more aggregating) trace based manner. We also observe that the trace-based aggregated transition system can be obtained directly in operational semantics and we present the “aggregating” semantics. Finally, we discuss how the open/closed approach can be used to also express discrete and continuous (exponential probabilistic) time and we show that, in such timed contexts, the trace-based equivalence can aggregate more with respect to traditional lumping based equivalences over Markov Chains.     

Movie forecast Guru: A Web-based DSS for Hollywood managers

Herein we describe a Web-based DSS to help Hollywood managers make better decisions on important movie characteristics, such as, genre, super stars, technical effects, release time, etc. These parameters are used to build prediction models to classify a movie in one of nine success categories, from a “flop” to a “blockbuster”. The system employs a number of traditional and non-traditional prediction models as distributed independent experts, implemented as Web services. The paper describes the purpose and the architecture of the system, the development environment, the user assessment results, and the lessons learned as they relate to Web-based DSS development.     

A program selection/resource allocation model for control of malaria and related parasitic diseases

Malaria and related parasitic diseases are in the midst of a severe resurgence world-wide. Due to a series of complex factors reflecting shifting economic and physical conditions and life styles, purely technical approaches to control of parasitic diseases are becoming less effective. An emerging theory calling for an integration of disease control efforts with socioeconomic development is now being proposed as essential to future success. This paper seeks to systematically identify and organize the basic tenets of this “integrated approach.” Based on the resulting analysis, a multiobjective planning and resource allocation model is formulated to help identify “most effective” program-based disease/development intervention strategies. Guidelines are offered for the quantification, sensitivity analysis, and solution of the model in real-world problem contexts. The model represents a first attempt to formally interface the major societal dimensions critical to control of parasitic diseases.     

Computer numerical control for assuring the machining accuracy of contour milling

In this paper, a software technology for improving the machining accuracy in contour milling is discussed, in which the continuous path control is thoroughly investigated from the viewpoint of system synthesis, and the computer numerical control is effectively used. It is shown that the proposed “real-time cutter path rectification” offers an effective means to overcome the serious problem of the thermal deformation of workpieces. In this case, it is necessary to take many factors into consideration; the diversity of shapes, the change of cutting conditions, the unstable thermal situation, and so on. Therefore, the adaptive control is applied to compensate the thermal displacement of the contour during the cutting process. Relating to this subject, the effective cutter radius, which depends on cutter wear, is also evaluated in real-time operation; and the cutter diameter compensation is included in the “cutter path rectification”. In order to assure the machining accuracy, a new approach to contour measurement is proposed, in which the continuous path control by CNC system is used. It is certified through some experiments that the method proposed in this paper is useful to realize the flexible automation with high machining accuracy.     

The formation of learners’ semiosphere by authentic inquiry with an integrated learning object “Young Scientist”

An integrated learning object, a web-based inquiry environment “Young Scientist” for basic school level is introduced by applying the semiosphere conception for explaining learning processes. The study focused on the development of students’ (n = 30) awareness of the affordances of learning objects (LO) during the 3 inquiry tasks, and their ability of dynamically reconstructing meanings in the inquiry subtasks through exploiting these LO affordances in “Young Scientist”. The problem-solving data recorded by the inquiry system and the awareness questionnaire served as the data-collection methods.It was demonstrated that learners obtain complete awareness of the LO affordances in an integrated learning environment only after several problem-solving tasks. It was assumed that the perceived task-related properties and functions of LOs depend on students’ interrelations with LOs in specific learning contexts. Learners’ overall awareness of certain LO affordances, available in the inquiry system “Young Scientist”, developed with three kinds of patterns, describing the hierarchical development of the semiosphere model for learners. The better understanding of the LO affordances, characteristic to the formation of the functioning semiosphere, was significantly related to the advanced knowledge construction during these inquiry subtasks that presumed translation of information from one semiotic system to another. The implications of the research are discussed in the frames of the development of new contextual gateways for learning with virtual objects. It is assumed that effective LO-based learning has to be organized through pedagogically constrained gateways by manifesting certain LO affordances in the context in order to build up the dynamic semiosphere model for learners.     

Implementing a hybrid simulation model for a Kanban-based material handling system

Plant floor material handling is a loose loop in most assembly plants. Simulation offers a quick, controllable and tunable approach for prototyping complex material handling processes in manufacturing environments. This paper proposes a hybrid simulation approach, using both discrete event and agent-based technologies, to model complex material handling processes in an assembly line. A prototype system is implemented using a commercial multi-paradigm modeling tool. In this prototype, JIT principles are applied to both the production and the material handling processes. The system performance is evaluated and system optimization directions are suggested. The proposed hybrid modeling approach facilitates the implementation of a responsive and adaptive environment in that various “what-if” scenarios can be simulated under different simulation configurations and real-time situations.