On the set partitioning type formulation for the discrete location problem

An approach to the discrete location problem is presented. The formulation is based on the set partitioning problem with the emphasis being placed on the weighted objective function and the importance of the “value” or “attractiveness” of the potential “covers”, i.e. the number of centres served by a specific location, FORTRAN programs were written to generate the potential subsets of centres to be served, for a specific county in northern Greece, and a mathematical programming package (APEX III) was used in its integer programming mode to provide solutions for various sets of subsets of centres which were generated according to certain criteria.     

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.     

FLASK-SG: A program to compute chemical equilibria in metamorphic petrology

Chemical equilibrium calculation program for metamorphic petrology, FLASK-SG, was written for Unix variants (Linux, IRIX, Tru64 UNIX). It is also ported to Windows 95/98. The user specifies a temperature, pressure, and substance amounts (in moles of any chemical formula in C–H–O–Si–Al–Ti–Fe–Mn–Mg–Ca–Na–K system) to this program, then it calculates the stable mineral assemblage, mineral amounts, and gas composition under the given conditions using Gibbs free energy minimization method with the Holland and Powell (1990) data set. Searching algorithm for the stable mineral assemblage is the Metropolis Monte Carlo method. The coding language is C++, and experimental object oriented programming style is adopted to make the main program part as a class library. Model-dependent functions such as fugacity coefficients and activities are implemented as virtual methods of the “systems” class, so they can be easily changed as methods of inherited class from the “systems” class. These characteristics are aimed for a future “simulation kit”.     

Strange Bedfellows: Human-Computer Interaction, Interface Design, and Composition Pedagogy

As digital interfaces increasingly mediate our access to information, the design of these interfaces becomes increasingly important. Designing digital interfaces requires writers to make rhetorical choices that are sometimes technical in nature and often correspond with principles taught in the computer science subfield of human-computer interaction. We propose that an HCI-informed writing pedagogy can complicate for both writing and computer science students the important role audience should play when designing traditional and digital interfaces. Although it is a subtle shift in many ways, this pedagogy seemed to complicate student understanding of the relationship between audience and the texts/interfaces they created: it was not just the “human” (beliefs, attitudes, values, demographics) or the “computer” (the software or hardware or other types of mediation) that mattered but rather the “interaction” between the two. First we explore some of the ways in which writing code and writing prose have merged and paved the way for an HCI-informed writing pedagogy. Next we examine some parallels between human-computer interaction principles and composition principles. Finally, we refer to assignments, student responses, and anecdotal evidence from our classes where an HCI-informed writing pedagogy drew—or could have drawn—student attention more acutely to various audience-related technical and rhetorical interface design choices.     

MCLP-based methods for improving “Bad” catching rate in credit cardholder behavior analysis

Cardholders’ behavior prediction is an important issue in credit card portfolio management. As a promising data mining approach, multiple criteria programming (MCLP) has been successfully applied to classify credit cardholders’ behavior into two groups. In order to better control credit risk for financial institutes, this paper proposes three methods based on MCLP to improve the “Bad” catching accuracy rate. One is called MCLP with unbalanced training set selection, the second is called fuzzy linear programming (FLP) method with moving boundary, and the third is called penalized multi criteria linear programming (PMCLP). The experimental examples demonstrate the promising performance of these methods.     

Stability and performance analysis of mixed product run-to-run control

Run-to-run control has been widely used in batch manufacturing processes to reduce variations. However, in batch processes, many different products are fabricated on the same set of process tool with different recipes. Two intuitive ways of defining a control scheme for such a mixed production mode are (i) each run of different products is used to estimate a common tool disturbance parameter, i.e., a “tool-based” approach, (ii) only a single disturbance parameter that describe the combined effect of both tool and product is estimated by results of runs of a particular product on a specific tool, i.e., a “product-based” approach. In this study, a model two-product plant was developed to investigate the “tool-based” and “product-based” approaches. The closed-loop responses are derived analytically and control performances are evaluated. We found that a “tool-based” approach is unstable when the plant is non-stationary and the plant-model mismatches are different for different products. A “product-based” control is stable but its performance will be inferior to single product control when the drift is significant. While the controller for frequent products can be tuned in a similar manner as in single product control, a more active controller should be used for the infrequent products which experience a larger drift between runs. The results were substantiated for a larger system with multiple products, multiple plants and random production schedule.     

MATLAB algorithm for grayscale analysis of carbonate cyclicity: example application to Demopolis chalk (Cretaceous, Alabama)

Cyclostratigraphic studies of rhythmically bedded pelagic/hemipelagic carbonate sequences, which are important for understanding paleo-oceanographic conditions and paleoclimatic controls, can be facilitated by computer-assisted grayscale analysis. Application of a simple yet flexible algorithm, “docore”, written for the MATLAB software package and its associated image processing toolbox, can be used to generate detailed grayscale curves or time series that closely approximate carbonate time series from rapidly scanned images. The potential of “docore”-derived grayscale data as proxies for carbonate is demonstrated through comparative analyses of carbonate, organic carbon and grayscale data from a core drilled within the Upper Cretaceous Demopolis Chalk of western Alabama.     

Internal reinforcement in a connectionist genetic programming approach

Genetic programming (GP) can learn complex concepts by searching for the target concept through evolution of a population of candidate hypothesis programs. However, unlike some learning techniques, such as Artificial Neural Networks (ANNs), GP does not have a principled procedure for changing parts of a learned structure based on that structure's performance on the training data. GP is missing a clear, locally optimal update procedure, the equivalent of gradient-descent backpropagation for ANNs. This article introduces a new algorithm, “internal reinforcement”, for defining and using performance feedback on program evolution. This internal reinforcement principled mechanism is developed within a new connectionist representation for evolving parameterized programs, namely “neural programming”. We present the algorithms for the generation of credit and blame assignment in the process of learning programs using neural programming and internal reinforcement. The article includes a comprehensive overview of genetic programming and empirical experiments that demonstrate the increased learning rate obtained by using our principled program evolution approach.     

Model-driven Transformation-based Generation of Java Stress Tests

This paper describes a practical application of transformation-based analysis and code generation. An overview is given of an approach for automatically constructing Java stress tests whose execution exercises all “interesting” class initialization sequence possibilities for a given class hierarchy.     

Reconfigurable control of robotized manufacturing cells

This paper investigates the field of manufacturing system control. The addressed subject is indeed very fascinating, due to the importance that it has reached in the last decades both at research and industrial level. On the other hand, it seems to the author that most of the complexity intrinsic to the subject itself relies on the different meanings or levels of abstraction that both the terms “manufacturing system” and “control” may symbolize. The presented research aims to face the topic in a concrete fashion, i.e., by developing a control software system for a specific, although easy to be generalized, robotized manufacturing cell. Two different development methodologies, from the conceptual design to the actual implementation, of a cell control system are presented and compared. The former, based on ladder logic diagrams, for a PLC controlled manufacturing cell; the latter, based on object-oriented modeling and programming techniques, for a PC controlled manufacturing cell. The analysis has been conducted considering the internal and external requirements of the manufacturing system, mostly driven by the contemporary industrial need of reconfigurable control systems, largely acknowledged as the critical key to succeed in the new era of mass customization.     

Optimal operation of Petlyuk distillation: steady-state behavior

The “Petlyuk” or “dividing-wall” or “fully thermally coupled” distillation column is an interesting alternative to the conventional cascaded binary columns for separation of multi-component mixtures. However, the industrial use has been limited, and difficulties in operation have been reported as one reason. With three product compositions controlled, the system has two degrees of freedom left for on-line optimization. We show that the steady-state optimal solution surface is quite narrow, and depends strongly on disturbances and design parameters. Thus it seems difficult to achieve the potential energy savings compared to conventional approaches without a good control strategy. We discuss candidate variables which may be used as feedback variables in order to keep the column operation close to optimal in a “self-optimizing” control scheme.     

Novel information discovery for intelligence and counterterrorism

Intelligence analysts construct hypotheses from large volumes of data, but are often limited by social and organizational norms and their own preconceptions and biases. The use of exploratory data mining technology can mitigate these limitations by requiring fewer assumptions. We present the design of the ATHENS system, which discovers novel information, relative to a specified set of existing knowledge, in large information repositories such as the World Wide Web. We illustrate the use of the system by starting from the terms “al Qaeda” and “bin Laden”" and running the ATHENS system as if on September 12th, 2001. This provides a picture of what novel information could have been known at the time. This is of some intrinsic interest, but also serves to validate the performance of the system since much of this novel information has been discovered by conventional means in the intervening years.     

A DFO technique to calibrate queueing models

A crucial step in the modeling of a system is to determine the values of the parameters to use in the model. In this paper we assume that we have a set of measurements collected from an operational system, and that an appropriate model of the system (e.g., based on queueing theory) has been developed. Not infrequently proper values for certain parameters of this model may be difficult to estimate from available data (because the corresponding parameters have unclear physical meaning or because they cannot be directly obtained from available measurements, etc.). Hence, we need a technique to determine the missing parameter values, i.e., to calibrate the model.As an alternative to unscalable “brute force” technique, we propose to view model calibration as a non-linear optimization problem with constraints. The resulting method is conceptually simple and easy to implement. Our contribution is twofold. First, we propose improved definitions of the “objective function” to quantify the “distance” between performance indices produced by the model and the values obtained from measurements. Second, we develop a customized derivative-free optimization (DFO) technique whose original feature is the ability to allow temporary constraint violations. This technique allows us to solve this optimization problem accurately, thereby providing the “right” parameter values. We illustrate our method using two simple real-life case studies.     

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.     

The information processing explanation of Gestalt phenomena

Gestalt psychology has shown the importance in human thinking and problem solving of the behavior that it labels “intuition,” “insight,” and “understanding.” This paper discusses computer programs, already described in the published literature, that stimulate exactly these kinds of behaviors. It is shown that much of what has been discussed under the heading of “insight” can be explained in terms of recognition processes that are readily simulated. Computer simulation has shown itself a powerful tool for interpreting and explaining a wide range of phenomena associated with the kinds of thinking and understanding that have been so usefully emphasized in the Gestalt literature.     

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.     

Factor structure for Young’s Internet Addiction Test: A confirmatory study

A number of diagnostic scales have been developed in recent years to assess Internet addiction. To better understand the structure, validity, and reliability of such assessment instruments, Young’s Internet Addiction Test (IAT) was evaluated using a confirmatory approach.Data collected through a survey of 410 Hong Kong university undergraduates was subjected to exploratory factor analysis and data from a hold-out sample was analyzed using confirmatory factor analysis in order to assess the psychometric properties and factor structure of the IAT scale. Three dimensions, namely, “Withdrawal and Social Problems”, “Time Management and Performance”, and “Reality Substitute” were extracted.These dimensions were then correlated with a number of criterion variables, including academic performance, online activities, gender, and Internet usage. The results show that academic performance was negatively correlated with the Internet addiction scores. The degree of Internet addiction was also found to vary across different types of online activity, with people engaged in cyberrelationships and online gambling having higher Internet addiction scores.     

Shortest distance and reliability of probabilistic networks

When the “length” of a link is not deterministic and is governed by a stochastic process, the “shortest” path between two points in the network is not necessarily always composed of the same links and depends on the state of the network. For example, in communication and transportation networks, the travel time on a link is not deterministic and the fastest path between two points is not fixed. This paper presents an algorithm to compute the expected shortest travel time between two nodes in the network when the travel time on each link has a given independent discrete probability distribution. The algorithm assumes the knowledge of all the paths between two nodes and methods to determine the paths are referenced.In reliability (i.e. the probability that two given points are connected by a path) computations, associated with each link is a probability of “failure” and a probability of “success”. Since “failure” implies infinite travel time, the algorithm simultaneously computes reliability. The paper also discusses the algorithm's capability to simultaneously compute some other performance measures which are useful in the analysis of emergency services operating on a network.     

Efficient constrained local model fitting for non-rigid face alignment

Active appearance models (AAMs) have demonstrated great utility when being employed for non-rigid face alignment/tracking. The “simultaneous” algorithm for fitting an AAM achieves good non-rigid face registration performance, but has poor real time performance (2–3 fps). The “project-out” algorithm for fitting an AAM achieves faster than real time performance (>200 fps) but suffers from poor generic alignment performance. In this paper we introduce an extension to a discriminative method for non-rigid face registration/tracking referred to as a constrained local model (CLM). Our proposed method is able to achieve superior performance to the “simultaneous” AAM algorithm along with real time fitting speeds (35 fps). We improve upon the canonical CLM formulation, to gain this performance, in a number of ways by employing: (i) linear SVMs as patch-experts, (ii) a simplified optimization criteria, and (iii) a composite rather than additive warp update step. Most notably, our simplified optimization criteria for fitting the CLM divides the problem of finding a single complex registration/warp displacement into that of finding N simple warp displacements. From these N simple warp displacements, a single complex warp displacement is estimated using a weighted least-squares constraint. Another major advantage of this simplified optimization lends from its ability to be parallelized, a step which we also theoretically explore in this paper. We refer to our approach for fitting the CLM as the “exhaustive local search” (ELS) algorithm. Experiments were conducted on the CMU MultiPIE database.     

Ascertaining Mathematical Theorems

Whereas to most logicians, the word “theorem” refers to any statement which has been shown to be true, to mathematicians, the word “Theorem” is, relatively speaking, rarely applied, and denotes something far more special. In this paper, we examine some of the underlying reasons behind this difference in terminology, and we show how this discrepancy might be exploited, in order to build a computer system which automatically selects the latter type of “Theorems” from amongst the former. Indeed, we have begun building the automated discovery system MATHsAiD, the design of which is based upon our research. We provide some preliminary results produced by this system, and compare these results to Theorems appearing in various mathematics textbooks.