Cybernetics, system(s) theory, information theory and Fuzzy Sets and Systems in the 1950s and 1960s

About 60 years ago Norbert Wiener and Claude Elwood Shannon established the new scientific discipline of information theory. However, it is very probable that Shannon’s article A Mathematical Theory of Communication would not have become famous without the help of Warren Weaver, whose popular text on “The Mathematics of Communication” re-interpreted Shannon’s work for broader scientific audiences. Weaver’s “preface” and Shannon’s article were published together in the book The Mathematical Theory of Communication. Norbert Wiener’s Cybernetics was an even more popular event, when it appeared in print. However publications were influential on two scientific areas with concepts unmentioned or unelaborated within the texts themselves: Systems Theory and information theory. A “General System Theory” had already been created by Ludwig von Bertalanffy in the late 1920s for biological and philosophical research. This approach melded in North America in the 1950s with cybernetics, as well as a new system theoretical approach in engineering sciences in the 1950s. Bertalanffy’s “General System Theory” - or simply “systems theory” was used, became even more famous in humanities. In the 1960s attempts to yield both systems theory took root in the humanities, with mixed success.This paper will review the links across these fields showing the influences across cybernetics, system(s) theory and information theory throughout the 1950s and the theory of Fuzzy Sets and Systems. Then we focus to the non-technical but philosophical aspects of information theory. When Weaver emphasized not the technical but the semantic and influential problems of communication, his arguments were very similar to Charles W. Morris’ foundations of the Theory of Signs (1938) - Semiotics. We will show some interesting ideas of Weaver related to semiotic thinking and we will advocate a “fuzzy information theory” that has to be appropriate to cover this “semiotic concept of information”. Finally, the paper presents epistemological reflections in historical perspective on the concept of “information” as a “fluctuating object” that we take as a fuzzy concept.     

Does Internet use reflect your personality? Relationship between Eysenck’s personality dimensions and Internet use

The aim of this study was to investigate the relationship between three Eysenckian personality dimensions – psychoticism, extroversion and neuroticism – and the Internet use. A sample of 427 Turkish university students completed the Eysenck’s Personality Questionnaire, an Internet survey which contained questions about interpersonal motives for Internet use and a scale for measuring the tendency for expressing one’s “true” self on the Internet. The results indicated that psychoticism was the only personality dimension related to establishing new relationships and having “Internet only” friends; and extroversion was the only personality dimension that is related to maintaining long-distance relationships, and supporting daily face-to-face relationships. The results supported the idea that for some individuals, Internet can be used as social substitute for face-to-face social interactions while for some others it can be used as a tool of social extension, depending on the user’s personality characteristics. Also, psychoticism and neuroticism were found to be positively associated with the expressing “true self” on the Internet, and it was shown that the relationship between psychoticism and Internet uses as social substitute is mediated by the tendency to express one’s true self on the Internet.     

Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey)

This study presents a data-driven and semiautomatic classification system carried out by object-based image analysis and fuzzy logic in a selected landslide-prone area in the Western Black Sea region of Turkey. In the first stage, a multiresolution segmentation process was performed using Landsat ETM+ satellite images of the study area. The model was established on 5235 image objects obtained by the segmentation process. A total of 70 landslide locations and 10 input parameters including normalized difference vegetation index, slope angle, curvature, brightness, mean band blue, asymmetry, shape index, length/width ratio, gray level co-occurrence matrix, and mean difference to infrared band were considered in the analyses. Membership functions were used to classify the study area by five fuzzy operators such as “and”, “or”, “mean arithmetic”, “mean geometric”, and “algebraic product”. In order to assess the performances of the so-produced maps, 700 image objects, which were not used in the model, were taken into consideration. Based on the results, the map produced by “fuzzy and” operator performed better than those classified by the other fuzzy operators. The proposed methodology applied in this study may be useful for decision makers, local administrations, and scientists interested in landslides. It may also be useful in landslide-prone areas for planning, management, and regional development purposes.     

Multi-level cognitive machine-learning based concept for human-like “artificial” walking: Application to autonomous stroll of humanoid robots

We propose a machine-learning based multi-level cognitive model inspired from early-ages’ cognitive development of human’s locomotion skills for humanoid robot’s walking modeling. Contrary to the most of already introduced works dealing with biped robot’s walking modeling, which place the problem within the context of controlling specific kinds of biped robots, the proposed model attends to a global concept of biped walking ability’s construction independently from the robot to which the concept may be applied. The chief-benefit of the concept is that the issued machine-learning based structure takes advantage from “learning” capacity and “generalization” propensity of such models: allowing a precious potential to deal with high dimensionality, nonlinearity and empirical proprioceptive or exteroceptive information. Case studies and validation results are reported and discussed evaluating potential performances of the proposed approach.     

Postural stability effects of random vibration at the feet of construction workers in simulated elevation

The risk of falls from height on a construction site increases under conditions which degrade workers’ postural control. At elevation, workers depend heavily on sensory information from their feet to maintain balance. The study tested two hypotheses: “sensory enhancement” – sub-sensory (undetectable) random mechanical vibrations at the plantar surface of the feet can improve worker’s balance at elevation; and “sensory suppression” – supra-sensory (detectable) random mechanical vibrations can have a degrading effect on balance in the same experimental settings.Six young (age 20–35) and six aging (age 45–60) construction workers were tested while standing in standard and semi-tandem postures on instrumented gel insoles. The insoles applied sub- or supra-sensory levels of random mechanical vibrations to the feet. The tests were conducted in a surround-screen virtual reality system, which simulated a narrow plank at elevation on a construction site. Upper body kinematics was assessed with a motion-measurement system. Postural stability effects were evaluated by conventional and statistical mechanics sway measures, as well as trunk angular displacement parameters.Analysis of variance did not confirm the “sensory enhancement” hypothesis, but provided evidence for the “sensory suppression” hypothesis. The supra-sensory vibration had a destabilizing effect, which was considerably stronger in the semi-tandem posture and affected most of the sway variables.Sensory suppression associated with elevated vibration levels on a construction site may increase the danger of losing balance. Construction workers at elevation, e.g., on a beam or narrow plank might be at increased risk of fall if they can detect vibrations under their feet. To reduce the possibility of losing balance, mechanical vibration to supporting structures used as walking/working surfaces should be minimized when performing construction tasks at elevation.     

The effect of an information ethics course on the information ethics values of students - A Chinese guanxi culture perspective

The development of information technology has a significant influence on social structure and norms, and also impacts upon human behavior. In order to achieve stability and social harmony, people need to respect various norms, and have their rights protected. Students’ information ethics values are of critical and radical importance in achieving this goal. Using qualitative approach, the present study utilizes Kohlberg’s CMD model to measure improvement in students’ “information ethics values” through “technology mediated learning (TML)” models, and to assess the extent to which it is influenced by gender and Chinese guanxi culture. We find that while e-learning improves female students’ “respect rules,” “privacy,” “accessibility” and “intellectual property” values more than male students, the percentages relating to “intellectual property” for females in the higher stages remain lower than for males. Moreover, these results are interpreted from a Chinese guanxi culture perspective. In light of these results, educators should take account of such improvements when designing effective teaching methods and incentives.     

An industry approach to shared, cross-organisational engineering change handling - The road towards standards for product data processing

Standards for cross-enterprise communication between systems that actively manage product data and which control the associated workflows–including release and approval processes–have been in industrial use for some time. Experiences gained during the last decade showed that purely data centric approaches, such as supported by IGES, ISO 10303 (STEP) and IFC are not sufficient. Cross-enterprise communication requires not only agreements about data format and semantics, but also about orderly procedures for efficient communication between the stakeholders in a workflow.This paper presents the background and approach taken for the development of a standard for cross-company engineering change management (ECM), which is currently undertaken as a joint activity between VDA (German Association of the Automotive Industry) and ProSTEP iViP (international association for information integration in industry). Based on the results of this joint activity, which was recently published as SASIG ECM Recommendation V2.0 and as VDA 4965 V3.0, ECM Pilot implementations within member companies were conducted. They proved that a lead-time reduction of the engineering change process of 20%–40% is possible while the quality of the process increases. The approach itself should work not only in engineering change or product data environments, but also in document oriented environments as well as in sectors other than automotive.The ECM standard provides specifications of reference business processes, including the definition of the participants’ roles and the interaction and synchronization (“touch”) points where data are communicated. It leverages and builds on other established product data standards wherever possible. Thus, the data model defined by STEP AP214, (Core Data for automotive mechanical design processes) is used to describe the “payload”–i.e. the product data content to be exchanged–at defined synchronization points. OMG’s PLM Services provide the framework for sending messages between the stakeholders of an Engineering Change, and business process modelling languages such as e.g. BPEL (Business Process Execution Language), standardized by OASIS, provide the capability to execute the ECM protocol’s specification. They ensure the ability to use the latest state-of-the-art internet technologies such as XML and web-services.     

System of Systems and Big Data analytics – Bridging the gap

Large data has been accumulating in all aspects of our lives for quite some time. Advances in sensor technology, the Internet, wireless communication, and inexpensive memory have all contributed to an explosion of “Big Data”. System of Systems (SoS) integrate independently operating, non-homogeneous systems to achieve a higher goal than the sum of the parts. Today’s SoS are also contributing to the existence of unmanageable “Big Data”. Recent efforts have developed a promising approach, called “Data Analytics”, which uses statistical and computational intelligence (CI) tools such as principal component analysis (PCA), clustering, fuzzy logic, neuro-computing, evolutionary computation (such as genetic algorithms), Bayesian networks, etc. to reduce the size of “Big Data” to a manageable size and apply these tools to (a) extract information, (b) build a knowledge base using the derived data, and (c) eventually develop a non-parametric model for the “Big Data”. This paper demonstrates how to construct a bridge between SoS and Data Analytics to develop reliable models for such systems. The subject material for this demonstration is using data analytics to generate a model to forecast produced photovoltaic energy to assist in the optimization of a micro grid SoS. Tools like fuzzy interference, neural networks, PCA, and genetic algorithms are used.     

Machine learning approach to model sport training

The aim of this study was to use a machine learning approach combining fuzzy modeling with an immune algorithm to model sport training, in particular swimming. A proposed algorithm mines the available data and delivers the results in a form of a set of fuzzy rules “IF (fuzzy conditions) THEN (class)”. Fuzzy logic is a powerful method to cope with continuous data, to overcome problem of overlapping class definitions, and to improve the rule comprehensibility. Sport training is modeled at the level of microcycle and training unit by 12 independent attributes. The data was collected in two months (February-March 2008), among swimmers from swimming sections in Wroc?aw, Poland. The swimmers had minimum of 7 years of training and reached the II class level in swimming classification from 2005 to 2008. The goal of the performed experiments was to find the rules answering the question - how does the training unit influence swimmer’s feelings while being in water the next day? The fuzzy rules were inferred for two different scales of the class to be predicted. The effectiveness of the learned set of rules reached 68.66%. The performance, in terms of classification accuracy, of the proposed approach was compared with traditional classifier schemes. The accuracy of the result of compared methods is significantly lower than the accuracy of fuzzy rules obtained by a method presented in this study (paired t-test, P < 0.05).     

Nonlocality as well as rejection of realism are only sufficient (but non-necessary!) conditions for violation of Bell’s inequality

In this review we remind the viewpoint that violation of Bell’s inequality might be interpreted not only as an evidence of the alternative - either nonlocality or “death of reality” (under the assumption the quantum mechanics is incomplete). Violation of Bell’s type inequalities is a well known sufficient condition of probabilistic incompatibility of random variables - impossibility to realize them on a single probability space. Thus, in fact, we should take into account an additional interpretation of violation of Bell’s inequality - a few pairs of random variables (two-dimensional vector variables) involved in the EPR-Bohm experiment are incompatible. They could not be realized on a single Kolmogorov probability space. Thus, one can choose between: (a) completeness of quantum mechanics; (b) nonlocality; (c) “ death of reality”; (d) non-Kolmogorovness. In any event, violation of Bell’s inequality has a variety of possible interpretations. Hence, it could not be used to obtain the definite conclusion on the relation between quantum and classical models.     

Application of practical fuzzy arithmetic to fuzzy internal model control

This paper applies a new fuzzy arithmetic of interval calculus and fuzzy quantities to automatic control. Practical results are obtained which overcome those based on the extension principle or α-cuts. The proposed approach is based on a different representation of fuzzy numbers, though most common arithmetic operators cannot be directly applied for designing a fuzzy controller due to the unjustified overestimation effect. To avoid this phenomenon, a procedure based on an “exact” resolution calculus is proposed, whose solutions allow creating a fuzzy internal model control scheme. The validity of the new method is illustrated by a real-time educational engineering application on classical control design: a coupled tanks system.     

Podcasting by synchronising PowerPoint and voice: What are the pedagogical benefits?

The purpose of this study was to investigate the efficacy of audio–visual synchrony in podcasting and its possible pedagogical benefits. ‘Synchrony’ in this study refers to the simultaneous playback of audio and video data streams, so that the transitions between presentation slides occur at “lecturer chosen” points in the audio commentary. Manufacturers of lecture recording software (e.g. ProfCast) would have us believe that the synchrony of image and audio should improve the learning experience. We have yet to see in the literature any empirical evidence to support this hypothesis. In our study, 90 participants in two groups undertook two electronic lectures (e-lectures) on two separate topics, the subject matter of neither was familiar to them beforehand. Each group experienced one “synchronous” presentation (e-lecture) of one of the topics, and one “separate” presentation (i.e. PowerPoint and audio files separately presented) of the other topic. Each group therefore experienced both “synchronous” and “separate” delivery and they were then given an MCQ test that assessed five levels of Bloom’s taxonomy. Results show no differences in innate ability between the two groups but the evidence supported our primary hypothesis in that statistically significantly higher test scores were seen when participants viewed a synchronous e-lecture; these scores were accounted for by subjects’ performance at three of the five levels of Bloom’s taxonomy. Qualitative ‘attitude’ survey results also displayed participant preference towards the synchronous over the asynchronous mode of delivery, and in spite of general acceptance of the proposed benefits of electronic proceedings, a majority preference towards traditional rather than electronic lectures. Despite this conservatism, this paper explores in more detail the potential benefits of podcasting via synchronous PowerPoint and voice.     

A facility location model for logistics systems including reverse flows: The case of remanufacturing activities

After a brief introduction to the basic concepts of reverse logistics, we present a two-level location problem with three types of facility to be located in a specific reverse logistics system, named a Remanufacturing Network (RMN). For this problem, we propose a 0–1 mixed integer programming model, in which we simultaneously consider “forward” and “reverse” flows and their mutual interactions. An algorithm based on Lagrangian heuristics is developed and the model is tested on data adapted from classical test problems.     

Exploring the value of purchasing online game items

The aims of this paper are to: (1) modify the theory of consumption values in order to investigate online game users’ perceived value of purchasable game items, and (2) develop a new construct – the “integrated value of purchasing game items” – based on the modified theory of consumption values. We found that the enjoyment, character competency, visual authority, and monetary values are appropriate for describing how online game users perceive the value of game items. Utilizing second order analysis, the “integrated value of purchasing game items” was developed. To show the validity of the new construct, we developed a research model and tested it using the results of 327 valid questionnaires. Results revealed that the new construct is statistically significant in affecting users’ intention to purchase game items.     

Fuzzy rule based decision trees

This paper presents a new architecture of a fuzzy decision tree based on fuzzy rules – fuzzy rule based decision tree (FRDT) and provides a learning algorithm. In contrast with “traditional” axis-parallel decision trees in which only a single feature (variable) is taken into account at each node, the node of the proposed decision trees involves a fuzzy rule which involves multiple features. Fuzzy rules are employed to produce leaves of high purity. Using multiple features for a node helps us minimize the size of the trees. The growth of the FRDT is realized by expanding an additional node composed of a mixture of data coming from different classes, which is the only non-leaf node of each layer. This gives rise to a new geometric structure endowed with linguistic terms which are quite different from the “traditional” oblique decision trees endowed with hyperplanes as decision functions. A series of numeric studies are reported using data coming from UCI machine learning data sets. The comparison is carried out with regard to “traditional” decision trees such as C4.5, LADtree, BFTree, SimpleCart, and NBTree. The results of statistical tests have shown that the proposed FRDT exhibits the best performance in terms of both accuracy and the size of the produced trees.     

A note on “fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain”

Liang (2008) [Liang, T. -F. (2008). A note on “fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain”. Computers & Industrial Engineering, 55, 676–694] proposed a production/distribution planning model and its solution approach in fuzzy environment. However, his mathematical model does not use backordering option. The main purpose of this paper is to demonstrate this handicap and propose a valid constraint.     

On discovery of soft associations with “most” fuzzy quantifier for item promotion applications

In item promotion applications, there is a strong need for tools that can help to unlock the hidden profit within each individual customer’s transaction history. Discovering association patterns based on the data mining technique is helpful for this purpose. However, the conventional association mining approach, while generating “strong” association rules, cannot detect potential profit-building opportunities that can be exposed by “soft” association rules, which recommend items with looser but significant enough associations. This paper proposes a novel mining method that automatically detects hidden profit-building opportunities through discovering soft associations among items from historical transactions. Specifically, this paper proposes a relaxation method of association mining with a new support measurement, called soft support, that can be used for mining soft association patterns expressed with the “most” fuzzy quantifier. In addition, a novel measure for validating the soft-associated rules is proposed based on the estimated possibility of a conditioned quantified fuzzy event. The new measure is shown to be effective by comparison with several existing measures. A new association mining algorithm based on modification of the FT-Tree algorithm is proposed to accommodate this new support measure. Finally, the mining algorithm is applied to several data sets to investigate its effectiveness in finding soft patterns and content recommendation.     

Synthesis of fuzzy logic and Dempster–Shafer Theory for the simulation of the decision-making process in stock trading systems

Modern computerized stock trading systems (mechanical trading systems) are based on the simulation of the decision-making process and generate advice for traders to buy or sell stocks or other financial tools by taking into account the price history, technical analysis indicators, accepted rules of trading and so on. Two stock trading simulating systems based on trading rules defined using fuzzy logic are developed and compared. The first is based on the so-called “Logic-Motivated Fuzzy Logic Operators” (LMFL) approach and aims to avoid certain disadvantages of the classical Mamdani’s method, which has been developed for use in fuzzy logic controllers and not for solving the decision-making problems of stock trading. The LMFL   approach is based on the modified mathematical representation of t$t$-norm and Yager’s implication rule. The second trading system combines the tools of fuzzy logic and Dempster–Shafer Theory (DST  ) to represent the features of the decision-making process more transparently. The fuzzy representation of trading rules based on the theory of technical analysis is used in these expert systems. Since the theory of technical analysis is based on the indicators used by experts to predict stock price movements, the method maps these indicators into new inputs that can be used in a fuzzy logic system. The only required inputs to calculate these indicators are past sequences (history) of stock prices. The method relies on fuzzy logic to choose an appropriate decision when certain price movements or certain price formations occur. The optimization procedure based on historical (teaching) data is used as it significantly improves the performance of such expert systems. The efficiency of the developed expert systems is measured by comparing their outputs versus stock price movements. The results obtained using real NYSE$NYSE$ data allow us to say that the developed expert system based on the synthesis of fuzzy logic and DST provides better results and is more reliable. Moreover, such a conjunction of fuzzy logic, DST and technical analysis, makes it possible to make a profit even when trading against a dominating trend.     

Monte Carlo simulations of the 2d-Ising model in the geometry of a long stripe

The two-dimensional Ising model in the geometry of a long stripe can be regarded as a model system for the study of nanopores. As a quasi-one-dimensional system, it also exhibits a rather interesting “phase behavior”: At low temperatures the stripe is either filled with “liquid” or “gas” and “densities” are similar to those in the bulk. When we approach a “pseudo-critical point” (below the critical point of the bulk) at which the correlation length becomes comparable to the length of the stripe, several interfaces emerge and the systems contains multiple “liquid” and “gas” domains. The transition depends on the size of the stripe and occurs at lower temperatures for larger stripes. Our results are corroborated by simulations of the three-dimensional Asakura–Oosawa model in cylindrical geometry, which displays qualitatively similar behavior. Thus our simulations explain the physical basis for the occurrence of “hysteresis critical points” in corresponding experiments.