A fuzzy logic model of fracture healing

A quantitative biomechanical model describes the tissue transformation during healing of a transverse osteotomy of a sheep metatarsal. The model predicts bridging of the bone ends through cartilage, followed by the growth of a callus cuff, and finally, the resorption of callus after ossification of the interfragmentary gap. We suggest bone density or the modulus of elasticity do not sufficiently characterize healing tissue for predictive purposes. In addition to the stimulus reflected by strain energy density we introduce a new osteogenic factor based upon stress gradients and which predicts areas of a high osteogenic capacity. Our model distinguishes three basic types of tissue, namely bone, cartilage and fibrous tissue. A fuzzy controller is proposed to model the tissue reaction. A set of fuzzy rules derived from medical knowledge has been implemented to describe tissue transformation such as intramembraneous or chondral ossification, atrophy or destruction. Fuzzy logic is able to model tissue transformation processes within the numerical simulation of remodeling processes. This approach improves the simulation tools and affords the potential to optimize planning of animal experiments and conduct parametric studies.     

Segmentation of protein surfaces using fuzzy logic

An algorithm has been developed that can be used to divide triangulated molecular surfaces into distinct domains on the basis of physical and topographical molecular properties. Domains are defined by a certain degree of homogeneity concerning one of these properties. The method is based on fuzzy logic strategies, thus taking into consideration the smooth changes of the properties considered along complex macromolecular surfaces. Scalar qualities assigned to every node point on a triangulated surface are translated into linguistic variables, which can then be processed using a special fuzzy dissimilarity operator.Possible applications are demonstrated using surface segmentation for properties like electrostatic potential, lipophilicity and shape for the analysis of serine proteinase substrate/inhibitor specificity.     

A multisensory integration model of human stance control

A model is presented to study and quantify the contribution of all available sensory information to human standing based on optimal estimation theory. In the model, delayed sensory information is integrated in such a way that a best estimate of body orientation is obtained. The model approach agrees with the present theory of the goal of human balance control. The model is not based on purely inverted pendulum body dynamics, but rather on a three-link segment model of a standing human on a movable support base. In addition, the model is non-linear and explicitly addresses the problem of multisensory integration and neural time delays. A predictive element is included in the controller to compensate for time delays, necessary to maintain erect body orientation. Model results of sensory perturbations on total body sway closely resemble experimental results. Despite internal and external perturbations, the controller is able to stabilise the model of an inherently unstable standing human with neural time delays of 100 ms. It is concluded, that the model is capable of studying and quantifying multisensory integration in human stance control. We aim to apply the model in (1) the design and development of prostheses and orthoses and (2) the diagnosis of neurological balance disorders. Received: 25 August 1997 / Accepted in revised form: 8 December 1998     

Sustainable transportation systems performance evaluation using fuzzy logic

Sustainability has become an overarching concern for transportation policy and planning around the world. This article presents an approach for urban transport sustainability performance evaluation using fuzzy logic. This article presents a model for transport sustainability performance evaluation. Appropriate transport sustainability indicators were identified based on literature. The model addresses all major dimensions of transport sustainability such as Economic Sustainability, Social Sustainability, Environmental Sustainability and Transportation System Effectiveness. Transport sustainability index has been computed as (5.05, 6.62, 8.12) and weaker transport sustainability attributes were found. Transport sustainability index highlights the question how far toward becoming transport sustainable is an enterprise or region? While, weaker transport sustainability attributes reveals that how can an enterprise or region improve its transport sustainability effectively? Appropriate actions were initiated to improve urban transport sustainability performance. The results indicate that the model is capable of effectively assessing transport sustainability and has practical relevance. An example is also used to illustrate the approach developed. The results obtained using fuzzy approach has been validated with conventional crisp approach. 20 transport sustainability attributes out of 60 are found to be weaker and appropriate actions were derived to improve the weaker attributes.     

Incorporating qualitative knowledge in enzyme kinetic models using fuzzy logic

Modeling of metabolic pathway dynamics requires detailed kinetic equations at the enzyme level. In particular, the kinetic equations must account for metabolite effectors that contribute significantly to the pathway regulation in vivo. Unfortunately, most kinetic rate laws available in the literature do not consider all the effectors simultaneously, and much kinetic information exists in a qualitative or semiquantitative form. In this article, we present a strategy to incorporate such information into the kinetic equation. This strategy uses fuzzy logic‐based factors to modify algebraic rate laws that account for partial kinetic characteristics. The parameters introduced by the fuzzy factors are then optimized by use of a hybrid of simplex and genetic algorithms. The resulting model provides a flexible form that can simulate various kinetic behaviors. Such kinetic models are suitable for pathway modeling without complete enzyme mechanisms. Three enzymes in Escherichia coli central metabolism are used as examples: phosphoenolpyruvate carboxylase; phosphoenolpyruvate carboxykinase; and pyruvate kinase I. Results show that, with fuzzy logic‐augmented models, the kinetic data can be much better described. In particular, complex behavior, such as allosteric inhibition, can be captured using fuzzy rules. The resulting models, even though they do not provide additional physical meaning in enzyme mechanisms, allow the model to incorporate semiquantitative information in metabolic pathway models. © 1999 John Wiley & Sons, Inc. Biotechnol Bioeng 62: 722–729, 1999.     

A fuzzy logic controller.

This paper describes a fuzzy sets method which is very useful for handling uncertainties and essential for knowledge acquisition of a human expert. Kinetics of a reactor is often complex and not trivial to describe by mathematical equations. Reactor control by traditional control technology is therefore difficult. A novel technology is presented. In the following a fuzzy inference (approximate reasoning) is used for decision making in analogy to human thinking, facilitating a more sophisticated control. Readers of this paper do not need any advanced mathematics beyond the four basic operations in arithmetic (+, -, x, divided by) and using the maximum and minimum values. This fuzzy inference is introduced to construct a fuzzy logic controller which is suitable for a nonlinear, multivariable and time variant system applied to a bioreactor.     

Control of unstable bioreactor using fuzzy tuned PI controller

A fuzzy tuning scheme for conventional PI controller is developed for controlling an unstable continuous bioreactor. The performance is compared with that of a fixed setting conventional PI controller. The performance of the tuning scheme is studied by simulating the non-linear model equations of the bioreactor. The robustness of the controller is also studied for uncertainties in the process parameters such as yield factor and measurement delay. Simulation results show that the fuzzy tuning improves the overall performance and particularly it is more robust to parameter uncertainties.     

Assessment of human operator functional state using a novel differential evolution optimization based adaptive fuzzy model

With the development of human–machine systems, there has been a growing concern about the consequences of operator performance breakdown under excessive level of workload, especially in safety-critical situations. Assessment and detection of the operator functional state (OFS) enable us to predict the high operational risks of operator. This paper adopts the psychophysiological signals and task performance measures to evaluate OFS under different levels of mental workload. Four indices extracted from electrocardiogram and electroencephalogram, including heart rate (HR), ratio of the standard deviation to the average of HR segment, task load indices (TLI1 and TLI2), are chosen as the inputs of the proposed model. A technique of differential evolution with ant colony search (DEACS) is developed to optimize the parameters of Adaptive-Network-based Fuzzy Inference System (ANFIS). The optimized ANFIS model is employed to estimate the OFS under a series of process control tasks on a simulated software platform of AUTOmation-enhanced Cabin Air Management System. The results showed that the proposed adaptive fuzzy model based on ANFIS and DEACS algorithm is applicable for the operator functional state assessment.     

An adaptive model of sensory integration in a dynamic environment applied to human stance control

An adaptive estimator model of human spatial orientation is presented. The adaptive model dynamically weights sensory error signals. More specific, the model weights the difference between expected and actual sensory signals as a function of environmental conditions. The model does not require any changes in model parameters. Differences with existing models of spatial orientation are that: (1) environmental conditions are not specified but estimated, (2) the sensor noise characteristics are the only parameters supplied by the model designer, (3) history-dependent effects and mental resources can be modelled, and (4) vestibular thresholds are not included in the model; instead vestibular-related threshold effects are predicted by the model. The model was applied to human stance control and evaluated with results of a visually induced sway experiment. From these experiments it is known that the amplitude of visually induced sway reaches a saturation level as the stimulus level increases. This saturation level is higher when the support base is sway referenced. For subjects experiencing vestibular loss, these saturation effects do not occur. Unknown sensory noise characteristics were found by matching model predictions with these experimental results. Using only five model parameters, far more than five data points were successfully predicted. Model predictions showed that both the saturation levels are vestibular related since removal of the vestibular organs in the model removed the saturation effects, as was also shown in the experiments. It seems that the nature of these vestibular-related threshold effects is not physical, since in the model no threshold is included. The model results suggest that vestibular-related thresholds are the result of the processing of noisy sensory and motor output signals. Model analysis suggests that, especially for slow and small movements, the environment postural orientation can not be estimated optimally, which causes sensory illusions. The model also confirms the experimental finding that postural orientation is history dependent and can be shaped by instruction or mental knowledge. In addition the model predicts that: (1) vestibular-loss patients cannot handle sensory conflicting situations and will fall down, (2) during sinusoidal support-base translations vestibular function is needed to prevent falling, (3) loss of somatosensory information from the feet results in larger postural sway for sinusoidal support-base translations, and (4) loss of vestibular function results in falling for large support-base rotations with the eyes closed. These predictions are in agreement with experimental results. Received: 12 November 1999 / Accepted in revised form: 30 June 2000     

Age-related changes of human balance during quiet stance

Certain aspects of balance control change with age, resulting in a slight postural instability. We examined healthy subjects between 20-82 years of age during the quiet stance under static conditions: at stance on a firm surface and/or on a compliant surface with eyes either open or closed. Body sway was evaluated from centre of foot pressure (CoP) positions during a 50 sec interval. The seven CoP parameters were evaluated to assess quiet stance and were analyzed in three age groups: juniors, middle-aged and seniors. The regression analysis showed evident increase of body sway over 60 years of age. We found that CoP parameters were significantly different when comparing juniors and seniors in all static conditions. The most sensitive view on postural steadiness during quiet stance was provided by CoP amplitude and velocity in AP direction and root mean square (RMS) of statokinesigram. New physiological ranges of RMS parameter in each condition for each age group of healthy subjects were determined. Our results showed that CoP data from force platform in quiet stance may indicate small balance impairment due to age. The determined physiological ranges of RMS will be useful for better distinguishing between small postural instability due to aging in contrast to pathological processes in the human postural control.     

Application of fuzzy logic to the Apgar scoring system

Apgar fuzzy expert system (AFES) applied fuzzy logic to the Apgar Scoring System (APG). We prepared the AFESs for both an inexperienced obstetrician (resident A) and an experience obstetrician (specialist B) separately. We then compared their evaluations of the same 80 neonates at 1 min after birth using both the AFES and the APG. Analysis of the relationship of the general evaluation by the APG (scores below 6 or over 7) and the AFES (bad or good) to the umbilical arterial blood gases (pH below or above 7.20) showed that the sensitivities were 0.36 for the APG evaluation by resident A, 0.50 for the APG evaluation by specialist B, 0.60 for the AFES rating by resident A, and 0.71 for the AFES rating by specialist B. The specificities were 0.94, 0.95, 0.97 and 0.97, respectively. These results demonstrated that the AFES was capable of reflecting the recognition of the examiner.     

模糊数学方法模拟水库运行影响下鱼类栖息地的变化

水库调度改变了河流水文情势,从而使得水生动植物栖息地的空间分布发生明显的变化。针对水库运行对鱼类栖息地的影响,利用模糊数学方法建立栖息地模型,并与水环境模型耦合,分析不同水文情势下鱼类在不同生长期的栖息地变化情况。基于专家分析法建立模糊函数隶属度及规则集,计算栖息地适宜性指数(HSI),提出适宜栖息地宽度指数(HSWI)表征河道内栖息地连通性,并对栖息地变化的有效性进行分析。选取漓江下游的某个复式河道为对象,模拟特征鱼种光倒刺鲃(Spinibarbus hollandi)在典型水文年份中水库不同调节模式下的栖息地变化情况。结果表明,在丰水年及枯水年的产卵期,水库补水明显增加了鱼类适宜栖息地面积,其中高适应性区域面积增幅近50%,而平水年影响较小;水库补水对越冬场的影响则相对微弱,仅增加5%左右。     

Inclusion of water temperature in a fuzzy logic Atlantic salmon (Salmo salar) parr habitat model

As water temperature is projected to increase in the next decades and its rise is clearly identified as a threat for cold water fish species, it is necessary to adapt and optimize the tools allowing to assess the quantity and quality of habitats with the inclusion of temperature. In this paper, a fuzzy logic habitat model was improved by adding water temperature as a key determinant of juvenile Atlantic salmon parr habitat quality. First, salmon experts were consulted to gather their knowledge of salmon parr habitat, then the model was validated with juvenile salmon electrofishing data collected on the Sainte-Marguerite, Matapedia and Petite-Cascapedia rivers (Québec, Canada). The model indicates that when thermal contrasts exist at a site, cooler temperature offered better quality of habitat. Our field data show that when offered the choice, salmon parr significantly preferred to avoid both cold areas (<15 °C) and warm areas (>20.5 °C). Because such thermal contrasts were not consistently present among the sites sampled, the model was only validated for less than 60% of the sites. The results nevertheless indicate a significant correlation between median Habitat Quality Index and parr density for the Sainte-Marguerite River (R² = 0.38). A less important, albeit significant (F-test; p = 0.036) relationship was observed for the Petite-Cascapedia river (R² = 0.14). In all instances, the four-variable (depth, velocity, substrate size and temperature) model provided a better explanation of parr density than a similar model excluding water temperature.     

An application of fuzzy logic to build ecological sympatry networks

In recent years sympatry networks have been proposed as a mean to perform biogeographic analysis, but their computation posed practical difficulties that limited their use. We propose a novel approach, bringing closer the application of well-established network analysis tools to the study of sympatry patterns using both geographic and environmental data associated with the occurrence of species. Our proposed algorithm, SGraFuLo, combines the use of fuzzy logic and numerical methods to directly compute the network of interest from point locality records, without the need of specialized tools, such as geographic information systems, thereby simplifying the process for end users. By posing the problem in matrix terms, SGraFuLo is able to achieve remarkable efficiency even for large datasets, taking advantage of well established scientific computing algorithms. We present sympatry networks constructed using real-world data collected in Mexico and Central America and highlight the potential of our approach in the analysis of overlapping niches of species that could have important applications even in evolutionary studies. We also present details on the design and implementation of the algorithm, as well as experiments that show its efficiency. The source code is freely released and datasets are also available to support the reproducibility of our results.     

Genetic algorithm based fuzzy logic control of a fed-batch fermentor

In the normal fuzzy logic control (FLC) system, both the membership functions and the rule sets are usually decided upon subjectively, case by case. The application of Genetic Algorithm(GA) could lead to proper selection of membership functions and rule base objectively. In this paper, the optimisation of membership functions of a FLC for a fed-batch fermentor is carried out with help of Genetic Algorithm (GA). Results are found to be satisfactory.     

Optimization of economic policies and investment projects using a fuzzy logic based cost-effectiveness model of coral reef quality: empirical results for Montego Bay, Jamaica

 For effective mitigation of human impacts, quantitative models are required that facilitate a comprehensive analysis of the effects of human activity on reefs. Fuzzy logic procedures generate a complex dose-response surface that models the relationships among coral abundance and various inputs (e.g., physical damage, sedimentation, nutrient influx), within the context of the abiotic marine environment. This is linked to a nonlinear economic structure incorporating technical interventions (e.g., pollution treatment) and policy interventions (e.g., taxation) in eight economic sectors. Optimization provides insights into the most cost-effective means for protecting coral reefs under different reef quality targets. The research demonstrates that: (1) it is feasible to use fuzzy logic to model complex interactions in coral reef ecosystems; and, (2) conventional economic procedures for modeling cost-effectiveness can result in sub-optimal policy choices when applied to complex systems such as coral reefs. In Montego Bay, Jamaica, up to a 20% increase in coral abundance may be achievable through using appropriate policy measures having a present value cost of US$153 million over 25 years; a 10% increase is achievable at a cost of US$12 million. Accepted: 20 June 1999     

Prediction of gastric ulcers based on the change in electrical resistance of acupuncture points using fuzzy logic decision-making

Many theories of reflexology use ancient concepts which do not coincide with the modern medical terminology of anatomy, physiology and biophysics. This substantially reduces the trust of physicians in reflexology methods. During this research, several mathematical models for the interaction of the internal and biological active points of meridian structures have been proposed. The analysis of these models allows the specification of a list of gastric diseases for which reflex diagnostics and reflex therapy methods are most effective and also allows increasing the effectiveness of these procedures. It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained using fuzzy logic decision making.     

An intelligent control method based on fuzzy logic for a robotic testing system for the human spine

In previous biomechanical studies of the human spine, we implemented a hybrid controller to investigate load-displacement characteristics. We found that measurement errors in both position and force caused the controller to be less accurate than predicted. As an alternative to hybrid control, a fuzzy logic controller (FLC) has been developed and implemented in a robotic testing system for the human spine. An FLC is a real-time expert system that can emulate part of a human operator's knowledge by using a set of action rules. The FLC provides simple but robust solutions that cover a wide range of system parameters and can cope with significant disturbances. It can be viewed as a heuristic and modular way of defining a nonlinear, table-based control system. In this study, an FLC is developed which uses the force difference and the change in force difference as the input parameters, and the displacement as the output parameter. A rule-table based on these parameters is designed for the controller Experiments on a physical model composed of springs demonstrate the improved performance of the proposed method.