Improved shear design rules of cold-formed steel beams

Light gauge cold-formed steel sections have been developed as more economical building solutions to the alternative heavier hot-rolled sections in the commercial and residential markets. Cold-formed lipped channel beams (LCB), LiteSteel beams (LSB) and triangular hollow flange beams (THFB) are commonly used as flexural members such as floor joists and bearers while rectangular hollow flange beams (RHFB) are used in small scale housing developments through to large building structures. However, their shear capacities are determined based on conservative design rules. For the shear design of cold-formed steel beams, their elastic shear buckling strength and the potential post-buckling strength must be determined accurately. Hence experimental and numerical studies were conducted to investigate the shear behaviour and strength of LCBs, LSBs, THFBs and RHFBs. Improved shear design rules including the direct strength method (DSM) based design equations were developed to determine the ultimate shear capacities of these open and hollow flange steel beams. An improved equation for the higher elastic shear buckling coefficient of cold-formed steel beams was proposed based on finite element analysis results and included in the design equations. A new post-buckling coefficient was also introduced in the design equations to include the available post-buckling strength of cold-formed steel beams. This paper presents the details of this study on cold-formed steel beams subject to shear, and the results. It proposes generalised and improved shear design rules that can be used for any type of cold-formed steel beam.

Who Rules Japan? Popular Participation in the Japanese Legal Process

"The dramatic growth of the Japanese economy in the postwar period, and its meltdown in the 1990s, has attracted sustained interest in the power dynamics underlying the management of Japan’s administrative state. Scholars and commentators have long debated over who wields power in Japan, asking the fundamental question: who really governs Japan? This important volume revisits this question by turning its attention to the regulation and design of the Japanese legal system. With essays covering the new lay-judge system in Japanese criminal trials, labour dispute resolution panels, prison policy, gendered justice, government lawyers, welfare administration and administrative transparency, this comprehensive book explores the players and processes in Japan’s administration of justice."--publisher website

Introduction: Who rules Japan?

This chapter reviews the debate about who governs Japan and considers the implications of legal system reforms initiated by the Justice System Reform Council report of 2001.

Towards simple rules heuristics for IT business value

The business value of IT (BVIT) has been a prominent and central research topic in the IS discipline. Due to continuous and unpredictable technology and business changes, a more dynamic perspective on IT business value that includes organizational learning is required. We suggest that simple rules heuristics can address this challenge. The simple rules heuristics approach has been introduced by Eisenhardt and co-authors (Bingham & Eisenhardt, 2011; Bingham, Eisenhardt, & Furr, 2007; Eisenhardt & Sull, 2001) to better understand strategic decision making for capturing superabundant, heterogeneous, fastmoving opportunities. They argue that explicit organizational learning can translate accumulated experience into increasingly effective heuristics for strategic processes in highvelocity environments. We make three main contributions by exploring the suitability of a simple rules heuristics approach for the creation of IT business value: (1) we propose six types of simple rules heuristics for capturing IT-based opportunities in dynamic environments, including synergy heuristics as specifically relevant in an IT context, (2) we show how a simple rules heuristics approach can advance our understanding of dynamics and organizational learning for BVIT, and; (3) we introduce the strategic logic of opportunity to BVIT.

“I understand. I am a participant”: Navigating the ‘fuzzy’ boundaries of visual methods in qualitative longitudinal research

In this chapter we discuss how utilising the participatory visual methodology, photovoice, in an aged care context with its unique communal setting raised several ‘fuzzy boundary’ ethical dilemmas. To illustrate these challenges, we draw on immersive field notes from an ongoing qualitative longitudinal research (QLR) exploring the lived experience of aged care from the perspective of older residents, and focus on interactions with one participant, 81 year old Cassie. We explore how the camera, which is integral to the photovoice method, altered the researcher/participant ethical dynamics by becoming a continual ‘connector’ to the researcher. The camera took on a distinct agency, acting as a non-threatening ‘portal’ that lengthened contact, provided informal opportunities to alter the relationship dynamics and enabled unplanned participant revelation.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

Fuzzy Logic-Based Approaches in Water Resource System Modelling

Recent research in modelling uncertainty in water resource systems has highlighted the use of fuzzy logic-based approaches. A number of research contributions exist in the literature that deal with uncertainty in water resource systems including fuzziness, subjectivity, imprecision and lack of adequate data. This chapter presents a broad overview of the fuzzy logic-based approaches adopted in addressing uncertainty in water resource systems modelling. Applications of fuzzy rule-based systems and fuzzy optimisation are then discussed. Perspectives on the scope for further research are presented.

Sharing social space with strangers: Setting, signalling and policing informal rules of driving etiquette

Recent research suggests that aggressive driving may be influenced by driver perceptions of their interactions with other drivers in terms of ‘right’ or ‘wrong’ behaviour. Drivers appear to take a moral standpoint on ‘right’ or ‘wrong’ driving behaviour. However, ‘right’ or ‘wrong’ in the context of road use is not defined solely by legislation, but includes informal rules that are sometimes termed ‘driving etiquette’. Driving etiquette has implications for road safety and public safety since breaches of both formal and informal rules may result in moral judgement of others and subsequent behaviours designed to punish the ‘offender’ or ‘teach them a lesson’. This paper outlines qualitative research that was undertaken with drivers to explore their understanding of driving etiquette and how they reacted to other drivers’ observance or violation of their understanding. The aim was to develop an explanatory framework within which the relationships between driving etiquette and aggressive driving could be understood, specifically moral judgement of other drivers and punishment of their transgression of driving etiquette. Thematic analysis of focus groups (n=10) generated three main themes: (1) courtesy and reciprocity, and the notion of two-way responsibility, with examples of how expectations of courteous behaviour vary according to the traffic interaction; (2) acknowledgement and shared social experience: ‘giving the wave’; and (3) responses to breaches of the expectations/informal rules. The themes are discussed in terms of their roles in an explanatory framework of the informal rules of etiquette and how interactions between drivers can reinforce or weaken a driver’s understanding of driver etiquette and potentially lead to driving aggression.

A fuzzy multistage evolutionary (FUME) clustering technique

n this paper, a multistage evolutionary scheme is proposed for clustering in a large data base, like speech data. This is achieved by clustering a small subset of the entire sample set in each stage and treating the cluster centroids so obtained as samples, together with another subset of samples not considered previously, as input data to the next stage. This is continued till the whole sample set is exhausted. The clustering is accomplished by constructing a fuzzy similarity matrix and using the fuzzy techniques proposed here. The technique is illustrated by an efficient scheme for voiced-unvoiced-silence classification of speech.

A Fuzzy Approximation Scheme for Sequential Learning in Pattern Recognition

An adaptive learning scheme, based on a fuzzy approximation to the gradient descent method for training a pattern classifier using unlabeled samples, is described. The objective function defined for the fuzzy ISODATA clustering procedure is used as the loss function for computing the gradient. Learning is based on simultaneous fuzzy decisionmaking and estimation. It uses conditional fuzzy measures on unlabeled samples. An exponential membership function is assumed for each class, and the parameters constituting these membership functions are estimated, using the gradient, in a recursive fashion. The induced possibility of occurrence of each class is useful for estimation and is computed using 1) the membership of the new sample in that class and 2) the previously computed average possibility of occurrence of the same class. An inductive entropy measure is defined in terms of induced possibility distribution to measure the extent of learning. The method is illustrated with relevant examples.

Determination of the magnetic moment by QCD sum rules

The magnetic moment of the Λ hyperon is calculated using the QCD sum-rule approach of Ioffe and Smilga. It is shown that μΛ has the structure μΛ=(2/3(eu+ed+4es)(eħ/2MΛc)(1+δΛ), where δΛ is small. In deriving the sum rules special attention is paid to the strange-quark mass-dependent terms and to several additional terms not considered in earlier works. These terms are now appropriately incorporated. The sum rule is analyzed using the ratio method. Using the external-field-induced susceptibilities determined earlier, we find that the calculated value of μΛ is in agreement with experiment.

Gluon-field contribution in QCD sum rules for the magnetic moments of the nucleons

The Wilson coefficient corresponding to the gluon-field strength GμνGμν is evaluated for the nucleon current correlation function in the presence of a static external electromagnetic field, using a regulator mass Λ to separate the high-momentum part of the Feynman diagrams. The magnetic-moment sum rules are analyzed by two different methods and the sensitivity of the results to variations in Λ are discussed.

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

A fuzzy dynamic flood routing model for natural channels

A fuzzy dynamic flood routing model (FDFRM) for natural channels is presented, wherein the flood wave can be approximated to a monoclinal wave. This study is based on modification of an earlier published work by the same authors, where the nature of the wave was of gravity type. Momentum equation of the dynamic wave model is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. Hence, the FDFRM gets rid of the assumptions associated with the momentum equation. Also, it overcomes the necessity of calculating friction slope (S-f) in flood routing and hence the associated uncertainties are eliminated. The fuzzy rule based model is developed on an equation for wave velocity, which is obtained in terms of discontinuities in the gradient of flow parameters. The channel reach is divided into a number of approximately uniform sub-reaches. Training set required for development of the fuzzy rule based model for each sub-reach is obtained from discharge-area relationship at its mean section. For highly heterogeneous sub-reaches, optimized fuzzy rule based models are obtained by means of a neuro-fuzzy algorithm. For demonstration, the FDFRM is applied to flood routing problems in a fictitious channel with single uniform reach, in a fictitious channel with two uniform sub-reaches and also in a natural channel with a number of approximately uniform sub-reaches. It is observed that in cases of the fictitious channels, the FDFRM outputs match well with those of an implicit numerical model (INM), which solves the dynamic wave equations using an implicit numerical scheme. For the natural channel, the FDFRM Outputs are comparable to those of the HEC-RAS model.

Structural Damage Detection Using Modal Curvature and Fuzzy Logic

A fuzzy logic system (FLS) with a new sliding window defuzzifier is proposed for structural damage detection using modal curvatures. Changes in the modal curvatures due to damage are fuzzified using Gaussian fuzzy sets and mapped to damage location and size using the FLS. The first four modal vectors obtained from finite element simulations of a cantilever beam are used for identifying the location and size of damage. Parametric studies show that modal curvatures can be used to accurately locate the damage; however, quantifying the size of damage is difficult. Tests with noisy simulated data show that the method detects damage very accurately at different noise levels and when some modal data are missing.