Critical discourse analysis, description, explanation, causes: Foucault's inspiration versus Weber's perspiration

The FOUCAULTian governmentality approach, in relying on a teleology - the ultimate purpose of human endeavour is the quest for ever-growing human reason, a reason that is the universal basis of moral judgements, especially moral judgements about political and legal actions - leads not to description, explanation and the possible identification of causes, but to critique, to the inappropriate conflation of, on the one hand, description, explanation and the identification of causes with, on the other, political criticisms sourced in the teleology. Drawing on some of WEBER's methodological insights, an argument is developed that critical discourse analysis, in taking on the FOUCAULTian approach, gives up the best traditions of description, explanation and the identification of causes in favour of the expression, in many different forms, of the teleology

Human Capital and Growth: What Can we Learn from Micro-data? Evidence from Taiwan (1976-95)

This paper uses micro-data to define aggregate human capital stock indicators and proposes various specifications to test for the role of human capital accumulation on economic growth. An empirical evaluation on the Taiwanese experience over the 1975-96 period suggests that: (i) the use of alternative human capital measures does not allow for the identification of significant differences with usual indicators when estimating the direct contribution of human capital accumulation to economic growth, (ii) specifying indirect channels through which human capital accumulation may affect economic growth allows for a clear identification of external effects arising through intersectoral interactions.Taiwan., externality, experience, human capital, economic growth

A human computer interactions framework for biometric user identification

Computer assisted functionalities and services have saturated our world becoming such an integral part of our daily activities that we hardly notice them. In this study we are focusing on enhancements in Human-Computer Interaction (HCI) that can be achieved by natural user recognition embedded in the employed interaction models. Natural identification among humans is mostly based on biometric characteristics representing what-we-are (face, body outlook, voice, etc.) and how-we-behave (gait, gestures, posture, etc.) Following this observation, we investigate different approaches and methods for adapting existing biometric identification methods and technologies to the needs of evolving natural human computer interfaces

Experimentally based numerical models and numerical simulation with parameter identification of human lumbar FSUs in traction

Numerical simulation of the behaviour of human lumbar spine segments, moreover, parameter-identification of the component organs of human lumbar FSUs are presented in traction therapies, by using FEM analysis. First, a simple 2D model, than a refined 2D model, and finally a refined 3D model were applied for modeling lumbar FSUs. For global numerical simulation of traction therapies the material constants of component organs have been obtained from the international literature. For local parameter identification of the component organs, an interval of the possible material moduli has been considered for each organ, and the possible combinations of real moduli were obtained, controlling the process by the measured global deformations. In this way, the efficiency of conservative traction therapies can be improved by offering new experimental tensile material parameters for the international spine research

Postmortem iris recognition and its application in human identification

Iris recognition is a validated and non-invasive human identification technology currently implemented for the purposes of surveillance and security (i.e. border control, schools, military). Similar to deoxyribonucleic acid (DNA), irises are a highly individualizing component of the human body. Based on a lack of genetic penetrance, irises are unique between an individual’s left and right iris and between identical twins, proving to be more individualizing than DNA. At this time, little to no research has been conducted on the use of postmortem iris scanning as a biometric measurement of identification. The purpose of this pilot study is to explore the use of iris recognition as a tool for postmortem identification. Objectives of the study include determining whether current iris recognition technology can locate and detect iris codes in postmortem globes, and if iris scans collected at different postmortem time intervals can be identified as the same iris initially enrolled. Data from 43 decedents involving 148 subsequent iris scans demonstrated a subsequent match rate of approximately 80%, supporting the theory that iris recognition technology is capable of detecting and identifying an individual’s iris code in a postmortem setting. A chi-square test of independence showed no significant difference between match outcomes and the globe scanned (left vs. right), and gender had no bearing on the match outcome. There was a significant relationship between iris color and match outcome, with blue/gray eyes yielding a lower match rate (59%) compared to brown (82%) or green/hazel eyes (88%), however, the sample size of blue/gray eyes in this study was not large enough to draw a meaningful conclusion. An isolated case involving an antemortem initial scan collected from an individual on life support yielded an accurate identification (match) with a subsequent scan captured at approximately 10 hours postmortem. Falsely rejected subsequent iris scans or "no match" results occurred in about 20% of scans; they were observed at each PMI range and varied from 19-30%. The false reject rate is too high to reliably establish non-identity when used alone and ideally would be significantly lower prior to implementation in a forensic setting; however, a "no match" could be confirmed using another method. Importantly, the data showed a false match rate or false accept rate (FAR) of zero, a result consistent with previous iris recognition studies in living individuals. The preliminary results of this pilot study demonstrate a plausible role for iris recognition in postmortem human identification. Implementation of a universal iris recognition database would benefit the medicolegal death investigation and forensic pathology communities, and has potential applications to other situations such as missing persons and human trafficking cases

Human operator identification model and related computer programs

Four computer programs which provide computational assistance in the analysis of man/machine systems are reported. The programs are: (1) Modified Transfer Function Program (TF); (2) Time Varying Response Program (TVSR); (3) Optimal Simulation Program (TVOPT); and (4) Linear Identification Program (SCIDNT). The TV program converts the time domain state variable system representative to frequency domain transfer function system representation. The TVSR program computes time histories of the input/output responses of the human operator model. The TVOPT program is an optimal simulation program and is similar to TVSR in that it produces time histories of system states associated with an operator in the loop system. The differences between the two programs are presented. The SCIDNT program is an open loop identification code which operates on the simulated data from TVOPT (or TVSR) or real operator data from motion simulators