The exegesis of Tabatabaei and the Hermeneutics of Hirsch: a comparative study

This thesis is a comparative study between Hermeneutics on the one hand and exegesis of the Holy Qur'an on the other. Its objective is to discover whether there are salient points of convergence between the two disciples, and whether issues germane to the Hermeneutical tradition in the West have been referred to and/or employed in Muslim works of Qur'an commentary. To this end, the works of one of the most prominent Shi'ite philosophers and exegetes. Allama Mohammad Hossein Tabataei, have been analysed and compared with the perspective and methodology of E D. Hirsch, one of the most important hermeneuticians in the Western World. Hirsch has been chosen since, in the opinion of the author, there is a considerable number of commonalities between the Hirschian approach to hermeneutics and the exegetical methodology of Tabatabaei and other Shi'ite Muslim interpreters of the Qur'an.. Hirsch, as an objectivist, along with a number of other Hermeneutical scholars, are critical of those who subscribe to philosophical Hermeneutics, such as Heideger and Gadimer. The same approach is taken in Tabatabaei's works, thus providing a strong rationale for an academic comparison of these two scholars. For this reason, this thesis attempts to study the theories of Tabatabaei and Hirsch in order to highlight the similarities and differences in their works. The central hypothesis is that while small differences in approach exist, there is much common ground, and that it is possible to use certain facets of Hirschian hermeneutics in the interpretation of the Qur'an, thus modernising some of the existing exegetical approaches employed by Shi'ite scholars.Since the aim of this thesis is to compare the interpretive works of Tabatabaei with those of Hirsch's, an introductory chapter has been dedicated to the study of the evolution of Shi'ite exegesis from the beginning to date. Tabatabaei's Al-Mizan has been chosen as the foremost work of Shi'ite exegesis in the modem period. Furthermore, a complete chapter has also been dedicated to Tabatabai's exegetical modus operandi as reflected in Al-Mizan, in order to arrive at a better understanding of his perspectives. This research arrives at the conclusion that philosophical Hermeneutics and Epistemology have opened new horizons on which we will always be dependent. Whatever interpretive theories with regards to the understanding of the text are accepted, or whatever the tendency as far as literary criticism is concerned, or whatever ideas are accepted in the arena of philosophy of human and social sciences, the discussion of the nature of understanding in general cannot be avoided. This does not mean that Hermeneutics is limited to these new theories. Rather, the opportunity always exists to introduce new interpretive theories in connection with the understanding of the text. It is indeed possible to study these discussions in detail in a separate sphere independent of the other branches of Islamic sciences and arrive at a number of stable principles in the interpretation of the text in Islamic research

Stationary and uniform entanglement distribution in qubit networks with quasi-local dissipation

We consider qubit networks where adjacent qubits besides interacting via XY-coupling, also dissipate into the same environment. The steady states are computed exactly for all network sizes and topologies, showing that they are always symmetric under permutation of network sites, leading to a uniform distribution of the stationary entanglement across the network. The maximum entanglement between two arbitrary qubits is shown to depend only on the total number of qubits in the network, and scales linearly with it. A possible physical realization by means of an array of doped cavities is discussed for the case of a linear chain.Comment: 6 pages, comments welcome. v2: published version with typos corrected and updated bibliograph

Impact of Harmonics on Power Quality and Losses in Power Distribution Systems

This paper investigates the harmonic distortion and losses in power distribution systems due to the dramatic increase of nonlinear loads. This paper tries to determine the amount of the harmonics generated by nonlinear loads in residential, commercial and office loads in distribution feeders and estimates the energy losses due to these harmonics. Norton equivalent modeling technique has been used to model the nonlinear loads. The presented harmonic Norton equivalent models of the end user appliances are accurately obtained based on the experimental data taken from the laboratory measurements. A 20 kV/400V distribution feeder is simulated to analyze the impact of nonlinear loads on feeder harmonic distortion level and losses. The model follows a “bottom-up” approach, starting from end users appliances Norton equivalent model and then modeling residential, commercial and office loads. Two new indices are introduced by the authors to quantize the effect of each nonlinear appliance on the power quality of a distribution feeder and loads are ranked based on these new defined indices. The simulation results show that harmonic distortion in distribution systems can increase power losses up to 20%

Robust and Communication-Efficient Collaborative Learning

We consider a decentralized learning problem, where a set of computing nodes aim at solving a non-convex optimization problem collaboratively. It is well-known that decentralized optimization schemes face two major system bottlenecks: stragglers' delay and communication overhead. In this paper, we tackle these bottlenecks by proposing a novel decentralized and gradient-based optimization algorithm named as QuanTimed-DSGD. Our algorithm stands on two main ideas: (i) we impose a deadline on the local gradient computations of each node at each iteration of the algorithm, and (ii) the nodes exchange quantized versions of their local models. The first idea robustifies to straggling nodes and the second alleviates communication efficiency. The key technical contribution of our work is to prove that with non-vanishing noises for quantization and stochastic gradients, the proposed method exactly converges to the global optimal for convex loss functions, and finds a first-order stationary point in non-convex scenarios. Our numerical evaluations of the QuanTimed-DSGD on training benchmark datasets, MNIST and CIFAR-10, demonstrate speedups of up to 3x in run-time, compared to state-of-the-art decentralized optimization methods

Drought assessment modelling using biophysical parameters and remote sensing data

This study considers the advancement in technical development of a few disciplines as an infrastructure for developing a suitable model and methodology for agricultural drought assessment in semi-arid area. It evaluates capabilities of multisource remote sensing data in developing raster-based biophysical drought assessment models. The capability for expressing the spatial and inter-annual variation of evapotranspiration (ET) over a study area by the proposed models has made it efficient. The base model, Mapping EvapoTranspiration at high Resolution with Internal Calibration (METRIC) has been evaluated for its performance in estimating ET over the pistachio plantation in a semi-arid region. The result proved that the base model gives good accuracy and is suitable for the selected study area. The base model, METRIC, is found sensitive to a number of meteorological parameters. Two-factor analysis for the primary inputs of the base model shows that the surface albedo and surface temperature pairs is the most effective while other tested pairs are found to be least effective. The study suggests that improving the equations of the effective pair should increase the accuracy. In this case, the multilayer perceptron Artificial Neural Network (ANN) technique is used for estimating spatial and temporal distribution of actual ET from satellite based biophysical parameters. The result shows that a strong correlation exist between ET values computed using METRIC and those generated using ANN. ANN sensitivity analysis shows that surface temperature, soil heat flux and surface albedo are the most significant parameters. Exploratory factor analysis using Principal Component Analysis (PCA) was performed to select the most significant biophysical parameters to be used as input to a newly developed BioPhysical Water Stress Index (BPWSI). The BPWSI is a new model for estimating water stress index using the selected biophysical parameters. The results of BPWSI are found to be significant and can be used for predicting the pistachio water status which represents the indication of agricultural drought