Optoelectronic Reservoir Computing

Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a single output layer. Within these constraints many implementations are possible. Here we report an opto-electronic implementation of reservoir computing based on a recently proposed architecture consisting of a single non linear node and a delay line. Our implementation is sufficiently fast for real time information processing. We illustrate its performance on tasks of practical importance such as nonlinear channel equalization and speech recognition, and obtain results comparable to state of the art digital implementations.Comment: Contains main paper and two Supplementary Material

Half-Metallic Ferromagnetism in the Heusler Compound Co2_2FeSi revealed by Resistivity, Magnetoresistance, and Anomalous Hall Effect measurements

We present electrical transport data for single-crystalline Co$_2$FeSi which provide clear-cut evidence that this Heusler compound is truly a half-metallic ferromagnet, i.e. it possesses perfect spin-polarization. More specifically, the temperature dependence of $\rho$ is governed by electron scattering off magnons which are thermally excited over a sizeable gap $\Delta\approx 100 K$ ($\sim 9 meV$) separating the electronic majority states at the Fermi level from the unoccupied minority states. As a consequence, electron-magnon scattering is only relevant at $T\gtrsim\Delta$ but freezes out at lower temperatures, i.e., the spin-polarization of the electrons at the Fermi level remains practically perfect for $T\lesssim\Delta$. The gapped magnon population has a decisive influence on the magnetoresistance and the anomalous Hall effect (AHE): i) The magnetoresistance changes its sign at $T\sim 100 K$, ii) the anomalous Hall coefficient is strongly temperature dependent at $T\gtrsim 100 K$ and compatible with Berry phase related and/or side-jump electronic deflection, whereas it is practically temperature-independent at lower temperatures

سيمياء الذات في شعر سعاد الكواري

مرت السيميائية بوصفها منهجًا لقراءة مختلف أنواع الخطاب بمرحلتين: مرحلة الحداثة (العمل)، ومرحلة ما بعد الحداثة (المشاريع)، وكثرت الدراسات التطبيقية لسيمياء العمل، ولم تكن كذلك لمرحلة المشاريع إلّا في جانب دراسة الأهواء، أما سيمياء الذات وسيمياء التوتّر فقلّما نجد لهما مقاربات تطبيقية. ولمشروع سيمياء الذات - كما جاء على يد جان كلود كوكي Jean Claude Coquet – برامجه وإجراءاته التي تدرس الذات المتلفظة، والذات الإدراكية، والذات الحاضرة، والذات الغائبة، وشبه الذات، من خلال تبيان كفاءتها واستقراء جهاتها (القدرة، المعرفة، الإرادة، الرغبة، الواجب)، واستجلاء القوانين السيميائية التي تتحكم بها في سياقَي اتّصالها وانفصالها عن موضوعها. ويسعى هذا البحث إلى مقاربة الذات في شعر سعاد الكواري مقاربة سيميائية؛ إذ إنّها تشكّل بؤرة مركزية تشعّ منها إبداعاتها الشعريّة وتدور في فلكها، الأمر الذي جعلها موضع عناية هذه الدراسة التطبيقية التي تعتمد المنهج السيميائي في معطياته ما بعد الحداثية

The Effectiveness of Using E-learning and Distance Learning Applications in Jordanian Universities in the light of the Coronavirus Pandemic from the Students Point of View

This study aims to determine the effectiveness of the use of e-learning and distance learning (DL) tools in Jordanian universities according to the students perception of the coronavirus. The study followed a descriptive research method using descriptive questionnaires. A sample of (372) male and female undergraduate and graduate students from different Jordanian universities. The results showed that (73.7%) of the respondents used online distance learning every day during the coronavirus pandemic. Most of the students believe that the coronavirus epidemic has changed the use of online education more and more and the use of electronic devices to increase communication with others (teachers, colleagues). There is no significant difference in the level (α≥ 0.05) of the effectiveness of using E-Learning and Distance Learning applications according to gender and residence. Although a significant difference occurred between the variable age and the degree of university. The results of the study can be used to advise the teacher to focus more on activities that show a high level of enjoyment, especially website optimization and instruction. Colleges are now seen as important places of learning in the classroom. Websites and tutorials must be updated regularly

Are ‘cultures of worklessness' passed down the generations?

This report critically investigates the idea of ‘intergenerational cultures of worklessness ’ and that there may be families where ‘three generations have never worked’. Although there is relatively little solid research evidence to support them, these ideas are said to help explain worklessness in the UK and continue to inform recent and current government policy agendas. Our study used qualitative research methods, with families in Middlesbrough and Glasgow. The report: • explores the existence of permanent worklessness across generations within families; • concludes that even two generations of extensive or permanent worklessness in the same family is a rare phenomenon; • examines whether families experiencing long-term worklessness can be described as having a ‘culture of worklessness’; • shows how the impact of complex and multiple problems, rooted in long-term experiences of deep poverty, can distance people from the labour market; and • argues that policy makers should abandon theories – and policies that flow from them – that see worklessness as primarily the outcome of a ‘culture of worklessness’, held in families and passed down the generations

Reservoir Topology in Deep Echo State Networks

Deep Echo State Networks (DeepESNs) recently extended the applicability of Reservoir Computing (RC) methods towards the field of deep learning. In this paper we study the impact of constrained reservoir topologies in the architectural design of deep reservoirs, through numerical experiments on several RC benchmarks. The major outcome of our investigation is to show the remarkable effect, in terms of predictive performance gain, achieved by the synergy between a deep reservoir construction and a structured organization of the recurrent units in each layer. Our results also indicate that a particularly advantageous architectural setting is obtained in correspondence of DeepESNs where reservoir units are structured according to a permutation recurrent matrix.Comment: Preprint of the paper published in the proceedings of ICANN 201

Reservoir Computing Approach to Robust Computation using Unreliable Nanoscale Networks

As we approach the physical limits of CMOS technology, advances in materials science and nanotechnology are making available a variety of unconventional computing substrates that can potentially replace top-down-designed silicon-based computing devices. Inherent stochasticity in the fabrication process and nanometer scale of these substrates inevitably lead to design variations, defects, faults, and noise in the resulting devices. A key challenge is how to harness such devices to perform robust computation. We propose reservoir computing as a solution. In reservoir computing, computation takes place by translating the dynamics of an excited medium, called a reservoir, into a desired output. This approach eliminates the need for external control and redundancy, and the programming is done using a closed-form regression problem on the output, which also allows concurrent programming using a single device. Using a theoretical model, we show that both regular and irregular reservoirs are intrinsically robust to structural noise as they perform computation