Space–Time Power Schedule for Distributed MIMO Links Without Instantaneous Channel State Information at the Transmitting Nodes

A space-time optimal power schedule for multiple distributed multiple-input multiple-output (MIMO) links without the knowledge of the instantaneous channel state information (CSI) at the transmitting nodes is proposed. A readily computable expression for the ergodic sum capacity of the MIMO links is derived. Based on this expression, which is a non-convex function of power allocation vectors, a projected gradient algorithm is developed to optimize the power allocation. For a symmetric set of MIMO links with independent identically distributed channels, it is observed that the space-time optimal power schedule reduces to a uniform isotropic power schedule when nominal interference is low, or to an orthogonal isotropic power schedule when nominal interference is high. Furthermore, the transition region between the latter two schedules is seen to be very sharp in terms of nominal interference-to-noise ratio (INR). For MIMO links with correlated channels, the corresponding space-time optimal power schedule is developed based on the knowledge of the channel correlation matrices. It is shown that the channel correlation has a great impact on the ergodic capacity and the optimality of different power scheduling approaches.     

10GbE成为主流

数年来，具有10Gbps速度的下一代以太网一直处于即将成为主流的状况。一段时间以来，网络的某些区域已在使用光学技术，并且随着流量的增加，对10GbE数据速率的需求正在增长。但是，需要一种比上一代以太网复杂许多的技术，用于在100m长的铜缆上运行10GbE。这一要求导致了昂贵的MAC（媒体访问控制器）和交换芯片，以及昂贵而又不方便的PHY层接口芯片，由此限制了快速LAN用于那些覆盖数据中心内较短距离的高性能应用。     

Some Thoughts on the Evolution of Work Teams in Organizations

In this time of flat, team-based and technology-enabled organizations the effectiveness of communication and team leadership practices will be more important than ever before. Therefore, we believe that some of the earlier, time-tested classic works on group dynamics and leadership are worthy of re-reading. We are particularly impressed by how relevant one of the oldest classics, Benne and Sheats' (1948) article on functional roles of group members, remains to this day.     

Carbon nanofibers as hydrogen adsorbing materials for power sources

Porous carbon nanofibers are synthesized by CVD method from acetylene with use of iron-containing catalysts. Activation of the nanofibers in melted potassium hydroxide results in increasing surface area from initial 300–400 m² g⁻¹ to 1700 m² g⁻¹. As follows from XRD data, activated nanofibers do not contain regular packages of graphene layers, but retain high electric conductivity. Deposition of copper improves electrochemical hydrogen storing characteristics of carbon nanofibers. Carbon nanomaterials obtained can be used as hydrogen storing materials in batteries instead of hydride forming metals.     

Xylene Isomerization in a ZSM-5/SS Membrane Reactor

A membrane reactor containing different types of ZSM-5/porous SS membranes was used to perform the xylene isomerization reaction. The parent Na-ZSM-5 layer was synthesized by secondary growth on top of porous stainless steel tubes. The xylene isomerization reaction was carried out at different temperatures in the membrane reactor and in a fixed-bed reactor of identical geometry for comparison. Two different kinds of membranes were prepared by ion exchange: a Pt/H-ZSM-5 catalytic membrane and two Ba-ZSM-5 composites with different Ba²⁺ concentration. The p-xylene production using 100% exchanged Ba-membrane was about 28% higher than the fixed-bed reactor at 370 °C, when m-xylene was fed.     

Ultrasonic treatment restores the photoelectric parameters of silicon solar cells degraded under the action of <Superscript>60</Superscript>Co gamma radiation

The photoelectric parameters of silicon solar cells degraded under the action of ⁶⁰Co gamma-radiation can be partly restored using an ultrasonic treatment (UST). The growth of the maximum output power of solar cells after the UST is related to a redistribution of the radiation defects and an increase in the homogeneity of a semiconductor crystal structure.     

Phase states of a two-dimensional non-Heisenberg ferromagnet

The effects of a biquadratic exchange and an external magnetic field on the phase states of a twodimensional non-Heisenberg ferromagnet have been studied with allowance for magnetoelastic and magnetodipolar interactions.     

Lattice structure on some fuzzy algebraic systems

In this paper, we study the lattice structure of some fuzzy algebraic systems such as (G-)fuzzy groups, some fuzzy ordered algebras and fuzzy hyperstructures. We prove that under suitable conditions, these structures form a distributive or modular lattice. This research partially is supported by the “ Fuzzy Systems and its Applications Center of Excelence, Shahid Bahonar University of Kerman, Iran”.     

Toward Human Level Machine Intelligence - Is It Achievable? The Need for a Paradigm Shift

Officially, AI was born in 1956. Since then, very impressive progress has been made in many areas - but not in the realm of human level machine intelligence. During much of its early history, AI "was rife "with exaggerated expectations. A headline in an article published in the late forties of last century was headlined, "Electric brain capable of translating foreign languages is being built". Today, more than half a century later, we do have translation software, but nothing that can approach the quality of human translation. Clearly, achievement of human level machine intelligence is a challenge that is hard to meet. A prerequisite to achievement of human level machine intelligence is mechanization of these capabilities and, in particular, mechanization of natural language understanding. To make significant progress toward achievement of human level machine intelligence, a paradigm shift is needed. More specifically, what is needed is an addition to the armamentarium of AI of two methodologies: (a) a nontraditional methodology of computing with words (CW) or more generally, NL-Computation; and (b) a countertraditional methodology "which involves a progression from computing with numbers to computing with words. The centerpiece of these methodologies is the concept of precisiation of meaning. Addition of these methodologies to AI would be an important step toward the achievement of human level machine intelligence and its applications in decision-making, pattern recognition, analysis of evidence, diagnosis, and assessment of causality. Such applications have a position of centrality in our infocentric society.