Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization.

The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product. While there have been many demonstrations of dot-product circuits and, separately, of stochastic neurons, the efficient hardware implementation combining both functionalities is still missing. Here we report compact, fast, energy-efficient, and scalable stochastic dot-product circuits based on either passively integrated metal-oxide memristors or embedded floating-gate memories. The circuit's high performance is due to mixed-signal implementation, while the efficient stochastic operation is achieved by utilizing circuit's noise, intrinsic and/or extrinsic to the memory cell array. The dynamic scaling of weights, enabled by analog memory devices, allows for efficient realization of different annealing approaches to improve functionality. The proposed approach is experimentally verified for two representative applications, namely by implementing neural network for solving a four-node graph-partitioning problem, and a Boltzmann machine with 10-input and 8-hidden neurons

Data protection: the challenges facing social networking

The popularity of social networking sites has increased dramatically over the past decade. A recent report indicated that thirty-eight percent of online users have a social networking profile. Many of these social networking site users (SNS users) post or provide personal information over the internet every day. According to the latest OfCom study, the average adult SNS user has profiles on 1.6 sites and most check their profiles at least once every other day. However, the recent rise in social networking activity has opened the door to the misuse and abuse of personal information through identity theft, cyber stalking, and undesirable screenings by prospective employers. Behavioral advertising programs have also misused personal information available on social networking sites. Society is now facing an important question: what level of privacy should be expected and required within the social networking environment

Electron Dynamics in the Diffusion Region of an Asymmetric Magnetic Reconnection

During a magnetopause crossing near the subsolar point Cluster observes the ion diffusion region of antiparallel magnetic reconnection. The reconnecting plasmas are asymmetric, differing in magnetic field strength, density, and temperature. Spatial changes in the electron distributions in the diffusion region are resolved and investigated in detail. Heating of magnetosheath electrons parallel to the magnetic field is observed. This heating is shown to be consistent with trapping of magnetosheath electrons by parallel electric fields

DDSL: Efficient Subgraph Listing on Distributed and Dynamic Graphs

Subgraph listing is a fundamental problem in graph theory and has wide applications in areas like sociology, chemistry, and social networks. Modern graphs can usually be large-scale as well as highly dynamic, which challenges the efficiency of existing subgraph listing algorithms. Recent works have shown the benefits of partitioning and processing big graphs in a distributed system, however, there is only few work targets subgraph listing on dynamic graphs in a distributed environment. In this paper, we propose an efficient approach, called Distributed and Dynamic Subgraph Listing (DDSL), which can incrementally update the results instead of running from scratch. DDSL follows a general distributed join framework. In this framework, we use a Neighbor-Preserved storage for data graphs, which takes bounded extra space and supports dynamic updating. After that, we propose a comprehensive cost model to estimate the I/O cost of listing subgraphs. Then based on this cost model, we develop an algorithm to find the optimal join tree for a given pattern. To handle dynamic graphs, we propose an efficient left-deep join algorithm to incrementally update the join results. Extensive experiments are conducted on real-world datasets. The results show that DDSL outperforms existing methods in dealing with both static dynamic graphs in terms of the responding time

On software-defined networking and the design of SDN controllers

© 2015 IEEE. Software-Defined Networking (SDN) has emerged as a networking paradigm that can remove the limitations of current network infrastructures by separating the control plane from the data forwarding plane. The implications include: the underlying network state and decision making capability are centralized; programmability is provided on the control plane; the operation at the forwarding plane is simplified; and the underlying network infrastructure is abstracted and presented to the applications. This paper discusses and exposes the details of the design of a common SDN controller based on our study of many controllers. The emphasis is on interfaces as they are essential for evolving the scope of SDN in supporting applications with different network resources requirements. In particular, the paper review and compare the design of the three controllers: Beacon, OpenDaylight, and Open Networking Operation System

SDN applications - The intent-based Northbound Interface realisation for extended applications

© 2016 IEEE. The Northbound Interface (NBI) plays a crucial role in promoting the adoption of SDN as it allows developers the freedom of developing their revenue-generating applications without being affected and constrained by the complexities of the underlying networks. To do so the NBI has to allow applications to express their requirements and constraints in their own application specific language, and the SDN controller to translate those requirements into SDN network specific language for provisioning network resources and services to satisfy the application requirements. The intent-based NBI is born from this consideration and the Open Networking Foundation (ONF) provides principles and guidelines to build such an intent-based NBI. However, these principles do not lend themselves readily to the design and practical realization of an intent-based NBI for extended classes of business-like network applications. This paper introduces a solution and its initial implementation in the form of a novel architecture for realizing the intent-based NBI. The new solution exploits the modularized and reuse features of the micro services and service oriented architectures

Ordered groupoids and the holomorph of an inverse semigroup

We present a construction for the holomorph of an inverse semigroup, derived from the cartesian closed structure of the category of ordered groupoids. We compare the holomorph with the monoid of mappings that preserve the ternary heap operation on an inverse semigroup: for groups these two constructions coincide. We present detailed calculations for semilattices of groups and for the polycyclic monoids.Comment: 16 page

Industri Perbankan Indonesia Periode 2001-2014: Deteksi Konsentrasi Pasar dan Prestasi Alma

This descriptive study aims to explain the condition of credits market and deposit market of Indonesian banking in the period of 2001-2014 includes the achievement of ALMA and CAMEL based on the secondary data and financial statements of 97 Indonesian banks. This graph result and tabulation and financial ratio show the information that Indonesian banking market is in the competitive condition (CR4 index and HHI index decrease and the market is classified in loose oligopoly condition), however all main variables of ALMA show the high ranking