Computer and Robot Vision Vol. 1, by R.M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10887-1.

Computer and Robot Vision

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[서평]「Computer Organization and Design, The Hardware/Software Interface」

Functional magnetic resonance imaging (fMRI) techniques have contributed significantly to our understanding of brain function. Current methods are based on the analysis of gradual and continuous changes in the brain blood oxygenated level dependent (BOLD) signal. Departing from that approach, recent work has shown that equivalent results can be obtained by inspecting only the relatively large amplitude BOLD signal peaks, suggesting that relevant information can be condensed in discrete events. This idea is further explored here to demonstrate how brain dynamics at resting state can be captured just by the timing and location of such events, i.e., in terms of a spatiotemporal point process. The method allows, for the first time, to define a theoretical framework in terms of an order and control parameter derived from fMRI data, where the dynamical regime can be interpreted as one corresponding to a system close to the critical point of a second order phase transition. The analysis demonstrates that the resting brain spends most of the time near the critical point of such transition and exhibits avalanches of activity ruled by the same dynamical and statistical properties described previously for neuronal events at smaller scales. Given the demonstrated functional relevance of the resting state brain dynamics, its representation as a discrete process might facilitate large-scale analysis of brain function both in health and disease.

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Criticality in large-scale brain FMRI dynamics unveiled by a novel point process analysis.

The fifth generation (5G) wireless network technology is to be standardized by 2020, where main goals are to improve capacity, reliability, and energy efficiency, while reducing latency and massively increasing connection density. An integral part of 5G is the capability to transmit touch perception type real-time communication empowered by applicable robotics and haptics equipment at the network edge. In this regard, we need drastic changes in network architecture including core and radio access network (RAN) for achieving end-to-end latency on the order of 1 ms. In this paper, we present a detailed survey on the emerging technologies to achieve low latency communications considering three different solution domains: 1) RAN; 2) core network; and 3) caching. We also present a general overview of major 5G cellular network elements such as software defined network, network function virtualization, caching, and mobile edge computing capable of meeting latency and other 5G requirements.

A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions

Recent experimental work has shown that activity in living neural networks can propagate as a critical branching process that revisits many metastable states. Neural network theory suggests that attracting states could store information, but little is known about how a branching process could form such states. Here we use a branching process to model actual data and to explore metastable states in the network. When we tune the branching parameter to the critical point, we find that metastable states are most numerous and that network dynamics are not attracting, but neutral.

Critical Branching Captures Activity in Living Neural Networks and Maximizes the Number of Metastable States

Latency is increasingly becoming a performance bottleneck for Internet Protocol (IP) networks, but historically, networks have been designed with aims of maximizing throughput and utilization. This paper offers a broad survey of techniques aimed at tackling latency in the literature up to August 2014, as well as their merits. A goal of this work is to be able to quantify and compare the merits of the different Internet latency reducing techniques, contrasting their gains in delay reduction versus the pain required to implement and deploy them. We found that classifying techniques according to the sources of delay they alleviate provided the best insight into the following issues: 1) The structural arrangement of a network, such as placement of servers and suboptimal routes, can contribute significantly to latency; 2) each interaction between communicating endpoints adds a Round Trip Time (RTT) to latency, particularly significant for short flows; 3) in addition to base propagation delay, several sources of delay accumulate along transmission paths, today intermittently dominated by queuing delays; 4) it takes time to sense and use available capacity, with overuse inflicting latency on other flows sharing the capacity; and 5) within end systems, delay sources include operating system buffering, head-of-line blocking, and hardware interaction. No single source of delay dominates in all cases, and many of these sources are spasmodic and highly variable. Solutions addressing these sources often both reduce the overall latency and make it more predictable.

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Reducing Internet Latency: A Survey of Techniques and Their Merits

A social network is composed by communities of individuals or organizations that are connected by a common interest. Online social networking sites like Twitter, Facebook and Orkut are among the most visited sites in the Internet. Presently, there is a great interest in trying to understand the complexities of this type of network from both theoretical and applied point of view. The understanding of these social network graphs is important to improve the current social network systems, and also to develop new applications. Here, we propose a friend recommendation system for social network based on the topology of the network graphs. The topology of network that connects a user to his friends is examined and a local social network called Oro-Aro is used in the experiments. We developed an algorithm that analyses the sub-graph composed by a user and all the others connected people separately by three degree of separation. However, only users separated by two degree of separation are candidates to be suggested as a friend. The algorithm uses the patterns defined by their connections to find those users who have similar behavior as the root user. The recommendation mechanism was developed based on the characterization and analyses of the network formed by the user's friends and friends-of-friends (FOF).

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A graph-based friend recommendation system using Genetic Algorithm

The invention concerns a method of providing an Internet protocol television service to a subscriber, and a network element (53, 63, 73) to execute this method. At an acquisition tier (1), IPTV packets are generated from video stream data of one or more video channels and transmitted to a FCC server cluster (61, 71) at a client-facing tier (2). IPTV packets associated with one of the one or more video channels selected by the subscriber are delivered from the deliver server cluster (61, 71) to a receiver (77, 671, 672, 673) of the subscriber at a client tier (3) wherein the IPTV packets associated with the one of the one or more video channels selected by the subscriber are reassembled at said receiver (77, 671, 672, 673) into a coherent video stream for display to the subscriber. Said generated IPTV packets are routed from a network (5) of a TV broadcaster to one or more networks (6, 7) of one or more TV operators or from a network (6, 7) of a TV operator to one or more networks (6, 7) of one or more TV operators by means of IPTV service routers (53, 63, 73) installed at an intertwine tier (4) arranged between the acquisition tier (1) and the client-facing tier (2), whereby each of the networks (5, 6, 7) of the TV broadcaster and/or TV operators has an IPTV service router (53, 63, 73) associated with it whereby each IPTV service router (53, 63, 73) is responsible for signalling and transport of said generated IPTV packets via said intertwine tier (4).

Method of providing an iptv service

This paper concerns the use of Active Queue Management (AQM) to reduce queuing delay. It offers insight into why it has proved hard for a Proportional Integral (PI) controller to remain both responsive and stable while controlling `Classic' TCP flows, such as TCP Reno and Cubic. Due to their non-linearity, the controller's adjustments have to be smaller when the target drop probability is lower. The PI Enhanced (PIE) algorithm attempts to solve this problem by scaling down the adjustments of the controller using a look-up table. Instead, we control an internal variable that is by definition linearly proportional to the load, then post-process it into the required Classic drop probability---in fact we show that the output simply needs to be squared. This allows tighter control, giving responsiveness and stability better or no worse than PIE achieves, but without all its corrective heuristics. Additionally, with suitable packet classification, it becomes simple to extend this PI2 AQM to support coexistence between Classic and Scalable congestion controls in the public Internet. Unlike a Classic congestion control, a Scalable congestion control ensures sufficient feedback at any flow rate, an example being Data Centre TCP (DCTCP). A Scalable control is linear, so we can use the internal variable directly without any squaring, by omitting the post-processing stage. We implemented this PI2 AQM as a Linux qdisc to extensively test our claims using Classic and Scalable TCPs.

PI2: A Linearized AQM for both Classic and Scalable TCP

Diversity of cluster size has been used as a measurement of complexity in several systems that generate a statistical distribution of clusters. Using Monte Carlo simulations, we present a statistical analysis of the cluster size diversity and the number of clusters generated on randomly occupied lattices for the Euclidean dimensions 1 to 6. A tuning effect for diversity of cluster size and critical probabilities associated with the maximum diversity and the maximum number of clusters are reported. The probability of maximum diversity is related to the percolation threshold and several scaling relations between the variables measured are reported. The statistics of cluster size diversity has important consequences in the statistical description of the Universe as a complex system.

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Ing-Jyh Tsang

Papers

Reducing Internet Latency: A Survey of Techniques and Their Merits

A graph-based friend recommendation system using Genetic Algorithm

Method of providing an iptv service

PI2: A Linearized AQM for both Classic and Scalable TCP

Cluster size diversity, percolation, and complex systems.