Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

Annealing and doping-dependent magnetoresistance in single layer poly(3-hexyl-thiophene) organic semiconductor device

We compare the current density–voltage (J–V) and magnetoconductance (MC) response of a poly(3-hexyl-thiophene) (P3HT) device (Au/P3HT(350 nm)/Al) before and after annealing above the glass transition temperature of 150 °C under vacuum. There is a decrease of more than 3 orders of magnitude in current density due to an increase of the charge injection barriers after de-doping through annealing. An increase, approaching 1 order of magnitude, in the negative MC response after annealing can be explained by a shift in the Fermi level due to de-doping, according to the bipolaron mechanism. We successfully tune the charge injection barrier through re-doping by photo-oxidation. This leads to the charge injection and transport transitioning from unipolar to ambipolar, as the bias increases, and we model the MC response using a combination of bipolaron and triplet-polaron interaction mechanisms.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

异构分层无线网络中基于逗留时间的动态流量均衡算法研究

为使异构分层无线网络能服务更多的移动用户,提出了一种基于逗留时间的动态流量均衡算法.该算法首先根据用户移动模型计算其在小区内的逗留时间,然后基于小区呼叫到达率和重叠覆盖小区的流量状态来确定一个周期内呼叫转移的数量,最后依据逗留时间门限值将重负载小区中满足条件的呼叫转移到轻负载的重叠覆盖小区中.为降低切换呼叫掉线率,还对异构网间的呼叫切换策略做了改进.仿真实验结果表明,本算法在新呼叫阻塞率和切换呼叫掉线率等性能指标上比传统方法有显著的提高.     

基于SONET/SDH的存储网络容灾技术分析

文章分析了存储网络（SAN）容灾技术，认为在某些企业中，数据是至关重要的资产之一，是业务系统运行的血脉．保护企业的重要数据是企业成功的关键因素。文章讨论了设计容灾技术解决方案应考虑的各种因素，并给出了基于SONET／SDH的存储网络技术的体系架构设计方案。     

Efficient multicast search under delay and bandwidth constraints

The issue of a multicast search for a group of users is discussed in this study. Given the condition that the search is over only after all the users in the group are found, this problem is called the Conference Call Search (CCS) problem. The goal is to design efficient CCS strategies under delay and bandwidth constraints. While the problem of tracking a single user has been addressed by many studies, to the best of our knowledge, this study is one of the first attempts to reduce the search cost for multiple users. Moreover, as oppose to the single user tracking, for which one can always reduce the expected search delay by increasing the expected search cost, for a multicast search the dependency between the delay and the search cost is more complicated, as demonstrated in this study. We identify the key factors affecting the search efficiency, and the dependency between them and the search delay. Our analysis shows that under tight bandwidth constraints, the CCS problem is NP-hard. We therefore propose a search method that is not optimal, but has a low computational complexity. In addition, the proposed strategy yields a low search delay as well as a low search cost. The performance of the proposed search strategy is superior to the implementation of an optimal single user search on a group of users. Amotz Bar-Noy received the B.Sc. degree in 1981 in Mathematics and Computer Science and the Ph.D. degree in 1987 in Computer Science, both from the Hebrew University, Israel. From October 1987 to September 1989 he was a post-doc fellow in Stanford University, California. From October 1989 to August 1996 he was a Research Staff Member with IBM T. J. Watson Research Center, New York. From February 1995 to September 2001 he was an associate Professor with the Electrical Engineering-Systems department of Tel Aviv University, Israel. From September 1999 to December 2001 he was with AT research labs in New Jersey. Since February 2002 he is a Professor with the Computer and Information Science Department of Brooklyn College - CUNY, Brooklyn New York. Zohar Naor received the Ph.D. degree in Computer Science from Tel Aviv University, Tel Aviv, Israel, in 2000. Since 2003 he is with the University of Haifa, Israel. His areas of interests include wireless networks, resource management of computer networks, mobility, search strategies, and multiple access protocols.     

Simulation of humidity control and greenhouse temperature tracking in a growth chamber using a passive air conditioning unit

In this paper, we define a dynamic discrete model of a passive air conditioning unit, without the more typical compression or absorption-refrigeration cycle. The unit is composed of heat exchangers, a positioning system and humid corrugated pads. The aim of the study was to follow the temperature in a greenhouse and to replicate it with a desired and stable relative humidity in a ventilated growth chamber. A control law, based on a quadratic criterion and dynamic programming, taking output error and energy consumption minimisation into account, was used to control the behaviour of the unit in spite of air intake disturbances. The results of the simulation indicate that the air conditioning unit can produce a variable climate in the growth chamber, with a wide range of relative humidity setpoints.     

Implementation of RNS-Based Distributed Arithmetic Discrete Wavelet Transform Architectures Using Field-Programmable Logic

Currently there are design barriers inhibiting the implementation of high-precision digital signal processing (DSP) objects with field programmable logic (FPL) devices. This paper explores overcoming these barriers by fusing together the popular distributed arithmetic (DA) method with the residue number system (RNS) for use in FPL-centric designs. The new design paradigm is studied in the context of a high-performance filter bank and a discrete wavelet transform (DWT). The proposed design paradigm is facilitated by a new RNS accumulator structure based on a carry save adder (CSA). The reported methodology also introduces a polyphase filter structure that results in a reduced look-up table (LUT) budget. The 2C-DA and RNS-DA are compared, in the context of a FPL implementation strategy, using a discrete wavelet transform (DWT) filter bank as a common design theme. The results show that the RNS-DA, compared to a traditional 2C-DA design, enjoys a performance advantage that increases with precision (wordlength).     

On the Automatic Recovery of Style-Specific Architectural Relations in Software Systems

The cost of maintaining a software system over a long period of time far exceeds its initial development cost. Much of the maintenance cost is attributed to the time required by new developers to understand legacy systems. High-level structural information helps maintainers navigate through the numerous low-level components and relations present in the source code. Modularization tools can be used to produce subsystem decompositions from the source code but do not typically produce high-level architectural relations between the newly found subsystems. Controlling subsystem interactions is one important way in which the overall complexity of software maintenance can be reduced.We have developed a tool, called ARIS (Architecture Relation Inference System), that enables software engineers to define rules and relations for regulating subsystem interactions. These rules and relations are called Interconnection Styles and are definedusing a visual notation. The style definition is used by our tool to infer subsystem-level relations in designs being reverse engineered from source code.In this paper we describe our tool and its underlying techniques and algorithms. Using a case study, we describe how ARIS is used to reverse engineer high-level structural information from a real application.