The cell probe complexity of succinct data structures

We consider time-space tradeoffs for static data structure problems in the cell probe model with word size 1 (the bit probe model). In this model, the goal is to represent n$n$-bit data with s=n+r$s=n+r$ bits such that queries (of a certain type) about the data can be answered by reading at most t$t$ bits of the representation. Ideally, we would like to keep both s$s$ and t$t$ small, but there are tradeoffs between the values of s$s$ and t$t$ that limit the possibilities of keeping both parameters small.     

Segmentation of microscope images of living cells

This paper describes a segmentation method combining a texture based technique with a contour based method. The technique is designed to enable the study of cell behaviour over time by segmenting brightfield microscope image sequences. The technique was tested on artificial images, based on images of living cells and on real sequences acquired from microscope observations of neutrophils and lymphocytes as well as on a sequence of MRI images. The results of the segmentation are compared with the results of the watershed and snake segmentation methods. The results show that the method is both effective and practical.

Toxicoproteomics and its application to human health risk assessment

Toxicoproteomics is the use of proteomic technologies to better understand environmental and genetic factors, toxic mechanisms, and modes of action in response to acute exposure to toxicants and in the long-term development of diseases caused or influenced by these exposures. Use of toxicoproteomic technologies to identify key biochemical pathways, mechanisms, and biomarkers of exposure and toxicity will decrease the uncertainties that are associated with human health risk assessments. This review provides an overview of toxicoproteomics from human health risk assessment perspectives. Key toxicoproteomic technologies such as 2-D gel-based proteomic methods and toxicoproteomic approaches are described, and examples of applications of these technologies and methodologies in the risk assessment context are presented. The discussion includes a focus on challenges and future directions.     

基于视觉的表格自动识别方法

表格是建筑工程图中表示信息的主要方式之一。计算机自动读图、读表技术对建筑业现代化有十分重要作用。借鉴人工读表的视觉原理和步骤, 针对表格形式的多变性等特点, 提出基于视觉、自顶向下的表格自动阅读方法, 有效地解决了表格格式分析, 识别并处理了耦合、嵌套、合并、复用等情况。     

共振属性元神经网络*

以属性论为基础,引入电磁共振思想,将按模式记忆理论网络化,提出一种共振属性元层次网络,可有效解决规模问题,降低推理对知识量的依赖。它将事物的关联直接表示为事物属性间的关联,用共振信息实现这种关联,以共振信息在网络中的传递实现智能推理。该网络具有高度的并行性、可扩展性、不完全属性的学习和推理能力。     

A Generalization of a Lower Bound Technique due to Fredman and Saks

{In a seminal paper of 1989, Fredman and Saks proved lower bounds for some important data-structure problems in the cell probe model. In particular, lower bounds were established on worst-case and amortized operation cost for the union-find problem and the prefix sum problem. The goal of this paper is to turn their proof technique into a general tool that can be applied to different problems and computational models. To this end we define two quantities: Output Variability depends only on the model of computation. It indicates how much variation can be found in the results of a program with certain resource bounds. This measures in some sense the power of a model. Problem Variability characterizes in a similar sense the difficulty of the problem. } Our Main Theorem shows that by comparing a model's output variability to a problem's problem variability, lower bounds on the complexity of solving the problem on the given model may be inferred. The theorem thus shows how to separate the analysis of the model of computation from that of the problem when proving lower bounds. We show how the results of Fredman and Saks fit our framework by computing the output variability of the cell probe model and the problem variability for problems considered in their paper. This allows us to reprove their lower bound results, and slightly extend them. The main purpose of this paper though is to present the generalized technique. Received January 25, 1999; revised July 30, 1999.     

A computational method for simulating growth patterns in unicell propagation

The modelling of natural phenomena through the use of computer-generated graphics has attracted much interest recently. It is believed that such methods will lead to new breakthroughs in understanding nature. One of the most popular methods used is the cell automata method, where cells are made to propagate and form cellular patterns according to certain predefined rules. Although much of the work in this area is for recreational purposes, as in the Game of Life, there can be more serious aspects to it. One of these is in the use of such methods to predict and simulate the growth behaviour of cell clusters in real-life situations. In this study, an attempt is made to formalise certain rules for modelling the growth characteristics of unicell populations. The methodology proposed models three fundamental factors: first, the generic propagational characteristics of a cell; second, the effect of adverse factors to growth; and, third, the effect of spatial constraints. The first two factors, relating to the population of a cell colony, can be modelled mathematically; the third factor determines the visual appearance of the cell colony. Patterns resulting from some computational simulations are presented and discussed.     

Seamless handover supported by parallel polling and dynamic multicast group in connected WLAN micro-cells system

WLAN (Wireless Local Area Network) has been seen to be one of the promising access technologies that adapts to 4G cellular network systems in providing very high speed connection with QoS guarantee through the polling function. However, when the handover happens, the contention-based medium access mechanism which is mainly used in WLAN is invoked and introduces unbounded transmission delay due to idle time periods and retransmission because of collision during the handover. If this technique is expanded to use in a microcellular network such as connected WLAN micro-cells, contention-based mechanism, therefore, should not be used to handle the MT’s handover, especially for vehicular users who change access point every few seconds. To overcome these difficulties in handover, we introduce parallel polling scheme in dynamic LMC (Logical Macro Cell) which can reduce delays much and remove packet loss rate. LMC is a virtual single macro cell which is built on a multicast group of adjacent micro-cells. In the same LMC, polling signals are sent from every BS (base station) to give MT (mobile terminal) permission to access one of these BSs. Instead of wasting much time to contend for resources of a new BS during handover, the MT answers the polling as an acknowledgment to connect to that new BS. The polling response is controlled to multicast to all BSs of the same LMC via the core network to synchronize for the next polling cycle. LMC is controlled to dynamically change when the MT comes in a new BS to make polling signals be continuous in a new LMC. Through analytical and simulation results, we show that the parallel polling scheme can achieve no handover latency, no packet loss and maintain mobile users’ throughput stably in the high traffic load condition though it causes overhead on the neighboring cells in both of wired and wireless sections. At speeds of up to70 m/s, the MT can still maintain its stable connection. OMNeT++ simulator with INET project is used to evaluate our proposal.