Dynamic Matching Algorithm Research Articles

A utility-based approach for customised cloud service selection

The fact that cloud computing is widely accepted results in an increasing number of cloud providers. Customers are now burdened with the task of deciding which provider to choose for serving their requirements. This work developed a broker-based framework capable of automatically selecting cloud services based on user-defined requirement parameters and the service level agreement (SLA) attributes of the cloud providers. The goal is to help customers make clever decisions to achieve their best benefit. The framework contains components for decision making, cloud monitoring, user authentication, cloud access and SLA management. More specifically, we developed a utility-based, dynamic and flexible matching algorithm capable of maximising the users' profits. The matching algorithms as well as the entire framework were evaluated using a realistic simulation environment. Experimental results show that our utility-based approach performs well in terms of the matching quality and cost-saving.

A Dynamic Matching Algorithm for Audio Timestamp Identification Using the ENF Criterion

The electric network frequency (ENF) criterion is a recently developed technique for audio timestamp identification, which involves the matching between extracted ENF signal and reference data. For nearly a decade, conventional matching criterion has been based on the minimum mean squared error (MMSE) or maximum correlation coefficient. However, the corresponding performance is highly limited by low signal-to-noise ratio, short recording durations, frequency resolution problems, and so on. This paper presents a threshold-based dynamic matching algorithm (DMA), which is capable of autocorrecting the noise affected frequency estimates. The threshold is chosen according to the frequency resolution determined by the short-time Fourier transform (STFT) window size. A penalty coefficient is introduced to monitor the autocorrection process and finally determine the estimated timestamp. It is then shown that the DMA generalizes the conventional MMSE method. By considering the mainlobe width in the STFT caused by limited frequency resolution, the DMA achieves improved identification accuracy and robustness against higher levels of noise and the offset problem. Synthetic performance analysis and practical experimental results are provided to illustrate the advantages of the DMA.

Efficient interscanline consistency enforcing method for dynamic programming-based dense stereo matching algorithms

The dynamic programming-based dense stereo matching algorithms are faster than other global ones, but they usually suffer from the tangible horizontal “streaks” in their generated disparity maps. This problem takes place due to the independent processing of scanlines, ignoring vertical consistency between them. In this paper the path remembering method, which uses the information of the best paths of previous rows, is employed with new developments to establish more depth similarity between rows, especially along the slanted edges of objects in the scene. Also, a new way for estimating matching costs in the left border of the image is presented based on the information of the right-hand neighboring pixels. Mentioned improvements were applied to a well known and standard dynamic programming-based algorithm called “DP.” Evaluation of the new proposed algorithm on standard stereo images shows considerable improvements in the depth estimation along the slanted edges and in the left border of the final results. As a more precise report, the average error rate reduces from 14.2% to 10.4%.

ELM based approximate dynamic cycle matching for homogeneous symmetric Pub/Sub system

The number of cycle matchings increases exponentially with the number of subscriptions and the maximum length of cycle matchings, which needs a large amount of space to store intermediate results. Approximate cycle matching aims to store only a small part of intermediate results and find cycle matchings as many as possible. The existing solution prunes the intermediate results by a threshold of probability of a subscription to be matched, where the discrete degree of probabilities is neglected. In this paper, we propose an approximate dynamic cycle matching algorithm based on intermediate results classification using extreme learning machine. We first introduce a method of incorporating probability information into feature vector, and then propose the approximate cycle algorithm. Further, we propose a dynamic classification strategy considering that the data distribution of subscriptions may change as time goes on. The proposed approximate cycle matching algorithm and the dynamic classification strategy are evaluated in a simulated environment. The results show that compared with the approximate cycle matching based on probability threshold, the approximate cycle matching based on ELM classification is faster, and the dynamic classification strategy is more efficient and convenient. ELM is more suitable for approximate dynamic cycle matching than SVM with regards to response time.

Research on dynamic pricing of supply chain products based on channel advantages

PurposeThe purpose of this paper is to study the pricing problem of product transfer price under the channel advantages; determine the structure models of optimal transfer price expectation; and compare the differences in pricing of different pricing dominant parties.Design/methodology/approachUncertain factors are introduced into dynamic pricing mathematics models; production and storage models are combined; the method of functional analysis is used to solve transfer pricing question under different advantage conditions; and price matching models in supply chain integration are put forth.FindingsThere is a proportional relationship between the optimal transfer price expectation and price fluctuation. The party which has channel advantages will gain relatively more profit, but the maximum revenue can be obtained only in the supply chain integration.Research limitations/implicationsThere is no appropriate empirical data to verify the models.Practical implicationsThe paper provides pricing reference method to monopoly competitive enterprises on different stages. The matching pricing models based on E‐commerce can deal with the price deviation caused by goal difference and random factors automatically.Originality/valueThe paper considers production and inventory pricing, reflects the influence of the whole pricing factors under different channel advantages, and puts forth dynamic matching pricing models and algorithm under the E‐commerce circumstances.

A dynamic sort-based DDM matching algorithm for HLA applications

Simulation is a low-cost and safe alternative to solve complex problems in various areas. To promote reuse and interoperability of simulation applications and link geographically dispersed simulation components, distributed simulation was introduced. The High-Level Architecture (HLA) is the IEEE standard for distributed simulation. To optimize communication efficiency between simulation components, HLA defines a Data Distribution Management (DDM) service group for filtering out unnecessary data exchange. It relies on the computation of overlap between update and subscription regions, which is called “matching”. There are many existing matching algorithms, among which a sort-based approach improves efficiency by sorting region bounds before the actual matching process, and is found to outperform other existing matching algorithms in many situations. However, the existing algorithm performs matching for all regions in one round and cannot dynamically deal with a selective region modification without processing all the regions once again. Realizing that in many spatial applications, only a small subset of all regions are actually modified in each time step, this article proposes a dynamic sort-based matching algorithm to deal with this efficiently. Theoretical analysis has been carried out for the proposed algorithm and experimental results show that the proposed algorithm has significantly better performance than major existing matching algorithms at dynamic matching.

Using Dynamic Graph Matching and Gravity Models for Early Detection of Bioterrorist Attacks

Timely detection of a bioterrorist attack is of profound significance for efficient emergency public health management. Various systems currently exist which are capable of detecting the biologic agents prior to (e.g. biosensors) and after exposure (syndromic surveillance) but suffer from limitations like high cost and false positives (Stoto et al., Williams). In this paper, we use novel dynamic graph matching and gravity models to formulate a more precise and efficient methodology for detection. The problem is complicated by the similarity of anthrax and small pox symptoms to common diseases like influenza, chickenpox, airborne characteristics of these agents (that increases the risk of infection spreading to proximal regions), and non uniform distribution of terrorism risk among areas belonging to the same region. Our methodology will analyze patient symptom data available at hospitals using dynamic graph matching algorithms. We propose a heuristic that dynamically updates the template graphs based on patient data before applying matching algorithms, a unique feature of this study. Successful matches will be used to update counters that generate alerts once the counters surpass the threshold values. We develop a heuristic that uses a gravity model to group hospitals in a region into clusters based on the population they serve. Hospitals grouped together as a cluster affect counters that are local to the population they serve and generate alarms to the Public Health Department when they surpass the set threshold values. In addition, we use the fact that some symptoms are unique to these agents to make our algorithms more robust. These models could be used to develop practical applications for agencies such as DHS due to its ability to increase not just the likelihood of detection of a bioterrorism attack but also to identify with greater precision the location(s) of the attack. With minor modification they could also be used to plan for other disasters/epidemics such as SARS, and bird flu.

Articulated motion reconstruction from feature points

A fundamental task of reconstructing non-rigid articulated motion from sequences of unstructured feature points is to solve the problem of feature correspondence and motion estimation. This problem is challenging in high-dimensional configuration spaces. In this paper, we propose a general model-based dynamic point matching algorithm to reconstruct freeform non-rigid articulated movements from data presented solely by sparse feature points. The algorithm integrates key-frame-based self-initialising hierarchial segmental matching with inter-frame tracking to achieve computation effectiveness and robustness in the presence of data noise. A dynamic scheme of motion verification, dynamic key-frame-shift identification and backward parent-segment correction, incorporating temporal coherency embedded in inter-frames, is employed to enhance the segment-based spatial matching. Such a spatial–temporal approach ultimately reduces the ambiguity of identification inherent in a single frame. Performance evaluation is provided by a series of empirical analyses using synthetic data. Testing on motion capture data for a common articulated motion, namely human motion, gave feature-point identification and matching without the need for manual intervention, in buffered real-time. These results demonstrate the proposed algorithm to be a candidate for feature-based real-time reconstruction tasks involving self-resuming tracking for articulated motion.

A Second-Order Multibit Complex Bandpass AD Modulator with I, Q Dynamic Matching and DWA Algorithm

We have designed, fabricated and measured a second-order multibit switched-capacitor complex bandpass ΔΣAD modulator to evaluate our new algorithms and architecture. We propose a new structure of a complex bandpass filter in the forward path with I, Q dynamic matching, that is equivalent to the conventional one but can be divided into two separate parts. As a result, the AS modulator, which employs our proposed complex filter can also be divided into two separate parts, and there are no signal lines crossing between the upper and lower paths formed by complex filters and feedback DACs. Therefore, the layout design of the modulator can be simplified. The two sets of signal paths and circuits in the modulator are changed between I and Q while CLK is changed between high and low by adding multiplexers. Symmetric circuits are used for I and Q paths at a certain period of time, and they are switched by multiplexers to those used for Q and I paths at another period of time. In this manner, the effect of mismatches between I and Q paths is reduced. Two nine-level quantizers and four DACs are used in the modulator for low-power implementations and higher signal-to-noise-and-distortion (SNDR), but the nonlinearities of DACs are not noise-shaped and the SNDR of the ΔΣAD modulator degrades. We have also employed a new complex bandpass data-weighted averaging (DWA) algorithm to suppress nonlinearity effects of multibit DACs in complex form to achieve high accuracy; it can be realized by just adding simple digital circuitry. To evaluate these algorithms and architecture, we have implemented a modulator using 0.18 μm CMOS technology for operation at 2.8 V power supply; it achieves a measured peak SNDR of 64.5 dB at 20MS/s with a signal bandwidth of 78 kHz while dissipating 28.4 mW and occupying a chip area of 1.82 mm 2 . These experimental results demonstrate the effectiveness of the above two algorithms, and the algorithms may be extended to other complex bandpass ΔΣAD modulators for application to low-IF receivers in wireless communication systems.

모양 기반의 식물 잎 이미지 검색 시스템

본 논문에서는 식물 잎 모양을 기반으로 이미지를 표현하고 검색하는 식물 잎 이미지 검색 시스템을 보인다. 보다 효과적인 잎의 모양 표현을 위하여, MPP(Minimum Perimeter Polygons) 알고리즘을 개선하였고, 처리시간을 줄이기 위하여, NN(Nearest Neighbor) 검색을 개선한 동적 매칭알고리즘을 제안하였다. 본 시스템은 사용자에게 질의 이미지를 업로드하는 인터페이스를 제공하거나 모양 특징에 기반한 질의를 생성하는 도구를 제공하고 유사도에 따른 이미지를 검색한다. 검색의 편의성을 위해, 웹상에서 잎 모양과 잎차례를 스케치하여 손쉽게 질의할 수 있게 하였다. 실험에서는, 한국에 자생하는 식물 이미지 데이터베이스를 구축하였으며, 질의를 통해 검색된 유사한 이미지의 개수를 기반으로 성능을 평가하였다. In this paper, we present a leaf image retrieval system that represents and retrieves leaf images based on their shape. For more effective representation of leaf images, we improved an existing MPP algorithm. Also, in order to reduce the response time, we proposed a new dynamic matching algorithm at basically revises the Nearest Neighbor search. The system provides users with an interface for uploading query images or tools to generate queries based on shape features and retrieves images based on their similarity. For convenience, users are allowed to easily query images by sketching leaf shape or leaf arrangement on the web. In the experiment, we constructed an image database of Korean native plants and measured the system performance by counting the number of similar images retrieved for queries.

Generating Realistic Facial Expressions with Wrinkles for Model-Based Coding

Due to the limitations of current computer graphics technology mimicing realistic facial textures, such as wrinkles, is very difficult. Facial texture updating and compression are crucial to achieving realistic facial animation for low bit rate model-based coding. In this paper, we present a partial texture updating method for realistic facial expression synthesis with facial wrinkles. First, fiducial points on a face are estimated using a color-based deformable template matching method. Second, an extended dynamic mesh matching algorithm is developed for face tracking. Next, textures of interest (TOI) in the potential expressive wrinkles and mouth–eye texture areas are captured by the detected fiducial points. Among the TOI, the so-called active textures or expressive textures are extracted by exploring temporal correlation information. Finally, the entire facial texture is synthesized using the active texture. Compared to the entire texture updating scheme, partially updating and compressing facial textures significantly reduce the computational complexity and bit rates while still producing an acceptable visual quality. Experiments on the video sequences demonstrate the advantage of the proposed algorithm.

Improved Dynamic Dictionary Matching

In the dynamic dictionary matching problem, a dictionary D contains a set of patterns that can change over time by insertion and deletion of individual patterns. The user also presents text strings and asks for all occurrences of any patterns in the text. The two main contributions of this paper are: (1) a faster algorithm for dynamic string dictionary matching with bounded alphabets, and (2) a dynamic dictionary matching algorithm for two-dimensional texts and patterns. The first contribution is based on an algorithm that solves the general problem of maintaining a sequence of well-balanced parentheses under the operations insert, delete, and find nearest enclosing parenthesis pair. The main new idea behind the second contribution is a novel method to efficiently manipulate failure links for two-dimensional patterns.