12829985
Type-2 Fuzzistics for Symmetric Interval Type-2 Fuzzy Sets: Part 2, Inverse Problems
In Part 1 of this two-part paper, we bounded the centroid of a symmetric interval type-2 fuzzy set (T2 FS), and consequently its uncertainty, using geometric properties of its footprint of uncertainty (FOU). We then used these bounds to solve forward problems, i.e., to go from parametric interval T2 FS models to data. The main purpose of the present paper is to formulate and solve inverse problems, i.e., to go from uncertain data to parametric interval T2 FS models, which we call type-2 fuzzistics. Given interval data collected from people about a phrase, and the inherent uncertainties associated with that data, which can be described statistically using the first- and second-order statistics about the end-point data, we establish parametric FOUs such that their uncertainty bounds are directly connected to statistical uncertainty bounds. These results should find applicability in computing with words
7613281
New results about the centroid of an interval type-2 fuzzy set, including the centroid of a fuzzy granule
The centroid of an interval type-2 fuzzy set (IT2 FS) provides a measure of the uncertainty of such a FS. Its calculation is very widely used in interval type-2 fuzzy logic systems. In this paper, we present properties about the centroid of an IT2 FS. We also illustrate many of the general results for a T2 fuzzy granule (FG) in order to develop some understanding about the uncertainty of the FG in terms of its vertical and horizontal dimensions. At present, the T2 FG is the only IT2 FS for which it is possible to obtain closed-form formulas for the centroid, and those formulas are in this paper.
9573622
On choosing models for linguistic connector words for Mamdani fuzzy logic systems
We examine ten antecedent connector models in the framework of a singleton or nonsingleton fuzzy logic system (FLS), to establish which models can be used. In this work, a usable connector model must lead to a separable firing degree that is a closed-form and piecewise-differentiable function of the membership function parameters and also the parameter characterizing that connector model. Our analysis shows that: for a singleton FLS where the Mamdani-product or Mamdani-minimum implication method is used, all ten antecedent connector models are usable; for a nonsingleton FLS where the Mamdani-product implication method is used, only one antecedent connector model is usable; and for a nonsingleton FLS where the Mamdani-minimum implication method is used, none of the ten antecedent connector models is usable. We also show, by examples, that the parameter of the antecedent connector model provides additional freedom in adjusting a FLS, so that the FLS has the potential to achieve better performance than a FLS that uses the traditional product or minimum t-norm for the antecedent connections.
7022867
Accurate prediction of orthologous gene groups in microbes
We present a new computational method for the prediction of orthologous gene groups for microbial genomes based on the prediction of co-occurrences of homologous genes. The method is inspired by the observation that homologous genes are highly likely to be orthologous if their neighboring genes are also homologous. Based on co-occurrences of homologous genes, we have grouped the (predicted) operons of 77 selected sequenced microbial genomes so that operons of the same group are highly likely to be functionally similar or related. We then cluster the homologous genes in the same operon group so that genes of the same cluster are highly likely to be similar in terms of their sequences and functions, i.e., they are predicted to be orthologous genes. By comparing our predicted orthologous gene groups with the COG assignments and NCBI annotations, we conclude that our method is promising to provide more accurate and specific predictions than the existing methods.
19790752
Classification of Battlefield Ground Vehicles Using Acoustic Features and Fuzzy Logic Rule-Based Classifiers
In this paper, we demonstrate, through the multicategory classification of battlefield ground vehicles using acoustic features, how it is straightforward to directly exploit the information inherent in a problem to determine the number of rules, and subsequently the architecture, of fuzzy logic rule-based classifiers (FLRBC). We propose three FLRBC architectures, one non-hierarchical and two hierarchical (HFLRBC), conduct experiments to evaluate the performances of these architectures, and compare them to a Bayesian classifier. Our experimental results show that: 1) for each classifier the performance in the adaptive mode that uses simple majority voting is much better than in the non-adaptive mode; 2) all FLRBCs perform substantially better than the Bayesian classifier; 3) interval type-2 (T2) FLRBCs perform better than their competing type-1 (T1) FLRBCs, although sometimes not by much; 4) the interval T2 nonhierarchical and HFLRBC-series architectures perform the best; and 5) all FLRBCs achieve higher than the acceptable 80% classification accuracy
7598933
SYN-MAC: A Distributed Medium Access Control Protocol for Synchronized Wireless Networks
In this paper, we propose a novel medium access control (MAC) protocol, called SYN-MAC (for SYNchronized MAC), based on a binary countdown approach tailored for wireless networks. SYN-MAC has several attractive features such as simplicity, robustness, high efficiency, fairness, and quality of service capability. We evaluate SYN-MAC in terms of collision probability, system throughput, and packet delay, via both analysis and simulation. Our results show that, with properly chosen parameters, SYN-MAC can achieve a very low collision probability, packet delay tolerance, and extremely high channel efficiency (of > 90%) under a wide range of traffic load. As a result, SYN-MAC may serve as an alternative to IEEE 802.11 for the wireless stations in synchronized networks.
14728640
Public Authentication of 3D Mesh Models
In this paper, a public-key scheme is proposed to authenticate 3D mesh models. It is well known that digital signature schemes can be used for data authentication by generating a separate signature and appending it to the file. Another way is divide the original data into two parts: the content to be authenticated and the cover content. In the embedding process, the signature of the first part is generated and imperceptibly embedded within the cover content to form the signed content. In the authentication process, a new hash value is produced from the signed content and compared with the value decrypted from the retrieved signature for tamper detection. Before we implement such a scheme on polygonal meshes, mesh partitioning technique is used to divide them into patches with a fixed amount of vertices. For each patch, a corresponding signature is generated to replace the least significant bits of vertex coordinates within it so that the tamper can be localized. The experimental results have shown the promising results
18504704
Instruction Scheduling with Timing Constraints on a Single RISC Processor with 0/1 Latencies
In this paper, We propose a faster algorithm for the following instruction scheduling problem: Given a set of UET (Unit Execution Time) instructions with precedence constraints in the form of a DAG(Directed Acyclic Graph), latency constraints where latencies between any two instructions are restricted to be either 0 or 1, timing constraints in the form of individual integer release times and deadlines and a single RISC processor, find a feasible schedule which satisfies all constraints. The time complexity of our algorithm is O(n2 log n) + min{O(ne), O(n2.376)}, where n is the number of instructions and e is the number of edges in the precedence graph. Our algorithm is faster than the existing algorithm which runs in O(n3α(n)) time, where α(n) is the inverse of Ackermann function. In addition, our algorithm can be used to solve the maximum lateness minimization problem in O(n2 log2 n + min{ne, n2.376}) time.
9865654
A reversible data hiding approach to mesh authentication
This paper proposes a reversible data hiding method to authenticate 3D meshes by modulating the distances from the mesh faces to the mesh centroid to embed a fragile watermark. It keeps the modulation information in the watermarked mesh so that the reversibility of the embedding process is achieved. Since the embedded watermark is sensitive to geometrical and topological processing, unauthorized modifications on the watermarked mesh can be therefore detected by retrieving and comparing the embedded watermark with the original one. Furthermore, as long as the watermarked mesh is intact, the original mesh can be recovered using some priori knowledge.
10090646
On Multiprocessor Utility Accrual Real-Time Scheduling with Statistical Timing Assurances
We present the first Utility Accrual (or UA) real-time scheduling algorithm for multiprocessors, called gMUA. The algorithm considers an application model where real-time activities are subject to time/utility function time constraints, variable execution time demands, and resource overloads where the total activity utilization demand exceeds the total capacity of all processors. We establish several properties of gMUA including optimal total utility (for a special case), conditions under which individual activity utility lower bounds are satisfied, a lower bound on system-wide total accrued utility, and bounded sensitivity for assurances to variations in execution time demand estimates. Our simulation experiments confirm our analysis and illustrate the algorithm's effectiveness