26954040
Multi-User Joint Doppler Spread Estimation in Generalized Distributed Antenna System
Generalized distributed antenna is one of the most promising architectures likely to be used in next generation mobile communication systems. In this paper, based on the architecture, multi-user co-channel interference in Doppler spread estimation is analyzed and several useful conclusions are obtained. Moreover, in order to combat this interference, a novel ACF-based multi-user joint Doppler spread estimation (M- JDSE) algorithm is proposed, taking advantage of centralized signal processing characteristic in generalized distributed antenna systems. Both theoretical analysis and simulation results demonstrate the significant performance improvement of proposed M-JDSE algorithm in multi-user environments.
3219801
Aspect mining from a modelling perspective
Aspect mining aims at identifying, analysing, and refactoring crosscutting concerns throughout a legacy system for the purpose of improving software modularisation. This paper presents our investigation into raising the benefits of aspect mining to high level domain-specific models. A key contribution is the capability to identify crosscutting concerns early in development, which will assist in the modularisation of a design through aspects, before proceeding to the implementation level. Furthermore, our experience has led us to believe that aspects are easier to identify at the modelling level, because much of the accidental complexities of implementation concerns are not present in the corresponding modelling abstractions.
14510404
Model replication: transformations to address model scalability
2 SUMMARY In Model-Driven Engineering, it is often desirable to evaluate different design alternatives as they relate to scalability issues of the modeled system. A typical approach to address scalability is model replication, which starts by creating base models that capture the key entities as model elements and their relationships as model connections. A collection of base models can be adorned with necessary information to characterize a specific scalability concern as it relates to how the base modeling elements are replicated and connected together. In current modeling practice, such model replication is usually accomplished by scaling the base model manually. This is a time-consuming process that represents a source of error, especially when there are deep interactions between model components. As an alternative to the manual process, this paper presents the idea of automated model replication through a model transformation process that expands the number of elements from the base model and makes the correct connections among the generated modeling elements. The paper motivates the need for model replication through case studies taken from models supporting different domains.
37283725
Business Process-Oriented Software Architecture for Supporting Business Process Change
As a business process is essential in running an enterprise, this paper aims toward improving software architecture by extracting business-relevant semantics from business logic and transforming them as important elements that need to be molded and represented in software architecture. This allows for the development of a business process-oriented software architecture (BPOSA) that can support smoother business process change. The paper introduces the structure of BPOSA and its work mode. Then it describes the steps involved in designing a process-oriented software system, and provides analysis and design methods of extending process-relevant attributes for application in business operations.
7333588
Automating change evolution in model-driven engineering
The escalating complexity of software and system models is making it difficult to rapidly explore the effects of a design decision. Automating such exploration with model transformation and aspect-oriented techniques can improve both productivity and model quality. The combination of model transformation and aspect weaving provides a powerful technology for rapidly transforming legacy systems from the high-level properties that models describe. Further, by applying aspect-oriented techniques and program transformation, small changes at the modeling level can trigger very large transformations at the source code level. Thus, model engineers can explore alternative configurations using an aspect weaver targeted for modeling tools and then use the models to generate program transformation rules for adapting legacy source code on a wide scale.
14774281
A Composition-Oriented Approach for Business Process Formal Design
Traditional approaches to designing business processes are often inadequate for complicated, distributed, and collaborated settings. However since network technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore a new approach is needed. To this end, we describe the motivation, conceptualization, and analysis of a composition-oriented business process design method. The key advance of our method is that it uses process algebra pi-calculus as its formal basis and builds a complex process by composing simple structured process control modules to reduce the complexity of business process design as well as let several designers collaborate the design of a complex process. To make business process more clear, we also provide way of separating exception processing logic from normal process control logic and provide scooping mechanisms to minimize the detrimental effects of unplanned contingencies by ways of composition
775586
Efficient Video Authentication for H.264/AVC
This paper proposed a novel and efficient scheme to authenticate the H.264/AVC video. The scheme makes an accurate usage of the tree-structured motion compensation, motion estimation and Lagrangian optimization of the standard. Authentication information is embedded strictly based on the best mode decision strategy in the sense that if undergone any spatial and temporal attacks, the scheme can detect the tampering by the sensitive mode change. And the experimental results prove the effectiveness the algorithm against many transcoding and signal processing attacks
13273680
Modular verification of dynamically adaptive systems
Cyber-physical systems increasingly rely on dynamically adaptive programs to respond to changes in their physical environment; examples include ecosystem monitoring and disaster relief systems. These systems are considered high-assurance since errors during execution could result in injury, loss of life, environmental impact, and/or financial loss. In order to facilitate the development and verification of dynamically adaptive systems, we separate functional concerns from adaptive concerns. Specifically, we model a dynamically adaptive program as a collection of (non-adaptive) steady-state programs and a set of adaptations that realize transitions among steady state programs in response to environmental changes. We use Linear Temporal Logic (LTL) to specify properties of the non-adaptive portions of the system, and we use A-LTL (an adapt-operator extension toLTL) to concisely specify properties that hold during the adaptation process. Model checking offers an attractive approach to automatically analyzing models for adherence to formal properties and thus providing assurance. However, currently, model checkers are unable to verify properties specified using A-LTL. Moreover, as the number of steady-state programs and adaptations increase, the verification costs (in terms of space and time) potentially become unwieldy. To address these issues, we propose a modular model checking approach to verifying that a formal model of an adaptive program satisfies its requirements specified in LTL and A-LTL, respectively.
26080905
Implementation Technique of Unrestricted LL Action Grammar
Action Grammar is a grammar with action symbols appearing in the right part of production rules, which can be used to implement semantic analyzer automatically. An action symbol represents the name of a semantic routine. Implementation of action grammar relies on specific parsing methods, such as LL(K), recursive-descent or LR, and so on. However, these parsing methods have their own restrictions on grammars, therefore, in order to accomplish these parsing methods certain equivalent transformations have been done to make the grammars meet the restrictions. This paper has proposed an implementation technique of LL action grammar, which requires no transformation to the original grammar. Our approach includes following steps: parsing the input string with back-tracking and producing the parsing paths for each non-terminal symbol, then constructing LL parsing table with the parsing paths obtained, finally conducting semantic analysis with LL parsing table. The main contribution of this paper is that non-backtracking semantic analyzer has been achieved without making any transformations to the grammar.
46004277
Improved Blind Decodings of STBC with Unknown and Known Channel Correlation to Transmitter
The subspace algorithm can be utilized for the blind detection of space-time block codes (STBC) without knowledge of channel state information (CSI) both at the transmitter and receiver. However, its performance degrades when the channels are correlated. In this letter, we analyze the impact of channel correlation from the orthogonality loss between the transmit signal subspace (TSS) and the statistical noise subspace (SNS). Based on the decoding property of the subspace algorithm, we propose a revised detection in favor of the channel correlation matrix (CCM) only known to the receiver. Then, a joint transmit-receive preprocessing scheme is derived to obtain a further performance improvement when the CCM is available both at the transmitter and receiver. Analysis and simulation results indicate that the proposed methods can significantly improve the blind detection performance of STBC over the correlated channels.
20175348
Optimized NURBS Curve and Surface Fitting Using Simulated Annealing