Comparative Analysis of Objective Distortion Measures for Speech Signals Degraded by Noise

Speech signals degraded by additive noise can affects different applications in telecommunication. The noise may degrades the intelligibility of the speech signals and its waveforms as well. In some applications such as speech coding, both intelligibility and waveform quality are important but only intelligibility has been focused lastly. So, modern speech quality measurement techniques such as PESQ (Perceptual Evaluation of Speech Quality) have been used and classical distortion measurement techniques such as Cepstral Distance are becoming unused. In this paper it is shown that some classical distortion measures are still important in applications where speech corrupted by additive noise has to be evaluated.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem

This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.

An objective reconstruction of the chain of contagion

North's clustering method, which is based on a much used ecological model, the nearest neighbor distance, was applied to the objective reconstruction of the chain of household-to-household transmission of variola minor (the mild form of smallpox). The discrete within-household outbreaks were considered as points which were ordered in a time sequence using a 10-40 day interval between introduction of the disease into a source household and a receptor household. The closer points in the plane were assumed to have a larger probability of being links of a chain of household-to-household spread of the disease. The five defining distances (Manhattan or city-block distance between presumptive source and receptor dwellings) were 100, 200, 300, 400 and 500 m. The subchain sets obtained with the five defining distances were compared with the subchains empirically reconstructed during the field study of the epidemic through direct investigation of personal contacts of the introductory cases with either introductory or subsequent cases from previously affected households. The criteria of fit of theoretical to empirical clusters were: (a) the number of clustered dwellings and subchains, (b) number of dwellings in a subchain and (c) position of dwellings in a subchain. The defining distance closet to the empirical findings was 200 m, which fully agrees with the travelling habits of the study population. Less close but acceptable approximations were obtained with 100, 300, 400 and 500 m. The latter two distances gave identical results, as if a clustering ceiling had been reached. It seems that North's clustering model may be used for an objective reconstruction of the chain of contagious whose links are discrete within-household outbreaks. © 1984.

Distributed generation impact evaluation using a multi-objective tabu search

Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the Distributed Generation penetration in passive networks considering different operation scenarios. Studying DG optimal siting and sizing the planner can identify the network behavior in presence of DG. Many approaches for the optimal DG allocation problem successfully used multi-objective optimization techniques. So this paper contributes to the fundamental stage of multi-objective optimization of finding the Pareto optimal solutions set. It is proposed the application of a Multi-objective Tabu Search and it was verified a better performance comparing to the NSGA-II method. © 2009 IEEE.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.

A multi-objective evaluation of the impact of the penetration of Distributed Generation

This paper proposes a methodology to consider the effects of the integration of DG on planning. Since DG has potential to defer investments in networks, the impact of DG on grid capacity is evaluated. A multi-objective optimization tool based on the meta-heuristic MEPSO is used, supporting an alternative approach to exploiting the Pareto front features. Tests were performed in distinct conditions with two well-known distribution networks: IEEE-34 and IEEE-123. The results combined minimization and maximization in order to produce different Pareto fronts and determine the extent of the impact caused by DG. The analysis provides useful information, such as the identification of futures that should be considered in planning. A future means a set of realizations of all uncertainties. MEPSO also presented a satisfactory performance in obtaining the Pareto fronts. © 2011 IEEE.

Post-processing association rules with clustering and objective measures

The post-processing of association rules is a difficult task, since a large number of patterns can be obtained. Many approaches have been developed to overcome this problem, as objective measures and clustering, which are respectively used to: (i) highlight the potentially interesting knowledge in domain; (ii) structure the domain, organizing the rules in groups that contain, somehow, similar knowledge. However, objective measures don't reduce nor organize the collection of rules, making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, making the search for relevant knowledge not so easy. This work proposes the PAR-COM (Post-processing Association Rules with Clustering and Objective Measures) methodology that, combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. Thereby, PAR-COM minimizes the user's effort during the post-processing process.

A bi-objective genetic approach for the selection of sugarcane varieties to comply with environmental and economic requirements

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Double-objective economic statistical design of the VP T-2 control chart: Wald's identity approach

Research has shown that applying the T-2 control chart by using a variable parameters (VP) scheme yields rapid detection of out-of-control states. In this paper, the problem of economic statistical design of the VP T-2 control chart is considered as a double-objective minimization problem with the statistical objective being the adjusted average time to signal and the economic objective being expected cost per hour. We then find the Pareto-optimal designs in which the two objectives are met simultaneously by using a multi-objective genetic algorithm. Through an illustrative example, we show that relatively large benefits can be achieved by applying the VP scheme when compared with usual schemes, and in addition, the multi-objective approach provides the user with designs that are flexible and adaptive.

Objective CT-Based Quantification of Lung Sequelae in Treated Patients With Paracoccidioidomycosis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Improvements in the sensibility of MSA-GA tool using COFFEE objective function

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Implementing the Objective Structured Clinical Examination in a Geriatrics Fellowship Program-A 3-Year Experience

The Objective Structured Clinical Examination (OSCE) appears to be an effective alternative for assessing not only medical knowledge, but also clinical skills, including effective communication and physical examination skills. The purpose of the current study was to implement an OSCE model in a geriatrics fellowship program and to compare the instrument with traditional essay examination. Seventy first- and second-year geriatric fellows were initially submitted to a traditional essay examination and scored from 0 to 10 by a faculty member. The same fellows subsequently underwent an OSCE with eight 10-minute stations covering a wide range of essential aspects of geriatric knowledge. Each OSCE station had an examiner responsible for its evaluation according to a predefined checklist. Checklist items were classified for analysis purposes as clinical knowledge items (CKI) and communication skills items (CSI); fellow responses were scored from 0 to 10.Although essay examinations took from 30 to 45 minutes to complete, 180200 minutes were required to evaluate fellows using the proposed OSCE method. Fellows scored an average of 6.2 +/- 1.2 on the traditional essay examination and 6.6 +/- 1.0 on the OSCE (P < .001). Subanalyses of OSCE scores indicated that average performance on CKI was lower than the average on CSI (6.4 +/- 1.1 vs. 8.4 +/- 1.1; P < .001). Fellow performance on the essay examination was similar to their performance on CKI (P = .13). Second-year fellows performed better than first-year fellows on the essay examination (P < .001) and CKI (P = .05), but not on CSI (P = .25).The OSCE was successfully implemented as an educational strategy during a geriatrics fellowship program. Combining different testing modalities may provide the best assessment of competence for various domains of knowledge, skills, and behavior.

Video Quality Assessments on Digital TV and Video Streaming Services Using Objective Metrics

There is a wide range of telecommunications services that transmit voice, video and data through complex transmission networks and in some cases, the service has not an acceptable quality level for the end user. In this sense the study of methods for assessing video quality and voice have a very important role. This paper presents a classification scheme, based on different criteria, of the methods and metrics that are being studied in recent years. This paper presents how the video quality is affected by degradation in the transmission channel in two kinds of services: Digital TV (ISDB-TB) due the fading in the air interface and video streaming service on an IP network due packet loss. For Digital TV tests was set up a scenario where the digital TV transmitter is connected to an RF channel emulator, where are inserted different fading models and at the end, the videos are saved in a mobile device. The tests of streaming video were performed in an isolated scenario of IP network, which are scheduled several network conditions, resulting in different qualities of video reception. The video quality assessment is performed using objective assessment methods: PSNR, SSIM and VQM. The results show how the losses in the transmission channel affects the quality of end-user experience on both services studied.

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.