Robustness Considerations Research Articles

Estimating Number of Speakers via Density-Based Clustering and Classification Decision

It is crucial to robustly estimate the number of speakers (NoS) from the recorded audio mixtures in a reverberant environment. Some popular time-frequency (TF) methods approach this NoS estimation problem by assuming that only one of the speech components is active at each TF slot. However, this condition is violated in many scenarios where the speeches are convolved with long length of room impulse response coefficients, which causes degenerated performance of NoS estimation. To tackle this problem, a density-based clustering strategy is proposed to estimate NoS based on a local dominance assumption of speeches. Our method consists of several steps from clustering to classification of speakers with the consideration of robustness. First, the leading eigenvectors are extracted from the local covariance matrices of mixture TF components and ranked by the combination of local density and minimum distance to other leading eigenvectors with higher density. Second, a gap-based method is employed to determine the cluster centers from the ranked leading eigenvectors at each frequency bin. Third, a criterion based on averaged volume of cluster centers is proposed to select reliable clustering results at some frequency bins for the classification decision of NoS. The experiment results demonstrate that the proposed algorithm is superior to the existing methods in various reverberation cases with noise-free condition or noise condition.

Autonomic Handover Management for Heterogeneous Networks in a Future Internet Context: A Survey

Future Internet (FI) scenarios envisage ubiquitous broadband coverage and seamless mobility, enabling the availability of personalized network connectivity at all places and with a high quality of service (QoS). In such a heterogeneous and complex environment, vertical handover (VHO) management is key for achieving the connectivity objectives, but also presents several challenges. In surveying this topic, this paper takes a direction that extends the state-of-the-art: By incorporating concepts of autonomic network management (ANM), in particular the self-management and cognitive functionalities therein, to VHO management, this paper sheds new light to VHO operations from an ANM point of view, encompassing FI environments and the emerging fifth generation networks. In doing so, the survey identifies the main concepts and provides a taxonomy of relevant architectural components. Based on this taxonomy, a number of important autonomic features are identified, each one promoting the system’s self-optimization along a certain direction toward the overall enhancement of the VHO operations. Another contribution of this paper is the consideration of robustness in VHO decision making (i.e., achieving stable decisions under uncertainty) and a discussion of the relation between robustness factors and the autonomic features previously introduced. The general concepts developed in this paper are applied to representative state-of-the-art handover management solutions with autonomic characteristics. These specific solutions are presented, analyzed, and correlated according to the proposed taxonomy and criteria, culminating to conclusions that provide useful insights toward future, further enhanced solutions.

Optimization of an Intelligent Community Hybrid Energy System With Robustness Consideration

An intelligent community hybrid energy system (ICHES) includes renewable energy power generation equipment, distributed controllable generation equipment, energy storage systems, mobile agents, and large numbers of fixed loads. In recent years, many studies of hybrid energy systems have been considered from the perspective of cost. However, the pollution and robustness of the system cannot be ignored. To address these issues, this paper introduces the environmental impact ratio of power generation and power supply robustness into the model and proposes a novel intelligent community hybrid energy optimization model. The proposed model is a multi-objective optimization problem. To address this complex multi-objective optimization problem, a direction vector adjustment (DVA) mechanism is introduced into the multi-objective evolutionary algorithm based on decomposition (MOEA/D) using localized penalty-based boundary intersection (LPBI) (MOEA/D-LPBI). Then, an improved MOEA/D-LPBI-DVA is proposed. The experimental results show that our model is more reasonable and outperforms existing models. The solutions obtained allow the problem to have a better effect, thereby effectively optimizing the hybrid energy output and achieving the multi-objective optimization requirements of low cost, low pollution, and high robustness of the system power supply.

An MPC Approach to Transient Control of Liquid-Propellant Rocket Engines

Abstract The current context of launchers reusability requires the improvement of control algorithms for their liquid-propellant rocket engines. Their transient phases are generally still performed in open loop. In this paper, it is aimed at enhancing the control performance and robustness during the fully continuous phase of the start-up transient of a generic gas-generator cycle. The main control goals concern end-state tracking in terms of combustion-chamber pressure and chambers mixture ratios, as well as the verification of a set of hard operational constraints. A controller based on a nonlinear preprocessor and on linear MPC (Model-Predictive Control) has been synthesised, making use of nonlinear state-space models of the engine. The former generates the full-state reference to be tracked while the latter achieves the aforementioned goals with sufficient accuracy and verifying constraints for the required pressure levels. Robustness considerations are included in the MPC algorithm via an epigraph formulation of the minimax robust optimisation problem, where a finite set of perturbation scenarios is considered.

Scientific Expertise and Risk Aggregation

When scientists are asked to give expert advice on risk-related questions, such as the authorization of medical drugs, deliberation often does not eliminate all disagreements. I propose to model these remaining discrepancies as differences in risk assessments and/or in risk acceptability thresholds. The normative question I consider, then, is how the individual expert views should best be aggregated. I discuss what “best” could mean, with an eye to some robustness considerations. I argue that the majority rule, which is currently often used in expert panels, has significant drawbacks.

Board Rooms and Jail Cells- Assessing NGO Approaches to Private Environmental Governance

Staff of the Nature Conservancy often find themselves in corporate board rooms. Staff of Greenpeace often find themselves in jail cells. The Nature Conservancy (TNC) prides itself on its non-confrontational, collaborative deal making, partnering closely with corporations like chemical giant Dow and agricultural lightning rod Monsanto. Both Dow and Monsanto, in fact, are members of TNC’s Business Council along with the likes of BP, Shell, and Cargill. Greenpeace, on the other hand, prides itself on direct action, civil disobedience, and non-violent confrontation. Greenpeace has launched combative operations against Dow, Monsanto, and other TNC collaborators. While business partners praise TNC’s cooperative efforts, they resist Greenpeace’s strategies, which have been the subject of recent litigation accusing Greenpeace of, among other things, racketeering, conspiracy, and defamation. Given the stark differences in personality and reputation, when it comes to environmental protection instrument choice it is startling to realize that Greenpeace and TNC are nearly indistinguishable. Both TNC and Greenpeace are, fundamentally, proponents of Private Environmental Governance. Private Environmental Governance is the striving for public goals through private endeavor. Through private land conservation and corporate collaborations, TNC is squarely engaged in private environmental governance. Though less obviously so, through public pressure on private companies, reputational campaigns, and consumer persuasion, Greenpeace too seeks to change the market and the behavior of private companies to achieve environmental goals without government involvement. The literature on Private Environmental Governance has been explicit that non-governmental organizations (NGOs) like TNC and Greenpeace have an important role to play, but there is little depth to this assertion. This article will add depth, by examining the efforts of NGOs in environmental instrument selection and implementation. This article offers a novel typology of environmental NGOs based on four categories: (1) Overarching Goal; (2) Governance Philosophy; (3) Advocacy Targets; and (4) Key Tactics. The article then overlays these categories on a diverse range of environmental groups. Critics often toss environmental NGOs into the single basket of Big Green. But this closer examination shows some important distinctions, including significant differences in the way these groups approach Private Environmental Governance. Across the legal literature there is a dearth of research on how advocacy organizations select and influence environmental protection instruments in the public and private spheres. Private Environmental Governance, with its principle focus on private actors rather than government entities, has recognized the importance of this inquiry, and this article opens the doors for a more searching and robust consideration of the role of NGOs in influencing public and private environmental policy.

The robust machine availability problem – bin packing under uncertainty

We define and solve the robust machine availability problem in a parallel machine environment, which aims to minimize the number of identical machines required while completing all the jobs before a given deadline. The deterministic version of this problem essentially coincides with the bin packing problem. Our formulation preserves a user-defined robustness level regarding possible deviations in the job durations. For better computational performance, a branch-and-price procedure is proposed based on a set covering reformulation. We use zero-suppressed binary decision diagrams for solving the pricing problem, which enable us to manage the difficulty entailed by the robustness considerations as well as by extra constraints imposed by branching decisions. Computational results are reported that show the effectiveness of a pricing solver with zero-suppressed binary decision diagrams compared with a mixed integer programming solver.

Ensemble Decision for Spam Detection Using Term Space Partition Approach.

This paper proposes an ensemble decision approach which combines global and local features of e-mails together to detect spam effectively. In the proposed method, a special feature construction method named term space partition (TSP) is utilized to divide the whole term space into several subspaces and adopt different feature construction strategies on each of them, respectively. This method can make each term play a distinct and important role when conducting detection. This method is utilized and extended by introducing the sliding window technique to extract local features from e-mails. The global classifier and local classifiers are constructed on a global feature vector set and local feature vector sets, respectively, and together make the ensemble decision by adopting the voting technique. The principles of the TSP-based approach and mechanism of the ensemble decision method are presented in detail. Five different and standard benchmark corpora are applied to experiments for performance evaluation of this proposed method. Comprehensive experimental results show that the proposed method brings significant performance improvement and better robustness on the basis of the TSP-based approach. In addition, the proposed method outperforms the current prevalent and state-of-the-art approaches, especially when a comprehensive consideration of performance, efficiency, and robustness is taken. This endows it with flexible capability and adaptivity in the real-world applications.

Three steps forward for predictability. Consideration of methodological robustness, indexical and prosodic factors, and replication in the laboratory

Abstract There is now abundant evidence that phonetic forms are shaped by probabilistic effects reflecting predictability or informativity. We outline a number of challenges for such work, where theoretical claims are often based on small differences in acoustic measurements, or interpretations of small statistical effect sizes. We outline caveats about the methods and assumptions encountered in many studies of predictability effects, particularly regarding corpus-based approaches. We consider the wide range of factors that influence patterns of variability in phonetic forms, taking a broad perspective on what is meant by “the message” in order to show that predictability effects need to be considered alongside many others, including indexical and prosodic factors. We suggest a number of ways forward to extend our understanding of the form-predictability relationship.

Development and evaluation of the organic chemistry‐specific achievement emotions questionnaire (AEQ‐OCHEM)

AbstractAffect is associated with success and persistence in STEM courses and degree programs. Measurement tools that produce valid and reliable data are essential to capturing the impact of evidenced‐based instructional practices and reformed curricula on learning. We report the development of the Achievement Emotions Questionnaire for use in postsecondary organic chemistry courses (AEQ‐OCHEM). Instrument development was based on the control‐value theory of achievement emotions and included a revision of the seminal Achievement Emotions Questionnaire (AEQ) used to measure institutional‐level learning. A thorough psychometric evaluation of the AEQ‐OCHEM was conducted including alternative measurement models and an extensive investigation of the nomological framework. All AEQ‐OCHEM subscales were determined to be coherent and distinct. Implications for future research using the AEQ‐OCHEM are offered. A call for the development of more discipline‐ and course‐based instruments is made. Finally, tools that measure achievement emotions in the context of instructional laboratories and undergraduate research are needed for more robust considerations of affect in STEM contexts.

Design of a 7-MeV APF DTL with robust considerations

A design principle with robust considerations has been applied to design a new alternating phase focused (APF) drift tube linear accelerator (linac) for particle beam therapy. By assuming a sinusoidal synchronous phase formula and a linearly increasing electrode voltage scheme, the structure of the APF linac is automatically optimized with a cost function including robustness using the nonlinear correlated stacking optimization method (CSM). The design procedure includes the radio frequency quadrupole (RFQ) to drift tube linac (DTL) matching, and an end-to-end simulation of the APF acceleration beam dynamics. Moreover, the stability of the solution obtained is analyzed with respect to various independent errors as well as a number of joint errors. The designed APF DTL linac together with an already established RFQ is planned to replace the existing Alvarez-type permanent magnet focused DTL linac aiming at easier manufacturing and cost reduction.

Carbon pathways in the global gas market: An attributional lifecycle assessment of the climate impacts of liquefied natural gas exports from the United States to Asia

While the United States is poised to become a major exporter of liquefied natural gas (LNG), relatively little attention has been paid to greenhouse gas emission impacts from exporting US natural gas to Asia, a key likely destination. Using bounding scenarios of attributional lifecycle analysis, this study finds that the climate impacts of United States exports to China, Japan, India, or South Korea could vary significantly, with annual global lifecycle emissions ranging from −88,000 metric tons CO2e to + 170,000 metric tons CO2e per Bcf of exports. Exact emissions will depend on factors such as (a) the final end-use of the LNG, (b) domestic market impacts from increased natural gas prices in the United States, (c) induced additional energy consumption in importing countries, and (d) methane leakage rates. Country specific greenhouse gas outcomes can differ from global outcomes, with major implications for extraction and consumption based emissions accounting. The study's results indicate the need for more robust consideration of the climate impacts of all energy exports in terms of country specific energy analyses, global climate regulations, and market uncertainty. Thus, how gas is governed becomes of critical importance, for it will determine whether LNG is a net sink or source of additional emissions.

New Hanger Design Approach of Tied-Arch Bridge to Enhance Its Robustness

As the crucial components among the tied-arch bridge, the local failure of hangers may trigger a progressive collapse through the entire tied-arch bridge. However, the current design guidance as regards hangers still lacks consideration of structure robustness under an extreme hazard. To improve the structural robustness of tied-arch bridge under extreme conditions, a new hanger design method is proposed, which is termed as asymmetric parallel double-hanger system. Based on Miner’s linear cumulative damage law, an analysis on the fatigue life of the double-hanger system was conducted to verify the feasibility of the proposal, and then a dynamic time-history analysis was employed to simulate the transitory fracture impact due to one or more hangers fracturing. According to the simulation results, the structural robustness is greatly enhanced with asymmetric parallel-double hanger system design, when compared with single hanger system design. When one or more hangers reveal local damage, it will not trigger a progress failure to the whole structure in particular. Several practical suggestions of bridge system’s load-carrying capacity are also put forward for the future arch bridge design at the end of this paper.

Stock-Bond Return Dynamic Correlation and Macroeconomic Announcements: Time-Scale Analysis and the Effects of Financial Crises

We use wavelet analysis to examine the impact of macro-news announcements on the stock-bond correlation. Significant announcement effects appear after controlling for the recent financial crisis, with a link between the speed of reaction and the timing of announcements, with early released news exhibiting a slower effect. The news effects differ when we replace the 2008 crisis with the 2001 dot-com or 2011 government debt ceiling dispute periods. Tests involving small stocks, different model specifications, volatility effects and other robustness considerations continue to support our results. These results will enhance our understanding of the links between financial markets and the macroeconomy.

Including robustness considerations in the search phase of Many-Objective Robust Decision Making

Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. MORDM has four phases: a systems analytical problem formulation, a search phase to generate candidate solutions, a trade-off analysis where different strategies are compared across many objectives, and a scenario discovery phase to identify the vulnerabilities. In its original inception, the search phase identifies optimal strategies for a single reference scenario for deep uncertainties, which may result in missing locally near-optimal, but globally more robust strategies. Recent work has addressed this issue by generating candidate strategies for multiple policy-relevant scenarios. In this paper, we incorporate a systematic scenario selection procedure in the search phase to consider both policy relevance and scenario diversity. The results demonstrate an increased tradeoff variety besides higher robustness, compared to the solutions found for a reference scenario. Future research can routinize multi-scenario search in MORDM with the aid of software packages.

Wind leading to improve cooling performance of natural draft air-cooled condenser

Natural draft air-cooled condenser (NDACC) has been adopted in chemical and power plants owing to its superior energy-efficient operation to the traditional fan-driven air-cooled condenser. However, the cooling capability of NDACC is generally impaired by ambient winds, which incur the unbalanced airflow distributions through the condenser cells. So, the wind flow fields are organized in this research to restrain the adverse wind effects. By numerical simulations, five types of windbreakers are studied and compared with the no-windbreaker case. The air velocity, pressure and temperature distributions, and the specific air flow rates of condenser cells as well as heat rejections of cooling sectors are analyzed. Furthermore, the three-dimensional path lines are additionally presented to highlight the leading effects of windbreakers, airflow inside the tower, and flow discharge at the tower outlet. The results show that, appropriate windbreaker configurations can effectively improve the cooling performance of NDACC, especially at high wind speeds, while the windbreaker arrangement inside the condenser cells plays a negligible role in the overall cooling performance. Besides, the cases with 12 and 48 exterior windbreak walls achieve almost the same best performances. In consideration of the system robustness and economy, the case with 48 exterior windbreakers can be recommended in the future engineering application.

Atmospheric teleconnection influence on North American land surface phenology

Short-term forecasts of vegetation activity are currently not well constrained due largely to our lack of understanding of coupled climate-vegetation dynamics mediated by complex interactions between atmospheric teleconnection patterns. Using ecoregion-scale estimates of North American vegetation activity inferred from remote sensing (1982–2015), we examined seasonal and spatial relationships between land surface phenology and the atmospheric components of five teleconnection patterns over the tropical Pacific, north Pacific, and north Atlantic. Using a set of regression experiments, we also tested for interactions among these teleconnection patterns and assessed predictability of vegetation activity solely based on knowledge of atmospheric teleconnection indices. Autumn-to-winter composites of the Southern Oscillation Index (SOI) were strongly correlated with start of growing season timing, especially in the Pacific Northwest. The two leading modes of north Pacific variability (the Pacific-North American, PNA, and West Pacific patterns) were significantly correlated with start of growing season timing across much of southern Canada and the upper Great Lakes. Regression models based on these Pacific teleconnections were skillful predictors of spring phenology across an east-west swath of temperate and boreal North America, between 40°N–60°N. While the North Atlantic Oscillation (NAO) was not strongly correlated with start of growing season timing on its own, we found compelling evidence of widespread NAO-SOI and NAO-PNA interaction effects. These results suggest that knowledge of atmospheric conditions over the Pacific and Atlantic Oceans increases the predictability of North American spring phenology. A more robust consideration of the complexity of the atmospheric circulation system, including interactions across multiple ocean basins, is an important step towards accurate forecasts of vegetation activity.

Design of cladding rods-assisted depressed-core few-mode fibers with improved modal spacing

Abstract This paper investigates the design details of cladding rods-assisted (CRA) depressed-core (DC) few-mode fibers (FMFs) that feature more equally spaced linearly polarized (LP) modal effective indices, suitable for high-spatial-density weakly-coupled mode-division multiplexing systems. The influences of the index profile of cladding rods on LP mode-resolved effective index, bending sensitivity, and effective area Aeff, are numerically described. Based on the design considerations of LP modal Aeff-dependent spatial efficiency and LP modal bending loss-dependent robustness, the small LP21-LP02 and LP22-LP03 modal spacing limitations, encountered in state-of-the-art weakly-coupled step-index FMFs, have been substantially improved by at least 25%. In addition, the proposed CRA DC FMFs also show sufficiently large effective areas (in excess of 110 μm2) for all guided LP modes, which are expected to exhibit good nonlinear performance.

Robust transmitter–receiver design for extended target in signal-dependent interference

This paper focuses on the robust transmitter–receiver design to improve the detectability of an extended target embedded in signal-dependent interference. Specifically, we allow uncertainties for both the interference and target impulse responses. An iterative algorithm is proposed to sequentially improve the worst-case Signal-to-Interference-plus-Noise Ratio (SINR) under the constant modulus constraint. Each iteration involves two max-min problems, which can be efficiently solved by generalized eigenvalue decomposition and the Dinkelbach’s procedure, respectively, to obtain the optimized receive filter vector and unimodular transmit sequence. The effectiveness of the proposed method is confirmed numerically in terms of the optimized SINR. We also highlight the improvements of the worst-case SINR compared to nominal designs without robustness considerations.

A Periodic Observers Synthesis Approach for LDP Systems Based on Iteration

The problem of state observer design for the linear discrete-time periodic (LDP) system and its robust consideration are discussed in this paper. Applying the lifting technique and algebraic operations based on the well-known CG-algorithm, an iterative algorithm for periodic observer gain can be generated. By optimizing the free parameter matrix in the proposed algorithm, an algorithm on the minimum norm and robust observer design for the LDP systems is presented. One numerical example is worked out to illustrate the effect of the proposed approaches.