Common Constraints Research Articles

Reliable Memory Sampled-Data Consensus of Multi-Agent Systems With Nonlinear Actuator Faults

This brief proposes a memory-based sampled-data consensus framework for general linear multi-agent systems (MAS) in the presence of a class of nonlinear actuator faults (NAF). To reduce state exchanges and preserve energy resources, communication between the neighboring agents are based on only samples of the states with variable sampling intervals. As two common constraints in the actuators, the bounded nonlinear partial loss of effectiveness and bias faults are both taken into account in the problem formulation. Sufficient conditions to guarantee consensus under the given circumstances are derived as linear matrix inequality (LMI) conditions. Different from existing Lyapunov-Krasovskii-based methods, the proposed design framework in this brief is based on a looped functional approach which reduces the conservation in designing the required consensus control gains. This less conservative approach allows a larger sampling interval as well as more severe actuator faults which together enhance the practicability of the proposed approach. Simulation results based on a tunnel diode circuit and a non-holonomic mobile robot MASs quantify the effectiveness of the proposed approach and the improved sampling intervals.

Software-Supported Audits of Decision-Making Systems: Testing Google and Facebook's Political Advertising Policies

How can society understand and hold accountable complex human and algorithmic decision-making systems whose systematic errors are opaque to the public? These systems routinely make decisions on individual rights and well-being, and on protecting society and the democratic process. Practical and statistical constraints on external audits--such as dimensional complexity--can lead researchers and regulators to miss important sources of error in these complex decision-making systems. In this paper, we design and implement a software-supported approach to audit studies that auto-generates audit materials and coordinates volunteer activity. We implemented this software in the case of political advertising policies enacted by Facebook and Google during the 2018 U.S. election. Guided by this software, a team of volunteers posted 477 auto-generated ads and analyzed the companies' actions, finding systematic errors in how companies enforced policies. We find that software can overcome some common constraints of audit studies, within limitations related to sample size and volunteer capacity.

Middle Leaders Addressing Concerns with Teaching Performance in New Zealand Secondary Schools

ABSTRACT Little is known about how middle leaders address concerns with teaching performance. This study used a problem-based methodology and critical incident interviewing to elicit eight middle leaders’ theories-in-use for 14 cases of concern. Our systematic analysis examined the beliefs constraining their actions, their actions as well as the resulting consequences. Our findings indicate common constraints across leaders including protecting relationships, accountabilities, their leadership approach and knowledge, and time. Concerns were rarely disclosed, subsequent actions were usually indirect, and little change in teaching practice resulted. The findings indicate the need for specific training and support for middle leaders in handling teacher-performance concerns.

Image stitching by disparity-guided multi-plane alignment

Image stitching aims to warp and align two or more images with overlapping areas to generate a panorama with a larger field of view. Due to the wide baseline or the abrupt depth changes caused by the foreground objects, the phenomenon that adjacent pixels or regions in one image are not adjacent in another image happens. It is difficult to avoid severe parallax artifacts and get good alignment results when stitching such images. In this paper, focusing on the images with large parallax, we design a multi-plane alignment algorithm guided by the disparity map. The concept of average tolerable parallax is proposed to help distinguish one background plane and multiple foreground objects from the image, which are robust to small parallax. In order to obtain the reliable disparity map of the image pairs got from any camera with unknown camera parameters, we propose an optimal homography estimation method based on the relative projection biases. This helps to satisfy the common epipolar line constraint when applying stereo matching modules. Experimental results demonstrate that our algorithm provides accurate stitching results on images with large parallax, and outperforms other existing state-of-the-art methods both qualitatively and quantitatively.

How to approach the resilience of livestock exposed to environmental challenges? Quantification of individual response and recovery by means of differential calculus

This work was originated from the need to study how animals individually react to environmental challenges. Common practical constraints in research protocols often lead to data collected at frequencies that are not high enough to capture the dynamics of animal responses. One approach to deal with that issue is to transform discrete empirical time series into continuous functions from which several descriptors can be extracted to characterise the response. A method for the extraction of smoothed functions from milk yield (MY) time series has been published before for dairy cows. This method was applied to detect challenges a posteriori. In this paper, we present an adaptation of this differential smoothing methodology, for the case when the environmental challenge is known a priori. This is advantageous because it allows for a more detailed characterisation of the response. Full description of the methodology is presented, where operations from differential calculus are applied to the smoothed functions to extract 23 descriptors that characterise the shape, dynamics and delay of individual responses to a single known challenge. We present examples of the application of the algorithm to individual time series of MY and plasma non-esterified fatty acid concentrations from suckling cows exposed to nutritional challenges that are known a priori. We propose a selection strategy for the smoothing coefficient (λ) based on the optimisation between noise reduction and output stability. If applied to groups of individuals that are sufficiently large, this methodology could provide information to help discriminating animals based on how they respond to the environmental challenges. This methodology may be used to develop decision-making tools for the selection of resilient individuals aiming at improving robustness and performance.

Artificial Intelligent Technologies for the Construction Industry: How Are They Perceived and Utilized in Australia?

Artificial intelligence (AI) is a powerful technology that can be utilized throughout a construction project lifecycle. Transition to incorporate AI technologies in the construction industry has been delayed due to the lack of know-how and research. There is also a knowledge gap regarding how the public perceives AI technologies, their areas of application, prospects, and constraints in the construction industry. This study aims to explore AI technology adoption prospects and constraints in the Australian construction industry by analyzing social media data. This study adopted social media analytics, along with sentiment and content analyses of Twitter messages (n = 7906), as the methodological approach. The results revealed that: (a) robotics, internet-of-things, and machine learning are the most popular AI technologies in Australia; (b) Australian public sentiments toward AI are mostly positive, whilst some negative perceptions exist; (c) there are distinctive views on the opportunities and constraints of AI among the Australian states/territories; (d) timesaving, innovation, and digitalization are the most common AI prospects; and (e) project risk, security of data, and lack of capabilities are the most common AI constraints. This study is the first to explore AI technology adoption prospects and constraints in the Australian construction industry by analyzing social media data. The findings inform the construction industry on public perceptions and prospects and constraints of AI adoption. In addition, it advocates the search for finding the most efficient means to utilize AI technologies. The study helps public perceptions and prospects and constraints of AI adoption to be factored in construction industry technology adoption.

Finite–State Source–Channel Coding for Individual Source Sequences With Source Side Information at the Decoder

We study the following semi–deterministic setting of the joint source–channel coding problem: a deterministic source sequence (a.k.a. individual sequence) is transmitted via a memoryless channel, using delay-limited encoder and decoder, which are both implementable by periodically–varying finite-state machines, and the decoder is granted with access to side information, which is a noisy version of the source sequence. We first derive a lower bound on the achievable expected distortion in terms of the empirical statistics of the source sequence, the number of states of the encoder, the number of states of the decoder, their period, and the overall delay. The bound is shown to be asymptotically achievable by universal block codes in the limit of long blocks. We also derive a lower bound to the best achievable excess–distortion probability and discuss situations where it is achievable. Here, of course, source coding and channel coding cannot be completely separated without loss of optimality. Finally, we outline a few extensions of the model considered, such as: (i) incorporating a common reconstruction constraint, (ii) availability of side information at both ends, and (iii) extension to the Shannon channel with causal state information at the encoder. This work both extends and improves on earlier work of the same flavor (Ziv 1980, Merhav 2014), which focused only on the expected distortion, without side information at either end, and without the above mentioned additional ingredients.

Structural Variability Shows Power-Law Based Organization of Vowel Systems.

Speech sounds are an essential vehicle of information exchange and meaning expression in approximately 7,000 spoken languages in the world. What functional constraints and evolutionary mechanisms lie behind linguistic diversity of sound systems is under ongoing debate; in particular, it remains conflicting whether there exists any universal relationship between these constraints despite of diverse sounds systems cross-linguistically. Here, we conducted cross-linguistic typological and phylogenetic analyses to address the characteristics of constraints on linguistic diversity of vowel systems. First, the typological analysis revealed a power-law based dependence between the global structural dispersion and the local focalization of vowel systems and validated that such dependence was independent of geographic region, language family, and linguistic affiliation. Second, the phylogenetic analysis further illustrated that the observed dependence resulted from correlated evolutions of these two structural properties, which proceeded in an adaptive process. These results provide empirical evidence that self-organization mechanisms helped shape vowel systems and common functional constraints took effect on the evolution of vowel systems in the world’s languages.

GITEC: A Generalized Inversion Technique Benchmark

ABSTRACT Generalized inversion techniques (GITs) have become popular for determining seismological parameters (e.g., source, attenuation, and site response), particularly in low-to-moderate seismicity regions. Indeed, GITs can potentially provide reliable site-response estimates when a minimum number of recordings is available, as well as valuable information about source parameters and regional attenuation characteristics. Significant advances have been made on GITs in which different approaches and hypotheses were investigated, such as the application of “nonparametric” and “parametric” inversion schemes. In this context, several scientific questions have arisen that depend on the final scope of the GITs: What is the optimal inversion strategy for a given dataset configuration? What is the impact of the different choices, assumptions, and implementations on the reliability of the results? Is it possible to quantify the associated epistemic uncertainties? Here, we have considered and compared the different approaches of GITs to improve the understanding of each for use in different applications. A methodological benchmark that includes different GIT methods and dataset configurations is set up to fulfill the objective, using a simple synthetic dataset, a French regional sparse dataset, and an Italian national dense dataset. The benchmark is developed in two phases: (1) phase I: a free phase with no common constraints; and (2) phase II: a constrained phase with unified reference conditions. Despite unifying the reference conditions in the different inversions, the variability was not reduced. Discrepancies are observed between different terms of GITs. Site responses appear to be the most robust estimates, compared to source and attenuation terms. The way that stress drops of earthquakes and quality factors for crustal attenuation are parameterized appears to lead to significant variability between different approaches. Finally, uncertainties are addressed by quantification of the inter-method variability for the different terms and parameters.

Tone-driven epenthesis in Wamey

AbstractThis paper argues that tone-driven epenthesis is possible in tonal languages. In Wamey, an epenthetic [ə] is inserted to host a high tone in two contexts: first, to host a tone which would otherwise be left floating due to a restriction on rising tones (/cv̀cⒽ/ maps to [cv̀cə́] due to a ban *[cv̌c]); and second, to host a tone which is introduced by word-level morphology but is restricted from associating across a stem boundary. These patterns cannot be attributed to syllable phonotactics, which freely allow all consonants in the coda position. We assemble the evidence for tone-driven epenthesis, focusing on the distribution of final [ə] in lexical stem structure and [ə]-alternating suffixes. A simple OT analysis derives [ə]-epenthesis, utilising common constraints (e.g. *Rise, OCP(H), etc.) together with constraints against associating tone across prosodic boundaries. In total, Wamey epenthesis exemplifies the cultivation of segmental environments for the purpose of realising pitch targets.

The “Connected” Caregivers: Exploring the Interplay of Left-Behind Women’s Socio-Structural Immobilities and Communicative Mobilities in Transnational Power Geometries

Abstract Drawing on an ethnographic study on different groups of left-behind women (mothers, aunts, and grandmothers) in Fuqing, a major transnational migrant-labor-sending area in China, this article examines how they collaborate with their overseas family members in childrearing through digital media use. Applying the “im/mobilities” framework, this study explains how different left-behind caregivers use mediated communication as communicative mobilities to negotiate family roles and relationships in situated transnational power geometry. Despite the common structural constraints (rural patriarchy and inadequate social resources), left-behind women’s socio-structural immobilities vary depending on their specific relationship with migrants (conjugal, kinship, and intergenerational dynamics), which embodies the asymmetrical nature of transnationalism. The findings highlight the dynamic negotiation between left-behind caregivers’ communicative mobilities and their contextualized socio-structural immobilities, which leads to diverse forms of agency and disempowerment. This article shows that communicative mobility is not only manifested as media use but also embodied as media (non)use. Lay Summary Transnational labor migration has allowed people in poor areas to improve their financial well-being, but has also caused separations among many families. Thanks to the prevalence of various digital media (e.g., instant messaging, webcam and voice calls, and social media platforms, etc.), fragmented family members are able to maintain and manage different family relationships despite geographic constraints. This study draws on three groups of female caregivers (mothers, aunts, and grandmothers) in Fuqing, a major transnational migrant-labor-sending area in China. I am particularly interested in how these left-behind women collaborate with migrant parents to fulfil their duties of raising left-behind children through digital media. The findings suggest that left-behind women’s life experiences are not only related to gender norms and inadequate social resources (e.g., a lack of job opportunities and robust social welfare system) in rural China, but also pertinent to their specific relationship with migrants (e.g., conjugal, kinship, and intergenerational dynamics). While female caregivers’ different situations influence their media practices during childrearing collaboration with migrant parents, such media engagement also contributes to the shaping of their transnational family relationships.

Affine term structure models: A time‐change approach with perfect fit to market curves

AbstractWe address the so‐called calibration problem, which consists of fitting in a tractable way a given model to a specified term structure such as yield, prepayment or default probability curves. Time‐homogeneous affine jump diffusions (HAJD) are tractable processes but have limited flexibility; they fail to perfectly replicate actual market curves. Applying a deterministic shift to the latter is a simple but efficient solution that is widely used by both academics and practitioners. However, the shift approach may not be appropriate when positivity is required, a common constraint when dealing with credit spreads or default intensities. In this paper, we address this problem by adopting a time‐change technique. Specific attention is paid to the Cox–Ingersoll–Ross model with compound Poisson jumps (JCIR), which remains standard for modeling intensities. Our time‐changed JCIR (TC‐JCIR) is compared to the shifted JCIR (JCIR++) in various credit applications such as credit default swap (CDS), credit default swaption, and credit valuation adjustment (CVA) under wrong‐way risk (WWR). The TC‐JCIR model is able to generate much larger implied volatilities and covariance effects than JCIR++ under positivity constraints and represents an appealing alternative to the latter.

Constraints in Adoption of Scientific Fish Farming in Nagaon District, Assam

The study is conducted at two randomly selected development blocks of Nagaon district, Assam viz. Rupahi and Kaliabor Block during 2019-2021 to find out the constraints faced by the farmers in adoption of scientific fish farming. A total of 50 farmers from each of the selected blocks were finally selected through simple random sampling. A structured questionnaire consisting of 20 questions was used to collect responses about scientific fish farming problems and related information specifically based on preliminary survey as well as focus group discussions and Constraint Index (CI) was calculated. Lack of quality fish seed of required size and number at the time of stock (CI 1.66) in both Kaliabor and Rupahi blocks were the most common constraint and poaching of fish (CI 0.05) was the least common constraint. It was also observed that most of the adopters in the studied area were within the age group of 18 to 30 years which calls for better entrepreneurship and employment generation.

Real-time Optimal Resource Allocation using Online Primal Decomposition*

Many industrial processes consist of several subsystems (i.e., clusters) that share common constraints. Typically, each subsystem strives for its objective by competing in obtaining the shared resource, e.g., electrical power, steam, and water. A distributed optimization can solve such a problem, however, it involves solving a numerical optimization problem online and is usually computationally extensive. One can utilize an online iteration of Dual decomposition (without a numerical solver) to solve such a problem. However, in this approach, the constraint is typically controlled on a slow time scale causing significant dynamic constraint violation in the transient, especially in active constraint region switching. In practice, a ”back-of” strategy is necessary, and it may lead to profit loss in the long run. To address this issue, we propose to utilize online Primal decomposition instead, where the problem turns into a feedback-based problem, and the constraint controller(s) distribute local setpoints without violating the common constraint. The simulation results show that the proposed approach can reach the ideal steady-state optimum.

Grain yield and lodging-related traits of ultrashort-duration varieties for direct-seeded and double-season rice in Central China

Lodging is the most common constraint on grain yield of direct-seeded rice. There is limited information about lodging resistance and its related plant traits in direct-seeded and double-season rice (DDR) in Central China. This study aims to identify the plant traits that achieve high lodging resistance in ultrashort-duration varieties (about 95 days) of DDR. Field experiments were conducted in 2017 and 2018 in Wuxue County, Hubei Province, China, with four ultrashort-duration varieties grown under two nitrogen (N) rates. Lodging-related traits were measured on the 15th day after heading, and yield and yield attributes were measured at maturity. The grain yield of the four varieties ranged from 4.59 to 7.61 t ha−1 across the two N rates, with a total growth duration of 85 to 97 days. Varietal differences in lodging index were mainly explained by the bending moment, which was closely related to plant height. Breaking resistance did not affect the lodging index significantly. Shortening plant height from 95.4 to 80.5 cm decreased the lodging index by 22.4% but did not reduce grain yield. Our results suggested that reducing plant height was effective in improving the lodging resistance of ultrashort-duration varieties of DDR. Lodging resistance should be enhanced by improving breaking resistance rather than reducing plant height to increase DDR grain yield further.

A review of multi-fault recovery for distribution networks under natural disasters

The distribution network is extremely vulnerable under the effect of extreme natural disasters because of broken towers (poles)and lines. This seriously endangered the safe and stable operation of the power system. With the large number of distributed generation (DG) connections, it poses a great challenge to repair and recover from faults in the distribution network. This paper first briefly analyses the emergency dispatch model of the distribution network, including common objective function and constraints. Then, the intelligent algorithm used to solve the distribution network repair dispatching model is summarized. Finally, the conclusion and prospect distribution network emergency repair dispatching problem including DG under natural disasters is analyzed.

SQP Methods for Mathematical Programs With Switching Constraints

The mathematical program with switching constraint (MPSC) problem makes a new-type optimization issue in recent years. Due to the existence of switching constraints, the common constraint specification is not satisfied, so that the convergence results of existing algorithms can not be directly applied to this problem. The sequential quadratic programming (SQP) method was applied to solve the problem, and to prove that the clustering point of the solution sequence of the subproblem is the Karush-Kuhn-Tucker point of the original problem under the linear independent constraint specification with the switching constraint. At the same time, in order to improve the relationship between stationary points, the equivalence between the strong stationary point and the KKT point was proved. Finally, the numerical results show that, the sequential quadratic programming method is feasible to deal with this type of problems.

Revealing mechanisms of infectious disease spread through empirical contact networks.

The spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling the dynamics of infectious disease spread through contact networks, however, can be challenging due to limited knowledge of how an infectious disease spreads and its transmission rate. We developed a novel statistical tool, INoDS (Identifying contact Networks of infectious Disease Spread) that estimates the transmission rate of an infectious disease outbreak, establishes epidemiological relevance of a contact network in explaining the observed pattern of infectious disease spread and enables model comparison between different contact network hypotheses. We show that our tool is robust to incomplete data and can be easily applied to datasets where infection timings of individuals are unknown. We tested the reliability of INoDS using simulation experiments of disease spread on a synthetic contact network and find that it is robust to incomplete data and is reliable under different settings of network dynamics and disease contagiousness compared with previous approaches. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumblebee colonies and Salmonella in wild Australian sleepy lizard populations. INoDS thus provides a novel and reliable statistical tool for identifying transmission pathways of infectious disease spread. In addition, application of INoDS extends to understanding the spread of novel or emerging infectious disease, an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.

Market Survey of Fresh and Marine Water Fishes and Socioeconomic Conditions of Fish Retailers in Three Markets of Chattagram City

The study was carried out to survey the fresh and marine water fishes sold out in three markets of Chattagram city and socioeconomic condition of the fish retailers. Overall 29 fresh water and 24 marine water fish species were found to be sold in the three markets. Prices of fishes were higher in Kazirdewri Bazar followed by Riazuddin Bazar and Bohaddarhat Bazar. Data of fish retailers were collected through questionnaires in terms of age, income source, living standards, family size, financial facilities, literacy and education. Sole income came from fish business for 97% of the fish retailers, whilst 3% of the retailers did other business as well. Among 45 retailers interviewed, 40% were below 45 years, 53% were between 45-55 years and remaining 7% were above 55 years age. For coping with the business, 15% of the retailers were self-sufficient, 53% took loan from bank, whilst 32% took loan from local money lenders. Of the fish retailers, 34% was illiterate and 66% was literate, where 36% received up to primary level, 16% secondary level, 10% S.S.C and 4% H.S.C levels of education. In comparison with their education status their children were more educated (93%). Although their income was low, they tried to make their children educated, which is a good sign for our education sector. Transport cost, unhygienic market place, lack of sanitary facilities, poor ice-supply, exploitation by the middlemen, lack of proper management, lack of capital and the political disturbances were the common constraints of fish marketing. Necessary measures were recommended to overcome these problems. Bangladesh J. Zool. 49 (2): 277-288, 2021

Spatial agents for geological surface modelling

Abstract. Increased availability and use of 3D-rendered geological models have provided society with predictive capabilities, supporting natural resource assessments, hazard awareness, and infrastructure development. The Geological Survey of Canada, along with other such institutions, has been trying to standardize and operationalize this modelling practice. Knowing what is in the subsurface, however, is not an easy exercise, especially when it is difficult or impossible to sample at greater depths. Existing approaches for creating 3D geological models involve developing surface components that represent spatial geological features, horizons, faults, and folds, and then assembling them into a framework model as context for downstream property modelling applications (e.g. geophysical inversions, thermo-mechanical simulations, and fracture density models). The current challenge is to develop geologically reasonable starting framework models from regions with sparser data when we have more complicated geology. This study explores the problem of geological data sparsity and presents a new approach that may be useful to open up the logjam in modelling the more challenging terrains using an agent-based approach. Semi-autonomous software entities called spatial agents can be programmed to perform spatial and property interrogation functions, estimations and construction operations for simple graphical objects, that may be usable in building 3D geological surfaces. These surfaces form the building blocks from which full geological and topological models are built and may be useful in sparse-data environments, where ancillary or a priori information is available. Critical in developing natural domain models is the use of gradient information. Increasing the density of spatial gradient information (fabric dips, fold plunges, and local or regional trends) from geologic feature orientations (planar and linear) is the key to more accurate geologic modelling and is core to the functions of spatial agents presented herein. This study, for the first time, examines the potential use of spatial agents to increase gradient constraints in the context of the Loop project (https://loop3d.github.io/, last access: 1 October 2021​​​​​​​) in which new complementary methods are being developed for modelling complex geology for regional applications. The spatial agent codes presented may act to densify and supplement gradient as well as on-contact control points used in LoopStructural (https://www.github.com/Loop3d/LoopStructural, last access: 1 October 2021) and Map2Loop (https://doi.org/10.5281/zenodo.4288476, de Rose et al., 2020). Spatial agents are used to represent common geological data constraints, such as interface locations and gradient geometry, and simple but topologically consistent triangulated meshes. Spatial agents can potentially be used to develop surfaces that conform to reasonable geological patterns of interest, provided that they are embedded with behaviours that are reflective of the knowledge of their geological environment. Initially, this would involve detecting simple geological constraints: locations, trajectories, and trends of geological interfaces. Local and global eigenvectors enable spatial continuity estimates, which can reflect geological trends, with rotational bias, using a quaternion implementation. Spatial interpolation of structural geology orientation data with spatial agents employs a range of simple nearest-neighbour to inverse-distance-weighted (IDW) and quaternion-based spherical linear rotation interpolation (SLERP) schemes. This simulation environment implemented in NetLogo 3D is potentially useful for complex-geology–sparse-data environments where extension, projection, and propagation functions are needed to create more realistic geological forms.