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Seabed minerals in form of ferromanganese or polymetallic nodules (PMN) have been reported in the Pacific, Atlantic, and Indian oceans. The distribution of these PMN are influenced by several factors, such as the associated topographic undulations, surface chlorophyll levels, sediment type and thickness, and water depth. Traditionally, determination of the existence and the distribution of PMN involves...
Autonomous swarm control, which is expected to be able to handle multiple unmanned vehicles (UxVs), is an important technology that can be applied to many operations and incorporated in many systems. For operations in real environments, we have to consider severe conditions under which communications between UxVs may be inadequate and the environment changes unexpectedly. In addition to optimality,...
We propose a swarm control algorithm for unmanned vehicles that adapts to unexpected environments while making the optimal formation. Our proposed algorithm, “autonomous and adaptive control”, is inspired by the control mechanism of living organisms and reconciles adaptability under a complex and changing environment and optimality for the various purposes of the system. In this paper, we apply the...
Modeling the spatial variation of resources is necessary because it gives an estimate of what to expect during their exploration and exploitation. We focus on the spatial modeling of polymetallic nodules found in the deep sea regions of the Clarion-Clipperton zone in the Pacific. The data from this region available in the open domain is sparse, which warrants modeling techniques that can efficiently...
In order to improve the maneuverability and safety of the air cushion vehicle (ACV), considering the internal uncertainties, external disturbances, chattering in sliding mode control, the second order nonsingular terminal sliding mode (SONTSM) controller with extended state observer (ESO) is designed to achieve the course control of ACV. The course controller includes two parts: second order nonsingular...
The paper deals with the issues of measurement traceability based on uncertainty of measurements as an integral part of specific measurement technologies based of new information system. A short review of papers devoted to measurement traceability problem in modern conditions is described. It is proposed to further expand a concept of "special technical means" in carrying out of measurements...
Estimating model parameters is a crucial step to understand the behavior of biological systems. To perform parameter estimation, a commonly used formulation is the least square method that minimizes the mean squared error. This method finds the model parameters that minimize the sum of the squared error between experimental data and model predictions. However, such a formulation can misguide parameter...
In the literature, a number of methods have been proposed for semi-supervised learning. Recently, graph-based methods of semi-supervised learning have become popular because of their capability of handling large amounts of unlabeled data. However, the existing graph based semi-supervised learning algorithms do not optimize the process of selecting better labeled data. We have developed a new selective...
Network centrality reflects node importance in networks, which is a challenging problem in social network analysis. Based on Fuzzy Set and MYCIN theory, this paper proposes a novel node centrality measuring method and models n-monkeys dataset, where n is 20. Initially, we created monkeys relationship graph and generated relationship matrix based on the monkeys' encountering times in a specific time...
Active learning aims to reduce manual labeling efforts by proactively selecting the most informative unlabeled instances to query. In real-world scenarios, it's often more practical to query a batch of instances rather than a single one at each iteration. To achieve this we need to keep not only the informativeness of the instances but also their diversity. Many heuristic methods have been proposed...
The present paper uses the learning ability of neural networks (NN) for nonlinear systems in order to design a controller for trajectory tracking problems in wheeled mobile robots that have their kinematic constraints violated. The singular perturbation approach is used to highlight the presence of uncertainties related to the violation of the kinematic constraints and propose an alternative global...
This paper investigates the generalized nonlinear resilient H∞ filter design problem for discrete-time systems with uncertain and nonlinear parameters. The uncertain parameters are assumed to have norm-bounded form and the nonlinear parameters are assumed to have Lipschitz form. We aim to design a generalized nonlinear resilient H∞ filter such that the stability and the H∞ performance of filtering...
The exploration of unknown environments is an important task for an autonomous robot. When exploring an unknown environment, robots face a common trade-off between visiting already mapped areas or exploring new areas. This can be done by using a planning stage in conjunction with the SLAM algorithm. This is normally called integrated exploration. In this paper, we propose a novel integrated exploration...
Geospatial Intelligence analysis involves the combination of multi-source information expressed in logical form (as sentences or statements), computational form (as numerical models of physics or other processes), and sensor data (as measurements from transducers). Each of these forms has its own way to describe uncertainty or error: e.g., frequency models, algorithmic truncation, floating point roundoff,...
We investigate methods to define a probabilistic logic and their application to multi-source fusion problems in geospatial decision support systems1. We begin with a discussion of augmenting propositional calculus with probabilities. Given a set of sentences, S, each with a known probability, the problem is to determine the probability of a query sentence that is a disjunction of literals appearing...
Over Several years, we observed that our students were sceptical of Software Engineering practices, because we did not convey the experience and demands of production quality software development. Assessment focused on features delivered, rather than imposing responsibility for longer term `technical debt'. Academics acting as 'uncertain' customers were rejected as malevolent and implausible. Student...
The correct functioning of data measuring systems is impossible without timely metrological examination and calibration of measuring channels. Uncalibrated channels can transmit unreliable data, leading to the poor monitoring and incorrect decision making. The overview of the current research in the field of measuring channels calibration shows the low research activity in this area and highlights...
Though accident data have been collected across industries, they may inherently contain uncertainty of randomness and fuzziness which in turn leads to misleading interpretation of the analysis. To handle the issue of uncertainty within accident data, the present work proposes a rough set theory (RST)-based approach to provide rule-based solution to the industry to minimize the number of accidents...
This paper presents a chance-constrained scheduling (CCS) approach for variable wind generation, in the day-ahead timescale, including energy storage. The day-ahead CCS utilizes the ramping of conventional generation as well as the dispatch of energy storage to enhance the load following and ramping support capabilities, to mitigate the impact of net load ramps. The proposed CCS approach is converted...
Genes that share transcription factors are biologically driven to show a more likely measurable correlation in their gene expression. No modern method of visualization displays these intricate co-expression and correlation patterns better than a graph. Structural observations about a co-expression graph can reveal the secrets of the biological system that it models, but experimentally validated co-expression...
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