2018 May - 22 articles
We address image processing workflow scheduling problems on a multicore digital signal processor cluster. We present an experimental study of scheduling strategies that include task labeling, prioritization, resource selection, and digital signal pro...
Cosine-modulated filter banks play a major role in digital signal processing. Sparse FIR filter banks have lower implementation complexity than full filter banks, while keeping a good performance level. This paper presents a fast design paradigm for...
This article deals with the modified Multi-Depot Vehicle Routing Problem (MDVRP). The modification consists of altering the optimization criterion. The optimization criterion of the standard MDVRP is to minimize the total sum of routes of all vehicle...
3D shape reconstruction from images has been an important topic in the field of robot vision. Shape-From-Shading (SFS) is a classical method for determining the shape of a 3D surface from a one intensity image. The Lambertian reflectance is a fundame...
Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low-levels of light (650–900 nm) to measure changes in cerebral blood volume and oxygenation. Over the last several decades, this technique has been...
In the field of investment, how to construct a suitable portfolio based on historical data is still an important issue. The second-order stochastic dominant constraint is a branch of the stochastic dominant constraint theory. However, only considerin...
Inspired by the migration behavior of monarch butterflies in nature, Wang et al. proposed a novel, promising, intelligent swarm-based algorithm, monarch butterfly optimization (MBO), for tackling global optimization problems. In the basic MBO algorit...
Functional Near InfraRed Spectroscopy (fNIRS) connectivity analysis is often performed using the measured oxy-haemoglobin (HbO2) signal, while the deoxy-haemoglobin (HHb) is largely ignored. The in-common information of the connectivity networks of b...
The Vehicle Routing Problem (VRP) is one of the most optimized tasks studied and it is implemented in a huge variety of industrial applications. The objective is to design a set of minimum cost paths for each vehicle in order to serve a given set of...
We address a scheduling problem in an actual environment of the tortilla industry. Since the problem is NP hard, we focus on suboptimal scheduling solutions. We concentrate on a complex multistage, multiproduct, multimachine, and batch production env...
With the rapid increase in new fNIRS users employing commercial software, there is a concern that many studies are biased by suboptimal processing methods. The purpose of this study is to provide a visual reference showing the effects of different pr...
We consider a single machine scheduling problem with uncertain durations of the given jobs. The objective function is minimizing the sum of the job completion times. We apply the stability approach to the considered uncertain scheduling problem using...
This paper focuses on the rational distribution of task utilities in coalition skill games, which is a restricted form of coalition game, where each service agent has a set of skills and each task agent needs a set of skills in order to be completed....
We developed a novel control strategy of speed servo systems based on deep reinforcement learning. The control parameters of speed servo systems are difficult to regulate for practical applications, and problems of moment disturbance and inertia muta...
In the quest for higher-performance shared data structures, weakening consistency conditions and relaxing the sequential specifications of data types are two of the primary tools available in the literature today. In this paper, we show that these tw...
Support Vector Regression (SVR), which converts the original low-dimensional problem to a high-dimensional kernel space linear problem by introducing kernel functions, has been successfully applied in system modeling. Regarding the classical SVR algo...
Supplier selection is an important decision-making link in bidding activity. When overall scores of several suppliers are similar, it is hard to obtain an accurate ranking of these suppliers. Applying the Diversity Factors Method (Diversity Factors M...
Current literature presents optimal control computational algorithms with regard to state, control, and conjunctive variable spaces. This paper first analyses the advantages and limitations of different optimal control computational methods and algor...
The analysis of self-stabilizing algorithms is often limited to the worst case stabilization time starting from an arbitrary state, i.e., a state resulting from a sequence of faults. Considering the fact that these algorithms are intended to provide...
Rough set theory and neutrosophic set theory are mathematical models to deal with incomplete and vague information. These two theories can be combined into a framework for modeling and processing incomplete information in information systems. Thus, t...
Uncertainty analysis is considered to be a necessary step in the process of vessel traffic risk assessment. The purpose of this study is to propose the uncertainty analysis algorithm which can be used to investigate the reliability of the risk assess...
This paper proposes the Bayesian Extreme Learning Machine Kohonen Network (BELMKN) framework to solve the clustering problem. The BELMKN framework uses three levels in processing nonlinearly separable datasets to obtain efficient clustering in terms...
