In this work we present an algorithmic approach to the analysis of the Visual Sequential Search Test (VSST) based on the episode matching method. The data set included two groups of patients, one with Parkinson’s disease, and another with chronic pai...
The standard expected utility model applied by economists and decision scientists assumes both that decision makers (DMs) are rational and that their information retrieval behavior and choices are determined by the observed and potential values of th...
In many social situations, individuals endeavor to find the single best possible partner, but are constrained to evaluate the candidates in sequence. Examples include the search for mates, economic partnerships, or any other long-term ties where the...
A ubiquitous challenge throughout all areas of data mining, particularly in the mining of frequent patterns in large databases, is centered on the necessity to reduce the time and space required to perform the search. The extent of this reduction pro...
This paper addresses the problem of information extraction using an AI-powered chatbot. The problem concerns searching and extracting relevant information from large databases in response to a human user’s query. Expanding the traditional discr...
This article involves forecasting daily electricity consumption in Thailand. Electricity consumption data are provided by the Electricity Generating Authority of Thailand, the leading power utility state enterprise under the Ministry of Energy. Five...
Given a monotone ordered multi-dimensional real array A and a real value k, an important question in computation is to establish if k is a member of A by sequentially searching A by comparing k with some of its entries. This search problem and its kn...
In this paper, the robot arm Dobot Magician and the Raspberry Pi development platform were used to integrate image processing and robot-arm drawing. For this system, the Python language built into Raspberry Pi was used as the working platform, and th...
Rapid search and localization for nuclear sources can be an important aspect in preventing human harm from illicit material in dirty bombs or from contamination. In the case of a single mobile radiation detector, there are numerous challenges to over...
Power quality signal feature selection is an effective method to improve the accuracy and efficiency of power quality (PQ) disturbance classification. In this paper, an entropy-importance (EnI)-based random forest (RF) model for PQ feature selection...
Product layout significantly impacts consumer demand for purchases in supermarkets. Product shelf renovation is a crucial process that can increase supermarket efficiency. The development of a sequential pattern mining algorithm for investigating the...
Feature selection is widely used in machine-learning-based intrusion detection systems (IDSs/NIDSs) to reduce dimensionality and computational burden, yet its benefits are difficult to attribute when feature evaluation, subset search, preprocessing,...
Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce fram...
Retrofitting existing buildings is widely recognized as a critical strategy for achieving global decarbonization goals. As a part of this effort, several tools have been developed for building retrofit analysis, each offering distinct advantages and...
Eye-tracking can offer a novel clinical practice and a non-invasive tool to detect neuropathological syndromes. In this paper, we show some analysis on data obtained from the visual sequential search test. Indeed, such a test can be used to evaluate...
The prediction accuracy of short-term load forecast (STLF) depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF)-based feature selection method for STLF is proposed. First, 243 related features wer...
The early detection of defective lithium-ion batteries in cellular phones is critical due to the rapid increase in popularity and mass production of cellular phones. It is essential for manufacturers to design an optimal burn-in policy to differentia...
Cultivation process (CP) modeling and optimization are ambitious tasks due to the nonlinear nature of the models and interdependent parameters. The identification procedures for such models are challenging. Metaheuristic algorithms exhibit promising...
Although Cyber–Physical Systems (CPSs) provide a flexible architecture for enterprises to deal with changing demand, an effective method to organize and allocate resources while considering sustainability factors is required to meet customers&r...
Recent advances in autonomy of unmanned aerial vehicles (UAVs) have increased their use in remote sensing applications, such as precision agriculture, biosecurity, disaster monitoring, and surveillance. However, onboard UAV cognition capabilities for...
15 October 2022
(1) Background: Word-of-mouth (WOM) can influence patients’ choice of doctors in online medical services (OMSs). Previous studies have explored the relationship between internal WOM in online healthcare communities (OHCs) and patients’ ch...
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer cells. The accurate prediction of ACPs from given peptide sequences remains as an open problem in the field of immunoinformatics. Recently, machine learning...
Let VIP indicate the variational inequality problem with Lipschitzian and pseudomonotone operator and let CFPP denote the common fixed-point problem of an asymptotically nonexpansive mapping and a strictly pseudocontractive mapping in a real Hilbert...
In a real Hilbert space, we denote CFPP and VIP as common fixed point problem of finitely many strict pseudocontractions and a variational inequality problem for Lipschitzian, pseudomonotone operator, respectively. This paper is devoted to explore ho...
The goal of the trade-off design method presented in this study is to achieve newly targeted performance requirements by modifying the current values of the design variables. The trade-off design problem is formulated in the framework of Sequential Q...
Precise odor source localization in turbulent and sparse environments plays a vital role in enabling robotic systems for hazardous chemical monitoring and effective disaster response. To address this, we propose Cooperative Gravitational-Rényi...
Autonomous search is an ongoing cycle of sensing, statistical estimation, and motion control with the objective to find and localise targets in a designated search area. Traditionally, the theoretical framework for autonomous search combines sequenti...
In long-range sequential orbital pursuit-evasion game scenarios, traditional Nash equilibrium algorithms rely on symmetric simultaneous decision-making assumptions. Such algorithms fail to fully exploit the sequential advantages of the leader-followe...
To address the poor searchability, population diversity, and slow convergence speed of the differential evolution (DE) algorithm in solving capacitated vehicle routing problems (CVRP), a new multistrategy-based differential evolution algorithm with t...
For parallelization of applications with high processing times and large amounts of storage in High Performance Computing (HPC) systems, shared memory programming and distributed memory programming have been used; a parallel application is represente...
In this paper, the weighted tardiness single-machine scheduling problem is considered. To solve it an approximate (tabu search) algorithm, which works by improving the current solution by searching the neighborhood, is used. Methods of eliminating ba...
Mutual information between a target variable and a feature subset is extensively used as a feature subset selection criterion. This work contributes to a more thorough understanding of the evolution of the mutual information as a function of the numb...
Frequency-guided sequential demodulation (FSD) is a technique used to recover the phase of closed fringe patterns when only a single interferogram is available. FSD is a sequential method that follows simple and intuitive processing steps for interfe...
12 February 2020
The Google search engine answers many health and medical information queries every day. People have become used to searching for this type of information. This paper presents a study which examined the visibility of health and medical information web...
When confronted with massive data streams, summarizing data with dimension reduction methods such as PCA raises theoretical and algorithmic pitfalls. A principal curve acts as a nonlinear generalization of PCA, and the present paper proposes a novel...
Truss layout optimization under complex constraints has been a hot and challenging problem for decades that aims to find the optimal node locations, connection topology between nodes, and cross-sectional areas of connecting bars. Monte Carlo Tree Sea...
This paper develops a new approach to band subset selection (BSS) for hyperspectral image classification (HSIC) which selects multiple bands simultaneously as a band subset, referred to as simultaneous multiple band selection (SMMBS), rather than one...
The paper considers an algorithm for the direct search for a nonparametric smooth histogram of the particle size distribution from small-angle X-ray and neutron scattering data. The features and details of the implementation of the method, which cons...
Background—Direct-to-consumer (DTC) sequential aligners promote “teeth straightening” at a low cost and with added patient convenience. DTC sequential aligners have risen in popularity among the general public and sparked debate amo...
Repeated search studies are a hallmark in the investigation of the interplay between memory and attention. Due to a usually employed averaging, a substantial decrease in response times occurring between the first and second search through the same se...
In RFID-assisted applications, the customers often request to provide the tag searching service to determine which specific tags are present in the system. In practice, tags are usually divided into different groups to represent different categories...
The reliability assesment of large power systems, particularly when considering both generation and transmission facilities, is a computationally demanding and complex problem. The sequential Monte Carlo simulation is arguably the most versatile appr...
Solving satisfiability problems is central to many areas of computer science, including artificial intelligence and optimization. Efficiently solving satisfiability problems requires exploring vast search spaces, where search space partitioning plays...
We investigate human overreliance on artificial intelligence (AI), a phenomenon in which users fail to critically verify AI outputs despite knowing the system is imperfect. To analyze this interaction, we model a cybersecurity scenario in which a hum...
Inundation forecast models with non-sequential regressors are advantageous in efficiency due to their rather fewer input variables required to be processed. This type of model is nevertheless rare mainly because of the difficulty in finding the prope...
Objective: The aim of this paper is to provide a systematic review of research on physical exercise in real-world settings on executive function of typical children and adolescents. Methods: The CNKI, WOS, PubMed, ScienceDirect, and SPORTDiscus datab...
6 November 2020
This review aimed to map the existing patents of double-chamber syringes that can be used for intravenous drug administration and catheter flush. A search was conducted in the Google patents database for records published prior to 28 October 2020, us...
The paper presents a framework for autonomous search for a diffusive emitting source of a tracer (e.g., aerosol, gas) in an environment with an unknown map of randomly placed and shaped obstacles. The measurements of the tracer concentration are spor...
As the number and capacity of photovoltaic (PV) power stations increase, it is of great significance to evaluate the PV-connected power systems in an effective, reasonable, and quick way. In order to overcome the challenge of PV’s time-sequenti...
Accurate indoor positioning is essential for many applications. However, current methods often fall short in complex environments due to signal fluctuations. We propose a new indoor positioning approach, that is, improved sequential deep learning (IS...
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