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Instead of aiming at a systematic survey, we consider further developments on several typical linear models and their mixture extensions for prediction modeling, portfolio management and market analyses. The f...
This study identified the main drivers of intermittent preventive therapy (IPTp) of malaria in pregnancy with the malaria drugs’ sulfadoxine–pyrimethamine (SP) uptake from a longitudinal data set in Ghana.
This paper ranks the voice transmission carriers as used by mobile telecommunication companies. The versatility of the PROMETHEE method made it a useful tool for this ranking process. However, in our approach,...
Biomedical text clustering is a text mining technique used to provide better document search, browsing, and retrieval in biomedical and clinical text collections. In this research, the document representation ...
Driving fatigue detection has been the subject of several studies which relied on a set of features describing driver’s facial expressions, driving behaviors, and bio-signals. The purpose of this study is to i...
Information and communication technology (ICT) is revolutionizing the lives of people and operations of organizations. ICT has become a major driver of touristic sectors to effectively promote tourist attracti...
This paper starts at a brief review on AlphaGoZero, Q learning, and Monte-Carlo tree search (MCTS), in a comparison with decades ago studies on A* search and CNneim-A that was proposed in 1986 and shares a sco...
Route prediction plays a vital role in many important location-based applications such as resource prediction in grid computing, traffic congestion estimation, vehicular ad hoc networks, and travel recommendat...
It is very important to analyze the network structure of interacting genes, proteins, RNAs, etc. in large-scale biological networks which represent complex biological systems. Many tools have been made for thi...
Since the dawn of time, the implementation of an information system has always been useful to represent an organization and its processes. ERP was then quickly adopted by organizations, because it is composed ...
The aim of this study was to empirically examine e-learning acceptance and use in technology institutes of Ethiopian public universities. Samples of 400 university teachers were selected using simple random sa...
The knapsack feasibility problems have been intensively studied both because of their immediate applications in industry and financial management, but more pronounced for theoretical reasons, as knapsack probl...
Advances in causal discovery from data are becoming a widespread topic in machine learning these recent years. In this paper, studies on conditional independence-based causality are briefly reviewed along a li...
Functional connectivity at resting state was found altered in early-onset schizophrenia patients. However, its potential as biomarker of clinical diagnosis is unknown. To test whether resting-state functional ...
Generalized tonic–clonic seizure (GTCS) is characterized by the abnormal functional organization among distant brain regions. Previous studies in GTCS that have comprehensively examined connectivity abnormalit...
This paper presents a simple and robust feature descriptor method, namely local dominant orientation feature histogram (LDOFH). In this method, the discriminant histogram contains dominant orientation, and the...
In this paper, we propose an end-to-end multiscale recurrent regression networks (MSRRN) approach for face alignment. Unlike conventional face alignment methods by utilizing handcrafted features which require ...
Many methods have been proposed to learn image priors from natural images for the ill-posed image restoration tasks. However, many prior learning algorithms assume that a general prior distribution is suitable...
OLAP (Online Analytical Processing) system appears as a revolutionary technology that provides adequate analytic solutions for decision support. Using OLAP, analysts and policymakers are able to process and an...
Precise neural encoding of varying pitch is crucial for speech perception, especially in Mandarin. A valid evaluation of the listeners’ auditory function which accounts for the perception of pitch variation ca...
Due to the progress of deep neural networks (DNN), DNN has been employed to cross-media retrieval. Existing cross-media retrieval methods based on DNN can convert separate representation of each media type to ...
Nowadays, more and more people use social network to share their lives and communicate with each other. In real social network, a person is influenced by others and also influences others at the same time. So ...
Complex systems are usually illustrated by networks which capture the topology of the interactions between the entities. To better understand the roles played by the entities in the system, one needs to uncove...
In the current competitive global market, organizations are implementing information and communication technology (ICT) that could add value to their products, processes, and satisfaction of their users. The a...
In this paper, we focus on the use of quaternary tree instead of binary tree to speed up the decoding time for Huffman codes. It is usually difficult to achieve a balance between speed and memory usage using v...
In the past few decades, video display terminals (VDTs) and computer use have been associated with various skin symptoms in several published reports. In addition, internet beauty sites report that extended co...
The ability to accurately and effectively search for 3D shape is crucial for many applications. In this study, we proposed a novel framework for 3D shape retrieval. We compensate the loss of high frequencies o...
In an effort to improve outcome of patients with sepsis, we developed and implemented a disease-specific alert and order set for our computerized physician order entry system. This alert and order set were imp...
Based on ranking of fuzzy numbers which deals with fuzzy-valued multi-objective programming problem and the modified crisp model, a modified approach is proposed. Also, two algorithms that play a pivotal role ...
Different from standard sampling strategy in compressive sensing (CS), we present a compressive partial sampling framework called adaptive-random sampling and recovery (ASR) for image. It could faithfully reco...
Sleep spindles are thought to be related to some sleep diseases and play an important role in memory consolidation. They were traditionally identified by physiology experts based on rules and recently detecte...
Analyzing functional magnetic resonance imaging (fMRI) data from the encoding perspective provides a powerful tool to explore human vision. Using voxel-wise encoding models, previous studies predicted the brai...
In this paper, we present a region merging-based method for object segmentation in natural images. The method consists of three separate steps: (1) initial over-segmentation such that pixels in each region are...
Post-traumatic stress disorder (PTSD) is an anxiety disorder that can develop following a traumatic event. Previous studies have found abnormal functional connectivity between the thalamus and other brain regi...
The data open sharing provides us opportunity to investigate mechanisms underlying autism spectrum disorder (ASD) by employing advanced techniques. In the current study, we employed structural covariance (SC) ...
In orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems, high out-of-band radiation (OOBR) results in severe interference to the neighboring users, including licensed users (LUs) a...
Diabetes mellitus is a major cause of morbidity and mortality in humans. Early diagnosis is the first step toward the management of this condition. However, a diagnosis involves several variables, which makes ...
Finding biomarkers for differentiation, prognosis, subtypes, and staging takes a key role in precision medicine, usually featured by association analysis on geno-measures and pheno-measures. Recent efforts tur...
This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After review...
Information retrieval systems are generally used to find documents that are most appropriate according to some query that comes dynamically from the users. In this paper, a novel fuzzy document-based informati...
A new formulation is proposed for multivariate test, consisting of not only a hierarchy of numerous tests organised in a lattice taxonomy of properties that come from different combinations of multi-variates a...
This paper extends the kernel affine projection algorithm to a rich, flexible and cohesive taxonomy of fractional signal processing approach. The formulation of the algorithm is established on the inclusion o...
An appropriate choice of the distance metric is a fundamental problem in pattern recognition, machine learning and cluster analysis. Some methods that based on the distance of samples, e.g, the k-means clustering...
Hypertension is a major global health problem associated with cardiovascular and cerebrovascular diseases. It is well established that blood pressure and hypertension are common complex phenotypes affected by ...
Blind image quality assessment (BIQA) is a challenging task due to the difficulties in extracting quality-aware features and modeling the relationship between the image features and the v...
Compared with supervised feature selection, selecting features in unsupervised learning scenarios is a much harder problem due to the lack of label information. In this paper, we propose sparsity preserving sc...
In this work, a fragile watermarking method based on incomplete cryptography for copyright protection is proposed. Our proposed method solves the original content leakage problem of the conventional digital ri...
The study proposes our extended method to assess structure complexity for symbol-free sequences, such as literal texts, DNA sequences, rhythm, and musical input. This method is based on L-system and topologica...
After a short tutorial on the fundamentals of Bayes approaches and Bayesian Ying-Yang (BYY) harmony learning, this paper introduces new progresses. A generic information harmonising dynamics of BYY harmony lea...
We pursue a threefold purpose in this paper. First, we suggest a Kullback-Leibler formulation for developing a statistics and making discriminative projection for case-control studies, based on which existing ...
