Assessment of mental workload using physiological measures, especially electroencephalography (EEG) signals, is an active area. Recently, a number wireless acquisition systems to measure EEG and other signals have become available. Few studies applied such assess cognitive evaluate their performance. This paper presents initial step explore the feasibility popular system (Emotiv EPOC headset) memory levels in well-known n-back task. We developed signal processing classification framework,...

Over the past decades, machine learning techniques, such as supervised learning, reinforcement and unsupervised have been increasingly used in control engineering community. Various algorithms developed to achieve autonomous operation intelligent decision making for many complex challenging problems. One of problems is bipedal walking robot control. Although still their early stages, techniques demonstrated promising potential build adaptive systems robots. This paper gives a review recent...

This paper presents a new computational framework for early detection of driver distractions (map viewing) using brain activity measured by electroencephalographic (EEG) signals. Compared with most studies in the literature, which are mainly focused on classification distracted and nondistracted periods, this study proposes to prospectively predict start end distraction period, defined map viewing. The proposed prediction algorithm was tested data set continuous EEG signals recorded from 24...

Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures. Being able to predict impending seizures could greatly improve lives patients with epilepsy. In this study, we propose a new adaptive learning approach for online seizure prediction based on analysis electroencephalogram (EEG) recordings. For each individual patient, construct baseline patterns normal and preseizure EEG samples, continuously monitor sliding windows recordings, classify window or...

Assessment of text relevance is an important aspect human–information interaction. For many search sessions it essential to achieving the task goal. This work investigates decision dynamics in a question‐answering by direct measurement eye movement using eye‐tracking and brain activity electroencephalography EEG. The EEG measurements are correlated with user's goal‐directed attention allocation revealed their movements. In within‐subject lab experiment ( N = 24), participants read short news...

Medical imaging provides quantitative and spatial information to evaluate treatment response in the management of patients with non-small cell lung cancer (NSCLC). High throughput extraction radiomic features on these images can potentially phenotype tumors non-invasively support risk stratification based survival outcome prediction. The prognostic value radiomics from different modalities time points prior during chemoradiation therapy NSCLC, relative conventional biomarker or delta models,...

Artificial Intelligence (AI) integration into Customer Relationship Management (CRM) within enterprise information systems (EIS) has provided businesses with transformative opportunities to improve customer engagement and operational efficiency. Due the accelerating momentum of AI technologies digital evolution prompted by COVID-19 pandemic, there been an increase in AI-based CRM research, yet comprehensive systematic studies are still lacking. This study presents overview historical...

Abstract Attributed to the extreme geological environment of deep shale reservoirs, characterized by high temperature and stress, hydraulic fracturing reservoir stimulation often faces a series problems, such as breakdown pressure unclear fracture propagation law. The purpose this study is restore evolution characteristics fractures in environment, clarify difficulty opening law propagation. For purpose, outcrop cores were collected from main gas-producing areas China, physical simulation...

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated proteins (Cas) systems have revolutionized genome editing by providing high precision and versatility. However, most applications rely on a limited number of well-characterized Cas9 Cas12 variants, constraining the potential for broader engineering applications. In this study, we extensively explored developed CasGen, novel transformer-based deep generative model with margin-based latent space regularization to...

Abstract In recent years, with the rapid development of national fitness movement, research related to energy-saving and lighting environments gymnasium buildings has become one hotspots. This paper builds a typical space model based on data combined sports building design codes. Through establishment parametric platform, key samples are selected for measuring analyzing indoor natural light environment. The environment simulation software ECOTECT is used simulate analyze stadium, parallel...

There is an urgent need for a quick screening process that could help neurologists diagnose and determine whether patient epileptic versus simply demonstrating symptoms linked to epilepsy but actually stemming from different illness. An inaccurate diagnosis have fatal consequences, particularly in operating rooms intensive care units. Electroencephalogram (EEG) has been traditionally used, as gold standard, patients by evaluating those brain functions might correspond other disorders. This...

The field data of shale fracturing demonstrate that the flowback performance fluid is different from conventional reservoirs, where rate lower than reservoirs. At early stage flowback, there no single-phase flow liquid phase in shale, but rather a gas-water two-phase flow, such model for tight oil and gas reservoirs not applicable. In this study, pores microfractures are extracted based on experimental results computed tomography (CT) scanning, spatial established. Then, influence rough...

Stuttering is a communication disorder that affects approximately 1% of the population. Although 5-8% preschool children begin to stutter, majority will recover with or without intervention. There significant gap, however, in our understanding why many from stuttering while others persist and stutter throughout their lives. Detecting neurophysiological biomarkers persistence critical objective this paper. In paper, we developed novel supervised sparse feature learning approach discover...

The sudden and spontaneous occurrence of epileptic seizures can impose a significant burden on patients with epilepsy. If seizure onset be prospectively predicted, it could greatly improve the life epilepsy also open new therapeutic avenues for treatment. However, discovering effective predictive patterns from massive brainwave signals is still challenging problem. prediction in its early stage. Most existing studies actually investigated predictability offline instead truly prospective...

EEG source imaging integrates temporal and spatial components of to localize the generating electrical potentials based on recorded data scalp. As sensors can't directly measure activated brain sources, many approaches were proposed estimate activation pattern given data. However, since most part activity is composed spontaneous non-task related activations, true task caused sources will be corrupted in strong background signal. For decades, inverse problem was solved an unsupervised way...

Warts are noncancerous benign tumors caused by the Human Papilloma Virus (HPV).The success rates of cryotherapy and immunotherapy, two common treatment methods for cutaneous warts, 44% 72%, respectively.The methods, therefore, fail to cure a significant percentage patients.This study aims develop reliable machine learning model accurately predict immunotherapy individual patients based on their demographic clinical characteristics.We employed support vector (SVM) classifier utilizing dataset...

The recent development of CRISPR-Cas technology holds promise to correct gene-level defects for genetic diseases. key element the system is Cas protein, a nuclease that can edit gene interest assisted by guide RNA. However, these proteins suffer from inherent limitations such as large size, low cleavage efficiency, and off-target effects, hindering their widespread application editing tool. Therefore, there need identify novel with improved properties, which it necessary understand...

Allosteric regulation is a well-established phenomenon defined as distal conformational or dynamical change of the protein upon allosteric effector binding. Here, we developed novel approach to delineate effects in proteins. In this approach, applied robust machine learning methods, including deep neural network and random forest, on extensive molecular dynamics (MD) simulations distinguish otherwise similar states Using PDZ3 domain PDS-95 model protein, demonstrated that could be...