HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.
Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.
The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple
... Show MoreAlzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n
... Show MoreThe adsorption isotherms and kinetic uptakes of Carbon Dioxide (CO2) on fabricated electrospun nonwoven activated carbon nanofiber sheets were investigated at two different temperatures, 308 K and 343 K, over a pressure range of 1 to 7 bar. The activated carbon nanofiber-based on polymer (PAN) precursor was fabricated via electrospinning technique followed by thermal treatment to obtain the carboneous nanofibers. The obtained data of CO2 adsorption isotherm was fitted to various models, including Langmuir, Freundlich, and Temkin. Based on correlation coefficients, the Langmuir isotherm model presented the best fitting with CO2 adsorption isotherms’ experimental data. Raising the equ
Copper Zinc Sulphide (Cu0.5Zn0.5S) alloy and thin films were fabricated in a vacuum. Nano crystallized (CZS) film with thick 450±20 nm was deposit at substrates glasses using thermal evaporation technique below ~ 2 × 10− 5 mbar vacuum to investigated the films structural, morphological and optical properties depended on annealing temperatures ( as-deposited, 423, 523 and 623) K for one hour. The influences annealed temperature on structurally besides morphologically characteristics on these films were investigated using XRD and AFM respectively. XRD confirms the formation a mixed hexagonal phase of CuS-ZnS in (102) direction with polycrystalline in nature having very fine crystallites size varying from (5.5-13.09) nm. AFM analys
... Show MoreQuantum calculations on the most stable structure were carried
out for calculating the electronic properties, energies and the charge
density at the Carbon and Hydrogen atoms by Semi-empirical
method (PM3) of zigzag carbon nano tube CNT (9,0) (SWCNTs), at
the equilibrium geometry depending on the pictures of Zigzag
CNT(9,0) which was found to has D3d symmetry point group by
applying for (Gaussian 2003) program. In this work the results
include calculation the relation for axial bonds length, which are the
vertical C-C bonds (annular bonds) in the rings and bonds length
which are in the outer ring that called the circumferential bonds. Also
include a different kind of vibration modes like breathing, puckering
Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and req
... Show MoreGeographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste
... Show MoreThis paper is attempt to study the nonlinear second order delay multi-value problems. We want to say that the properties of such kind of problems are the same as the properties of those with out delay just more technically involved. Our results discuss several known properties, introduce some notations and definitions. We also give an approximate solution to the coined problems using the Galerkin's method.
In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri
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