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Human Activity Recognition using Smartwatch and Smartphone: A Review on Methods, Applications, and Challenges
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     Recently, Human Activity Recognition (HAR) has been a popular research field due to wide spread of sensor devices. Embedded sensors in smartwatch and smartphone enabled applications to use sensors in activity recognition with challenges for example, support of elderly’s daily life . In the aim of recognizing and analyzing human activity many approaches have been implemented in researches.  Most articles published on human activity recognition used a multi -sensors based methods where a number of sensors were tied on different positions on a human body which are not suitable for many users. Currently, a smartphone and smart watch device combine different types of sensors which present a new area for analysis of human attitude. This paper presents a review on methodologies applied to solve problems related to human activity recognition that use the equipped sensors in smartphone and smartwatch with the employ of Machine Learning and the advance of deep learning approaches. The literature is summarized from four aspects:  sensors types, applications, Machine Learning (ML) and Deep Learning (DL) models, results and challenges.

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Phylogenetic Analysis of Streptomyces spp. Exhibited Different Antimicrobial Activities
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Fourteen isolates were collected from a previous study and all were assigned to be Streptomyces genus, according to physiological and biochemical tests, however all the isolates varied morphologically and exhibited different antimicrobial activity.  All 14 isolates were confirmed Streptomyces by  16S rRNA PCR amplification. Six isolates with high antimicrobial activities were ascertained   Streptomyces spp. by sequencing and phylogenetic analysis. Two isolates among the selected 6 isolates with antimicrobial activity against  E. coli and S. aureus . It recommended to make a complete sequence for 16S  rRNA to detect the  species that

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Publication Date
Wed Oct 01 2008
Journal Name
Journal Of The Faculty Of Medicine Baghdad
INCIDENCE OF POST-OPERATIVE DEEP VEIN THROMBOSIS IN PATIENTS WITH LOWER LIMB OPEN FRACTURE
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Background: Venous thromboembolic (VTE) disease with i t ' s h i g h morbidity and mo r t a l i t y is currently one of the most serious postoperative complication, (DVT) can lead to
fatal pulmonary embolism (PE). or the development of post thrombotic syndrome.
Patients and methods: This is a prospective study which was carried on 85 patients had s i n g l e lower l i m b open fracture with no other major i n j u r i e s in other sites of body
(with the exception of superficial wounds or b r u i s e s ) .They were d i v i d e d i n t o groups according to age, gender, weight, type of fracture, methods of immobilization, duration of
h o s p i t a l i z a t i o n , duration of operation. All the patients includin

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Chromosomal Aberrations in Peripheral Blood Lymphocytes in Brick Kilns Workers
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This study was conducted on the workers of the brick kilns at Al- Nahrawan area south-east of Baghdad city to investigate the effect of the pollutant emissions (fumes and gases) released from the burned fuel in this kiln. Blood samples were taken from group individuals of workers at this brick kilns and non-working individuals as a control. The influence of these emissions on the workers' health was measured by examining certain chromosomal aberrations among the workers. These aberrations were a formation of: chromosomal rings, dicentric chromosomes, breaks arm and acentric fragments. It has been observed that most of these aberrations were found within workers of age 40 years and above, represented by formations of averages 1.50 and 1.0

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Hybrid Techniques with Support Vector Machine for Improving Artifact Ultrasound Images
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     The most common artifacts in ultrasound (US) imaging are reverberation and comet-tail. These are multiple reflection echoing the interface that causing them, and result in ghost echoes in the ultrasound image. A method to reduce these unwanted artifacts using a Otsu thresholding to find region of interest (reflection echoes) and output applied to median filter to remove noise. The developed method significantly reduced the magnitude of the reverberation and comet-tail artifacts. Support Vector Machine (SVM) algorithm is most suitable for hyperplane differentiate. For that, we use image enhancement, extraction of feature, region of interest, Otsu thresholding, and finally classification image datasets to normal or abnormal image.

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Possible Anti-Asthmatic Effect of Iraqi Ammi Majus Seeds Extract Against Asthma Induced by Ovalbumin in Mice
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Asthma is a chronic respiratory disorder of airways characterized by inflammation, hyperresponsiveness, inflammatory cell infiltration, mucous secretion, and remodelling. Ammi majus is medicinal plant belong to family of Apiaceous which has anti-inflammatory and antioxidant activities. This study designed to investigate of anti-asthmatic activity of alcoholic extract of Ammi majus in improvement of asthma. Forty-eight healthy female mice divided to six groups Group I:  the negative control group (distal water only), Group II: Positive control group (ovalbumin group), Group III: Ammi majus (64 mg/kg/day) with sensitization, Group IV:Ammi majus  (128 mg/kg/day) w

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Sun Mar 28 2021
Journal Name
Journal Of The College Of Education For Women
The Role of Social Work in Reducing the Phenomenon of Fanaticism: حسن فاضل جواد
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The present study is concerned with the concept of ethics academically. It aims to investigate the major problems that contemporary Iraqi society suffers from; on top of which is the problem of sectarian and religious intolerance. Such a problem has a major role in the emergence of extremism and terrorism. It further destabilizes the security and stability of the country, exposing, as a result, the lives of citizens to the danger of genocide, disintegrating the social structure, stopping the wheel of development, rampant corruption, and deteriorating the political, social, moral and economic situation. Here comes the role of social work as governmental institutions and civil society organizations in curbing this reprehensible phenomenon

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Publication Date
Wed Dec 11 2019
Journal Name
Aip Conference Proceedings
An analytical study of soil temperature with respect to its salinity
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In this study, the relationship between the bare soil temperature with respect to its salinity is presented, the bare soil feature is considered only by eliminating all other land features by classifying the site location by using the support vector machine algorithm, in the same time the salinity index that calculated from the spectral response from the satellite bands is calibrated using empirical salinity value calculated from field soil samples. A 2D probability density function is used to analyze the relationship between the temperature rising from the minimum temperature (from the sunrise time) due to the solar radiation duration tell the time of the satellite capturing the scene image and the calibrated salinity index is presented. T

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Publication Date
Wed Sep 29 2021
Journal Name
Biomass Conversion And Biorefinery
Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterificatio

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Science
Brain MR Images Classification for Alzheimer’s Disease
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    Alzheimer’s Disease (AD) is the most prevailing type of dementia. The prevalence of AD is estimated to be around 5% after 65 years old and is staggering 30% for more than 85 years old in developed countries. AD destroys brain cells causing people to lose their memory, mental functions and ability to continue daily activities. The findings of this study are likely to aid specialists in their decision-making process by using patients’ Magnetic Resonance Imaging (MRI) to distinguish patients with AD from Normal Control (NC). Performance evolution was applied to 346 Magnetic Resonance images from the Alzheimer's Neuroimaging Initiative (ADNI) collection. The Deep Belief Network (DBN) classifier was used to fulfill classification f

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