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Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two supervised machine learning classification techniques, Learning Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers, to achieve better search performance and high classification accuracy in a heterogeneous WBASN. These classification techniques are responsible for categorizing each incoming packet into normal, critical, or very critical, depending on the patient's condition, so that any problem affecting him can be addressed promptly. Comparative analyses reveal that LVQ outperforms SVM in terms of accuracy at 91.45% and 80%, respectively.

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Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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Publication Date
Wed Mar 01 2017
Journal Name
Ieee Transactions On Cognitive Communications And Networking
Multi-Channel Distributed DSA Networks: Connectivity and Rendezvous Tradeoffs
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In this paper, we investigate and characterize the effects of multi-channel and rendezvous protocols on the connectivity of dynamic spectrum access networks using percolation theory. In particular, we focus on the scenario where the secondary nodes have plenty of vacant channels to choose from a phenomenon which we define as channel abundance. To cope with the existence of multi-channel, we use two types of rendezvous protocols: naive ones which do not guarantee a common channel and advanced ones which do. We show that, with more channel abundance, even with the use of either type of rendezvous protocols, it becomes difficult for two nodes to agree on a common channel, thereby, potentially remaining invisible to each other. We model this in

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Environmental Compatibility of the Suggested New Cities Study Area -Samawah New City
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Abstract<p>The research presented the experience of creating a new sustainable city, and this experience of establishing an Eco-City (Environmentally friendly) is considered the first experience in Iraq. The current study stressed the importance of the need for environmental planning in the early stages of planning new cities based on realism in planning, design and implementation. Subsequently, that aims to preserve the ecosystem, which is difficult to compensate if degraded or polluted. The research incorporated environmental planning indicators within sustainable urban planning (Reliance on generating electric power that is based on clean and renewable energy sources, Availability of public t</p> ... Show More
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Publication Date
Sun Sep 07 2008
Journal Name
Baghdad Science Journal
Effect of Low Level Acute of Aflatoxin on Performance in Faw- Bro Broiler
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This study was conducted in the Poultry farm of the animal during the Production department, Iraqi during the (Ministry of Science and Technology) period from 3-9-2001 to 8-4-2002. The objectives of this study were to evaluate the effect of low – level chronic aflatoxicosis on performance (body weight, feed conversion efficiency and mortality), Serum biochemistry and activity of some enzymes (GOT,GPT, ALKP, LDH). A total of 300 male chicks of broiler breeder (Faw–Bro) were used. Chicks at day 1 of age were fed diets contaminated with aflatoxine at levels of 0, 0.3, 0.6, 0.9, 1.2, and 1.5 the feeding period were extended to 8 weeks. The data were subjected to analysis of variance by the completely randomized design. The results showed

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Enrichment Programs on the Performance of Gifted Students in KSA
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       The current study aimed at identifying the impact of each of the full and part time summer enrichment programs on the performance of gifted students. Moreover, it aimed to study the difference between the full and part time programs on the performance of gifted students. The study sample consisted of (115) students from the full time programs and (137) students from the part time programs, they have been randomly selected from the gifted students participating in the full and part time summer enrichment programs. The researcher used the scale of student performance. The results indicated that there were statistically significant differences between the averages of the pre and post applications of the

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Animal Health And Production
Impact of Anastrozole Administration at Different Levels on Physiological Performance in Broiler Roosters
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The primary objective of current study was to evaluate the effects of different anastrozole dosages on the physiological performance, hematological profile, and serum biochemical parameters of broiler roosters. A total of Twenty-six Lohmann Brown roosters were randomly assigned to four treatment groups. The first group (T1) served as the control and received no anastrozole, while the other groups (T2, T3, and T4) were administered 0.2 mg, 0.4 mg, and 0.6 mg of anastrozole per day, respectively. The first and second groups consisted of six birds each, while the third and fourth groups had seven. The results demonstrated a significant improvement (P ≤ 0.05) in several physiological and biochemical parameters in the group receiving 0.6 mg of

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Emotional Intelligence on Employee Performance in Saudi Arabia Banking Sector
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Saudi Arabia’s banking sector plays an important role in the country’s development as it is among the leading sectors in the financial sector. Considering, two main Saudi banks (The National Commercial Bank and Saudi American bank), the present study aims to observe the impact of emotional intelligence on employee performance. The components of emotional intelligence affecting employee performance include self-management, relationship management, self-awareness, and social awareness. A quantitative methodology was applied to analyse the survey results of 300 respondents over the period from 2018 to 2019. The results show that there was a significant positive impact of self-management, self-awareness, and relationship manageme

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
A Face Mask Detection Method in the Era of the COVID-19 Pandemic Based on GLCM and YOLO
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In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
Mefenamic Acid Selective Membranes Sensor and Its Application to pharmaceutical Analysis
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PVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M,

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Publication Date
Thu Mar 09 2017
Journal Name
University Of Baghdad
Synthesis of modified Graphene Oxide and its application as Electrochemical Sensor
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This study involved preparation of Graphene oxide (GO) and reduced graphene oxide (RGO) using Hummer method and chemical method respectively. These carbon nanomaterials were used as starting material to make novel functionalize with thiocarbohydrazide (TCH) which was prepared by reacting CS2 with hydrazine to form GO or RGO- 4-amino,5-substituted 1H,1,2,4 Triazole 5(4H) thion (ASTT) ,(GOT) and( RGOT) respectively via cyclocondensation reaction. Also MnO2 nanorod was prepared to form hybridized with GOT and RGOT. A commercial multiwall carbon nanotube (MWCNT) and functionalization with carboxylic groups' (f-MWCNT) and its nanocomposite with GOT were also prepared. All carbon nanomaterials were characterized with different techniques such as

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