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A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multiple RS datasets to overcome limitations and produce comparatively detailed outcomes. However, there are still knowledge gaps in examining the effectiveness of these RS approaches in enhancing the detection of archaeological remains/areas. Thus, this review paper is likely to deliver valuable comprehension for archaeological studies to fill knowledge gaps and further advance exploration of archaeological areas/features using RS along with DL approaches.

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Thu Jun 08 2023
Journal Name
University Of Thi-qar Journal Of Agricultural Research
A review: Machine relationship with the tractor and its effect on the productivity and compaction of agricultural soil
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The influence of process speed (PS) and tillage depth (TD) , on growth of corn (Zea mays L) yield, for Maha cultivar, were tested at two ranges of PS of 2.483 and 4.011 km.hr-1, and three ranges of TD of 15,20 and 25cm. The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the PS of 2.483 km.hr-1 was significantly better than the PS of 4.011km.hr-1 in all studied conditions. The , slippage ratio (SR) and the machine efficiency (ME), the physical soil characteristics represented by the soil density and porosity (SBD and TSP), and the plant characteristics represented the roots dry weight, PVI and the crop productivity (CP), except adjective of the fu

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Publication Date
Tue Apr 02 2024
Journal Name
Iraqi Journal Of Applied Physics
Effect of Substrate Temperature on Characteristics and Gas Sensing Properties of Nb2O5/Si Thin Films
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Thin films of Nb2O5 have been successfully deposited using the DC reactive magnetron sputtering technique to manufacture NH3 gas sensors. These films have been annealed at a high temperature of 800°C for one hour. The assessment of the Nb2O5 thin films structural, morphological, and electrical characteristics was carried out using several methods such as X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity assessments. The XRD analysis confirms the polycrystalline composition of the Nb2O5 thin films with a hexagonal crystal structure. Furthermore, the sensitivity, response time, and recovery time of the gas sensor were evaluated for the Nb2O5 thin film

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
“The impact of the critical factors for the transfer of knowledge on opportunities and strategic success”
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The current research discusses “The impact of the critical factors for the transfer of knowledge on opportunities and strategic success ", the attention have been increased on knowledge transfer and strategic success subjects because on being one of the important and contemporary issues, which have a significant impact on the existence of organizations and its future. The research aims to identify the critical factors for knowledge transfer in private high education environment which enables (the college community surveyed) to achieve strategic success, also the research sought to answer questions related to research problem by testing a number of major and minor hypothes in impact, in order to test the hypotheses I used a fiel

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Circulating Interleukin-23 Levels in Rheumatoid Arthritis and its Relationship to Disease Activity: a Systematic Review with Meta-Analysis
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Background: Rheumatoid arthritis (RA) is a chronic and systemic autoimmune disease that is characterized by severe synovial inflammation, cartilage erosion, bone loss, and generalized vasculopathy. Although the immunologic mechanism of RA is still unclear, it is now thought to be a primarily Th17-driven disease. Along with other factors, IL-23 stimulates the expansion of Th17 cells from naive CD4+ T cells.

Objective: The objective of this study is to assess the circulating levels of interleukin (IL)-23 in rheumatoid arthritis (RA) and determine the correlation between plasma/serum IL-23 levels and disease activity. So, we performed a systematic review with meta-analysis comparing

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Sport Science Technology And Physical Activities
The effect of using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students
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The aim of this study to identity using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students. The researchers used the experimental method to design equivalent groups with a preand post-test, and the research community was identified with the students of the third stage in the college for the academic year 2020-2021 .The subject was, (3) class were randomly selected, so (30) students distributed into (3) groups). has been conducted pretesting after implementation of the curriculum for (4) weeks and used the statistical bag of social sciences(SPSS)to process the results of the research and a set of conclusions was reached, the most important of which is t

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Publication Date
Mon May 01 2023
Journal Name
Complementary Therapies In Medicine
Effects of almond intake on oxidative stress parameters: A systematic review and meta-analysis of clinical trials
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Publication Date
Tue Mar 02 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education
Deep understanding skills and their relationship to mathematical modelling among fifth grader
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Abstract: The aim of the current research is to identify (the relationship between deep understanding skills and mathematical modeling among fifth grade students) the research sample consisted of (411) male and female students of the fifth grade of biology distributed over the General Directorates of Education in Baghdad / Al-Rusafa / 2 / and Al-Karkh / 1 /, and two research tools were built: 1- A test of deep understanding skills, consisting of (20) test items and a scale for two skills. 2- The second test consists of (24) test items distributed among (18) essay items and (6) objective items. The psychometric properties of validity, stability, discriminatory strength, and effectiveness of alternatives were verified for the two tests fo

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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
How geometric reverse engineering techniques can conserve our heritage; a case study in Iraq using 3D laser scanning
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Abstract<p>Laser scanning has become a popular technique for the acquisition of digital models in the field of cultural heritage conservation and restoration nowadays. Many archaeological sites were lost, damaged, or faded, rather than being passed on to future generations due to many natural or human risks. It is still a challenge to accurately produce the digital and physical model of the missing regions or parts of our cultural heritage objects and restore damaged artefacts. The typical manual restoration can become a tedious and error-prone process; also can cause secondary damage to the relics. Therefore, in this paper, the automatic digital application process of 3D laser modelling of arte</p> ... Show More
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