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.
Objective: To review and see the pattern of histopathological diagnoses of one year appendectomy specimens.
Methodology: This retrospective study was carried in Sulaimani Teaching Hospital over the period of one year (from 1st
of January to 31st of December 2009). All pathological reports were reviewed retrospectively for patient’s age, sex,
histopathological diagnosis and operative findings (if present). Histopathological diagnoses then were classified into
either positive or negative for acute inflammation. Any associated findings or any surgical specimen removed with the
appendix was recorded. The obtained data were analyzed by using the statistical package social sciences (SPSS) version
19; with Chi square to test
Background A prospective clinical study was
performed to compare the efficacy of the use of lowmolecular-
weight heparin group (enoxparin group)
with control group in the prevention of deep-vein
thrombosis after total knee arthroplasty.
Aim of the study: to assess the prevalence of DVT
after total knee arthroplasty and evaluate the
importance of the use of low molecular weight
heparin in the prevention of this DVT.
Methods Thirty-three patients undergoing total
knee arthroplasty were randomly divided into two
groups. One group consisted of 12 patients who
received no prophylaxis with an anticoagulant (the
control group), other group consisted of 21 patients
who received the low-molecular-weight h
ole in all sta Oil well logging, also known as wireline logging, is a method of collecting data from the well environment to determine subterranean physical properties and reservoir parameters. Measurements are collected against depth along the well's length, and many types of wire cabling tools depend on the physical property of interest. Well probes generally has a dynamic respon to changes in rock layers and fluid composition. These probes or well logs are legal documents that record the history of a well during the drilling stages until its completion. Well probes record the physical properties of the well, which must then be interpreted in petrographic terms to obtain the characteristics of the rocks and fluids associated with
... Show Moreole in all sta
Oil well logging, also known as wireline logging, is a method of collecting data from the well environment to determine subterranean physical properties and reservoir parameters. Measurements are collected against depth along the well's length, and many types of wire cabling tools depend on the physical property of interest. Well probes generally has a dynamic respon to changes in rock layers and fluid composition. These probes or well logs are legal documents that record the history of a well during the drilling stages until its completion. Well probes record the physical properties of the well, which must then be interpreted in petrographic terms to obtain the characteristics of the rocks and flui
... Show MoreBackground: Educational environment is one of the most important determinants of an effective curriculum. Students' perceptions of their educational environment have a significant impact on their behavior and academic progress. Objective: 1. To identify students’ perception to the educational environment.2. To identify any gender or class level differences in the students’ perception.Type of the study: This is a descriptive cross-sectional studyMethodology: The study was carried out on convenient sample of 150 students of 2nd and 5th grade. This study was done in Al Kindy Medical College, Baghdad, Iraq and conducted during the period from the 1st of October 2013 till the end of March 2014, by using DREEM questionnaire a validated uni
... Show MorePurpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.
Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.
Methodology:
This research aims to examine the effectiveness of a teaching strategy based on the cognitive model of Daniel in the development of achievement and the motivation of learning the school mathematics among the third intermediate grade students in the light of their study of "Systems of Linear Equations”. The research was conducted in the first semester (1439/1440AH), at Saeed Ibn Almosaieb Intermediate School, in Arar, Saudi Arabia. A quasi-experimental design has been used. In addition, a (pre & post) achievement test (20 Questions) and a (pre & post) scale of learning motivation to the school mathematics (25 Items) have been applied on two groups: a control group (31Students), and an experimental group (29 Students). The resear
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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