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Adaptive Security Model for Data Protection Using Behavioral User Authentication
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Credential compromise is one of the most widespread security threats, allowing adversaries to bypass traditional authentication measures and impersonate legitimate users. Traditional intrusion detection systems are often based on network-level or macro-behavioral indicators, which can be easily spoofed by an attacker, thus compromising the effectiveness of those mechanisms. This study presents an improved adaptive intrusion detection system to authenticate user behavior based on micro-digital behavioral profiling. It involves the use of timing of keystrokes, micro-mouse, navigation in the application, and interaction rhythm signatures. The proposed system uses a hybrid model consisting of Long Short-Term Memory (LSTM) sequence prediction and an Autoencoder reconstruction network to learn both structural and temporal variation of user behavior. Also, an adaptive learning module (implemented by a replay buffer and a drift-detection mechanism based on Kullback-Leibler divergence) to continually recalibrate the model when authentic user behavior varies. Experimental testing on a controlled set of 42 subjects in multiple sessions shows that the proposed model can achieve 94.8 0.91 F1-score and 0.05 false-positive rate, which outperforms the use of individual models; adaptive learning brings this number down by half in the case of drift.  The comparison analysis proves the superiority of the proposed system in the areas of anomaly detection, stability, and real-time performance, which demonstrates the viability of micro-behavior analytics as a high-resolution security layer that can be used as a persistent authentication and identity-based threat detector.

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Intelligent Dust Monitoring System Based on IoT
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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Publication Date
Sun Jun 01 2025
Journal Name
Microbial Biosystems
Distribution and association of an usp genotoxin gene with biofilm formation in E. coli
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Uropathogenic specific protein is a genotoxic protein targeting the DNA, leading to mutations and modifications in the normal cell's DNA and subsequently, cancer development. This study aims to determine the prevalence of the usp gene in Uropathogenic Escherichia coli isolated from females with urinary tract infections and study its correlation with biofilm formation. One hundred and five urine specimens were collected from female patients (20 to 55 years old) with urinary tract infections attending hospitals. Traditional laboratory methods using selective and differential culture media were used for initial bacterial isolation and identification, and molecular techniques that targeted a segment of the 16SrRNA gene with a specific primer pa

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Improving Building Information Modeling (BIM) Implementation throughout the Construction Industry
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Building Information Modeling (BIM) is extensively used in the construction industry due to its benefits throughout the Project Life Cycle (PLC). BIM can simulate buildings throughout PLC, detect and resolve problems, and improve building visualization that contributes to the representation of actual project details in the construction stage. BIM contributes to project management promotion by detecting problems that lead to conflicts, cost overruns, and time delays. This work aims to implement an effective BIM for the Iraqi construction projects’ life cycle. The methodology used is a literature review to collect the most important factors contributing to the success of BIM implementation, interview the team of the Cent

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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology & Applied Science Research
Automated Glaucoma Detection Techniques: A Literature Review
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Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

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Publication Date
Sun Jan 15 2012
Journal Name
Talanta
Molecularly imprinted polymer as sorbent in micro-solid phase extraction of ochratoxin A in coffee, grape juice and urine
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A simple, environmental friendly and selective sample preparation technique employing porous membrane protected micro-solid phase extraction (μ-SPE) loaded with molecularly imprinted polymer (MIP) for the determination of ochratoxin A (OTA) is described. After the extraction, the analyte was desorbed using ultrasonication and was analyzed using high performance liquid chromatography. Under the optimized conditions, the detection limits of OTA for coffee, grape juice and urine were 0.06 ng g−1, 0.02 and 0.02 ng mL−1, respectively while the quantification limits were 0.19 ng g−1, 0.06 and 0.08 ng mL−1, respectively. The recoveries of OTA from coffee spiked at 1, 25 and 50 ng g−1, grape juice and urine samples at 1, 25 and 50 ng mL

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The Impact of Cognitive Behavior Program Based on Meichenbaum Theory in Reducing the Negative Emotional Sensitivity among the Intermediate Stage Students
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The aim of this research is to construct a cognitive behavior program based on the theory of Meichenbaum in reducing the emotional sensitivity among Intermediate school students. To achieve the aims of the research, two hypotheses were formulated and the experimental design with equal groups was chosen. The population of research and its sample are determined. The test of negative emotional sensitivity, which is constructed by the researcher, was adopted. The test contains (20) items proved validity and reliability as a reliable test by presenting it to a group of arbitrators and experts in education and psychology. An educational program is constructed based on the theory of Meichenbaum. The test was applied to a sample of (60) second i

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Animation Films and Their Impact on the Behavior of Kindergarten Child from the Point of View of Mothers
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The child spends several hours watching animated films, which affect their behavior negatively and positively. This calls parents to monitor what their children are watching, to show them the serious risks of some violent films, and to direct them toward choosing both positive and educational programs that develop their positive behavior. This study aimed to explore the positive and negative effects of watching animation films as well as to identify the role animation films in increasing the cognitive knowledge of kindergarteners. To do this, the descriptive and analytical methods were used. A questionnaire was adopted as a tool for data collection. A scale of (45) items classified into three categories was applied on  the r

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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluating the effect of natural, industrial juices and beverage on orthodontic bonding composite (in-vitro study)
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Background: Dental erosion is a common oral condition which results due to consumption of high caloric and low pH acidic food such as carbonated drinks and fruit juices. It is expected that these food types can cause irreversible damage to dental hard tissues and early deterioration of the dental restorations. So, this study aimed to evaluate and compare the erosive potential effects of orange fruit juice and Miranda orange drink on the microhardness of an orthodontic composite material. Materials and methods: Thirty discs with a thickness of 2 mm and a diameter of 10 mm were prepared from orthodontic bonding composite. The prepared discs were equally divided into three groups (n=10). Microhardness analysis was carried out both prior to

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Publication Date
Wed May 15 2019
Journal Name
Tikrit Journal Of Pure Science
Improvement of Alert System against Tampering and Theft in Surveillance Cameras
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Use of Surveillance cameras in houses and markets became common, that resulted to minimize theft and make it a difficult task because it let recording and viewing what is going around. The wide application of these cameras, pushed thieves to seek new ways for abolition of the surveillance system and digital recording of events, such as cutting the signal wire between the camera and Digital video recorder or changing the direction of the camera away from the focus spot or damaging the camera or steal the device which means the loss of the recorded media. This paper focuses on such abolitions and fixed it by suggesting a way to notify the administrator immediately and automatically by Email about any violation of the system using MATLAB, whic

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Interior Visual Intruders Detection Module Based on Multi-Connect Architecture MCA Associative Memory
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Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

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