Intelligent System for the Classification of Arterial Blood Pressure Waveform Abnormalities Due to Mistiming in Intra-Aortic Balloon Pump

Zainab A.; Sadiq J.; Wisam S.

doi:https://doi.org/10.54216/JISIoT.130105

Journal of Cybersecurity and Information Management | 2025

Effective Integration of Database Security Tools into SDLC Phases: A Structured Framework

As organizations increasingly rely on digital data, securing database systems has become a critical priority for protecting sensitive information, ensuring system integrity, and meeting regulatory compliance standards. This paper explores a comprehensive framework for database security, focusing on developing, assessing, and testing effective security tools. We begin by outlining the essential steps in creating robust security tools, including defining specific requirements based on database types and access needs and implementing real-time monitoring systems for immediate threat detection. The paper also emphasizes the importance of regular vulnerability assessments and advanced security analytics to identify and address potential risks proactively. Insights from a recent survey conducted among database administrators revealed that key areas of concern include access control, real-time monitoring, and vulnerability assessments. Furthermore, we highlight the significance of integrating security practices throughout the Software Development Life Cycle (SDLC). Additionally, best practices for evaluating and testing database security, including penetration testing to uncover vulnerabilities and stress testing to assess performance under load, are discussed. By synthesizing these strategies and survey feedback, this paper provides a comprehensive approach to enhancing database security, ensuring data protection, and maintaining system resilience against evolving cyber threats

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Ahmed Naguib mail -

Haba K. Aslan mail -

Khaled M. Fouad mail

link https://doi.org/10.54216/JCIM.160114

Volume & Issue

Vol. Volume 16 / Iss. Issue 1

Details open_in_new

Metaheuristic Optimization Review | 2025

Review: AI-Driven Advances in Physiotherapy Stimulation Devices

This embraces rehabilitation medicine as it significantly boosts the doctor's way of working and presents new ways or new tools that the doctor might consider to enhance or augment the results that the patients benefit from physically. This review focuses on applying AI technologies such as robotic systems, virtual reality (VR), machine learning algorithms, wearable devices and predictive analytics in different fields, including stroke recovery, neuromuscular disorder rehabilitation, orthopedic and critical care. AI utilization improves patient treatment, the accuracy of therapy, and the administration of evaluation to deal with issues such as a lack of therapists, comparative analysis, and the expensive nature of conventional treatment. Although the outlook for its progress is positive, there are twofold problems: ethical questions, data privacy and policy concerns, and regulatory challenges. Future directions indicate directions for research and practice and call for increased interdisciplinary cooperation, large-scale validation studies and appropriate ethical standards to unlock the full potential of AI in reinventing rehabilitation medicine and rendering patient-centered care possible.

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Mohamed Saber mail

link https://doi.org/10.54216/MOR.030103

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2024

The impact of AI-based cyber security on the banking and financial sectors

BD and AI are now transforming the banking and finance industry at a very fast pace, which is leading to change in the banking and finance institutions. This change is making them better, customer-oriented and financially rewarding organizations. Big data and AI have been useful in the banking and financial institutions to assess and manage the risks. Through the analysis of big amounts of unstructured data in real time, AI algorithms are capable of identifying risks. This makes it easy to put preventive measures in place to avert the risks. In addition, big data and AI have come a long way in solving the problem of fraud in banking and finance. This paper showed how big data and AI improve risk management, Cyber threat, and fraud in banking and finance by using data analysis and data pattern identification in real-time. That is why our work emphasizes the importance of implementing secure privacy and explaining the AI algorithm to eliminate ethical and Cyber security issues. Using analytical approaches, AI can identify the transactions with the help of comparison with the previous data and the behavioral characteristics related to the fraud. This approach to fraud prevention has been effective in reducing losses while at the same time improving the customer’s confidence in the company. On the other hand, there are disadvantages of big data and AI such as privacy, security, and ethical issues. Measures that can be used to safeguard customer information have to be employed in order to effectively safeguard the consumer data. Furthermore, transparency and accountability of the AI algorithms are crucial in order to avoid unfair decisions.

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Haya saleh alrafi mail -

Shailendra Mishra mail

link https://doi.org/10.54216/JCIM.140101

Volume & Issue

Vol. Volume 14 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2024

Anomaly-Based Intrusion Detection Systems Using Machine Learning

With the increased use of the Internet, unauthorized access has increased, allowing malicious users to hack networks and carry out malicious activities. One of the essential modern approaches in today's cybersecurity efforts is the limitation of access by suspect users. In this study, the approach toward real-time intrusion detection was to consider behavioral patterns of past users on the network. We classified the users as two categories: intervention and non-intervention, and employed the machine learning techniques Artificial Neural Networks [ANN], Support Vector Machines [SVM], and Decision Trees [DT]. The Decision Trees model was chosen as it had a mature capability concerning complex pattern recognition and an enhancement capability of the intrusion detection systems. The efficiency of these algorithms is examined via the key performance metrics: confusion matrix, F1-score, and Area Under the Curve [AUC]. Decision Tree, which came up as the best model for both the training and testing phases, produced an outstanding F1-score of 99.96% and AUC score of 99.93% in the testing phase. SVM and ANN gave good results; the F1 scores of SVM and ANN in the testing phase were 92.76% and 93.33%, while the AUC was 90.57% and 94.78%, respectively. This research will enlighten us on the influence of machine learning on the scope of intrusion detection, fostering more development efforts toward more responsive and dynamic intrusion detection systems. The comparative evaluation of these models will help in providing vital information for the further enhancement of cybersecurity strategies, ensuring better defenses against these ever-evolving cyber threats.

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Alsamir Alqahtani mail -

Hanan AlShaher mail

link https://doi.org/10.54216/JCIM.140102

Volume & Issue

Vol. Volume 14 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2024

Securing the Digital Commerce Spectrum and Cyber Security Strategies for Web, E-commerce, M-commerce, and E-mail Security

Secure protection of sensitive data and financial transactions is of the utmost importance in the dynamic world of online trade. In this study, we present a full-stack security architecture that uses five separate algorithms: ECF, Transaction Anomaly Detection, Adaptive Threat Intelligence, Behavioral Biometric Authentication, and Dynamic Encryption Protocol. By creating encryption keys on the fly while the user logs in, the DEP method lays a solid groundwork for safe data transfer. Behavioral biometric authentication (BBA) uses DEP output to verify users based on their distinct behavior, which is an extra layer of security. By combining both current and past threat information, the ATI algorithm is able to constantly adjust security protocols, providing a preventative shield against new dangers. TAD is an expert at detecting anomalies in online purchases, which helps keep financial transactions honest. When ECF and DEP work together, they filter email content, making communication more secure. Flowcharts help to illustrate the interactions between various algorithms, which helps to understand their operations in detail. Every algorithm's importance is brought to light by an ablation study, which shows how each one contributes and how they all work together to affect the overall security posture. The suggested security framework outperforms the state-of-the-art in terms of efficacy, adaptability, and usability, according to performance evaluations conducted using a number of metrics. These findings can help decision-makers build a strong security plan that is specific to the challenges of online shopping. To conclude, the suggested framework is an integrated and complementary strategy that will strengthen online trade in the face of several cyber dangers while simultaneously protecting the confidentiality, authenticity, and availability of all associated communications and transactions.

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Rohit Pachlor mail -

R. Mohanraj mail -

K. Sharada mail -

Savya Sachi mail -

K. Neelima mail -

Punyala Ramadevi mail

link https://doi.org/10.54216/JCIM.140103

Volume & Issue

Vol. Volume 14 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2024

Secure Medical Records Through Big Data Analytics and Blockchain

As healthcare shifts to digital platforms, the healthcare sector is suffering from multiple security vulnerabilities that make it vulnerable to various types of cyberattacks. Therefore, robust security solutions need to be implemented to resolve these vulnerabilities. In this context, blockchain technology has emerged as a promising solution in several sectors, including the healthcare sector. This study harnesses blockchain technology to improve medical record management. By integrating blockchain, we address issues like data breaches and inefficient data sharing. The proposed study ensures a seamless health record exchange that is secure, transparent, and beneficial to both patients and healthcare providers. The goal of this study is to empower patients to be more in control of their data while streamlining processes and enhancing security for healthcare institutions. Medical records are increasingly secure, interoperable, and accessible when blockchain technology and big data are used. According to the study, healthcare workers recognize the importance of protecting medical records through blockchain technology and big data, which can improve security, interoperability, and accessibility. This minimizes concerns related to data manipulation while providing a more cost-effective and efficient method of managing medical records. Medical records management is made more cost-effective and efficient by reducing concerns related to data manipulation.

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Hamad Almani mail -

Shailendra Mishra mail -

Aditi Singh mail

link https://doi.org/10.54216/JCIM.140104

Volume & Issue

Vol. Volume 14 / Iss. Issue 1

Details open_in_new

International Journal of BIM and Engineering Science | 2024

Enhancing the Syrian Construction Industry through Augmented Reality: Applications and Challenges

The Syrian construction industry faces numerous challenges that hinder its efficiency and productivity, including outdated practices and a lack of modern technological integration. This study explores the potential of Augmented Reality (AR) to enhance industry practices through a descriptive analytical approach using surveys and case studies. Key findings indicate a growing awareness and favorable perception of AR among construction professionals, pinpointing substantial benefits such as enhanced project visualization, safety, and resource management. Despite these positives, significant barriers such as technological infrastructure and expertise gaps limit AR's widespread adoption. The study concludes that AR offers significant potential to revolutionize the Syrian construction industry, recommending focused governmental and private sector investment in technological training and infrastructure to leverage these benefits fully. These findings suggest that AR could be pivotal in transforming construction practices in emerging markets like Syria

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Mirna Hammoudi mail -

Abdussalam Shibani mail

link https://doi.org/10.54216/IJBES.080104

Volume & Issue

Vol. Volume 8 / Iss. Issue 1

Details open_in_new

Journal of International Economics Research | 2026

Ways to Improve Uzbekistan’s Logistics Indicators for the Development of International Trade

The paper advances an analysis of the role of logistics in respect to various factors contributing to the export performance of Uzbekistan. The study relied on annual time-series data obtained from 2007 to 2023, and descriptive statistics, correlation analysis, and ordinary least-squares regression were employed to take into consideration the effects of infrastructure quality, transportation efficiency, and technology availability on exports of goods and services in relation to GDP. The empirical findings suggest that via Internet usage, technology availability positively with statistical significance affects export performance. Infrastructure quality has a positive, albeit statistically weakly significant association with exports, and transportation efficiency negatively associates weakly. It can be concluded based on the studies’ results that technological advancement is the main factor affecting export competitiveness, while infrastructure and transport systems mainly contribute to this long-term. This analysis is of major policy importance, stressing further improvements in digital infrastructure as well as investments in logistics and transport systems to cater for sustainable export growth in Uzbekistan.

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Feruza Sayidova mail

link https://doi.org/10.54216/JIER.040102

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

International Journal of BIM and Engineering Science | 2024

Proposal for Temporary Safety Facilities for Fall Protection Using 4DBIM to Meet OSHA Standards

Temporary Safety Facilities (TSFs) constitute a vital support infrastructure ensuring the safety of workers throughout construction operations, with the overarching goal of averting accidents onsite; However, the schedule and location of installation and dismantling of technical support facilities is still based on work experience, and is often omitted from official drawings or documents. This leads to thousands of accidents in the construction sector, especially in small and midsize construction enterprises construction firms due to many limiting factors; Therefore, this study proposes automatic workspace planning for temporary safety facilities (in our case guardrails for fall protection) based on construction activities, which is a structured approach for SMEs working in construction to practice Occupational Health and Safety (OHSA). By employing Building Information Modeling (BIM), safety facilities can be simulated and visually incorporated into the assigned workspace. Utilizing 4D-BIM, the devised system facilitated the installation of temporary safety features, such as fall protection railings, which underwent validation via a case study involving a mall project. The results indicated that integrating temporary safety facilities with the model enhances comprehension of safety protocols throughout project execution. Additionally, temporary facility workspace planning provides an affordable approach that stimulates safety practices; Thus, significantly enhancing the management effectiveness of construction safety measures.

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Dima Salameh mail -

Lama Saoud mail

link https://doi.org/10.54216/IJBES.080105

Volume & Issue

Vol. Volume 8 / Iss. Issue 1

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2024

Intelligent System for the Classification of Arterial Blood Pressure Waveform Abnormalities Due to Mistiming in Intra-Aortic Balloon Pump

Cardiovascular diseases detection or diagnosis on appropriate time is crucial to avoid health complications. In this study, an advanced procedure for classifying changes in the blood pressure has been used analyzing the wave-forms inside the arterial system where such variation can occur due to improper timing in intra-aortic balloon pump (IABP) control. Inaccurate pressure extends with probable injury can be caused by improper timing in the heart valve in both pumping and compression of the balloon. This investigation focuses on accurately recognizing and classifying any irregularities in the artery wave-forms in IABP in the blood pressure initiated by mistiming. Accumulated blood pressure records are used for the progression of providing information to IABP trainer. The wave-forms require pre-handling employing image digitizing software to acquire automated identifications. Any undesirable image features have been removed using Wavelet in MATLAB software. Afterward, such features can be employed to develop a technique for arrangement depending on neural networks. The artificial neural network technique has used marked data to properly detect irregularities in wave-forms in vascular blood pressure due to improper IABP timing. As a result, the validation has proved to appropriately recognize and classify such anomalies, denoting a considerable prospect to improve patient protection with an efficacy of treatment in the area of cardiovascular prescription.

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Zainab A. Wajeeh mail -

Sadiq J. Hamandi mail -

Wisam S. Alobaidi mail

link https://doi.org/10.54216/JISIoT.130105

Volume & Issue

Vol. Volume 13 / Iss. Issue 1

Details open_in_new