Design of Artificial Intelligence-Based Biometric Authentication System using Deepfake Detection Model for Patient Data Privacy Protection and Identity Verification

Louai A. Maghrabi

doi:https://doi.org/10.54216/JCIM.160119

International Journal of Neutrosophic Science | 2025

Analyzing the local Lindelöf proper function and the local proper function of deep learning in bitopological spaces

It is essential to create new mathematical strategies to deal with everyday problems since they require a lot of data and ambiguity. The best tool for doing this is proper functions, which are the most common mathematical technique. In order to generate suitable functions, we investigate several set operators. A connection between symmetry and certain types of proper functions and their classical topologies can be made. As a result of this symmetry, we can examine the traits and behaviors of traditional topological notions through settings, and vice versa. We describe a new class of proper functions in this paper and launch a preliminary investigation into them. These functions are referred to as pairwise local proper functions and pairwise local Lindel¨of proper functions in bitopological spaces. In general topology, we also establish the connection between this new class of proper functions and other classes of generalized functions already in existence. Regarding the new ideas, a number of relationships, necessary and sufficient conditions, examples and counter-examples are provided. In addition, a different argument for the pairwise regularity of a pairwise Hausdorff and pairwise locally compact bitopological space is presented. As part of this research, we also look at the images and inverse images of specific bitopological features under these functions. A few product theorems pertaining to these concepts were finally discovered.

groups

Ali A. Atoom mail -

Hamza Qoqazeh mail -

Eman Hussein mail -

Anas Owledat mail

link https://doi.org/10.54216/IJNS.260223

Volume & Issue

Vol. Volume 26 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2025

Sensor-Based Spatio-Temporal Human Activity Recognition: A Systematic Review of Advancements, Challenges, and Future Directions

Spatio-temporal human activity recognition (HAR) is an emerging field that uses spatial and temporal data to identify and classify human activities accurately. It has been effectively applied in areas like healthcare for monitoring daily activities, detecting anomalies, and aiding rehabilitation with real time feedback. However, there is a gap in research specifically focusing on integrating spatio temporal data with advanced machine and deep learning techniques for HAR based on sensor data. Existing reviews do not comprehensively cover spatio-temporal HAR based on sensor data, resulting in a lack of summaries on recent models, datasets, sensor technologies, applications, and machine/deep learning techniques used in this field. This systematic review provides a comprehendsive overview of spatio-temporal HAR based on sensor data, tracing its development from the origin of sensor-based spatio-temporal HAR field to the present. It highlights the main challenges in spatio- temporal HAR. The review also examines model trends over the years, including the distribution of models used in HAR and the identification of those frequently combined to form hybrid models. Additionally, it analyzes accuracy trends of the commonly used datasets and identifies the datasets that are widely used in spatio-temporal HAR research. Furthermore, various application domains and sensor technologies used in spatio-temporal HAR are identified.

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Asmaa Badran mail -

Ahmad Salah mail -

A. A. Soliman mail -

Dina A. Elmanakhly mail -

Ahmed Fathalla mail

link https://doi.org/10.54216/JISIoT.160221

Volume & Issue

Vol. Volume 16 / Iss. Issue 2

Details open_in_new

International Journal of Wireless and Ad Hoc Communication | 2025

FPGA Implementation of High Performance Accurate and Approximate Signed and Unsigned Multipliers using Structure of LUT configurations

A recent study examined the applications of multiplication and division in video and image manipulation and there has been mention of machine learning. DSP blocks that function as high performance multipliers are given by FPGA providers. However routing lag time and inefficiencies, particularly for lower bit width multiplications, might emerge from the fixed placements and restricted number of these FPGA multipliers, raising power consumption. FPGA companies offer IP cores that are soft made especially for multiplication to solve this problem. Even if these IP cores have improved over time, they can yet be improved. This can be accomplished by creating low latency, accurate, and core multiplier topologies that maximize the space of FPGA and take advantage of its architectural characteristics, like rapid carry chains and look up table structures. These architectures seek to improve overall efficiency by lowering the crucial path delay and multiplier resource consumption. Here a proposed method for building accurate and approximate signed and unsigned multipliers for an eight bit configuration is presented. This entails changing the LUT 6 architecture to use a one LUT 5 with multiplexers in place of a dual LUT 5 with multiplexers. Using Xilinx software, the design was built in Verilog HDL and synthesized. At the conclusion of the process, variables including area, delay and power were compared.

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Saravanan V. mail -

Elarmathi S. mail -

Rajalakshmi V. R. mail

link https://doi.org/10.54216/IJWAC.090202

Volume & Issue

Vol. Volume 9 / Iss. Issue 2

Details open_in_new

International Journal of Wireless and Ad Hoc Communication | 2025

An Efficient Detection of Copy-Move Forgery Using Phase Correlation

Creating images is one of the main focuses of digital image processing. There are multiple techniques to spot image fraud. This work proposes a new approach to detect attacks that mimic Copy-Move forgeries. The proposed method applies DWT on the input image to create a reduced dimensional representation of the image. After that, the compressed image is divided into overlapping blocks. After these blocks are sorted, phase correlation is utilized as a similarity criterion to find duplicate blocks. Due to DWT usage, the lowest-level picture representation is first employed for detection. This work also covers the examination of numerous limits that are imposed to the input image, and the results are used in the analysis that follows.

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L. Chitirap Paavai mail -

V. Vadivu mail -

L. Krishnan mail

link https://doi.org/10.54216/IJWAC.090203

Volume & Issue

Vol. Volume 9 / Iss. Issue 2

Details open_in_new

International Journal of Wireless and Ad Hoc Communication | 2025

Joint PAPR and Spectrum Sensıng in CRNS: A VLSI-Based Approach for Secondary User Integration

In Cognitive Radio Networks (CRNs), Peak-to-Average-Power-Ratio (PAPR) reduction is crucial for mitigating distortion in signals while optimizing spectral efficiency. This work offers a novel strategy for effectively reducing that PAPR in CRN systems, especially when secondary users are incorporated, by utilizing VLSI (Very-Large-Scale Integration) design approaches. The proposed strategy investigates VLSI methods for PAPR reduction, such as Partial-Transmit-Sequence (PTS) techniques. The system is appropriate for CRN applications because it can accomplish real-time PAPR reduction while preserving low power consumption and compact size by implementing these approaches in VLSI hardware. This could entail particular strategies for controlling PAPR with secondary users, such as joint PAPR and spectrum sensing approaches, dynamic power allocation, or user scheduling algorithms. Utilizing the predetermined values of pilot tones, the suggested decoder investigates every possible combination of weighting variables to determine which combination the transmitter has chosen and employed. There appears to be no data rate loss with the proposed decoder since it does not require any more pilot tones. This study next gives a digital execution of the described PTS decoder and illustrates its low power qualities, as well as the design and the encoder required at the transmitter to operate the suggested system is being developed using VLSI. The suggested architecture makes it easier for SUs to integrate with CRNs seamlessly. It allows SUs to effectively take advantage of available spectrum opportunities while complying with CRN restrictions and reducing interference with primary users by tackling PAPR and spectrum sensing concurrently. Furthermore, the study discusses the difficulties of incorporating secondary users into CRNs while retaining PAPR management.

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P. Shanmuga Sundaram mail -

M. Vasanthi mail -

P. Sangeetha mail

link https://doi.org/10.54216/IJWAC.090204

Volume & Issue

Vol. Volume 9 / Iss. Issue 2

Details open_in_new

International Journal of BIM and Engineering Science | 2025

HBIM’s Role in the Conservation and Restoration of Archaeological Buildings: Case Study: Omar Al-Khyam Hotel in Damascus

Historic Building Information Modelling (HBIM) has emerged as a critical methodology for preserving cultural heritage by documenting the condition of building materials, assessing the extent and causes of damage, and managing restoration and maintenance activities. By integrating advanced technologies such as thematic mapping and 3D modeling, HBIM offers a comprehensive approach to analyzing and conserving historic structures. This research highlights the significance of HBIM in preserving the integrity and sustainability of heritage buildings, emphasizing its role in maintaining their historical and cultural value. The study focuses on the Omar al-Khiam Hotel in Damascus, an iconic historic building requiring urgent restoration. A detailed photographic survey was conducted using a mobile camera, with images processed through AGISOFT METASHAPE and enhanced using Photoshop. These data were used to create a precise 3D model in EDIFICIUS HBIM software, incorporating detailed assessments of material conditions, including corrosion, damage, leakage, and environmental pollution. Based on this analysis, a restoration and maintenance schedule was developed to guide the rehabilitation process and ensure effective project management. The findings demonstrate the effectiveness of HBIM in providing a dynamic and collaborative platform for heritage conservation. The study underscores the need for integrating diverse data sources and engaging stakeholders in restoration efforts. While HBIM offers significant advantages, challenges such as data precision and software complexity were identified. Future research should focus on enhancing HBIM’s predictive capabilities for long-term material degradation and exploring its application across diverse heritage sites to refine conservation strategies further.

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Rasha Daoud mail -

Sonia Ahmad mail -

Khaled Alfahed mail

link https://doi.org/10.54216/IJBES.110101

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

A Multi-Year Financial Performance Comparison of Banks: Neutrosophic Approach

In this work, a comparison plan of Agrobank and NBU for the financial years 2021, 2022, 2023, and 2024 is provided via neutrosophic approach in terms of indicators of profitability, liquidity, and solvency. The profits of the banks are analyzed through the application of net profit margin, profitability coefficient, absolute liquidity ratio, and solvency ratios. The economic ratios on profitability and liquidity point out that the NBU bank is performing better than the Agrobank but solvency ratios depict that Agrobank is more stabilized than NBU. This framework will avail a relative comparison of the two banks in terms of the opportunities, threats, strengths and weaknesses of each. In this way, findings can improve the understanding of banking industry’s performance in Uzbekistan and provide useful information to policuemakers and researchers. Continuation of the study could include the consideration of factors outside the firm to determine how they affect financial performance.  

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Samandarboy Sulaymanov mail

link https://doi.org/10.54216/IJNS.260225

Volume & Issue

Vol. Volume 26 / Iss. Issue 2

Details open_in_new

International Journal of BIM and Engineering Science | 2025

Proposed BIM–CMMS Framework for Facility Management in Digital Transformation Era

Digital transformation is crucial for construction projects due to its numerous benefits, including increased productivity and improved collaborative environments. This research discusses the stages, components, and strategies that lead construction projects to digital transformation. Furthermore, it aims to advance the technological process of 3D digitization in built environments and simplify management operations in the construction phase through digital methodologies. To achieve this, an integrated framework combining Building Information Modeling (BIM) and Computerized Maintenance Management Systems (CMMS) applications is proposed. By using these integrated models, facility management is simulated within a 3D environment via a CMMS. The results indicated that digital models and BIM could indeed be integrated through direct linkage mechanisms without compromising the efficiency of information synchronization and management. This 3D representation allowed for a better understanding of dynamics and spatial interactions, facilitating quicker identification of potential issues and more efficient maintenance operations. Therefore, integrating these advanced digital models not only improves operational efficiency, but also enhances collaborative environments. The proposed model represents what is known as a Digital Twin, a comprehensive system that manages all information flows associated with a building throughout its lifecycle.

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Nisren Sharief mail -

Bashar Abd Alnoor mail -

Khaled Al-fahed mail

link https://doi.org/10.54216/IJBES.110102

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new

International Journal of BIM and Engineering Science | 2025

Ethics and Data Privacy in BIM

The rapid advancement of Building Information Modeling (BIM) has revolutionized the construction industry, enabling collaborative workflows among architects, engineers, contractors, and clients. However, it has introduced critical ethical and legal challenges related to data ownership, intellectual property rights, and privacy. This thesis explores these issues by analyzing legal frameworks, contractual agreements, and ethical considerations governing BIM data ownership. It examines stakeholder roles, recurring disputes, and the impact of BIM’s collaborative environment, with a focus on global and regional contractual adequacy. Findings reveal frequent conflicts between engineering teams and clients over intellectual property, highlighting the need for explicit contractual provisions and ethical guidelines addressing privacy, consent, and data control. The study proposes actionable recommendations to establish a robust framework for equitable, transparent, and sustainable data management in the construction sector.

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Nura ALHallak mail -

Hassan M. Ali mail -

Mohamed Shaban mail

link https://doi.org/10.54216/IJBES.110103

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2025

Design of Artificial Intelligence-Based Biometric Authentication System using Deepfake Detection Model for Patient Data Privacy Protection and Identity Verification

In biometric applications, deepfake detection is a major field of research, as it is vital to certify the authenticity and integrity of biometric data. The manipulation of biometric information, like facial and fingerprint images, presents a critical attack on patient confidentiality and healthcare security. Deepfake is one of the manipulated digital media, for instance, an image or video of an individual can be substituted with a resemblance of another being. On the other hand, the growth of deepfake technology sets major attacks on biometric security by making hyper-realistic fake individualities that can deploy authentication methods. For deepfake recognition, a vital method in biometric applications utilizes a machine learning (ML) system, mainly deep learning (DL) that might study to differentiate amongst real and fake biometric data. In this manuscript, we present a Design of an Artificial Intelligence-Based Biometric Authentication System for Deepfake Detection with Patient Data Privacy Protection and Identity Verification (AIBADD-PDPPIV) algorithm. The main intention of the AIBADD-PDPPIV model is to deliver a secure and efficient biometric authentication approach that contributes to the advancement of privacy-preserving biometric security in healthcare systems. To accomplish this, the AIBADD-PDPPIV method employs an image preprocessing stage using the adaptive median filter (AMF) to reduce noise and enhance essential biometric features. For feature extraction, the vision transformer (ViT) model can be employed to capture intricate spatial dependencies in biometric images. Moreover, the multi‐head attention mechanism-based bidirectional gated recurrent unit (MA-BiGRU) model is exploited for deepfake detection and authentication processes. Eventually, the hyperparameter tuning process is accomplished through the pelican optimization algorithm (POA) to improve the detection performance of the MA-BiGRU model. To show the improved performance of AIBADD-PDPPIV model, a wide sort of simulations take place and the outcomes are inspected under numerous measures. The comparison study reported the betterment of AIBADD-PDPPIV system under various metrics.

groups

Louai A. Maghrabi mail

link https://doi.org/10.54216/JCIM.160119

Volume & Issue

Vol. Volume 16 / Iss. Issue 1

Details open_in_new