Journal articles - International Journal of Wireless and Microwave Technologies

All articles: 674

A Deep Analysis of Image Based Video Searching Techniques

A Deep Analysis of Image Based Video Searching Techniques

Sadia Anayat, Arfa Sikandar, Sheeza Abdul Rasheed, Saher Butt

Scientific article

For many applications like brand monitoring, it’s important to search a video from large database using image as query[1]. Numerous visual search technologies have emerged with the passage of time such as image to video retrieval(I2V), video to video retrieval(V2V), color base video retrieval and image to image retrieval. Video searching in large libraries has become a new area of research. Because of advance in technology, there is a need of introducing the well established searching techniques for image base video retrieval task. The main purpose of this study is to find out the best image based video retieving technquie. This research shows the importance of image base video retrieving in the searching field and addresses the problem of selecting the most accurate I2V retrieval technique. A comparison of different searching techniques is presented with respect to some characteristics to analyze and furnish a decision regarding the best among them. The accuracy and retrieval time of different techniques is different. This research shows that there are a number of visual search techniques, all those techniques perform same function in different way with different accuracy and speed. This study shows that CNN is best as compare to others techniques. In future, the best among these techniques can be implemented to reduce the searching time and produce the promising result.

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A Density Control Algorithm For Wireless Sensor Network

A Density Control Algorithm For Wireless Sensor Network

Danyan Luo, Haiying Zhou, Zhan Zhang, Decheng Zuo

Scientific article

If all nodes of a sensor network worked simultaneously, not only there would be a lot of redundant information, but also they would have great adverse impact on network throughput, bandwidth, latency, energy and network lifetime. Consequently, density control technology is necessary for sensor networks, because it can reduce the number of active sensor nodes under the precondition of ensuring network coverage and network connectivity. This paper proposes SNDC (Sensor Network Density Control), a location-free and range-free density control algorithm for wireless sensor network to keep as few as possible sensors in active state to achieve an optimal complete connected coverage of a specific monitored area by periodically sending three beacons of different transmission ranges. Inactive sensors can turn off sensing modules to save energy and sleep. Simulation results show that this algorithm can prolong the network lifetime and guarantee the small number of active nodes and complete network coverage.

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A Design Approach of GSM, Bluetooth and Dual band Notched UWB Antenna

A Design Approach of GSM, Bluetooth and Dual band Notched UWB Antenna

Durgesh Katre, Rekha Labade

Scientific article

In this paper, printed GSM Bluetooth dual band notch UWB antenna is presented. In this prototype corner cut patch for Bluetooth application and dual band notch characteristics of UWB antenna perform by inverting U- Slot in the radiation patch of antenna. With the enclosing of λ/4 stub in the patch of antenna for GSM (1.710-1.885 GHz) band operation. Simulation results show that the antenna yields an impedance bandwidth of 2.4-2.48 and 3-11 GHz with -10 dB reflection coefficients, except for the dual notched bands of 3.3-3.7 for Wi-MAX and 5.15-5.825 GHz for WLAN. The electrical characteristics in frequency domain show suitability of this antenna for use in UWB systems.

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A Design of Trust Degree Transfer Algorithm for P2P Network

A Design of Trust Degree Transfer Algorithm for P2P Network

Wang Hao-yu, Ge Tong-min, Ji Xiao-juan, Hu Bao-an

Scientific article

The design of mechanism is used to calculate node reliability of incredible P2P network. The mechanism through matrix shows the trust relationship between nodes in the network, through matrix operation realizes the trust transfer process fast, and through a trusted server provides calculation service of trust degree for nodes in P2P network.

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A Discussion of a 60GHz Meander Slot Antenna for an RFID TAG with Lumped Element

A Discussion of a 60GHz Meander Slot Antenna for an RFID TAG with Lumped Element

Omrane NECIBI, Abdelhak FERCHICHI, Tan-phu VUONG, Ali GHARSALLAH

Scientific article

In this paper, a novel approach to design an antenna for a transponder in radio frequency identification (RFID) is proposed. This approach is based on using a meander slot patch with a coplanar waveguide excitation (CPW). The RFID frequency chosen is the free 60 GHz band. The proposed circuit does not require complex package or bonding, thanks to the on-chip antenna, and it does not need battery. This technology is characterized by the low-cost, low-weight and low-area occupation. These particular specifications are important of this micro-RFID, especially if produced in large scale for the mass-market. Since the model of antennas in silicon technology is one of the main challenges, particularly for this proposal. The structure is simulated by using Computer Simulation Technology (CST). The antenna size is 1.95 * 1.99 mm2.This proposed antenna presents again which means a possibility to increase the readable range.

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A Group-oriented Access Control Scheme for P2P Networks

A Group-oriented Access Control Scheme for P2P Networks

Wang Xiaoming, Cheng Fan

Scientific article

A group-oriented access control scheme is proposed for P2P (peer to peer) networks. In the proposed scheme, authentication control, admission control and revocation control are used in order to provide security services for P2P networks. Moreover, the proposed scheme can simply and efficient establish share key between two members without interactions, therefore it can perform secure communications with them. The analysis of security and performance shows that the proposed scheme not only can realize authentication and secure communication, but also can easily and efficiently add new group members and revoke malicious group members. Therefore, it is more efficient, and more practical protocol for P2P networks.

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A Hybrid MAS-CBR Framework with Optimization for Adaptive Supply Chain Design and Management

A Hybrid MAS-CBR Framework with Optimization for Adaptive Supply Chain Design and Management

Rajbala, Pawan Kumar Singh Nain, Avadhesh Kumar

Scientific article

Global supply chains are increasingly characterized by complexity, uncertainty, and vulnerability to disruptions, creating a pressing need for intelligent, adaptive systems that support decentralized decision-making and real-time control. This paper develops a new framework that integrates Multi-Agent Systems (MAS) with Case-Based Reasoning (CBR) to address these challenges. The model leverages autonomous agents representing suppliers, manufacturers, distributors, retailers, and coordinators that negotiate through defined protocols while embedding CBR mechanisms to retrieve and adapt historical supply chain cases for enhanced responsiveness. An optimization layer, guided by both agent heuristics and case-driven initial solutions, targets key objectives such as cost minimization, lead-time reduction, and resilience improvement. Simulation experiments were conducted under both static and dynamid environments with disruptions including supplier failures and demand fluctuations. Results demonstrate that the proposed framework achieves convergence up to 34- 41% faster than heuristic-only baselines (p<0.05) and sustains solution quality with supply chain sizes increasing from 50 to 500 agents, indicating near-linear scalability. Comparative analysis further highlights adaptability in dynamic contexts and robustness under uncertainty. A case study illustrates practical deployment and validates its effectiveness. The findings provide evidence of a powerful synergy between MAS and CBR, with implications for next-generation supply chain intelligence.

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A Hybrid Mimo Technique for Better Ber in High Data Rate Wireless Communication System

A Hybrid Mimo Technique for Better Ber in High Data Rate Wireless Communication System

Kehinde Odeyemi, Erastus Ogunti

Scientific article

The need for high data rate and better quality of service in wireless communications has become imperative in the past few years judging by user demand. Obtaining these requirements has become very challenging for wireless communication systems due to the problems of channel multi-path fading, higher power and bandwidth limitations. One of the most promising solutions to this problem is the Multiple Input Multiple Output (MIMO) system. This paper proposed a combined spatial multiplexing MIMO scheme with beamforming for high data rate wireless communication. The proposed transmission scheme combines the benefits of both techniques resulting in the system ability to transmit parallel data streams as well as provide beamforming gain. Actually, these diverse techniques, share the same requirement of multiple antenna elements, but differ in the antenna element spacing necessary for the different schemes to work. Thus, smart antenna arrays were proposed as a possible solution and were adopted at both the transmitter and the receiver. The proposed hybrid technique provides better Bit Error Rate (BER) performance than the conventional MIMO, spatial multiplexing or beamforming technique alone under the same simulation environment.

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A Hybrid Selection Approach Based on Advanced Antenna Technologies for Cellular LTE-A

A Hybrid Selection Approach Based on Advanced Antenna Technologies for Cellular LTE-A

Mina Malekzadeh

Scientific article

While addressing cellular network performance issues, resolving problems with coverage and capacity is critical. The coexistence of cellular networks and smaller femtocells working within the macrocell area is among the alternative solutions. The simultaneous functioning of macrocells and femtocells, however, introduces new technical challenges that pose serious concerns about the efficiency of cellular networks. Therefore, this work proposes a hybrid approach based on variant advanced antenna technologies including MIMO methods and antenna systems for the deployment of femtocells and macrocells. To accomplish this, three distinct LTE-A network models with and without femtocells are set up with different architectures for high-density areas. The models further cover tri-sector and omnidirectional antenna systems to analyze the relevant effects on the performance of the LTE-A macrocells as well as femtocells. Also, to extend the analysis, integration of different MIMO methods for the models is provided. The networks are implemented and the link performance evaluation is carried out with regard to spectral and energy efficiency, cell and user throughputs, fairness, and SINR. The results contribute to determining the performance gains and energy saving of the LTE-A femtocells as well as macrocells by employing different advanced antenna technologies.

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A Hybrid Stacked Ensemble Framework for Fraud Detection in Nigerian Financial Ecosystems: Evaluation with Localized Synthetic Data

A Hybrid Stacked Ensemble Framework for Fraud Detection in Nigerian Financial Ecosystems: Evaluation with Localized Synthetic Data

Jumoke Soyemi, Jamiu R. Olasina

Scientific article

Financial fraud presents a major challenge to financial establishments, with Nigerian banks losing over ₦685 million to digital fraud in 2023. Traditional rule-based detection systems have high false-positive rates and limited adaptability; meanwhile, existing machine learning models are generally trained on non-localized datasets that ineffectively represent African fintech ecosystems. This study proposes a Hybrid Stacked Ensemble framework for fraud detection that improves detection accuracy, robustness, and explainability in localized financial environments. The proposed framework combines Random Forest, Gradient Boosting, and Extra Trees as base learners with XGBoost as the meta-classifier and integrates SHAP for model explainability. Performance was evaluated using the Kaggle credit card fraud dataset (284,807 transactions; 0.17% fraud) and a newly curated Nigerian synthetic dataset (150,000 transactions; 1.12% fraud) incorporating localized fraud patterns such as POS, USSD, mobile money, and rural–urban transaction disparities. Class imbalance was addressed using SMOTE oversampling, random undersampling, and cost-sensitive learning. On the Kaggle dataset, the Hybrid Ensemble achieved 99.96% accuracy, 97.14% precision, 79.70% recall, an F1-score of 0.880, and an AUC-ROC of 0.986, outperforming the best individual classifier in recall and AUC-ROC. On the Nigerian dataset, where individual classifiers achieved recall below 3.1%, the proposed framework attained 64.10% recall, an F1-score of 0.460, and an AUC-ROC of 0.866, representing improvements of 106.77% in recall and 488.57% in F1-score over XGBoost. Ablation studies and paired t-tests (p < 0.001) confirmed the effectiveness of the stacking strategy. The study contributes a localized Nigerian fraud dataset, a hybrid stacked ensemble architecture that exploits classifier diversity for improved fraud detection, and an explainable AI framework that enhances transparency, accountability, and regulatory compliance. Deployment as a containerized Streamlit application with JWT authentication demonstrates the framework's practicality as a scalable, explainable, and deployment-ready solution for fraud detection in Nigeria and similar African financial ecosystems.

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A Lattice-Enhanced Dynamic Threshold CRT-Based Secret Sharing for Mobile Agent Security in Decentralized Networks

A Lattice-Enhanced Dynamic Threshold CRT-Based Secret Sharing for Mobile Agent Security in Decentralized Networks

Pradeep Kumar, Kakoli Banergee, Bijendra Tyagi, Anuradha Singh, Priyank Sirohi

Scientific article

A mobile agent is a small piece of program that migrates automatically among different platforms, on which it executes assigned tasks. Mobile agents migrate in malicious and unsecure networks. So, there will be chances of compromising mobile agent as well as host computer. So, during the mobile agent executing life cycle there will be chances of stealing of confidential information about host and agents. The application of mobile agents is increasing day by day in various domains such as distributed computing, cloud computing and Internet of Things. In this article, we propose a method based on lattice-based dynamic threshold Chinese Remainder Theorem for the security of mobile agents. The combination of dynamic threshold, lattice-based encryption-decryption and Chinese remainder theorem provides optimal security as compared to traditional approach. After the analysis of turnaround time of creation of share, distribution and recreation of secret is optimal as compared to traditional approach. Another comparison is also done on the basis of memory utilization, computational cost, communication overhead and scalability of proposed method. Proposed approaches provide effectiveness of security for mobile agents in a decentralized and malicious environment. The framework was implemented in Python and analyzed with 10 to 1000 mobile agents. With 1000 mobile agents, the framework gains a turnaround time of 12.4 ms, memory utilization of 18.7 MB, and CPU efficiency of 91.3%, demonstrating better scalability and computational cost compared with Shamir Secret Sharing, Integer CRT, Homomorphic Encryption, Vectorized Tree Parity Machine and Boneh Goh Nissim techniques. Performance evaluation based on computational cost, communication overhead and scalability further shows the effectiveness of the framework. These outcomes show that the proposed methods provide an efficient, scalable and post-quantum-secure method for securing mobile agents in cloud computing, Internet of Things (IoT), and other decentralized distributed computing environments.

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A Lightweight CNN-GRU Based Intrusion Detection Model with Mutual Information Feature Selection for IoT Edge Devices

A Lightweight CNN-GRU Based Intrusion Detection Model with Mutual Information Feature Selection for IoT Edge Devices

Safwan Ishrak, Puja Dhar, Md. Abdul Wahab, Ratnadip Kuri, ARM Mahamudul Hasan Rana, Humayun Kabir

Scientific article

The rapid expansion of memory and resource-constrained IoT devices has enormously increased vulnerability to cyber intrusions. Although deep learning-based intrusion detection systems (IDS) aim to improve intrusion precision, this improvement comes at the cost of increased inference latency and resource utilization. In this paper, we propose a lightweight CNN-GRU-based IDS model that utilizes mutual information-based feature selection to reduce input dimensionality, retaining the most informative features. The model is validated using four popular IoT security datasets: BoT-IoT, ToN-IoT, Edge-IIoTSeT and NSL-KDD. We employ SMOTE to reduce class imbalance in the training dataset for classifying both major and minor attacks. We achieve accuracies of 99.31%, 98.80%, 96.73%, and 94.20% on BoT-IoT, NSL-KDD, ToN-IoT and Edge-IIoTSeT respectively. Since inference latency is a critical requirement for resource-constrained IoT devices, the proposed model achieves inference times of 0.064 ms, 0.086 ms, 0.078 ms, and 0.073 ms on the respective datasets. These results demonstrate that the proposed IDS provides an effective balance between detection performance and computational efficiency for real-time IoT applications. In future we will focus on validating the proposed framework in real-world IoT deployment scenarios.

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A Linear Polarized Coaxial Feeding Dual Band Circular Microstrip Patch Antenna for WLAN Applications

A Linear Polarized Coaxial Feeding Dual Band Circular Microstrip Patch Antenna for WLAN Applications

Sheikh Dobir Hossain, K. M. Abdus Sobahan, Md. Khalid Hossain, Md. Khalid Hossain Jewel, Rebeka Sultana, Md. Al Amin

Scientific article

A dual band linear polarized micro-strip antenna is designed and simulated to obtain electronic circuit miniaturization of an antenna in high speed wireless local area networks (IEEE 802.11a standard). The proposed antenna contains a substrate layer (FR-4 lossy) with a dielectric constant of 4.4 and there is a circular patch on the upper layer of the substrate. The coaxial probe feed is used to excite the desired antenna which reduces the spurious radiation and hence obtained good efficiency. It is shown that using cavity model 20% excess bandwidth can be achieved while maintaining the lower size of the antenna. An 'E' shaped slot is introduced in the radiating patch to obtain dual band resonance frequency with maximum current distribution on the surface. Finally the simulated results using Computer Simulation Technology (CST) microwave studio 2009 in this design is compared with manual computation results which are found to be suitable for WLAN applications.

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A Low-Cost Noise Wave Correlator for Noise Parameters Extraction by Cold Noise Power Measurement

A Low-Cost Noise Wave Correlator for Noise Parameters Extraction by Cold Noise Power Measurement

Abdul-Rahman Ahmed, Kyung-Whan Yeom

Scientific article

Conventionally, the noise parameters of a Device under Test (DUT) which generally characterize the noise performance of the DUT, are obtained via the impedance tuner technique. The authors have previously presented a technique which eliminates the need for impedance tuner, and rather employs an 8-port network that enables the extraction of the noise correlation matrix of a given DUT and thus its noise parameters. In this paper, we present a further simplification of the 8-port network technique, which also eliminates the need for a conventional external noise source. Cold noise powers emanating from a DUT are measured via a 6-port network with the aid of matched termination. The measured noise powers provide sufficient information for determining the noise wave correlation matrix of a DUT, which are then converted into the conventional 2-port noise parameters. The proposed technique is simple, fast and is verified to give a good estimation of the noise parameters of selected DUTs.

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A Method of Target Detection in Remote Sensing Image Captured based for Sensor Network

A Method of Target Detection in Remote Sensing Image Captured based for Sensor Network

Yingchun Shen, Hai Jin

Scientific article

A refined energy constrained minimization method is developed for target detection in hyperspectral remote sensing images captured by unmanned aerial vehicles (UAVs) during their surveillance missions, which has been tested in the experiment under this paper. The experiment result proves, in the detection process, this method can effectively restrain noises so far as the spectral characteristics of any potential target are known, and find sub-pixel targets out effectively from the hyperspectral remote sensing image in unknown background spectrum.

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A Metric for Evaluating Security Models based on Implementation of Public Key Infrastructure

A Metric for Evaluating Security Models based on Implementation of Public Key Infrastructure

Sigsbert Rwiza, Mussa Kissaka, Kosmas Kapis

Scientific article

International security evaluation metrics are too general and not focused on evaluating security models implemented using Public Key Infrastructure (PKI). This study was conducted to develop the metric for evaluating security models based on implementation of PKI by using insights from literature. Literature review was done based on inclusion and exclusion criteria. The developed metric was tested using ranking attributes and ranking scales. The results reveal that the developed metric is applicable for evaluating security models based on implementation of PKI. This is verified by the tabular results indicating evaluation of selected security models based on implementation of PKI by using ranking attributes and ranking scales. This study contributes to the body of knowledge a metric for evaluating security models based on implementation of PKI.

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A Multi-UAV Planning Framework for Task Allocation, Route Optimization and Trajectory Smoothing

A Multi-UAV Planning Framework for Task Allocation, Route Optimization and Trajectory Smoothing

Mykola Nikolaiev, Mykhailo Novotarskyi

Scientific article

Coordinated mission planning for multiple unmanned aerial vehicles in cluttered static three-dimensional environments requires consistent treatment of obstacle-aware motion, fleet-level task allocation, route sequencing, and executable trajectory generation. In many existing approaches, these elements are optimized separately, or fleet-level decisions are made using simplified geometric distances that do not accurately reflect UAV-specific motion feasibility in obstacle-constrained space. This paper presents a Multi-UAV Planning Framework for Task Allocation, Route Optimization and Trajectory Smoothing for static environments with known obstacle geometry. In the first stage, an offline single-UAV planner based on a hybrid Differential Evolution and Enhanced Whale Optimization Algorithm computes feasible raw paths for all relevant ordered node pairs and constructs a UAV-specific directed travel-cost matrix. In the second stage, these planner-derived matrices are used for feasibility-aware balanced task distribution and route optimization with exchange-based refinement under a composite total-cost–makespan objective. In the third stage, the raw paths corresponding to the final selected routes are reconstructed and transformed into executable trajectories by adaptive cubic B-spline smoothing. Experimental evaluation was conducted at the local-planning, fleet-planning, and smoothing levels in known static environments. The hybrid planner generated high-quality pairwise obstacle-avoiding paths and exhibited favorable convergence behavior relative to standard WOA, PSO, DE, SOS, and GWO in the tested scenarios. At the fleet level, the full framework reduced makespan by 2.1–3.4% and the composite objective by 0.9–1.4% relative to balanced partitioning without exchange refinement on benchmark instances. In the smoothing stage, the adaptive cubic B-spline reduced path length by 8.5% and maximum curvature by 41.5% relative to the unsmoothed polyline representation. These results demonstrate that the proposed hierarchical formulation is computationally effective, physically consistent, and well suited to multi-UAV mission planning.

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A Multi-objective Fuzzy Logic based Multi-path Routing Algorithm for WSNs

A Multi-objective Fuzzy Logic based Multi-path Routing Algorithm for WSNs

G. Spica Sujeetha

Scientific article

Wireless Sensor Networks (WSNs) have included one of the major challenges as energy efficiency. The optimal routing is the better solution for tackling the energy-efficiency problem as the energy is consumed with massive amount by the communication of a network. The clustering technique is the reliable data gathering algorithm for achieving energy-efficiency. The data transmit to the cluster head (CH) by each node that belonging to the cluster for clustered networks. The data transmission towards the BS or SINK is occurred once all data is received by CH from all member nodes. In multi-hop environments, the data transmission happens via other cluster-heads. It leads to the earlier death of CHs that are nearer to the SINK because of the heavy inter-cluster relay, i.e. called as hot-spot problem. The existing methods of unequal clustering approaches have been used to resolve this issue. The algorithms generate the clusters with smaller sizes while approaching towards the sink for reducing the intra-cluster relay. These algorithms didn’t consider the hotspot problem very effectively. Therefore, in this work, we introduce a multi-objective fuzzy logic based multi-path routing solution (MOFL-MPR) to address the above said problem. The popular clustering algorithms have been evaluated the performance results and the MOFL-MPR is outperformed the existing algorithms based on the obtained experimental results in terms of stable CH selection, energy efficiency and better data delivery.

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A Multi-step Attack Recognition and Prediction Method Via Mining Attacks Conversion Frequencies

A Multi-step Attack Recognition and Prediction Method Via Mining Attacks Conversion Frequencies

MAN Da-peng, LI Xue-zhen, YANG Wu, WANG Wei, XUAN Shi-chang

Scientific article

Massive security alerts produced by safety equipments make it necessary to recognize and predict multi-step attacks. In this paper, a novel method of recognizing and predicting multi-step attacks is proposed. It calculates attack conversion frequencies, and then mines the multi-step attack sequences. On this basis, it matches the new alert sequences dynamically, recognizes the multi-step attacks and predicts the next attack step. The result of experiment shows that the proposed method is effective and accurate.

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A Multicast Routing Mechanism in Mobile Ad Hoc Network Through Label Switching

A Multicast Routing Mechanism in Mobile Ad Hoc Network Through Label Switching

Li MengYang, Duan YunNa, Zhang ChunFei

Scientific article

Merging MPLS into multicast routing protocol in Mobile Ad hoc network is an elegant method to enhance the network performance and an efficient solution for multicast scalability and control overhead problems. Based on the Wireless MPLS technology, the mechanism and evaluation of a new multicast protocol, the Label Switching Multicast Routing Protocol (LSMRP) is presented in this paper.

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