International Journal of Wireless and Microwave Technologies @ijwmt
Journal articles - International Journal of Wireless and Microwave Technologies
All articles: 648
Scientific article
This paper encompasses the numerical analysis involved with the Electromagnetic (EM) full-wave simulation tool Advanced Design System (ADS) which uses the Method of Moment (MOM) and Finite Element Method (FEM). MOM is utilized to solve Maxwell’s equations which are transformed into integral equations before discretization and boundary conditions are applied while FEM computes the electrical behavior of the high frequency EM wave distribution, and then analyze the antenna parameters. The main objective is to investigate the effect of reactive loading on the microstrip patch surface which is used to control the behavior of the impedance bandwidth and obtain dual-band frequency operation. The study further examines how the perturbed patch antenna design targets the operating frequencies of 2.4 GHz and 5.8 GHz for possible range and speed. The proposed method provides insight into the analysis of the mathematical model employed in attaining the Driving Point Impedance Function (DPF) of the E-patch microstrip patch antenna. This approach was done to quantify the reduction in reflections for improved Radio Frequency (RF) network output.
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FusionNet - SQL-Fusion-Based Deep Learning Model for SQL Injection Detection
Scientific article
SQL injection is a hacking attack where malicious code is inserted into database queries through user inputs like search boxes, login forms, or URL parameters. These attacks pose a significant threat to web applications and ERP systems, making early detection crucial. Traditional detection methods, such as rule-based and signature-based approaches, rely on known SQL injection patterns. However, they often fail to identify novel, obfuscated, or zero-day attacks, highlighting the need for more adaptive and intelligent detection mechanisms. This research proposes FusionNetSQL, a fusion-based deep learning model that combines Convolutional Neural Networks, Long Short-Term Memory networks, and Transformers to detect SQL injection attacks. By integrating these architectures, FusionNet-SQL gains a comprehensive understanding of SQL queries, enabling it to differentiate between legitimate interactions and malicious injections. The CNN captures local patterns, the LSTM models sequential dependencies, and the Transformer enhances global context understanding. The model achieves high performance, with 98.02% accuracy, 99.39% precision, 96.79% recall, 98.07% F1-score, and 98.07% AUC-ROC. With its robust performance and adaptability, FusionNet-SQL offers a powerful solution for securing web applications and ERP systems against SQL injection attacks. Its ability to detect both straightforward and sophisticated attacks makes it well-suited for real-world deployment, reinforcing database security and protecting critical data. This research marks a significant step forward in combating evolving cybersecurity threats.
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GSM based Monitoring and Control of Systems
Scientific article
In this paper we have proposed a method to make a base for the monitoring and Control of systems. The monitoring and Control of systems could be from monitoring of movements in any particular area to the monitoring of any external electrical, mechanical device. Every person is pocketed with the cell. So, taking the advantage of the same we developed the system for the monitoring and Control system using GSM technology. This will provide the owner, manager of the system to know about the working or any kind of default in the system. Also the system is controlled which is needed in special circumstances and is be implemented with the help of complete circuitry which is a different module (DTMF module) has a specific code as input through GSM encoder that is processed by decoder circuitry of our system. The goal is to find an improvement over the previous surveillance systems .The maintainability of the new and improved is quite efficient as it is easy to handle it by simple software demo. The facilities provided by it such as easy handling, a secrecy support, an immediate action are granted. A prototype is built in the Windows platform using C# to demonstrate the functioning of the entire system.
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Geometric Invariant Robust Image Hashing Via Zernike Moment
Scientific article
Robust image hashing methods require the robustness to content preserving processing and geometric transform. Zernike moment is a local image feature descriptor whose magnitude components are rotationally invariant and most suitable for image hashing application. In this paper, we proposed Geometric invariant robust image hashing via zernike momment. Normalized zernike moments of an image are used as the intermediate hash. Rotation invariance is achieved by taking the magnitude of the zernike moments. Image normalization method is used for scale and translation invariance. A randomization diffusion processing enhance hashing security. The test results show that our method is robust with respect to the geometrical distortions and content preserving processing.
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Scientific article
Human beings live in a world that is vulnerable to disasters and huge security threats. The common occurrence of global natural disasters and security threats call for major attention by the government of nations and the International community. Man continues to live under perpetual fear of the unknown because of these events. Notably, the human being is at the receiving end of these events either as a victim or at times as a perpetrator. Locating and rescuing victims or perpetrators of these events can be effectively achieved using smart digital devices that are configured with their unique identities and this will aid in achieving sustainable peace and stability in society. Equally, the global proliferation of digital devices is always on the rise; hardly today is there anyone on the planet earth without a form of one digital device or the other. This study is exploring the use of smart mobile digital devices, geospatial, cloud, communication, and technologies in mitigating the impact of natural and security threats with the significance of promoting peaceful human co-existence in the society. A Google App for finding a device, clock- timer app, an Internet speed check app and an online weather app were used for the experiments conducted for the proof of concept of the model. A test of model robustness was evaluated using response time and visibility. The model consistently showed good attributes of robustness in its behavior. Furthermore, the following parameters: latency, upload speed, download speed, air quality index, visibility, humidity, wind gust and temperature were observed against the response time in the experiments. A single sample (one-tail) t-test for the response time with a mean population of 0.9 gave a t-test value of 1. The value of p is 0.162791 and the result is not significant at p<.05. This indicates that there was no significant difference in the response time of the model irrespective of the time of the day, weather conditions, and the communication parameters. The result showed that the response time of the conceptual model was fast and consistent with the experiments indicating that the model can be leveraged, to address the problem identified in an affordable manner. The study is highly significant due to the fact that exploring the technologies that support location-based systems has greater potential in addressing the problem occasioned by natural disasters and security threats to humans. Future consideration is focused on enhancing the model by scaling up the biometrics features of the victim or perpetrator for speedy location.
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Scientific article
Antenna selection in reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) systems presents has significant computational challenges. The contribution of each transmit antenna is determined by the combined effects of direct and RIS-reflected channels. To address the complexity of combinatorial search a graph neural network (GNN)-based antenna selection framework is proposed. In this framework transmit antennas are represented as graph nodes with channel-correlation information forming. The graph edges and magnitude-phase channel statistics serve as node features. A three-layer feedforward GNN is trained using greedy-selection labels generated from 1000 channel realizations and evaluated on 200 independent test realizations. For a 16×8 MIMO system assisted by a 64-element RIS at 28 GHz the proposed method achieves a spectral efficiency of 63.41 bits/s/Hz and corresponding to 94.5% of the greedy baseline performance of 67.09 bits/s/Hz. While reducing the average selection time from 0.441 ms to 0.025 ms. These results determine that graph-structured learning enables near-greedy antenna selection with considerably lower inference complexity. The current study is limited to simulated settings with fixed system dimensions and idealized channel assumptions; future work will address broader channel models and larger-scale configurations.
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Scientific article
This paper presents an analytical and simulation-based treatment of the far-field radiation characteristics of a Multiple Log-Periodic Dipole Array (MLPA) antenna using Green’s function–based magnetic vector potential formulations. The study consolidates established electromagnetic theory by explicitly combining log-periodic element scaling, cumulative spatial phase delays, and array-level superposition into a single, transparent analytical workflow. The scalar free-space Green’s function is employed to derive the magnetic vector potential, from which far-field electric field expressions are obtained under standard approximations. Radiation characteristics such as half-power beamwidth, peak directivity, and sidelobe levels are extracted from MATLAB-based simulations and compared with representative theoretical LPDA performance ranges reported in the literature. The results demonstrate consistency with expected broadband LPDA behavior and serve primarily to illustrate the applicability of Green’s function methods to hierarchically structured log-periodic arrays. The work is intended as a reproducible analytical reference and pedagogical baseline for MLPA modeling, rather than as a replacement for full-wave numerical solvers or experimental validation.
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HACCP and the Risk Assessment of Cold-chain
Scientific article
Considering that cold-chain involves lots of complicated operations which suffer from various uncertain factors during the process of implementing, it is inevitable to establish a sound and detailed risk assessment principle or means to guarantee the safety of cold-chain. HACCP, Hazard Analysis and Critical Control Point, is chosen to be a useful tool to analyze the processes of cold-chain, assess the potential risks for each operation link, and then identify the critical control points and give the appropriate risk weights, so as to ensure the safety, quality and reliability of the cold-chain.
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Scientific article
The last few years have witnessed exponential rise in internet-of-things (IoT) systems for communication; yet, ensuring quality-of-service (QoS) and transmission reliability over mobile topology has remained challenge. Despite the fact that the use of software defined networks (SDN) have enabled IoTs to achieve resource efficiency and reliability; it doesn’t guarantee optimality of the solution over the network with high dynamism and non-linearity. Moreover, the major at hand SDN-IoT protocols have applied standalone node parameters to perform routing and allied transmission decision that confine its robustness over dynamic network topologies. Interestingly, none of the state-of-art SDN-IoT protocols could address the problem of iterative link-outage and corresponding network discovery cost. Furthermore, even multi-path selection strategies too failed in addressing the problem of joined shortest path selection and allied iterative link-outage due to the common node failure. Considering it as motivation, in this paper a novel and robust Heuristic-Driven Disjoint Alternate Path Switching -based Fault-Resilient Multi-Constraints Routing Protocol for SDN-mIOT system (HDAP-SDNIoT) is proposed. HDAP-SDNIoT exploits multiple dynamic parameters like medium access control information, flooding and congestion probability information. HDAP-SDNIoT exploits aforesaid node parameters to perform node profiling that serves multi-constraints best forwarding path selection. The proposed model retrieves multiple best alternating paths which are fed as input to the Adaptive Genetic Algorithm (AGA) that retains three disjoint best forwarding paths. HDAP-SDNIoT protocol at first avoids any malicious node(s) to become forwarding node, while it provides auto-switching capability to the forwarding node to select a disjoint forwarding alternate path in case of any link-outage in current forwarding path. _Simulation results confirm robustness of the proposed model in terms of high packet delivery rate of 96.5%, low packet loss rate 3.5% and low delay of 211 ms that affirms its suitability towards real-time SDN-mIoT applications.
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High-reliability vehicle detection and lane collision warning system
Scientific article
In the last two decades, developing Driving Assistance Systems for security has been one of the most active research fields in order to minimize traffic accidents. Vehicle detection is a vital operation in most of these applications. In this paper, we present a high reliable and real-time lighting-invariant lane collision warning system. We implement a novel real-time vehicles detection using Histogram of Oriented Gradient and Support Vector Machine which could be used for collision prediction. Thus, in order to meet the conditions of real-time systems and to reduce the searching region, Otsu’s threshold method play a critical role to extract the Region of Interest using the gradient information firstly. Secondly, we use Histogram of Oriented Gradient (HOG) descriptor to get the features vector, and these features are classified using a Support Vector Machine (SVM) classifier to get training base. Finally, we use this base to detect the vehicles in the road. Two sets generated the training data of our system a set of negative images (non-vehicles) a set of positive images (vehicles), and the test is performed on video sequences on the road. The proposed methodology is tested in different conditions. Our experimental results and accuracy evaluation indicates the efficiency of your system proposed for vehicles detection.
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ILBEECP for data aggregation in wireless sensor networks: a new technique
Scientific article
To design a load balanced energy efficient network has been a major concern in Wireless Sensor Networks (WSNs) since last many years. The load balancing energy-efficient clustering protocols are developed to attain the energy efficient network. But there was an issue related to the Cluster Head (CH) selection process. As the selected CH has to transmit the data to the sink node whether the node is located at a farther distance and this leads to the extra consumption of the energy by the current CH node. In order to overcome this, the novel approach is developed which is based on the multilayer architecture. The proposed method elects the CH and then a Leader node is elected from the volunteer nodes to gather the data from respective CH and then to transmit it to the base station. The simulation results depict that ILBEECP (Improved Load balanced energy Efficient Clustering protocol) outperforms the LBEECP (Load balanced energy Efficient Clustering protocol) in the terms of the dead node, alive nodes, residual energy, and energy consumption.
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IP Packet Filtering using Hash Table for Dedicated Real Time IP Filter
Scientific article
IP filtering is a technique used to control IP packets flow in and out of a network where Filter engine inspects at source and destination IP of incoming and outgoing packets. Here Filter engine is designed to improve the performance of the filter, i.e. to reduce the processing time of the filtering mechanism. The data structure used in the IP filter is hashing, for larger number of hosts and variety ranges IP network of hosts hashing provides much better performance than link list. Here hash function for the hash table is valid IP classes with host capacities i.e. class A, class B, class C. The IP filter engine have to compare the source and destination IP of each IP packet. In hash table technique the comparison can be done with minimum number of comparisons.
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IPv6 Migration Strategy Using Carrier Grade Network Address Translation
Scientific article
Due to the increased strain each new Internet-connected item puts on the IPv4 infrastructure, the emergence of additional Internet-connected places and devices has accelerated IPv4 exhaustion. Service providers have been obliged to invest in infrastructure to handle greater traffic due to unexpected growth in subscribers and linked IoT devices. Service providers are struggling to maintain growth and business continuity due to the expiration of IPv4 globally and the adoption of IPv6. There is strongly a need to address both a short-term solution for the maintenance of their current IPv4 address allocation and a long-term solution for a seamless transition to an IPv6 infrastructure, various service providers will need to design an address translation strategy. This paper presents a solution using CGNAT towards the migration of IPv6 networks. A general overview of the various parts needed to manage the depletion of IPv4 addressing and the engagement of full carrier grade network address translation solution is also discussed in this paper along with the different types of NAT.
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Identifying Protein Structural Classes Using MVP Algorithm
Scientific article
A new method for the prediction of protein structural classes is constructed based on MVP (Maximum variance projection) algorithm, which is a manifold learning-based data mining method. DC (Dipeptide Composition) and PseAA (Pseudo Amino Acid) are used as conditional attributes for the construction of decision system. A DR (Dimensionality Reduction) algorithm, the so-called MVP is introduced to reduce the decision system, which can be used to classify new objects. Experimental results thus obtained are quite encouraging, which indicate that the above method is used effectively to deal with this complicated problem of protein structural classes.
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Identifying Sentiment in Web Multi-topic Documents
Scientific article
Most of web documents coverage multiple topic. Identifying sentiment of multi-topic documents is a challenge task. In this paper, we proposed a new method to solve this problem. The method firstly reveals the latent topical facets in documents by Parametric Mixture Model. By focusing on modeling the generation process of a document with multiple topics, we can extract specific properties of documents with multiple topics. PMM models documents with multiple topics by mixing model parameters of each single topic. In order to analyze sentiment of each topic, conditional random fields techniques is used to identify sentiment. Empirical experiments on test datasets show that this approach is effective for extracting subtopics and revealing sentiments of each topic. Moreover, this method is quite general and can be applied to any kinds of text collections.
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Impact of Mobility on MANETs Routing Protocols Using Group Mobility Model
Scientific article
The MANET routing protocols should be tested under realistic conditions of the network including various parameters such as network size, representative data traffic models, realistic movements of the mobile users, etc. Many factors impinge the performance evaluation of MANETs routing protocols. Mobile nodes are communicated with each other with the help of routing protocols. Unpredictable movement of a mobile node affect the routing information which directly interrupt the subsist communication. A mobility model is used to depict the realistic movements of mobile nodes in the designed scenario. In this study the group mobility model has been used to deploy the mobility effect in the scenario. The goal of this paper is to investigate the impact of group mobility on performance of routing protocols under group mobility model using QualNet simulator. In the paper it is illustrate that how the performance results of an ad hoc network protocol drastically change with the increasing node density.The various scenarios investigated with varying density of nodes in groups. Performance analysis is carried out on the basis of performance metrics under group mobility model. The outcome of this work shows that mobility has a detrimental impact on the performance of routing protocols. From the simulation results, it is shown that the DSR protocol clearly outperform all other routing protocols with increasing node density under group mobility model.
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Impact of Reducing Multicollinearity in a Dataset on Artificial Intelligence Algorithms
Scientific article
It is known that multicollinearity not only leads to the generation of redundant data as a result of data repetition, but also affects the stability of linear models of artificial intelligence and the reliability of results. The negative effects of multicollinearity can be seen especially clearly in the development of mathematical models of artificial intelligence algorithms. That is, the coefficients will be unstable in a mathematical model developed on the basis of a data set with multicollinearity. As a result of it, misconceptions arise in scientific conclusions drawn based on the coefficients. This article first discusses multicollinearity and its negative consequences in detail. In addition to, methods for determining multicollinearity in a data set based on the correlation coefficient, the variance inflation coefficient, and the condition index are discussed in detail. Moreover, this research paper analyzes the methods of eliminating multicollinearity by removing, combining features, and Principal Component Analysis. At the same time, the research will investigate the impact of multicollinearity on machine learning models such as LogisticRegression, LinearRegression, LinearSVC, and XGBClassifier using a multicollinearity dataset. The results of the study showed that eliminating multicollinearity leads to an increase in the accuracy of all considered artificial intelligence models. In particular, the ROC value increased by 0.102 in the Logistic Regression model, by 0.129 in the Ridge Classifier, and by 0.121 in the Linear SVC. Although the smallest difference value of 0.094 was achieved in the XGBoost model, the accuracy was higher than that of the other models. After the experimental results, the article presents conclusions and recommendations based on the results obtained.
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Impact of Wall Coating on the Behavior of Indoor OWC under Diffuse Topology
Scientific article
Optical wireless communication (OWC) is an innovative technology that is gaining more attention as the demand for capacity continues to increase. It is one of the most promising alternative technologies for indoor and outdoor applications. In this paper, the effect of the inner wall coating material, color and roughness on the performance of OWC system implementing single-diffuse topology is studied. A new procedure is proposed to generate a rough surface model with predetermined statistical properties to simulate the matte painting material on the internal walls of a room. Additionally, a new technique that applies the geometrical theory of diffraction (GTD) in conjunction with a ray tracing (RT) scenario is developed to evaluate the scattered optical beam due to a primary ray incident on a Lambertian surface. The performance of the single-diffuse OWC strategy is assessed by investigating some important performance measurements such as signal strength and the bit error rate (BER) due to unavoidable ambient light which is modeled as an additive white Gaussian noise. It is shown that the surface roughness of the matte painting on the Lambertian diffuse surface has a major effect on the indoor OWC system performance.
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Implementation of Internet of Things Based Data Security Using Hybrid Cryptography
Scientific article
Internet of Things (IoT) is the current trends in tracking the variation of process variables in plant operations. The security threats and security issues continues to rise due to the wide usage of internet. The hybrid cryptography is proposed that involves symmetric AES, asymmetric RSA and hash functions all together enhance the security. The key length of this proposed symmetric AES encryption is 128-bit, RSA public key encryption is 1024-bit and 128-bit message digest is generated from the hash algorithm. It offers low latency in executing the proposed encoding and decoding algorithm. It is developed and verified in real-time environment using embedded system with internet of things. It assures data security and allows only authorized parties to monitor the plant parameters through the wireless networks. It preserves the intruders from gathering and modifying the sensitive plant information. It is suitable for protecting the plant parameters over the wide range of industrial applications.
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Implementation of a Locator-Based Route Switching Scheme for Improved Routing in Proxy Mobile IPv6
Scientific article
Proxy Mobile IPv6 (PMIPv6) is a promising IP mobility protocols that is being deployed in emerging wireless technologies. This however has a non-optimal packet route as a result of the triangular routing problem. This creates a bottle neck at the Local Mobility Anchor (LMA) thereby increasing packet delays. This paper presents the implementation of a locator-based route switching scheme on OPNET Modeler. The Mobility Access Gateway (MAG) and the LMA were enhanced by making them intelligent. This enables them to be able to check the position of the Corresponding Node (CN) with respect to the Mobile Node (MN) and also determine the available bandwidth on each link. From the checks made, a three-stage decision process is used to switch routing to the most optimal route that guarantees the best QoS. Node Models were developed for the MAG and LMA, network models were deployed and simulation tests were carried out. The results show that the developed scheme switched packets to a more optimal route according to the designed algorithm. The impact of this switching on differences between transmitted throughput at MN and the received throughput at CN was also evaluated. The receiver activity result shows a reduction in the bottleneck at the LMA-MAG link. The end-to-end delay results show over 50 milliseconds drop in packet delay as a result of the switching to a more optimal route. This shows that the packet delays result from the congestion at the LMA-MAG interface due to suboptimal routing.
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