World Academy of Science, Engineering and Technology

Authors: Bayram Orhun Ergul, Sultan Aldirmaz Colak, Merve Emin Kechagia, Mohammed Abuibaid

Abstract:

Physical Resource Block (PRB) is the fundamental unit of frequency and time resources in 4G and 5G networks. The allocation of these blocks is crucial in determining data transmission speed and quality of service for mobile users. In mobile networks, the limited spectrum is managed through the PRB structure, dividing it into high-efficiency units that can be optimally shared among users. In times of high network traffic, an insufficient number of PRBs may lead to service disruptions or quality degradation. In this study, the future PRB utilization rate in a network was predicted using the Bayesian Neural Networks (BNN) technique. These predictions were generated based on models built from historical data collected from real networks. Furthermore, the study explains how these predictions can be used for proactive actions in 4G and 5G networks. Predicting PRB utilization can improve resource allocation optimization, energy-saving algorithms, and overall network efficiency. The simulation results indicate that PRB utilization predictions made using the BNN technique outperform other methods in terms of data accuracy.

Keywords: LTE, physical resource block, 5G, neural networks, prediction, radio resource management

Procedia PDF Downloads 15

Authors: Yijia Guo, Chengpeng Ye, Jun Geng, Peng Lei, Xue Li

Abstract:

In this paper, a carrier domain method is proposed to suppress first-order spreading sea clutter in shipborne hybrid sky-surface wave passive radar operating in the high-frequency (HF) band, with Digital Radio Mondiale (DRM) signals serving as illuminators. The shipborne hybrid sky–surface wave passive radar exploits ionospheric reflection to detect targets. The DRM signal is a broadcast transmission based on orthogonal frequency-division multiplexing (OFDM). In shipborne hybrid sky-surface wave radar systems using DRM signals, the influence of sea clutter sidelobes and the limited number of space-time snapshots in the traditional Space Time Adaptive Processing (STAP) algorithm degrades the clutter suppression performance. A Space-Time Multiple-Beam STAP by Carrier (STMB-STAP-C) algorithm is proposed to improve clutter suppression performance by exploiting the multi-carrier characteristics of OFDM. STMB-STAP-C removes the transmitted symbol information from the space-time snapshots in the carrier domain, thereby significantly mitigating the influence of sea clutter sidelobes. Furthermore, STMB-STAP-C can obtain space-time snapshots from all subcarriers, substantially increasing the number of available snapshots and thereby improving clutter suppression performance. Simulation results show that the proposed algorithm has a high improve factor (IF) and requires less computational time.

Keywords: clutter suppression, DRM signal, shipborne hybrid sky-surface wave passive radar, STMB-STAP-C

Procedia PDF Downloads 9

Authors: J. A. Ojo, T. H. Salami

Abstract:

The negative impacts of oil spills on ecosystems are issues of concern in the political, environmental, and scientific communities since their frequency has continuously increased with the volume of traffic. Sensor-based oil spill detection systems are capital-intensive, paving the way for digital image processing approaches, although there are challenges such as the recognition of black spots on Synthetic Aperture Radar images. Despite the numerous advancements in oil spillage detection, there is a need for better light-efficient systems that can produce improved results with minimal false detections as compared to the previous ones. Therefore, this research aims to develop an intelligent oil spillage detection and classification system capable of detecting oil spillage from high-resolution SAR images in a more efficient manner. The aim of this research would be achieved by acquiring and pre-processing an oil spill dataset using the wavelet coefficient shrinkage method for filtering, and a designed DeepLab V3+ semantic segmentation system will be used on the pre-processed data. The descriptors of the segmented images of the oil spill data will be acquired through the modified version of the Xception architecture. The descriptors of the oil spill dataset will then be classified using a Multi-class Support Vector Machine into Oil spill, Look-alike, and others. The implementation of the system will be implemented in MATLAB R2024, and the performance of the system will be evaluated using the Confusion Matrix, Receiver Operating Characteristics (ROC) and Area Under ROC Curve. This work is expected to produce a faster method with high recognition capability for the early identification of oil leakage from high-resolution synthetic aperture radar images (SAR). The system is to improve the performance of Xception architecture, recognize the black sport of SAR image, and provide better efficient system that gives minimal false detection.

Keywords: deeplabv3, xception, oil spill detection and classification, multi class support vector machine

Procedia PDF Downloads 12

Authors: Othmane Essahili, Mohamed Ilsouk, Omar Moudam

Abstract:

In this work, five phenanthroline derivatives substituted with different methyl groups have been selected to synthesize βdiketonate-based europium complexes to check the influence of the substitutions on the degradation effect of those complexes in poly (methyl methacrylate) (PMMA) films. The photophysical properties of Eu(III) complexes, including absorbance, excitation, and emission, have been carefully investigated in solution, solid-state, and doped in PMMA film. In all these states, the complexes exhibit an impressive red emission at 614 nm with a high photoluminescence quantum yield of up to 85%. The films have been exposed to outdoor, indoor, and dark storage stability lifetime conditions for 1200 hours. The photoluminescence measurements recorded every 400, 800, and 1200 hours demonstrated that the film containing europium complex with phenanthroline ligand substituted by a high number of methyl groups (Eu(TTA)3L5) showed good photoluminescent stability in indoor and dark conditions and exhibited better resistance to degradation in outdoor conditions compared to other complexes. This study has proved that phenanthroline ligands could be tuned chemically, leading to better stability of those types of complexes in films, which can be end-used for future stable optoelectronic devices such as luminescent solar concentrators.

Keywords: photoluminescence lifetime, photostability, f β-diketonate europium complexes, luminesence solar concentrators

Procedia PDF Downloads 9

Authors: Guoxiang Han, Yuchuan Huang, Ruiyang Yang, Shichao Sun

Abstract:

As cybersecurity threats continue to evolve in complexity and severity, traditional detection methods are increasingly insufficient in addressing modern attacks. To tackle this challenge, this study proposes a hybrid deep learning model that integrates one-dimensional convolutional neural networks (1D CNN), bidirectional long short-term memory networks (BiLSTM), and an attention mechanism. The model is designed for fine-grained classification of 19 types of network traffic, including both benign and malicious flows, using the USTC-TFC2016 dataset. Data preprocessing, performed with CICFlowMeter, involved removing sensitive information, handling missing values, and constructing time series sequences via a sliding window approach. Experimental results demonstrate that the model achieves 98% accuracy and a macro-average F1 score of 0.98, with all classes attaining AUC and AP scores of 1.00. These findings indicate strong discriminative capability and an excellent balance between precision and recall. The proposed model shows significant promise for enhancing real-time network threat detection and strengthening enterprise-level intrusion detection systems.

Keywords: cybersecurity, network traffic classification, 1D CNN, Bi-LSTM, attention

Procedia PDF Downloads 9

Authors: Piero Alaimo, Filippo Saiano, Marcello Cabibbo, Roberto Macaluso, Isodiana Crupi, Dominique Persano Adorno, Mauro Mosca

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Carbon dots (CDs) are nanoscale carbon-based materials renowned for their exceptional optical properties, biocompatibility, and stability. These attributes make them promising candidates for applications such as bioimaging, optoelectronic devices, and chemical sensing. By tailoring their composition and structure, their light-emitting properties can be finely tuned, offering significant potential for advancements in nanotechnology and communication systems. This study conducts a systematic comparison of two types of carbon dots synthesized from distinct precursor pairs: urea-citric acid (a widely used binary system) and piperazine-phthalic acid. The primary objective is to evaluate how dialysis—a critical purification step for removing unreacted precursors and by-products—affects the optical and structural properties of these nanomaterials. CDs were synthesized via microwave-assisted carbonization, followed by dialysis. Their properties were characterized using UV-Vis spectroscopy, photoluminescence (PL) spectroscopy, and transmission electron microscopy (TEM). Prior to dialysis, urea-citric acid-derived CDs exhibited a broad emission spectrum peaking at 540 nm, whereas piperazine-phthalic acid-derived CDs showed a narrower emission peak at 505 nm with approximately 10-fold higher photoluminescence intensity. Post-dialysis, both CD types demonstrated altered optical properties, including improved quantum yield, reduced fluorescence quenching, and narrower particle size distribution. The results underscore the impact of precursor choice and dialysis on CD performance. While both precursors yield CDs with unique optical characteristics, dialysis significantly enhances purity and functionality, particularly for applications in sensors, drug delivery, and optoelectronics. This study provides critical insights into optimizing CD synthesis and purification protocols. Future work will focus on functionalizing these CDs to expand their utility in targeted applications.

Keywords: carbon dots, urea, citric acid, piperazine, phthalic acid, dialysis, nanomaterials, optical properties, TEM characterization

Procedia PDF Downloads 18

Authors: D. Saranyanandhini, Nivethitha T.

Abstract:

To improve intrusion detection in environmental sensor networks, this study investigates the use of cutting-edge deep learning techniques. For proactive decision-making and early anomaly identification to be possible, accurate and effective detection is essential. The dataset used includes readings from multiple sensors that track temperature, humidity, light intensity, air quality, soil moisture, and pH levels, thereby capturing the dynamic nature of environmental conditions in the real world. The performance of conventional deep learning models, namely Support Vector Machine (SVM), Random Forest (RF), and Long Short-Term Memory (LSTM), is compared to more sophisticated architectures, namely Bidirectional LSTM (Bi-LSTM) and Deep Convolutional Neural Network (DCNN), to handle the complexity of such data. The findings show that Bi-LSTM and DCNN perform noticeably better than conventional models on several important evaluation parameters. Bi-LSTM obtained the best results (accuracy 0.97, recall 0.95, precision 0.96, and F1-score 0.955), followed by DCNN (accuracy 0.92, F1-score 0.905). Traditional models like SVM and RF, on the other hand, produced lower accuracies of 0.85 and 0.88, respectively. Bi-LSTM's bidirectional architecture improves sequential data comprehension, and DCNN's superior ability to extract complex spatial patterns makes it an excellent choice for environmental data analysis. These results have important ramifications for infrastructure management, environmental monitoring, and agriculture, as early intrusion identification can reduce risks and maximize resource use. The study emphasizes how well-advanced deep learning models work to provide reliable, real-time monitoring in dynamic environmental scenarios.

Keywords: intrusion detection, machine learning, Bi-LSTM, image processing, internet of things, security & privacy, agriculture

Procedia PDF Downloads 22

Authors: Zhengjie Niu, Hongxi Xue

Abstract:

This paper presents the application of a new 5th generation communication network（5G）radio frequency (RF) front-end technology and proposes a related solution for 5G indoor coverage enhancement. By applying these technologies, the corresponding 5G broadband high-power linear power amplifier module is developed. 5G broadband high-power linear power amplifier （LPA） module can independently provide broadband signal amplification and linearization functions, which would enable more efficient coverage solutions. This paper also compares the distinct solution with existing technology in terms of equipment count, and power consumption for the same coverage area. Our solution achieves not only the same coverage with more system margin but also less equipment with much lower energy consumption.

Keywords: RF power amplifier, linearization technology, 5g, repeater solution

Procedia PDF Downloads 17

Authors: Azad Siahmakoun, Sergio Granieri

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We propose a straightforward approach for implementing optical single-sideband suppressed-carrier microwave modulation using a standard Mach-Zehnder Modulator (MZM) and passive fiber-optic components in a Sagnac interferometer. The functionality of the proposed modulator is theoretically analyzed and experimentally demonstrated using a Sagnac configuration to suppress the sideband, with a non-reciprocal optical element producing orthogonal linear-polarized propagating light in each arm. The carrier attenuation is controlled by setting the MZM at the quadrature bias point. Using only commercially available components, we will experimentally demonstrate sideband suppression and carrier attenuation of up to 28.5 dB.

Keywords: sideband suppression, RF carrier suppression, sagnac interferometer, microwave photonics

Procedia PDF Downloads 23

Authors: Mateusz Burczaniuk, Tomasz Kuryłowicz, Michał Ostapowicz, Hoang Nghia Le

Abstract:

Planning big telecommunication networks containing millions of devices is a challenging process. The first stage of the task is to divide the network into smaller parts that are easier to design. Within the stage, the designed network is partitioned into subnetworks, and the optimal topology for each subnetwork is chosen. At present, the process is, in most cases, executed manually by experienced specialists, which generates vast costs. The paper presents Genetic Algorithm (GA) and Ant Colony Optimization (ACO) methods tailored to the problem. A minimax criterion was used to compare alternative solutions to the problem. This criterion prefers a solution with the least cost of the most expensive subnet, which allows to balance result subnetworks. The presented solutions can consider four subnetwork topologies: tree, bus, ring, and mesh. The user can choose which topologies should be utilized and whether to prefer some over others. To evaluate presented approach, both qualitative and quantitative methods were used. Results obtained with analyzed methods are of good quality and can be used commercially. Thanks to the adopted approach, the duration of solving the decomposition task, a few weeks of manual work, was reduced to less than 1 hour.

Keywords: ACO, genetic algorithm, network decomposition, network planning

Procedia PDF Downloads 23

Authors: Yuanzhi Dong, Yunxia Jin, Yuxing Han

Abstract:

3D aperiodic volume holographic gratings (AVHGs) recorded with non-planar wavefronts have been extensively applied in various fields—including volume holographic lenses for lensless imaging systems, vortex volume gratings for free-space optical communications, and chirped volume gratings for chirped pulse amplification systems. However, owing to the 3D variation of grating vectors and the potential for significant refractive index modulation, no existing theory is capable of accurately computing the genuine diffraction field of these devices. Although the localized method is effective for surface aperiodic structures, it fails to capture the volumetric aperiodicity inherent in AVHGs. Similarly, while the diffraction integral method is designed for three-dimensional aperiodic structures, its utility is limited when dealing with gratings exhibiting large refractive index modulation. In this work, we propose a multilayer localized coupled wave method that deciphers the genuine diffraction field of AVHGs. Surface-segmented local gratings are further considered as stacks of multiple layers of periodic gratings with different transmission properties. The boundary conditions are solved using a proposed concept of average grating vector, reaching a local electric field that is approximately described as plane waves that collectively form the complete electric field. For the first time, our method calculates the genuine diffraction field of AVHGs featuring both substantial grating vector variations and significant refractive index modulation, thereby correcting the pseudo-fields produced by conventional localized and diffraction integral methods. Simulations demonstrate that the proposed approach not only restores the desired wavefront conversion under perfect reconstruction but also predicts diffraction efficiency roll-off and spectral broadening in cases of imperfect reconstruction, as well as far-field distortion and focusing advance under overmodulation conditions. The proposed method allows for a precise analysis of various aperiodic volume holographic gratings, providing strong theoretical support for their design and optimization while potentially requiring high differential accuracy and more computation time.

Keywords: aperiodic volume holographic gratings, coupled wave theory, 3D grating vector variation, refractive index modulation, wavefront conversion

Procedia PDF Downloads 18

Authors: Yubo Wu, Yunxia Jin, Yuxing Han

Abstract:

Ultra-intense femtosecond optical vortex pulses, which can be utilized in particle acceleration and high-harmonic generation, remain challenging to generate at Petawatt power levels. Upon utilizing the reflective spiral phase plate for mode conversion, high-energy vortex beams can be achieved at the focal plane. However, the fabrication of large-aperture reflective spiral phase plates presents significant challenges, and topological charge dispersion becomes evident across a broad bandwidth. Several studies have proposed methods for amplifying vortex seed beams using Chirped Pulse Amplification technology. This approach necessitates the generation of vortex seed light at the system's front end, thereby increasing system complexity. Additionally, during the amplification process, it is crucial to suppress Gaussian modes; otherwise, the ring structure of the vortex beam may be compromised. This study investigates a novel reflective vortex grating exhibiting broadband operation and high diffraction efficiency. By substituting this grating for the conventional straight-line grating in the compression cavity, it enables the transformation of nanosecond Gaussian pulses into femtosecond vortex pulses. Additionally, the proposed optical setup is relatively straightforward. This study presents the fringe distribution of vortex gratings and employs the Fresnel diffraction integral method to simulate the diffraction field of Gaussian beams passing through the grating. A reflective vortex grating was fabricated using the double-beam interference method, achieving a diffraction efficiency of 70% within a bandwidth over 200 nm near the center wavelength of 925 nm. The ability of vortex gratings to generate femtosecond vortex pulses was experimentally investigated in the Station of Extreme Light 100-PW front end. The generated vortex pulses, with topological charges of 1~3, had durations of ~17 fs. This work demonstrates that vortex gratings possess the capability to simultaneously compress pulse width and modulate the wavefront. These findings indicate significant potential for applications in generating ultra-intense femtosecond optical vortex pulses, as well as in ultrafast pulse shaping.

Keywords: bessel gaussian beam, chirped pulse compression, ultrafast vortex pulse, vortex grating

Procedia PDF Downloads 20

Authors: Akande Hakeem Babalola, Akande Noah Oluwatobi, Adeniran Caroline Temitayo, Shuaib Mariam Morenike

Abstract:

Cognitive radio (CR) represents a significant advancement in spectrum utilization due to its ability to dynamically allocate spectrum (DSA) while minimizing interference. Spectrum sensing (SS) is crucial for CR to implement DSA by periodically monitoring channels to detect licensed users' presence or absence. Although existing research has compared various SS techniques, including two-stage methods, most studies have been limited to a few well-known techniques and have often not utilized fuzzy logic. This research addresses this gap by proposing a two-stage fuzzy-based SS technique that integrates four different SS methods—energy detection (ED), matched filter detection (MFD), cyclostationary function detection (CFD), and wavelet transform-based detection (WTD). In the first stage, these techniques individually assess the spectrum, and in the second stage, their outputs are combined using fuzzy logic to make the final decision. MATLAB simulations demonstrate that the proposed technique outperforms conventional one- and two-stage methods in terms of detection probability, although it has higher detection times due to the computational complexity of the fuzzy logic controller. Despite this trade-off, the technique's superior detection performance is evident. The technique's accuracy, precision, sensitivity, and F1 score were also evaluated, showing exceptional performance across a range of SNR conditions.

Keywords: fuzzy logic, two-stage technique, spectrum sensing, cognitive radio networks

Procedia PDF Downloads 28

Authors: S. Valenti, M. Manganelli, P. Zito, T. Franke, A. Ferro

Abstract:

Ensuring power quality and stability in fusion power plant grids is crucial for the successful integration of demonstration power plant (DEMO) into future electrical networks. This paper presents the preliminary design of an active power filter (APF) aimed at compensating reactive power in the DEMO toroidal field power supply. In the high-current coil configuration, assuming ITER-like thyristor converter technology, the DEMO toroidal field power supply (TFPS) is a 2-quadrant AC/DC 12-pulse converter with a no-load voltage of ±1 kV and operating current of 105 kA. This AC/DC converter is fed by two converter transformers with the following characteristics: voltage ratio V₁/V₂₀ = 22 kV/0.74 kV and capacity rating S = 2 x 58 MVA. The proposed APF employs a control strategy based on the park transform, which enables efficient detection and mitigation of harmonic distortions and reactive power fluctuations. The methodology involves systematic modeling of the APF, allowing, thus, the extraction of the fundamental and harmonic components from the power signals. A robust control scheme is then implemented to ensure dynamic compensation of reactive power and to minimize total harmonic distortion (THD). Preliminary design is carried out through comprehensive simulation studies to assess the effectiveness of the APF under conditions mimicking real-time grid scenarios. In particular, the APF has been shown to maintain a power factor (cos φ) that nearly always complies with the stringent guidelines typically required for nuclear installations to ensure both efficient and safe operation. Results demonstrate that the APF can effectively enhance power quality by significantly reducing distortion and increasing the power factor, thereby improving the overall reliability of the DEMO electrical power system. The findings suggest that the integration of this APF design in the ITER-like solution can play a pivotal role in maintaining grid compliance with international power quality standards, thus contributing to the secure operation of future nuclear fusion power plants.

Keywords: active power filter, DEMO power plant, park transform, power factor, power quality, reactive power compensation

Procedia PDF Downloads 22

Authors: Puya Behnia

Abstract:

In this paper, the goal is to achieve a high-reduced gain for low-voltage electric vehicle charger applications (LVEVs) using a modified SEPIC without a diode converter. The non-bridge-free structure, as well as the simultaneous switching switches, reduce the complexity of control. The extensive converter reduction is achieved through the Switched Inductor structures, which allow for the battery charge profile needed for low-voltage batteries. The function of the discontinuous current states not only facilitates the ability to correct the intrinsic power coefficient on the network side but also reduces the size of the magnetic components. DICM's operation also provides zero -currents for switches and zero currents for high-frequency diodes, thus minimizing losses associated with reverse diode recovery transfers.

Keywords: SEPIC, THD, PF, efficiency

Procedia PDF Downloads 23

Authors: Puya Behnia

Abstract:

In this article, a direct matrix converter in normal method of switching with 380 V and 50 Hz input is designed and simulated. The proposed output is 150 V and 150 HZ. It is tried to reduce the THD (Total Harmonic Distortion) of output voltage and output current in order to improve power quality transmission in this converter. The next aim of this converter is to increase input PF (Power Factor) of the converter. This converter can change both amplitude and frequency of the input. In this article, nine bidirectional switches are used. Each of these bi-directional switches has two diodes which are used to protect the bi-directional switch against the reverse voltage.

Keywords: direct matrix converter, THD, power factor, power quality

Procedia PDF Downloads 21

Authors: Puya Behnia

Abstract:

In this paper, a boost PFC converter is designed and presented. In this converter, the input current has a very strong third harmonic which has a phase difference of π radian with respect to the fundamental component. This converter is able to transfer the power from the input side of the converter to the load side of the converter with the least THD of the third harmonic of the input current. This converter can convert the AC input voltage to the higher amplitude DC voltage in the CCM mode of the inductor current with the least overshoot of the DC output voltage due to the PID-controllers setup. Boost PFC converter, which operates in the CCM mode of the inductor current, has become particularly popular because of the reduced electromagnetic interference (EMI) levels resulting from its utilization. With this converter, the power factor of the input side of the converter is improved in the 30 kHz switching frequency of the power electronic switch of the boost PFC converter, which is a MOSFET due to the input current’s third harmonic THD, which is reduced.

Keywords: power quality, PFC, boost PFC, third harmonic THD, input power factor

Procedia PDF Downloads 26

Authors: Puya Behnia

Abstract:

Nowadays, power quality is one of the most important aspects of power electronics engineering. In this article, it is tried to reduce the power losses in power transmission in the presented three-phase inverter from the AC main to the load side with the space vector pulse width modulation method of switching the three-phase inverter in the controlling circuit unit. This article presents a three-phase inverter with a switching frequency of 10 kHz. This three-phase inverter is controlled by the space vector pulse width modulation method of switching the power electronic switches of this inverter. This switching method of the inverter is helpful due to the reduction of the output voltage third total harmonic distortion. After the output voltage’s third total harmonic distortion is reduced, we have a better output voltage waveform with lower third harmonic and higher power factor and better power quality of the output signal; as a result, better power transmission from the DC side of the inverter to the AC side and the least power losses is seen by using this controlling method.

Keywords: three-phase inverter, SVPWM, THD, power factor, power quality

Procedia PDF Downloads 18

Authors: Mesfin Leranso Betalo, Getaneh Berie Tarekegn

Abstract:

Ultra-dense wireless sensor networks (WSNs) are vital for numerous applications, including smart agriculture systems supported by fifth-generation (5G) and beyond technologies. These WSNs rely on multiple unmanned aerial vehicles (UAVs) to gather data from sensor nodes (SNs) and transmit it to a central controller for processing. UAVs also enhance network coverage and provide essential resources to SNs across large geographical regions. This flexibility makes UAV-assisted WSNs a suitable choice for meeting the stringent demands of smart agriculture, such as real-time data transmission and remote monitoring. Despite these advantages, several challenges persist, including the limited battery capacity of UAVs, restricted transmission power, and energy limitations of SNs. These constraints hinder efficient data collection and task execution, leading to suboptimal resource management in smart agricultural systems. To address these issues, this paper proposes a unified framework for UAV task scheduling, trajectory optimization, and resource sharing in multi-UAV-assisted WSNs for smart agricultural monitoring. The framework schedules UAV charging, data collection, and landing activities while enabling UAVs to share energy with SNs. The primary objective of this framework is to minimize energy consumption and network latency, ensuring timely and efficient data collection. The problem is formulated as a multi-objective, non-convex optimization task and redefined as a Markov Decision Process (MDP), which is solved using a multi-agent deep reinforcement learning (MADRL) algorithm. Simulation results demonstrate that the proposed MADRL approach achieves significant energy savings, reducing energy consumption costs by 71.92%, 78.02%, and 79.9% compared to deep Q-network, greedy, and mixed-integer linear programming (MILP) approaches, respectively

Keywords: UAV-assisted wireless sensor networks, energy optimization, multi-agent deep reinforcement learning, task scheduling, trajectory planning, resource sharing

Procedia PDF Downloads 19

Authors: Aoqi Fang, Rongjing Wang, Jixin Liu, Hao Xu, Penghao Tang, Baolu Guan, Jie Sun, Weiling Guo

Abstract:

This paper reports a micro-light-emitting diode (μLED) with enhanced emission through a graphene-connected nanorod array and Ag nanoparticles (NPs) wrapped in a SiO₂ insulating layer. The nanorod structure enables close or direct contact between the Ag/SiO₂ NPs and the quantum wells (QWs), enhancing the radiative recombination efficiency within the QWs via localized surface plasmon resonance (LSPR). Graphene serves as a transparent conductive layer that connects the individual nanorods, ensuring uniform light emission. Experimental results show that the presence of Ag/SiO₂ NPs enhances the photoluminescence (PL) intensity of the nanorods by 27%. Compared to traditional planar μLEDs, the NR-μLED-Ag/SiO₂ we designed shows a 40% increase in electroluminescence (EL) intensity at a current density of 40 A/cm². This work paves the way for the application of localized surface plasmon resonance in GaN-based μLEDs.

Keywords: micro-LED, nanorod, LSPR, nanoparticle

Procedia PDF Downloads 24

Authors: Alex Gramann, Luther Hindley, Samuel Hamilton, Gerard Whoriskey

Abstract:

Industrial hyperspectral imaging has grown rapidly since its inception, seeing use in a diverse range of applications from pharmaceuticals and food quality inspection to art conservation and archaeology, among others. Although some developments in these fields have pertained to improving the light source used, the primary focus has been on improvements to camera technology and analysis methods to obtain more accurate spectral data. Typically used are halogen systems for conveyor belt applications, while in agriculture and other outdoor applications the sun can be used as the light source. However, particularly when considering food inspection and pharmaceuticals (for which halogen systems are used) several drawbacks become evident. While halogen illumination systems have a broad and relatively smooth spectrum, the high running temperature (which increases further if deep blue or UV measurements are required) decreases the working lifetime of halogen bulbs, with some systems only lasting a few hundred to a thousand hours before needing to be replaced. This can lead to high running costs while also causing significant periods of down-time while bulbs are replaced. Consequently, these systems can be both highly power intensive and expensive to operate, particularly for industrial applications where such systems run constantly for extended periods. Issues with sourcing replacement halogen bulbs are also becoming more common due to efficiency limits being placed on manufactured bulbs, effectively banning the production of halogen bulbs. As their supply is increasingly limited, solid-state LEDs are being taken up as a more energy efficient alternative. While attempts have been made previously to develop commercially viable solid state illumination systems for broadband hyperspectral applications, such systems have suffered from low irradiance, inhomogeneous spectra, or both, limiting their effectiveness in high end applications. This is primarily due to the discrete nature of spectral emissions from LEDs. However, with the developments in homogenising techniques presented in this work, the aforementioned limitations can be overcome, hence paving the way for the development of solid-state hyperspectral illumination systems. With the roll-off in power towards the edges of the emitting region included spectral characterisation of current early-stage prototypes, having a spectral coverage from 400 - 1000 nm, show > 95% spectral homogeneity across a 50 mm long output region. For further improvements to the performance of this homogenising technique, mechanical changes would be necessary; however, these initial results prove promising for the method developed. Further, spectral flux measurements of the illuminated region projected from the prototype systems showed an exponentially decaying irradiance reaching 50 mW/cm2 at a distance of 15 cm from the final lens. While this would be on the limit of that which can be used for industrial applications currently, further developments to both the optics and thermal management systems could improve the irradiance, making the system fully viable. Such advances in light source technology will drive efficiency increases and cost reduction across the many industries already utilising hyperspectral imaging.

Keywords: solid state, LED Illumination, industrial hyperspectral imaging, spectral homogenisation

Procedia PDF Downloads 21

Authors: Kifetewe Yisfalem Tigistu, Abdul Karim Patwary, Khalil Ud Din, Shanko Demise Daniel

Abstract:

This paper presents a compact bandpass filter design for wireless communication systems using coupled microstrip lines operating over 12–14 GHz. A Butterworth prototype ensures a flat passband and steep stopband roll-off. The filter, implemented on an FR4 substrate (εr = 4.4, H = 1.27 mm), targets an insertion loss greater than -8 dB and a return loss below -10 dB. Key design parameters, including the width, length, and spacing of the coupled lines, are determined through calculations and simulations. The schematic circuit design is converted into a layout and optimized using electromagnetic simulations in ADS software. The final design meets performance goals for insertion loss, return loss, selectivity, and stopband rejection, proving its suitability for high-frequency wireless applications.

Keywords: bandpass filter, Butterworth filter, coupled microstrip lines, FR4 substrate

Procedia PDF Downloads 41

Authors: Mohammad Moradi

Abstract:

In this study, copper cobalt ferrite nanoparticles were synthesized by the chemical formula Co1- xCuxFe2O4 and (x = 0, 0.2, 0.4, 0.6, 0.8, 1) by co-precipitation method. The X-ray diffraction pattern of the samples confirmed the single-phase spinel structure of the fabricated nanoparticles, and the average size of the crystals was calculated from the entire width of the diffraction peak with the highest intensity and Scherrer’s equation. Using transmission electron microscope images, the nanoparticle size was about 10 nm. The magnetic properties of copper cobalt ferrite nanoparticles were measured by Alternative Gradient Force Magnetometer (AGFM), and it was seen that with increasing substitution of copper Cations instead of cobalt Cations in the samples, the amount of induction decreased and the saturation magnetization first increased and then decreased. In order to investigate Faraday’s effect on copper-cobalt ferrite nanoparticles, the transmittance values were measured using a laboratory experiment and their graphs were plotted in terms of the applied magnetic field, all of which were in agreement with the theory. In addition, transmittance was investigated for two angular positions of the analyzer at -45˚ and +45˚ in different fields.

Keywords: magnetic nanoparticles, Ferrite co-precipitation, Faraday rotation, magneto- optical property

Procedia PDF Downloads 28

Authors: Saqib Warsi

Abstract:

The evolution of optical communication technologies is pivotal in meeting the growing data demand driven by emerging technologies such as 5G, IoT, and upcoming 6G networks. This paper presents advancements in Dense Wavelength Division Multiplexing (DWDM) systems, focusing on the integration of Zero Touch Provisioning (ZTP) for simplified deployment and the ability to scale data transmission over single fiber pairs. The proposed methodology leverages high-capacity DWDM channels capable of supporting data rates exceeding 800G, ensuring future-proof solutions for both residential and enterprise communication infrastructures. Moreover, this paper examines the impact of these technologies on operational efficiency by minimizing the need for manual configuration, leading to reduced costs and faster deployment timelines. We also explore how the integration of optical amplifiers, Optical Line Amplifier (OLA) alternatives, and optical control plane protocols (such as ASON, GMPLS, OpenFlow, and SDN) play a critical role in enhancing the flexibility, scalability, and energy efficiency of optical networks. By focusing on optical solutions, this paper seeks to address the future challenges of reducing fiber pair consumption and improving network performance without compromising on capacity or reliability.

Keywords: zero-touch provisioning (ZTP), dense wavelength division multiplexing (DWDM), optical networks, optical control plane (ASON, GMPLS, OpenFlow, SDN)

Procedia PDF Downloads 35

Authors: Daniel Ngusha Chile

Abstract:

The rapid advancement of communication and information technology has significantly transformed how organisations engage in strategic communication. As the world becomes increasingly interconnected, leveraging the convergence of these fields is essential for driving impact and fostering innovation. This study examines the integration of communication, information technology, and strategic communication, exploring how their synergy enhances message delivery, audience engagement, and organisational effectiveness. Using a mixed-methods approach, the research employs surveys and case studies to investigate the adoption of digital tools and platforms in strategic communication practices across various industries. Quantitative data were analysed to identify trends in technology use, while qualitative insights were drawn from interviews with communication professionals to understand challenges and best practices. The findings reveal that organisations which strategically integrate communication and information technology experience improved message clarity, wider audience reach, and stronger brand positioning. However, the study also highlights barriers such as gaps in technological literacy and ethical concerns regarding data privacy. In conclusion, the convergence of communication, information technology, and strategic communication is pivotal in shaping the future of organisational success. Embracing these advancements enables more effective engagement, adaptability, and resilience in a rapidly evolving digital landscape.

Keywords: communication, information technology, strategic communication, digital transformation

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Authors: Daniel Ngusha Chile

Abstract:

In the contemporary digital age, networking and mobile computing have become integral to advancing strategic communication within organisations. The ability to communicate effectively across various platforms and devices has enhanced organisational connectivity, fostering seamless collaboration and improving decision-making processes. This study explores how networking and mobile computing contribute to strategic communication by providing a robust framework for enhancing organisational efficiency and adaptability in dynamic environments. Using a mixed-methods approach, the research combines surveys and interviews with communication professionals to assess the adoption of networking and mobile computing technologies. Quantitative data were analysed to identify patterns in technology utilisation, while qualitative insights from interviews provided a deeper understanding of how these tools shape communication strategies. Case studies of leading organisations further highlight best practices in leveraging mobile computing for strategic objectives. The findings reveal that integrating networking and mobile computing into strategic communication frameworks significantly improves message delivery, real-time collaboration, and accessibility. However, challenges such as cybersecurity threats and technological skill gaps persist, necessitating targeted interventions to maximise these benefits. In conclusion, the study underscores the transformative potential of networking and mobile computing in driving strategic communication. By adopting these technologies, organisations can enhance connectivity, streamline operations, and maintain a competitive edge in an increasingly digital and mobile-centric world.

Keywords: strategic communication, networking, mobile computing, organisational connectivity

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Authors: Daniel Ngusha Chile

Abstract:

Language serves as a powerful tool in strategic communication, shaping cultural narratives, identity construction, and audience influence, particularly within digital media environments. This study examines the dynamics of language in strategic communication, focusing on the interaction between linguistic framing, cultural values, and identity representation across digital platforms. Drawing on theories from sociolinguistics and strategic communication, the research employs a mixed-methods approach, including discourse analysis of digital campaigns and surveys to gauge audience perceptions. The findings reveal that language which is culturally nuanced significantly enhances audience engagement, while inclusive linguistic strategies impact identity resonance and message effectiveness. Additionally, the study highlights the role of digital media in amplifying cultural diversity and fostering linguistic breakthrough in strategic messaging. These insights highlight the importance of integrating language sensitivity and cultural awareness into digital communication strategies to maximize audience impact.

Keywords: language dynamics, strategic communication, digital media, cultural identity

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Authors: Reema Zagzoog, Bedour Al-Abbadi, Haneen Iskandar

Abstract:

FaceApp, a popular photo editing app, has taken the world by storm with its ability to transform faces using advanced AI. This project dives deep into the app's features, analyzing its impact and user perception. By collecting and analyzing user feedback and app metrics, we explored how AI is used to manipulate facial features, such as age, gender, and expression. We dissected the realism of these transformations and the appeal they hold for users. Additionally, we investigated the most popular editing tools within the app, gaining insights into user preferences and behavior. Through a blend of quantitative and qualitative analysis, we uncovered key findings that shed light on the effectiveness of AI-powered photo editing. Our research provides valuable insights into user behavior and preferences, offering implications for future developments in the field of digital image processing.

Keywords: features, AI-powered photo editing, facial, analyze

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Authors: Ojo Samson Iyanda, Adeleke Oluseye A., Ojo Oluwaseun A.

Abstract:

Recent developments in the Wireless communication (WC) community has necessitated a paradigm shift in the effective usage of network resources to provide better Quality of Service (QoS) to wireless subscribers. However, the daily increase in the number of users accessing WC services makes frequency spectrum a valuable yet limited resource. Energy harvesting-enabled Decode and Forward Cooperative Cognitive Radio (DFCCR) used to solve this problem faced significant challenges in achieving efficient performance and signal insecurity due to channel fading and broadcast nature of the transmitted signal. Hence, this paper enhanced the performance of the existing DFCCR. PU signal is propagated from the source at different time slots using time diversity. The different versions of the transmitted signal are received at the SU’s transceiver. The received signal at the SU transceiver is decoded and SU superimposes its own information on the decoded signal using exclusive OR (XOR) rule. Jamming signal is created at the SU node and added to the SU transmitting signal. Outage Probability (OP) and Secrecy Capacity (SC) are derived to evaluate the performance of the proposed technique. The proposed energy harvesting-enabled DFCCR enhanced the performance of existing technique with 65% reduction in OP and 50% improvement in SC.

Keywords: cognitive radio, RF energy harvesting, decode and forward, secrecy capacity

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Authors: Emmanuel Ekwueme, Anwar Ali

Abstract:

As the Internet of Things (IoT) continues to expand, the demand for battery-free devices is increasing, which is crucial for the efficiency of 5G networks and eco-friendly industrial systems. The solution is a device that operates indefinitely, requires no maintenance, and has no negative impact on the ambient environment. One promising approach to achieve this is energy harvesting, which involves capturing energy from the ambient environment and transferring it to power devices. This method can revolutionize industries. Such as manufacturing, agriculture, and healthcare by enabling real-time data collection and analysis, reducing maintenance costs, improving efficiency, and contributing to a future with lower carbon emissions. This research explores various energy harvesting techniques, focusing on radio frequencies (RF) and multiple energy sources. It examines RF-based and solar methods for powering battery-free sensors, low-power circuits, and IoT devices. The study investigates a hybrid RF-solar harvesting circuit designed for remote sensing devices. The proposed system includes distinct RF and solar energy harvester circuits, with the RF harvester operating at 2.45GHz and the solar harvester utilizing a maximum power point tracking (MPPT) algorithm to maximize efficiency.

Keywords: radio frequency, energy harvesting, Internet of Things (IoT), multisource, solar energy

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