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14th international conference on Ubiquitous and Future networks, ICUFN 2023

作者： Aouto, Ali Jun, Taesoo Lee, Jae-Min Kim, Dong-Seong Kumoh National Institute of Technology Networked Systems Lab. Dept. of It Convergence Engineering Gumi Korea Republic of

ISBN: (纸本)9798350335385

the proliferation of commercial unmanned aerial vehicles (UAVs) of various sizes and shapes, equipped with cameras and even signal sabotage devices, has raised concerns regarding privacy and safety. Some websites even offer weapons that can be attached to drones, adding to the security threats. As a result, researchers have been motivated to develop an intelligent system that can be integrated into surveillance systems to classify unauthorized UAVs that are flying in restricted areas. In this paper, we propose a convolutional neural network (CNN) for UAV detection based on Radar image data. the Radar system, called Real Doppler RAD-DAR (Radar with Digital Array Receiver), is a range-doppler system developed by the Microwave and Radar Group. We construct and analyze the CNN by adjusting its hyper-parameters using the RAD-DAR dataset. Our simulation results show that setting the number of filters to 32 results in the best time-wise accuracy. the network achieved an accuracy of 97.63%, which is higher than other benchmark image classifiers. Additionally, we conducted an ablation study to investigate and validate the contribution of each part of the neural network. © 2023 IEEE.

关键词： Image classification

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Performance Analysis of Interference Limited Hybrid FSO/RF systems 14

Performance Analysis of Interference Limited Hybrid FSO/RF S...

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14th IEEE international conference on Signal Processing and communications (SPCOM)

作者： Kirubakaran, S. Selvaraj, M. D. IIITDM Kancheepuram Dept ECE Chennai Tamil Nadu India

ISBN: (数字)9781665482509

ISBN: (纸本)9781665482509

Free Space Optics (FSO) is a promising choice for dealing with high data-rate applications, and it improves reliability by using RF communication as a backup link. In a practical scenario, the RF link is affected by co-channel interference. We investigate the performance of an interference-limited hybrid FSO/RF system. We consider a transmitter (T-X) and a receiver (R-X) with threshold-based switching selection at the R-X. Atmospheric turbulence, path loss, and pointing errors influence the FSO link, which is modelled using the gamma gamma distribution, whereas the RF link is modelled using the kappa-mu distribution. We have derived the end-to-end symbol error rate and the outage probability for the interference limited system. Results show that interference increases the error rate and degrades the system performance. the impact of interference is high in the lower SNR's and it is controlled by increasing the Signal to Interference Ratio (SIR) of RF link. To verify the results, Monte carlo simulations are used.

关键词： Co-channel interference Gamma-Gamma distribution Hybrid FSO/RF kappa-mu distribution Pointing errors

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Prediction of Crop Based on Characteristics of Agricultural Environment Using Machine Learning Techniques 14th

Prediction of Crop Based on Characteristics of Agricultural ...

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14th EAI international conference on Broadband communications, networks, and systems, BROADNETS 2024

作者： Rao, Madhavarapu Prathima Jegadeesan, R. Pranitha, P. Praveen Kuamar, D. Krishna Chaitanya, J. Department of CSE Jyothishmathi Institute of Technology and Science Telangana Karimnagar India Department of Electronics and Communication Engineering Vardhaman College of Engineering Shamshabad Hyderabad India

ISBN: (纸本)9783031811678

Horticulture related research is creating to anticipate crops, farming, specifically, essentially depend on soil and natural components including temperature, stickiness, and precipitation. Ranchers used to be accountable for picking the yield to be developed, watching out for its development, and choosing when to gather it. But since of the climate’s fast changes these days, it is hard for the cultivating local area to proceed. Accordingly, AI methods are continuously dislodging ordinary forecast strategies. A few of these procedures have been utilized in this review to gauge rural yield. To guarantee that a specific AI (ML) model capabilities with an elevated degree of accuracy/properness, it is critical to use effective component determination strategies to change over the crude information into a dataset that is AI well disposed. To lessen copy information and increment model exactness, just information qualities that are exceptionally applicable to characterizing the last result of the model ought to be incorporated. It is basic to utilize ideal element determination to ensure that main the most pivotal highlights are remembered for the model. Assuming we coordinate all attributes from the crude information without first considering part in the model-building procetures, this model will turn out to be excessively perplexing. the incorporation of new boundaries that have negligible bearing on the model’s presentation will likewise raise the time and spatial intricacy of the ML model. the outcomes exhibit that a group procedure gives higher expectation exactness when contrasted with the ongoing characterization techniques. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Zigbee

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Epistolution: How a systems View of Biology May Explain General Intelligence 1

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14th international conference on Artificial General Intelligence (AGI)

作者： Munford, C. S. 1610 Robert E Lee Blvd New Orleans LA 70122 USA

ISBN: (数字)9783030937584

ISBN: (纸本)9783030937577;9783030937584

the genes-first view of life provides a theory of traits interacting with ecological niches, and of genes as determinants of these traits, but fails to link the two with a logic of physiology. How are genes selected for expression? It is on this level of physiology that intelligence appears. In this paper, I propose a formula by which epistemology, the sources of knowledge, and evolution might be united-an "epistolution" that offers in principle a testable synthesis to predict organismic behavior. Perhaps organisms and their microbiota, through allostasis, mediate between their ecological niches and their DNA. Perhaps they form networks nested within networks that are sensitive enough to synchronize with their niches using the formula: if used, then reinforce;else mutate stochastically.

关键词： Epistolution Downward causation Sleep Synchrony Niche Allostasis Artificial general intelligence

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Kaiser and Cumulative Proportion Principal Component Analysis for Temperature Compensation of Vibration in Reinforced Concrete Bridge 14

Kaiser and Cumulative Proportion Principal Component Analysi...

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14th IEEE international conference on Humanoid, Nanotechnology, Information Technology, communication and Control, Environment, and Management, HNICEM 2022

作者： Concepcion, Ronnie Cruz, Febus Reidj G. Carpio, Joy Bandala, Argel Relano, R-Jay De Leon, Joseph Aristotle Genevie Janairo, Adrian Guillermo, Marielet Galupino, Joenel Genoguin, Marvin Jade James Loresco, Pocholo De la Salle University Department of Manufacturing Engineering and Management Manila Philippines Mapua University School of Electrical Electronics and Computer Engineering Manila Philippines University of California Systems Engineering Department BerkeleyCA United States De la Salle University Department of Electronics and Computer Engineering Manila Philippines De la Salle University Department of Civil Engineering Manila Philippines Eastern Visayas State University Department of Civil Engineering Tacloban City Philippines FEU Institute of Technology Electrical and Electronics Engineering Department Manila Philippines

ISBN: (纸本)9781665464932

Structural health monitoring (SHM) was developed to provide diagnosis of the state of civil structures, such as bridge and building, throughout their lifespan. the superstructure degrades over time mainly because of the continuous effect of environmental factors including temperature, wind, humidity, and traffic loading. Consequently, this study is concerned in reducing the masking effect of environmental factors, specifically on temperature. Principal component analysis (PCA), a supervised machine learning algorithm, was employed as the embedded statistical treatment for multidimensional reduction of feature matrix data to eliminate the temperature effect. Kaiser's criterion eliminated data variance of almost 20% that may result to poor data reconstruction. Cumulative proportion (CP) criterion eliminated data variance around 4%, which is a better choice for deciding the number of principal components to eliminate. thus, the proposed experimental study addressed successful temperature compensation from reinforced concrete bridge vibration data by using PCA and CP criterion. © 2022 IEEE.

关键词： Structural health monitoring

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Planning and Distribution Algorithm of Heterogeneous Resources in Industrial Telecommunication networks with Ordered Sets of Tasks 14

Planning and Distribution Algorithm of Heterogeneous Resourc...

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14th international conference ELEKTRO, ELEKTRO 2022

作者： Perepelkin, Dmitry Pham, Minh Ryazan State Radio Engineering University Faculty of Computer Engineering Ryazan Russia

ISBN: (纸本)9781665467261

In this paper, an algorithm for planning and distribution heterogeneous resources in a stochastic system with ordered sets of tasks is proposed. Processing resources and memory resources are considered. the algorithm is based on the GERT-network model with a new parameter - a random variable of resource. A system consisting of many parallel processes is described in the model. Each process includes multiple tasks. By finding the start and end times of a pair of tasks it is possible to determine whether one task can start when another has finished. If the probability is satisfied for a given value, then that pair of tasks can be performed by the same processing resource unit. the ordered set of multiple sequential tasks is the desired outcome. Each set comes with a probability of completing all the tasks in the set with only one processing resource unit. the fewer the number of sets, the more resources are saved. However, it is necessary to consider the probability of the set. Accepting a certain level of risk can save a corresponding number of resources. To support the computation process, an algorithm to find the distribution laws of any arc in the GERT-network has been introduced. It speeds up the computation and allows selected arc located on the loop. Assuming that the memory resources are released as soon as the task is complete, the total memory resources for the system are recalculated. An example of the analysis process, planning and distribution resources in network devices is given. © 2022 IEEE.

关键词： Stochastic systems

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Electromagnetic Exposure Aware RSMA for Multiuser Massive MIMO Uplink 14

Electromagnetic Exposure Aware RSMA for Multiuser Massive MI...

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14th international conference on Signal Processing systems, ICSPS 2022

作者： Jiang, Hanyu You, Li Elzanaty, Ahmed Wang, Jue Wang, Wenjin Gao, Xiqi Alouini, Mohamed-Slim Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Institute for Communication Systems University of Surrey 5GIC & 6GIC GuildfordGU2 7XH United Kingdom School of Information Science and Technology Nantong University Nantong226019 China King Abdullah University of Science and Technology Thuwal Computer Electrical and Mathematical Science and Engineering Division Makkah Province Saudi Arabia

ISBN: (纸本)9798350336313

this paper investigates the rate-splitting multiple access (RSMA) transmission design for multiuser multiple-input multiple-output (MIMO) uplink with EM exposure constraints. Specifically, the transmit covariance matrices and decoding order are optimized at the users and BS, respectively, via utilizing statistical channel state information (CSI) to maximize the energy efficiency (EE). the problem is formulated as non-convex mixed integer program, which is divided into the equivalent two subproblems. We first handle the inner problem by adopting the minorization-maximization (MM) and Dinkelbachs methods. then, a modified water-filling scheme is proposed to obtain the transmit covariance matrices with fixed decoding permutation. For the outer problem, a greedy approach is proposed to obtain the decoding permutation. Numerical results verify the effectiveness of the proposed EM exposure aware EE maximization scheme for uplink RSMA. © 2022 IEEE.

关键词： Energy efficiency

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Optimising corporate governance with internet of things and artificial intelligence: a data-driven framework for legal systems

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international Journal of Information and communication Technology 2025年第13期26卷 81-100页

作者： Li, Yi School of Law Dongguan City University Dongguan523106 China

this research introduces an IoT-driven data analysis and AI framework for optimising corporate governance. the framework leverages deep learning algorithms, including transformer-based neural networks, convolutional neural networks (CNNs), and reinforcement learning models, to enhance decision-making, regulatory compliance, and transparency. Real-time data streams from IoT devices were processed, and a dataset of over 500 corporate entities was analysed. Transformer models achieved a predictive accuracy of 99.2% in identifying governance risks, CNNs detected anomalies in IoT data with 98.6% accuracy, and reinforcement learning models reduced compliance-related delays by 47%. the framework also led to a 38% increase in regulatory adherence and a 55% improvement in operational efficiency. these results demonstrate the potential of IoT and AI in addressing modern governance challenges and provide a scalable solution for sustainable governance. Copyright © the Author(s) 2025.

关键词： Convolutional neural networks

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Early Eye Disease Detection Using Machine Learning

Early Eye Disease Detection Using Machine Learning

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international conference on communication systems and Network Technologies (CSNT)

作者： Ashish Mishra Niyati Choubey Parnavi Jumde Ananya Samiya Abhilasha Garg Ashlesha Kale Department of CSE Gyan Ganga Institute of Technology and Sciences Jabalpur India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Early detection of eye diseases such as diabetic retinopathy, glaucoma, and cataracts is crucial in preventing severe vision impairment and blindness. this study explores the application of machine learning (ML) techniques, particularly Convolutional Neural networks (CNNs), for the automated diagnosis of eye diseases. A deep learning model was trained on a labeled dataset of retinal images, utilizing CNNs for feature extraction and classification. the Tkinter-based Graphical User Interface (GUI) facilitates easy user interaction, enabling real-time diagnosis from uploaded eye images. Experimental results demonstrate a high accuracy rate of 91%, outperforming traditional diagnostic techniques. Additionally, explainable AI (XAI) methodologies were incorporated to enhance model interpretability, improving trust and usability in clinical settings. In the proposed methodology the findings highlight the potential of ML in ophthalmology, paving the way for cost-effective and scalable screening solutions.

关键词： Glaucoma Cataracts Visual impairment Retina Software Real-time systems Ophthalmology Convolutional neural networks Usability Graphical user interfaces

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Passivity and Anti-Synchronization Analysis of Delay Characterization Based CMSDC for Electrical communication Network

Passivity and Anti-Synchronization Analysis of Delay Charact...

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international conference on Properties and Applications of Properties and Applications of Dielectric Materials

作者： Vadivel Rajarathinam Putsadee Pornphol Porpattama Hammachukiattikul Akarachai Inthanil Department of Mathematics Faculty of Science and Technology Phuket Rajabhat Univeristy Phuket Thailand Department of Digital Technology Faculty of Science and Technology Phuket Rajabhat Univeristy Phuket Thailand

ISBN: (数字)9798350374605

ISBN: (纸本)9798350386165

In this article deals Memory based sampled-data control with coupling terms (MSDC) to analyze the passivity and anti-synchronization of inertial neural networks (INNs). In addition, Lyapunov-Krasovskii functional (LKF), enhanced inequality techniques, designed feedback controllers, and linear matrix inequality (LMI) are used to provide the conditions that guarantee passivity and anti-synchronization between uncontrolled and regulated systems. To demonstrate the viability and validity of the suggested methods and standards, an example is provided at the end of the study.

关键词： Couplings Neural networks Dielectric materials Numerical simulation Linear matrix inequalities Delays Synchronization communication networks Adaptive control Standards

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