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Image Enhancement Using Adaptive Fractional Order Filter

computer systems science & Engineering 2023年第5期45卷 1409-1422页

作者： Ayesha Heena Nagashettappa Biradar Najmuddin M.Maroof Surbhi Bhatia Arwa Mashat Shakila Basheer Department of Electronics and Communication Engineering Bheemanna Khandre Institute of TechnologyBhalkiVisveswaraya Technological UniversityBelagaviIndia Department of Electronics and Communication Engineering Khaja Banda Nawaz College of EngineeringVisveswaraya Technological UniversityBelagaviIndia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl-HofufAl-AhsaSaudi Arabia Faculty of Computing&Information Technology King Abdulaziz UniversityP.O.Box 344Rabigh21911Saudi Arabia Department of Information Systems College of Computer and Information Science Princess Nourah bint Abdulrahman UniversityP.O.BOX 84428Riyadh11671Saudi Arabia

Image enhancement is an important preprocessing task as the contrast is low in most of the medical images,Therefore,enhancement becomes the mandatory process before actual image processing should *** research article proposes an enhancement of the model-based differential operator for the images in general and Echocardiographic images,the proposed operators are based on Grunwald-Letnikov(G-L),Riemann-Liouville(R-L)and Caputo(Li&Xie),which are the definitions of fractional order *** this fractional-order,differentiation is well focused on the enhancement of echocardiographic *** provoked for developing a non-linear filter mask for image *** designed filter is simple and effective in terms of improving the contrast of the input low contrast images and preserving the textural features,particularly in smooth *** novelty of the proposed method involves a procedure of partitioning the image into homogenous regions,details,and ***,a fractional differential mask is appropriately chosen adaptively for enhancing the partitioned pixels present in the *** is also incorporated into the Hessian matrix with is a second-order derivative for every pixel and the parameters such as average gradient and entropy are used for qualitative *** wide range of existing state-of-the-art techniques such as fixed order fractional differential filter for enhancement,histogram equalization,integer-order differential methods have been *** proposed algorithm resulted in the enhancement of the input images with an increased value of average gradient as well as entropy in comparison to the previous *** values obtained are very close(almost equal to 99.9%)to the original values of the average gradient and entropy of the *** results of the simulation validate the effectiveness of the proposed algorithm.

关键词： Adaptive filter differential filter enhancement mask fractional differential mask fractional-order calculus hessian matrix

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Fostering Digital Innovation in Indonesia: The Role of STEM-AI Skills in Overcoming Talent Deficits and Gender Stereotypes

Fostering Digital Innovation in Indonesia: The Role of STEM-...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Erwin Halim Amalia Zahra Maryani Lili Ayu Wulandhari Devi Fitrianah Virienia Puspita Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Communication Department BINUS Graduate Program Master of Strategic Marketing Communication Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

This research explores the optimization of digital talent in advanced industries, particularly in the context of rapid digital transformation. Despite the increasing importance of digital talent for gaining a competitive edge, several challenges persist. In Indonesia, for example, there is a significant shortage of digitally skilled workers, with the World Bank reporting a gap of 9 million skilled individuals over the past 15 years. Additionally, artificial intelligence (AI) is expected to impact 9.5 million jobs, further exacerbating the demand for digital skills. Furthermore, the employability of graduates remains low, largely due to inadequate training, poor language proficiency, and limited cultural sensitivity. Many companies face difficulties in finding qualified individuals, quickly upskilling their workforce, and fostering an innovative organizational culture. This study seeks to evaluate the factors influencing digital talent performance in the context of these challenges. It examines seven key variables: digital readiness, digital technology adoption, relevance of AI, digital skills, individual performance, problem-solving ability, and overall digital talent performance. Hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data was collected from 378 participants, primarily students with STEM backgrounds, in the Jabodetabek area of Indonesia in November 2024. The findings reveal that all hypotheses are significant, with results indicating that user satisfaction and the perceived value of digital talent in Indonesia have a notable impact on continued usage intentions in digital roles.

关键词： Training Industries Technological innovation Sensitivity Mathematical models Problem-solving Artificial intelligence Optimization Faces Gender issues

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Towards Rehabilitation at Home After Total Knee Replacement

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Tsinghua science and Technology 2021年第6期26卷 791-799页

作者： Wenbing Zhao Shunkun Yang Xiong Luo Department of Electrical Engineering and Computer Science Cleveland State UniversityClevelandOH 44115USA School of Reliability and Systems Engineering Beihang UniversityBeijing 100191China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China

In this paper,we present the design and implementation of an avatar-based interactive system that facilitates rehabilitation for people who have received total knee replacement *** system empowers patients to carry out exercises prescribed by a clinician at the home settings more *** system helps improve accountability for both patients and *** primary sensing modality is the Microsoft Kinect sensor,which is a depth camera that comes with a Software Development Kit(SDK).The SDK provides access to 3-dimensional skeleton joint positions to software developers,which significantly reduces the challenges in developing accurate motion tracking systems,especially for use at ***,the Kinect sensor is not wellequipped to track foot orientation and its subtle *** overcome this issue,we augment the system with a commercial off-the-shelf Inertial Measurement Unit(IMU).The two sensing modalities are integrated where the Kinect serves as the primary sensing modality and the IMU is used for exercises where Kinect fails to produce accurate *** this pilot study,we experiment with four rehabilitation exercises,namely,quad set,side-lying hip abduction,straight raise leg,and ankle *** Kinect is used to assess the first three exercises,and the IMU is used to assess the ankle pump exercise.

关键词： rehabilitation physical therapy total knee replacement avatar virtual reality repetition count range of motion

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Map Building of Indoor Environment with Sensors using Neural Network

Map Building of Indoor Environment with Sensors using Neural...

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2023 Winter Summit on Smart Computing and Networks, WiSSCoN 2023

作者： Latha Mary, S Angel Ulagapriya, K. Poonguzhali, A. Menaha, R. David, Beaulah Priyadharshini, T.R. Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India Sri Sairam College of Engineering Department of Electronics and Communication Engineering Bangalore India Sri Eshwar College of Engineering Department of Information Technology Coimbatore India Hindusthan College of Engineering and Technology Department of Information Technology Coimbatore India

ISBN: (纸本)9798350334050

The necessity of a blueprint of a building structure is a mandatory requirement for any reconnaissance or rescue operations. In our project, we build a modular system combining sensors related to sonar, laser, micro-wave to read sensory values and generate a 2D path of any building. The data is fetched and stored to feed to anOptimal Neural Network (ONN)-based computing system to create a 2D route with minimal discrepancies of error. Here the NN architecture is fine-tuned using Modified Dolphin Partner Optimization (MDPO) Exploration of unknown environments and space using autonomous vehicles has recently gained good attention in the field of Robotic Mapping. The recent advancements in the Internet of Things have enabled us to establish an ideal frame of reference for sonar and lidar-based systems. New effects are displayed by the sensors according to the physical characteristics of a room. The range data from sensors in various surroundings are interpreted by NNs. The distorted errors due to the material medium, particles, and moving objects present in the environment pose a threat to building a high-quality path map. The sensor fusion technique is applied to the rotatable modular array sensor to minimalize discrepancies caused by cloth materials during sonar readings, particle noise in an environment for Lidar reading, and moving human bodies present in the environment for path building and obstacle detection. © 2023 IEEE.

关键词： Optical radar

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Association rule learning for threat analysis using traffic analysis and packet filtering approach

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International Journal of Information Technology (Singapore) 2023年第6期15卷 3245-3255页

作者： Rawat, Romil Chakrawarti, Rajesh Kumar Raj, A. Samson Arun Mani, Gayathri Chidambarathanu, K. Bhardwaj, Ramakant Computer and Communication Technology Department University of Extremadura Badajoz Spain Department of Computer Science and Engineering Sushila Devi Bansal College (SDBC) Bansal Group of Institutions (BGI) Indore India Karunya Institute of Technology and Sciences Karunya Nagar Tamil Nadu Coimbatore India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Computer Science and Business Systems R.M.K. Engineering College Chennai India Department of Mathematics Amity University West Bengal Kolkata India

The Mirai botnet source code, which was distributed on the dark web, is still changing as malware designers modify it to produce more sophisticated varieties of the botnet—the Satori—based on the malware source code. An botnet that is tied to the Internet of Things, infested with malware, and administered by offenders creates a backdoor for cybercriminals to carry out destructive operations throughout the system. The work provides association rule learning, which reveals design characteristics and warning indications of hazards using data (a data stream) collected for darknet vulnerability research. The negative effects of threat-originating computers associated with malware scripts are investigated by looking at trends in IoT-linked applications (like destination port, TCP window lengths, and kind of service).This paper provides an study of an attack (both before and after) with the first source scripts development of a conventional IoT malware, the Satori, as well as an uncommon insight into the viral processes of an attack campaign. Trials demonstrate that the suggested system is efficient in anticipating and tracking new virus tendencies in cyberspace, demonstrating that it is a viable way for streamlining and accelerating the discovery of new illicit patterns in online activities. Satori-based mathematical modelling of destination ports, ToS, and TCP window size is provided with NICT/16 DN sensor dataset that is employed in the research. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Association rule learning Cyber-attack Dark web IoT Malware

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Towards a Cyber Defense System in Software-Defined Tactical Networks

Towards a Cyber Defense System in Software-Defined Tactical ...

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International Conference on Military communications and Information systems (ICMCIS)

作者： Sean Kloth Paulo H.L. Rettore Philipp Zißner Bruno P. Santos Peter Sevenich Institute of Computer Science 4 University of Bonn Bonn Germany Department of Communication Systems Fraunhofer FKIE Bonn Germany Department of Computer Science Federal University of Bahia Salvador Brazil

ISBN: (数字)9798350373196

ISBN: (纸本)9798350373202

This study investigates the robustness of a Software-defined Networking (SDN) controller when confronted with a distributed Denial-of-Service (DDOS) attack in a tactical environment. A proactive defense mechanism is introduced to detect and respond to a flooding of “packet-in” requests, triggering a response once the network features indicate an anomaly. The methodology consists of two components: the Cyber Defense Agent (CDA), consisting of monitoring, feature engineering, detection, and responses, and the Cyber Attack Agent (CAA), including the preparation, execution, and evaluation of the attack. The CDA monitors all the IP flows from the SDN controller and processes four main features such as the average number of “packet-in” requests, the response time to these requests, the entropy of IP addresses and ports for source and destination, and “packet-in” requests per switch to identify compromised switches. All the components were emulated and tested, collecting quantitative evidence to demonstrate the effectiveness of both agents.

关键词： Switches Feature extraction Denial-of-service attack Control systems Entropy IP networks Time factors

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Towards a Unified Flow Description Language for CPPSs: An Example with Material Flows

Towards a Unified Flow Description Language for CPPSs: An Ex...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jana Gödeke Maximilian Horstrup Peter Detzner Department for AI and Autonomous Systems Fraunhofer Institute for Material Flow and Logistics Dortmund Germany Ruhr University Bochum Faculty of Computer Science Distributed and Networked Systems Group Bochum Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

This paper presents a unified approach for repre-senting multiple domains alongside production in cyber-physical production systems (CPPSs) through domain-specific languages (DSLs). The approach is illustrated using material flows (MFs) as an example. The paper identifies requirements for DSLs in CPPSs and MFs, including concurrency, synchronization, constraints, and heterogeneity support. Subsequently, a plugin system is in-troduced for the existing Production Flow Description Language (PFDL), which allows users to incorporate additional domain-specific functionality in the form of plugins. To demonstrate this approach, we present the MF plugin, resulting in the combined PFDLMF. This showcases the reusability of such an approach and the easy integration of new CPPS domains. We envision the convergence of the PFDL with plugins towards a unified flow description language for CPPSs. A practical CPPS use-case demonstrates the expressiveness of the PFDLMF in modeling and executing complex MFs in an agent-based architecture.

关键词： Concurrent computing Production systems DSL Synchronization Manufacturing automation Domain specific languages Convergence

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A Dynamic Resource-Aware Routing Protocol in Resource-Constrained Opportunistic Networks

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computers, Materials & Continua 2022年第2期70卷 4147-4167页

作者： Aref Hassan Kurd Ali Halikul Lenando Slim Chaoui Mohamad Alrfaay Medhat A.Tawfeek Department of Computer Systems and Communication Technologies Faculty of Computer Science and Information TechnologyUniversiti Malaysia Sarawak(UNIMAS)Kota Samarahan94300Malaysia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka2014KSA Unit-Lab of Sciences of Electronics Technologies of Information and TelecommunicationsSfax UniversitySfaxTunisia Department of Basic Sciences First Common Year DeanshipJouf UniversitySakaka2014KSA Department of Computer Sciences College of Computer and Information SciencesJouf UniversitySakaka2014KSA Department of Computer Sciences Faculty of Computers and InformationMenoufia UniversityEgypt

Recently,Opportunistic Networks(OppNets)are considered to be one of the most attractive developments of Mobile Ad Hoc Networks that have arisen thanks to the development of intelligent *** are characterized by a rough and dynamic topology as well as unpredictable contacts and contact *** is forwarded and stored in intermediate nodes until the next opportunity ***,achieving a high delivery ratio in OppNets is a challenging *** is imperative that any routing protocol use network resources,as far as they are available,in order to achieve higher network *** this article,we introduce the Resource-Aware Routing(ReAR)protocol which dynamically controls the buffer usage with the aim of balancing the load in resource-constrained,stateless and non-social *** ReAR protocol invokes our recently introduced mutual informationbased weighting approach to estimate the impact of the buffer size on the network performance and ultimately to regulate the buffer consumption in real *** proposed routing protocol is proofed conceptually and simulated using the Opportunistic Network Environment *** show that the ReAR protocol outperforms a set of well-known routing protocols such as EBR,Epidemic MaxProp,energy-aware Spray and Wait and energy-aware PRoPHETin terms of message delivery ratio and overhead ratio.

关键词： Opportunistic networks mobile ad hoc networks routing protocols resource-constrained networks load balancing buffer management

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A Novel Dual Temporal Channel Convolutional Network with Exponential Distribution Optimizer for Satellite Image Classification with Google Earth Engine 4

A Novel Dual Temporal Channel Convolutional Network with Exp...

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4th International Conference on Ubiquitous Computing and Intelligent Information systems, ICUIS 2024

作者： Ragavendiran, S. D. Prabu Gowthami, N.R. Gayathri, C. Ramya, D. Padmapriya, D. Aparna, S.V. Suji Builders Engineering College Department of Computer Science and Engineering Tamil Nadu Tirupur638108 India Annamacharya University Department of Civil Engineering Andhra Pradesh Rajampet516126 India Mahendra Institute of Technology Tamil Nadu Namakkal637503 India Sri Eshwar College of Engineering Department of Computer Science and Business Systems Tamil Nadu Coimbatore641202 India Panimalar Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai600123 India Department of Computer Science and Engineering CMR Technical Campus Kandlakoya Medchal Telangana Hyderabad501401 India

ISBN: (纸本)9798331529635

Classification of satellite images using Google Earth Engine entails identifying features on the satellite images to classify the land cover in a particular region through the use of deep learning algorithms. Such a process contributes to monitoring the environment and geographical distribution of resources, planning of cities, and management of resources. However, in many existing approaches, some challenges are worth noting. To address these challenges, this study introduces a new approach, the Dual Temporal Channel Convolutional Network with Exponential Distribution Optimizer (ANDualTCCNet+EDO) for satellite image classification using Google Earth Engine. This approach uses satellite imagery from the Landsat 8 Surface Reflectance dataset, with the input images preprocessed through the Adaptive Tri-Plateau Limit Tri-Histogram Equalization Algorithm (ATri-PLTri-HEA) technique. Following preprocessing, features are extracted from the images using the DenseNet201 method. Then, classification is carried out by A Novel Dual Temporal Channel Convolutional Network (ANDualTCCNet), optimized by the Exponential Distribution Optimizer (EDO) for precise satellite image classification in Google Earth Engine (GEE). The ANDualTCCNet+EDO method is implemented in Python. The proposed method was evaluated using the Landsat 8 Surface Reflectance dataset, achieving a high accuracy of 99.8%, surpassing existing methods. The results presented in this paper show that the use of this method allows for the accurate classification of satellite images in Google Earth Engine. The outcomes of the proposed method improve the method of satellite image classification in Google Earth Engine. This model captures both short- and long-duration temporal characteristics, therefore enhancing spatial-temporal feature acquisition compared to the previous method used in the classification of land cover, especially for temporal dynamics of land covers with different seasonal changes. © 2024 IEEE.

关键词： Equalizers

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3D Visualization of Femoral Shaft Fractures 4

3D Visualization of Femoral Shaft Fractures

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4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Mi, Lam Xin Hoon, Saw Seow Wang, Khor Siak Hui, Saw Seow Utar Faculty of Information and Communication Technology Dept. of Information Systems Perak Malaysia Utar Dr. WLT-CRCD Utar Sg. Long Faculty of Science Dept. of Allied Health Sciences Perak Malaysia Utar Faculty of Information and Communication Technology Department of Computer Science Perak Malaysia

ISBN: (纸本)9798350318432

The absence of an independent learning platform to address femoral shaft fractures poses challenges in understanding and classifying these fractures. The existing anatomy platforms, such as 3D interactive anatomical atlases, are insufficient in providing comprehensive information on the fractures and the high cost of these interactive anatomical atlases can be a barrier for learning to proceed due to the needs of the actual bones and human models. This study aims to develop an accessible, cost-effective educational 3D mobile application that caters to the learning needs associated with human femoral shaft fractures. Although femoral fractures are relatively uncommon, the increased cases of fractures necessitate awareness and preparedness among individuals as well as medical professionals. The proposed mobile application will enhance users' understanding of anatomical structures in femoral shaft fractures and contribute to improved patient care as well as enhance medical education. © 2023 IEEE.

关键词： Fracture

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