Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-Based Recruitment
- Alejandro Peña,
- Ignacio Serna,
- Aythami Morales,
- Julian Fierrez,
- Alfonso Ortega,
- Ainhoa Herrarte,
- Manuel Alcantara,
- Javier Ortega-Garcia
The presence of decision-making algorithms in society is rapidly increasing nowadays, while concerns about their transparency and the possibility of these algorithms becoming new sources of discrimination are arising. There is a certain consensus ...
An Exploration into Human–Computer Interaction: Hand Gesture Recognition Management in a Challenging Environment
Scientists are developing hand gesture recognition systems to improve authentic, efficient, and effortless human–computer interactions without additional gadgets, particularly for the speech-impaired community, which relies on hand gestures as ...
Design and Implementation of Enhanced Security Algorithm for Hybrid Cloud using Kerberos
Cloud computing refers to a network-enabled service that allows users to access large data centres and web services through the internet. A hybrid cloud comprises of both private and public clouds that allows users to integrate resources and ...
Imprecise Probabilistic Model Checking for Stochastic Multi-agent Systems
Standard techniques for model checking stochastic multi-agent systems usually assume the transition probabilities describing the system dynamics to be stationary and completely specified. As a consequence, neither non-stationary systems nor ...
Gaussian Differential Privacy Integrated Machine Learning Model for Industrial Internet of Things
- Arokia Jesu Prabhu Lazar,
- Sivaprakash Soundararaj,
- Vijaya Krishna Sonthi,
- Vishnu Raja Palanisamy,
- Vanithamani Subramaniyan,
- Sudhakar Sengan
Agriculture, energy, mining, healthcare, and transportation are a few of the top industries transformed by the industrial internet of things (IIoT). Industry 4.0 mainly relies on machine learning (ML) to use the vast interconnectedness and large ...
Intrusion Detection System in Industrial Cyber-Physical System Using Clustered Federated Learning
- Vellingiri Jayagopal,
- Mohanraj Elangovan,
- Saranya Sathasivam Singaram,
- Kavitha Bharathi Shanmugam,
- Balu Subramaniam,
- Srinivasarao Bhukya
The quick convergence in the industrial infrastructure with computing and networking has proliferated the attacks of industry-based Cyber-Physical Systems (CPS). Protecting such massive, sophisticated, and varied industrial CPSs from cyber-attacks ...
Mathematically Modified Adaptive Neuro-Fuzzy Inference System for an Intelligent Cyber Security System
- Divyapushpalakshmi Marimuthu,
- Ganga Rama Koteswara Rao,
- Abolfazl Mehbodniya,
- Dhavamani Mohanasundaram,
- Chandru Kavindapadi Sundaram,
- Anto Bennet Maria,
- Devi Mani
Cybersecurity is defending sensitive information and crucial systems against Internet attacks. Cyber-Physical Systems (CPS) and the Internet of Things (IoT) are becoming increasingly significant in critical infrastructure, government, and daily ...
An Efficient Vehicle Detection and Shadow Removal Using Gaussian Mixture Models with Blob Analysis for Machine Vision Application
Cities in the modern era often face a hectic challenge due to increased urbanization and industrialization. This problem arises as the number of cars on the road increases over time, and the need for traffic data becomes important. This increase ...
Energy Efficient Mathematical Model for Cyber-Physical Systems: A Model for Industrial Internet of Things
- Ramachandran Veerachamy,
- Ganga Rama Koteswara Rao,
- Vishnu Priya Arivanantham,
- Sangeetha Kuppusamy,
- Priya Velayutham,
- Rajeshkumar Govindaraj
Proliferated usage of computer devices, smart objects, and electronics significantly impacts the atmosphere, which is inevitable. The existing context has engineered schemes, or Cyber-Physical Systems (CPS), that integrate physical and computation ...
Towards to Characterization of Network Management Traffic in OpenStack-Based Clouds
- Adnei W. Donatti,
- Charles C. Miers,
- Guilherme P. Koslovski,
- Maurício A. Pillon,
- Tereza C. M. B. Carvalho
OpenStack is versatile and popular, allowing full customization for creating private or public IaaS clouds. This work addresses a network traffic analysis and characterization for the management domain inside OpenStack clouds. We conduct an ...
MC-NN: An End-to-End Multi-Channel Neural Network Approach for Predicting Influenza A Virus Hosts and Antigenic Types
Influenza poses a significant threat to public health, particularly among the elderly, young children, and people with underlying diseases. The manifestation of severe conditions, such as pneumonia, highlights the importance of preventing the ...
Impact Analysis to Detect and Mitigate Distributed Denial of Service Attacks with Ryu-SDN Controller: A Comparative Analysis of Four Different Machine Learning Classification Algorithms
Today, the Distributed Denial of Service (DDoS) attacks are progressed, which appears in different profiles besides dissimilar standards, in this manner it is very difficult to identify and tackle with these attacks. The fiscal impact of DDoS is ...
Prediction of Early Dropouts in Patient Remote Monitoring Programs
The analysis of medical data is a significant opportunity worldwide for national health systems to reduce costs and at the same time improve healthcare. The utilization of these technologies is done in the context of monitoring health issues, ...
An Efficient Tactic for Analysis and Evaluation of Malware Dump File Using the Volatility Tool
Malware refers to “malicious software” which is designed to disrupt or steal data from a computer, network or server. Malware-based attacks are significantly on the rise, among which ransomware attacks are quite prominent and capable of ...
ABE Cloud Privacy Improvisation on Healthcare Systems Using Trained Neural Networking Technique
Healthcare organizations deal with sensitive data and patient information shared via medical servers and Electronic Health Records (EHR). The data on cloud are unsecure as it operates on multi-user recommendations. In this paper, a machine ...
An Efficient Graph Mining Approach Using Evidence Based Fuzzy Soft Set Method
The Dempster-Shafer theory of evidence is a method of fuzzy soft that is a very hot way to deal with uncertainty in the information technology field. Existing Measures to determine the position of a node within a graph are either based on the ...
Fault Diagnosis of Tenessee Eastman Process with Detection Quality Using IMVOA with Hybrid DL Technique in IIOT
This work presents a deep learning (DL) based approach to defect identification in continuous systems. The Tennessee Eastman Procedure was chosen as a use case for this study because it involves a dispersed network of sensors throughout a ...
ROS-Enabled Collaborative Navigation and Manipulation with Heterogeneous Robots
One of the most difficult tasks for a mobile robot is navigation. Navigation and manipulation of heterogeneous robots are becoming more important in the field of industry, defence, search and rescue, etc. This paper mainly focuses on the ...
Bibo the Moving Cup for People Affected by Dementia: Design, Ethical Considerations, and First Observations in Use
- Avgi Kollakidou,
- Kevin Lefeuvre,
- Christian Sønderskov Zarp-Falden,
- Elodie Malbois,
- Leon Bodenhagen,
- Norbert Krüger,
- Eva Hornecker
We present the concept and technical realisation for a cup that moves and lights up to bring itself to the attention of a person to trigger him/her taking a sip as a response. We then reflect on different ethical dimensions connected to the ...
Explaining Eye Diseases Detected by Machine Learning Using SHAP: A Case Study of Diabetic Retinopathy and Choroidal Nevus
Most visual impairment and eye cancers are preventable if detected in their early stages. Diabetic retinopathy (DR) is a significant cause of blindness worldwide and a serious public health concern in a population aged 20–65. With the increasing ...
Assessing the Impact of IoT Enabled E-Learning System for Higher Education
- Shameemul Haque,
- Md Alimul Haque,
- Devanshu Kumar,
- Khushboo Mishra,
- Farheen Islam,
- Sultan Ahmad,
- Kailash Kumar,
- Binay Kumar Mishra
In this paper, a hypothetical investigation alongside a genuine review is investigated. The theoretical and empirical results demonstrated the significant impact of IoT in the physical training system in terms of learning and making due factors. ...
An Enhanced Generative Adversarial Network Model for Fingerprint Presentation Attack Detection
Automatic fingerprint recognition systems (AFRS) have played a significant role in biometric security in recent years. However, it is vulnerable to several threats which can put the AFRS at substantial risk. Presentation attack or spoofing is one ...
Protecting Data and Queries in Cloud-Based Scenarios
The availability of cloud services offered by different providers brings several advantages to users and companies, facilitating the storage, sharing, and processing of data. At the same time, the adoption of cloud services brings new security and ...
Deep Learning-Based Computer-Aided Diagnosis Model for the Identification and Classification of Mammography Images
Cancer of the breast is an illness that has the potential to be fatal for females all over the world. Even with the advancements that have been made in treatment, breast cancer cannot be prevented or cured; however, with early identification, one'...
Designing of Energy-Efficient Approximate Multiplier Circuit for Processing Unit of IoT Devices
Approximation strategies and techniques play a vital role in reducing power consumption, area and enhancing efficiency for numerous applications such as Internet of Things (IoT), digital signal processing, image processing and wearable devices. ...
An Efficient Hybrid Approach for Intrusion Detection in Cyber Traffic Using Autoencoders
Intrusion detection is an essential security issue in the present digital climate. Spiteful cyber attacks can frequently hide/sneak in abundant volumes of regular data in lopsided network traffic. In cyberspace, it has a great level of stealth and ...
A Semi-automated Approach for Bengali Neologism
Neologisms refer to newly coined words or phrases adopted by a language, and it is a slow but ongoing process that occurs in all languages. Sometimes, rarely used or obsolete words are also considered neologisms. Certain events, such as wars, the ...
Graph-Enhanced Biomedical Abstractive Summarization Via Factual Evidence Extraction
- Giacomo Frisoni,
- Paolo Italiani,
- Gianluca Moro,
- Ilaria Bartolini,
- Marco Antonio Boschetti,
- Antonella Carbonaro
Infusing structured semantic representations into language models is a rising research trend underpinning many natural language processing tasks that require understanding and reasoning capabilities. Decoupling factual non-ambiguous concept units ...
Energy-Aware Reliable Medium Access Control Protocol for Energy-Efficient and Reliable Data Communication in Wireless Sensor Networks
Wireless Sensor Networks (WSN) can be considered as a self-organizing system that might be a good alternative to wired systems due to their ease of deployment in distant places. The primary goal of this project is to develop an energy-efficient, ...