Editorial 3/07 DOI Creative Commons

Michael McLean

Current Oncology, Journal Year: 2007, Volume and Issue: 14(3), P. 85 - 85

Published: June 1, 2007

Malignant melanoma (MM) is the "great mime" of dermatopathology, and it can present such rare variants that even most experienced pathologist might miss or misdiagnose them.Naevoid (NM), which accounts for about 1% all MM cases, a constant challenge, when not diagnosed in timely manner, lead to death.In recent years, artificial intelligence has revolutionised much what been achieved biomedical field, once seemed distant now almost incorporated into diagnostic therapeutic flow chart.In this paper, we results machine learning approach applies fast random forest (FRF) algorithm cohort naevoid melanomas an empt understand if how could be business process modelling notation (BPMN) approach.The FRF provides innovative formulating clinical protocol oriented toward reducing risk NM misdiagnosis.The work methodology integrate mapped process.

Language: Английский

A multilevel interleaved group attention-based convolutional network for gas detection via an electronic nose system DOI
Shichao Zhai, Zhe Li, Huisheng Zhang

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 133, P. 108038 - 108038

Published: Feb. 8, 2024

Language: Английский

Citations

11
A New Trend in Cryptographic Information Security for Industry 5.0: A Systematic Review DOI Creative Commons
Zaffar Ahmed Shaikh, Fahima Hajjej,

Yeter Demir Uslu

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 7156 - 7169

Published: Jan. 1, 2024

Malicious assaults and information leakage have grown in importance practically every area of communication technology (ICT) recent years. Enterprise ledger organization, preservation, security, protection are all greatly aided by security (IS). To maintain their positions the market, industries must safeguard data other vital assets. The main goals this paper's systematic review, which covers entire process privacy to introduce cryptographic IS for Industry 5.0 (the Fifth Industrial Revolution) as a comprehensive solution that provides regulatory compliance policies addition industrial goals. review four areas: (i) recognizing need frameworks be developed secure lifecycle; (ii) emphasizing guidelines, procedures, countermeasures 5.0; (iii) applying control, access, availability real-time; (iv) proposing futuristic architecture security. Furthermore, analysis previously published state-of-the-art techniques is presented paper. These survive with various limitations challenges, including intercommunication exchange, fine-grained control interconnectivity-related issues, affect adoption an programmes. At end we investigated few open research problems mentioned those involved design re-encryption-enabled future developments.

Language: Английский

Citations

9
An Entrepreneurial University Ecosystem for Sustaining the Twin Transition through a Complex Adaptive System Approach DOI
Giustina Secundo, Alessandro Massaro, Pasquale Del Vecchio

et al.

IEEE Transactions on Engineering Management, Journal Year: 2024, Volume and Issue: 71, P. 10966 - 10983

Published: Jan. 1, 2024

The impact of digital and green transitions (the " twin transition ") brings societal challenges that universities must address proactively by assuming an ecosystem organisational model. Beginning from this premise, paper aims to investigate how entrepreneurial university having adopted a dynamic evolution model can sustain its stakeholders in facing the twin transition. study proposes adopt system dynamics as methodology for modelling complexity characterising terms nodes knowledge flow their accomplishment Accordingly, presents evidence case South Italy, LUM University "Giuseppe Degennaro" Bari. evolved response stakeholders' both transformation Findings show change quickly incorporate entrepreneurship activities complex interrelationships among various according adaptive Implications theory practice regard novel role ecosystems actively engaged sustaining achievement transition's strategic goals.

Language: Английский

Citations

4
Quasi-particle band structure and optical absorption in MoS 2: Impact of spin-orbit coupling and vdW corrections for photodetection application DOI
Shehu Aminu Yamusa, Najeh Rekik,

A. Shaari

et al.

Physica B Condensed Matter, Journal Year: 2025, Volume and Issue: unknown, P. 417074 - 417074

Published: March 1, 2025

Language: Английский

Citations

0
Intelligent Materials and Nanomaterials Improving Physical Properties and Control Oriented on Electronic Implementations DOI Open Access
Alessandro Massaro

Electronics, Journal Year: 2023, Volume and Issue: 12(18), P. 3772 - 3772

Published: Sept. 6, 2023

The review highlights possible research topics matching the experimental physics of matter with advances in electronics to improve intelligent design and control innovative smart materials. Specifically, following European guidelines Key Enabling Technologies (KETs), I propose different suitable for project proposals research, including nanomaterials, nanocomposite materials, nanotechnology, artificial intelligence (AI), a focus on implementation. paper provides new framework addressing study AI driving electronic systems procedures determine physical properties versatile materials dynamically material’s “self-reaction” when applying external stimuli. proposed allows one ideate circuital solutions be integrated embedded formed algorithms circuits. challenge is bring together concepts regarding provide direction applications. discussed are classified as Technology Readiness Levels (TRL) 1 2.

Language: Английский

Citations

9
Artificial Intelligence Applied to a First Screening of Naevoid Melanoma: A New Use of Fast Random Forest Algorithm in Dermatopathology DOI Creative Commons
Gerardo Cazzato, Alessandro Massaro, Anna Colagrande

et al.

Current Oncology, Journal Year: 2023, Volume and Issue: 30(7), P. 6066 - 6078

Published: June 23, 2023

Malignant melanoma (MM) is the “great mime” of dermatopathology, and it can present such rare variants that even most experienced pathologist might miss or misdiagnose them. Naevoid (NM), which accounts for about 1% all MM cases, a constant challenge, when not diagnosed in timely manner, lead to death. In recent years, artificial intelligence has revolutionised much what been achieved biomedical field, once seemed distant now almost incorporated into diagnostic therapeutic flow chart. this paper, we results machine learning approach applies fast random forest (FRF) algorithm cohort naevoid melanomas an attempt understand if how could be business process modelling notation (BPMN) approach. The FRF provides innovative formulating clinical protocol oriented toward reducing risk NM misdiagnosis. work methodology integrate mapped process.

Language: Английский

Citations

8
ANNs Predicting Noisy Signals in Electronic Circuits: A Model Predicting the Signal Trend in Amplification Systems DOI Creative Commons
Alessandro Massaro

AI, Journal Year: 2024, Volume and Issue: 5(2), P. 533 - 549

Published: April 17, 2024

In the proposed paper, an artificial neural network (ANN) algorithm is applied to predict electronic circuit outputs of voltage signals in Industry 4.0/5.0 scenarios. This approach suitable possible uncorrected behavior control circuits affected by unknown noises, and reproduce a testbed method simulating noise effect influencing amplification input sinusoidal signal, which basic fundamental signal for controlled manufacturing systems. The performed simulations take into account different changing their time-domain trend frequency prove possibility predicting when complex are considered at input, including additive disturbs noises. results highlight that it construct good ANN training model processing only registered output without considering profile (which typically unknown). behaves as black box 5.0 processes automating machine tuning procedures. By analyzing state-of-the-art ANNs, study offers innovative ANN-based versatile solution able process various profiles requiring prior knowledge characteristics.

Language: Английский

Citations

2
Artificial Intelligence Enabling Denoising in Passive Electronic Filtering Circuits for Industry 5.0 Machines DOI Creative Commons
Alessandro Massaro

Machines, Journal Year: 2024, Volume and Issue: 12(8), P. 551 - 551

Published: Aug. 13, 2024

The paper proposes an innovative model able to predict the output signals of resistance and capacitance (RC) low-pass filters for machine-controlled systems. Specifically, work is focused on analysis parametric responses in time- frequency-domain filter signals, by considering a white generic noise superimposed onto input sinusoidal signal. goal using black-box support denoising process means double-stage RC filter. Artificial neural networks (ANNs) random forest (RF) algorithms are compared noisy signals. concluded defining guidelines correct voltage knowing predictions adding further elements correcting distorted suitable implementation Industry 5.0 Digital Twin (DT) applied manufacturing processes.

Language: Английский

Citations

1
Deep Learning-Based Intrusion Detection for Rare Class Network Attacks DOI Open Access
Yang Yu, Yuheng Gu, Yu Yan

et al.

Published: Aug. 24, 2023

With the continuous development of network technology, complex systems generate massive unbalanced attack traffic. Due to severe imbalance in quantities normal samples and samples, as well among different types intrusion detection suffer from low rates for rare class data. In this paper, we propose a geometric synthetic minority oversampling technique based on optimized kernel density estimation algorithm. This method can diverse data by learning distribution while maintaining similarity with original sample features. Meanwhile, balanced is input feature extraction module built upon multiple denoising autoencoders, reducing information redundancy high-dimensional improving performance unknown attacks. Subsequently, soft voting ensemble utilized multi-class anomaly dimensionally reduced Finally, an system constructed preprocessing, handling, extraction, modules, validated NSL-KDD N-BaIoT datasets. Comparative experiments baseline models other state-of-the-art methods demonstrate that proposed improves rate Furthermore, it achieves good overall Internet Things dataset (N-BaIoT), indicating its strong applicability.

Language: Английский

Citations

2
RETRACTED ARTICLE: Optoelectronic sensor fault detection based predictive maintenance smart industry 4.0 using machine learning techniques DOI

Chenfeng Zhu,

Sihao Shao

Optical and Quantum Electronics, Journal Year: 2023, Volume and Issue: 55(13)

Published: Oct. 7, 2023

Language: Английский

Citations

2