Blockchain technology39;s decentralized and immutable data storage has changed a number of sectors. But typical blockchain networks scalability issues prevent them from being widely used for large-scale applications...
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The proceedings contain 114 papers. The topics discussed include: multi-attribute featured layout generation for graphic design using capsule networks;combining CNNs and Bi-LSTMs for enhanced network intrusion detecti...
ISBN:
(纸本)9798350321487
The proceedings contain 114 papers. The topics discussed include: multi-attribute featured layout generation for graphic design using capsule networks;combining CNNs and Bi-LSTMs for enhanced network intrusion detection: a deep learning approach;IoT-based monitoring of refrigerated vaccine storage: a literature review and a proposed solution;review the recent IoT systems.for healthcare applications;combining data mining with rigorous whole-genome phylogenetics enables detailed comparative genomics from over 2.3 million genomes across Coronaviridae;fake news detection using cellular automata based deep learning;a new approach to sentiment analysis on twitter data with LSTM;action localization and recognition through unsupervised I3D and TSN;and improving prospective healthcare outcomes by leveraging open data and explainable AI.
This study paper explores the critical topic of formal verification of smart contracts in distributed ledger technology (DLT) systems. Smart contracts, self-executing code running on blockchain platforms, have gained ...
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The main target is to use genetic algorithms to calculate the optimal location and size of distributed Generation (DG) units for power distribution systems. The algorithm39;s flexibility allows engineers, electric u...
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The proceedings contain 15 papers. The special focus in this conference is on Smart Technologies and Innovation Management. The topics include: Prospective Directions in the Computer systems.Industry Foundation Classe...
ISBN:
(纸本)9783031649561
The proceedings contain 15 papers. The special focus in this conference is on Smart Technologies and Innovation Management. The topics include: Prospective Directions in the Computer systems.Industry Foundation Classes (IFC) Shaping Data Exchange for Cities Sustainability and Resilience;a Proposal of Model Combining Semantic Analysis and Knowledge Graph for Question Answering System in Vietnamese Law of Science and Technology;trends and Innovative Tactics in Startup Innovation: A Survey;interactive Web Mapping for Geolocation of Socio-community Infrastructure in a Developing Country;development of Digital Capabilities for E-commerce Agribusiness: An Exploratory Research;a Social-Software-Based Telemedicine Information System for Facilitating Healthcare Services;lab-to-Market Product Innovation: Implications of Using a Translational Research & Development Model and Methodology;a Multilayered Process Framework for Predicting Students’ Academic Performance in Open and Distance Learning;a New Notification System for Tracking Ethereum Transactions with Social Media Software;A Secure Consortium-Blockchain-Enabled Communication Scheme for DNA-Based Smart Health systems.review on Machine Learning for Zero-Day Exploit Detection and Response;A Review of AI in Spear Phishing Defense: Detecting and Thwarting Advanced Email Threats;energy-Efficient Dynamic Adaptive Encryption for Low-Resource Internet of Things.
The proceedings contain 11 papers. The topics discussed include: EMiRAs-empathic mixed reality agents;empathic directions for the sounds of parenting technology: the case of baby monitors;empathy-building through pers...
ISBN:
(纸本)9798400717888
The proceedings contain 11 papers. The topics discussed include: EMiRAs-empathic mixed reality agents;empathic directions for the sounds of parenting technology: the case of baby monitors;empathy-building through personalized pixel crafting: a co-creation platform for researchers and individuals with intellectual disabilities;mENTER: co-designing an mHealth peer navigator intervention for people with disabilities;on the design risks of empathy fatigue;weight bias in design: unpacking implicit researcher beliefs for building empathy;beyond empathy: role-taking as a structural approach to participatory design;differences in physiological responses to emotional stimuli and physiological responses to walking movements while playing a walking-type VR game;and empathy-centric design in assistive technologies for cerebral palsy and disabilities: balancing aesthetics and functionality.
This paper explores the application of ARIMA(AutoRegressive Integrated Moving Average) and LSTM(Long Short-Term Memory) in predicting future global temperatures in the context of climate change. The authors employ bot...
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This article puts forward a method to address the issue of time synchronization in distributed current sensing for underground high-voltage (HV) cable systems. In the context, the detection of distributed sheath curre...
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In recent years, Closed-circuit Television (CCTV) cameras have been playing a vital role in the surveillance of both public and private areas. The primary objective of surveillance is to monitor human behavior and roa...
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ISBN:
(纸本)9798350372977;9798350372984
In recent years, Closed-circuit Television (CCTV) cameras have been playing a vital role in the surveillance of both public and private areas. The primary objective of surveillance is to monitor human behavior and road conditions. In the real-world situation, detecting, and recognizing abnormal activities poses significant challenges due to the densely crowded environment and the complex nature of transportation systems. These factors make it difficult to automatically identify various anomalies that occur while traveling, leading to emergencies, and endangering human life and property. This study introduces an automatic detection framework for recognizing road anomalies such as accidents, fighting, car fires, and armed snatching (gunpoint) in road surveillance videos. After reviewing the literature, the review directs that convolutional neural networks (CNNs) are a specialized deep learning approach well suited for image and video analysis. The proposed methodology combines the pre-trained CNN models with Data Augmentation (DA) techniques to fine-tune hyperparameters such as learning rate and momentum that enhance the model learning accuracy and performance for recognizing road anomalies. Furthermore, it introduced a rolling prediction algorithm to solve the flickering problem during testing and created a new road anomaly dataset (RAD) as a benchmark consisting of road surveillance videos and images. Our proposed model combined with the InceptionV3 pre-trained model achieved a best accuracy is 98.81% for detection and classification as compared to other deep learning models.
With the establishment and development of integrated monitoring platforms and communication information platforms for intelligent substations, the data volume of the power system is showing explosive growth. However, ...
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