In a digital landscape demanding cost-effective yet robust data storage solutions, Portable Storage Area Network (SAN) became an affordable alternative for data storage systems. A portable SAN system using the Raspber...
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ISBN:
(数字)9798350372632
ISBN:
(纸本)9798350372649
In a digital landscape demanding cost-effective yet robust data storage solutions, Portable Storage Area Network (SAN) became an affordable alternative for data storage systems. A portable SAN system using the Raspberry Pi solution offers personal users the ability to easily expand their storage capacity, improve data organization and management, protect their data, and have a flexible and mobile solution. Users can share any sort of data. This project aims to address the increasing demand for efficient storage solutions by constructing a portable SAN system using the Raspberry Pi's compact size and budget-friendly hardware. The proposed SAN system enhances data organization, expands storage capacity, and offers secure, flexible data access. Targeting individual users and small to medium-sized enterprises, the project covers hardware specifications, intricate design elements, and the seamless integration of OpenMedia Vault, Raspberry Pi OS, and the iSCSI protocol. Performance, stability, and practicality of the SAN solution are visually presented through extensive testing, to prove its potential benefits for diverse storage needs.
This study presents a novel approach for brain MRI classification by integrating multiple state-of-the-art deep learning (DL) architectures, including VGG16, EfficientNet, MobileNet, AlexNet, and ResNet50, with an att...
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Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for smal...
Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs.
Road traffic injuries cause considerable life and economic losses to individuals, their families, and nations as a whole. To avoid road accidents, Vehicular Ad-hoc Networks (VANETs) play a vital role by enhancing tran...
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Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense ***,an optimality system for HWSNs is developed to suppress malware propagation in...
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Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense ***,an optimality system for HWSNs is developed to suppress malware propagation in this ***,a heterogeneous-susceptible-exposed-infectious-recovered-susceptible(HSEIRS)model is proposed to describe the state dynamics of heterogeneous sensor nodes(HSNs)in ***,the existence of an optimal control problem with installing antivirus on HSNs to minimize the sum of the cumulative infection probabilities of HWSNs at a low cost based on the HSEIRS model is proved,and then an optimal control strategy for the problem is derived by the optimal control ***,the optimal control strategy based on the HSEIRS model is transformed into corresponding Hamiltonian by the Pontryagin’s minimum principle,and the corresponding optimality system is ***,the effectiveness of the optimality system is validated by the experimental simulations,and the results show that the infectious HSNs will fall to an extremely low level at a low cost.
作者:
Karale, AnkitaRajawat, Anand SinghGoyal, S.B.Computer Engineering
Sandip Foundation’s Sandip Institute of Research Center Nashik School of Computer Science & Engineering Sandip University Nashik India Faculty of Information Technology City University Petaling Jaya Malaysia
Waste management has become a pressing problem in a world that is becoming more and more urbanised. Traditional ways of dealing with trash are usually inefficient and bad, leading to pollution, health problems, and wa...
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ISBN:
(纸本)9781839539831
Waste management has become a pressing problem in a world that is becoming more and more urbanised. Traditional ways of dealing with trash are usually inefficient and bad, leading to pollution, health problems, and wasted resources. As an answer to these problems, the Internet of Things (IoT) has changed the way trash is handled in a big way. This abstract looks at how smart waste management based on the Internet of Things could totally change the business of garbage disposal. Through a network of sensors and devices, the Internet of Things (IoT) connects trash cans, garbage trucks, and waste processing facilities so that they can be monitored and improved in real time. A smart waste management system that is built on IoT has many benefits. With the real-time information it gives about how much trash is being made, routes for collecting trash can be made more efficient in terms of time and fuel use. This cuts down on the number of times trash needs to be picked up, reduces the amount of greenhouse gases released, and saves money. Sensors in trash cans can also find dangerous or flammable items, so they can be dealt with right away and any problems can be avoided. Also, the Internet of Things makes it possible for predictive analytics, which help waste management officials predict how much trash will be made and use their resources well. Using smart waste sorting methods like optical sensors and machine learning algorithms, recyclable and non-recyclable trash can be correctly found and sorted. This helps people recycle more and puts less pressure on landfills. Smart trash management systems that are based on the Internet of Things (IoT) get more people involved and help them understand. Mobile apps and smart devices can tell a person when their trash will be picked up, where the nearest recycling sites are, and how much trash they make. People are encouraged to act responsibly and throw away trash in ways that are good for the environment. Smart waste management base
Predictions of variations in exchange rates of other currencies to a vehicle currency such as the Dollar (USD) are vital in order to reduce the risks for international transactions. In this study, we use a heuris...
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Research on fake news has gained significant traction in a number of fields, We describe how the issue is tackled from a natural language processing standpoint in this research with the aim of developing identify fals...
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Sarcasm detection is one the most challenging task in natural language processing. Though sentiment semantics are necessary to improve sarcasm detection performance, existing DL-based sarcasm detection models do not f...
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Autonomous Vehicle (AV) usage has become predominant in the rapidly evolving landscape of urban transportation. Integrating AVs and non-AVs in the existing traffic infrastructure has significantly increased the comple...
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