Mobile Cloud Computing and Sustainable Development

García-Peñalvo, Francisco José; Sharma, Akash; Chhabra, Anureet; Singh, Sunil K.; Kumar, Sudhakar; Arya, Varsha; Gaurav, Akshat

doi:10.4018/ijcac.312583

Cited by 17 publications

(6 citation statements)

References 23 publications

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“…Participants in the study needed to be between 18 and 70 years old and capable of adhering to the anticipated ages of the research procedure 28 , 37 , 38 . VOICED used a built-in microphone of a mobile device 39 and an applicable m-health system, Vox4Health 40 , 41 , to collect a speech signal of vowel ‘a’ in real time. In every recording, the sample rate was set at 8000 Hz, and the resolution was set at 32 bits.…”

Section: Methodsmentioning

confidence: 99%

A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection

Verma,

Benjwal,

Chhabra

et al. 2023

Sci Rep

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Voice is an essential component of human communication, serving as a fundamental medium for expressing thoughts, emotions, and ideas. Disruptions in vocal fold vibratory patterns can lead to voice disorders, which can have a profound impact on interpersonal interactions. Early detection of voice disorders is crucial for improving voice health and quality of life. This research proposes a novel methodology called VDDMFS [voice disorder detection using MFCC (Mel-frequency cepstral coefficients), fundamental frequency and spectral centroid] which combines an artificial neural network (ANN) trained on acoustic attributes and a long short-term memory (LSTM) model trained on MFCC attributes. Subsequently, the probabilities generated by both the ANN and LSTM models are stacked and used as input for XGBoost, which detects whether a voice is disordered or not, resulting in more accurate voice disorder detection. This approach achieved promising results, with an accuracy of 95.67%, sensitivity of 95.36%, specificity of 96.49% and f1 score of 96.9%, outperforming existing techniques.

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Section: Methodsmentioning

confidence: 99%

A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection

Verma,

Benjwal,

Chhabra

et al. 2023

Sci Rep

Self Cite

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“…This involves reusing and recycling IT equipment and components to reduce waste and environmental impact. By extending the lifespan of IT equipment, circular economy principles can help reduce the need for new equipment and promote more sustainable consumption patterns (Peñalvo et al, 2022;Ion & Gheorghe, 2014). Finally, there is a need for increased awareness and education about sustainable CC.…”

Section: Literature Reviewmentioning

confidence: 99%

Cloud computing for sustainable development: An analysis of environmental, economic and social benefits

Yenugula¹,

Sahoo²,

Goswami³

2024

10.5267/j.jfs

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This research paper examines the role of cloud computing in promoting sustainable development. Cloud Computing (CC) has emerged as a transformative technology that has the potential to reduce the environmental impact of businesses and organizations, while also enabling economic growth and social development. The paper explores the environmental benefits of cloud computing, including energy efficiency, reduced carbon emissions, and the potential for renewable energy integration. It also examines the economic and social benefits of cloud computing, including cost savings, increased productivity, and improved access to technology. The paper concludes by highlighting the potential challenges and opportunities associated with the adoption of cloud computing for sustainable development and identifies key areas for future research and policy action. Overall, the paper argues that cloud computing has the potential to play a critical role in promoting sustainable development, and that further research and policy action are needed to realize its full potential.

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“…The proposed approach can be seamlessly extended to mobile devices and cloud computing [31], making them more resistant to errors and breakdowns. This improves connections between devices and cloud services, which helps the environment by using less energy and saving resources.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Stochastic Fault Tolerance for Self-Healing P2P Networks

Kumar,

Goyal,

Singh

et al. 2024

Preprint

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In the complex domain of reliable and flexible distributed systems, the challenging issue of Byzantine fault resilience is pervasive, particularly within the intricate framework of Peer-to-Peer (P2P) networks. The 'Adaptive Stochastic Fault Tolerance for Self-Healing P2P Networks' proposes a novel approach to self-healing in distributed peer-to-peer (P2P) systems. It combines ideas from stochastic Byzantine fault tolerance models with adaptive resilience strategies to detect and recover from failures within these complex networks by using probabilistic modeling. This allows P2P systems to adjust their resilience measures in real-time, effectively shielding themselves from unforeseen faults. Furthermore, the research provides extensive experimentation and empirical validation to demonstrate the effectiveness of the proposed approach.

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Mobile Cloud Computing and Sustainable Development

Cited by 17 publications

References 23 publications

A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection

A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection

Cloud computing for sustainable development: An analysis of environmental, economic and social benefits

Adaptive Stochastic Fault Tolerance for Self-Healing P2P Networks

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