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.

The number of smartphone users has increased from 3.6 billion in 2016 to 6.25 billion by 2021, which shows that mobile phone usage has increased dramatically over the past few years. This is due to the development of mobile computing applications like commerce, healthcare, e-learning, etc. The use of mobile devices has resulted in an exponential rise in the amount of data generated and as a result the amount of energy consumed has increased. This is where cloud computing plays a major role. Cloud computing has transformed traditional mobile computing. The new mobile cloud not only provides on-demand services but also data storage and increased energy efficiency. Through mobile computing based on cloud computing, mobile device functions can be virtualized, reducing power consumption. In this paper, the authors survey application and potential of mobile cloud computing and present the energy-efficient ways. Also, the paper discusses development opportunities of mobile cloud computing. The research also mentions some of the major challenges in current mobile computing technology.