Android applications are becoming increasingly powerful in recent years. While their functionality is still of paramount importance to users, the energy efficiency of these applications is also gaining more and more a...
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Android applications are becoming increasingly powerful in recent years. While their functionality is still of paramount importance to users, the energy efficiency of these applications is also gaining more and more attention. Researchers have discovered various types of energy defects in Android applications, which could quickly drain the battery power of mobile devices. Such defects not only cause inconvenience to users, but also frustrate Android developers as diagnosing the energy inefficiency of a software product is a non-trivial task. In this work, we perform a literature review to understand the state of the art of energy inefficiency diagnosis for Android applications. We identified 55 research papers published in recent years and classified existing studies from four different perspectives, including power estimation method, hardware component, types of energy defects, and program analysis approach. We also did a cross-perspective analysis to summarize and compare our studied techniques. We hope that our review can help structure and unify the literature and shed light on future research, as well as drawing developers' attention to build energy-efficient Android applications.
Satellite image classification is the most significant remote sensing method for computerized analysis and pattern detection of satellite data. This method relies on the image's diversity structures and necessitat...
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Clinical auxiliary decision-making is related to life and health of patients, so the deep model needs to extract the personalised representation of patients to ensure high analysis and prediction accuracy;and provide ...
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Gait recognition is an active research area that uses a walking theme to identify the subject *** Gait Recognition(HGR)is performed without any cooperation from the ***,in practice,it remains a challenging task under ...
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Gait recognition is an active research area that uses a walking theme to identify the subject *** Gait Recognition(HGR)is performed without any cooperation from the ***,in practice,it remains a challenging task under diverse walking sequences due to the covariant factors such as normal walking and walking with wearing a ***,over the years,have worked on successfully identifying subjects using different techniques,but there is still room for improvement in accuracy due to these covariant *** paper proposes an automated model-free framework for human gait recognition in this *** are a few critical steps in the proposed ***,optical flow-based motion region esti-mation and dynamic coordinates-based cropping are *** second step involves training a fine-tuned pre-trained MobileNetV2 model on both original and optical flow cropped frames;the training has been conducted using static *** third step proposed a fusion technique known as normal distribution serially *** the fourth step,a better optimization algorithm is applied to select the best features,which are then classified using a Bi-Layered neural *** publicly available datasets,CASIA A,CASIA B,and CASIA C,were used in the experimental process and obtained average accuracies of 99.6%,91.6%,and 95.02%,*** proposed framework has achieved improved accuracy compared to the other methods.
The surrounding environmental and climatic conditions have a significant impact on the utilisation of ecosystem services for recreational purposes. Climate change poses a threat to future natural leisure opportunities...
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In today’s fast-paced world,many elderly individuals struggle to adhere to their medication schedules,especially those with memory-related conditions like Alzheimer’s disease,leading to serious health risks,hospital...
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In today’s fast-paced world,many elderly individuals struggle to adhere to their medication schedules,especially those with memory-related conditions like Alzheimer’s disease,leading to serious health risks,hospital-izations,and increased healthcare *** reminder systems often fail due to a lack of personalization and real-time *** address this critical challenge,we introduce MediServe,an advanced IoT-enabled medication management system that seamlessly integrates deep learning techniques to provide a personalized,secure,and adaptive *** features a smart medication box equipped with biometric authentication,such as fingerprint recognition,ensuring authorized access to prescribed medication while preventing misuse.A user-friendly mobile application complements the system,offering real-time notifications,adherence tracking,and emergency alerts for caregivers and healthcare *** system employs predictive deep learning models,achieving an impressive classification accuracy of 98%,to analyze user behavior,detect anomalies in medication adherence,and optimize scheduling based on an individual’s habits and health ***,MediServe enhances accessibility by employing natural language processing(NLP)models for voice-activated interactions and text-to-speech capabilities,making it especially beneficial for visually impaired users and those with cognitive ***-based data analytics and wireless connectivity facilitate remote monitoring,ensuring that caregivers receive instant alerts in case of missed doses or medication ***,machine learning-based clustering and anomaly detection refine medication reminders by adapting to users’changing health *** combining IoT,deep learning,and advanced security protocols,MediServe delivers a comprehensive,intelligent,and inclusive solution for medication *** innovative approach not only improves the quality of life for elderly
In the contemporary landscape, autonomous vehicles (AVs) have emerged as a prominent technological advancement globally. Despite their widespread adoption, significant hurdles remain, with security standing out as a c...
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With the prevalence of artificial intelligence, people collect data through numerous sensors and use machine learning to create models for intelligent services. However, data privacy and massive data issues are raised...
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Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wirel...
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Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wireless propagation environment and the broad coverage pose severe threats to the protection of private data. Emerging covert communications provides a promising solution to achieve robust communication security. Aiming at facilitating the practical implementation of covert communications in space/air networks, we present a tutorial overview of its potentials, scenarios, and key technologies. Specifically, first, the commonly used covertness constraint model, covert performance metrics, and potential application scenarios are briefly introduced. Then, several efficient methods that introduce uncertainty into the covert system are thoroughly summarized, followed by several critical enabling technologies, including joint resource allocation and deployment/trajectory design, multi-antenna and beamforming techniques, reconfigurable intelligent surface(RIS), and artificial intelligence algorithms. Finally, we highlight some open issues for future investigation.
Through Wireless Sensor Networks(WSN)formation,industrial and academic communities have seen remarkable development in recent *** of the most common techniques to derive the best out of wireless sensor networks is to ...
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Through Wireless Sensor Networks(WSN)formation,industrial and academic communities have seen remarkable development in recent *** of the most common techniques to derive the best out of wireless sensor networks is to upgrade the operating *** most important problem is the arrangement of optimal number of sensor nodes as clusters to discuss clustering *** this method,new client nodes and dynamic methods are used to determine the optimal number of clusters and cluster heads which are to be better organized and proposed to classify each *** of effective energy use and the ability to decide the best method of attachments are *** Problem coverage find change ability network route due to which traffic and delays keep the performance to be very high.A newer version of Gravity Analysis Algorithm(GAA)is used to solve this *** proposed new approach GAA is introduced to improve network lifetime,increase system energy efficiency and end delay *** results show that modified GAA performance is better than other networks and it has more advanced Life Time Delay Clustering Algorithms-LTDCA *** proposed method provides a set of data collection and increased throughput in wireless sensor networks.
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