Driven by a wide range of real-world applications, significant efforts have recently been made to explore device-free human activity recognition techniques that utilize the information collected various wireless infrastructures infer activities without need for monitored subject carry dedicated device. Existing device free approaches and systems, though yielding reasonably good performance in certain cases, are faced with major challenge. The signals arriving at receiving devices usually...

This paper presents WiPose, the first 3D human pose construction framework using commercial WiFi devices. From pervasive signals, WiPose can reconstruct skeletons composed of joints on both limbs and torso body. By overcoming technical challenges faced by traditional camera-based perception solutions, such as lighting occlusion, proposed sensing technique demonstrates potential to enable a new generation applications health care, assisted living, gaming, virtual reality. is based novel deep...

With the popular usage of mobile devices and smartphones, crowd sensing becomes pervasive in real life when human acts as sensors to report their observations about entities. For same entity, users may conflicting information, thus it is important identify true information reliable users. This task, referred truth discovery, has recently attracted much attention. Existing work typically assumes independence among However, correlations entities are commonly observed many applications. Such...

The recent proliferation of human-carried mobile devices has given rise to the crowd sensing systems. However, sensory data provided by individual participants are usually not reliable. To identify truthful values from data, topic truth discovery, whose goal is estimate user quality and infer truths through quality-aware aggregation, drawn significant attention. Though able improve aggregation accuracy, existing discovery approaches fail take into consideration an important issue in their...

In online social networks (OSNs), to evaluate trust from one user another indirectly connected user, the evidence in trusted paths (i.e., built through intermediate trustful users) should be carefully treated. Some may overlap with each other, leading a unique challenge of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">path dependence</i> , i.e., how aggregate values multiple dependent paths. OSNs bear characteristic high clustering, which...

The recent proliferation of human-carried mobile devices has given rise to the crowd sensing (MCS) systems. However, sensory data provided by participating workers are usually not reliable. As an efficient technique extract truthful information from unreliable data, truth discovery drawn significant attention. Currently, privacy concern poses a major challenge on design mechanisms. Although existing mechanism can conduct with high accuracy and strong guarantee, tremendous overhead is...

Abstract Na 3 V 2 (PO 4 ) , based on multi‐electron reactions between 3+ /V 4+ 5+ is a promising cathode material for SIBs. However, its practical application hampered by the inferior conductivity, large barrier of and stepwise phase transition. Herein, these issues are addressed constructing medium‐entropy (Na 3.2 1.1 Ti 0.2 Al Cr Mn Ni 0.1 ME‐NVP) with strong ME─O bond highly occupied Na2 sites. Benefiting from effect, ME‐NVP manifests phase‐transition–free reaction mechanism, two...

With the proliferation of sensor-rich mobile devices, crowd sensing has emerged as a new paradigm collecting information from physical world. However, sensory data provided by participating workers are usually not reliable. In order to identify truthful values data, topic truth discovery, whose goal is estimate each worker's reliability and infer underlying truths through weighted aggregation, widely studied. Since discovery incorporates workers' into aggregation procedure, it shows...

The recent proliferation of human-carried mobile devices has given rise to the crowd sensing systems. However, sensory data provided by individual participants are usually not reliable. To better utilize such data, topic truth discovery, whose goal is estimate user quality and infer reliable aggregated results through quality-aware aggregation, drawn significant attention. Though able improve aggregation accuracy, existing discovery approaches fail address privacy concerns users. In this...

Recent advances in deep learning motivate the use of neural networks Internet-of-Things (IoT) applications. These are modelled after signal processing human brain, thereby leading to significant advantages at perceptual tasks such as vision and speech recognition. IoT applications, however, often measure physical phenomena, where underlying physics (such inertia, wireless propagation, or natural frequency oscillation) fundamentally a function frequencies, offering better features domain....

Recently, significant efforts are made to explore device-free human activity recognition techniques that utilize the information collected by existing indoor wireless infrastructures without need for monitored subject carry a dedicated device. Most of work, however, focuses their attention on analysis signal received single In practice, there usually multiple devices "observing" same subject. Each these can be regarded as an source and provides us unique "view" observed Intuitively, if we...

Product reviews play an important role in guiding users’ purchase decision-making e-commerce platforms. However, it is challenging for users to find helpful that meet their preferences and experiences among overwhelming amount of reviews. Some works have been done recommend users, either from personalized or non-personalized views. While some existing models similar a target user, they neglect the user’s aspect user-product interactions measuring user similarity. Moreover, those predict...

Trust is a central component of social interactions among humans. Many applications motivate the consideration trust evaluation in online networks (OSNs). Some work has been proposed based on trusted graph. However, it still an open challenge to construct graph, especially terms selecting proper recommenders, which can be used predict trustworthiness unknown target efficiently and effectively. Based intuition that people who are close influential us make more acceptable recommendations, we...

As an effective way to solicit useful information from the crowd, crowdsourcing has emerged as a popular paradigm solve challenging tasks. However, data provided by participating workers are not always trustworthy. In real world, there may exist malicious in systems who conduct poisoning attacks for purpose of sabotage or financial rewards. Although aggregation methods such majority voting conducted on workers» labels order improve quality, they vulnerable treat all equally. capture variety...

Lithium-rich manganese-based layered oxides (LLOs) are considered to be the most promising cathode materials for next-generation lithium-ion batteries (LIBs) their higher reversible capacity, operating voltage, and lower cost compared with those of other commercially available materials. However, irreversible lattice oxygen release associated severe structural degradation that exacerbate under high temperature deep delithiation hinder large-scale application LLOs. Herein, we propose a...

Trust-based recommendation systems study how people form opinions via trusted friends, so as to predict unknown ratings based on the expressed by friends. Most of existing work only considers at current time slot. In real life, a user's opinion evolves over time, since he receives influence different sequentially. addition, usually targets single user time; there is need multiple for connected users. To reach these ends, we propose novel multiple-rating prediction scheme, FluidRating, which...

In recent years, significant research efforts have been spent towards building intelligent and user-friendly IoT systems to enable a new generation of applications capable performing complex sensing recognition tasks. many such applications, there are usually multiple different sensors monitoring the same object. Each these can be regarded as an information source provides us unique "view" observed Intuitively, if we combine complementary carried by sensors, will able improve performance....

Falls among the elderly comprise a major health problem. Daily activity monitoring and fall detection using wearable sensors provide an important healthcare system for or frail individuals. We investigated classification accuracy of daily data based on surface electromyography (sEMG) plantar pressure signals. sEMG signals were collected, their features extracted. Suitable selected combined posture transition, gait, Fisher class separability index. A feature-level fusion method, named as...