The effective physical data sharing has been facilitating the functionality of Industrial IoTs, which is believed to be one primary basis for Industry 4.0. These data, while providing pivotal information multiple components a production system, also bring in severe privacy issues both workers and manufacturers, thus aggravating challenges sharing. Current designs tend simplify behaviors participants better theoretical analysis, they cannot properly handle IIoTs where are more complicated...

Due to the prominent development of public transportation systems, taxi flows could nowadays work as a reasonable reference trend urban population. Being aware this knowledge will significantly benefit regular individuals, city planners, and companies themselves. However, mindlessly publish such contents severely threaten private information companies. Both their own market ratios sensitive passengers drivers be revealed. Consequently, we propose in paper novel framework for...

Smart IoT systems can integrate knowledge from the surrounding environment, and they are critical components of next-generation Internet. Such usually collect data various dimensions via numerous devices, collected linkable. This means that be combined to derive abundant valuable knowledge. However, may also accessed by malicious third parties reveal sensitive information. In this article, we investigate privacy issues linkable in smart systems, which have not been thoroughly studied...

The data collected in Internet of Thing (IoT) systems (IoT data) have stimulated dramatic extension to the boundary commercialized statistic analysis, owing pervasive availability low-cost wireless network access and off-the-shelf mobile devices. In such cases, many consumers post their queries for urban analysis system, like scales traffics, then contributors IoT networks upload contents, which can be evaluated by brokers responded consumers. However, huge volumes devices bring large data,...

Natural Language Processing (NLP) constitutes a pivotal domain of artificial intelligence focused on enabling computers to comprehend, process, and generate human language. Text classification, fundamental NLP task, aims categorize text into predefined classes. In recent years, deep learning has emerged as dominant force across various research domains become staple technology within NLP, particularly in classification tasks. Unlike numerical visual data, processing underscores the need for...

Background: Early prediction of the clinical outcome patients with sepsis is great significance and can guide treatment reduce mortality patients. However, it clinically difficult for clinicians. Methods: A total 2,224 were involved over a 3-year period (2016–2018) in intensive care unit (ICU) Peking Union Medical College Hospital. With all key medical data from first 6 h ICU, three machine learning models, logistic regression, random forest, XGBoost, used to predict mortality, severity...

Motivating the mobile users to participate in sensing services for efficient data generation and collection is one of most critical issues Mobile Crowdsensing Systems (MCSs). Auction based mechanisms are seen be promising effective solutions incentivize users. However, price not unique factor dominating participants' contribution MCSs. Participant's preference different tasks also a pivotal which should considered auction as assigning least favorite discourages them future tasks....

In recent years, rapeseed oil has received considerable attention in the agricultural sector, experiencing appreciable growth. However, weed-related challenges are hindering expansion of production. This paper outlines development an intelligent weed detection and laser weeding system—a non-chemical precision protection method Veronica didyma winter fields Yangtze River Basin. A total 234 images were obtained to compile a database for deep-learning model, YOLOv7 was used as model training....

Recent progress in Machine Unlearning (MU) has introduced solutions for the selective removal of private or sensitive information encoded within deep neural networks. Nonetheless, MU Multimodal Large Language Models (MLLMs) remains its nascent phase. Therefore, we propose to reformulate task multimodal era MLLMs, which aims erase only visual patterns associated with a given entity while preserving corresponding textual knowledge original parameters language model backbone. Furthermore,...

The pervasiveness of mobile applications stimulates more eager demand for Quality Experience (QoE) than Service (QoS), especially on the aspect link scheduling in wireless networks. In many applications, end users concern about transmission quality an individual task rather packet. A may correspond to a piece video, music, etc. And include packets. This paper proposes new network model aiming at improving users' experience that pushes problem layer. We first introduce QoE requirement can...

The detection of anomaly status plays a pivotal role in the maintenance public transportation and facilities smart cities. Owing to pervasively deployed sensing devices, one can collect apply multi-dimensional data detect analyze potential anomalies react promptly. Current efforts concentrate on offline manners fail fit situation cities, where efficient online solutions are expected. In this paper, novel framework is designed for over edge-assisted Internet-of-Things (IoTs). allows...

Graph data publication has been considered as an important step for analysis and mining. data, which provide knowledge on interactions among entities, can be locally generated held by distributed owners. These are usually sensitive private, because they may related to owners' personal activities hijacked adversaries conduct inference attacks. Current solutions either consider private graph centralized contents or disregard the overlapping of graphs in manners. Therefore, this work proposes a...

In social networks, several influential individuals can promote an idea or a product to numerous individuals. Thus, it is valuable solve the influence maximization (IM) problem, which asks for finding most set of in network. To estimate individuals, existing independent cascade (IC) model simulates diffusion only considering influences from direct in-neighbors nodes. This consideration does not hold real life. many cases, people are likely influenced by information depending on where comes...

With the boom in production of smartphones and easy access to networks, mobile crowd-sensing (MCS) is becoming a promising rapidly growing sensing paradigm for Internet Things (IoT). In MCS, workers can get rewarded by participating data collection while traveling their destination from some starting point. However, privacy leakage becomes serious unavoidable problem that hinders users' engagement. Taking task at specific location or even going through seemingly innocent locations may both...

Nowadays, more and online content providers are offering multiple types of data services. To provide users with a better service experience, Quality Experience (QoE) has been widely used in the delivery quality measurement network How to accurately measure QoE score for all services become meaningful but difficult problem. solve this problem, we proposed unified scoring framework that measures user experience almost The first uses machine learning model (random forest) classify services,...

Internet of Thing (IoT) systems have been treated as a novel platform for graph data acquisition. Contents like dynamic network topology, organization and control flows, interactions among monitored objects all contribute to the huge volumes generated in IoT. These are believed brought significant benefits both operation functionalities IoT systems, especially when combined with cutting-edge Artificial Intelligence techniques. However, these usually locally collected by contributors sensing...

Nowadays, wireless sensor networks (WSNs) are based on techniques more and oriented towards image, video sound processing, hence the recent need of multimedia (WMSNs). One important challenges for real-time surveillance system is end-to end delay QoS packet deliveries. Providing end-to-end difficult due to two reasons. As nodes may require multichip transmissions reach sink some be not successful. Multimedia data characterised by their large volume, have strict requirements in terms quality...

The easy and pervasive involvement of devices in Industrial Internet Things has greatly benefited the implementation adoption various smart services. One prominent prerequisite such trends is extensive continuous support sharing data resources among devices. However, previous efforts usually treat as one-time task devices, which are incapable when applied for distributed iterative training machine learning models. Therefore, this article proposes a novel framework Things. system consists...