Guest Editorial Special Section on AI-Driven Developments in 5G-Envisioned Industrial Automation: Big Data Perspective

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Synthesizing an Agent-Based Heterogeneous Population Model for Epidemic Surveillance

In this paper we propose a probabilistic approach to synthesize an agent-based heterogeneous population interaction model to study the spatio-temporal dynamics of an air-born epidemic, such as influenza, in a metropolitan area. The methodology is generic in nature and can generate a baseline population for cities for which detailed population summary tables are not available. The joint probabilities of population demographics are estimated using the International Public Use Microsimulation Data (IPUMS) sample data set. Agents, are assigned various activities based on several characteristics. The agent-based model for the city of Lahore, Pakistan is synthesized and a rule based disease spread model of influenza is simulated. The simulation results are visualized to analyze the spatio-temporal dynamics of the epidemic. The results show that the proposed model can be used by officials and medical experts to simulate an outbreak

Deep distributed learning-based POI recommendation under mobile edge networks

With the rapid development of edge intelligence in wireless communication networks, mobile edge networks (MEN) have been broadly discussed in academia. Supported by considerable geographical data acquisition ability of mobile Internet of Things (IoT), the MEN can also provide spatial locations-based social service to users. Therefore, suggesting reasonable points-of-interest (POIs) to users is essential to improve user experience of MEN. As the simple user-location data is usually sparse and not informative, existing literature attempted to extend feature space from two perspectives: contextual patterns and semantic patterns. However, previous approaches mainly focused on internal features of users, yet ignoring latent external features among them. To address this challenge, in this paper, a deep distributed learning-based POI recommendation (Deep-PR) method is proposed for situations of MEN. In particular, hidden feature components from both local and global subspaces are deeply abstracted via representative learning schemes. Besides, propagation operations are embedded to iteratively reoptimize expressions of the feature space. The successive effect of the above two aspects contributes a lot to more fine-grained feature spaces, so that recommendation accuracy can be ensured. Two types of experiments are also carried out on three real-world datasets to assess both efficiency and stability of the proposed Deep-PR. Compared with seven typical baselines with respect to four evaluation metrics, obtained results of the overall performance of the Deep-PR are excellent

Asynchronous FDRL-based low-latency computation offloading for integrated terrestrial and non-terrestrial power IoT

Integrated terrestrial and non-terrestrial power internet of things (IPIoT) has emerged as a paradigm shift to three-dimensional vertical communication networks for power systems in the 6G era. Computation offloading plays key roles in enabling real-time data processing and analysis for electric services. However, computation offloading in IPIoT still faces challenges of coupling between task offloading and computation resource allocation, resource heterogeneity and dynamics, and degraded model training caused by electromagnetic interference (EMI). In this article, we propose an asynchronous federated deep reinforcement learning (AFDRL)-based computation offloading framework for IPIoT, where models are uploaded asynchronously for federated averaging to relieve network congestion and improve global model training. Then, we propose Asynchronous fedeRated deep reinforcemenT learnIng-baSed low-laTency computation offloading algorithm (ARTIST) to realize low-latency computation offloading through joint optimization of task offloading and computation resource allocation. Particularly, ARTIST adopts EMI-aware federated set determination to remove aberrant local models from federated averaging and improve training accuracy. Next, a case study is developed to validate the excellent performance of ARTIST in reducing task offloading and total queuing delays

Hiding in Fresh Fruits and Vegetables: Opportunistic Pathogens May Cross Geographical Barriers

Different microbial groups of the microbiome of fresh produce can have diverse effects on human health. This study was aimed at identifying some microbial communities of fresh produce by analyzing 105 samples of imported fresh fruits and vegetables originated from different countries in the world including local samples (Oman) for aerobic plate count and the counts of Enterobacteriaceae, Enterococcus, and Staphylococcus aureus. The isolated bacteria were identified by molecular (PCR) and biochemical methods (VITEK 2). Enterobacteriaceae occurred in 60% of fruits and 91% of vegetables. Enterococcus was isolated from 20% of fruits and 42% of vegetables. E. coli and S. aureus were isolated from 22% and 7% of vegetables, respectively. Ninety-seven bacteria comprising 21 species were similarly identified by VITEK 2 and PCR to species level. E. coli, Klebsiella pneumoniae, Enterococcus casseliflavus, and Enterobacter cloacae were the most abundant species; many are known as opportunistic pathogens which may raise concern to improve the microbial quality of fresh produce. Phylogenetic trees showed no relationship between clustering of the isolates based on the 16S rRNA gene and the original countries of fresh produce. Intercountry passage of opportunistic pathogens in fresh produce cannot be ruled out, which requires better management

Blockchain-based secure and efficient secret image sharing with outsourcing computation in wireless networks

Secret Image Sharing (SIS) is the technology that shares any given secret image by generating and distributing n shadow images in the way that any subset of k shadow images can restore the secret image. However, in the existing SIS schemes, the shadow images will be easily tampered and corrupted during the communication, which will pose serious security issues. Recently, blockchain has emerged as a promising paradigm in the field of data communication and information security. To securely communicate and effectively protect the secret image data in wireless networks, we propose a Blockchain-based Secure and Efficient Secret Image Sharing (BC-SESIS) scheme with outsourcing computation in wireless networks. In the proposed BC-SESIS scheme, the shadow images are encrypted and stored in the blockchain to prevent them from being tampered and corrupted. The identity authentication-enabled smart contract is deployed to achieve the ( k, n ) threshold for secret image restoring. Furthermore, to reduce the computational burden of smart contract and users, an efficient outsourcing computation method is designed to outsource the restoring task, which is securely implemented by agent miners in the encryption domain. Theoretical analysis and extensive experiments demonstrate that the BC-SESIS scheme can achieve desirable communication security and high computational efficiency in the wireless networks

Response timing in the lunge and target change in elite versus medium-level fencers.

The aim of the present work is to examine the differences between two groups of fencers with different levels of competition, elite and medium level. The timing parameters of the response reaction have been compared together with the kinetic variables which determine the sequence of segmented participation used during the lunge with a change in target during movement. A total of 30 male sword fencers participated, 13 elite and 17 medium level. Two force platforms recorded the horizontal component of the force and the start of the movement. One system filmed the movement in 3D, recording the spatial positions of 11 markers, while another system projected a mobile target over a screen. For synchronisation, an electronic signal enabled all the systems to be started simultaneously. Among the timing parameters of the reaction response, the choice reaction time (CRT) to the target change during the lunge was measured. The results revealed differences between the groups regarding the flight time, horizontal velocity at the end of the acceleration phase, and the length of the lunge, these being higher for the elite group, as well as other variables related to the temporal sequence of movement. No significant differences have been found in the simple reaction time or in CRT. According to the literature, the CRT appears to improve with sports practice, although this factor did not differentiate the elite from medium-level fencers. The coordination of fencing movements, that is, the right technique, constitutes a factor that differentiates elite fencers from medium-level ones

CO2 gasification of chars prepared from wood and forest residue

The CO2 gasification of chars prepared from Norway spruce and its forest residue was investigated in a thermogravimetric analyzer (TGA) at slow heating rates. The volatile content of the samples was negligible; hence the gasification reaction step could be studied alone, without the disturbance of the devolatilization reactions. Six TGA experiments were carried out for each sample with three different temperature programs in 60 and 100% CO2. Linear, modulated, and constant-reaction rate (CRR) temperature programs were employed to increase the information content available for the modeling. The temperatures at half of the mass loss were lower in the CRR experiments than in the other experiments by around 120 degrees C. A relatively simple, well-known reaction kinetic equation described the experiments. The dependence on the reacted fraction as well as the dependence on the CO2, concentration were described by power functions (n-order reactions). The evaluations were also carried out by assuming a function of the reacted fraction that can mimic the various random pore/random capillary models. These attempts, however, did not result in an improved fit quality. Nearly identical activation energy values were obtained for the chars made from wood and forest residues (221 and 218 kJ/mol, respectively). Nevertheless, the forest residue char was more reactive; the temperatures at half of the mass loss showed 20-34 degrees C differences between the two chars at 10 degrees C/min heating rates. The assumption of a common activation energy, E, and a common reaction order, v, on the CO2, concentration for the two chars had only a negligible effect on the fit quality