Malware Identification Method in Industrial Control Systems Based on Opcode2vec and CVAE-GAN.

Industrial Control Systems (ICSs) have faced a significant increase in malware threats since their integration with the Internet. However, existing machine learning-based malware identification methods are not specifically optimized for ICS environments, resulting in suboptimal identification performance. In this work, we propose an innovative method explicitly tailored for ICSs to enhance the performance of malware classifiers within these systems.

Multi-Channel Multi-Scale Convolution Attention Variational Autoencoder (MCA-VAE): An Interpretable Anomaly Detection Algorithm Based on Variational Autoencoder.

With the rapid development of industry, the risks factories face are increasing. Therefore, the anomaly detection algorithms deployed in factories need to have high accuracy, and they need to be able to promptly discover and locate the specific equipment causing the anomaly to restore the regular operation of the abnormal equipment. However, the neural network models currently deployed in factories cannot effectively capture both temporal features within dimensions and relationship features between dimensions; some algorithms that consider both types of features lack interpretability.

Kidney medicine meets computer vision: a bibliometric analysis.

Background And Objective: Rapid advances in computer vision (CV) have the potential to facilitate the examination, diagnosis, and treatment of diseases of the kidney. The bibliometric study aims to explore the research landscape and evolving research focus of the application of CV in kidney medicine research.

Methods: The Web of Science Core Collection was utilized to identify publications related to the research or applications of CV technology in the field of kidney medicine from January 1, 1900, to December 31, 2022.

A Lightweight Unsupervised Intrusion Detection Model Based on Variational Auto-Encoder.

With the gradual integration of internet technology and the industrial control field, industrial control systems (ICSs) have begun to access public networks on a large scale. Attackers use these public network interfaces to launch frequent invasions of industrial control systems, thus resulting in equipment failure and downtime, production data leakage, and other serious harm. To ensure security, ICSs urgently need a mature intrusion detection mechanism.

An Access Control System Based on Blockchain with Zero-Knowledge Rollups in High-Traffic IoT Environments.

The access control (AC) system in an IoT (Internet of Things) context ensures that only authorized entities have access to specific devices and that the authorization procedure is based on pre-established rules. Recently, blockchain-based AC systems have gained attention within research as a potential solution to the single point of failure issue that centralized architectures may bring. Moreover, zero-knowledge proof (ZKP) technology is included in blockchain-based AC systems to address the issue of sensitive data leaking.

Intelligent Reflecting Surface-Assisted Physical Layer Key Generation with Deep Learning in MIMO Systems.

Physical layer secret key generation (PLKG) is a promising technology for establishing effective secret keys. Current works for PLKG mostly study key generation schemes in ideal communication environments with little or even no signal interference. In terms of this issue, exploiting the reconfigurable intelligent reflecting surface (IRS) to assist PLKG has caused an increasing interest.

Semi-Supervised Instance-Segmentation Model for Feature Transfer Based on Category Attention.

In the task of image instance segmentation, semi-supervised instance segmentation algorithms have received constant research attention over recent years. Among these algorithms, algorithms based on transfer learning are better than algorithms based on pseudo-label generation in terms of segmentation performance, but they can not make full use of the relevant characteristics of source tasks. To improve the accuracy of these algorithms, this work proposes a semi-supervised instance segmentation model AFT-Mask (attention-based feature transfer Mask R-CNN) based on category attention.

Potential for volatile fatty acid production via anaerobically-fermenting rice straw pretreated with silage effluent and phenyllactic acid.

To resolve environmental problems associated with rice straw and silage effluent disposal, silage effluent pretreating rice straw for the anaerobic production of volatile fatty acids (VFAs) was investigated. To prevent the lactic acid bacteria in silage effluent from inhibiting anaerobic fermentation, four phenyllactic acid (PLA) levels were set (0, 0.1, 0.

High-Speed Extraction of Regions of Interest in Optical Camera Communication Enabled by Grid Virtual Division.

Optical camera communication (OCC), enabled by light-emitting diodes (LEDs) and embedded cameras on smartphones, has drawn considerable attention thanks to the pervasive adoption of LED lighting and mobile devices. However, most existing studies do not consider the performance bottleneck of Region of Interest (RoI) extraction during decoding, making it challenging to improve communication capacity further. To this end, we propose a fast grid virtual division scheme based on pixel grayscale values, which extracts RoI quickly without sacrificing computational complexity, thereby reducing the decoding delay and improving the communication capacity of OCC.

High-Accuracy Height-Independent 3D VLP Based on Received Signal Strength Ratio.

Visible light positioning (VLP) has attracted intensive attention from both academic and industrial communities thanks to its high accuracy, immunity to electromagnetic interference, and low deployment cost. In general, the receiver in a VLP system determines its own position by exploring the received signal strength (RSS) from the transmitter according to a pre-built RSS attenuation model. In such model-based methods, the LED's emission power and the receiver's height are usually required known and constant parameters to obtain reasonable positioning accuracy.

Antioxidant Activities of Hot Water Extracts from Mycelial Biomass of Different Combinations of Medicinal Agaricomycetes Mushrooms.

This study aimed to determine the free radical scavenging and antioxidant potential of hot water extracts prepared from different combinations and ratios of submerged cultivated mycelial biomass of medicinal mushrooms. Total phenolic compounds, flavonoid content, and antioxidant activity were evaluated for combined crude hot water extracts from medicinal higher Basidiomycetes mushrooms belonging to ten genera. The results demonstrate that almost all tested combinations were good sources of phenolic compounds and flavonoids, ranging between 16.

Effects of LAB Inoculants on the Fermentation Quality, Chemical Composition, and Bacterial Community of Oat Silage on the Qinghai-Tibetan Plateau.

Lactic acid bacteria (LAB) have been proposed for the control of undesirable fermentation and, subsequently, aerobic deterioration due to their ability to produce antimicrobial metabolites in silage mass. To investigate the effect of specific LAB on the silage fermentation characteristics and bacterial community composition of oat in cold regions, silages were treated without (control) or with three LAB strains (LB, Lentilactobacillus buchneri; nLP, low temperature tolerant Lactiplantibacillus plantarum; pLP, phenyllactic acid-producing Lactiplantibacillus plantarum), and then stored at ambient temperature (−2.63 ± 5.

DeepEdge: A Novel Appliance Identification Edge Platform for Data Gathering, Capturing and Labeling.

With the development of the Internet of Things for smart grid, the requirement for appliance monitoring has become an important topic. The first and most important step in appliance monitoring is to identify the type of appliance. Most of the existing appliance identification platforms are cloud based, thus they consume large computing resources and memory.

Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation.

Background: It is hard to distinguish cerebral aneurysms from overlapping vessels in 2D digital subtraction angiography (DSA) images due to these images' lack of spatial information.

Objective: The aims of this study were to (1) construct a deep learning diagnostic system to improve the ability to detect posterior communicating artery aneurysms on 2D DSA images and (2) validate the efficiency of the deep learning diagnostic system in 2D DSA aneurysm detection.

Methods: We proposed a 2-stage detection system.

Effects of Phenyllactic Acid, Lactic Acid Bacteria, and Their Mixture on Fermentation Characteristics and Microbial Community Composition of Timothy Silage.

This study investigated the effects of phenyllactic acid (PL), lactic acid bacteria (LAB), and their mixture on fermentation characteristics and microbial community composition of timothy silage. Timothy silages were treated without (CK) or with PL [10 mg/kg fresh matter (FM) basis], LAB inoculant (IN; a mixture of and , 10 cfu/g FM), and their mixture (PI) and stored at ambient temperature (5°C∼15°C) in a dark room for 60 days. Compared with CK, all treated silages showed lower ( < 0.

Effects of Additives on Silage Fermentation Characteristic and In Vitro Digestibility of Perennial Oat at Different Maturity Stages on the Qinghai Tibetan.

To effectively use local grass resources to cover the winter feed shortage on the Qinghai-Tibetan Plateau, the silage fermentation and in vitro digestibility of perennial oat ( Henr.) were investigated. Perennial oat was harvested at the heading/flowering stage, wilted under sunny conditions, chopped, vacuumed in small bag silos, and stored at ambient temperatures (5-15 °C) for 60 days.

Improved optical camera communication systems using a freeform lens.

Optical camera communication (OCC) systems, which utilize image sensors embedded in commercial-off-the-shelf devices to detect time and spatial variations in light intensity for enabling data communications, have stirred up researchers' interest. Compared to a direct OCC system whose maximum data rate is strongly determined by the LED source size, a reflected OCC system can break that limitation since the camera captures the light rays reflecting off an observation plane (e.g.

Inclusion of abandoned rhubarb stalk enhanced anaerobic fermentation of alfalfa on the Qinghai Tibetan Plateau.

To investigate the effects of lactic acid bacteria inoculant (LI) and abandoned rhubarb stalk (RS) on the anaerobic fermentation and bacterial community of alfalfa on the Qinghai Tibetan Plateau, the alfalfa was harvested and ensiled without (control) or with LI and RS at ambient temperature (5 ∼ 15℃) for 90 days. Addition of RS at ensiling increased (P < 0.05) lactate, acetate and propionate contents, and decreased (P < 0.

Study on the bacterial community structure and fermentation characteristics of fresh and ensiled paper mulberry.

Two experiments were conducted to investigate the bacterial community of fresh and ensiled paper mulberry prepared with or without lactic acid bacteria (LAB) inoculants in South China. In Experiment 1, the bacterial community, chemical composition, and fermentation products of paper mulberry were analyzed. The results showed that fresh paper mulberry had high crude protein content, buffering capacity value, and amounts of uncultured bacteria.

Milk Production and Quality of Lactating Yak Fed Oat Silage Prepared with a Low-Temperature-Tolerant Lactic Acid Bacteria Inoculant.

This study aimed to investigate the effect of oat silage treated with a low-temperature-tolerant lactic acid bacteria (LAB) inoculant on milk yield and the quality of lactating yaks. Oat silages were prepared in big round bales, treated without (control) or with a low-temperature-tolerant LAB inoculant (a mixture of BP18, HS1 and LP22; the application rate of 10 cfu/g on a fresh matter basis). Eighteen lactating yaks were divided into nine pairs with a similar milk yield.

Chemical Composition and Antioxidant Properties of Different Combinations of Submerged Cultured Mycelia of Medicinal Mushrooms.

This research describes the investigation of submerged cultivated mycelial biomass and hot water extracts prepared from different combinations and ratios of medicinal mushroom (MM) dry powders, comprising various biologically active compounds/secondary metabolites. In particular, it was evaluated the proximate composition (moisture, ash, crude protein, fat, total carbohydrates, and total energy), γ-aminobutyric acid (GABA) and ergothioneine (ERG), amino acid content of mycelia of 16 higher Basidiomycetes MM species. The results obtained demonstrate that almost all tested combinations were found to be good sources of polysaccharides, with content varying in the ranges of 4.

Effects of Delayed Harvest and Additives on Fermentation Quality and Bacterial Community of Corn Stalk Silage.

This study aimed to investigate the effects of delayed harvest and additives on the fermentation quality and bacterial community of corn stalk silage in South China. The corn stalks after ear harvest at the 0 day (D0), 7 days (D7), and 15 days (D15) were used to produce small-bale silages. The silages at each harvest time were treated without (control, CK) or with (LP) and sodium benzoate (BF).

Enhancing the performance of optical camera communication via accumulative sampling.

Deemed as a practical approach to realize Visible Light Communication on commercial-off-the-shelf devices, the Optical Camera Communication (OCC) is attracting increasing attention, thanks to its readiness to be built purely upon ubiquitous LED illuminating infrastructure and handy smartphones. However, limited by the low sampling ability of the built-in camera on a smartphone, the performance of existing OCC systems is still far away from the requirements of practical applications. To this end, we further investigate the reception ability of the smartphone's camera and propose an accumulative sampling scheme to improve the performance of the OCC system.

HAGP: A Heuristic Algorithm Based on Greedy Policy for Task Offloading with Reliability of MDs in MEC of the Industrial Internet.

In the Industrial Internet, computing- and power-limited mobile devices (MDs) in the production process can hardly support the computation-intensive or time-sensitive applications. As a new computing paradigm, mobile edge computing (MEC) can almost meet the requirements of latency and calculation by handling tasks approximately close to MDs. However, the limited battery capacity of MDs causes unreliable task offloading in MEC, which will increase the system overhead and reduce the economic efficiency of manufacturing in actual production.

Optical-spatial-summing-based NOMA with fine-grained power allocation for VLC-enabled IoT applications.

In this Letter, we propose and demonstrate a practical optical-spatial-summing-based non-orthogonal multiple access (OSS-NOMA) technique for visible light communication (VLC) systems. This technique is innovative in adopting OSS in that the transmitter of OSS-NOMA VLC can be built upon commercial illuminating light emitting diodes (LEDs), free of LEDs' harmful nonlinearity. Unlike conventional NOMA VLC using analog components such as digital-to-analog converters and bias-T in the transmitter side, OSS-NOMA exploits only digital control signals to drive a LED array in forming optical power superposition for NOMA signals.