Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet.Traditional signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging attacks.Therefore,there is the need for an IDS which can learn from data and detect new threats.Ensemble Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking technique.In this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta learner.The proposed DSNN model was trained and evaluated with the next-generation dataset,TON_IoT.Several pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE technique.Accuracy,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble model.Our experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML models.In addition,the model proposed for IDS has been compared with similar models.The proposed DSNN achieved better performance metrics than the other models.The proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

A new prediction NN framework design for individual stock based on the industry environment

There is a research gap in accurately predicting an individual stock’s finances from industry environment factors.Therefore,to predict trading strategies for a target stock’s closing price,this study constructed a prediction module and an environment module for a hybrid variational mode decomposition and stacked gated recurrent unit(VMD-StackedGRU)model,with individual stock information input into the prediction module and industry information input into the environment module.The results from the U.S.banking industry generalization tests proved that the proposed model could significantly improve prediction performances and that the environment module did not play an important role and was not equal to the prediction module.The hybrid neural network framework was a new application for financial price predictions based on an industry environment.Profitable trading strategies and accurate predictions can be valuable in hedging against market volatility risk and in assuring significant returns for investors and investment institutions.

Advancements and Prospects of Waterborne Coatings in the Coating Industry: A Comprehensive Analysis

This paper presents an overview of resins used in coatings,categorizing them into commonly used cross-linking agents such as methyl etherified melamine formaldehyde resin,and matrix resins including acrylic resin,polyurethane,epoxy resin,and alkyd resin.It further examines the demand and market size trends of these matrix resins in China over the recent seven years(2016-2022).The analysis reveals that in terms of both demand and market size,polyurethane resin ranks highest,followed by alkyd resin,acrylic resin,and epoxy resin.Additionally,the paper provides a comprehensive analysis of the development status,advantages,and macro-environment of the waterborne coatings industry.The competitive landscape within the industry is also discussed.The application of water-based coatings has shown significant potential to reduce the emission of pollutants such as volatile organic compounds(VOCs).Moreover,water-based coatings exhibit excellent performance characteristics.Market data from 2011 to the present indicates a consistent growth trend in the market size of waterborne coatings.However,intense competition among coating enterprises has led to a high level of product homogenization.In response to increasingly stringent national environmental protection policies,companies are accelerating the development and adoption of water-based coatings and other environmentally friendly products.This strategic shift towards waterborne coatings is expected to drive significant advancements and growth in the industry.

Analysis of inhibition of concrete steel-rebar corrosion by Na_2Cr_2O_7 concentrations:Implications for conflicting reports on inhibitor effectiveness

Corrosion test data were measured using non-destructive electrochemical techniques and analysed for studying inhibition effectiveness by different concentrations of NazCr207 on the corrosion of concrete steel-rehar in NaC1 and in H2SO4 media. For these, specifications of ASTM G16-95 R04 were combined with the normal and the Gumbel probability density functions as model analytical methods for addressing issues of conflicting reports of inhibitor effectiveness that had generated concerns. Results show that reinforced concrete samples admixed with concentrations having 4 g （0.012 7 tool）, 8 g （0.025 4 mol） and 6 g （0.019 l tool） NaaCr207 exhibited, in that order, high inhibition effectiveness, with respective efficiency, r/, of （90.46±1.30）%, （88.41＋2.24）% and （84.87±4.74）%, in the NaC1 medium. These exhibit good agreements within replicates and statistical methods for the samples. Also, optimal inhibition effectiveness model in the H2SO4 medium was exhibited by 8 g （0.025 4 mol） Na2Cr207 concentration having r/=（78.44±1.10）%. These bear implications for addressing conflicting test data in the study of effective inhibitors for mitigating steel-rebar corrosion in aggressive environments.

Costs and Benefits of China＇s Environmental Regulation

This paper examines the current costs, benefits and intensity of China＇s industrial environment regulation, as well as the path of regulatory enhancement. Regulatory intensity has been on the rise since 1997. The intensity was only 43 in 1997 and then reached 68 by 2007. This paper for the first time compares the treatment costs at the front and rear ends of pollution chain, employs the concept of regulatory benefit multiplier, and calculates the benefit multipliers for different pollutants. Results indicate that enhanced environmental protection since 1997 makes social and economic sense, particularly for the front end treatment of various pollutants since 2004, which have considerable economic benefits. After comparing the benefit multipliers, we have prioritized the pollutants for regulatory consideration： environmental regulation shouM be made tougher for waste water first, and then dust and fumes, followed by SO2 and lastly CO2. This will help to achieve the best environmental outcomes while incurring no additional economic costs.

Smart contract applications in the built environment: How prepared are Nigerian construction stakeholders?

Studies have demonstrated that advanced technology,such as smart contract applications,can enhance both pre-and post-contract administration within the built environment sector.Smart contract technology,exemplifying blockchain technologies,has the potential to improve transparency,trust,and the security of data transactions within this sector.However,there is a dearth of academic literature concerning smart contract applications within the construction industries of developing countries,with a specific focus on Nigeria.Consequently,this study seeks to explore the relevance of smart contract technology and address the challenges impeding its adoption,offering strategies to mitigate the obstacles faced by smart contract applications.To investigate the stakeholders,this research conducted 14 virtual interview sessions to achieve data saturation.The interviewees encompassed project management practitioners,senior management personnel from construction companies,experts in construction dispute resolution,professionals in construction software,and representatives from government construction agencies.The data obtained from these interviews underwent thorough analysis employing a thematic approach.The study duly recognizes the significance of smart contract applications within the sector.Among the 12 identified barriers,issues such as identity theft and data leakage,communication and synchronization challenges,high computational expenses,lack of driving impetus,excessive electricity consumption,intricate implementation processes,absence of a universally applicable legal framework,and the lack of a localized legal framework were recurrent impediments affecting the adoption of smart contract applications within the sector.The study also delves into comprehensive measures to mitigate these barriers.In conclusion,this study critically evaluates the relevance of smart contract applications within the built environment,with a specific focus on promoting their usage.It may serve as a pioneering effort,especially within the context of Nigeria.

Decreasing inhaled contaminant dose of a factory worker through a hybrid Emergency Ventilation System:Performance evaluation in worst-case scenario

Air pollution is detrimental to human health,causing several human illnesses.The industrial microenvironment generates high levels of indoor airborne pollutants,becoming a pervasive issue for workers.It is essential to im-prove the indoor air quality in this workplace by applying enhanced ventilation systems to minimize inhalation risk.Displacement ventilation is used in industrial buildings because of its stratified air distribution and low cost.However,in case of accidental pollutant release,an enhancement is needed to minimize inhalation exposure.This study proposes a hybrid emergency ventilation system using localized push-pull ventilation to improve the installed displacement ventilation system of a representative workshop.Computational fluid dynamics was ap-plied to calculate steady-state indoor air flow and volume-averaged pollutant concentration.System performance was evaluated in terms of source position;a computer simulated person was integrated to the building to confirm effectiveness against personal inhalation.Results showed marked improvement in performance when push-pull technique was used:room-averaged concentration diminished up to 91%while ventilation rate only increased 4%.Inhaled pollutant mitigation was achieved but performance dependence against leakage source and personal position was confirmed.