Infrastructure Applications Research Articles

A Softwarized Intrusion Detection System for IoT-Enabled Smart Healthcare System

The Internet of Things-enabled Smart Healthcare System (IoT-SHS) is a networked infrastructure of intelligent wearables, software applications, health systems, and services that continuously monitors and transmits patient-sensitive data using an open wireless channel. The conventional security mechanisms are unsuitable for detecting attacks in the dynamic IoT-SHS context due to resource limitations and heterogeneity in low-cost healthcare devices. Deep Learning (DL) solutions for Intrusion Detection System (IDS) and softwarization of the network has the potential to achieve secure network services in the IoT-SHS environment. Motivated by the aforementioned discussion, we propose an intelligent softwarized IDS for protecting the critical infrastructure of the IoT-SHS ecosystem. Specifically, the DL-based IDS is designed using a hybrid cuda Long Short-Term Memory Deep Neural Network (cuLSTM-DNN) algorithm to assist network administrators in efficient decision-making for the generated intrusions. To further bolster the system’s resilience, we suggest a deployment architecture for the proposed CUDA-powered IDS using OpenStack Tacker in a real SDN environment, ensuring that virtual machines can directly utilize the host’s NVIDIA GPU, thereby streamlining and enhancing the network’s operational efficiency. The experimental results using the CICDDoS2019 dataset confirm the effectiveness of the proposed framework over some baseline and recent state-of-the-art techniques.

On the benefits of optical disaggregated datacentre infrastructures for machine learning applications

On the benefits of optical disaggregated datacentre infrastructures for machine learning applications

High-frequency dynamic distributed fiber optic strain sensing for civil infrastructure applications

High-frequency dynamic distributed fiber optic strain sensing for civil infrastructure applications

The Impact of the Digital Economy on the High-Quality Development of Xi’an’s Manufacturing Industry

Abstract This paper first explains the research on the digital economy to optimize the resource allocation of the Xi’an high-tech manufacturing industry. Secondly, the evaluation index system for the digital economy and Xi’an manufacturing industry is constructed, and the weight of secondary indexes is determined using the entropy weight method. Then, a mediating effect model is constructed to determine explanatory variables, core explanatory variables, mediating variables and control variables according to the purpose of the study, and the mediating effect and impulse response are analyzed. The results show that, in terms of mediating effect, the level of digital economy development significantly positively impacts transaction size, infrastructure, and digital applications. In terms of the impulse response, when the digital economy variables generate a standard deviation shock, the response value of Xi’an’s high-quality manufacturing development is zero in the current period, reaches the maximum response value in the third period, and this positive effect gradually decreases in the fourth period and beyond but always maintains a positive development trend.

Physics-guided generative adversarial network for probabilistic structural system identification

Structural system identification (ID) is an important tool for many structural and infrastructure applications, such as structural health monitoring and structural model updating. A novel physics-guided generative adversarial network (PG-GAN) is proposed in this study for probabilistic structural parameter ID. The PG-GAN leverages the powerful distribution learning ability of GANs while also enabling physical awareness by incorporating additional generators for physical parameters and developing a physics-based loss function that links the data generator with the parameter generators through existing physics knowledge to guide the training of generative models. Two experiments are performed to validate the effectiveness of the PG-GAN for structural parameter ID and demonstrate its application in structural damage detection. The PG-GAN is shown to successfully capture the uncertainty inherent in structural parameter estimation and accurately locate and quantify structural damages in terms of probabilistic distributions of the damage extent. The main contributions of this study are threefold: (1) compared with traditional methods for structural parameter ID, the proposed PG-GAN provides an intelligent framework for probabilistic identification of structural parameters without the need for any assumption on the data distribution and does not require an initial guess of parameters; (2) unlike traditional data-driven GANs, the proposed PG-GAN provides a linkage between GAN and physics knowledge to enables physical awareness in generative model training; and (3) the proposed PG-GAN can serve as an intelligent diagnostic system to better inform the decision-making on structural health management as it can quantify the uncertainty in the structural damage extent.

Dynamic and Energy Efficient Cache Scheduling Framework for IoMT over ICN

The Internet of Medical Things (IoMT) is the network of medical devices, hardware infrastructure, and software applications used to connect the healthcare information technology. Massive traffic growth and user expectations cause challenges in the current exhausting models of IoMT data. To reduce the IoMT traffic, Information Centric Network (ICN) is a suitable technique. ICN uses persistent naming multicast communication that reduces the response time. ICN in IoMT provides a promising feature to reduce the overhead due to the distribution of commonly accessed contents. Some parameters such as energy consumption, communication cost, etc., influence the performance of sensors in the IoMT network. Excessive and unbalanced energy consumption degrades the network performance and lifetime. This article presents a framework called Dynamic Cache Scheme (DCS) that implements energy-efficient cache scheduling in IoMT over ICN to reduce network traffic. The proposed framework establishes a balance between the multi-hop traffic and data item freshness. The technique improves the freshness of data; thus, updated data are provided to the end-users via the effective utilization of caching in IoMT. The proposed framework is tested on important parameters, i.e., cache-hit-ratio, stretch, and content retrieval latency. The results obtained are compared with the state-of-the-art models. Results’ analysis shows that the proposed framework outperforms the compared models in terms of cache-hit-ratio, stretch, and content retrieval latency by 59.42%, 32.66%, and 18.8%, respectively. In the future, it is intended to explore the applicability of DCS in more scenarios and optimize further.

Dynamic Properties of Cellular Glass Aggregate as a Lightweight Material

Cellular glass aggregates made from recycled glass are increasingly used in civil engineering and infrastructure applications. However, as this material is relatively new and innovative, it's necessary to obtain a complete mechanical characterization for its usage in the civil engineering field. In this article, the dynamic properties of cellular glass aggregate are investigated with the aid of a large‐scale triaxial apparatus (300 mm diameter and 600 mm height) under cyclic loading. The experimental procedure for building the samples is presented with a brief description of the test setup. A series of cyclic triaxial tests are performed to characterize and evaluate the dynamic properties of the material, which are of interest in the seismic approach (Young's modulus and damping ratio).

Experimental Assessment of the Mechanical Performance of Graphene Nanoplatelets Coated Polymers

This study presents the effect of spray‐coated graphene nanoplatelets on the mechanical response of various polymers to cyclic loadings. The substrates material (three polymers) and the coating (various numbers of coating layers) are assessed. The experimental results suggest that the compressive stiffness, compressive modulus, damping, and energy dissipation of the samples coated with graphene nanoplatelets improve with respect to the uncoated samples. The outcomes of this experimental research highlight the feasibility of utilizing films of graphene nanoplatelets to improve the mechanical properties of polymers for vibration isolation, foreseeing application in various environments, for instance, in buildings and infrastructures (bridges, railways) for seismic and acoustic isolation.

Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality research in Africa

Abstract. The Multi-Scale Infrastructure for Chemistry and Aerosols Version 0 (MUSICAv0) is a new community modeling infrastructure that enables the study of atmospheric composition and chemistry across all relevant scales. We develop a MUSICAv0 grid with Africa refinement (∼ 28 km × 28 km over Africa). We evaluate the MUSICAv0 simulation for 2017 with in situ observations and compare the model results to satellite products over Africa. A simulation from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), a regional model that is widely used in Africa studies, is also included in the analyses as a reference. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Both models underestimate carbon monoxide (CO) compared to in situ observations and satellite CO column retrievals from the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument. MUSICAv0 tends to overestimate ozone (O3), likely due to overestimated stratosphere-to-troposphere flux of ozone. Both models significantly underestimate fine particulate matter (PM2.5) at two surface sites in East Africa. The MUSICAv0 simulation agrees better with aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and tropospheric nitrogen dioxide (NO2) column retrievals from the Ozone Monitoring Instrument (OMI) than WRF-Chem. MUSICAv0 has a consistently lower tropospheric formaldehyde (HCHO) column than OMI retrievals. Based on model–satellite discrepancies between MUSICAv0 and WRF-Chem and MOPITT CO, MODIS AOD, and OMI tropospheric NO2, we find that future field campaign(s) and more in situ observations in the East African region (5∘ S–5∘ N, 30–45∘ E) could substantially improve the predictive skill of atmospheric chemistry model(s). This suggested focus region exhibits the largest model–in situ observation discrepancies, as well as targets for high population density, land cover variability, and anthropogenic pollution sources.

An integrated CMOS–silicon photonics transmitter with a 112 gigabaud transmission and picojoule per bit energy efficiency

The widening application of advanced digital infrastructure requires the development of communications technologies with increased data transmission rates. However, ensuring that this can be achieved in an energy-efficient way is challenging. Here we report an integrated complementary metal–oxide–semiconductor/silicon-photonics-based transmitter in which a switching current is applied to the passive-equalization-network-guided silicon Mach–Zehnder modulator, rather than driving a standard Mach–Zehnder modulator with a traditional voltage swing. This approach allows the total electrical energy to be selectively distributed to different frequency components by choosing an appropriate inductance and near-end termination impedance values. With the approach, we achieve 112 gigabaud—112 gigabits per second on–off keying and 224 gigabit per second pulse-amplitude modulation with four levels—transmission with energy efficiencies below picojoules per bit, and without the need for signal-shaping functions in the data source. We also investigate the bit error rate for different electrical and optical power conditions at 100 gigabaud, including the electrical power consumption of the driver amplifier.

Computational analysis of time-fractional models in energy infrastructure applications

In this paper, we propose an effective numerical method to solve the one- and two-dimensional time-fractional convection-diffusion equations based on the Caputo derivative. The presented approach employs a hybrid method that combines Lucas and Fibonacci polynomials with the Caputo derivative definition. The main objective is to transform the problem into a time-discrete form utilizing the Caputo derivative technique and then approximate the function's derivative using Fibonacci polynomials. To evaluate the efficiency and accuracy of the proposed technique, we apply it to one- and two-dimensional problems and compare the results with the exact as well as with existing methods in recent literature. The comparison demonstrates that the proposed approach is highly efficient, accurate and ease to implement.

Microstructural and polymer film interaction mechanisms: Insights of GO-reinforced polymer-modified cement composites

The effects of graphene oxide (GO) on cement hydration phases and polymer film formation in GO-reinforced polymer-modified cement (GOPMC) composites were investigated by analysing interactions of film chemical structure and cement hydration kinetics towards enhanced engineering performance. Chemical characterisation by FTIR and XRD analyses revealed that alterations of the cement matrix's chemical structure, such as slow Ethylene vinyl acetate (EVA) hydrolysis, increased calcium-silicate-hydrate (C–S–H) and portlandite Ca(OH)2, were more pronounced in GOPMC composites, indicating direct and robust involvement of GO during early-age hydration kinetics. Isothermal calorimetry displayed an increased heat flow of ∼7.2 % for GOPMC compared with the reference PMC composite. Notably, air voids of GOPMC composite revealed polymer film sheets intermingled with cement hydration products to promote elastic interconnections and microstructural uniformity. Accordingly, the GOPMC composite displayed ∼16 % higher tensile strength at 28 days versus the PMC composite, primarily attributable to GO nucleation, due to its seeding effect on cement hydration kinetics thereby inducing marginally slower EVA hydrolysis, increased C–S–H nucleation sites, and smaller-sized CH crystals while mechanically reinforcing polymer films. More significantly, GO reinforced the microstructure of the GOPMC composites with no apparent chemical interference of crucial film-forming properties. This research provides a fundamental understanding of this novel material's characteristic properties and framework of engineering performance optimization for future infrastructure applications.

Can infrastructure help ‘left behind’ places ‘catch up?’ Theorizing the role of built infrastructure in regional development

Abstract The application of infrastructure as a regional development tool in resource peripheries has received little direct inquiry in both policy and scholarly debates. This article synthesizes theoretical and empirical directions across economic geography, regional studies and critical infrastructure studies to form a research agenda for investigating the role of built infrastructure in the development of ‘left behind’ peripheral regions in the USA. We argue that infrastructural systems’ material, social, fiscal and political dimensions potentially deepen rather than mitigate structural ‘left behind-ness’. Future research and policy design must account for such dynamics if infrastructure interventions are to prove generative for regional development.

Six Sigma methodology based on the PMBOK guide in the release management process in software developer enterprise

The objective of this work was to analyze the application of the Six Sigma methodology based on the PMBOK guide in the release management process in a software developer company. With the increasing complexity of the release management process in the software developer company, we saw the need to analyze the mapped process, and identify points of failure or improvement that could be fixed/improved. For the implementation of the Six Sigma methodology, it was defined that the PMBOK would be used as the guiding basis for the definition of which project management processes would be used. The methodology was used as a reference for quality methods and tools for application in the process carried out by the application infrastructure area. A qualitative approach was applied as a research methodology, with bibliographic research for the theoretical foundation and documentary research, making annotations about the observed process, as well as its results. By defining the project management processes, the project was executed in such a way as to provide the methodology to be applied assertively on the process, thus identifying the points of failure and improvement to be addressed, thus achieving the expected goal.

Design of the Si-PDKT Application for the Memorandum-in Validation process when inspection of ship documents

Arriving Vessel Document Inspection System (Si-PDKT) is a web-based application that is implemented by utilizing information technology as a supporting tool for optimizing memorandum services in the process of inspecting arriving ship documents at the Class II Cirebon Harbormaster and Port Authority Office. The purpose of developing the Si-PDKT application that will be implemented in KSOP Class II Cirebon Section Legal Status and Ship Certification is more efficient management of ship data, digitally stored ship documents, avoiding document loss, facilitating the management of ship transactions, conducting validation and verification quickly. The method used is development research. In development research, a system design is carried out which is carried out in several stages based on an analysis of the needs of the system to be used. The stages are divided into three main stages, namely infrastructure requirements, system creation, and application usage. The research results show that the Si-PDKT that was built can be accessed at the address https://sipdkt.ksopcirebon.id. The stages of using Si-PDKT are (1) creating an account via email; (2) the user uploading the company decree; (3) After being verified, the user changes the profile; (4) on the company data menu, the user can choose the company where it works; (5) on the ship data menu, the user can add ships; (6) on the menu data memo-in contains the ship's data along with the documents and the memo-in (7.) If it has been filled in, a memo-in history will appear. At the end of verification from the operator, a verification status will appear where there is a color change following the verification status, and if you click on verification, the verification history will appear. If it has been verified as final, then the Memo In document can be downloaded.

Utilizing Industrial By-Products for Sustainable Three-Dimensional-Printed Infrastructure Applications: A Comprehensive Review

Industrial secondary products (e.g., fly ash, blast furnace slag, and silica fume) have found extensive application as alternative construction materials in conventional manufacturing methods to reduce carbon emissions due to cement usage and solve the waste management problem. To date, additive manufacturing or 3D printing has been massively developed for every material, including cement-based materials. Some possibilities have arisen to incorporate industrial wastes in cement mixtures in 3D printing applications. However, a comprehensive study about fly ash (FA), ground granulated blast-furnace slag (GGBFS), and silica fume (SF) usage in 3D-printed materials needs to be conducted. This paper shows that some aspects of 3D printing, such as printability, buildability, and rheological properties, need to be considered, and waste materials affect these fresh mixture properties. Applying waste materials as supplementary cementitious materials also gives different mechanical properties and durability performances. Furthermore, the environmental and economic benefits of 3D-printed and conventional materials are compared. The results show that 3D printing methods can enhance the environmental and economic benefits while maintaining the performance of materials created using traditional methods. Studying industrial waste application in 3D printing has become a promising way to develop sustainable materials in this digitalization era.

A comparative study on blockchain-based distributed public key infrastructure for IoT applications

A comparative study on blockchain-based distributed public key infrastructure for IoT applications

Auxetic cementitious cellular composite (ACCC) PVDF-based energy harvester

The high deformation capacity of auxetic cementitious cellular composites (ACCCs) makes them promising for strain-based energy harvesting applications in infrastructure. In this study, a novel piezoelectric energy harvester (PEH) with ACCCs and surface-mounted PVDF film based on strain-induced piezoelectric mechanisms has been designed, fabricated, and experimentally tested. Furthermore, a numerical model for simulating the energy harvesting of ACCC-PVDF system undergoing repeated mechanical loading has been established and validated against the experimental data. The mechanical behavior of ACCCs was simulated by the concrete damage plasticity model during the preloading stage, which was converted to the second-elasticity model during cyclic loading stage. Based on the mechanical responses, analytical formulas for piezoelectric effects were developed to calculate the output voltage of the PVDF film. The output voltages of the ACCCs-PVDF system under different loading amplitudes and loading frequencies were assessed. The experimental results and models of the ACCCs-PVDF energy harvester lay a solid foundation for utilizing architected cementitious composites in energy harvesting applications to supply self-power electronics in infrastructure.

Study on the impact of digital economy on innovation output based on dynamic panel data model

PurposeThe digital economy has become a new engine for economic development, promoting the upgrading and transformation of traditional industries as well as fostering emerging industries and forms of business. Nonetheless, how does the digital economy affect innovation? The research objective is to explore the specific impact of the digital economy on innovation output.Design/methodology/approachThis paper innovatively adopts the dynamic panel data model (DPDM) to carry out an empirical study on the impact of the digital economy on innovation output, through the observation of 30 provincial-level administrative regions in China. Furthermore, the paper innovatively analyzes the impact of different dimensions of the digital economy on innovation output and the impact of the digital economy on different dimensions of innovation output.FindingsIt is found that the digital economy is conducive to boosting innovation output considering innovation continuity. Specifically, the driving impact of core industries and enterprise application of digital economy on innovation output is more prominent, but the driving impact of infrastructure and personal application on innovation output is not fully played. Meanwhile, the driving impact of the digital economy on the innovation output quality is more significant than that digital economy on the innovation output quantity.Originality/valueThis study employs a DPDM for the first time to investigate the specific impact of the digital economy on innovation output, and contributes to the existing literature on the digital economy and digital economy-driven innovation. The findings offer a comprehensive explanation for the impact of the digital economy on innovation output, which has reference value for the formulation of innovation policies driven by digital economy, thereby providing impetus for the sustained and stable development of China's economy.

Biomimetic intruder tip design for horizontal penetration into a granular pile.

In nature, woodpeckers peck trees with no reported brain injury. A highly functional system comprising a hyoid bone, smooth skull, straight pointed beak with varying lengths of upper and lower beak bones, and rhamphotheca is one of the adaptations that enable efficient pecking. Soil penetration is an energy-intensive procedure used in civil infrastructure applications and is often followed by pushing, impact driving, and digging. This study uses discrete element modeling to evaluate the effect of woodpecker beak mimetic intruder tip design with wedge offsets on lift and drag forces during horizontal penetration into granular piles. The findings show that the wedge offsets of the intruder have a negligible effect on drag forces. By contrast, lift forces can be manipulated by adjusting the top and bottom offsets of the intruder, which can be used to guide the intruder upward, downwards, or horizontally. Furthermore, as the width of the intruder increased, the lift and drag forces also increased.