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A newly developed frequency-independent lumped parameter model (LPM) is the purpose of the present paper. This new model’s direct outcome ensures high efficiency and a straightforward calculation of foundations’ vertical vibrations. A rigid circular foundation shape resting on a nonhomogeneous half-space subjected to a vertical time-harmonic excitation is considered.

A simple model representing the soil–foundation system consists of a single degree of freedom (SDOF) system incorporating a lumped mass linked to a frequency-independent spring and dashpot. Besides that, an additional fictitious mass is incorporated into the SDOF system. Several numerical methods and mathematical techniques are used to identify each SDOF’s parameter: (1) the vertical component of the static and dynamic foundation impedance function is calculated. This dynamic interaction problem is solved by using a formulation combining the boundary element method and the thin layer method, which allows the simulation of any complex nonhomogeneous half-space configuration. After, one determines the static stiffness’s expression of the circular foundation resting on a nonhomogeneous half-space. (2) The system’s parameters (dashpot coefficient and fictitious mass) are calculated at the resonance frequency; and (3) using a curve fitting technique, the general formulas of the frequency-independent dashpot coefficients and additional fictitious mass are established.

Comparisons with other results from a rigorous formulation were made to verify the developed model’s accuracy; these are exceptional cases of the more general problems that can be addressed (problems like shallow or embedded foundations of arbitrary shape, other vibration modes, etc.).

In this new LPM, the impedance functions will no longer be needed. The engineer only needs a limited number of input parameters (geometrical and mechanical characteristics of the foundation and the soil). Moreover, a simple calculator is required (i.e. we do not need any sophisticated software).

Several studies were made on paired site and soil–structure interaction (SSI) effects, but most of them were site specific. This paper aims to investigate the impact of SSI effects in conjunction with local soil condition effects on the seismic response of typical multistory low- to mid-rise–reinforced concrete (RC) buildings resting on Algerian regulatory design sites through a global explicit transfer function (TF).

A preliminary quantification of SSI effects associated with site effects is carried out through a frequency-domain solution based on the concept of rock-to-soil surface displacement TF performed for each design site category. It results from the combination of the TFs of structure, foundation and soil and reflects how seismic waves are amplified due to changes in the geological contrast between the rock and overlying soil deposits. As well, response modification factors, denoting displacement ratios of the building responses within the flexible and site-structure conditions with respect to the fixed-base one, are carried out.

In the context of Algerian seismic regulation, the study provides a clear vision of how and when site or SSI effects are expected to be influential, as opposed to the fixed-base hypothesis still retained by the current regulation. This helps engineers to be aware of the extent of the expected seismic damage.

The research applies to low- to mid-rise RC buildings within the Algerian seismic regulation, but it may also be expanded to other examples that fall under other seismic regulations.

The response modification ratio is a quantitative approach to assessing response fluctuations. It draws attention to how the roof level drift varies depending on the condition. These results can be used as numerical parameters in structural seismic design when the structure is comparable because they provide useful information about how the two phenomena interact with the structure.

The study goes beyond particular situations dealing with site specific and offers effective indicators and quantitative evaluation of combined site and SSI effects according to the current national seismic provisions, where no indication about site or SSI effects exists.

This study aims to investigate the behavior of different types of stone columns, including the short and floating columns, as well as the ordinary and the geosynthetic encased stone columns (OSC and GESC). The effectiveness of the geosynthetic encasement and the impact of the installation using the lateral expansion method on the column performance is evaluated through a three-dimensional (3D) unit cell numerical analysis.

A full 3D numerical analysis is carried out using the explicit finite element code PLAXIS 3D to examine the installation influence on settlement reduction (ß), lateral displacement (U_x) and vertical displacement (U_z) relative to different values of lateral expansion of the column (0% to 15%).

The findings demonstrate the superior performance of GESC, particularly short columns outperforming floating counterparts. This enhanced performance is attributed to the combined effects of geosynthetic encasement and increased lateral expansion. Notably, these strategies contribute significantly to decreasing lateral displacement (U_x) at the column’s edge and reducing vertical displacement (U_z) under the rigid footing.

In contrast to previous studies that examined the installation effect of OSC contexts, this paper presents a comprehensive investigation into the effect of geosynthetic encasement and the installation effects using the lateral expansion method in very soft soil, using 3D numerical simulation. The study emphasizes the significance of the consideration of geosynthetic encasement and lateral expansion of the column during the design process to enhance column performance.

In the UK, responses to intense weather events regarding national and regional level perils include the support of a General Insurance policy at the address level as part of private residential and other insurance policies covering the key risks of flooding, subsidence and windstorm. In respect of the subsidence peril, dry summers can lead to many thousands of properties on shrinkable clay soils suffering differential downward movement as water is abstracted from the soil by vegetation. These events are forecast to increase in frequency and severity due to climate change, with costs for a dry event year of more than £500m to UK insurers. Assessing the character of these event years can inform government, local government, insurers and their agents as to the typical characteristics of an event year and its impacts. The purpose of this paper is to provide a comprehensive overview of the 2018 UK subsidence event year as it relates to trees and low rise buildings.

The research material is taken from claims that originated within the period commencing in the Summer of 2018, which in the UK was dry and with high levels of claim notification, and is from the private database of Property Risk Inspection Limited, one of the largest UK specialist subsidence claims handling businesses.

The data clearly illustrates the wide range of vegetative species causing or contributing to claims in the UK, their age ranges, sizes and conditions, management options and the range of land uses and statutory controls that exist in relation to title and other boundaries.

There have been various small-scale studies looking at individual cases of subsidence and the impacts of vegetation, but there have been no detailed investigations of large-scale claims-driven events such as the 2018 surge. The importance of this population-level investigation will only increase given the modelling for increased hot and dry summers over the coming decades.

The main objective of the present research is to investigate the benefits of using geogrid reinforcement in minimizing the rate of deterioration of ballasted rail track geometry resting on soft clay and to explore the effect of load amplitude, load frequency, presence of geogrid layer in ballast layer and ballast layer thickness on the behavior of track system. These variables are studied both experimentally and numerically. This paper examines the effect of geogrid reinforced ballast laying on a layer of clayey soil as a subgrade layer, where a half full scale railway tests are conducted as well as a theoretical analysis is performed.

The experimental tests work consists of laboratory model tests to investigate the reduction in the compressibility and stress distribution induced in soft clay under a ballast railway reinforced by geogrid reinforcement subjected to dynamic load. Experimental model based on an approximate half scale for general rail track engineering practice is adopted in this study which is used in Iraqi railways. The investigated parameters are load amplitude, load frequency and presence of geogrid reinforcement layer. A half full-scale railway was constructed for carrying out the tests, which consists of two rails 800 mm in length with three wooden sleepers (900 mm × 90 mm × 90 mm). The ballast was overlying 500 mm thick clay layer. The tests were carried out with and without geogrid reinforcement, the tests were carried out in a well tied steel box of 1.5 m length × 1 m width × 1 m height. A series of laboratory tests were conducted to investigate the response of the ballast and the clay layers where the ballast was reinforced by a geogrid. Settlement in ballast and clay, was measured in reinforced and unreinforced ballast cases. In addition to the laboratory tests, the application of numerical analysis was made by using the finite element program PLAXIS 3D 2013.

It was concluded that the settlement increased with increasing the simulated train load amplitude, there is a sharp increase in settlement up to the cycle 500 and after that, there is a gradual increase to level out between, 2,500 and 4,500 cycles depending on the load frequency. There is a little increase in the induced settlement when the load amplitude increased from 0.5 to 1 ton, but it is higher when the load amplitude increased to 2 ton, the increase in settlement depends on the geogrid existence and the other studied parameters. Both experimental and numerical results showed the same behavior. The effect of load frequency on the settlement ratio is almost constant after 500 cycles. In general, for reinforced cases, the effect of load frequency on the settlement ratio is very small ranging between 0.5 and 2% compared with the unreinforced case.

Increasing the ballast layer thickness from 20 cm to 30 cm leads to decrease the settlement by about 50%. This ascertains the efficiency of ballast in spreading the waves induced by the track.

As video-based interventions are continuously utilized as alternatives to physical site visits, directing students' attention to specific learning contents within videos could increase their comprehension and stimulate their interest. Students' knowledge of construction practice can be reinforced, misconceptions and improper inferences can be reduced by calling out significant learning concepts. However, few studies have formalized practice concepts that could be beneficial in preparing students for the workplace. This paper presents an investigation of construction practice concepts, based on site visits that would be beneficial in complimenting classroom teaching to prepare students for the realities of practice.

A mixed methods research approach was employed combining qualitative and quantitative data collection and analysis. An online questionnaire, semi-structured interviews and a focus group were conducted with industry practitioners and instructors to identify the topics and practice concepts significant for supporting classroom teaching with site visits.

The findings suggest that the most relevant topics typically supported with site visits are preconstruction management, excavation and foundation work, construction equipment, construction means and methods, project management, road construction, sustainability, building systems, structures, construction technology, building construction, capstone, site logistics and safety. Practice concepts were identified for each of these topics.

The study will guide researchers in the design of video-based pedagogical tools to be used as an effective complement of or alternative to site visit experiences. The findings will support instructors on how to structure their teaching practices to prepare students for some of the complexities of the workplace.

This study adds value to the existing literature by providing insights into industry perception of practice concepts for complementing classroom teaching.

The purpose of this study was to investigate the likely causes of failure of some sections of road pavements in Ajaokuta, Northcentral Nigeria. This was achieved through a geotechnical assessment of subgrade soils in affected areas.

The methods entailed field and laboratory methods and statistical analysis. Subgrade soil samples were retrieved from a depth of 1,000 mm beneath the failed portions using a hang auger. The soils were analyzed for natural moisture content (NMC), Atterberg limit (liquid limit, plastic limit and linear shrinkage), grain size distribution, compaction and California bearing ratio (CBR), respectively.

The results of the geotechnical tests ranged from NMC (12.5%–19.4%), sand (84%–98%), fines (2%–16%), LL (16.0%–32.2%), PL (17%–27.5%), LS (2.7%–6.4%), PI (2.5%–18.4%), maximum dry density (1756 kg/m2–1961 kg/m2), optimum moisture content (13.2%–20.2%), unsoaked CBR (15.5%–30.5%) and soaked CBR (8%–22%), respectively. Pearson’s correlation coefficient performed on the variables showed that some parameters exhibited a strong positive correlation with r2 > 0.5.

Funding was the main limitation.

Comparing the results with Nigerian standards for road construction, and the AASHTO classification scheme, the subgrade soils are competent and possess excellent to good properties. The soils also exhibited very low plasticity, a high percentage of sand, high CBR and low NMC, which implies that it has the strength required for road pavement subgrades. The likely causes of the failures are, therefore, due to the use of poor construction materials, technical incompetence and poor compaction of sub-base materials, respectively.

This work aims to demonstrate the feasibility of fully preserving the historical heritage at the same time reordering the cities and their traffic.

This paper describes the sustainable solution designed for the landscape change required and to maintain the bridge integrity by excavating under the pier with the maintenance of traffic during its execution.

It is concluded that the elimination of urban motorways on the surface often leads to the excavation of tunnels under the existing buildings, with little coverage in most of them. This complicates the implementation of burials in cities with an important historical heritage, which must be given conservation priority in the choice of technical solutions.

The Segovia Bridge over the Manzanares River, the oldest bridge in Madrid, was built in the 16th century. With the burial of the M-30 motorway, it has been necessary to build a tunnel immediately under one of the bridge piers, practically without lining between the foundations and the upper slab of the tunnel.

The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers one’s intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience.

The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently.

The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models.

Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverse’s experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverse’s economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust.

In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators.

The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models.

Most previous studies predicting review helpfulness ignored the significance of deep features embedded in review text and instead relied on hand-crafted features. Hand-crafted and deep features have the advantages of high interpretability and predictive accuracy. This study aims to propose a novel review helpfulness prediction model that uses deep learning (DL) techniques to consider the complementarity between hand-crafted and deep features.

First, an advanced convolutional neural network was applied to extract deep features from unstructured review text. Second, this study used previous studies to extract hand-crafted features that impact the helpfulness of reviews and enhance their interpretability. Third, this study incorporated deep and hand-crafted features into a review helpfulness prediction model and evaluated its performance using the Yelp.com data set. To measure the performance of the proposed model, this study used 2,417,796 restaurant reviews.

Extensive experiments confirmed that the proposed methodology performs better than traditional machine learning methods. Moreover, this study confirms through an empirical analysis that combining hand-crafted and deep features demonstrates better prediction performance.

To the best of the authors’ knowledge, this is one of the first studies to apply DL techniques and use structured and unstructured data to predict review helpfulness in the restaurant context. In addition, an advanced feature-fusion method was adopted to better use the extracted feature information and identify the complementarity between features.

大多数先前预测评论有用性的研究忽视了嵌入在评论文本中的深层特征的重要性, 而主要依赖手工制作的特征。手工制作和深层特征具有高解释性和预测准确性的优势。本研究提出了一种新颖的评论有用性预测模型, 利用深度学习技术来考虑手工制作特征和深层特征之间的互补性。

首先, 采用先进的卷积神经网络从非结构化的评论文本中提取深层特征。其次, 本研究利用先前研究中提取的手工制作特征, 这些特征影响了评论的有用性并增强了其解释性。第三, 本研究将深层特征和手工制作特征结合到一个评论有用性预测模型中, 并使用Yelp.com数据集对其性能进行评估。为了衡量所提出模型的性能, 本研究使用了2,417,796条餐厅评论。

广泛的实验验证了所提出的方法优于传统的机器学习方法。此外, 通过实证分析, 本研究证实了结合手工制作和深层特征可以展现出更好的预测性能。

据我们所知, 这是首个在餐厅评论预测中应用深度学习技术, 并结合了结构化和非结构化数据来预测评论有用性的研究之一。此外, 本研究采用了先进的特征融合方法, 更好地利用了提取的特征信息, 并识别了特征之间的互补性。