Local Construction Research Articles

The Real-Time Local Surface Model Construction Method of Unknown-Model Workpieces for Robotic Polishing

The Real-Time Local Surface Model Construction Method of Unknown-Model Workpieces for Robotic Polishing

Designing and presenting a conceptual model of technology transfer for the provision of technological products in the localization and internal construction of oil and gas industry equipment

Technology transfer in the oil and gas industry plays a vital role in improving domestic capabilities and reducing dependence on imports. This article deals with the design and presentation of a conceptual model for technology transfer in order to provide technological products and localization of equipment in this industry. The documents obtained from the searches were used to identify the most important challenges of technology transfer. In the next step, in order to validate the identified critical challenges, ten experts were interviewed and their qualitative judgments about the identified challenges were collected. Among these ten experts, seven experts were from the industry and three experts were from university professors of technology management. Also, in the expert interview stage, in addition to validating the challenges identified based on the literature, a number of new challenges faced by the country's oil and gas industries regarding technology transfer And the first purchases of technological products face them; was identified In the next step, the weights of each of the identified challenges were calculated based on the subject literature and expert interviews, with the design of special questionnaires for pairwise comparisons and the multi-criteria decision-making method of Analytical Hierarchy (AHP). The results of the research show that the use of this model can help to improve the localization process and promote the industrial capabilities of the country in the field of oil and gas. Also, suggestions have been made to facilitate and accelerate the technology transfer process and increase its effectiveness.

The Necessity for Precise Estimation: Formulating a Malaysian Labour and Plant Constant for Construction Productivity

The Malaysian construction industry plays a vital role in driving economic growth and infrastructure development. However, the sector faces significant challenges in achieving accurate productivity measurement and cost estimation due to its reliance on foreign-based Labour and Plant Constants. These metrics, often misaligned with local conditions, lead to budget overruns, project delays, Extension of Time (EOT) claims, and Variation Orders (VOs). The lack of a standardized approach to determine the optimal combination of labour, plant, and machinery further complicates resource allocation and project planning, ultimately affecting the industry’s overall efficiency and competitiveness. This paper emphasizes the urgent need to develop a Malaysian Labour and Plant Constant that reflects the unique conditions of the local construction environment, including labour skills, environmental factors, and machinery capabilities. Such localized constants will enhance cost estimation accuracy, improve resource management, reduce project delays, and foster sustainability in Malaysia’s construction sector. Additionally, this initiative would align the industry with global best practices, boosting its competitiveness both locally and internationally. Establishing a robust resource optimization methodology will improve cost estimates, reduce project delays, and enhance overall efficiency. This paper emphasizes the necessity for a Malaysian-specific approach to productivity measurement and cost estimation to boost the accuracy and reliability of tender evaluations, ultimately strengthening the competitiveness and sustainability of the Malaysian construction industry.

Appraisal of Alternative Dispute Resolution Methods Used in Construction Industry of Abeokuta Ogun State.

The construction industry is a vital component of economic development in Abeokuta, Ogun State, Nigeria, characterized by its dynamic and complex nature. With the increase in construction activities, disputes are inevitable, often leading to project delays, cost overruns, and strained relationships among stakeholders. To address these challenges, alternative dispute resolution (ADR) methods have gained popularity as effective mechanisms for resolving disputes in the construction industry. This research paper aims to provide a comprehensive appraisal of the ADR methods used in the construction industry in Abeokuta, Ogun State. The study employs a qualitative research methodology with the aid of focus group discussion strategy employing various stakeholders, including construction professionals, legal experts, government officials, and project owners. The research investigates the types and frequency of disputes encountered in construction projects, explores the awareness and utilization of ADR methods, and evaluates the effectiveness and efficiency of these methods in resolving disputes. The research highlights the need for increased awareness and education about ADR methods among construction professionals in Abeokuta. It underscores the importance of establishing an ADR framework tailored to the specific needs and challenges of the local construction industry. Furthermore, the study suggests that a more structured and standardized approach to ADR could lead to more efficient and timelier dispute resolution, ultimately benefiting the construction industry's stakeholders.

The impact of migration processes on the construction sector of Kyrgyzstan: Problems and strategies of public administration

This article examines the impact of migration on the construction industry of Kyrgyzstan, and also analyzes the main problems faced by government agencies in managing this process. Aspects such as labor instability, increasing demand for housing resources, changes in urban infrastructure and sociocultural changes are discussed. Possible solutions are proposed for the effective management of migration flows in the construction sector, including improving mechanisms for regulating labor migration, developing programs to support local construction companies and creating conditions for improving the skills of local personnel. In conclusion, a conclusion is drawn about the need for an integrated approach to managing migration processes, taking into account their impact on various aspects of the economy and society of Kyrgyzstan.

Quantitative ethnobotany of plants used for vernacular building construction in Ghana.

Vernacular construction uses locally available materials, including plant-based materials. The sustainability of plant use raises concerns. Social evaluation using an ethnobotanical approach gives a clear overview of the sustainability of wild plant harvesting as it incorporates the views of resource users. In Ghana, plant-based materials are commonly used for vernacular housing construction, especially in rural areas. However, the cultural significance of plant species used for vernacular building construction remains unexplored. This study aimed to take an inventory of plant species and use their ethnobotanical indices to evaluate the sustainability of utilization in vernacular building construction. Ethnobotanical data on plant species used for vernacular building construction was collected from 258 respondents in the Adaklu district of the Volta region. Quantitative ethnobotanical analysis revealed that of the 26 plant species identified to be used for vernacular building construction, Bambusa vulgaris, Borassus aethiopum, Elaeis guineensis, Senna siamea, and Azadirachta indica were the most culturally significant and valuable. Bambusa vulgaris had the highest cultural importance, value, and relative importance index. Elaeis guineensis had the highest relative frequency of citations. The findings reveal a high potential for valorizing the culturally important and valuable plant species in the local construction industry. Promoting culturally significant and valuable plant species commercialization presents an opportunity for poverty alleviation at the local level, as most of the species are abundant in the natural environment and are among the commonly planted species for the afforestation program in Ghana.

LiDAR-SLAM loop closure detection based on multi-scale point cloud feature transformer

Loop closure detection is an important part of simultaneous localization and mapping (SLAM), used to detect and correct map and trajectory drift issues caused by accumulated errors. For the LiDAR-SLAM system, the sparsity and disorder of point clouds make position recognition based on 3D point clouds more challenging. In recent years, many deep learning-based closed-loop detection algorithms have been proposed. However, due to the sparsity of point clouds, current deep learning algorithms often convert point clouds into histograms or depth maps and then process them using deep learning algorithms, undoubtedly causing information loss. In this paper, we propose a closed-loop detection method based on multi-scale point cloud features transformer, which introduces multi-scale point cloud feature extraction and transformer global context modeling. We use voxel sparse convolution to obtain features of original point clouds at different resolutions and establish contextual relationships between features at different resolutions using the transformer network to achieve multi-scale feature fusion, and then obtain global descriptors. The obtained global descriptors can be used not only for closed-loop detection but also for front-end registration to address the challenges of point cloud processing in the SLAM system, especially in enhancing global modeling capabilities and reducing information loss. Our method directly processes point cloud data and integrates multi-scale point cloud feature information, which can better adapt to the characteristics of LiDAR-SLAM systems, improving the accuracy and robustness of localization and map construction, thus having broad application prospects in the field of measurement. We evaluated our method on multiple sequences of the KITTI and KITTI-360 datasets, each containing more than 5000 frames of point clouds, and extensively evaluated on a self-collected dataset of over 3.6 km. The experimental results show that our method achieves an accuracy of over 80% on multiple datasets and demonstrates superior performance in different environments.

STUDY OF TRANSFORMATION OF JHAROKHA WINDOW FORM IN LAHORE

The traditional architecture of any area embodies its true character, deeply rooted in the history, geography, and culture of that region. It does not only satisfy the functional requirements but also stems from local construction techniques and materials available. Traditional architecture faces the problem of its coexistence with modern technological development everywhere. The built heritage which stands in Lahore over centuries is encroached by modern and efficient techniques. The present paper specifically focuses on the development of Jharokha windows (Bay windows) in Lahore. The Jharokha window that was used in the Indian sub-continent during and after the Mughal period was the solution to the climatic conditions of the region. This research will investigate the old Jharokha window form and how with technology and advancement it starts losing its original form. The change in Jharokha form will be studied by the existing examples from different time periods available in the city of Lahore.

IRGWP: An international network of key players for a better understanding and industrial developments in wood protection and preservation

IRGWP: An international network of key players for a better understanding and industrial developments in wood protection and preservation

Research on the Current Situation of Thermal Environment in Guanzhong Farmhouses and Strategies for Improving Human Settlement Environment

Energy is one of the most important factors that constrain global economic development, and it is the fundamental guarantee for national economic development and the circular development of various industrial links. Building energy conservation is the key to achieving energy conservation and emission reduction. The Guanzhong region is a typical cold winter and hot summer area, and in the development process, Guanzhong residential buildings have also formed a set of construction strategies suitable for the regional climate characteristics. Combining local unique construction techniques and materials, the building exhibits significant local characteristics. This study analyzed the climate characteristics and passive technologies in the Guanzhong region, and constructed a 3D model of typical rural houses. Based on field research, a green development strategy was proposed by comparing and analyzing the differences between actual monitoring of ventilation and lighting and mathematical simulation. This study contributes to promoting the improvement of regional living environment and sustainable development.

MR-MD:MULTI-ROBOT MAPPING WITH MANHATTAN DESCRIPTOR

Abstract. Simultaneous Localization and Mapping (SLAM) technology, utilizing Light Detection and Ranging (LiDAR) sensors, is crucial for 3D environment perception and mapping. However, the absence of absolute observations and the inefficiency of single-robot perception present challenges for LiDAR SLAM in indoor environments. In this paper, we propose a multi-robot (MR) collaborative mapping method based on the Manhattan descriptor (MD) named MR-MD to overcome these limitations and improve the perception accuracy of LiDAR SLAM in indoor environments. The proposed method consists of two modules: MD generation and MD optimization. In the first module, each robot builds a local submap and constructs MD by parameterizing the planes in the submap. In the second module, the global main direction is updated using the historical MD of each robot, and constraints are built for each robot's horizontal and vertical directions according to their current MD and optimized. We conducted extensive comparisons with other multi-robot and single-robot LiDAR SLAM methods using real indoor data, and the results show that our method achieved higher mapping accuracy.

Projecting future carbon emissions from cement production in developing countries

Achieving low-carbon development of the cement industry in the developing countries is fundamental to global emissions abatement, considering the local construction industry’s rapid growth. However, there is currently a lack of systematic and accurate accounting and projection of cement emissions in developing countries, which are characterized with lower basic economic country condition. Here, we provide bottom-up quantifications of emissions from global cement production and reveal a regional shift in the main contributors to global cement CO2 emissions. The study further explores cement emissions over 2020-2050 that correspond to different housing and infrastructure conditions and emissions mitigation options for all developing countries except China. We find that cement emissions in developing countries except China will reach 1.4-3.8 Gt in 2050 (depending on different industrialization trajectories), compared to their annual emissions of 0.7 Gt in 2018. The optimal combination of low-carbon measures could contribute to reducing annual emissions by around 65% in 2050 and cumulative emissions by around 48% over 2020-2050. The efficient technological paths towards a low carbon future of cement industry vary among the countries and infrastructure scenarios. Our results are essential to understanding future emissions patterns of the cement industry in the developing countries and can inform policies in the cement sector that contribute to meeting the climate targets set out in the Paris Agreement.

ОСОБЕННОСТИ КИНЕМАТОГРАФА РОССИЙСКИХ РЕГИОНОВ: КОНСТРУИРОВАНИЕ СОЦИАЛЬНЫХ СМЫСЛОВ

The article analyzes the phenomenon of regional cinema in Russia. It analyzes the main theoretical and methodological approaches in the study of film art, as well as interpretations of the concepts of “images”, “meanings” and “constructs” contained in contemporary regional films. It is noted that the positioning of the region in the sociocultural space is conditioned by the emergence of such a form of representation as cinema. It is shown that regional cinema represents a variety of local value constructs that are capable of self-reflection and active transformation of social reality. Symbolic constructs displayed in films can be perceived as unifying (images of historical events and figures, hard provincial life in the regions) and distinctive (customs, myths, rituals, church). The analysis of film content showed that modern regional cinema combines cultural and ethnic diversity, i.e. preservation of ethnic traditions and customs, Soviet values such as mutual aid and responsibility, and local specifics – the role of family, relationships and love for the small homeland.

Nma nwoke (“Man's Beauty”)

Abstract Since the 1980s, low male enrollment in secondary schools has been observed in Anambra State in southeast Nigeria. Previous studies largely attribute the phenomenon to a masculine drive toward the quick accumulation of material wealth. This article draws on two primary qualitative studies conducted in the state in 2012 and 2020 and on Bourdieu's notion of habitus to discuss how the local construction of masculinity and social expectations influence boys’ aspirations and preferences and contribute to their decision to drop out of high school. Participants were both males and females who dropped out of school of high school or who did not enroll in high school before entering the workforce. While economic factors are central to males’ disengagement from school, they are underpinned by demands and pressures associated with the social construction of masculinity. Material wealth is seen as a symbol of a man's beauty (nma nwoke). Policy and intervention programmes are needed to mitigate societal pressures on boys in Anambra State.

Improvement of Productivity in Buildings Construction

Abstract Improving productivity in construction projects has long been a major concern, and much research has been carried out to try to ameliorate construction productivity. To this end, this study aims to improve and increase the productivity rate of flat slab formwork used in residential construction projects. A survey consisting of 150 questionnaires was undertaken to identify the factors that influence on the productivity. Based on the relative Importance Index (RII), data on eleven factors deemed to affect productivity were selected. A collection of 100 data points from various sites were utilized to develop two models. Firstly, an Artificial Neural Network (ANN) model was employed, and secondly, a parametric approach was investigated. The data were divided into two sets, with 70% of the data used for training and the remaining 30% used for testing. The models’ performance was evaluated using the Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) values. In the test phase, the artificial neural network model yielded an MSE value of 2.6610e−4 and a MAPE value of 4.9227, whereas the parametric model produced an MSE of 0.040 and a MAPE of 9.525. It was found that the artificial neural network model provided reliable prediction accuracy compared to the parametric model. However, the artificial neural network approach can be selected as a robust model in predicting and controlling the productivity rate in local construction projects by using the developed model based on the identified factors.

Collaborative Innovation and New Ideas for Talent Training in Local Normal Universities

The purpose of this paper is to explore the new ideas of collaborative innovation and talent training in local normal universities and to promote the reform of the training model of high-quality and skilled applied undergraduate talents by building a collaborative innovation platform for schools, enterprises, and social organizations, to meet the needs of local economic and social development. This paper proposes the idea of cultivating new talents based on collaborative innovation, including interdisciplinary integrated education, practical project-driven learning, innovative technology integration, and collaborative innovation platform construction. Through the chapters of literature review, correlation analysis between collaborative innovation and talent training in local normal universities, and construction and practice of new ideas, the theoretical basis and practical operation of the new ideas are comprehensively discussed.

La cerámica de cocina y mesa de Talavera de la Reina

The production of Talavera ceramics in Talavera de la Reina (Castilla-La Mancha, Spain) takes part of local cultural constructions of deep tradition. Halfway between the manufactures made for the upper or ruling classes and the most popular productions, over time, ceramics from Talavera have both intimate relationships with the productions made for the wealthier classes, as well as an interesting link with lower-scale social groups. In this article and starting from some historical considerations in relation to this type of ceramic production, we will analyze the evolution of Talavera pottery up to the present day, inscribed as intangible cultural heritage by UNESCO and looking for new ways to stay alive and in use over time.

A Decoding Method Using Riemannian Local Linear Feature Construction for a Lower-Limb Motor Imagery Brain–Computer Interface System

Recently, motor imagery brain–computer interfaces (BCIs) have been developed for use in motor function assistance and rehabilitation engineering. In particular, lower-limb motor imagery BCI systems are receiving increasing attention in the field of motor rehabilitation, because these systems could accurately and rapidly identify a patient’s lower-limb movement intention, which could improve the practicability of the motor rehabilitation. In this study, a novel lower-limb BCI system combining visual stimulation, auditory stimulation, functional electrical stimulation, and proprioceptive stimulation was designed to assist patients in lower-limb rehabilitation training. In addition, the Riemannian local linear feature construction (RLLFC) algorithm is proposed to improve the performance of decoding by using unsupervised basis learning and representation weight calculation in the motor imagery BCI system. Three in-house experiment were performed to demonstrate the effectiveness of the proposed system in comparison with other state-of-the-art methods. The experimental results indicate that the proposed system can learn low-dimensional features and correctly characterize the relationship between the testing trial and its k-nearest neighbors.

Local carbon emission zone construction in the highly urbanized regions: Application of residential and transport CO2 emissions in Shanghai, China

Optimizing urban morphology can help city managers deploy internal carbon reduction strategies. However, due to the numerous factors that influence urban carbon emissions and the complex paths of their effects, existing research findings are diverse and difficult to compare. This study constructed the local carbon emission zone (LCEZ) which links the highly urbanization morphology profiles and CO2 emission intensity to favor summarizing the form characteristics for the low CO2 emission control in new communities. The approach involved selecting six indicators from the perspectives of urban external morphology, internal characteristics, and development intensity, and using geographically weighted regression (GWR) to identify three key factors. The selected factors were divided into low(1) medium(2) and high(3) categories and were combined with each other to construct the LCEZ. The nonparametric test and GeoDetector model were used to test the difference and similarity of LCEZs, respectively. The results showed that 1) The impacts of functional mixing entropy (FME), building height (BH) and road density (RD) on residential and transport CO2 emissions (RTCE) were relatively large and positive; 2) The low- and medium-FME areas were the major types of LCEZ; 3) The area proportions of the low FME LCEZs in different population areas of the RTCE cold spot regions were the highest (81.84%–88.25%); 4) It is recommended that the morphological feature values of compact-low rise-low network (1-1-1), mid compact-low rise-mid network (1-1-2), compact-mid rise-low network (1-2-1) and mid compact-mid rise-mid network (1-2-2) were taken as the low CO2 emission control of highly urbanized regions.

A local construction of zip period maps of Shimura varieties

Let S be the special fibre of a Shimura variety of Hodge type of good reduction at a fixed place above p . We give a local approach to the construction of the zip period map for S , which is used to define the Ekedahl–Oort strata of S . The method employed is p -adic and group theoretic in nature.