Construction Activities Research Articles

Deep learning-based recognition of construction activities in real construction site environment

PurposeToday’s technological advancements have had a significant impact on the construction industry. Managing and controlling complex construction projects has been made significantly easier using technological tools. One such advancement is the automatic identification of workers’ activities. This study aims to classify construction worker activities by analyzing real-time motion data collected from sensors.Design/methodology/approachIn accordance with our specific goals, we utilized advanced deep-learning methodologies such as deep neural networks, convolutional neural network, long short-term memory and convolutional long short-term memory to analyze the data thoroughly. This involved experimenting with various window sizes and overlap ratios to determine the optimal combination that would result in the most accurate predictions.FindingsBased on the analysis results, the convolutional long short-term memory (ConvLSTM) deep learning model with a window size of 4.8 s and an overlap rate of 75% was found to be the most accurate prediction model. This model correctly predicted 98.64% of the basic construction worker activities in a real construction site environment.Originality/valuePrevious studies have mainly been conducted in laboratory environments and have focused on basic construction activities such as lifting, moving, sawing and hammering. However, this study collected data from real workers in a real construction site environment. Various deep learning models were employed to determine the most accurate one. Additionally, several options were tested to determine the optimal window size and overlap ratio during the data segmentation phase, aiming to select the most suitable ones for preparing the data for the model.

Integration of In-VEST Habitat Quality Model with Landscape Pattern Indices to Assess Habitat Fragmentation Under the Dynamic Development of Park City: Southwest China Case

With rapid urbanization, the types of land in China’s cities are continuously evolving, irreversibly impacting the habitat patches within urban areas. However, the development of park cities has reversed this trend to some extent, particularly in Chengdu, China. To investigate the influence of land use type changes on habitat quality in Chengdu Tianfu New District, the research team selected remote sensing imagery data from the Landsat satellite for three distinct periods: 2014, 2019, and 2024. By employing a comprehensive approach that includes land cover trajectory analysis, land transfer matrices, FRAG-STATS landscape pattern indices, and the habitat quality module within the In-VEST model, this study analyzes the spatial and temporal evolution of land use patterns and the dynamics of habitat quality categories. The findings reveal: (1) the coverage of trees and shrubs in the study area initially declined but later increased, primarily driven by anthropogenic construction activities. Specifically, the land use types in the built-up areas on the northern side of Tianfu New District underwent notable fluctuations, whereas those on the southern side, adjacent to the Longquan Mountain Range, remained relatively stable. (2) From 2014 to 2019, high-quality habitats were predominantly distributed in the southeast of Tianfu New District, characterized by a robust ecological foundation, high landscape integrity, and strong connectivity of ecological land. In contrast, the areas with the poorest habitat quality were situated in the northern built-up areas of Tianfu New District, exhibiting highly fragmented habitat patches, simple edge shapes, and low connectivity. However, between 2019 and 2024, the overall habitat quality within the study area improved, characterized by an increase in the number of high-quality habitats and continuous expansion of habitat areas. The research findings offer valuable insights into future urban planning, ecological restoration, and conservation efforts in Chengdu Tianfu New District, providing critical guidance for the implementation and strategic development of the park city policy.

Suppressing cyclic deactivation of magnesium-calcium dual-functional materials via dispersed metal-carbonate interfaces for integrated CO2 capture and conversion

The integrated CO2 capture and utilization employs chemical looping approach for suppressing the equilibrium limitations of traditional gas-solid catalytic reactions, enabling efficient conversion of dilute CO2 into high-value fuels with minimal energy consumption. However, the diminishing cyclic activity of dual-functional materials poses significant challenges to their industrial application. Herein, we tailored a series of magnesium-calcium materials, the influence of coordinated metals on the cyclic performance were quantitatively investigated. Notably, Fe2Ni2Ce2Mg5Ca20CO3 achieves a cumulative CO yield of 121.0 mmol/g over 15 cycles at 650°C, with a maximum CO yield of 8.3 mmol/g per cycle and 99.0% CO selectivity, and its CO2 capture capacity remains stable at 10.6 mmol/g over 37 adsorption/desorption cycles. Experimental results indicate that lattice phase separation is a fundamental mechanism underlying the decline in cyclic activity. The strategic incorporation of transition metal intermediates promotes the formation of dispersed metal-carbonate interfaces, providing surface hydrogenation sites and accelerating the lattice decomposition and reconstruction of CO3* within a dispersed lattice. This modification mitigates the adsorption/catalytic lattice phase separation, boosts metal migration and deoxygenation activity for cyclic nanoparticle construction. The findings offer valuable strategies for designing highly efficient and stable DFMs in CO2 capture and utilization.

Optimization of chitosan-gelatin-based 3D-printed scaffolds for tissue engineering and drug delivery applications

The combination of biocompatible materials and advanced three-dimensional (3D) additive manufacturing technologies holds great potential in the development of finely tuned complex scaffolds with reproducible macro- and micro-structural characteristics for biomedical applications, such as tissue engineering and drug delivery. In this study, biocompatible printable inks based on chitosan, collagen and gelatin were developed and 3D-printed with a pneumatic-based extrusion printer. The printability of various chitosan–gelatin (CS-Gel) hydrogel inks was assessed by evaluating the quality of the printed constructs. The inks required an extrusion pressure of 150 ± 40 MPa with G22 and G25 nozzles for optimal printing. Inks with low chitosan concentrations (<4% w/v) exhibited poor printability, while inks with 4 % w/v chitosan and 1 % w/v gelatin (CG) demonstrated satisfactory extrusion and printing quality. The addition of collagen (0.1 % w/v) to the optimized ink (CGC) did not compromise printability. Post-printing stabilization using KOH produced self-supporting scaffolds with consistent morphological integrity, while weaker bases like NaOH/EtOH and ammonia vapors resulted in lower pore sizes and reduced structural stability. Water evaporation studies showed that neutralized samples had slower evaporation rates due to the strong intermolecular interactions formed during the neutralization process, contributing to a stable crosslinked network. FTIR spectra confirmed the formation of polyelectrolyte complexes in the CS-Gel and CS-Gel-Collagen blends, further enhancing structural stability. Swelling tests indicated that neutralized constructs maintained stability in different pH environments, with KOH-treated samples exhibiting the lowest swelling ratios and the highest structural stability. After optimizing the ink composition, 10 wt% Levofloxacin was loaded in the constructs as a model antibiotic and it’s in vitro release rate was quantified. Drug loading was approximately 4 % for both ink compositions GC and CGC. CG Levo released over 80 % of levofloxacin within the first hour, reaching full release in 24 h, indicating inadequate control, while CGK Levo exhibited slower initial release (55 % in 15 min) followed by stabilized release after 4 h, likely due to controlled diffusion from expanded constructs. These findings demonstrate that the developed hydrogel inks and optimized printing parameters can produce scaffolds suitable for tissue engineering applications. Finally, the cell compatibility of the 3D-printed constructs was confirmed with MTT assay on fibroblasts and the antimicrobial activity of the drug-loaded constructs was tested against E. coli and S. aureus, showing an increase of the bacteria free zone from 8 ± 0.4 mm of the control against E. coli up to 16.4 ± 0.37 mm in the presence of the KOH-treated CG Levo printed construct.

LSTM-CNN Architecture for Construction Activity Recognition Using Optimal Positioning of Wearables

LSTM-CNN Architecture for Construction Activity Recognition Using Optimal Positioning of Wearables

Artificial Sand: Properties, Applications, and Future Implications

Abstract: Artificial sand, or manufactured sand, has emerged as an alternative to natural sand due to the depletion of natural sand resources and environmental concerns. The scarcity of natural sand due to such heavy demands in growing construction activities have forced to find the suitable substitute. This paper explores the properties, manufacturing processes, applications, advantages, and challenges associated with artificial sand, aiming to highlight its potential in sustainable construction. The promotional use of artificial sand will conserve the natural resources for the sustainable development of the concrete in construction industry

Fully hydro-mechanical coupled analyses of the deep excavation above a multi-aquifer-aquitard system

Deep work shaft excavations have become increasingly common as a preliminary step of tunnel construction. Deep excavation above a multi-aquifer-aquitard system (MAAS) complicates the flow field and stress field surrounding the excavation, inevitably affecting the performance of excavations. However, previous studies with drained or undrained analyses ignored the effects of dewatering-induced groundwater flow on the performance of deep excavations. To better understand this aspect, this study performs fully hydro-mechanical coupled analyses to investigate the performance of a 39.5 m-deep excavation above a multi-aquifer-aquitard system, which considers dewatering in two confined aquifers. A sophisticated three-dimensional (3D) numerical model is developed to simulate the detailed construction processes of drainage, excavation, dewatering, and strut installation. The study presents a comparison of two scenarios (with and without dewatering in a confined aquifer) with respect to wall deflection, stratum deformation, pore pressure, and effective stress path. The analysis results indicate that the effective stress paths are highly dependent on stratum permeability and construction activities. The dewatering behavior significantly reduces the excavation-induced deformation, primarily due to increased effective level and consequently increased resistance on the excavated side. As a result, ground settlements decrease due to less wall deflection.

DLX4 promotes the expression of PD-L1 through GATA1 in Gestational Trophoblastic Neoplasia

Gestational Trophoblastic Neoplasia (GTN) is a highly malignant tumor that originates from trophoblastic cells during embryonic development. In this study, we observed that DLX4, a member of the Distal-Less Homeobox (Dlx) gene family, was upregulated in GTN tissues and cell lines. Bioinformatic analysis showed that DLX4 was highly expressed in most cancers and had a poor survival prognosis in certain tumors; further analysis showed that DLX4 was significantly associated with genes of immune pathways and immune infiltration. Functional analyses revealed that DLX4 overexpression or knockdown did not affect GTN cell proliferation; however, we observed that DLX4 could regulate PD-L1 expression via GATA1. The luciferase reporter activity of the wild-type construct increased after overexpression of GATA1, whereas the mutation of the binding sites abolished the transcriptional increase. In conclusion, our findings suggest that DLX4 regulates PD-L1 expression via GATA1 in GTN and may be a new target for antitumor therapy.

Determination of the importance of material management activities in construction works in terms of their contribution to productivity

In a construction project, a significant part of the costs and construction process is controlled by materials. It is possible to significantly increase productivity at the construction site with successful material management. In this study, first, a comprehensive literature review on material management processes was conducted and how material planning, material procurement, material acceptance and inspection, storage and inventory control, material handling and productivity issues were discussed in the literature was reviewed. Then, the contribution of nine criteria regarding material management to productivity was evaluated through surveys conducted at different construction sites. The study revealed that there were significant differences between the participants’ evaluations according to their gender, education level, profession and construction site size. However, according to general evaluations, the most important criteria were found to be proper storage of materials, identification of critical materials and proper handling of materials. It is evaluated that the study will be a guide for stakeholders in the establishment of material management processes.

Safety Dynamic Monitoring and Rapid Warning Methods for Mechanical Shaft

In the context of urban space constraints, subway and underground projects have become crucial strategies to alleviate urban congestion and enhance residents’ quality of life. However, pit engineering, a frequent accident area in geotechnical engineering, urgently requires innovative safety monitoring technologies. Traditional monitoring methods face challenges such as high labor costs, lengthy monitoring cycles, high-risk working environments, and over-reliance on human judgment. To address these issues, this paper introduces an innovative monitoring system integrating Fiber Bragg Grating (FBG) sensing technology based on a subway pit project in Guangzhou. This system not only achieves fully automated data acquisition but also includes an intelligent monitoring cloud platform, providing unprecedented automated and intelligent monitoring solutions for support structures and the surrounding environment during mechanical shaft construction. The key findings of this paper include the following: (1) The breakthrough application of distributed optical fiber monitoring technology, including successfully deploying this advanced technology in complex pit engineering environments, enabling the precise and continuous monitoring of support structures and surrounding changes, and demonstrating its high effectiveness and intelligence in practical engineering. (2) The innovative design of an intelligent safety monitoring system. By integrating sensors and wireless communication technology, an efficient data networking architecture is constructed, supporting remote configuration and flexible adjustment of monitoring equipment, significantly enhancing data collection‘s real-time performance and continuity while greatly reducing safety risks for field staff, achieving an intelligent upgrade of monitoring work. (3) Comprehensive and accurate empirical analysis. During shaft excavation, the monitoring data collected by the system were stable and reliable, with all indicators maintained within reasonable ranges and closely matching expected changes caused by construction activities, validating the system’s practical application effectiveness in complex construction environments and providing a scientific basis for pit engineering safety management.

Three-Dimensional Air Quality Monitoring and Simulation of Campus Microenvironment Based on UAV Platform

This study innovatively employs drones equipped with air quality sensors to collect three-dimensional air quality data in a campus microenvironment. Data are accurately corrected using a BP neural network, and a cubic model is constructed using three-dimensional interpolation. Combining photogrammetry technology, this study analyzes air quality patterns, finding significant differences from macro trends. Construction activities and large electronic experimental equipment significantly increase PM2.5 levels in the air. In rainy weather, the respiration of vegetation is enhanced, leading to higher CO2 concentrations, while water bodies exhibit higher temperatures in rainy weather due to their high specific heat capacity. This research not only provides a new perspective for microenvironment air quality monitoring but also offers a scientific basis for future air quality monitoring and management.

Construction and biological activity of metallothionein fused with ELP

Metallothionein (MT) plays a significant role in heavy metal removal, antioxidant defense, and immune regulation. The current predominant approach for obtaining natural MT is extraction from tissue, which often entails complex procedures resulting in limited yields. In recent years, researchers have adopted the strategy of fusing labels such as GST or His for the heterologous expression of MT. However, a challenge in industrial production arises from the subsequent removal of these labels, which often leads to a significant reduction in the yield. The fusion with elastin-like polypeptides (ELPs) offers a promising solution for achieving soluble expression of the target protein, while providing a simple and fast purification process. In this study, ELP was fused with MT, which significantly up-regulated the soluble expression of MT. The fusion protein ELP-MT with the purity above 97% was obtained efficiently and simply by inverse transition cycling (ITC). ELP-MT exhibited a remarkable 2,2'-azinobis(3-ethylbenzothiazoline-6- sulfonic acid) ammonium salt (ABTS) scavenging activity, with the half maximal inhibitory concentration (IC50) of 0.77 μmol/L, which was 53.7 times that of the vitamin E derivative Trolox. In addition, the fusion protein demonstrated strong 1,1-diphenyl-2-trinitrohydrazine (DPPH) scavenging ability. Furthermore, ELP-MT had no toxicity to the proliferation and promoted the adhesion and migration of NIH/3T3 cells. All these results indicated that ELP-MT had good biocompatibility. We constructed the fusion protein ELP-MT combining the unique properties of MT and elastin, laying a technical foundation for the large-scale production of recombinant MT and facilitating the applications in food, health supplement, and cosmetic industries.

Assessing the impact of Niger Delta Development Commission interventions on road construction and economic activities in Cross River and Akwa Ibom States, Nigeria

Road construction and maintenance are key interventions that support economic potential in the country. However, the deplorable state of some roads in Nigeria, and in Cross River and Akwa Ibom states draws research concerns. This paper seeks to examine the impact of the Niger Delta Development Commission Intervention on road construction and economic activities in Cross River and Akwa Ibom States, Nigeria. Using the Sustainable Development Framework, a survey research design was employed, gathering data from 400 respondents across both states. The chi-square statistical technique was used to test the hypothesis that the Niger Delta Development Commission Intervention has no significant impact on road construction in Akwa Ibom and Cross River States. The result of the data analysis showed the calculated value X2 = 1592 &gt; 16.92. By this result, the null hypothesis was rejected (16.92) at 0.05 level of significance and 9 Degrees of Freedom, and the alternate was accepted. The study concludes that NDDC road projects have positively influenced economic activities and livelihoods in the states. However, it highlights the need for further improvements, particularly on the Calabar-Itu federal highway.

A BIM-based carbon footprinting of earthworks in road construction process

Carbon dioxide emissions are a major component of greenhouse gases and their evaluation during the life cycle of civil infrastructures is increasingly becoming a pivotal criterion for project tendering. During construction activities, the use of heavy-duty vehicles generally accounts for most of the energy consumption. However, the CO2 emissions deriving from earthwork machines have not been thoroughly calculated yet due to the inner complexity of such task. In this regard, this research streamlines a quantitative assessment process of carbon dioxide leveraging digital tools and considering a bicycle lane project stretching approximately 3 km in Trondheim, Norway. Building Information Modelling (BIM) is adopted to define the necessary earthwork operations and provide accurate data to appraise quantity take-off volumes. Three earthwork tasks, namely excavation, transport and compaction, are investigated. The corresponding CO2 emissions are subsequently quantified considering three operating modes for excavator (idling, moving and working), three types of transport vehicles (wheel dozer, tractor scraper and articulated dump truck) and two models of compaction machines (sheepsfoot and vibratory rollers). The results indicate that 75.5 t CO2 emissions are generated from the on-site heavy machines. In particular, the transport activities contribute to the largest proportion of CO2 emissions (56 %), half of which is produced while moving excess soil to the dump pit. Besides, the amount of carbon dioxide (2.9 t) generated during the idling and moving statuses of excavator is not negligible. Therefore, an optimized construction workflow and proper planning process are required to reduce machine fuel consumptions as well as increase the working efficiency. Bearing in mind the strategic importance represented by early planning for sustainable construction activities, this study provides innovative insights regarding the assessment of carbon footprints generated by earthwork machines.

Developing WasteSAM: A novel approach for accurate construction waste image segmentation to facilitate efficient recycling

The escalating volume of construction activities and resultant waste generation underscores the imperative for developing sophisticated segmentation models to facilitate efficient sorting and recycling processes. This study introduces WasteSAM, an enhanced iteration of the segment anything model (SAM), specifically tailored to address the intricate complexities inherent in construction waste imagery. Drawing upon a comprehensive dataset comprising over 15,000 masks representing five distinct categories of construction materials, WasteSAM exhibits notably superior segmentation capabilities. Quantitative analysis demonstrates significant performance improvements, with WasteSAM outperforming the original SAM model by an average of 23.9% in dice similarity coefficient and 30.0% in normalized surface distance metrics. The integration of stereo-image techniques in refining the training dataset has facilitated WasteSAM in more accurately discerning the three-dimensional structure of waste materials, thereby augmenting the precision of waste classification. Noteworthy is the model’s adeptness in handling intricate textures and patterns across diverse imaging modalities, including varying lighting conditions and complex object interactions. While showing promising results, this study also highlights the need for high-quality, diverse datasets that reflect real-world construction site complexities, rather than merely larger datasets.

Assessing the Level of Construction Mechanization in Kenya: A Survey of Highrise Building Projects in Nairobi

This paper examines the construction mechanization level in high-rise building projects in Kenya. It focuses on Site Preparation and Earthworks (SPE), Scaffolding and Formwork (SF), Concreting (C), Walling (W), Plastering and Flooring (PF), Tiling and Painting (TP), and Building Services (BS). Mechanization, defined as the replacement of manual labour with machines, is analyzed through a quantitative survey involving 125 accredited construction site supervisors with the unit of analysis being the construction project. The findings reveal that SPE tasks predominantly utilize Hand Tools (43%) and Automated Hand Tools (41%), with Machines accounting for only 16%. Comparatively, SF tasks show slightly lower mechanization levels, primarily relying on Hand Tools (50%) and Automated Hand Tools (41%). Concreting is the most mechanized work category with most of the tasks primarily executed using Automated Hand Tools (67%) and Machine/Workstation (26%). Walling tasks mainly rely on Hand Tools (54%) and Automated Hand Tools (33%). PF, TP, and BS tasks predominantly rely on Hand Tools (70%, 77%, and 68% respectively). Consequently, more than half (53%) of the activities in the building construction sector in Kenya are carried out using Hand Tools. This is then followed by Automated Hand Tools with an approximate usage of 31%. Completely Manual methods and Machines (workstations) are used almost similarly at 9% and 7% respectively. None of the activities in construction are Completely Automated (robotized). The mechanization levels for the various work categories are as follows; SPE=52%, SF=47%, C=64%, W=48%, PF=41%, TP=38%, and BS=39%. The overall mechanization level for the construction industry of Kenya was found to be 47%, indicating a substantial reliance on manual methods. Despite the advantages of mechanization, such as improved efficiency and safety, its application in Kenyan construction remains limited. The study highlights the need for increased mechanization to enhance productivity and safety in construction practices

КОНСТРУКТИВНИТЕ ИГРИ – ОСНОВНО СРЕДСТВО ЗА СЕНЗОРНО ВЪЗПИТАНИЕ НА ДЕЦАТА

The child's contact with his environment is organically connected with the course of sensory processes. The task of the educator is to organise, guide and explain this interaction with the environment, drawing on scientific paradigms from psychology, pedagogy, methodology, as well as the use of specialised literature, but last but not least – drawing on his own experience. The place of ideas, imagination and pictorial thinking occupy a significant share in the planning of the upcoming construction activity. However, in the actual implementation of the conception, the necessity of the sensory processes of sensation and perception, without which the realisation of the constructive game is impossible, comes to the fore again.

Environmental Management Practices and Sustainable Green Concrete Use in Malaysia's Construction Industry: Challenges, Benefits, and Future Directions

This review examines the environmental management practices (EMPs) employed within Malaysia's construction sector, with a particular focus on sustainable practices and the adoption of green concrete, including fly ash, rice husk ash, and palm oil fuel ash varieties. The study identifies key challenges, such as low awareness, high costs, weak legal enforcement, and the underdevelopment of green materials in the country. To address these issues, the report proposes solutions such as capacity-building programs, government incentives like tax breaks and grants, regular site inspections, and investment in research and development of green materials. The review also assesses the advantages and limitations of different green concrete types used in Malaysia. The aim of this study is to enhance sustainability efforts and reduce the environmental impact of construction activities through greater awareness, stronger regulatory support, and commitment from all stakeholders. Implementing greener concrete and EMPs is expected to not only mitigate environmental concerns but also yield long-term economic benefits for Malaysia.

Spatial-temporal patterns and driving mechanism of rural vulnerability at county level：A case study of 117 counties in Heilongjiang Province, China

Rural vulnerability is used to understand the potential multi-hazard threats and describe the fragile state of rural areas, which engage decision-makers in developing policies and strategies to reduce vulnerability. Existing studies about rural vulnerability focused on the single exogenous disturbance but paid inadequate attention to the multi-disturbances of rural coupled human-environment system. In addition, current studies mainly analyzed the spatial differentiation of vulnerability degree, ignoring the temporal evolution and the internal elements’ relationships of rural systems. In this study, we structured the cognition of rural vulnerability with a framework for understanding coupled human-environment system, evaluated rural vulnerability with the dimensions of exposure, sensitivity and adaptability, and analyzed the driving mechanism based on spatial-temporal heterogeneity. Taking 117 county units in Heilongjiang Province as study cases, we found that (1) rural vulnerability was indeed significant, as the area of county units with extreme or high vulnerability levels accounts for 50.4% of the total area, indicating a trend of high vulnerability in the counties on the north and south sides and low vulnerability in the center. (2) The spatial-temporal heterogeneity of rural vulnerability presented a clustering trend, shifting from a relatively balanced spatial distribution from 2010 to 2013 to a state of vulnerability aggregation at all levels from 2016 to 2019. (3) Rural vulnerability was mainly affected by changes in the principal factors of sensitivity and adaptability, and driving sources mainly generated by human activities, which was largely derived from rural construction activities and government policy guidance on rural regulation. Based on the results, we classified county units into different rural vulnerability types, put forward a rural resilience planning mode of “General + Special” with planning strategies for each type, which can be used as a reference for rural planning positioning of county and township level land spatial planning in the national territory spatial planning.

Monitoring Hazards in Dam Environments Using Remote Sensing Techniques: Case of Kulekhani-I Reservoir in Nepal

Maintaining the operability of a hydroelectric power station at a scale originally designed is being compromised by continuous reservoir sedimentation. The underlying factors include a complex mix of landscape alterations owing to natural and anthropogenic activities around dam areas, such as gully erosion, landslides, floods triggered by heavy rainfall, climate change, and construction activities. The hydropower projects in the low-to-mid mountain regions of Nepal are witnessing a combination of these phenomena, affecting their optimal performance in meeting long-term sustainable power supply targets. This paper presents a combination of geo-spatial analysis and field evaluations to identify the trends from Kulekhani-I, one of the oldest storage-type hydropower projects in Nepal, using long-term time series remote sensing satellite imagery from 1988 to 2020. Our analysis shows an expansion of the surface water content area over time, attributed mainly to high sedimentation deposition owing to multiple factors. This study has identified an urgent need for addressing the following two key contributory factors through an effective control mechanism to avoid rapid sedimentation in the reservoirs: natural—landslides and floods leading to mainly silt deposition during heavy rainfalls; and anthropogenic—road construction materials dumped directly in the reservoir. Effective implementation of a remote sensing monitoring scheme can safeguard future damages to dam environments of more recently built storage-type hydropower projects.