Essential Objects Research Articles

The Influence of Land Subsidence on Risk of Constructing 150 kV Transmission Tower for South Sumatra – Bangka Belitung Interconnector

Transmission system is one of the national essential objects and should be reliable when functioning. Moreover, disturbances in transmission system can lead to disruption of the service function. A common risk to the reliability of electric distribution is land subsidence on transmission tower. Furthermore, the 150 KV interconnector of South Sumatra-Bangka Belitung (Sumsel-Babel) is located in the coastal area of Banyuasin Dua sub-district, South Sumatra. This area is a river delta with peat and clay soil structures and is prone to land subsidence. Therefore, this research aimed to identify environmental factors that affect land subsidence and cause risk to transmission tower. In the context of this research, Copras (Complex Proportional Assessment) and MCSA (Multi Criteria Spatial Analysis) were used for parameter weighting and risk assessment of tower location, respectively. The results of an expert survey to assess risk of potential land subsidence at tower location showed five parameters, namely, land use, distance to waters or potential flooding, land slope factor, soil type, and conus value. Individual parameters were weighted quantitatively and qualitatively based on the opinions of construction experts. Specifically, the qualitative method was performed by weighting based on criteria and sub-criteria, which were analyzed using Analytic Hierarchy Process (AHP). On the other hand, spatial analysis of locations at risk of land subsidence was conducted using GIS software. Based on the assessment results obtained, land use criteria had the largest weighting influence of 0.340 and the smallest weighting on the cone value was 0.08. Finally, tower location that are most at risk of land subsidence are on peatland, near water, and clay soil.

Renewable methanol production based on in situ synergistic utilization of excavated waste and landfill gas: life cycle techno-environmental-economic analysis

Excavated waste (EW) and landfill gas (LFG), as the two main landfill products, are essential objects of Enhanced landfill mining (ELFM). In this study, for the in situ synergistic utilization of LFG and the residue-derived fuel (RDF) from EW, an RDF-LFG to methanol (MeOH) unit with high exergy efficiency and low carbon emission is proposed. Then, to evaluate the environmental impacts and economic feasibility comprehensively, the life cycle assessment (LCA) and life cycle cost (LCC) are conducted on the EW-LFG to MeOH system based on the Aspen Plus simulation data of the RDF-LFG to MeOH unit. The system using EW landfilled in 2005 & 2015 as feedstocks are named Scheme A & B, respectively. The results show that both schemes have an exergy efficiency of more than 70 %. Regarding environmental impacts, RDF-LFG to MeOH, EW pretreatment, Storage and transport of products, and EW Mining are the main contributors. This study pays particular attention to global warming (GW) potential. The direct and indirect carbon emission of the RDF-LFG to MeOH unit are about 35 and 650 kg CO2 eq/ton MeOH, and the life-cycle GW of the EW-LFG to MeOH system is between 707 to 874 kg CO2 eq/ton MeOH. Levelized cost (LC) and levelized profit (LP) are about 452 $/ ton MeOH and 94 $/ton MeOH. With the transformation of the power grid, the decrease in carbon emission factor of power grids can improve both the environmental, and economic performance of the EW-LFG to MeOH system. Methanol selling price, carbon tax and electricity cost are the major sensible factors to the economic feasibility.

Development of a Three-Finger Adaptive Robotic Gripper to Assist Activities of Daily Living.

A significant number of individuals in the United States use assistive devices to enhance their mobility, and a considerable portion of those who depend on such aids require assistance from another individual in performing daily living activities. The introduction of robotic grippers has emerged as a transformative intervention, significantly contributing to the cultivation of independence. However, there are few grippers in the fields, which help with mimicking human hand-like movements (mostly grasping and pinching, with adoptive force control) to grasp and carry objects. Additionally, the data are not available even on how many Activities of Daily Living (ADL) objects they can handle. The goal of the research is to offer a new three-fingered gripper for daily living assistance, which can both grasp and pinch with adaptive force, enabling the capabilities of handling wide-ranging ADL objects with a minimal footprint. It is designed to handle 90 selective essential ADL objects of different shapes (cylindrical, irregular, rectangular, and round), sizes, weights, and textures (smooth, rough, bumpy, and rubbery). The gripper boasts a meticulously engineered yet simple design, facilitating seamless manufacturing through 3D printing technology without compromising its operational efficacy. The gripper extends its functionality beyond conventional grasping, featuring the capability to pinch (such as holding a credit card) and securely hold lightweight objects. Moreover, the gripper is adaptable to grasping various objects with different shapes and weights with controlled forces. In evaluation, the developed gripper went through rigorous load tests and usability tests. The results demonstrated that the users picked and placed 75 objects out of 90 daily objects. The gripper held and manipulated objects with dimensions from 25 mm to 80 mm and up to 2.9 kg. For heavy-weight objects (like books) where the centroid is far apart from the grasping areas, it is difficult to hold them due to high torque. However, objects' textures have no significant effect on grasping performance. Users perceived the simplicity of the gripper. Further investigation is required to assess the utility and longevity of grippers. This study contributes to developing assistive robots designed to enhance object manipulation, thereby improving individuals' independence and overall quality of life.

O consequencialismo na Nova Lei de Licitações e Contratos Administrativos e a Análise Econômica do Direito como ferramenta concretizadora

The New Administrative Bidding and Contracts Law (NLLC) brings pragmatic requirements to the senior management of the public agency or public entity. In particular, it is noted that the most advantageous result to be pursued by the Administration is measured by the concepts of efficiency, efficacy and effectiveness, in accordance with art. 169, §1º of Law No. 14.133/21, which attracts the incidence of consequentialist ethics to the public contracting area. The hypothesis studied, to be evaluated from the perspective of the deductive method, resides in the possibility of using a tool from the Economic Analysis of Law (AED) to give concreteness to the consequentialism present in the NLLC in decisions of the Courts of Auditors, such as Cost-Benefit Analysis (CBA) or Cost-Effectiveness Analysis (CEA). In this context, in which there is greater deference to the practical consequences of administrative decisions to which public managers will be subjected, the issuance of precautionary measures by the Audit Courts has gained new contours, especially regarding the time factor to decide on the merit of the irregularity and, moreover, the definition of how the situation will be resolved in cases of emergency or essential objects, protecting the (infamous) public interest facing possible alternatives.

Criticism of Mustafa Azami's Critical Thoughts in Study of Hadith

The existence and authenticity of hadith have become two of the most essential objects in the discourse of hadith among Muslims, especially after coming into contact with criticism from Orientalists. This article describes explicitly and criticizes Azami's hadith thought in the hadith debate among Orientalists. This research is an analytical descriptive research based on content analysis. The results reveal that Azami can position himself as a critic of the Western thesis by presenting historical data as a basis for his thoughts. The rhythm of the scientific debate modeled on by Western thinkers can be dived into and followed convincingly so that their responses and criticisms reach the Orientalists. Orientalists believe that Azami's criticism has not been able to divert the orientation of the general thesis that hadiths are not historically authentic. Azami's defense still needs convincing, and the arguments are still circular. This model of thinking has yet to satisfy the scientific desires of the Orientalists, so it has a small implications.

Research on the Standardized Management System and Operational Indicators of Water Control Dikes Based on GA-BP Artificial Neural Network Model

Water control dikes, as an important infrastructure for national economic and social development, play an important supporting and guaranteeing role in flood control, irrigation, power generation, water supply, tourism, and other aspects. Jiangxi is a major province in water conservancy, with dense rivers and lakes, and it owns tens of thousands of water control dikes of various types. Most of the water control dikes exhibit structural aging, continuous medical risks, and reduced benefits, which urgently require efficient maintenance and standardized management. Management is a complex task, and the level of management directly affects the functional efficiency and service life of dikes. In view of these issues, this study takes dikes as essential and typical water conservancy engineering objects and analyzes the evaluation criteria of safe production and the demands of engineering management. It establishes an evaluation index system suitable for normalized management. The Analytic Hierarchy Process (AHP) model is utilized to determine indicator weights, and a neural network water conservancy engineering evaluation algorithm is constructed to match the evaluation model. Finally, an improved algorithm for the GA (genetic algorithm)-BP (backpropagation) neural network is proposed, incorporating additional momentum factors and considering adaptive learning rates. The developed model is validated through a case study in Jiangxi, China, and the results demonstrate its accuracy and comprehensiveness in reflecting the actual situation. This research is relevant to designers, contractors, and governments seeking solutions to achieve standardized management in water control dikes.

Legal Responsibility for Environmental Damage Caused by Russian and Ukrainan Wars: International Humanitarian and Criminal Law Perspectives

Not only inflicted human casualities, the war between Russia and Ukraine, also injured the environment. Russia's discriminating attacks on essential objects such as gas, energy, oil, and mining infrastructure become the most significant root cause. UNEP affirmed that the attacks resulted in widespread water, soil and air pollution, as well as a significant deterioration in Ukraine's ecosystem stability. Accordingly, the study intends to examine the framework of international humanitarian and criminal law, specifically in terms of enviromental protection, as well as to analyze accountability before the International Criminal Court. The study employed doctrinal method involving a statutory and conceptual approach. In this case, relevant legal instruments such as the 1949 Geneva Conventions and their Additional Protocols, as well as the Rome Statute, were being examined. Furthermore, the study is also certified by the evolution of legal doctrines in books, jounals, and other credible sources. According to the findings, humanitarian law, which is underpinned by customary international law, protects the environment slightly better than international criminal law. In short, the state bears multiple duties for environmental damage caused by the outbreak of war. Individual accountability before the ICC, on the other hand, is being overlooked. It is due to the Rome Statute's flaws, which include vagueness in the formulation of the articles, stringent standards for proof of environmental damage, and bias in proving mens rea. As a result, improvements in the enforcement of international crimes (war crimes and related types) that cause environmental damage are urgently required

Detection of 3D Object in Point Cloud: Cloud Semantic Segmentation in Lane Marking

Managing a city efficiently and effectively is more important than ever as growing population and economic strain put a strain on infrastructure like transportation and public services like keeping urban green areas clean and maintained. For effective administration, knowledge of the urban setting is essential. Both portable and stationary laser scanners generate 3D point clouds that accurately depict the environment. These data points may be used to infer the state of the roads, buildings, trees, and other important elements involved in this decision-making process. Perhaps they would support "smart" or "smarter" cities in general. Unfortunately, the point clouds do not immediately supply this sort of data. It must be eliminated. This extraction is done either by human specialists or by sophisticated computer programmes that can identify objects. Because the point clouds might represent such large locations, relying on specialists to identify the things may be an unproductive use of time (streets or even whole cities). Automatic or nearly automatic discovery and recognition of essential objects is now possible with the help of object identification software. In this research, In this paper, we describe a unique approach to semantic segmentation of point clouds, based on the usage of contextual point representations to take use of both local and global features within the point cloud. We improve the accuracy of the point's representation by performing a single innovative gated fusion on the point and its neighbours, which incorporates the knowledge from both sets of data and enhances the representation of the point. Following this, we offer a new graph point net module that further develops the improved representation by composing and updating each point's representation inside the local point cloud structure using the graph attention block in real time. Finally, we make advantage of the global structure of the point cloud by using spatial- and channel-wise attention techniques to construct the ensuing semantic label for each point.

Identification of Ecological Restoration Approaches and Effects Based on the OO-CCDC Algorithm in an Ecologically Fragile Region

A full understanding of the patterns, trends, and strategies for long-term ecosystem changes helps decision-makers evaluate the effectiveness of ecological restoration projects. This study identified the ecological restoration approaches on planted forest, natural forest, and natural grassland protection during 2000–2022 based on a developed object-oriented continuous change detection and classification (OO-CCDC) method. Taking the Loess hilly region in the southern Ningxia Hui Autonomous Region, China as a case study, we assessed the ecological effects after protecting forest or grassland automatically and continuously by highlighting the location and change time of positive or negative effects. The results showed that the accuracy of ecological restoration approaches extraction was 90.73%, and the accuracies of the ecological restoration effects were 86.1% in time and 84.4% in space. A detailed evaluation from 2000 to 2022 demonstrated that positive effects peaked in 2013 (1262.69 km2), while the highest negative effects were observed in 2017 (54.54 km2). In total, 94.39% of the planted forests, 99.56% of the natural forest protection, and 62.36% of the grassland protection were in a stable pattern, and 35.37% of the natural grassland displayed positive effects, indicating a proactive role for forest management and ecological restoration in an ecologically fragile region. The negative effects accounted for a small proportion, only 2.41% of the planted forests concentrated in Pengyang County and 2.62% of the natural grassland protection mainly distributed around the farmland in the central-eastern part of the study area. By highlighting regions with positive effects as acceptable references and regions with negative effects as essential conservation objects, this study provides valuable insights for evaluating the effectiveness of the integrated ecological restoration pattern and determining the configuration of ecological restoration measures.

Smart camera placement for building surveillance using OpenBIM and an efficient Bi-level optimization approach

Cameras have been widely used in buildings for safety and efficiency surveillance. Especially with the integration of artificial intelligence and building information modeling (BIM), many intelligent applications have emerged. However, optimizing the camera plan in buildings with various geometric and semantic properties remains challenging. This study proposes a smart camera placement framework that can be generally applied in different building scenarios to solve this problem. Firstly, a camera-integrated BIM is constructed based on a systematic literature review (SLR) and Industry Foundation Classes (IFC) schema, followed by a sample-based voxelization method to convert BIM models to semantic voxels. Secondly, a realistic camera coverage analysis method is developed to consider the object's properties, based on which a bi-level formulation is proposed. Finally, an efficient bi-level genetic algorithm (EBGA) is proposed to ensure both optimization accuracy and efficiency. The performance of the proposed placement framework is validated in a study of a multi-purpose laboratory and office floor. The validation demonstrated that EBGA obtained full coverage of essential objects and 21.4% more coverage values over the experience-based method. Compared with two benchmark GAs, EBGA saved 65.2% and 49.7% of computation time correspondingly in the experiment.

Transdisciplinarity and Boundary Work for Landscape Architecture Scholars

To substantively advance sustainability and equity, landscape architecture scholars must reform our own scholarly norms. To increase the influence of our discipline and offer practitioners and communities more relevant knowledge and tools, we can build on our strong tradition of transdisciplinary work to: 1) more credibly affect and be informed by knowledge in other socio-environmental disciplines that study landscapes and communities, and 2) confront our own “two cultures” problem in which science may be misunderstood as limiting creative excellence. To achieve these aims, I suggest we employ the landscape as a transdisciplinary boundary object—recognizing that all landscapes function within dynamic multiscalar socio-environmental systems, and viewing both commonplace and unique landscapes as essential objects of our scholarship. Doing this presents opportunities for individual scholars to serially specialize in different areas of landscape inquiry, teaching and learning from colleagues and communities throughout our careers, and to be credible leaders of transdisciplinary science. It also offers a conceptual frame for activating boundary work between the two cultures within our own discipline. Importantly, it also helps us to be more fully prepared to teach future practitioners to use landscape science in design and planning, empowering the profession to support communities in advancing sustainability and equity.

Investigating ESL Learners’ Perception and Problem towards Artificial Intelligence (AI) -Assisted English Language Learning and Teaching

The contemporary language learning strategy, Artificial Intelligence (AI) Assisted Language Learning (AI-ALL), incorporates AI-powered applications to support learners' learning activities. Many scholars have been experimenting with AI applications concerning activities relevant to education. The major objectives of this study are 1) The ESL learners' perspectives concerning AI-assisted English language learning and teaching; 2). ESL learners’ problems concerning artificial AI-assisted English language learning and teaching. The present investigation employed a quantitative methodology utilizing survey instruments to accumulate distinct information from 81 engineering stream students including essential primary research objects. A survey with a 5-point Likert Scale was administered to collect the data. According to the study, most of the students had favorable perceptions toward using AI-powered tools, particularly while learning English. The major problem is the lack of quality in AI-powered language-learning apps on smartphones. However, it is envisaged that AI-powered apps in language learning would be deployed as one of the instructional media that might help learners learn English as a Second Language efficiently. The present study recommends further research to investigate thoroughly how experienced language instructors use AI-powered applications in their classrooms to build best practices for utilizing AI in teaching and learning in ESL environments.

Robust Guardrail Instantiation and Trajectory Optimization of Complex Highways Based on Mobile Laser Scanning Point Clouds

As a basic asset of highways, guardrails are essential objects in the digital modeling of highways. Therefore, generating the vectorial 3D trajectory of a guardrail from mobile laser scanning (MLS) point clouds is required for real digital modeling. However, most methods limit straight-line guardrails without considering the continuity and accuracy of the guardrails in turnoff and bend areas; thus, a completed 3D trajectory of a guardrail is not available. We use RANDLA-Net for extracting guardrails as preprocessing of MLS point clouds. We perform a region growth strategy based on linear constraints to obtain correct instantiations and a forward direction. The improved Douglas– Puke algorithm is used to simplify the center points of guardrail, and the 3D trajectory of every guardrail can be vectorized using cubic spline curve fitting. The proposed approach is validated on two 3-km case data sets that can completely instantiate MLS point clouds with remarkable effects. Quantitative evaluations demonstrate that the proposed guardrail instantiation algorithm achieves an overall precision and recall of 98.80% and 97.5%, respectively. The generated 3D trajectory can provide a high-precision design standard for the 3D modeling of the guardrail and has been applied to a long highway scene.

A Major Earthquake and Tsunami in the Gulf of Cadiz in the Sixth Century B.C.? A Review of the Historical, Archaeological, and Geological Evidence

AbstractThis article offers an overview of the published evidence of the possible occurrence of an earthquake and tsunami that, if factual, would have struck the shores of the Gulf of Cadiz sometime in the sixth century B.C. It addresses the oldest literary sources containing accounts of earthquakes and tsunamis in the Iberian peninsula, and their inclusion in the most important seismic catalogs in Spain and Portugal, as well as examining the geoarchaeological evidence of an earthquake and tsunami in the city of Huelva, dating to the first quarter of the sixth century B.C., relating it to geomorphological and sedimentary evidence of extreme wave events in the Gulf of Cadiz in about 2500 B.P. The information provided by Greek authors writing in the fifth and fourth centuries B.C., which depicts the ocean beyond the Strait of Gibraltar as impassable and replete with shallows, might also be an indirect reference to that seismic and high-energy marine event, whose intensity, exact date, and repercussions for the inhabitants of the Gulf of Cadiz are essential objects of research.

Effect of anion structure on the network of hydrogen bonds formed between counter ions in salts composed of triethylamine and derivatives of 2,1-benzothiazine 2,2-dioxide and 1,2-benzoxathiine 2,2-dioxide

The investigated symmetrical bis-adducts, i.e., bis(1-ethyl-4‑hydroxy-2,2-dioxido-1H-2,1-benzothiazin-3-yl)(furan-2-yl/phenyl)methane and bis(4‑hydroxy-2,2-dioxido-2H-1,2-benzoxathiin-3-yl)(furan-2-yl/4-methoxyphenyl)methane, essential objects for pharmacological studies, were found to exist in the liquid and solid phases in a double tautomeric enol form which allows the existence of acid-base interactions related to the proton transfer to the triethylamine and the formation of an intramolecular O―H···O− hydrogen bond between the intact OH group and the enolate O− atom. In the crystal lattice of triethylammonium salts containing 1,2-benzoxathiine 2,2-dioxide moieties in the anion molecules, counter ions are connected by N―H···O hydrogen bonds, in which the enolate O− atom plays the role of a proton acceptor. Whereas in crystals with 2,1-benzothiazine 2,2-dioxide fragments in the anion molecules cation and anion molecules are linked by N—H···O hydrogen bonds, in which the role of a proton acceptor is played by an O atom of a sulphonyl group that belongs to a bicyclic fragment which contains an enolate group. We have shown that the dipole-dipole interactions in the investigated ammonium salts may explain the orientation of the cationic N−H group once to the O− atom of the enolate group, another time to the O atom of the sulfonyl group. The effect of the structure of the anion molecule on the hydrogen bonding network in the crystals studied was analyzed by the X-ray diffraction method, the 1H and 13C NMR technique including COSY, NOESY, HSQC and HMBC two-dimensional patterns, and the Fourier transform infrared (FTIR) spectroscopy. Theoretical analysis of the interactions in the crystals was performed using Density Functional Theory (DFT) and Quantum Theory of Atoms in Molecules (QTAIM).

TIME SERIES MODELING OF NATURAL GAS FUTURE PRICE WITH FUZZY TIME SERIES CHEN, LEE AND TSAUR

Investment is the process of investing money or capital for profit or material results. The investor carefully calculates the investment object to minimize losses and maximize profits. One of the essential investment objects is the futures price of natural gas considered a commodity that plays a vital role in the Indonesian economy. The movement of natural gas futures prices can be modeled using a time series model. The data in the time series model is believed to have particular pattern to model the data in the future. The natural gas futures price is modeled into a time series method by using fuzzy time series (FTS) approach of the FTS Chen, Lee and Tsaur. Model accuracy is calculated using the criteria of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The three FTS methods have good performance of accuracy for this time series data, where FTS Tsaur as fuzzy times series approach with average based method shows the best results with the smallest error rate to the data of natural gas future price.

Student essays as evidential resource in placement meetings

A large body of research from the perspectives of EMCA has examined how documents are used as situated resources to accomplish institutional tasks. Building on this research, our study examines the embodied use of student essays written for a placement test in academic English by a team of trained raters in placement meetings, with a focus on the “sequential particulars” (Day & Mortensen, 2017, p. 132) of the talk and the embodied practices that make the textuality and materiality of the essays consequential for their assessment and, reflexively, for the placement of their author. The evaluative meetings are organized as object-focused interaction in which the raters treat the essays as essential and omnirelevant objects. We show how the essays are mobilized as situated objects in different sequential environments and how the raters, by using the essays in locally specific ways, work towards accomplishing their institutional charge of making a placement decision.

Spatial Semiotics and Landscape Hermeneutics in the Professional Training of Managers of Socio-Cultural Activity

Introduction. Socio-cultural activity managers' training involves students’ mastering and fluent operating the concepts of “cultural landscape” and “semiosphere”, which are used to carry out hermeneutic and semiotic analyses of regional and world culture phenomena. Purpose and methods. The article aims to reveal the main provisions of spatial semiotics and landscape hermeneutics and determine their didactic potential in the context of socio-cultural activity managers' training. Research methods include analyzing cultural, art history, and philosophical literature, theoretical generalization, and synthesis. Results. When analyzing cultural space and cultural phenomena as texts, concepts and terms are used that characterize cultural space as a semiotic system: language, text, metatext, intertextuality, and communication. One of the essential shared objects of spatial semiotics and landscape hermeneutics is the city, the high degree of semioticization determined by such essential features as “doneness” and “artificiality”. Conclusions. Space and culture interact and influence each other. At the same time, spatial categories such as “center”, and “periphery” appear as universal models for describing texts and phenomena of any branch of the cultural sphere. The analysis of landscape and cultural phenomena is carried out according to the parameters of the level of semiotic saturation of the environment; the level of significance of symbolic activity; the intensity of semiotic exchange; level of self-identification.

Origin and Evolution of Dust-obscured Galaxies in Galaxy Mergers

Dust-obscured galaxies (DOGs), which are observationally characterized as faint in the optical and bright in the infrared, are the final stage of galaxy mergers and are essential objects in the evolution of galaxies and active galactic nuclei (AGNs). However, the relationship between the torus-scale gas dynamics around AGNs and the DOGs’ lifetime remains unclear. We obtained the evolution of the spectral energy distributions (SEDs) of a galaxy merger system with AGN feedback from postprocessed pseudo-observations based on an N-body/smoothed particle hydrodynamics (SPH) simulation. We focused on a late-stage merger of two identical galaxies with a supermassive black hole (SMBH) of 108 M ⊙. We found that the infrared luminosity of the system reaches ultra- and hyperluminous infrared galaxy classes (1012 and 1013 L ⊙, respectively). The DOG phase corresponds to a state in which the AGNs are buried in dense gas and dust, with the infrared luminosity exceeding 3.3 × 1012 L ⊙. We also identified subcategories of DOGs, namely bump and power-law DOGs, from the SEDs and their evolution. The bump DOGs tend to evolve to power-law DOGs over several Myrs. We found that contribution from the hot dust around the nucleus in the infrared radiation is essential for identifying the system as a power-law DOG; the gas and dust are distributed nonspherically around the nucleus, therefore, the observed properties of DOGs depend on the viewing angle. In our model, the lifetime of merger-driven DOGs is less than 4 Myr, suggesting that the observed DOG phase is a brief aspect of galaxy mergers.

UAV and TLS point cloud integration for the surface plant infrastructure of underground coal mines

The surface plant infrastructure (SPI) of underground coal mines is one of important sets of underground mines as it includes essential objects, such as office buildings, structures and equipment used to load, receive, sort or process minerals; receive and discharge waste rocks; provide ventilation for tunnels and energy for mining operations. The measurement and collection of spatial data of SPI are important to ensure the safe and effective management and operation of mining activities in underground mines. A rapid development in geospatial technologies has facilitated the acquisition of geospatial data in the mining industry. Unmanned Aerial Vehicle (UAV) photogrammetry and Terrestrial Laser Scanning (TLS) are two of the typical geospatial technologies, which have made significant contributions to the field of geospatial data collection. While UAV photogrammetry allows to create dense point clouds with centimeter - level accuracy in a short time and large areas, TLS technology can produce dense point clouds with millimeter - level accuracy. However, the latter is time - consuming and expensive while performing on a large area. The integration of UAV and TLS data can be seen as a reasonable solution to gain the advantages of both and avoid the disadvantages of each technology. This paper presents the results of an integrated study of point cloud data generated by UAV and TLS for the plant infrastructure of the underground coal mine. Featuring structures in the study area include mineshaft tower, office and factory buildings. The results show that the UAV and TLS integrated point cloud data has millimeter - level accuracy for important objects such as mineshaft towers, while ancillary structures in the study area have centimeter - level accuracy.