Level Of Detail Research Articles

Possibility of Substitution of LOD1 Data for LOD2 Data on Photovoltaic Potential Estimation at City Districts Level Using a 3D City Model

Abstract. We developed a system to estimate the photovoltaic (PV) potential of urban buildings using a 3D city model at level of detail 2 (LOD2), considering an arrangement of solar panels. Although the PV potential estimation of buildings at the level of city districts prefers LOD2 data, many urban city districts with buildings capable of installing solar panels on façades do not have LOD2 data owing to the high production cost of LOD2 data. Therefore, we investigated the possibility of utilising LOD1 data instead of LOD2 data in the PV potential estimation of buildings at the level of city districts. We conducted an experiment in the investigation using 3D city model data from 24 city districts, which are most of the large cities with LOD2 data in Japan. The experiment results suggest that LOD1 would not be a substitute for LOD2 data in the PV potential estimation of building roofs. The cause of the inadaptability is that most roofs in LOD2 buildings have more small polygons than LOD1 building roofs. Roofs of a LOD2 building with many small polygons have fewer solar panels than roofs of a LOD1 building with a large polygon. On the contrary, the experiment results indicate that LOD1 may be a substitute directly for LOD2 in the PV potential estimation of building façades that are expected to be used as a mounting platform for solar panels in urban buildings from now on. The average of the relative differences in the calculated PV potential of building façades between using LOD1 data and using LOD2 data is approximately 10% in the experiment.

A method to integrate hydraulic structure models into 3D terrain models for irrigation infrastructure visualization

Seamless integration of three-dimensional (3D) terrain models and hydraulic structure models is a technical challenge in the construction of 3D virtual scenes for irrigation areas. This study proposes a level-of-detail (LOD)-based dynamic classification integration method for hydraulic structure models and 3D terrain models, called CM-D-LOD. Hydraulic structures are classified according to their point, line, and surface morphologies, as well as their dependence on or independence of the terrain into four categories: point-like hydraulic structures independent of terrain, line-like hydraulic structures dependent on terrain, surface-like hydraulic structures dependent on terrain, and surface-like hydraulic structures independent of terrain. By utilizing the proposed model classification integration method, a visualization management platform for virtual geographical environments of irrigation areas is developed, and experiments are conducted in the Zhuluo Ba Irrigation Area within the large economic zone along China’s eastern coast. Results demonstrate that the integration accuracy can be controlled between 0.2 and 0.7 m and that the 3D virtual scene of the irrigation area can be updated in real time. The proposed classification integration method transforms the traditional global model integration approach into a more efficient one, significantly improving the efficiency of constructing virtual geographical scenes for irrigation areas.

3D LoD2 modelling of Halong City based on UAV point cloud

3D urban building models are crucial for linking, converging, and integrating economic and social urban data. They are extensively utilized in numerous domains such as smart city development, comprehensive social management, and emergency decision-making. Advanced technologies like affordable UAV (Unmanned Aerial Systems) imagery enable a greater level of automation in data acquisition compared to traditional digital photogrammetry methods. The main objective of this research is to build a 3D LoD2 CityGML model with dense point clouds from UAV images. This study presents a completed workflow for generating 3D CityGML models of the city at LoD2 using UAV data. The use of dense point cloud data from UAV technology in the experimental area has been performed using a DJI Phantom 4 Pro. The original point clouds should be denoised using the statistical outlier remover (SOR), the main goal is to reduce noise while preserving the building's geometry. After that, the point clouds of object features were vectored for the level of detail 2 (LoD2) of the object's 3D volume corresponding to its actual height, and objects belonging to the Feature Class 3D layer will represent LoD2 on SketchUp Pro 2021 software to generate a highly accurate 3D model. The evaluation results show that the square errors calculated from the test points for the three axes X, Y, Z are 1.4 cm, 1.6 cm, 1.7 cm, respectively. Conducting research to choose the UAV photography method aims to offer an efficient and cost-effective solution, saving time and human resources, to address the 3D mapping challenges in urban areas across Vietnam.

Efficient and Robust From-Point Visibility.

This article presents two from-point visibility algorithms: one aggressive and one exact. The aggressive algorithm efficiently computes a nearly complete visible set, with the guarantee of finding all triangles of a front surface, no matter how small their image footprint. The exact algorithm starts from the aggressive visible set and finds the remaining visible triangles efficiently and robustly. The algorithms are based on the idea of generalizing the set of sampling locations defined by the pixels of an image. Starting from a conventional image with one sampling location at each pixel center, the aggressive algorithm adds sampling locations to make sure that a triangle is sampled at all the pixels it touches. Thereby, the aggressive algorithm finds all triangles that are completely visible at a pixel regardless of geometric level of detail, distance from viewpoint, or view direction. The exact algorithm builds an initial visibility subdivision from the aggressive visible set, which it then uses to find most of the hidden triangles. The triangles whose visibility status is yet to be determined are processed iteratively, with the help of additional sampling locations. Since the initial visible set is almost complete, and since each additional sampling location finds a new visible triangle, the algorithm converges in a few iterations.

A Hierarchical 3D Gaussian Representation for Real-Time Rendering of Very Large Datasets

Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering inevitably limit the size of the captured scenes that can be represented with good visual quality. We introduce a hierarchy of 3D Gaussians that preserves visual quality for very large scenes, while offering an efficient Level-of-Detail (LOD) solution for efficient rendering of distant content with effective level selection and smooth transitions between levels. We introduce a divide-and-conquer approach that allows us to train very large scenes in independent chunks. We consolidate the chunks into a hierarchy that can be optimized to further improve visual quality of Gaussians merged into intermediate nodes. Very large captures typically have sparse coverage of the scene, presenting many challenges to the original 3D Gaussian splatting training method; we adapt and regularize training to account for these issues. We present a complete solution, that enables real-time rendering of very large scenes and can adapt to available resources thanks to our LOD method. We show results for captured scenes with up to tens of thousands of images with a simple and affordable rig, covering trajectories of up to several kilometers and lasting up to one hour.

Precise photoionisation treatment and hydrodynamic effects in atmospheric modelling of warm and hot Neptunes

Context. Observational breakthroughs in the field of exoplanets in the last decade have motivated the development of numerous theoretical models, such as those describing atmospheres and mass loss, which is believed to be one of the main drivers of planetary evolution. Aims. We outline for which types of close-in planets in the Neptune-mass range the accurate treatment of photoionisation effects is most relevant, particularly with respect to atmospheric mass loss and the parameters relevant for interpreting observations, such as temperature and ion fraction. Methods. We developed the Cloudy e Hydro Ancora INsieme (CHAIN) model, which combines our 1D hydrodynamic upper atmosphere model with the non-local thermodynamical equilibrium (NLTE) photoionisation and radiative transfer code Cloudy accounting for ionisation, dissociation, detailed atomic level populations, and chemical reactions for all chemical elements up to zinc. The hydro-dynamic code is responsible for describing the outflow, while Cloudy solves the photoionisation and heating of planetary atmospheres. We applied CHAIN to model the upper atmospheres of a range of Neptune-like planets with masses between 1 and 50 M⊕, also varying the orbital parameters. Results. For the majority of warm and hot Neptunes, we find slower and denser outflows, with lower ion fractions, compared to the predictions of the hydrodynamic model alone. Furthermore, we find significantly different temperature profiles between CHAIN and the hydrodynamic model alone, though the peak values are similar for similar atmospheric compositions. The mass-loss rates predicted by CHAIN are higher for hot strongly irradiated planets and lower for more moderate planets. All differences between the two models are strongly correlated with the amount of high-energy irradiation. Finally, we find that the hydrodynamic effects significantly impact ionisation and heating. Conclusions. The impact of the precise photoionisation treatment provided by Cloudy strongly depends on the system parameters. This suggests that some of the simplifications typically employed in hydrodynamic modelling might lead to systematic errors when studying planetary atmospheres, even at a population-wide level.

Computational characterization of novel nanostructured materials: A case study of NiCl[formula omitted

A computational approach combining dispersion-corrected density functional theory (DFT) and classical molecular dynamics is employed to characterize the geometrical and thermomechanical properties of a recently proposed 2D transition metal dihalide NiCl2. The characterization is performed using a classical interatomic force field whose parameters are determined and verified through the comparison with the results of DFT calculations. The developed force field is used to study the mechanical response, thermal stability, melting and solidification of a NiCl2 monolayer on the atomistic level of detail. The 2D NiCl2 sheet is found to be thermally stable at temperatures below its melting point of ∼695 K. At higher temperatures, several subsequent structural transformations of NiCl2 are observed, namely a transition into a porous 2D sheet and a 1D nanowire. The MD simulations of NiCl2 cooling show that the molten NiCl2 system solidifies into an amorphous porous 2D structure at T∼450 K. The resulting structure has lower cohesive energy with respect to the initial 2D sheet. The computational methodology presented through the case study of NiCl2 can also be utilized to study the properties of other novel 2D materials, including recently synthesized NiO2, NiS2, and NiSe2.

ЭФФЕКТИВНОСТЬ АВТОМАТИЗИРОВАННОГО УПРАВЛЕНИЯ ТРАНСПОРТНЫМИ СРЕДСТВАМИ В ТРАМВАЙНЫХ СИСТЕМАХ

The intellectualization of water transport is accompanied by an expansion of the landscape of threats to transport security, caused by the characteristics and weaknesses of the technologies being introduced, which are the convergence of information and telecommunication technologies, automated and automatic control technologies and artificial intelligence. The peculiarity of these technologies is working with large volumes of information. Violation of the security of information processed in intelligent systems of water transport (illegal access, modification, deletion and similar unauthorized influence) causes a violation of transport security and, as a consequence, the security of critical information infrastructure and the country’s critical infrastructure, national security. Convergent technologies used in intelligent transport systems are characterized by multiple and poorly formalized manifestations of the consequences of threats. The article presents a model for assessing the risks of information security of intelligent water transport systems, based on the methods of the theory of fuzzy sets and fuzzy logic, the use of which makes it possible to take into account the above-mentioned features of the technologies being implemented. The hierarchical structure of the model and the use of fuzzy set theory and fuzzy logic methods make it possible to adapt the model to various risk criteria, types of input data and the level of detail of risk analysis. For the presented model, a methodology for assessing information security risks has been developed and an example of risk calculation is given. The developed model and methodology are intended to build an information security risk management system for autonomous shipping, implementing technologies of hybrid (augmented, extended) intelligence, providing for the use of artificial intelligence controlled by people.

Analytical Framework to Understand the Origins of Methyl Side-Chain Dynamics in Protein Assemblies.

Side-chain motions play an important role in understanding protein structure, dynamics, protein-protein, and protein-ligand interactions. However, our understanding of protein side-chain dynamics is currently limited by the lack of analytical tools. Here, we present a novel analytical framework employing experimental nuclear magnetic resonance (NMR) relaxation measurements at atomic resolution combined with molecular dynamics (MD) simulation to characterize with a high level of detail the methyl side-chain dynamics in insoluble protein assemblies, using amyloid fibrils formed by the prion HET-s. We use MD simulation to interpret experimental results, where rotameric hops, including methyl group rotation and χ1/χ2 rotations, cannot be completely described with a single correlation time but rather sample a broad distribution of correlation times, resulting from continuously changing local structure in the fibril. Backbone motion similarly samples a broad range of correlation times, from ∼100 ps to μs, although resulting from mostly different dynamic processes; nonetheless, we find that the backbone is not fully decoupled from the side-chain motion, where changes in side-chain dynamics influence backbone motion and vice versa. While the complexity of side-chain motion in protein assemblies makes it very challenging to obtain perfect agreement between experiment and simulation, our analytical framework improves the interpretation of experimental dynamics measurements for complex protein assemblies.

The green window view index: automated multi-source visibility analysis for a multi-scale assessment of green window views

ContextProviding accessible urban green spaces is crucial for planning and ensuring healthy, resilient, and sustainable cities. The importance of visually accessible urban green spaces increases due to inner urban development processes.ObjectivesThis article proposes a new index, the Green Window View Index (GWVI) for analyzing and assessing visible vegetation, that promotes an integrated planning of urban green spaces and buildings at different scales and levels. It is defined as the proportion of visible vegetation area in a field of view when looking out of a specific window with a defined distance to the window.MethodsThe method for estimating GWVI consists of three steps: (a) the modeling of the three-dimensional environment, (b) the simulation of the two-dimensional window views using modern rendering engines for three-dimensional graphics, (c) the computation of the GWVI. The method is proposed and tested through a case study of the urban area of Bonn, Germany, using a Digital Terrain Model (DTM), CityGML-based semantic 3D City Model at level of detail (LoD) 2, airborne Light Detection and Ranging (LiDAR) data, and 2D land use data from the official German property cadaster information system (ALKIS).ResultsWith an average processing time of 0.05 s per window view, an average GWVI of 26.00% could be calculated for the entire study area and visualized in both 2D and 3D.ConclusionThe proposed engine generates multi-scale visibility values for various vegetation shapes. These values are intended for use in participatory citizenship and decision-making processes for analysis by architects, real-estate appraisers, investors, and urban as well as landscape planners.

Fault Identification of UHVDC Transmission Based on DF-AD and Ensemble Learning

High-resistance ground faults are difficult to detect with existing ultrahigh voltage direct current (UHVDC) transmission fault detection systems because of their low sensitivity. To address this challenge, a straightforward mathematical method has been proposed for fault detection in UHVDC system based on the downsampling factor (DF) and approximation derivatives (AD). The signals at multiple sampling frequencies were analysed using the DF, and the AD approach was used to generate various levels of detail and approximation coefficients. Initially, the signals were processed with different DF values. The first, second, and third order derivatives of the generated signals were calculated by the AD method. Next, the entropy features of these signals were computed, and the Random Forest-Recursive feature elimination with cross-validation (RF-RFECV) algorithm was used to select a high-quality feature subset. Finally, an ensemble classifier consisting of Light Gradient Boosting Machine (LightGBM), K Nearest Neighbor (KNN), and Naive Bayes (NB) classifiers was utilized to identify UHVDC faults. The MATLAB/Simulink simulation software was used to develop a ±800 kV UHVDC transmission line model and perform simulation experiments with various fault locations and types. Based on the experiments, it has been established that the suggested approach is highly precise in detecting several faults on UHVDC transmission lines. The method is capable of accurately identifying low or high resistance faults, irrespective of their incidence, and is remarkably resistant to transitional resistance. Furthermore, it exhibits excellent performance in identifying faults using a small sample size and is highly reliable.

An ontology‐based rule mapping approach for integrating IFC and CityGML

AbstractBuilding information modeling (BIM) and geographic information system (GIS) are often integrated to achieve more refined urban management. Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) are widely used standards in BIM and GIS. The main problem of the transformation of these two standards lies in the gap between them in geometry and semantics. This article introduces an ontology‐based rule mapping approach, achieving the transformation from IFC to CityGML through coordinate system conversion, geometric expression conversion, and semantic mapping. For semantic mapping, we have designed and established rules, enabling the effective mapping of the IFC model to the CityGML level of detail 0 (LOD0) to LOD4 model based on entities, appearance properties and building properties. To fully demonstrate the entire process, we give a detailed elaboration of the conversion of several IFC models.

Underwater image enhancement by using amalgamation of colour correction, contrast-enhancing and dehazing

Underwater images can be captured either with the help of light waves or sound waves. Images that are taken underwater typically are not of optimum quality as they suffer from issues such as low contrast, blurring of detail, colour distortion, and greenish tones. Several physical processes that take place in the aquatic environment, such as light absorption, refraction, and scattering, are responsible for the existence of such degradation in underwater images. To address these challenges, numerous researchers have put forth a range of cutting-edge techniques for enhancing and restoring such degraded underwater images, with the aim of addressing these issues. These techniques primarily focus on improving visibility and enhancing the level of detail. To achieve this, we propose a method that performs White Balancing in the LAB colour space to remove the bluish-greenish tones present in the image. Next, we enhance the contrast by first converting the RGB image into HSV and HLS colour spaces and then by using the S & V channels in HSV and L & S colour channels in HLS, we apply Contrast Limited Adaptive Histogram Equalization (CLAHE). To control the brightness of the enhanced image, we apply Gamma Correction. Lastly, by using the method Dark Channel Prior (DCP), we separate the image’s red channel from the RGB colour space and perform the dehazing operation to get the final enhanced image. We have conducted a comprehensive qualitative analysis of our proposed approach as well as existing techniques, evaluating them objectively and subjectively through metrics such as peak signal-to-noise ratio (PSNR), root-mean-square error (RMSE), structural similarity (SSIM), and the underwater colour image quality evaluation metric (UCIQE) and underwater image quality measure (UIQM). Since our proposed approach uses traditional image processing methods, it is computationally less expensive and quicker as compared to deep learning or frequency domain-based methods. With this, it can be adapted for using in real-time applications such as underwater navigation, examination of the behavior of marine ecosystems and other scientific research.

Analysis in Making Animation Movements Using Traditional Methods (Keyframe) and Motion Capture Methods

The keyframe method for making 3D animation movements is a traditional technique used by animators around the world to create certain animation movements based zon the 12 principles of animation. Meanwhile, motion capture is a motion recording technique used to describe the process of recording movements and interpreting these movements into a digital model. Motion capture itself is commonly used in the military, entertainment, sports, and other fields. In this study, we analyze the use of the two methods, the results of which can be used as a suggestion for the use of the two methods for the production of animated films. Three aspects were used to analyze the two methods, namely the number of keyframes, the level of refinement and detail, the final process and cleanup.
 Keywords: keyframe, motion capture

A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics.

Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 fecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: (i) 20 Gbp of Illumina short-read data, (ii) 40 Gbp of short-read data, (iii) 20 Gbp of PacBio HiFi long-read data, and (iv) 40 Gbp of hybrid (20 Gbp of short-read +20 Gbp of long-read) data. No strategy was best for all metrics; instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific and depends on how researchers assess the trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.

Digitally Aided Analysis: A New Reading of the Cloister Vaults at Norwich Cathedral

ABSTRACT This article offers a new approach to analysing the medieval vaults of Norwich cathedral cloister, which at first appearance seem to be of a consistent design, yet detailed inspection and analysis reveals this not to be the case. Whilst previous scholars have recognised the presence of inconsistencies, their focus has been on chronology, patronage as well as the iconographic programme of the extraordinary range of sculpted bosses. Our approach is based on accurate digital surveying and analysis methods and comparison with similar data obtained from other sites. This enables us to understand the design of the cloister vaults in plan, including bay proportions and the nuances of the tierceron star arrangement of ribs. We then employ a representation technique termed the ‘middle plan’ to identify and analyse specific design runs and their breaks in a greater level of detail than previously achieved, including analysis of geometric data to explain different processes that were likely used to create the curvatures of individual ribs. In doing so, we have identified methods not previously described, which reveal the inventiveness of medieval masons faced with a series of complex constructional issues and enabling them to achieve a range of visual effects.

COMPARATIVE STUDY BETWEEN SHELL AND SOLID FINITE ELEMENT MODELS FOR STEEL JOINTS CHARACTERIZATION

AbstractSolid and shell finite element models (FEM) are two commonly used possibilities to analyse the structural behaviour of steel joints. The choice between solid and shell models often comes down to a balance between computational resources and the level of detail required for the study. In this paper, a set of welded beam‐column joints with hot‐rolled open sections is studied using both modelling techniques. The joints' behaviour is assessed in terms of resistance and initial stiffness. An improved shell FEM is proposed. The results indicate that for the studied dataset, both techniques return comparable results. Hence, the use of shell FEM seems to be a possible alternative to solid FEM and can be efficiently used for the joint characterization.

Recent molecular techniques to strengthen ecological studies in echinoderms

Introduction: Echinoderms, an integral component of marine ecosystems worldwide, have captivated scientific interest for centuries. Despite this longstanding attention, comprehending key facets such as trophic relationships, diet composition, and host-microbiota relationships still represents a challenge using traditional techniques. Recent years, however, have witnessed a transformative shift, thanks to the emergence of advanced molecular techniques, offering new approaches to strengthen ecological studies in echinoderms.
 Objective: Explore how recent advancements in molecular tools have impacted ecological research on echinoderms. Specifically, we aim to investigate the potential of these tools to shed light on trophic interactions, diet composition, and the characterization of gut microbial communities in these organisms.
 Methods: Available literature was used to clarify how novel molecular techniques can improve ecological studies. The focus is diet, trophic relationships, and gut microbiota.
 Results: Traditionally, studies of stomach contents using compound microscopy have provided an idea of ingested material; nevertheless, sometimes a simple magnified visualization of dietary content does not allow exhaustive identification of the entire food spectrum, as it is limited due to the rapid digestion and maceration of food items within the echinoderm’s digestive tract. The use of DNA-metabarcoding, targeting specific DNA regions, such as the mitochondrial COI gene, has allowed us to enhance the accuracy and precision of diet characterization by enabling the identification of prey items down to the species or even genetic variant level, providing valuable insights into specific dietary preferences. Another approach is the use of stable isotopes, particularly carbon and nitrogen, which provide a powerful tool to trace the origin and flow of nutrients through food webs. By analyzing the isotopic signatures in muscular tissues and food items, we can discern the sources of their primary food items and gain insights into their trophic position within the ecosystem. Lastly, a third new technique used to elucidate the characterization of the prokaryotic community is 16S rRNA sequencing. This method allows us to explore the composition and dynamics of the digestive tract microbial communities.
 Conclusions: This is a promising era for ecological research on echinoderms, where advances of molecular tools have enabled an unprecedented level of detail, resolving longstanding challenges in comprehending their trophic interactions, diet composition, and host-microbiota relationships, and opening new avenues of investigation in ecological studies.

Systematic Design of a Natural Sciences Collections Digitisation Dashboard

This paper describes the design and build of a pilot Natural Sciences Collections Digitisation Dashboard (CDD). The CDD will become a key service for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo) and aims to improve the discoverability of natural science collections (NSCs) held in European institutions, both digitised and undigitised. Furthermore, it will serve as a dynamic visual assessment tool for strategic decision-making, including the prioritisation of digitisation. The CDD pilot includes high-level information from nine European NSCs, covering the number of objects, taxonomic scope, storage type, chronostratigraphy (Earth Science Collections), geographical region and level of detail in digitisation. This information is structured through a standardised Collection Classification Scheme, which uses high-level categorisation to describe physical natural science collections.

Beyond Catalogue Life calculation in Solving Bearing related Failures in Steel Plant

Abstract: This technical paper explains an approach of solving problems related to bearing failures in steel industry by working beyond catalogue calculation using conventional as well as speciality software. Bearing manufacturing companies usually publish a detailed method of L10 life calculation in their catalogue based on international standards as well their own. Whereas they conduct more detailed system level calculations using their own advanced software. But those advance calculation are not easily available to engineers working on design from scratch or solving problem of industrial equipment in-house. So called catalogue method of bearing analysis are mostly done for bearings in isolation without considering the effect of surrounding parts as a system. This paper elaborates a couple of examples of calculation beyond catalogue life of bearing using a commercially available software such as KISSOFT by overcoming some of the constraints in catalogue approach and extends engineers’ capability to carry out more realistic analysis of bearing failures and devise a solution with better predictability of success. In this paper two examples one from general steel plant applications and another from gearbox, have been explained to guide design, application and maintenance engineers across industrial domain to critically think beyond hand calculation and bring in more systematic and prediction based approach for bearing related problems