Texture Blocks Research Articles

The Guiding Role of Humanistic Spirit in Sittes Urban Design Philosophy in Protecting Historical Districts A Case Study of Qingdao Guantao Road Historical and Cultural District

The basic block texture and design principles of historical preservation districts in Qingdao originate from the urban design carried out during the German colonial period in Qingdao, and the urban design during the German colonial period was mainly guided by the Sittes urban design philosophy prevalent in the West in the early 20th century. Camillo Sittes urban design philosophy, which adheres to artistic principles, criticizes pure functionality and calls for humanistic spirit, advocates for the harmony between technicality and artistry, and adopts a speculative attitude. This paper will focus on analyzing the significant importance of its humanistic spirit in urban design and its application in guiding the protection and renewal of historical districts in Qingdao.

MENINGKATKAN KEMAMPUAN MOTORIK HALUS ANAK KELOMPOK A MELALUI PERMAINAN SUSUN BALOK BERTEKSTUR DI PAUD AL-FIRDAUS KARENG KIDUL WONOMERTO PROBOLINGGO

This research indicates that the consistent application of textured block games has a positive impact on enhancing the fine motor skills of children in the PAUD AL-FIRDAUS Kareng Kidul Wonomerto Probolinggo group. Utilizing the Classroom Action Research (PTK) method with 22 subjects aged 4-5 years, the study reveals a significant improvement in fine motor skills with the implementation of textured block games. In the pre-cycle, 28% of the 22 children showed improvement. In cycle I, the first meeting, 50% of the 22 children demonstrated an increase in fine motor skills, and in cycle II, the second meeting, 80.2% of the 22 children exhibited even higher improvement. The research concludes that playing with textured blocks is effective in enhancing children's fine motor skills, making it a potential model for improving fine motor skills in young children. The implications of this research can guide educators in PAUD to design learning activities that stimulate and enhance children's fine motor skills. Keywords: textured block play, fine motor skills

Effect of varying sand percentage in sheath of nature-based capillary barriers composite on water storage capacity and okra growth in arid climate

Agricultural development in many arid countries including Oman is limited due to water scarcity which is currently exacerbated with increasing demand due to rapid population growth, economic development, and mismanagement of water resources. Impact of climate change is expected to adversely impact the water resources. Therefore, finding new efficient, environmentally friendly, and affordable water-saving techniques in agronomy is a necessity for achieving agricultural sustainability. Irrigation water can be saved by creating capillary barriers (CB) to unsaturated moisture flow. In this study, a “nature-inspired capillary barrier design” called hereafter as Smart Capillary Barrier (SCB) (mosaic of fine textured blocks, made of silt loam, and sandy sheath surrounding the blocks) was tested in series of field experiments with soil columns and pots. We investigated the effect of the percentage of sand of the sheath on water storage capacity of the SCB blocks and growth of okra (Abelmoschus esculentus L.) under deficit irrigation. Three proportions of sand to silt loam (sand%:silt loam%) in the sheaths were used in this study, SCB-25 (25:75%), SCB-50 (50:50%) and SCB-75 (75:25%). Our results show that increasing the percentage of sand in the designed and constructed SCB composite reduces evaporative and drainage water losses and therefore increases the water storage capacity of the blocks. Our SCB-75 attains 1.7–1.3 smaller drying rate than that for SCB-25 and SCB-50, respectively. Therefore, this composite had higher water saving capacity than a homogeneous soil (no capillary barrier) and a soil with a standard sand mulch (coarse soil overlies fine soil). The study found that using SCB composite did not consistently have a clear effect on the growth of okra plants at all stages of their development. However, during the development stage, using SCB-75 resulted in significantly higher dry biomass of the plants compared to using a homogeneous soil (the control). Additionally, during the initial stage of fruit yield, using SCB-75 also resulted in significantly higher fruit yield compared to using a homogeneous soil. Application of our SCB composite is a promising approach for saving water in desertic farming.

Seismic random noise attenuation using DnCNN with stratigraphic dip constraint

Abstract In this paper, a method for seismic random noise detection and suppression using a denoising convolutional neural network (DnCNN) is presented. Thanks to the residual learning and batch normalization, deep learning networks can converge faster, the gradient descent and disappearance due to the increase of network layers are solved, and the residual results can be predicted more accurately. For seismic data, the variance estimation method is useful for obtaining an accurate noise distribution model and statistical parameters that provide a useful assessment of the noise level. With the variance estimation method based on weak texture blocks, a noise distribution model and statistical parameters can be derived with high accuracy, and this method effectively estimates seismic noise levels. The DnCNN networks are trained, and non-Gaussian noise reduction technology is used to achieve blind noise reduction at unknown levels, improving the noise reduction of seismic data. In addition, stratigraphic dip characteristics related to layer structure are used as DnCNN training network constraints to prevent effective signals in seismic data from being corrupted by conventional DnCNN noise reduction methods. Geological features such as faults and fracture-cavities can be effectively protected. Carbonate faults in the Tarim Basin in China are affected by the desert surface and the depth at which reservoirs are buried. The seismic data has a low signal-to-noise ratio, and the effective signals of the reservoir are low resolution. The seismic data can be effectively enhanced with this method for noise reduction in this area, the fracture-cavity is effectively displayed, and the fault features are also highlighted.

PELATIHAN PEMBUATAN PAVING BLOCK TEXTURE SEAMLESS BAGI PEMUDA DESA MESJID PEUNTEUT KOTA LHOKSEUMAWE

Youth dropping out of school in Mesjid Peunteut Village, Blang Mangat District, Lhokseumawe City as a partner village were still less productive and have an impact on low income levels. In fact, they have never received training from any party for entrepreneurial activities and have the expertise to create certain products, especially in the field of civil engineering. This training aimed to provide knowledge and skills to out-of-school youth in order to provide them with the expertise to make seamless texture paving block products that are easy to market so as to generate a steady income. The number of participants involved in the activity were 20 people, consisted of 8 women and 12 men with an age range of 20 - 25 years. Partners acquired theoretical knowledge, technical skills in making paving block texture seamless manual products, production management and product marketing. The offline method was used for theoretical debriefing activities combined with presentation techniques in class and hands-on practice in civil engineering workshops. The results of the training obtained an average value of theoretical understanding of 88.1 and technical understanding of 95. This showed partners have acquired theoretical and technical knowledge to plan mix compositions, manufacture products manually, arrange production and marketing costs. Thus, it becomes a job field for youth who drop out of school to get a steady income.

Adaptive HEVC video steganography based on distortion compensation optimization

With the development of digital video communication, the steganography based on H.265/HEVC has attracted more and more attention. Because of higher security and better compatibility, the traditional video steganography often used quantized discrete cosine transform (QDCT) or quantized discrete sine transform (QDST) coefficients to embed secret messages. However, the QDCT/QDST-based steganographic methods will cause distortion drift seriously. Although the distortion compensation optimization method can eliminate the intra-frame distortion drift, it ignored the influence of inter-frame distortion. This limitation prompts authors to propose an adaptive HEVC steganography, which eliminates the intra-frame distortion drift while reducing inter-frame distortion. First, the distortion of intra-block and inter-block is analyzed with the prediction and transform process. Then, the corresponding embedding influence is defined, which includes intra-block distortion, inter-frame distortion accumulation, the block texture complexity and the cost of coefficient groups. Finally, the proposed adaptive cost function is designed based on the above definition and the syndrome trellis codes (STC) is used for embedding. The experimental results show that the proposed method has better performance compared with the state-of-the-art coefficient-based steganography in visual quality, bit rate increment and anti-steganalysis.

Super diffraction limit spectral imaging detection and material type identification of distant space objects.

The image information of distant objects shows a diffuse speckle pattern due to diffraction limit, non-uniform scattering, etc., which is difficult to achieve object discrimination. In this study, we have developed a staring spectral video imaging system mounted on a ground-based telescope observation platform to detect the high orbit space objects and gain their spectral images for six groups of GEO targets. The speckle remains basically the same characteristic as the projection structure of the object due to "the balloon inflation phenomenon of near parallel light during long-distance atmospheric transmission" under the premise of considering the bi-directional reflection distribution function (BRDF), Rayleigh scattering theory, and the memory effect. Based on this phenomenon, a mathematical model of remote target scattering spectrum imaging is established where the speckle can be treated as both a global speckle and speckle combination of texture blocks caused by various components of the target. The radial basis function (RBF) neural network is separately used to invert the global speckle and the speckle combination of the texture blocks on account of the typical target material database. The results show that the target materials are of relatively fewer kinds in the global inversion with only including gallium arsenide panel (GaAs) and carbon fiber (CF), for which the highest goodness of curve fitting is only 77.97. An improved algorithm makes their goodness of fit reach 90.29 and 93.33, respectively, in view of one conjecture that the target surface contains unknown materials. The spectral inversion result of the texture blocks shows that the types of materials in each target texture block increase significantly, and that the area ratio of different materials inverted in the block is different from each other. It is further confirmed that the speckle image contains the overall projection structure of distant target and the spectral image projection of each component is relatively fixed, which is the result of the comprehensive action of various mechanisms of ultra-long-haul atmospheric transmission and optical system focusing imaging after BRDF spectral scattering. The spectral image fine inversion is expected to restore the clear structure of the target. This discovery provides important support for the remote imaging and identification of distant and ultra-diffractive targets.

Computational Application on English Translation System Based on Intelligent Image Text Recognition

This work offers an enhanced intelligent picture text recognition algorithm based on the intelligent image text recognition method to increase the impact of English image text translation. Texture blocks of adaptable size are used to successfully increase the accuracy and efficiency of restoration due to the varying texture information present in various photos. Furthermore, the repair sequence is altered as a result of the improved priority calculation algorithm, and the weight of the structural information is enhanced at the same time. In addition, in order to reduce the overall structural complexity and calculation amount of the system, the gated loop unit is also selected as the RNN structure. Finally, this article constructs an English translation system based on intelligent image text recognition according to the requirements of intelligent image text recognition and designs experiments to evaluate the performance of the system constructed in this article. The experimental statistical results show that the English translation system constructed in this article can basically meet the needs of English image text recognition.

Activity-Based Block Partitioning Decision Method for Versatile Video Coding

Versatile Video Coding (VVC), the latest international video coding standard, has more than twice the compression performance of High-Efficiency Video Coding (HEVC) through adopting various coding techniques. The multi-type tree (MTT) block structure offers more advanced flexible block partitioning by allowing the binary tree (BT) and ternary tree (TT) structures, as well as the quadtree (QT) structure. Because VVC selects the optimal block partition by performing encoding on all possible CU partitions, the encoding complexity increases enormously. In this paper, we observe the relationship between block partitions and activity that indicates block texture complexity. Based on experimental observations, we propose an activity-based fast block partitioning decision method to reduce the encoding complexity. The proposed method uses only information of the current block without using the information of neighboring or upper blocks, and also minimizes the dependency on QP. For these reasons, the proposed algorithm is simple and parallelizable. In addition, by utilizing the gradient calculation used in VVC’s ALF, a VVC-friendly fast algorithm was designed. The proposed method consists of two-step decision-making processes. The first step terminates the block partitioning early based on observed posterior probability through the relationship between the block size and activity per sample. Next, the sub-activities of the current block are used to determine the type and direction of partitioning. The experimental results show that in the all-intra configuration, the proposed method can reduce the encoding time of the VVC test model (VTM) by up to 45.15% with 2.80% BD-rate loss.

Implementation of manifold coverage for 3D rock fracture network modeling and its application in rock permeability prediction

Fracture network modeling is an important prerequisite for studies on rock mechanical behaviors and permeability properties. At present, fracture patterns in most discrete fracture network (DFN) models are expressed by Euclidean geometries, which leads to distortion in describing complex fractured rocks. In order to solve this problem, a block texture synthesis method is proposed in this paper to generate multi-resolution two-dimensional (2D) DFN models for fractured coal. The results show that the generated multi-resolution 2D DFN models largely retain the fracture texture structure in the original exemplar. In addition, the concept of manifold coverage is adopted to optimize the 2D fracture image, and the three-dimensional (3D) texture-based DFN models are generated by the solid texture synthesis method from the optimized image. The results indicate that the 3D texture-based DFN models have good fidelity of natural fractures in fracture sets, orientation, density, roughness, fluctuation, aperture and connectivity from the perspective of geometric appearance. Comparison between the 3D DFN model with texture coverage and random coverage shows good consistency in fracture proportion, geometric pattern, and permeability properties. Therefore, the 3D DFN models based on random coverage provide a new idea for modeling fractured rocks and lattice models in numerical simulation of rock mechanical behaviors and permeability properties by various methods, such as RFPA2D/3D, FLAC2D/3D, and Lattice Boltzmann Method (LBM).

Encoding data into metal alloys using laser powder bed fusion

Beyond near-net shape manufacturing of parts with complex geometry, additive manufacturing (AM) makes it possible to fabricate materials with distinct, site-specific microstructures. This ability is unique to AM and enables the design of architected materials that were previously unattainable. Here, we leverage this strategy to encode data into metal parts using the microstructure as the medium to store information. We use a novel laser scanning technique to control the local solidification conditions during laser powder bed fusion and embed a linear barcode and Quick Response (QR) code into stainless steel 316 L. The codes use blocks of different crystallographic texture–i.e., regions in which the crystal lattice of most grains is aligned towards a preferred orientation–as the data “bits”. The data may be retrieved by analytical techniques that are sensitive to local microstructure variations. As a demonstration, we decode the barcodes by measuring the scattering of optical light from their etched surface using a technique called directional reflectance microscopy. The resulting texture maps are readable by conventional barcode scanners, such as those found on mobile phones. The ability to embed data has significant potential in fields such as law enforcement, biomedicine, and transportation, where permanent, damage-resistant tracking is essential.

A novel method for modeling the 3D discrete fracture network from a single 2D exemplar

Fracture network modeling is an important prerequisite for studying many rock mechanics and permeability topics. At present, the fracture morphology in the most discrete fracture network (DFN) models is expressed by Euclidean geometries. In order to improve the accuracy of natural fracture description, this paper proposes using the block texture synthesis method to generate large-scale models of 2D fractured coal rock. The results show that these large-scale models remain the original texture or fracture structures from the exemplars. In addition, this paper presents using the idea of physical cover to transform exemplar that is used to generate 3D DFN models. The results show that the fracture density of the 3D DFN model generated by uncovered fracture structures is low. In contrast, the fracture structures with texture or random coverage can generate high-quality 3D DFN models. Furthermore, compared with the traditional DFN model, the texture-based DFN model has an excellent restoration of natural fractures in orientation, roughness, fluctuation, aperture, density, and connectivity. Therefore, the texture-based DFN method can provide a new idea for constructing 3D DFN models.

IMAGE CONVERTER BASED ON BLOCK COMPRESSION ALGORITHMS OF DXT1, DXT3 AND DXT5 TEXTURES

This article analyzes the existing applications that implement block texture compression algorithms. Based on it, the most optimal variant of technical implementation is introduced. A set of technologies for the implementation of the prototype is selected and substantiated and its architecture is developed on the basis of the principles that ensure the maximum extensibility and purity of the code. With the development of technology and the integration of computerized systems into all possible areas of human activity, more and more software with three-dimensional graphics is being used. Such programs have long since ceased to be used only in the entertainment field for tasks such as computer game development or special effects for cinema. Now with their help doctors can plan the most complex operations, architects check the developed plans of constructions and engineers to model prototypes without use of any materials. On the one hand, such a rapid increase can be explained by the increase in the power of components for personal computers. For example, modern graphics processors, which play a key role in the operation of graphics software, have become much faster in recent decades and have increased their memory hundreds of times. However, no matter how many resources the system has, the question of their efficient use still remains. It is to solve this problem that block texture compression algorithms have been created. In fact, they made it possible to create effective software when computer resources were still quite limited. And with increasing resources allowed to develop software with an incredible level of detail of the models, which led to its active implementation in such demanding areas as medicine, construction and more. The end result of this work is a developed application that takes into account the modern needs of the user. During the development, the most modern technologies were used for the highest speed and relevance of the application. The main advantages and disadvantages of existing solutions were also taken into account during the development. The capabilities of the system were tested using manual testing on a local machine.

Оптические свойства квазиобъемных кристаллов нитрида галлия со структурой высокоориентированной текстуры

The results of a study of the optical properties of gallium nitride samples with a highly oriented texture structure grown without the use of traditional semiconductor or sapphire substrates are presented. It is shown that the stacking faults contained in the GaN blocks of the texture of the studied material are self-organized heteropolytype nanostructures, and that the effective luminescence in the ultraviolet spectral region associated with stacking faults I1 in the basal plane is determined by optical transitions of excitons localized near such natural defects in the single-crystalline bulk of the blocks of the GaN texture.

Deep Learning Model for Cell Nuclei Segmentation and Lymphocyte Identification in Whole Slide Histology Images

Anti-cancer immunotherapy dramatically changes the clinical management of many types of tumours towards less harmful and more personalized treatment plans than conventional chemotherapy or radiation. Precise analysis of the spatial distribution of immune cells in the tumourous tissue is necessary to select patients that would best respond to the treatment. Here, we introduce a deep learning-based workflow for cell nuclei segmentation and subsequent immune cell identification in routine diagnostic images. We applied our workflow on a set of hematoxylin and eosin (H&E) stained breast cancer and colorectal cancer tissue images to detect tumour-infiltrating lymphocytes. Firstly, to segment all nuclei in the tissue, we applied the multiple-image input layer architecture (Micro-Net, Dice coefficient (DC) $0.79\pm 0.02$). We supplemented the Micro-Net with an introduced texture block to increase segmentation accuracy (DC = $0.80\pm 0.02$). We preserved the shallow architecture of the segmentation network with only 280 K trainable parameters (e.g. U-net with ∼1900 K parameters, DC = $0.78\pm 0.03$). Subsequently, we added an active contour layer to the ground truth images to further increase the performance (DC = $0.81\pm 0.02$). Secondly, to discriminate lymphocytes from the set of all segmented nuclei, we explored multilayer perceptron and achieved a 0.70 classification f-score. Remarkably, the binary classification of segmented nuclei was significantly improved (f-score = 0.80) by colour normalization. To inspect model generalization, we have evaluated trained models on a public dataset that was not put to use during training. We conclude that the proposed workflow achieved promising results and, with little effort, can be employed in multi-class nuclei segmentation and identification tasks.

Noise Intensity Estimation Method Based on PCA and Weak Textured Block Selection for Neutron Image

Noise intensity estimation has a very important application in image denoising. In image processing, the denoising method can achieve an ideal denoising effect under the assumption that the Gaussian noise intensity in the image is known. But in real denoising applications, especially the neutron image, the noise level is unknown, which will greatly affect the denoising effect of neutron image processing. In this paper, a method which combined the principal component analysis with weak texture block selection is proposed for noise intensity estimation of neutron images. The experimental results show that the proposed method can accurately estimate the Gaussian noise in the neutron image. Compared with the existing noise intensity estimation methods, the qualitative and quantitative results show that the proposed method has higher accuracy and stability.

WSMN: An optimized multipurpose blind watermarking in Shearlet domain using MLP and NSGA-II

Digital watermarking is a remarkable issue in the field of information security to avoid the misuse of images in multimedia networks. Although access to unauthorized persons can be prevented through cryptography, it cannot be simultaneously used for copyright protection or content authentication with the preservation of image integrity. Hence, this paper presents an optimized multipurpose blind watermarking in the Shearlet domain with the help of smart algorithms, including MLP and NSGA-II. In this method, four copies of the robust copyright logo are embedded in the approximate coefficients of Shearlet by using an effective quantization technique. Furthermore, an embedded random sequence as a semi-fragile authentication mark is effectively extracted from details by the neural network. Due to performing an effective optimization algorithm for selecting optimum embedding thresholds and also distinguishing the texture of blocks, the imperceptibility and robustness have been preserved. The experimental results reveal the superiority of scheme with regard to the quality of watermarked images and robustness against hybrid attacks over other state-of-the-art schemes. The average PSNR and SSIM of the dual watermarked images are 38 dB and 0.95, respectively; Besides, it can effectively extract the copyright logo and locates forgery regions under severe attacks with satisfactory accuracy.

Microstructure analysis of epitaxial BaTiO3 thin films on SrTiO3-buffered Si: Strain and dislocation density quantification using HRXRD methods

Barium titanate (BTO) is a promising perovskite-like material, exhibiting interesting functionalities, such as ferroelectricity, piezoelectricity, high dielectric constant, and electrooptic coefficients. All these properties are closely related to the orientation, density of linear defects and the stability of the tetragonal phase, which depends in turn on its fabrication conditions.High-vacuum Chemical Vapor Deposition (HVCVD) is a method allowing to deposit epitaxial BTO thin films on suitable substrates. In this study, we correlate the microstructure of BTO thin films to the Ba and Ti precursors flow parameters applied in the HVCVD process. In particular, strain, texture, and mosaicity of the crystalline blocks of BTO are investigated in both out-of-plane and in-plane orientation to assess the epitaxial relationships and the crystalline quality. The size of the BTO crystalline domains that scatter the X-ray radiation coherently is calculated using three methods. The mosaicity of the films has been correlated to the concentration of line defects. The value of the screw-type dislocations density has been derived and we discuss its close relationship with the coating deposition conditions.

The Method to Add Sky Background in 3D Virtual Engine

In GTENG engine, scene manager is used to establish the corresponding mesh nodes of skybox or sky hemisphere, and sky texture files are set up in the order of the built-in texture name. These sky texture files are placed in the directory that can be searched by state manager, and they can be called when using to generate sky background. This paper gives the general process of creating skybox and sky hemisphere. By classifying and defining the outer, inner and cloud layer of skybox, the composition of their texture files is explained. Further, the general procedure of making skybox texture by using Terragen software is discussed. The methods of making outer and inner sky texture are illustrated, including setting and adjusting atmosphere, light, water, camera, coordinate, rendering and texture block. The application shows that it is a very effective and connvenient method to add sky background in GTENG engine cooperating with Terragen software to create skybox texture, and the effect of sky background in the application of 3D visual simulation is realistic.

High-Capacity Constructive Steganography Using Optimal Texture Block Synthesis

In this paper, we design a new high-capacity constructive steganographic scheme by optimal texture image block synthesis. First, original texture pattern is divided into multiple seed patches, which are hashed into a blank stego pattern by the key. Furthermore, we employ generated seed patches to reconstruct a candidate pattern, which is scanned by sliding window to generate a series of candidate texture blocks. Subsequently, we sort these candidate texture blocks and select the appropriate ones that their serial number equals to the secret messages to achieve information hiding. After theses texture blocks containing secret messages are hashed into the stego pattern by the key, the remaining positions of stego pattern are sequentially filled with the optimal candidate texture patches by calculating the least square error. Finally, the stego pattern is completely synthesized as the constructive stego image. Compared with the existing schemes, our proposed scheme has a significant high embedding capacity, while keeping a higher visual quality of stego images.