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This paper describes a robotic system developed for tiling mosaics based on image processing according to customer expectations.

Many varieties of mosaics art in different forms has been applied manually over centuries for art decorating. Although the mosaics material is cheap with immense decorative potential, the mosaics tiling process is difficult and costly skill to perform. Therefore, an image processing based robotic tiling system has been presented and applied in this study. An algorithm has been developed for converting the computer image to mosaic picture by using Borland C++ Builder 6.0 and successfully utilized on six degrees of freedom Ultimate Puma 500 type industrial robot for tiling glass mosaics to any plane.

According to result of this study, it can be realized that the robots could be successfully utilized on decorating processes, e.g. tiling mosaics, for faster and flexible production.

Presented robotic system allows the craftsmen to produce large and extra ordinary mosaic figures by using computer image and glass mosaic tiles. The goal of using a robot in this application is to increase the speed without man‐faults and flexibility.

Tile finishes are very commonly used in external walls of buildings. However, the ageing process of the tile system is very seldom studied, which makes maintenance scheduling on external wall finishes impossible. The paper aims to contend that weathering exposure is one of the main accelerators of delamination. This paper seeks to test empirically the effects of orientation and shading on the probability of wall tile delamination.

This paper analyses the weathering effects, including orientation and shading, on thepercentage of deliminated areas of the external wall tiles by regression in a large estate in Hong Kong. Wall tile delamination data are collected from ten blocks of a high‐rise housing estate in Hong Kong, multiple linear regression is used to analyse the effects of orientation and shading on the probability of failure of the wall tiling systems.

The results of this paper indicate the effects of orientation and shading on the proportion of delamination of the external wall tile finishes.

The results agree with our contention that shaded areas are found to have lower rate of delamination, while north‐west and exposed façades are found with serious delamination. The results have great implications on maintenance scheduling for external wall tile finishes. Exposed areas receiving intensive thermal and moisture cycles are found to have significantly higher probability of failure. The study is limited by the small number of samples.

The results provide a set of data on the probability of failure of external wall tiling systems, for further ageing and durability analyses of external wall tiling systems. The findings are also of importance to designers and property managers for choosing external wall finishes and shading devices; and for maintaining external wall tile finishes.

This paper is the first study on the probability of failure and weathering impacts on external wall tiling systems. It is also the first attempt to achieve the objectives by means of empirical evidence.

Frost damage is well-known as the main cause of roof tile deterioration. The purpose of this paper is to develop an analytical model for predicting the deterioration process under certain climatic conditions. This paper describes the results of a field survey conducted to acquire fundamental information useful to this aim.

A field survey of roof tile damage by freezing was conducted in an old temple precinct in Kyoto, Japan. Using detailed observations and photographic recordings, the damage progress was clarified. To examine the impact of climatic conditions upon the damage characteristics, weather data and roof tile temperatures were measured and logged in the winter season.

The deterioration process was observed under the climatic conditions associated with the measured temperature of the roof tiles. In particular, it was revealed that the orientation has a significant influence on increasing or decreasing the risk of frost damage. For certain distinctive forms of damage, the deterioration mechanisms were estimated from the viewpoint of the moisture flow and temperature distribution in the tile.

This study contributes to the elucidation of the mechanism behind frost damage to roof tiles. The findings will guide the construction of a numerical model for frost damage prediction.

Climate change is expected to cause larger and more frequent precipitation events in key agricultural regions of the United States, damaging crops and soils. Subsurface tile drainage is an important technology for mitigating the risks of a wetter climate in crop production. In this study, the authors examine how quickly farmers adapt to increased precipitation by investing in drainage technology.

Using farm-level data from the 2018 Agricultural Resource Management Survey (ARMS) of soybean producers, the authors construct a drainage adoption timeline based on when the operator began farming their land and when tile drainage was installed, if at all. The authors examine both the initial investment decision and the speed with which drainage is installed by adopters. A Heckman-style Poisson regression is used to model the count nature of adoption speed (measured in years taken to install tile drainage) and to correct for potential sample-selection bias.

The authors find that local precipitation is not a significant determinant of the drainage investment decision but may be highly influential in the timing of adoption among drainage users. Farms exposed to crop-damaging levels of precipitation install tile drainage faster than those with low to moderate levels of rainfall. Estimates of farm adaptation speeds are heterogeneous across farm and operator characteristics, most notably land tenure status.

Understanding how US farmers adapt to extreme weather through technology adoption is key to predicting the long-term impacts of climate change on America's food system. This study extends the existing climate adaptation literature by focusing on the speed of adoption of an important and increasingly common climate-mitigating technology – subsurface tile drainage.

Image classification or more specifically, annotating images with keywords is one of the important steps during image database indexing. However, the problem with current research in terms of image retrieval is more concentrated on how conceptual categories can be well represented by extracted, low level features for an effective classification. Consequently, image features representation including segmentation and low‐level feature extraction schemes must be genuinely effective to facilitate the process of classification. The purpose of this paper is to examine the effect on annotation effectiveness of using different (local) feature representation methods to map into conceptual categories.

This paper compares tiling (five and nine tiles) and regioning (five and nine regions) segmentation schemes and the extraction of combinations of color, texture, and edge features in terms of the effectiveness of a particular benchmark, automatic image annotation set up. Differences between effectiveness on concrete or abstract conceptual categories or keywords are further investigated, and progress towards establishing a particular benchmark approach is also reported.

In the context of local feature representation, the paper concludes that the combined color and texture features are the best to use for the five tiling and regioning schemes, and this evidence would form a good benchmark for future studies. Another interesting finding (but perhaps not surprising) is that when the number of concrete and abstract keywords increases or it is large (e.g. 100), abstract keywords are more difficult to assign correctly than the concrete ones.

Future work could consider: conduct user‐centered evaluation instead of evaluation only by some chosen ground truth dataset, such as Corel, since this might impact effectiveness results; use of different numbers of categories for scalability analysis of image annotation as well as larger numbers of training and testing examples; use of Principle Component Analysis or Independent Component Analysis, or indeed machine learning techniques for low‐level feature selection; use of other segmentation schemes, especially more complex tiling schemes and other regioning schemes; use of different datasets, use of other low‐level features and/or combination of them; use of other machine learning techniques.

This paper is a good start for analyzing the mapping between some feature representation methods and various conceptual categories for future image annotation research.

Heritage buildings are consistently impacted by technical and pathological issues associated with their maintenance and conservation such as diminish of building's authenticity and damaging environmental impact. This paper aims to evaluate the environmental maintenance impact (EMI) of the Singgora roof tiles repair in heritage buildings. The EMI is an evaluation upon embodied carbon expenditure during maintenance phase, thus important in repair efficiency appraisal.

Calculation procedures within selected boundaries of life cycle assessment (LCA) and arbitrary period enabled evaluation of the EMI of Singgora roof tiles repair in heritage buildings during the maintenance phase.

Evaluation of the EMI could be appreciated as a carbon LCA of Singgora roof tiles repair and has been recognised in embodied carbon expenditure reduction in the form of CO₂ emissions mitigation. Importantly, the evaluation underpins decision-making for heritage buildings repair.

EMI evaluation encompasses all building types and forms, thus comprehends the associated applied methodologies. Moreover, the evaluation reflects the emerging environmental challenges of sustaining resilient buildings globally.

EMI evaluation highlights options that may be adopted in repair. Indirectly, this implicates heritage building preservation and place's identity protection. Significantly, the evaluation supports environmentally focused conservation and promotes a sustainable repair approach.

EMI evaluation of this paper may devoted to the holistic understanding of the complex relations between Singgora roof materials and their environmental performance. Meanwhile, the application of a carbon LCA had dictated integration of multidisciplinary of heritage buildings maintenance and conservation.

This paper provides a comprehensive review of the literature concerning the various causes of failures of external wall tile finishes.

A 4×3 matrix hierarchy framework is developed for a systematic analysis of the literature reviewed.

The findings from this paper indicate the importance of environmental effects, movement joints, and adhesive on the performance of external wall tile finishes. Thermal and moisture effects induce movement of tiles, and the failure of the tiling system depends very much on the adhesive strength and the provision of movement joints. Workmanship is also a key factor affecting the performance of external wall tile finishes and should not be overlooked.

Various studies have been carried out on the causes of defects in external finishes in the past. However, many of them were case‐oriented and were not supported by laboratory findings. The hierarchical framework developed in this paper serves as a basis for further laboratory and field studies on this issue.

The framework is conducive to the diagnosis of external wall tile delamination.

This paper reviews systematically and comprehensively the literature on the causes of external wall tile delamination.

Double pressing systems have recently been introduced to speed up and improve the pressing step of porcelain stoneware tiles. This paper aims to analyze double pressing systems using discontinuous pre‐compaction, both technically and economically. Two operative conditions are considered: the traditional forming of tiles during pressing is compared with the innovative production of a unique large‐sized slab, subsequently customized according to market requirements. Furthermore, manufacturing conditions are explored with infrequent or frequent production runs, due to increasingly smaller production batches, in order to evaluate which production process is more suitable when changing operative conditions are managed.

The analysis is carried out experimentally, by collecting data in existing pilot plants, producing batches of products of different size and colour. Details are provided concerning the technical characteristics of the systems, along with costs per manufactured square metre for investments, personnel, maintenance, spare parts and electric power. A case in which some production days are reserved for each manufactured batch is compared to a case in which production runs are repeated more frequently in a day.

Manufacturing large‐sized slabs and customization has shown to be an efficient solution for companies operating in changing markets.

Further research should study double pressing systems using continuous pre‐compaction.

The proposed analysis, by presenting an evaluation process and sharing data collected experimentally, provides innovative support for addressing decision makers when new pressing systems for porcelain stoneware tiles are selected.

A popular façade treatment for buildings in Hong Kong is tile cladding. It is used for the majority of low and high‐rise residential buildings and the less expensive office developments in lower grade business districts. Mosaic and ceramic tiles are generally durable, versatile, waterproof and need little maintenance. However, tile defects such as dislodgement and water penetration can affect buildings that are only a few years old. The paper examines the typical causes of tiling defects and the range of repair methods that are being adopted in Hong Kong.

The purpose of this paper is to present a new tile dispensing decision-making to improve a row formation of a product flow-based tiling automation that has been being developed to support tile placement for custom mosaic design.

A new tile dispensing decision-making combines maximum tile loading and simple cycle strategies to minimize time for forming rows of tiles. The maximum tile loading strategy is for minimizing the number of loading rounds, while the simple cycle strategy is for minimizing the movement during the row formation.

This proposed decision-making has been developed; implemented in LabVIEW software; linked with other LabVIEW-based programs to control the system; and tested. The results showed the tile dispensing with the proposed decision-making performed better than the previous one.

The tiling automation is being developed and is currently on a prototyping stage.

Tile dispensing is critical for this row by row automated assembly, but the existing shortest distance strategy does not guarantee the best performance for a row formation. Therefore, the combination of the maximum tile loading and simple cycle strategies has been developed to improve the performance of the product flow-based tiling automation to better support assembly of custom mosaic design that requires individual tesserae to be assembled to particular positions to illustrate an image properly.