Condition assessment is an integral component in any infrastructure asset management system. Without condition information, asset managers lack the ability to make appropriate decisions regarding needed maintenance, rehabilitation, and replacement of infrastructure. Existing and emerging technologies for assessing the condition of water and sewer pipes provide a better picture of the state of these buried assets. Unfortunately, many of these technologies are costly and provide results that are not always highly reliable. This paper presents a methodology to assist asset managers in balancing

One of the key challenges in applying deep learning to solve real-life problems is the lack of large annotated datasets. Furthermore, for a deep learning model to perform well on the test set, all samples in the training and test sets should be independent and identically distributed (i.i.d.), which means that test samples should be similar to the samples that were used to train the model. In many cases, however, the underlying training and test set distributions are different. In such cases, it is common to adapt the test samples by transforming them to their equivalent counterparts in the

In the era of digital transformation, a mass disruption in the global industries have been detected. Big data, the Internet of Things (IoT) and Artificial Intelligence (AI) are just examples of technologies that are holding such digital disruptive power. On the other hand, retailing is a high-intensity competition and disruptive industry driving the global economy and the second largest globally in employment after the agriculture. AI has large potential to contribute to global economic activity and the biggest sector gains would be in retail. AI is the engine that is poised to drive the

Corrosion occurs in all sectors including oil pipelines, drinking water and sewerage in the majority of cases linked to corrosion of steel. Good corrosion management includes optimising corrosion control actions and minimising lifecycle corrosion costs whilst meeting environmental goals. The toxicity of commonly used synthetic inhibitors are the subject of recent legislations (REACH and PARCOM) have led to search on more eco-friendly corrosion inhibitors. Extensive research is conducted to assess the corrosion inhibition rate of diverse green inhibitors. However, it was not adequately

This paper describes a field study conducted over a period of 11-months on labour productivity observed during the construction of a new university campus in Cairo, Egypt. The campus is being built on 127 acres and the field study was conducted during the construction of two main buildings; each of 20,000 m 2 built up area. The study utilized work sampling (WS), craftsman questionnaire (CQ), and foreman delay survey (FDS) methods to analyze labour productivity of three indicative and labour-intensive trades, namely formwork, masonry work, and HVAC duct installation. The results were also

Dissolved oxygen (DO) is an important water quality parameter. It is considered the most important parameter. DO concentration in water is affected by different parameters such as volume flow rate, water velocity, and re-aeration rate. Those parameters are directly affected by the geometry of the waterway. Thus, studying the impact of changing channel geometry on DO is very important. Many researchers studied the effect of influential parameters on water quality variables but the influence of channel geometric parameters on DO was not studied thoroughly before. This research aims to study the

The increase in population, food demand, and the pollution levels of the environment are considered major problems of this era. For these reasons, the traditional ways of farming are no longer suitable for early and accurate detection of biotic stress. Recently, precision agriculture has been extensively used as a potential solution for the aforementioned problems using high resolution optical sensors and data analysis methods that are able to cope with the resolution, size and complexity of the signals from these sensors. In this paper, several methods of machine learning have been utilized

Recent works show that the plants can exhibit nonlinear memristive behavior when excited with low-frequency signals. However, in the literature, only linear bio-impedance models are extensively considered to model the electrical properties of biological tissues without acknowledging the nonlinear behavior. In this paper, we show with experiments, for the first time, the pinched hysteresis behavior in seven fruits and vegetables including tomato, orange, lemon, aubergine, and kiwi which exhibit single pinch-off point, and others such as carrot and cucumber exhibit double pinch-off points (i.e

Sensor Actor NETworks (SANET) represent a major component of ubiquitous service environments promising interesting solutions to a wide range of problems. Despite the obvious increase in the research activities proposing architectures and protocols for SANETs, we are still no where near the production of industrial-grade SANET software that can be relied upon for mission critical applications. The cost of programming, deploying and maintaining SANET environments is still highly prohibitive due to the lack of industrial tools capable of realizing adaptive SANET software in a cost effective way

Titanium dioxide (TiO2) nanocomposites have been extensively employed in many fundamental optoelectronic and photocatalytic applications due to their outstanding optical, electronic and chemical properties. In the present work, we introduce a simple layer-by-layer approach to design a magnetic TiO2 nanocomposite that could be easily recycled using an external magnetic field without affecting its quantum efficiency. The crystallinity, size, surface area, stability, morphology, purity and other optical, thermal and magnetic properties of the composite have been investigated. Surface topology