The applications of Federated Learning are many, and they can be used to predict electricity consumption and, at the same time, enable smart meters to collaboratively learn a shared model while keeping all their data locally in their own private database. With this approach, the central model will see more data and will work better to predict electricity consumption more accurately than the models trained on only one local Dataset. The planning of infrastructure, grid operation, and budgeting all depend on accurate load forecasting. As a result, this paper suggests federated learning for load

The amount and variety of raw data generated in the agriculture sector from numerous sources, including soil sensors and local weather stations, are proliferating. However, these raw data in themselves are meaningless and isolated and, therefore, may offer little value to the farmer. Data usefulness is determined by its context and meaning and by how it is interoperable with data from other sources. Semantic web technology can provide context and meaning to data and its aggregation by providing standard data interchange formats and description languages. In this paper, we introduce the design

Customer churn poses a formidable challenge within the Telecom industry, as it can result in significant revenue losses. In this research, we conducted an extensive study aimed at developing a viable customer churn prediction method. Our method utilizes the Apriori algorithm's strength to identify the key causes of customer churn. In the pursuit of this goal, we utilized multiple machine learning predictive models. All of which were developed from the insights gleaned from the Apriori algorithm's feature extraction for churning customers. This extensive analysis encompassed a spectrum of

Rice is considered a strategic crop in Egypt as it is regularly consumed in the Egyptian people’s diet. Even though Egypt is the highest rice producer in Africa with a share of 6 million tons per year [5], it still imports rice to satisfy its local needs due to production loss, especially due to rice disease. Rice blast disease is responsible for 30% loss in rice production worldwide [9]. Therefore, it is crucial to target limiting yield damage by detecting rice crops diseases in its early stages. This paper introduces a public multispectral and RGB images dataset and a deep learning pipeline

Document forgery detection is becoming increasingly important in the current era, as forgery techniques are available to even inexperienced users. Source printer identification is a method for identifying the source printer and classifying the questioned document into one of the printer classes. According to what we know, most earlier studies segmented documents into characters, words, and patches or cropped them to obtain large datasets. In contrast, in this paper, we worked with the document as a whole and a small dataset. This paper uses three techniques dependent on CNN to find the

Plain concrete is used for water canal lining due to its low permeability to reduce water losses due to seepage. However, cement manufacture has a negative environmental impact as it produces large amount of CO2 emissions in addition to high energy consumption. In this study, bio-sludge of sewage plants was used an alternative for cement, mixed with sand and crushed stone, and used as an alternative to plan concrete for canal lining. An experimental testing program was designed based on percentages of sludge and soil equal to 2.5%, 5%, and 10% by weight. For each sludge mix, properties were

Shell folded footings have drawn the interest of researchers for decades as an alternative to typical flat isolated footings because folded footings can reduce the needed amount of reinforced concrete in addition to enhancing the overall geotechnical performance of the supporting soil medium. The main setback of utilizing such folded footings is the relatively complex geometry of the bottom cavity, which requires proper compaction of the soil used to fill that cavity. Current geosynthetic materials such as geofoam or expanded polystyrene (EPS) proved efficiency in many geotechnical

Biosolid-sludge of sewage treatment plants was mixed with clean coarse sands to reduce soil permeability and assess the potential of utilizing such mix for several geotechnical applications. One of the applications was to develop a soil mix with low permeability for use in roadway embankments subjected to torrents from sudden heavy rain in desert areas. The main purpose was to address a sustainable and eco-friendly mix to be used as an additional protection to the current boulder lining for such embankments. In this study, biosolid sludge was mixed with medium dense sand using percentages

One of the inevitable challenges that face the construction industry is the delay of project completion. The current state of the industry makes the need for delay analysis apparent, however the process of choosing the most reliable delay analysis technique can get very complex in some situations. This research aims to develop a framework to identify and analyze the most important factors to consider when choosing a delay analysis technique. The most reliable technique is decided based on a weighted multicriteria decision matrix. The proposed numerical weight for each factor and the pointing

Construction, demolition, and renovation activities generate a significant amount of waste, posing serious environmental risks. The scarcity of recycling facilities makes it difficult to implement the new legislation, which calls for producing recycled aggregates. Moreover, the lack of studies on the environmental feasibility of recycling construction and demolition waste in regions with plentiful natural resources of aggregates is a contributing factor to this scarcity. Therefore, this paper studies the environmental feasibility of establishing a construction and demolition waste (CDW)