Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

Hydroponics is the cultivation of plants by utilizing water without using soil which emphasizes the fulfillment of the nutritional needs of plants. This research has introduced smart hydroponic system that enables regular monitoring of every aspect to maintain the pH values, water, temperature, and soil. Nevertheless, there is a lack of knowledge that can systematically represent the current research. The proposed study suggests a systematic literature review of smart hydroponics system to overcome this limitation. This systematic literature review will assist practitioners draw on existing literature and propose new solutions based on available knowledge in the smart hydroponic system. The outcomes of this paper can assist future r

    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedu

Morphological theories shape the leading platform to theoretically and practically consider the assets connected with the emergence of the city, and its growth and development over time. In this paper, five elements of the urban form are typified: structure/tissue, plot, building, block, and the street pattern will be addressed. Understanding the urban form at the different levels within its ingredients could lead to shape a base launch of how to consider the potentiality of the development and sustainability of a particular area.   

For the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s

          Fruits sorting, recognizing, and classifying are essential post-harvest operations, as they contribute to the quality of food industry, thereby increasing the exported quantity of food. Today, an automated system for fruit classification and recognition is very important, especially when exporting to markets where quality of fruit must be high. In this study, the advantages and disadvantages of the various shape-based feature extraction algorithms and technologies that are used in sorting, classifying, and grading of fruits, as well as fruits quality estimation, are discussed in order to provide a good understanding of the use of shape-based feature extraction techniques.

Conventional dosage forms for topical and transdermal drug delivery have several disadvantages related mainly to its poor skin permeation and patient compliance. Many approaches have been developed to improve these dosage forms. Film forming drug delivery systems represents a recent advancement in this field. It provides improved patient compliance with enhanced skin permeation of drugs. In its simplest form, these consist of a polymeric solution, usually in a supersaturated state, in a suitable solvent. A plasticizer is usually added to improve the flexibility and enhance the tensile strength to the film. It is also possible to control and sustain the drug release from the films by controlling the polymeric content, concentration o

Recently times, industrial development has increased, including plastic industries, and since plastic has a very long analytical life, it will cause environmental pollution. Therefore studies have resorted to reusing recycled plastic waste (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, some studies were reviewed and then summarized into several things, including the percentage of plastic replacement from the aggregate and the effect of this percentage on the fresh properties of concrete, such as the workability and the effect of plastic waste on the hardening properties of concrete such as dry density, compressive, tensile and flexural strength.

Alongside the development of high-speed rail, rail flaw detection is of great importance to ensure railway safety, especially for improving the speed and load of the train. Several conventional inspection methods such as visual, acoustic, and electromagnetic inspection have been introduced in the past. However, these methods have several challenges in terms of detection speed and accuracy. Combined inspection methods have emerged as a promising approach to overcome these limitations. Nondestructive testing (NDT) techniques in conjunction with artificial intelligence approaches have tremendous potential and viability because it is highly possible to improve the detection accuracy which has been proven in various conventional nondestr