Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

     This paper attempts to develop statistical modeling for air-conditioning analysis in Jakarta, Indonesia, during an emergency state of community activity restrictions enforcement (Emergency CARE), using a variety of parameters such as PM₁₀, PM_2.5, SO₂, CO, O₃, and NO₂ from five IoT-based air monitoring systems. The parameters mentioned above are critical for assessing the air quality conditions and concentration of air pollutants.  Outdoor air pollution concentration variations before and after the Emergency CARE, which was held in Indonesia during the COVID-19 pandemic on July 3-21, 2021, were studied. An air quality monitoring system based on the IoT generates sensor data

 
      The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca

Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

  The indicators were important core for any work, and may be occurring this indicators way of communicating among planers and decision makers, even also for public participating, do make any decision. The urban and regional planning is one of those science highly depending on using indictors, for two  reasons, first, way to communicating ideas between specialist and non-specialist, (politician and decision makers), the second one, this field are multidisciplinary science, so the need indictors to clearing thoughts among different backgrounds in one team, as common language.

This research tries to clear importance of GIS in forming and building Spatial Planning Indicators, to cross communication problem among planning g

The calculation of potential earth's surface solar radiation is imperative for analyzing the atmosphere-vegetation-soil interaction process. Therefore, many schemes were introduced with  direct (using net radiometer) or indirect (using air temperature or air plus soil temperatures) formulas. Three combinations of factors are known to control the R_n value; the astronomical based factors which determine the general spatial distribution of R_n values, the climatological factors which determine the assigned spatial variation of those values, and the topographical factors that influence climatological factors rates ( i.e. have indirect effects on Rn values).

     For Iraq, the ecosystem in

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat