Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

This study was conducted on Lake Hamrin situated in Diyala governorate, focal Iraq, between latitudes 44^º 53ʹ 26.16 '- 45º 07 ʹ 28.03^ʺ and 34º 04ʹ 24.75^ʺ ــ 34º 19ʹ 12.74^ʺ . As in this study, the surface area of Hamrin Lake was calculated from satellite images during the period from October 2019 to September 2020, with an average satellite image for each month, furthermore,by utilizing the Normalized Differences Water Index (NDWI), the largest surface area was 264,617 km² for October and the lowest surface area 140.202 km² for September. The surface temperature of the lake water was also calculated from satellite images of the Landsat 8 satellite, based on ban

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

The organization uses many techniques and methods to ensure that they will succeed and adapted with velocity change in the internal and external environment by decision taking, especially strategic decisions.

Strategic decisions are very important for organization success because it can predict the future and deal with uncertainty, in this circumstances they need accurate and comprehensive information to make effective strategic decision.

To achieve that purpose it must owned successful Strategic Information System ( SIS ) and determined the critical success factors for this system ,which can assisted the worker to focus on the important activities to develop it.

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F