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

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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MPEG-DASH is an adaptive bitrate streaming technology that divides video content into small HTTP-objects file segments with different bitrates. With live UHD video streaming latency is the most important problem. In this paper, creating a low-delay streaming system using HTTP 2.0. Based on the network condition the proposed system adaptively determine the bitrate of segments. The video is coded using a layered H.265/HEVC compression standard, then is tested to investigate the relationship between video quality and bitrate for various HEVC parameters and video motion at each layer/resolution. The system architecture includes encoder/decoder configurations and how to embedded the adaptive video streaming. The encoder includes compression besi

The performance of a solar assisted desiccant cooling system for a meeting-hall located in the College of Engineering/University of Baghdad was evaluated theoretically. The system was composed of four components; a solar air heater, a desiccant dehumidifier, a heat exchanger and an evaporative cooler. A computer simulation was developed by using MATLAB to assess the effect of various design and operating conditions on the performance of the system and its components. The actual weather data on recommended days were used to assess the load variation and the system performance during those days. The radiant time series method (RTS) was used to evaluate the hourly variation of the cooling load. Four operation modes were employed for perform

This study aims to assess the accuracy of digital elevation model (DEM) created with utilization of handheld Global Positioning System (GPS) and comparing with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. It is known that the quality of the DEM is affected by both of accuracy of elevation at each pixel (absolute accuracy) and accuracy of presented morphology (relative accuracy). The University of Baghdad, Al Jadriya campus was selected as a study area to create and analysis the resulting DEM. Additionally, Geographic Information System (GIS) was used to visualize, analyses and interpolate GPS track points (elevation data) of the study area. In this

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Pulsatile drug delivery systems are time-controlled dosage forms which are designed to release the active pharmaceutical ingredient after a predetermined lag time to synchronize the disease circadian rhythm. A migraine shows circadian rhythm with a marked increase in attacks between 6 a.m. and 8 a.m.

Sumatriptan is a selective agonist at serotonin (5-Hydroxy tryptamine1  (5-HT1))receptors, is an effective treatment for acute migraine attacks.

The aim of this work is to prepare time-controlled press-coated tablet with a lag time of 5.45 hrs.

Six formulas of fast dissolving core tablets and three formulas of press-coated tablets were prepared by using direct compression method using different variables to prepa

This paper deals with a Twin Rotor Aerodynamic System (TRAS). It is a Multi-Input Multi-Output (MIMO) system with high crosscoupling between its two channels. It proposes a hybrid design procedure that combines frequency response and root locus approaches. The proposed controller is designated as PID-Lead Compensator (PIDLC); the PID controller was designed in previous work using frequency response design specifications, while the lead compensator is proposed in this paper and is designed using the root locus method. A general explicit formula for angle computations in any of the four quadrants is also given. The lead compensator is designed by shifting the dominant closed-loop poles slightly to the left in the

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

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select