Nowadays, the robotic arm is fast becoming the most popular robotic form used in the industry among others. Therefore, the issues regarding remote monitoring and controlling system are very important, which measures different environmental parameters at a distance away from the room and sets various condition for a desired environment through a wireless communication system operated from a central room. Thus, it is crucial to create a programming system which can control the movement of each part of the industrial robot in order to ensure it functions properly. EDARM ED-7100 is one of the simplest models of the robotic arm, which has a manual controller to control the movement of the robotic arm. In order to improve this control system, a new controller system was redesigned in this work by using Zigbee. It is a communication protocol for safety and economic data communication in an industrial field, where the wired communication is either expensive or difficult under physical and experimental conditions, such as the worker cannot recognize the error through the manufacturing process. Hence, this paper introduced a system that used microcontroller (AT89S52) with wireless devices (Zigbee) and sensors to control the robotic hand (EDARM ED-7100) and to monitor the information regarding the robot's parameter using WiFi technology. A mathematical model was derived through an empirical method to specify the robot's configuration changes. In this work, the ability of controlling system had increased, as well as hardware, while the necessities of other similar equipment for data communication were minimized. In addition, it presents the comparison of two controlling systems: using the Zigbee and without using it. Based from the experiment it can be safely concluded that the robotic arm's movement had followed a linear function.
Samples of Iraqi bentonitic sediments, representing local montmorillonite brought from Traifawi region near the Syrian border. Mineralogical the samples were characterized as low grade of Ca-smectite, particle size, chemical analysis, XRD, and BET surface area analyses of the samples were carried out to examine the structure of bentonite before and after acid activation. The goal is to prepare a bleaching earth for edible oil production. Iraqi Bentonite was beneficiated and activated by series of physical and chemical steps, using 4N & 6N concentration of hydrochloric acid and at a temperature of 70-80 ° C. Surface area and pore volume of the samples were determined to assess the bleaching power
Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.
The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou
... Show MoreThis work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
... Show MoreThe "Nudge" Theory is considered one of the most recent theories, which is clear in the economic, health, and educational sectors, due to the intensity of studies on it and its applications, but it has not yet been included in crime prevention studies. The use of Nudge theory appears to enrich the theory in the field of crime prevention, and to provide modern, effective, and implementable mechanisms.
The study deals with the "integrative review" approach, which is a distinctive form of research that generates new knowledge on a topic through reviewing, criticizing, and synthesizing representative literature on the topic in an integrated manner so that new frameworks and perspectives are created around it.
The study is bas
... Show MoreIn this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample
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