Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using MBAM make it timeless because it will deal with a complete answer sheet, it no need to extract the answer boxes from the answers sheet. The proposed OMR exhibits accuracy is 99.998% in the recognition of marked and non-marked.
This work aims to analyze and study the bit performance in directional oil wells which leads to get experience about the drilled area by monitoring bit performance and analyzing its work. This study is concerned with Rumaila Oil Field by studying directional hole of one oil well with different angles of inclination. Drilling program was used in order to compare with used parameters (WOB, RPM and FR).in those holes. The effect of the drilling hydraulic system on the bit performance was studied as well as the hydraulic calculation can be done by using Excel program. This study suggests method which is used to predict the value of penetration rate by studying different formation type to choose the best drilling parameters t
... Show MoreIn this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.
This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.
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.
This paper presents the motion programming and control of omni-directional mobile robot through the process of building and programming a small robotic platform with secondary design criteria of modularity and simplified control. This is accomplished by combining the positive aspects of several different robotics platform ideas. The platform is shaped like an equilateral triangle with a servo motor, sensors, and omni-wheel, controlled by a PIC microcontroller.
In this work the kinematics, inverse kinematics and dynamic module for the platform is derived. Two search algorithms (the wall-following search and the “most-open-area” search) is designed, tested, and analyzed experimentally.
Directional control valves are designed to control direction of flow, while actuators maintain required speeds and precise positions. Magnetorheological (MR) fluid is a controllable fluid. Utilizing the MR fluid properties, direct interface between magnetic fields and fluid power is possible, without the need for mechanical moving parts like spools. This study proposes a design of a four-way three-position MR directional control valve, presents a method of building, and explains the working principle of the valve. An analysis of the design and finite elements using finite element method of magnetism (FEMM) software was performed on each valve. The magnetic circuit of the MR valve was analyzed and the performance was simulated. The
... Show MoreThere are many configurations of directional control valve. Directional control valve has complex construction, such as moving spool to control the direction of actuator and desired speed. Magneto-rheological (MR) fluid is one of controllable fluids. Utilizing the MR fluid properties, direct interface can be realized between magnetic field and fluid power without the need for moving parts like spool in directional control valves. This paper presents the design of multi configuration MR directional control valve. The construction and the principle of work of the valve are presented. The experiment was conducted to show the working principle of the valve functionally. The valve worked proportionally to control the direction and speed of hydra
... Show MoreOver the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time. In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D
... Show MoreMethods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the
... Show MoreThe area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.