The role of annealing temperature on the optical energy gap and Urbach energy of Se:2%Sb thin films

The optical energy gap(Eopt) and the width of the tails of localized states in the band gap (?E) for Se:2%Sb thin films prepared by thermal co-evaporation method as a function of annealing temperature are studied in the photon energy range ( 1 to 5.4)eV.Se2%Sb film was found to be indirect transition with energy gap of (1.973,2.077, 2.096, 2.17) eV at annealing temperature (295,370,445,520)K respectively. The Eopt and ?E of Se:2%Sb films as a function of annealing temperature showed an increase in Eopt and a decrease in ?E with increasing the annealing temperature. This behavior may be related to structural defects and dangling bonds

Study a quality of the Hazy image by using YIQ color space

Determining the quality of the hazy image is difficult problem, thus these images need to analyzing after determined the quality or dehazing. In this paper, we analyzed the hazy(by the dust) images depending on YIQ color space. First we designed the system captured images which graded for high to very low hazy (by adding the dust) by using HeNe laser, in these images we calculated the Normalize Mean Square error (NMSE) for each components in YIQ and RGB color space, and the basic components in the Structure Similarity Index (SSIM) are (contrast, structure and luminance) moreover the mean for all has been calculated. We can see the lightness (in YIQ) and luminance ( in SSIM) component are not effected by the dust whereas the  chromatic components are highly effected by the dust. Keywords: The dust images, Dehazing , YIQ color space , Luminanc

Motor imagery-based brain-computer interface by implementing a frequency band selection

Les interfícies cervell-ordinador basades en imaginacions motores (MI-BCI) són una promesa per a revolucionar la manera com els humans interactuen amb les màquines o el programari, realitzant accions només amb el pensament. Els pacients que pateixen discapacitats de moviment crítiques, com l'esclerosi lateral amiotròfica (ALS) o la tetraplegia, podrien utilitzar aquesta tecnologia per controlar una cadira de rodes, pròtesis robòtiques o qualsevol altre dispositiu que els permeti interactuar de manera independent amb el seu entorn. L'objectiu d'aquest projecte és ajudar les comunitats afectades per aquests trastorns amb el desenvolupament d'un mètode que sigui capaç de detectar, amb la màxima precisió possible, la intenció d'executar moviments (sense que es produeixin) en les extremitats superiors del cos. Això es farà mitjançant senyals adquirits amb un electroencefalograma (EEG), el seu condicionament i processament, i la seva posterior classificació amb models d'intel·ligència artificial. A més, es dissenyarà un filtre de senyal digital per mantenir les bandes de freqüència més característiques de cada individu i augmentar significativament l’exactitud del sistema. Després d'extreure les característiques estadístiques, freqüencials i espacials més discriminatòries, va ser possible obtenir una exactitud del 88% en les dades de validació a l'hora de detectar si un participant estava imaginant un moviment de la mà esquerra o de la dreta. A més, es va utilitzar una xarxa neuronal convolucional (CNN) per distingir si el participant estava imaginant un moviment o no, la qual cosa va aconseguir una exactitud del 78% i una precisió del 90%. Aquests resultats es verificaran mitjançant la implementació d'una simulació en temps real amb l'ús d'un braç robòtic.Las interfaces cerebro-computadora basadas en imaginaciones motoras (MI-BCI) son una promesa para revolucionar la forma en que los humanos interactúan con las máquinas o el software, realizando acciones con tan solo pensar en ellas. Los pacientes que sufren discapacidades críticas del movimiento, como la esclerosis lateral amiotrófica (ALS) o la tetraplejia, podrían usar esta tecnología para controlar una silla de ruedas, prótesis robóticas o cualquier otro dispositivo que les permita interactuar de manera independiente con su entorno. El objetivo de este proyecto es ayudar a las comunidades afectadas por estos trastornos con el desarrollo de un método que sea capaz de detectar, con la mayor precisión posible, la intención de ejecutar movimientos (sin que se produzcan) en las extremidades superiores del cuerpo. Esto se hará mediante señales adquiridas con un electroencefalograma (EEG), su acondicionamiento y procesamiento, y su posterior clasificación con modelos de inteligencia artificial. Además, se diseñará un filtro de señal digital para mantener las bandas de frecuencia más características de cada individuo y aumentar significativamente la exactitud del sistema. Después de extraer características estadísticas, frecuenciales y espaciales discriminatorias, fue posible obtener una exactitud del 88% en los datos de validación a la hora de detectar si un participante estaba imaginando un movimiento con la mano izquierda o con la derecha. Además, se utilizó una red neural convolucional (CNN) para distinguir si el participante estaba imaginando un movimiento o no, lo que logró un 78% de exactitud y un 90% de precisión. Estos resultados se verificarán implementando una simulación en tiempo real con el uso de un brazo robótico.Motor Imagery-based Brain-Computer Interfaces (MI-BCI) are a promise to revolutionize the way humans interact with machinery or software, performing actions by just thinking about them. Patients suffering from critical movement disabilities, such as amyotrophic lateral sclerosis (ALS) or tetraplegia, could use this technology to control a wheelchair, robotic prostheses, or any other device that could let them interact independently with their surroundings. The focus of this project is to aid communities affected by these disorders with the development of a method that is capable of detecting, as accurately as possible, the intention to execute movements (without them occurring) in the upper extremities of the body. This will be done through signals acquired with an electroencephalogram (EEG), their conditioning and processing, and their subsequent classification with artificial intelligence models. In addition, a digital signal filter will be designed to keep the most characteristic frequency bands of each individual and increase accuracy significantly. After extracting discriminative statistical, frequential, and spatial features, it was possible to obtain an 88% accuracy on validation data when it came to detecting whether a participant was imagining a left-hand or a right-hand movement. Furthermore, a Convolutional Neural Network (CNN) was used to distinguish if the participant was imagining a movement or not, which achieved a 78% accuracy and a 90% precision. These results will be verified by implementing a real-time simulation with the usage of a robotic arm

Modern studies of training modalities in the professional sport field

This paper highlights on the different modern trainings at the professional sport activities. All the modern methods of Karate trainings were discussed in details, even the training obstacles that confront coaches. All the modern training methods have seen in details taken from scientific and practical studies belong to the trainee and coaches of that sport. This paper contains more than twenty training method with schedules supported with statistics and comparisons between the basic training methods that are taken from some exercise of different sports such as pushing the iron ball and the hammer's sight, and the influence of these sports to develop the coach and the trainee of karate

Prevalence Of Osteopenia And Osteoporosis: The Assessment Of Osteoporosis Knowledge, Health Belief And Self-Efficacy Among Patients With Type 2 Diabetes Mellitus In Penang

Type 2 diabetes mellitus (T2DM) and osteoporosis are both chronic conditions and the relationship between them is complex. Knowledge, health belief and self-efficacy toward osteoporosis are fundamental to all osteoporosis management programs and are often a pre-requisite for initiating desired behavioural changes. Therefore, the aims of the present study were to assess the prevalence of osteoporotic conditions and the level of knowledge, health belief and self-efficacy toward osteoporosis among T2DM patients in Penang

Object tracking using motion flow projection for pan-tilt configuration

We propose a new object tracking model for two degrees of freedom mechanism. Our model uses a reverse projection from a camera plane to a world plane. Here, the model takes advantage of optic flow technique by re-projecting the flow vectors from the image space into world space. A pan-tilt (PT) mounting system is used to verify the performance of our model and maintain the tracked object within a region of interest (ROI). This system contains two servo motors to enable a webcam rotating along PT axes. The PT rotation angles are estimated based on a rigid transformation of the the optic flow vectors in which an idealized translation matrix followed by two rotational matrices around PT axes are used. Our model was tested and evaluated using different objects with different motions. The results reveal that our model can keep the target object within a certain region in the camera view

Gender detection in children’s speech utterances for human-robot interaction

The human voice speech essentially includes paralinguistic information used in many real-time applications. Detecting the children’s gender is considered a challenging task compared to the adult’s gender. In this study, a system for human-robot interaction (HRI) is proposed to detect the gender in children’s speech utterances without depending on the text. The robot's perception includes three phases: Feature’s extraction phase where four formants are measured at each glottal pulse and then a median is calculated across these measurements. After that, three types of features are measured which are formant average (AF), formant dispersion (DF), and formant position (PF). Feature’s standardization phase where the measured feature dimensions are standardized using the z-score method. The semantic understanding phase is where the children’s gender is detected accurately using the logistic regression classifier. At the same time, the action of the robot is specified via a speech response using the text to speech (TTS) technique. Experiments are conducted on the Carnegie Mellon University (CMU) Kids dataset to measure the suggested system’s performance. In the suggested system, the overall accuracy is 98%. The results show a relatively clear improvement in terms of accuracy of up to 13% compared to related works that utilized the CMU Kids dataset

Adaptive Backtracking Search Strategy to Find Optimal Path for Artificial Intelligence Purposes

There are numerous of Artificial Intelligence (AI) search strategies that used for finding the solution path to a specific problem, but many of them produce one solution path with no attention if it is the optimal path or not. The aim of our work is to achieve the optimality by finding direct path from the start node to the goal node such that it is the shortest path with minimum cost .In this paper adaptive backtracking algorithm is produced to find the optimal solution path, such that all possible paths in the tree graph of the search problem that have an expected optimal solution is tested, also a heuristic function related to the actual cost of the moving from one node to another is used in order to reduce the search computation time. The adaptive algorithm ignored any path that it is not useful in finding the optimal solution path, our adaptive algorithm implemented using visual prolog 5.1, evaluated on tree diagram and produced good result in finding the optimal solution path with efficient search time equivalent to O(bd/2) and space complexity O(bd). Keywords: Backtracking Algorithm, Optimal solution Path, Heuristic function, Dead end, shortest path, Minimum cost

Topological concepts and their relation to engineering thinking among middle school students

The current research aims to investigate the topological concepts for intermediate stage students, engineering thinking among intermediate stage students, and the relationship between topological concepts and engineering thinking for intermediate stage students. The research sample consisted of (220) students from the first intermediate class / first Rusafa, where verification of validity and reliability were conducted for the topological test concepts as a first tool and a test for engineering thinking as a second tool. Accordingly, the two tests were ready to be applied to the basic sample and in their final form, which the topological concepts test items reached (16) items, while the engineering thinking test items reached (18) items,  Furthermore, the statistical package for social sciences (SPSS) was applied to analyze the research results.  and the results showed that first intermediate class students possess topological concepts and engineering thinking that exceeds the assumption average of the test and that there is a positive relation between topological concepts and engineering thinking. Finally, the researchers presented a set of proposals and recommendations based on the results of the study &nbsp

Evaluation of Polycystic Ovary Syndrome (PCOS) Through Androstolone and Pituitary Hormones Lab Testing

        Hyperandrogenemia is an essential symptom of PCOS. Androgens are produced in the ovaries and adrenal glands as the final products of a series of enzymatic reactions starting from a common precursor, i.e, cholesterol. The critical intermediate stages of androgen production involve the conversion of cholesterol into dehydroepiandrosterone and androstenedione. These reactions take place in the theca cells . Hyperandrogenemia is considered the main clinical hallmark of PCOS. It is estimated that more than 80% of women who exhibit signs or symptoms of hyperandrogenism , including hirsutism, acne or alopecia, have PCOS .Abnormalities in the neuroendocrine system like increased pulse frequency of gonadotropin-releasing hormone, stimulating the pituitary for excessive production of luteinizing hormone than that of follicle-stimulating hormone is seen in PCOS women. Excess LH stimulates ovarian androgen production, whereas a relative deficit in FSH impairs follicular development. The imbalance in LH: FSH causes proliferation of ovarian theca cells leading to increased steroid genesis , and ultimately leading to hyperandrogenism in PCOS women