Speed sensorless field oriented control of ac induction motor using model reference adaptive system

In order implement the vector control technique, the motor speed information is required. Incremental encoder, resolvers and tachogenerator, are used to reveal the speed. These sensors require careful mounting and alignment and special attention is required with electrical noises. Sensorless speed vector control is greatly used and applied in induction machine drives instead of scalar control and vector control for their robustness and reliability, and very low maintenance cost. In this project MRAS based techniques are used to estimate the rotor speed based on rotor flux estimation, the estimated speed in the MRAS algorithm is used as a feedback for the vector control system. The model reference adaptive control system is predicated on the comparison between the outputs of adjustable model and reference model. The error between them is employed to drive a suitable adaptation mechanism which generates the estimated rotor speed for the adjustable model. And indirect vector control scheme controls the flux and torque by restricting the torque and flux errors with respective hysteresis bands, and motor flux and torque are controlled by the stator voltage space vectors using optimum inverter switching table. Modeling and simulation of the induction machine and the vector control drives implemented in MATLAB/SIMULINK. Simulation results of proposed MRAS and indirect vector control technique are presented

Simultaneous Hand Pose and Skeleton Bone-Lengths Estimation from a Single Depth Image

Articulated hand pose estimation is a challenging task for human-computer interaction. The state-of-the-art hand pose estimation algorithms work only with one or a few subjects for which they have been calibrated or trained. Particularly, the hybrid methods based on learning followed by model fitting or model based deep learning do not explicitly consider varying hand shapes and sizes. In this work, we introduce a novel hybrid algorithm for estimating the 3D hand pose as well as bone-lengths of the hand skeleton at the same time, from a single depth image. The proposed CNN architecture learns hand pose parameters and scale parameters associated with the bone-lengths simultaneously. Subsequently, a new hybrid forward kinematics layer employs both parameters to estimate 3D joint positions of the hand. For end-to-end training, we combine three public datasets NYU, ICVL and MSRA-2015 in one unified format to achieve large variation in hand shapes and sizes. Among hybrid methods, our method shows improved accuracy over the state-of-the-art on the combined dataset and the ICVL dataset that contain multiple subjects. Also, our algorithm is demonstrated to work well with unseen images.Comment: This paper has been accepted and presented in 3DV-2017 conference held at Qingdao, China. http://irc.cs.sdu.edu.cn/3dv

New Common Fixed Points for Total Asymptotically Nonexpansive Mapping in CAT(0) Space

          تم دراسة التقارب و Δ- تقارب لعملية تكرار من خطوتين بأستخدام تطبيقات اللامتمددة المقاربة (asymptotically nonexpansive) واللامتمددة المقاربة كليآ (total asymptotically nonexpansive) في فضاء CAT(0) وكذلك تم مبرهنة بعض نظريات التقارب القوي باستخدام شبه المتراصة (semi-compact) وشرط (Μ). نتائجنا تحسن وتطور العديد من النتائج المعروفة في الادبيات الموجودة.      Strong and ∆-convergence for a two-step iteration process utilizing asymptotically nonexpansive and total asymptotically nonexpansive noneslf mappings in the CAT(0) spaces have been studied. As well, several strong convergence theorems under semi-compact and condition (M) have been proved. Our results improve and extend numerous familiar results from the existing literature

METHODS FOR TEACHING SPEAKING SKILL AT THAMAR SCHOOLS AND THEIR IMPACTS ON LEARNERS’ ORAL COMPETENCY

In the Republic of Yemen, English is taught as a foreign language (FL) in schools and universities. It is a compulsory subject in the curriculum of Yemeni schools and universities and it is the only foreign language that is taught in all Yemeni Public Schools. However, teachers and educators complain about students’ lack of oral competency. Hence, this paper attempts to evaluate the current teaching methods, approaches, techniques and activities used for teaching English speaking skill at Thamar Secondary Public Schools. Besides, it also investigates the utilization of instructional aides as well as technological resources and facilities available at schools in Thamar city. Three different data collection techniques were used, namely observation, questionnaire, and interview. The results revealed that English teachers in Thamar still follow the traditional teaching methods. Above all, speaking skill is almost neglected. The lack of proper teaching methods and activities coupled with the absence of instructional aides stand behind students’ deficiency in English speaking. Thus, it is recommended that several training sessions for in-service teachers to be held in order to familiarize them with the methods, techniques, and activities used for teaching English speaking skill

Structure from Articulated Motion: Accurate and Stable Monocular 3D Reconstruction without Training Data

Recovery of articulated 3D structure from 2D observations is a challenging computer vision problem with many applications. Current learning-based approaches achieve state-of-the-art accuracy on public benchmarks but are restricted to specific types of objects and motions covered by the training datasets. Model-based approaches do not rely on training data but show lower accuracy on these datasets. In this paper, we introduce a model-based method called Structure from Articulated Motion (SfAM), which can recover multiple object and motion types without training on extensive data collections. At the same time, it performs on par with learning-based state-of-the-art approaches on public benchmarks and outperforms previous non-rigid structure from motion (NRSfM) methods. SfAM is built upon a general-purpose NRSfM technique while integrating a soft spatio-temporal constraint on the bone lengths. We use alternating optimization strategy to recover optimal geometry (i.e., bone proportions) together with 3D joint positions by enforcing the bone lengths consistency over a series of frames. SfAM is highly robust to noisy 2D annotations, generalizes to arbitrary objects and does not rely on training data, which is shown in extensive experiments on public benchmarks and real video sequences. We believe that it brings a new perspective on the domain of monocular 3D recovery of articulated structures, including human motion capture.Comment: 21 pages, 8 figures, 2 table

Effect of Using Ginger Roots Powder and Pure Allicin in Fattening Awassi Lambs Rations on Productive Performance and the Accessory Cut Parts of Carcasses

   أُجري البحث بهدف دراسة تأثير إضافة الاليسين أو الزنجبيل أو خليطهما إلى علائق تسمين الحملان العواسية في الصفات الإنتاجية وبعض الأجزاء الثانوية للذبائح.     استعمل في البحث 28 حملاً عواسياً وزعت عشوائياً على أربعة معاملات متساوية كل معاملة احتوت 7 حملان ، غذيت الحملان على أربعة أنواع من العلائق التجريبية والتي كانت كالآتي: العليقة الأولى عليقة مركزة خالية من الإضافات الغذائية (سيطرة)، العليقة الثانية احتوت على الاليسين النقي بنسبة 3 كغم لكل طن علف مركز، العليقة الثالثة احتوت على مسحوق جذور الزنجبيل بنسبة 2 كغم لكل طن علف مركز أما العليقة الرابعة فقد احتوت على خليط من الاليسين (1.5 كغم/ طن علف مركز) ومسحوق جذور الزنجبيل (1كغم/ طن علف مركز).    غذيت الحملان بطريقة التغذية الجماعية ولمدة 91 يوماً ودرست الصفات الإنتاجية والتي تضمنت الزيادات الوزنية الكلية واليومية ومعامل التحويل الغذائي وكميات العلف المستهلك من الخشن والمركز.    ذبح 12 حملاً من حملان التجربة بواقع ثلاثة حملان من كل معاملة لغرض تسجيل أوزان الأجزاء الثانوية للذبيحة والتي شملت الرأس والجلد والأرجل.    أشارت نتائج البحث إلى عدم وجود فروقات معنوية بين المعاملات المدروسة للأوزان الابتدائية والنهائية والزيادات الوزنية اليومية والكلية، ولم تلاحظ فروقات معنوية في كميات العلف المركز والخشن المستهلك ومعامل التحويل الغذائي، و أوضحت نتائج البحث أيضاً عدم وجود فروقات معنوية في صفة الرأس للذبائح بين المعاملات المختلفة بينما كانت الفروقات معنوية (P<0.05) لصفة الجلد والأرجل.The research has been conducted to investigate the effect of ginger roots powder with allicin in the fattening of Awassi lambs rations with its effect on productive traits as well as the secondary cuts parts of carcasses. A total number of 28 Awassi lambs were used in the research , those lambs were randomly distributed into 7 treatments, lambs fed on 4 experimental rations as follows the first ration was concentrated ration without any supplement (control), the second ration supplemented with 3.0 kg/ton of allicin, the third ration supplemented with 2.0 kg/ton ginger powder, the fourth ration supplemented with a combination of allicin (1.5 kg /ton) and ginger powder (1.0 kg/ton). Lambs fed by group feeding along with the experiment which had been lasted 91 days. The productive traits were studied such as a daily and total weight gain as well as feed conversion ratio and the consumed quantity of concentrated and rough feed. Twenty-one lambs were slaughtered (three lambs for each treatment)  to study the secondary cuts parts of the carcasses. Results revealed no significant differences among treatments in the initial and final weights and daily and total weight gains.  There were no significant differences in the consumed feed among treatments and feed conversion ratio. Results indicated also nonsignificant differences in weights of the head among treatments. Meanwhile, there were significant differences (P<0.05) in skin and legs weights among treatments. &nbsp