An Approach to Calculate Exact Coverage Area for Connected Wireless Sensor Network

واحدة من التقنيات المتقدمة المستخدمة في أنظمة الاتصالات للشبكة الذكية هي شبكة الاستشعار اللاسلكية (WSN). WSN لديها مجموعة واسعة من التطبيقات تغطي العديد من المجالات مثل، إدارة الكوارث، اكتشاف حقل المعركة، التأمين على الحدود، مراقبة صحة المرضى، وغيرها. أن مشاكل الربط والتغطية للمستشعرات في الآونة الاخيرة لها أهمية عظيمة.  في البحث، قمنا بعرض الاتصال وتغطية العقد في WSN, تم اعداد خوارزمية لحساب مساحة التغطية المضبوطة لمجموعة عقد شبكة الاستشعار بالتوزيع المتجانس المستوي لنموذج القرص البسيط. هذه الخوارزمية تعتمد ارتباطات العقد ضمن مدى الاتصالات الاقصى للعقدة لذلك لايوجد في المساحات مناطق منفصلة. في حين تم احتساب كل المساحات غير المغطاة بالاستشعار ضمن المنطقة قيد الاهتمام (RoI) ضمن المساحة المغطاة. لذا تم احتساب النسبة المئوية للمساحة المغطاة بالضبط. ان استخدام هذه الطريقة سيكون الحجر الاساس للدراسات التي تتطلب سيطرة أفضل لنشر عقد المتحسسات. One of the advanced technologies used in the communicating systems of the intelligent grid is Wireless Sensor Network (WSN). WSN has a wide range of applications covers many fields like catastrophe management, hostilities field recognition, border insurance, patient health monitoring, and others. The sensor connectivity and coverage problems recently have a great attention. In this paper, we presented the connectivity and coverage of nodes in WSN, a new algorithm is prepared to extract exact coverage area of plain uniform depletion of node samples according to simple disk model. This algorithm considers the connection of nodes within maximum range of transmission communications, therefore no disconnected graph occurs. While uncovered area within region of interest (RoI) inside coverage area is calculated, although many uncovered regions occurred. So the coverage percentage area is calculated in an exact solution. This algorithm will be one of keystone study to better control of sensor depletion.    &nbsp

HUMAN GENDER CLASSIFICATION USING KINECT SENSOR: A REVIEW

Human Gender Classification using Kinect sensor aims to classifying people’s gender based on their outward appearance. Application areas of Kinect sensor technology includes security, marketing, healthcare, and gaming. However, because of the changes in pose, attire, and illumination, gender determination with the Kinect sensor is not a trivial task. It is based on a variety of characteristics, including biological, social network, face, and body aspects. In recent years, gender classification that utilizes the Kinect sensor became a popular and essential way for accurate gender classification. A variety of methods and approaches, like machine learning, convolutional neural networks, sport vector machine (SVM), etc., have been used for gender classification using a Kinect sensor. This paper presents the state of the art for gender classification, with a focus on the features, databases, procedures, and algorithms used in it. A review of recent studies on this subject using the Kinect sensor and other technologies is provided, together with information on the variables that affect the classification\u27s accuracy. In addition, several publicly accessible databases or datasets are used by researchers to classify people by gender are covered. Finlay, this overview offers insightful information about the potential future avenues for research on Kinect-based human gender classification

PERFORMANCE ANALYSIS OF QUADRATURE CHAOS SHIFT

One of the most famous techniques of non-coherent differential chaos shift keying (DCSK) is Quadrature chaos shift keying (QCSK) system, this system suffered from lowering the data rate and increasing the bit energy during the bit transmission even though its rate doubling the one of the DCSK. Short reference (SR) algorithm is proposed for the QCSK system to design the SR-QCSK communication system that enhances these drawbacks. The main idea of the short reference technique is minimizing the length of the reference chaotic signal (β) at a transmitter by a factor P comparing to produce R samples for the new reference signal while the length of the information-bearing signal remained unchanged, this occurs by duplicating the reference signal P times to get the same length as the conventional QCSK. Therefore, the symbol duration is reduced from 2βTc to (R+β)Tc. The data rate and energy saving improvement factor in a percent form is derived and compared with the QCSK and DCSK systems. Also, the BER analytical expression is derived for the SR-QCSK in additive white Gaussian noise and Rayleigh fading channel. The experimental simulation results proved that the theory derivation gives a good analysis tracking for the BER performance. The SR-QCSK system is compared with other DCSK techniques and the simulation results show that it has a superior performance in the multipath Rayleigh fading channel

ROBUST HYBRID FEATURES BASED TEXT INDEPENDENT SPEAKER IDENTIFICATION SYSTEM OVER NOISY ADDITIVE CHANNEL

Robustness of speaker identification systems over additive noise is crucial for real-world applications. In this paper, two robust features named Power Normalized Cepstral Coefficients (PNCC) and Gammatone Frequency Cepstral Coefficients (GFCC) are combined together to improve the robustness of speaker identification system over different types of noise. Universal Background Model Gaussian Mixture Model (UBM-GMM) is used as a feature matching and a classifier to identify the claim speakers. Evaluation results show that the proposed hybrid feature improves the performance of identification system when compared to conventional features over most types of noise and different signal-to-noise ratios

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CONSORT 2010 checklist of information to include when reporting a randomised trial*.

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List of interventions.

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Map of Saudi Arabia with distribution of participating ICUs.

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Distribution of compliance, non-compliance and contraindications (with reasons) to the interventions.

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List of participating sites and ethics committee approvals.

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