6 research outputs found

    تحليل العوامل للتكاليف الإنتاجية والتنبؤ بإنتاجية أهم المحاصيل الحقلية في مصر

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    The research problem is to answer the question: What are the main components of the production costs items for the most important field crops (wheat, rice, summer maize) in Egyptian agriculture? Are there changes in the area of these crops? In achieving its goals, the research relied on a descriptive and quantitative analysis method, relying on tabular and graphical presentation, percentages, engineering and mathematical averages, and growth rates, in addition to Runs Test, Factor Analysis using the major or fundamental component analysis method (PCA) for the most important Items of costs (workers’ wages, seeds, fertilizers, mechanization, other) of the field crops under study question. The research reached a number of results, including: •Wheat crop: From the test runs of the wheat crop area in the four geographical regions during the study period, it is noted that the number of courses during the study period reached two courses for the sea side, 4 courses in Middle Egypt, 6 courses for the tribal face and the total of the republic, and it is expected that the value of acre productivity in In 2024 to 20.9 million erdeb for Lower Egypt and Middle Egypt, 16.7 million erdeb for Upper Egypt, 20.7 million erdeb for the total Egypt. •Rice crop: Results of the test runs for the rice crop area in the four geographical regions during the study period. It is noted that the number of courses during the study period reached 8 courses for the sea side and the total of the republic, 11 courses in Middle Egypt, 7 courses for the tribal face, and it is expected that the value of acre productivity In the year 2024 to 3.4 million tons for Lower Egypt and the total Egypt, 3.5 million tons for Middle Egypt, 4.3 million tons for Upper Egypt. •Maize crop: Runs test for the rice crop area in the four geographical regions during the study period, from which it is noted that the number of courses during the study period reached 14 courses for Lower Egypt, 6 courses in Middle Egypt, 4 courses for Upper Egypt and the total of the Republic, and it is expected that the value of productivity will reach to 25.8 million erdeb in 2024 for Lower Egypt, 22.3 million erdeb for Middle Egypt, 17.8 million erdeb for Upper Egypt, 23.6 million erdeb for the total Egypt. تتمثل مشكلة البحث في الإجابة على التساؤلات التالية: ما هي المكونات الأساسية لبنود التكاليف الإنتاجية لأهم المحاصيل الحقلية (القمح، الأرز، الذرة الشامية الصيفية) في الزراعة المصرية؟ وهل هناك تغيرات فى المساحة لهذه المحاصيل؟ واعتمد البحث في تحقيق أهدافه على أسلوب التحليل الوصفي والكمي، معتمداً على العرض الجدولي والبياني، والنسب المئوية، والمتوسطات الحسابية والهندسية، ومعدلات النمو، بالإضافة إلى اختبار الأشواطRuns Test، تحليل العوامل Factor Analysis باستخدام طريقة تحليل المكون الرئيسي أو الأساسي Principle Component Analysis “PCA” لأهم بنود التكاليف (أجور العمال، التقاوي، الأسمدة، الميكنة، أخرى) للمحاصيل موضع البحث، وتوصل البحث إلى عدد من النتائج منها: • محصول القمح: من اختبار الأشواط لمساحة محصول القمح بالمناطق الجغرافية الثلاثة بالإضافة إلى إجمالي الجمهورية خلال فترة الدراسة، يُلاحظ أن عدد الدورات خلال فترة الدراسة بلغ دورتين للوجه البحري، 4 دورات في مصر الوسطى، 6 دورات للوجه القبلي وإجمالي الجمهورية، ومن المتوقع أن تصل قيمة الإنتاجية الفدانية في عام 2024 إلى 20.9 مليون أردب للوجه البحري ومصر الوسطى، 16.7 مليون أردب للوجه القبلي، 20.7 مليون أردب لإجمالي الجمهورية. • محصول الأرز: نتائج اختبار الأشواط لمساحة محصول الأرز بالمناطق الجغرافية الأربعة خلال فترة الدراسة، يُلاحظ أن عدد الدورات خلال فترة الدراسة بلغ 8دورات للوجه البحري وإجمالي الجمهورية، 11 دورات في مصر الوسطى، 7 دورات للوجه القبلي، ومن المتوقع أن تصل قيمة الإنتاجية الفدانية في عام 2024 إلى 3.4 مليون طن للوجه البحريوإجمالي الجمهورية، 3.5 مليون طن لمصر الوسطى، 4.3 مليون طن للوجه القبلي. • محصول الذرة الشامية: اختبار الأشواط لمساحة محصول الأرز بالمناطق الجغرافية الأربعة خلال فترة الدراسة، ومنها يُلاحظ أن عدد الدورات خلال فترة الدراسة بلغ 14 دورة للوجه البحري، 6 دورات في مصر الوسطى، 4 دورات للوجه القبلي وإجمالي الجمهورية، ومن المتوقع أن تصل قيمة الإنتاجية الفدانية في عام 2024 إلى 25.8 مليون أردب للوجه البحري، 22.3 مليون أردب لمصر الوسطى، 17.8 مليون أردب للوجه القبلي، 23.6 مليون أردب لإجمالي الجمهورية. الكلمات الدليلية: تحليل العوامل Factor Analysis، اختبار الأشواط Runs Test، التنبؤ، الإنتاجية

    Structure Learning for Activity Recognition in Robot Assisted Intelligent Environments

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    Abstract-This paper presents a novel structure learning algorithm for the creation of distributed Bayesian networks over static and mobile Vision Sensor Network (VSN) nodes. These compose an assistive, intelligent environment for activity recognition. We provide results demonstrating a higher level of accuracy in the recognition of fine motor tasks when the environment is augmented with a mobile robot and show the ability of our learning algorithm to reduce VSN communication compared to a naïve, greedy structure learning technique. I. INTRODUCTION UE to recent advances in medical care and the adoption of increasingly healthy lifestyles, we are witnessing a demographic shift towards an increasingly aged population Where environments are to contain multiple ambient sensors, installation may be performed by a visiting carer or those living within the domicile. Consequently, it is unreasonable to expect these to be located at optimal locations for the determination of individual activities. Furthermore, since each dwelling is unique, their relative positioning can not be assumed prior to installation thus there is a strong requirement for such networks to be self configuring. To this end, we provide a structure learning algorithm for Bayesian networks which is considerate of both inference and communication cost within ambient Vision Sensor Networks (VSNs). Using Pearl's message propagation algorithm, activity inference can be implemented in a distributed manner over the VSNs, without the requirement for a centralized data repository. Where assistive robots are present, our algorithm can seamlessly incorporate such data to augment recognition accuracy. We demonstrate the efficacy of this algorithm in a home healthcare scenario for fine motor tasks occurring at several locations within the environment. II. RELATED RESEARCH For detecting Activities of Daily Living (ADLs), omnidirectional cameras [6] have previously been employed to capture behavioral patterns in a household environment. For example, a system operating at multiple resolutions has been defined, with a wide angle camera directing the pan, tilt and zoom of other camera

    GWMAC- A TDMA Based MAC Protocol for a Glacial Sensor Network

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    Wireless sensor networks demand the need to design practical and robust communication protocols to meet the application specifications. Our research focuses on designing and implementing an environmental sensor network to be used for sub-glacial study. The glacier is a very hostile environment presenting severe challenges and complications in the smooth functioning of such a network. In light of these challenges, we present a low power sensor node design and an energy-efficient medium access control protocol called GWMAC developed for a network deployed in a glacier in Norway. The general architecture of GWMAC is based on scheduling and time division multiple accesses (TDMA). We argue that for a highly dynamic network such as ours, GWMAC is more desirable over more widespread protocols such as S-MAC and LMAC. In doing so, we perform extensive series of simulations to empirically evaluate our claim. Our results illustrate that on average GWMAC can increase the network life time by at least 63%. This also has a significant effect on the amount of data that can be collected over network life time

    A self-optimising portable FES system using an electrode array and movement sensors

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    A portable functional electrical stimulation system has been designed using embedded systems technology. The system, which was applied to patients suffering from foot drop, uses sensors to monitor foot movement and orientation in a unique way, uses sophisticated algorithms for feedback, and drives an array of surface electrodes for stimulation. This system meets British Standards and safety requirements for medical equipment. A new technique was invented based on using the twitch response of muscles to optimise the configuration of the electrode array. This reduces the setup time in the clinic. Using feedback from the sensors, the optimum configuration of electrodes is chosen to produce correct stimulation and movement in real time. The instrument presents the patient with a ranked list of electrode combinations that are likely to be optimum; the patient can then choose a combination that is both effective and comfortable. The system is also able to vary the chosen pattern of electrodes and the stimulation signal parameters during the stimulation process. This may enable some problems associated with fatigue and skin irritation to be reduced. Trials were carried on 30 controls and 12 patients to test the instrument and study and develop the system optimisation and control algorithms. These preliminary clinical trials showed that control of the stimulation during walking, based on the optimisation algorithms developed in this work, gives high quality correction of foot drop. This was shown by gait assessment analysis by the physiotherapists involved in the project and blind assessment using independent researchers. These trials prove that the concept of using the electrode array for stimulation has advantages over using a conventional 2-electrode system

    PPAR agonists as effective adjuvants for COVID-19 vaccines, by modifying immunogenetics: a review of literature

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    Abstract Background Several coronavirus vaccine have been fast-tracked to halt the pandemic, the usage of immune adjuvants that can boost immunological memory has come up to the surface. This is particularly of importance in view of the rates of failure of seroconversion and re-infection after COVID-19 infection, which could make the vaccine role and response debatable. Peroxisome proliferator-activated receptors (PPARs) have an established immune-modulatory role, but their effects as adjuvants to vaccination have not been explored to date. Main body of the abstract It is increasingly recognized that PPAR agonists can upregulate the levels of anti-apoptotic factors such as MCL-1. Such effect can improve the results of vaccination by enhancing the longevity of long-lived plasma cells (LLPCs). The interaction between PPAR agonists and the immune system does not halt here, as T cell memory is also stimulated through enhanced T regulatory cells, antagonizing PD-L1 and switching the metabolism of T cells to fatty acid oxidation, which has a remarkable effect on the persistence of T memory cells. What is even of a more significant value is the effect of PPAR gamma on ensuring a profound secretion of antibodies upon re-exposure to the offending antigen through upregulating lipoxin B4, therefore potentially assisting the vaccine response and deterring re-infection. Short conclusion In view of the above, we suggest the use of PPAR as adjuvants to vaccines in general especially the emerging COVID-19 vaccine due to their role in enhancing immunologic memory through DNA-dependent mechanisms
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