Applying the sustainable development orientations in a municipality programme in South-West of France

This paper discusses how a sustainable development programme could be applied to a village in respecting to the, European, French and Regional regulations. Léguevin is a small village in the South-West of France near Toulouse. The environment problems are one of the major concerns of the community as well as to the politicians. For the new municipality council elected in 2008, a proposed environmental and sustainable development programme taken part in their new municipality engagement. A Plan Communal Environment has been adopted and taken into consideration of the orientations to preserve the environment. Several axes have been chosen and some of these are to reduce the communal buildings power consumption, transportation and water consumption, preserve water resources, eco purchase, population information and environmental education. Several measures have been taken such as significant reduction of power and water consumption, and increased the use of renewable resources. Also, encouraging eco purchase grouping, utilizing recycling papers, E-mail and others means. It could be concluded that even for a small village with a limited financial resources, the application of the sustainable development orientation could be achieved at local level

MODELLING of HEAT and MASS TRANSFER in the EVAPORATION of a BINARY MIXTURE in a FALLING FILM APPARATUS

A research on a mathematical modeling of simultaneous heat and mass transfer during the process of the evaporation of a saturated binary mixture of n Hexane-Toluene flowing down a tube has been carried out. The flow is characterized by a falling liquid film and the film theory model is used. The geometry retained is a cylindrical column with a smooth uniform heat flux. The objective of the study is to investigate the sensitivity of flow, heat and mass transfer parameters. Functioning and designing of this process on constant transfer parameters will be discussed. The findings show that a higher dependency on the liquid phase parameters along the column height, phase compositions and flux density are found. A further study of the variation of the transfer parameters as a function of the internal flow, composition and chemical properties could be introduced to the given model to establish a model behavior

Measuring and analyzing the major economic factors affecting the Iraqi dinar exchange rate ( An applied study in Iraq from the period 1996 – 2011 )

This research has attempted to study the effect of some of the economical factors on the Iraqi dinar exchange rate price from the period (1996 – 2011)  . The ( Minitab ) was adopted to obtain some evaluations for the indicators that were used to analyze and evaluate the nature of relationships among the variants of the research and their tendencies and also testing the hypotheses . The research has reached a series of conclusions related to both the theoretical and practical sides of the research , and through which the hypo theses of the research were verified . Some recommendations were reached , the main one was that Iraq must be in aware of the importance of correcting the violation resulted from the Iraqi dinar exchange price versus the American dollar exchange price as the Iraqi dinar being the main goal of the economic policy and the fundamental condition of developing the economic performance and the insurance of the total economic stability , and consequently , the violation of the price exchange rate had received a greater attention in the economic literature and in the establishment of the economic policies and the main reason of any economic instability . Achieving its stability is not an easy task . Achieving such tasks without knowing the affecting factors , and how to direct them would from a greater challenge . keywords : ( The Iraqi rate exchange , Rate inflation , Real  interest rate , Commercial openness indicator )

MICRO-APARTMENT IN PONTIANAK

As the world population, the majority of Indonesian’s town all knows an increase of their population that results in an augmentation of the housing needs. What is called Micro-housing is a new global trend that targets a younger worker part of the population and also a newly married couple that doesn’t have children yet. Indeed, this part of the population is in need to find house or apartment close to their workplace, close to the transportation of the city but also close to all the other town facilities like hospitals, restaurant, stores. This desire of finding a house or apartment in a strategic location known as the center of a town tends to increase but the available spaces to build more houses tend to decrease. That is why one of the solutions to this space problem is micro-housing; this type of new housing will allow responding to this problem of available space. This design project is not only about reducing space, but it is also focus on being able to design and create a layout space that responds to the multiple needs of the tenant by using multiple techniques in the design layout but also using transformable and foldable pieces of furniture

Classifying Three Stages of Cataract Disease using CNN

مقدمة:   من بين العديد من الأمراض التي تصيب شبكية العين هو الساد . يعتبر مرض الساد من أخطر مشاكل الصحة العامة الدوائية في الدول النامية.  يمكن أن يحدث  دون التسبب في أي أعراض. وهو يعتبر أحد الأسباب الرئيسية للعمى أو عدم وضوح الرؤية لكبار السن. لذلك ، فإن الاكتشاف الدقيق والمبكر لإعتام عدسة العين حسب شدة الحالة مطلوب للحفاظ على الرؤية ومنع الزيادة العالمية في العمى الناجم عن إعتام عدسة العين. كما هو الحال مع معظم الأمراض المتعلقة بالعيون، فقد ثبت أن العلاجات والتشخيص المبكر يمنعان فقدان البصر . و بالمقارنة مع طرق التشخيص اليدوية، تساعد أنظمة تحليل الشبكية الأوتوماتيكي في تقليل وقت للمرضى وتقليل التكلفة. اكتسبت طرق الكشف عن مرض عتمة العين المبنية على استخدام الذكاء الاصطناعي اهتمامًا كبيرًا في المجتمع العلمي. ينتج هذا البحث طريقة فعالة وقوية للتشخيص التلقائي لإعتام عدسة العين باستخدام الشبكة العصبية التلافيفية (CNN) لاكتشاف وتصنيف الساد تلقائيًا في صور قاع العين. يستخدم محسن آدم ومجموعة بيانات (ODIR) لتدريب النموذج. تتفوق الطريقة المقترحة على أحدث أنظمة الكشف عن المياه البيضاء بمتوسط ​​دقة 100٪ لفئتين (عادي، إعتام عدسة العين)، 96.9٪ لأربع فئات (عادي، خفيف، معتدل، شديد) وفقًا للنتائج التجريبية. طرق العمل: باستخدام شبكة Convolution العصبية (CNN) لاكتشاف وتصنيف إعتام عدسة العين تلقائيًا في صور قاع العين.. الاستنتاجات:    حيث يقترح هذا البحث نظام التشخيص الآلي لإعتام عدسة العين باستخدام الشبكة العصبية العميقة (DCNN). تمت معالجة مجموعة بيانات الساد لصور قاع العين مسبقًا وتحسينها لجعل مجموعة البيانات أكثر ملاءمة لتغذية الشبكة العميقة في البداية. تعمل الشبكة المقترحة في طبقات مختلفة، ودوال التنشيط ، ودوال الخسارة، وخوارزميات التحسين من أجل تقليل تكاليف الحوسبة مع الحفاظ على دقة النموذج. استخدم النظام المقترح طرق تكبير متعددة للصور ، ثم طبق النظام على هذه الصور المعززة لتقليل مشكلة فرط التجهيز وتحسين كفاءة النظام المقترح ، حيث تم الحصول على أفضل دقة لتصنيف 96.9 بالمائة لصور قاع العين التي تمت زيادتها قاعدة بيانات ODIR ، ولكن بنسبة 94 في المائة فقط عند تطبيق النظام على صور قاع العين الأصلية. عند مقارنته بأعمال أخرى مماثلة، كان أداء هذا النظام رائعًا. نظرًا لأن هذا النهج كان فعالًا للغاية من حيث التكلفة وتوفير الوقت اللازم لطبيب العيون، فقد كان فعالاً من حيث الوقت، قادراً على اكتشاف إعتام عدسة العين بشكل أسرع ودقيق مع عدد أقل من المعاملات المستخدمة في الشبكة وطاقة كمبيوتر أقل. كذلك في صور قاع الشبكية، فإن الطريقة المقترحة قادرة على اكتشاف مراحل الساد. وتم الكشف عن مراحل إعتام عدسة العين (خفيفة، معتدلة، وشديدة) بواسطة نظام DCNNs المقترح.      Among the many diseases that affect the retina, a cataract. It is one of the most serious pharmacological public health issues in developing nations, it can develop without causing any symptoms. It is one of the prime reasons for blindness or blurred vision for senior citizens. Therefore, accurate and early detection of cataracts depending on the severity of the condition is required to preserve vision and prevent the global increase in blindness caused by cataracts. As with most of the diseases related to the eyes, treatments, and early diagnosis have been shown to prevent visual loss and blindness. Compared with the manual diagnostic methods, automated retinal analysis systems help save patients' time, vision and cost. Artificial intelligence-based cataract detection methods have gained a lot of attention in the scientific community. This research produces an efficient and robust method for the automatic diagnosis of cataract by using Convolution Neural Network (CNN) for detection and classification cataract grading automatically in fundus images. It used Adam optimizer and (ODIR) dataset to train the model. The suggested method beats state-of-the-art cataract detection systems with an average accuracy of 100 % for two classes (Normal, Cataract) ,96.9% for four classes (Normal, Mild, Moderate, Sever) according to experimental results.  Materials and Methods: Used Convolution Neural Network for detection and classification cataract grading automatically in fundus images.  Results: The suggested method beats state-of-the-art cataract detection systems with an average accuracy of 100 %  for two classes (Normal, Cataract) ,96.9% for four classes (Normal, Mild, Moderate, Sever) according to experimental results. Conclusion: The proposed network looked at different layers, activation functions, loss functions, and optimization algorithms in order to reduce computing costs while maintaining model accuracy. The proposed system used multi-image augmentation methods, then implemented the system on these augmented images to decrease the issue of overfitting and to improve the efficiency of the suggested system, as best accuracy obtained for classification 96.9 percent was get for fundus images which augmented of ODIR dataset, but only 94 percent when the system was applied to the original fundus images. When compared to other similar works, this system performed admirably. Because this approach was extremely cost- effective, accurate, and ophthalmologists, time-efficient were able to detect cataract more quickly and accuracy with fewer parameters and less computer power.  In retinal fundus images, the suggested approach is able to detect cataract phases. The detection of cataract stages (mild, moderate, and severe) will be done by the DCNNs system

Reinforcement learning for graph theory, II. Small Ramsey numbers

We describe here how the recent Wagner's approach for applying reinforcement learning to construct examples in graph theory can be used in the search for critical graphs for small Ramsey numbers. We illustrate this application by providing lower bounds for the small Ramsey numbers $R(K_{2,5}, K_{3,5})$, $R(B_3, B_6)$ and $R(B_4, B_5)$ and by improving the lower known bound for $R(W_5, W_7)$.Comment: 6 page

Reinforcement learning for graph theory, I. Reimplementation of Wagner's approach

We reimplement here the recent approach of Adam Zsolt Wagner [arXiv:2104.14516], which applies reinforcement learning to construct (counter)examples in graph theory, in order to make it more readable, more stable and much faster. The presented concepts are illustrated by constructing counterexamples for a number of published conjectured bounds for the Laplacian spectral radius of graphs.Comment: 16 pages, 1 table, 8 figure

Modelling of heat and mass transfer in the evaporation of a binary mixture in a falling film apparatus

A research on a mathematical modeling of simultaneous heat and mass transfer during the process of the evaporation of a saturated binary mixture of n Hexane-Toluene flowing down a tube has been carried out. The flow is characterized by a falling liquid film and the film theory model is used. The geometry retained is a cylindrical column with a smooth uniform heat flux. The objective of the study is to investigate the sensitivity of flow, heat and mass transfer parameters. Functioning and designing of this process on constant transfer parameters will be discussed. The findings show that a higher dependency on the liquid phase parameters along the column height, phase compositions and flux density are found. A further study of the variation of the transfer parameters as a function of the internal flow, composition and chemical properties could be introduced to the given model to establish a model behavior

Data protection based neural cryptography and deoxyribonucleic acid

The need to a robust and effective methods for secure data transferring makes the more credible. Two disciplines for data encryption presented in this paper: machine learning and deoxyribonucleic acid (DNA) to achieve the above goal and following common goals: prevent unauthorized access and eavesdropper. They used as powerful tool in cryptography. This paper grounded first on a two modified Hebbian neural network (MHNN) as a machine learning tool for message encryption in an unsupervised method. These two modified Hebbian neural nets classified as a: learning neural net (LNN) for generating optimal key ciphering and ciphering neural net CNN) for coding the plaintext using the LNN keys. The second granulation using DNA nucleated to increase data confusion and compression. Exploiting the DNA computing operations to upgrade data transmission security over the open nets. The results approved that the method is effective in protect the transferring data in a secure manner in less tim

Survey of Features Extraction and Classification Techniques for Speaker Identification

تكسب تقنيات معالجة الكلام شيوعًا اكثر يومًا بعد يوم لتوفير قدر هائل من الأمان.كما يشيع استخدام الكلام لغرض التوثيق. التعرف على المتكلم هو الطريقة التي يمكن من خلالها فحص المتكلم والتعرف عليه. يختلف نظام التعرف على الكلام عن طريقة التعرف على المتكلم. يشيع استخدام التعرف على المتكلمين في القطاعات والمستشفيات والمختبرات وما إلى ذلك. فوائده أكثر أمانًا وأسهل في التنفيذ وأكثر سهولة في الاستخدام. تعد طريقة تحديد المتكلم واحدة من أكثر التقنيات شيوعًا في المنطقة حيث تعتبر السلامة أمرًا بالغ الأهمية. تقدم هذه المقالة نظرة عامة على الطرق المختلفة التي يمكن استخدامها للتعرف على المتكلمين مثل الترميز الخطي التنبؤي (LPC) ، معاملات الطيف التنبؤية الخطية (LPCC) ، التحويل الحقيقي الفريد المعين (UMRT) ، معاملات Cepstral الحقيقية (RCC) ، "تردد ميل Cepstrum" (MFCC).   بالإضافة إلى مجموعة من المصنفات المختلفة مثل "نموذج الخليط الغاوسي (GMM)"، "تزييف الوقت الديناميكي (DTW)" ، آلة المتجهات الداعمة (SVM) ، الشبكة العصبية (NN) ، "تكميم المتجهات" (VQ). الغرض الأساسي من شرح طرق التعرف على السماعات الشائعة. النتائج التي تم الحصول عليها هي أنه تم اختيار MFCC لكفاءة عالية ومنخفضة التعقيد. و GMM مفيد في تصنيف ذاكرة أقل ونتائج تخطيط واختبار أقل.Speech processing is more common day by day to provide enormous safety. The speech for the purpose of authentication is commonly used. Recognition of the speaker is the method that can check and recognize the speaker. The scheme of speech recognition is distinct from the scheme of speaker recognition. Recognition of speakers is commonly used in sectors, hospitals, laboratories, etc. Its benefits are safer, easier to implement, more user-friendly. Speaker identification method is one of the most commonly used techniques for the region where safety is very crucial. This article presents an overview of various methods that can be used to recognize speakers’ systems, the feature extraction techniques such as Linear Predictive Coding (LPC), Linear Predictive Cepstral Coefficients (LPCC), Unique Mapped Real Transform (UMRT), Real Cepstral Coefficients (RCC), “Mel-frequency Cepstrum” (MFCC), in addition to  various classification techniques such as “Gaussian mixture model (GMM)”, “Dynamic Time Warping (DTW)”, Support Vector Machine (SVM), Neural Network (NN), “Vector Quantization” (VQ). The primary purpose of is to explain the common speaker recognition methods. The obtained results are that, MFCC is chosen for high efficiency and low complexity. and GMM is helpful in classifying less memory and less planning and efficient test results