Encrypting of Text Based on Chaotic Map

 مقدمة:        نظرًا للتوسع السريع للإنترنت مؤخرًا، أصبح الأمان مشكلة حاسمة عند نقل البيانات الرقمية عبر قنوات غير آمنة. يمكن تطبيق     ذلك من خلال استخدام طرق تشفير يمكن الاعتماد عليها. قدم هذا البحث نظامًا لتشفير النص لإنشاء قواعد بيانات آمنة. طرق العمل:          يستخدم البحث خريطة فوضوية مبنية على خريطة لوجستية نظرا لتطبيقها الواسع في البحث العلمي، حيث يتم استخدام عدة عمليات لتنفيذ نشاط التشفير. أولاً، تم تنسيق النص في مصفوفة ثنائية الأبعاد من الأرقام المحولة إلى متجه. ثانيًا، لإنشاء تسلسل لاستخدامه في عملية التشفير، يتم استخدام النظام الفوضوي. ثالثًا، فرز المتجه الذي تم إنشاؤه من أجل خلط القيم النصية بناءً عليه. تتضمن الخطوة الأخيرة ترميز النص المخفوق باستخدام عملية حسابية. أيضًا، هناك العديد من الخطوات المستخدمة في عملية فك التشفير. في الخطوة الأولى، يتم استخدام نفس الأسلوب الرياضي لفك تشفير النص المشفر بعد إنشاء التسلسل الفوضوي المتطابق. في الخطوة الثانية، يتم تفكيك القيم الممزوجة للحصول على النص الذي تم فك تشفيره. الاستنتاجات:          أظهرت النتائج التجريبية أن الطريقة المقترحة تحصل على قيمة ممتازة للإنتروبي تساوي (0.9955) ومعامل الارتباط يساوي      (-0.0024) وتأثير الانهيار الجليدي يساوي (0.5120) وكذلك النظام المقترح الذي تم فحصه تحت اختبارات NIST حصل على نتائج جيده (> 0.01) وتم فحصها لعدة ملفات أخرى والحصول على نتائج جيدة، من حيث اختبارات وقت التنفيذ، تم تطبيق النظام المقترح في فترة زمنية قصيرة.Background:                         Due to the internet's recent rapid expansion, security has become a crucial issue when transmitting digital data via unsecure channels. This can be applied by employing dependable encryption methods. This research brought forward a text encryption system order to create safe databases. Materials and Methods:         The research uses a chaotic map based on a logistic map Due to its widespread application in scientific research. Several processes are used to carry out the encryption activity. Firstly, the text is formatted in 2D matrix of numbers converted into vector. Secondly, to create a sequence for using it in the encryption process, the chaotic system is employed. Thirdly, sorting the generated vector in order to scramble the text values based on it. The final step involves encoding the scrambled text using a mathematical operation. Also, there are many steps used in the decryption process. In the first step, the same mathematical technique is used to decrypt the encrypted text after the identical chaotic sequence has been generated. In the second step, the scrambled values are descrambled to obtain the decrypted text. Results:        The experimental results demonstrate that the suggested approach obtain an excellent value of entropy equal to (0.9955) and Correlation coefficient equal to (-0.0024) and Avalanche effect equal to (0.5120) as well as the proposed system examined under NIST tests and obtain a good results (>0.01) and examined for multiple other files and obtain a good results, in terms of execution time tests, the proposed system applied in a short amount of time. Conclusion:      The proposed system matched the criteria for encryption techniques in terms of high sensitivity for initial values, high security, high randomizing Whatever text is to be encrypted. Also the proposed system can be applied for real time application due to its Short implementation time

Classification of EEG Signal by Using Optimized Quantum Neural Network

In recent years the algorithms of machine learning was used for brain signals identifing which is a useful technique for diagnosing diseases like Alzheimer's and epilepsy. In this paper, the Electroencephalogram (EEG) signals are classified using an optimized Quantum neural network (QNN) after normalizing these signals, wavelet transform (WT) and the independent component analysis (ICA), were utilized for feature extraction.  These algorithms used to reduces the dimensions of the data, which is an input to the optimized QNN for the purpose of performing the classification process after the feature extraction process. This research uses an optimized QNN, a form of feedforward neural network (FFNN), to recognize (EEG) signals. The Particle swarm optimization (PSO) algorithm was used to optimize the quantum neural network, which improved the training process of the system's performance. The optimized (QNN) provided us with somewhat faster and more realistic results. According to simulation results, the total classification for (ICA) is 82.4 percent, while the total classification for (WT) is 78.43 percent; from these results, using the ICA for feature extraction is better than using WT

Electrocardiograph signal recognition using wavelet transform based on optimized neural network

Due to the growing number of cardiac patients, an automatic detection that detects various heart abnormalities has been developed to relieve and share physicians’ workload. Many of the depolarization of ventricles complex waves (QRS) detection algorithms with multiple properties have recently been presented; nevertheless, real-time implementations in low-cost systems remain a challenge due to limited hardware resources. The proposed algorithm finds a solution for the delay in processing by minimizing the input vector’s dimension and, as a result, the classifier’s complexity. In this paper, the wavelet transform is employed for feature extraction. The optimized neural network is used for classification with 8-classes for the electrocardiogram (ECG) signal this data is taken from two ECG signals (ST-T and MIT-BIH database). The wavelet transform coefficients are used for the artificial neural network’s training process and optimized by using the invasive weed optimization (IWO) algorithm. The suggested system has a sensitivity of over 70%, a specificity of over 94%, a positive predictive of over 65%, a negative predictive of more than 93%, and a classification accuracy of more than 80%. The performance of the classifier improves when the number of neurons in the hidden layer is increased

Improving the quality of architectural learning outcomes in Iraq

The research is concerned with the development of the quality of the learning outcomes through the development of a general system and a road map in order to make a qualitative leap in these outputs. This requires knowledge of the nature of the contemporary global intellectual climate (the climate of globalization) In the developed world. If specialized architectural knowledge is one of this economic knowledge, the graduates of this specialization are a feature of that knowledge that characterizes the country and carry cultural characteristics in addition to the qualities of their architectural specialization in order to practice their profession and provide the local labor market and then the world with their skills and expertise of the quality of excellence Scientifically and practically. This requires the knowledge of the nature of educational thought with its different philosophies and theories, which contribute effectively to the creation of an environment of architectural learning and the formation of those skills and specialized architectural expertise, and then to identify the quality features in architectural education, which is an integral part of the quality of higher education. The problem of research was to determine the quality requirements of the architectural learning outcomes in Iraq within a temporal space compatible with the contemporary intellectual climate, assuming a comprehensive strategic system for the different intellectual contexts affecting the architectural education under one intellectual umbrella to achieve the objective of research in building the ground for the development of architectural education. Which outlines the requirements for the quality of these outputs, and this is what the research done specifically through the development of a general framework for it. To come up with a set of conclusions and recommendations that emphasize the importance of taking into account the impact of global thought and educational thought and the conditions and standards of quality of architectural education by placing them within one system of development that takes into account the conditions of specialization and local culture and market needs

Investigation of effective parameters in the production of alumina gel through the sol-gel method

Sol-gel chemistry is currently applied as one of the most widely used methods for synthesis of nanoparticles. In this method hydrolysis and poly-condensation reactions occur when the gel precursors are mixed with water and catalyst. The further condensation of sol particles into a three-dimensional network produces a gel. There are several parameters that effect on gelation time such as the molar ratio of alkoxide to water, the rate of hydrolysis, the type and amount of catalyst used, initial concentration of precursors and the temperature of hydrolysis and drying. Encapsulated solvent can be removed from a gel by either evaporative drying or supercritical drying. Where the resulting solids are known as a xerogel and an aerogel, respectively. During the drying process due to the surface tension of the liquid, a capillary pressure gradient is built in the pore walls, which is able to collapse most part of the pore volume. The volume shrinkage may be prevented by supercritical drying. The strength, thermal stability, pore structure and morphology of aerogels are keys to success for wider applications such as catalyst supports, thermal and acoustic insulators and adsorbents. Among catalyst support materials, alumina became popular recently due to its highly thermal and chemical stability and higher porosity. In the present study, synthesis of alumina gel as a support for nano-catalysts through hydrolysis of aluminum tri-sec-butoxide (ASB) in ethanol was investigated. The gel synthesis was carried out at 32 and 60 °C with different concentrations of water and precursor and different types and amounts of acid as catalyst. Rate of gel formation, efficiency of hydrolysis and polymerization and amount of gel production were measured and discussed. Results showed that acid addition around 0.2 ml and water to ASB malar ratio of 2 at 60 °C maximized the amount of gel produced and minimized the gelation time. Then, the alumina gel that synthesized at optimum conditions was dried by two different methods, at atmospheric pressure and temperature and at supercritical conditions of carbon dioxide and the results of Scanning Electron Microscopy were compared

Nanomaterials as transmitters of non-viral gene vectors: A review

With the rapid development of nanotechnology in the recent decade, novel DNA and RNA delivery systems for gene therapy have become available that can be used instead of viral vectors. These non-viral vectors can be made of a variety of materials, including inorganic nanoparticles, carbon nanotubes, liposomes, protein and peptide-based nanoparticles, as well as nanoscale polymeric materials. They have as advantages over viral vectors a decreased immune response, and additionally offer flexibility in design, allowing them to be functionalized and targeted to specific sites in a biological system with low cytotoxicity.gene therapy keeps hopes a life for the treatment of a wide range of diseases such as cancer, nano particles are now known as promising carriers for the effective and safe vectors of genes to specific cells or tissues. This could provide alternative therapies for conventional approaches that use viruses as gene carriers. The expression of genetic material such as DNA, RNA into cells and tissues has raised considerable hopes for therapeutic and diagnostic purposes. But getting nucleic acids into the cell also faces challenges. These challenges are less for non-virus carriers as a gene and drug vectors method than for viral or free vectors and are therefore considered less risky and more appropriate. of expanding nonverbal nano carriers, we will look at a few of these nano carriers, penicillin, PEI, PLGA, silica, block copolymer, Quantum dot, gold nano particles, and common carbon nano tubes. Problems include the use of nano particles such as polymer nano particles, liposomes, solid lipid particles, in targeted gene vectors will be investigated. Gene-based therapy is the intentional modulation of gene expression in specific cells to treat pathological conditions. This modulation is accomplished by introducing exogenous nucleic acids such as DNA, mRNA, small interfering RNA (siRNA), microRNA (miRNA) or antisense oligonucleotides. Given the large size and the negative charge of these macromolecules, their delivery is typically mediated by carriers or vectors. In this Review, we introduce the biological barriers to gene delivery in vivo and discuss recent advances in material sciences, nanotechnology and nucleic acid chemistry that have yielded promising non-viral delivery systems, some of which are currently undergoing testing in clinical trials. The diversity of these systems highlights the recent progress of gene-based therapy using non-viral approaches