The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

Portable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail,  appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls,  intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fu

The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

In this paper a new method is proposed to perform the N-Radon orthogonal frequency division multiplexing (OFDM), which are equivalent to 4-quadrature amplitude modulation (QAM), 16-QAM, 64-QAM, 256-QAM, ... etc. in spectral efficiency. This non conventional method is proposed in order to reduce the constellation energy and increase spectral efficiency. The proposed method gives a significant improvement in Bit Error Rate performance, and keeps bandwidth efficiency and spectrum shape as good as conventional Fast Fourier Transform based OFDM. The new structure was tested and compared with conventional OFDM for Additive White Gaussian Noise, flat, and multi-path selective fading channels. Simulation tests were generated for different channels

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

Growing interest in the subject of corporate governance after the repercussions of financial collapses of some of the leaders of American companies and European, and the consequent crisis of confidence in global financial lists of companies due to weak accounting disclosure and transparency, was quick from many countries and international organizations to adopt the concept in an attempt to improve the situation of companies and promote transparency and prevent further financial crises in the future. Based on this background, the present study aims to shed light on the concept of exercising the powers of governance that has become invitations for adoption in Iraq of great importance, given the increasing role of corporations both restrict

تتطلب كرة القدم الحديثة تطوير الصفات البدنية والمهارية للوصول باللاعب إلى لمستويات العليا، ولما كانت هذه الصفات مرتبطة مع بعضها البعض، فانها تتطلب ان يتم تطويرها معا في نفس الوقت دون تنمية كل صفة على حده، وإن توافر الحد الأدنى من الصفات البدنية كمتطلبات أساسية للأداء المهاري يعتبر الهدف الأساسي للتخطيط لأي برنامج تدريبي، وإن الصفات البدنية لها مفهوم شاسع وواسع الاستعمال في مجال البحوث الرياضية، وقد أعطيت ع

The research has  focused on accounting for marketing risks faced by banks because they are exposed to a high level of risk as a result of their great utilization of financial instruments, which may make them liable to insolvency or bankruptcy and collapse, and accordingly to major economic crises. Therefore, banks are required to manage (reduce) risks so as to prevent them. As Iraqi banks don^'t manage these risks according to modern methodology of using derivatives, as well as lack of both the standard accounting system for banks and the Iraqi accounting criterion (standard) No. 10 to an obvious methodology for these risks identification, classification, hedging and disclosure, the researchers was prompted to concentrate