The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

The article characterizes metaphors and comparisons as a means of rethinking the phenomena of the surrounding world; two directions are named within which metaphors and comparisons are studied: 1) the linguo-classification direction combines several classifications of metaphors and comparisons, which are basically focused on comparing two denotations through the meanings of word forms that are part of the trope; 2) the theoretical and conceptual direction is associated with the concept of conceptual displacement and is the basis of the theoretical and methodological study of metaphor and comparison, i.e. the modern theory of metaphor is being formed; The main attention is focused on the comparative concept of Aristotle, which postul

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 paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

A laboratory experiment was carried out and repeated at field of College of Agricultural Engineering Sciences, University of Baghdad in 2017. First factor was three cultivars of lupine 'Giza-1', 'Giza-2' and 'Hamburg'. Second factor was three seed weights (lower weight, medium weight and higher weight) which was following the cultivars factor. Nested design was used. Results showed supremacy of 'Giza-1' cultivar significantly and gave higher germination ratio, radical length, seedling dry weight, seedling vigour index, field emergence ratio, plant height and number of leaves per plant. The treatment ('Giza-1'×higher seed weight) was supremacy significantly and gave higher germination ratio, radical length, plumule length, and seedling vigo

The latest open commercial markets among countries, shift of capitals, and rise of mass economic, large international organizations, and international contracts leaded to a great increase of competition among countries for attracting capital for investments, specially among under developing countries which had bad economic situation, and which thinks that investment is the best solution to solve their old economic problems.

Developing small, and medium establishments in all economic sectors became the main economic force and natural resources for the development and growth of under developing countries. Small and medium establishments became the majority of any country establishments, and the past international experience shows t

أختير مشروع مزرعة فدك في محافظة النجف االشرف المستثمر من العتبة العلوية المقدسة. يقع المشروع في الجهة الشمالية شرقا ة عرض ''54.38 '57 º31 الـــــــــــى ً الغربية لمحافظة النجف االشرف بين خطي طول ''18.78 '0 º 44 الى ''53.46 '7 º44 ودائر ''17.53 '2 º32 شماال بمساحة اجمالية للمشروع تقدر بـــ 35493 هكتار لتقييم بعض الصفات الكيميائية للترب الصحراوية في تحديد دليل نوعيتها وصحتها لمشروع مزرعة فدك/ محافظة النجف االشرف، اذ تم اخذ 40 عينة سطحية