<p><span>This research deals with the feasibility of a mobile robot to navigate and discover its location at unknown environments, and then constructing maps of these navigated environments for future usage. In this work, we proposed a modified Extended Kalman Filter- Simultaneous Localization and Mapping (EKF-SLAM) technique which was implemented for different unknown environments containing a different number of landmarks. Then, the detectable landmarks will play an important role in controlling the overall navigation process and EKF-SLAM technique’s performance. MATLAB simulation results of the EKF-SLAM technique come with better performance as compared with an odometry approach performance in terms of measuring the

In recent years, there has been a rise in interest in the study of antibiotic occurrence in the aquatic environment due to the negative consequences of prolonged exposure and the potential for bacterial antibiotic resistance. Most antibiotic residues from treated wastewater end up in the aquatic environment as they are not eliminated in facilities that treat wastewater. Antibiotics must be identified in influent and effluent wastewater using reliable analytical techniques for several reasons. Firstly, monitoring antibiotic presence in aquatic environments. Secondly, assessing environmental risks, computing wastewater treatment plant removal efficiencies, and estimating antibiotic consumption. Therefore, this work aims to provide an overview

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonic

The aim of the research is to identify the extent of the direct and indirect relationship of the population growth of the cities as a result of the urbanization process witnessed by the Arab region for the urban development of the city structures and their formative structures, changing the planning criteria of some cities and the extent of their changes in spatial and temporal dimensions and their relation to the standards of the western cities. In changing the concept of the modern Arab city, such as the emergence of new functional uses affecting the change in the pattern of formal formations of its urban fabric associated with its ancient morphology and distinctive human nature. The research seeks to identify the extent to which plann

Abstract:

                 The research aims to clarify the impact of adopting the IFRS16 financial reporting standard on lease contracts in insurance companies on audit procedures. The change in the classification of lease contracts in the case of adopting the IFRS16 financial reporting standard necessarily requires audit procedures that are compatible with this change. A proposed audit program was prepared, guided by international auditing standards, based on the study of the client's environment and analysis of external and internal risks in the light of financial and non-financial indicators. The researchers reached a set of concl

In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ

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