The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

Reseach target the most important topic, is Activity and ProfitabilityIndictors Analysis for
Nationality and Iraqi Insurance Company, In order to stand on them ability to cover its risks
and explore the efficiency asset and its avialible resources using to determine them abilities to
profit generation from its insurance activity. The analysis was focus to examine their profit
and activity power, and test the significant differences aming them performance. Test 2
hypothese that is related and result it sign that the 2 company no has significant differences at
profitability and activity level. The research depend on coneclusion, recommended two
company to work at efficiency with cost element of insurance activity in or

   Receipt date:10/27/2021    accepted date:12/15/2021     Publication date:31/12/2021

        This work is licensed under a Creative Commons Attribution 4.0 International License.

The phenomenon of extremist extremism (terrorism) was one of the most prominent issues that took a large space in the twenty-first century, in which cognitive motives were mixed with strategic and ideological motives, leading to the emergence of terrorist extremi

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

This research aims primarily to highlight personal tax exemptions A comparative study with some Arab and European regulations. And by conducting both theoretical comparative analyses. Most important findings of the study is the need to grant personal and family exemptions that differ according to the civil status of the taxpayer (single or married). In other words, the exemption increases as the number of family members depend on its social sense. Also taking into account some incomes that require a certain effort and looking at the tax rates, it is unreasonable for wages to be subject to the same rates applied to commercial profits.      

With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored