A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

The aim of this research is to show the importance of the effective use
of the internet in academic libraries; to improve the services and to increase
the competence of librarians.
The research has given some recommendations to improve the quality
of services and the need for cooperative network among academic libraries.

The railways network is one of the huge infrastructure projects. Therefore, dealing with these projects such as analyzing and developing should be done using appropriate tools, i.e. GIS tools. Because, traditional methods will consume resources, time, money and the results maybe not accurate. In this research, the train stations in all of Iraq’s provinces were studied and analyzed using network analysis, which is one of the most powerful techniques within GIS. A free trial copy of ArcGIS®10.2 software was used in this research in order to achieve the aim of this study. The analysis of current train stations has been done depending on the road network, because people used roads to reach those train stations. The data layers for this st

Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i

The development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifesp

The development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifesp

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover.  The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit