Searchable encryption (SE) is an interesting tool that enables clients to outsource their encrypted data into external cloud servers with unlimited storage and computing power and gives them the ability to search their data without decryption. The current solutions of SE support single-
A model reference adaptive control of condenser and deaerator of steam power plant is presented. A fuzzy-neural identification is constructed as an integral part of the fuzzy-neural controller. Both forward and inverse identification is presented. In the controller implementation, the indirect controller with propagating the error through the fuzzy-neural identifier based on Back Propagating Through Time (BPTT) learning algorithm as well as inverse control structure are proposed. Simulation results are achieved using Multi Input-Multi output (MIMO) type of fuzzy-neural network. Robustness of the plant is detected by including several tests and observations.
The autonomous navigation of robots is an important area of research. It can intelligently navigate itself from source to target within an environment without human interaction. Recently, algorithms and techniques have been made and developed to improve the performance of robots. It’s more effective and has high precision tasks than before. This work proposed to solve a maze using a Flood fill algorithm based on real time camera monitoring the movement on its environment. Live video streaming sends an obtained data to be processed by the server. The server sends back the information to the robot via wireless radio. The robot works as a client device moves from point to point depends on server information. Using camera in this work allows voiding great time that needs it to indicate the route by the robot.
Multidimensional Online analytical processing (MOLAP) technology is considered a good tool to produce meaningful and quality results by using a multidimensional cube. The term “multidimensional cube” is used to refer to the multiple layers of data that are used to show the result. This result is identified by high-level management to increase the Iraqi court work and to improve its quality. The Iraqi court needs an analytical report to make a strategic decision on case date, case type, case state, judge, criminal age, and criminal gender. Currently, MOLAP is known as the best and strongest technique because it provides rapid, dynamic, and multiple analyses of data; presents knowledge from different perspectives; comes up with data in time series intervals; and drills down into multiple levels of data layers to present different types of details. The SQL Server Reporting Service (SSRS) presents analysis reports based on the MOLAP cube. This paper focuses on designing and developing the analysis reports of the court data system of the Republic of Iraq by using SSRS with SQL Server Analysis Service to create the MOLAP cubes.
The problem of outlier detection is one of the most important issues in the field of analysis due to its applicability in several famous problem domains, including intrusion detection, security, banks, fraud detection, and discovery of criminal activities in electronic commerce. Anomaly detection comprises two main approaches: supervised and unsupervised approach. The supervised approach requires pre-defined information, which is defined as the type of outliers, and is difficult to be defined in some applications. Meanwhile, the second approach determines the outliers without human interaction. A review of the unsupervised approach, which shows the main advantages and the limitations considering the studies performed in the supervised approach, is introduced in this paper. This study indicated that the unsupervised approach suffers from determining local and global outlier objects simultaneously as the main problem related to algorithm parameterization. Moreover, most algorithms do not rank or identify the degree of being an outlier or normal objects and required different parameter settings by the research. Examples of such parameters are the radius of neighborhood, number of neighbors within the radius, and number of clusters. A comprehensive and structured overview of a large set of interesting outlier algorithms, which emphasized the outlier detection limitation in the unsupervised approach, can be used as a guideline for researchers who are interested in this field.