Reliable Mark-Embedded Algorithm for Verifying Archived/Encrypted Image Contents in Presence Different Attacks with FEC Utilizing Consideration

Wireless Personal Communications - Due to the widely spreading of fake news utilizing image manipulation and its bad effects, this paper investigates efficient image contents verification and...     

Hybrid intelligent framework for one-day ahead wind speed forecasting

Neural Computing and Applications - Nowadays wind power is considered as one of the fastest growing alternative energies, that is expected to continue to grow rapidly in the upcoming...     

Object segmentation and labeling by learning from examples

We propose a system that employs low-level image segmentation followed by color and two-dimensional (2-D) shape matching to automatically group those low-level segments into objects based on their similarity to a set of example object templates presented by the user. A hierarchical content tree data structure is used for each database image to store matching combinations of low-level regions as objects. The system automatically initializes the content tree with only "elementary nodes" representing homogeneous low-level regions. The "learning" phase refers to labeling of combinations of low-level regions that have resulted in successful color and/or 2-D shape matches with the example template(s). These combinations are labeled as "object nodes" in the hierarchical content tree. Once learning is performed, the speed of second-time retrieval of learned objects in the database increases significantly. The learning step can be performed off-line provided that example objects are given in the form of user interest profiles. Experimental results are presented to demonstrate the effectiveness of the proposed system with hierarchical content tree representation and learning by color and 2-D shape matching on collections of car and face images.     

Electronic data acquisition forms in construction management

Effective management of construction projects depends on good access to and control of data, especially data pertaining to cost and schedule control functions. However, the proper design and development of automated mechanisms have not had the facility to acquire and store quality data in a timely manner. The purpose of this paper, then, is to discuss a prototype, automated data acquisition system that was developed to support an integrated project management system. The data acquisition system is composed of an integrated set of electronic forms used in conjunction with a bar coding data-entry tool.     

Risk Assessment in Construction

This study is concerned with the assessment of risk for major construction activities. Risk has been defined as a measure of the probability, the severity, and the exposure of all hazards of an activity. A risk assessor model (RAM) was developed and computerized to determine the risk associated with a particular activity and the justification factor for a proposed remedy. Knowing the value of risk would help contractors identify the high risk of major construction activities and would enable them to allocate safety precautions in a more efficient manner.     

A knowledge-based system for sensor selection

This paper presents a Knowledge-based system (KBS) developed to allow users, who may not be knowledgeable about sensors, to select sensors suitable for their specific needs. The KBS runs on a micro-computer. The selection criteria are user specified and are based on the desired measurement parameters. The system output includes all of the operational and dimensional parameters of the recommended sensor, price, and vendor information.     

Electroplating of nickel-cadmium alloys from alkaline solutions

The electroplating of Ni-Cd alloy coatings was carried out from alkaline baths (pH 10). For comparison, electroplating of the parent metals, Ni and Cd, was performed individually under the same conditions. The cathodic current efficiency for codeposition was high and decreased with increasing current density. The codeposition process is an anomalous type of plating with Cd being the preferentially deposited metal. The Ni content in the deposits increased with increasing current density. This increase in Ni content improves the corrosion resistance and microhardness of the deposits. X-ray diffraction analysis showed that the deposits consist of a mixture of Ni, β, γ, γ¹ phases.     

On an evolutionary approach for constrained optimization problem solving

Over the last few decades, many different evolutionary algorithms have been introduced for solving constrained optimization problems. However, due to the variability of problem characteristics, no single algorithm performs consistently over a range of problems. In this paper, instead of introducing another such algorithm, we propose an evolutionary framework that utilizes existing knowledge to make logical changes for better performance. The algorithmic aspects considered here are: the way of using search operators, dealing with feasibility, setting parameters, and refining solutions. The combined impact of such modifications is significant as has been shown by solving two sets of test problems: (i) a set of 24 test problems that were used for the CEC2006 constrained optimization competition and (ii) a second set of 36 test instances introduced for the CEC2010 constrained optimization competition. The results demonstrate that the proposed algorithm shows better performance in comparison to the state-of-the-art algorithms.