The feature extraction step plays major role for proper object classification and recognition, this step depends mainly on correct object detection in the given scene, the object detection algorithms may result with some noises that affect the final object shape, a novel approach is introduced in this paper for filling the holes in that object for better object detection and for correct feature extraction, this method is based on the hole definition which is the black pixel surrounded by a connected boundary region, and hence trying to find a connected contour region that surrounds the background pixel using roadmap racing algorithm, the method shows a good results in 2D space objects.
Keywords: object filling, object detection, objec

      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

Steganography can be defined as the art and science of hiding information in the data that could be read by computer. This science cannot recognize stego-cover and the original one whether by eye or by computer when seeing the statistical samples. This paper presents a new method to hide text in text characters. The systematic method uses the structure of invisible character to hide and extract secret texts. The creation of secret message comprises four main stages such using the letter from the original message, selecting the suitable cover text, dividing the cover text into blocks, hiding the secret text using the invisible character and comparing the cover-text and stego-object. This study uses an invisible character (white space

Preserving and saving energy have never been more important, thus the requirement for more effective and efficient heat exchangers has never been more important. However, in order to pave the way for the proposal of a truly efficient technique, there is a need to understand the shortcomings and strengths of various aspects of heat transfer techniques. This review aims to systematically identify these characteristics two of the most popular passive heat transfer techniques: nanofluids and helically coiled tubes. The review indicated that nanoparticles improve thermal conductivity of base fluid and that the nanoparticle size, as well as the concentrations of the nanoparticles plays a major role in the effectiveness of the nanofluids.

Delays occur commonly in construction projects. Assessing the impact of delay is sometimes a contentious
issue. Several delay analysis methods are available but no one method can be universally used over another in
all situations. The selection of the proper analysis method depends upon a variety of factors including
information available, time of analysis, capabilities of the methodology, and time, funds and effort allocated to the analysis. This paper presents computerized schedule analysis programmed that use daily windows analysis method as it recognized one of the most credible methods, and it is one of the few techniques much more likely to be accepted by courts than any other method. A simple case study has been implement

Ultraviolet light radiation is applied to treat Plaque Psoriasis disease by targeted phototherapy. This is available through Narrowband-UVB light radiation devices peaked at wavelength 311 nm. Ten cases were chosen as a study group, 8 males aged 22-40 years old, and 2 females aged 25 and 32 years old who were exposed to ultraviolet light radiation. Their recovery or improvement was followed weekly. Different doses were used according to the severity of the lesion and as a trial for the outcome. The dose was given two times a week, starting with 200mJ/cm^2, and subsequently increased by 100 or 200 mJ/cm² reaching a maximum dose as tolerated by each individual patient. Improvement was observed after 4 – 6 weeks. The

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.