Malignant melanoma is one of the most rapidly increasing cancers globally and it is the most dangerous form of human skin cancer. Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma. Early detection of melanoma can be helpful and usually curable. Due to the difficulty for dermatologists in the interpretation of dermoscopy images, Computer Aided Diagnosis systems can be very helpful to facilitate the early detection. The automated detection of the lesion borders is one of the most important steps in dermoscopic image analysis. In this paper, we present a fully automated method for melanoma border detection using image processing techniques. The hair and several noises aredetected and removed by applying a bank of directional filters and Image Inpainting method respectively. A hybrid method is developed by combining Particle Swarm Optimization and Markov Random Field methods, in order to delineate the border of the lesion area in the images. The method was tested on a dataset of 200 dermoscopic images, and the experimental results show that our method is superior in terms of the accuracy of drawing the lesion borders compared to alternative methods.

The current paper proposes a novel scheme for non-blind watermarking of images, making use of discrete wavelet transform (DWT), discrete time Fourier transform (DTFT), as well as singular value decomposition, or SVD. During the process of embedding, 1-level DWT is used to decompose the host image into its various frequency sub-bands. After this, the high-frequency sub band receives an application of DTFT. This is followed then by SVD, after which the watermark becomes embedded into the now-transformed host image's singular matrix. Then, the inverses of 1-level DWT, DTFT and SVD are applied in order to obtain a watermarked final image. This paper evaluates the performance of the proposed method of watermarking against a number of attacks, including sharpening, salt and pepper noise, AWGN, gamma correction, histogram equalisation, flipping and cropping. Results obtained during experiments have found that the scheme as proposed does provide high levels of robustness and imperceptibility against various signal processing attacks.

With regard to oil production in Libya, the following instruments are particularly important:

- Sustainability guidelines

- Risk analyses

- Eco-efficiency analyses

- Balanced scorecards -

Key sustainability criteria (KPI)

- Certification systems

Sustainability consists of the balance between economic efficiency/economics on the one hand and ecology/environmental compatibility on the other. 15 Sustainable energy systems are always geared to demand. Energy is just one resource among many.

Employees, raw materials, knowledge, etc. are also important resources that need to be managed sustainably and a balance found. A system that is only one-sidedly focused on profit maximization or social compatibility

Abstract

This article presents yet another methodology for the calculation of dimensionless thermal response factors for vertical borehole ground heat exchanger (GHX) arrays, which is a concept introduced by Eskilson (1987). The presented method is based on a well-known solution to an analogous problem in the field of well hydraulics. This solution method, known mathematically as an incomplete Bessel function, and known in the field of well hydraulics as the 'leaky aquifer function', describes the hydraulic head distribution in an aquifer with predominantly radial flow to a well combined with vertical 'leakage' from geologic layers above and below the pumped aquifer. The solution is adapted to model heat transfer from an array of arbitrarily-placed vertical boreholes of finite depth. With proper expression of parameters in the incomplete Bessel function, we show that g-functions of previous researchers can be approximated. The proposed method has been implemented into Matlab and Excel/VBA for g-function generation and monthly GHX simulation.

Malignant melanoma is the most hazardous type of human skin cancer and its incidence has been rapidly increasing. Early detection of malignant melanoma in dermoscopy images is very important and critical, since its detection in the early stage can be helpful to cure it. Computer Aided Diagnosis systems can be very helpful to facilitate the early detection of cancers for dermatologists. In this paper, we present a novel method for the detection of melanoma skin cancer. To detect the hair and several noises from images, pre-processing step is carried out by applying a bank of directional filters. And therefore, Image inpainting method is implemented to fill in the unknown regions. Fuzzy C-Means and Markov Random Field methods are used to delineate the border of the lesion area in the images. The method was evaluated on a dataset of 200 dermoscopic images, and superior results were produced.

One of the most important structures in dermoscopy images is the pigment network, which is also one of the most challenging and fundamental task for dermatologists in early detection of melanoma. This paper presents an automatic system to detect pigment network from dermoscopy images. The design of the proposed algorithm consists of four stages. First, a pre-processing algorithm is carried out in order to remove the noise and improve the quality of the image. Second, a bank of directional filters and morphological connected component analysis are applied to detect the pigment networks. Third, features are extracted from the detected image, which can be used in the subsequent stage. Fourth, the classification process is performed by applying feed-forward neural network, in order to classify the region as either normal or abnormal skin. The method was tested on a dataset of 200 dermoscopy images