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

Abstract-A series of polyelectrolyte hydrogels ranging from 92-98wt% were synthesized by copolymerization of acrylamide,

AAM with 2-acrylamido-2-methyl propane sulphonic acid, AMPS using 0.001g APS as initiator in the presence of 30wt% H2O

and 1.0wt% ethylene glycol dimethacrylate,EDMA as cross-linking agent. The final copolymers was obtained in the form of

glassy and transparent roads at room temperature, these roads were soaked in water for two days to remove unreacted

monomers. The swelling behavior of the hydrogels was studied in distilled water and salt solutions of 1.5 mol/l each of NaCl

and KCl. The Swelling in water shows decreasing values of q, LE, Ø1, EWC% and increasing polymer volume fraction, Ø2 by

increasing acrylamide, due to increasing hydrophobicity and decreasing the hydrophilicity. The swelling in salt solutions

shows a decreasing in the values of ESSNa%, WCNa%, SCNa%, ESSK%, WCK% and SCK% by increasing acrylamid

monomer in the feed due to increasing the hydrophobicity and decreasing the ionized ionic groups (SO3H). The increasing

values of ESSNa%, WCNa% and SCNa% compared with the values of ESSK%, WCK% and SCK% respectively, is due to

the higher charge density of sodium ion than that of potassium ion.

Six Hakea species varying greatly in seed size were selected for cotyledon damage experiments. The

growth of seedlings with cotyledons partially or completely removed was monitored over 90 days. All

seedlings perished by the fifth week when both cotyledons were removed irrespective of seed size.

Partial removal of cotyledons caused a significant delay in the emergence of the first leaf, and reduction

in root and shoot growth of the large-seeded species. The growth of seedlings of small-seeded species

was less impacted by cotyledon damage. The rate of survival, root and shoot lengths and dry biomass

of the seedlings were determined after 90 days. When seedlings were treated with balanced nutrient

solutions following removal of the cotyledons, survival was 95–98%, but 0% when supplied with

nutrient solutions lacking N or P or with water only. The addition of a balanced nutrient solution failed

to restore complete growth of any species, but the rate of root elongation for the small-seeded species

was maintained. Cotyledons provide nutrients to support early growth of Hakea seedlings, but other

physiological roles for the cotyledons are also implicated. In conclusion, small-seeded Hakea species can

tolerate cotyledons loss better than large-seeded species.

Abstract

Walking considered as one of the safest modes of

travel available, sustainable to human society as well as

environmentally beneficial. In this context, the aim of this

research is to investigate pedestrians’ traffic gap acceptance

and crossing decision for Mid-block Street crossing in urban

areas in Malaysia. Pedestrian crossing behaviour at

Rughaya Street has been examined in terms of the decision

to cross or not the street and size of traffic gaps accepted by

pedestrian, as well as the related contributing factors. A

field study was conducted to collect the data of pedestrians’

decisions under real mix traffic Condition using video

camera on a typical unsignalized urban street section. JPEG

files were obtained from video recording by using Snapshot

Wizard software. The data extracted included traffic

characteristics such as traffic size, traffic speed, etc.

pedestrian individual characteristics such as gender, in

addition to individual behavior such as waiting, frequency

of attempt, etc.). Furthermore, The extracted data were

used to develop and examine a pedestrian gap acceptance

model based on A lognormal regression model and binary

logistic model by SPSS (22) in order to validate the impact

of various parameters on the size of traffic gaps accepted by

pedestrians as well as the effect on the decision of

pedestrians to cross the street or not. So that the effect of

the gap accepted available and of other factors on the

decision of pedestrians to cross the street or not is examined.

These results indicate that the data set for this particular

location has a majority of male pedestrians which were

insignificant variables in both models moreover a lognormal

regression results shows that accepted gaps size depend on

traffic size, crossing distance, speed of approaching vehicle

and time spent by pedestrian at the curb waiting for a

suitable gap size to start crossing. The BL model performs

well for the reason that it captures the pedestrian decision

making process with traffic taking the relevant attributes

into consideration. According to the coefficients of BL

regression analysis equation we noticed that the illegal

parking, traffic size, traffic waiting time and gap size are the

vital attributes for the Pedestrian gap acceptance model..

Index Terms: Pedestrian crossing, gap acceptance, crossing

decision, multiple linear regression, binary logistic

regression.

This paper presents a computational model for measuring diversity in terms of variety, balance and disparity. This model is informed by the Stirling’s framework for understanding diversity from social science and underpinned by semantic techniques from computer science. A case study in learning is used to illustrate the application of the model. It is driven by the desire to broaden learners’ perspectives in an increasingly diverse and inclusive society. For example, interpreting body language in a job interview may be influenced by the different background of observers. With the explosion of digital objects on social platforms, selecting the appropriate ones for learning can be challenging and time consuming. The case study uses over 2000 annotated comments from 51 YouTube videos on job interviews. Diversity indicators are produced based on the comments for each video, which in turn facilitate the ranking of the videos according to the degree of diversity in the comments for the selected domain.

Abstract—With a rapidly increasing incidence of melanoma

skin cancer, there is a need for decision support systems to

detect it in its early stages, which would lead to better decisions

in treating it successfully. However, developing such systems is

still a challenging task for researchers. Several Computer Aided-

Diagnosis (CAD) systems have been proposed in the last two

decades to increase the accuracy of melanoma detection. Image

feature extraction is a critical step in differentiating between

melanoma and normal skin lesions. In this paper, we propose

to improve a bag-of-words approach by combining features

consisting of the color histogram and first order moments with the

Histogram of Oriented Gradients (HOG). Experimental results

show that the proposed technique significantly improves the

detection accuracy, with an average sensitivity of 91% and

specificity of 85%. The proposed system was validated on a

dataset of 200 medically annotated images (40 melanomas and

160 non-melanomas) obtained from the database of the Hospital

Pedro Hispano. 

The measurement errors problem is endemic in many econometric studies, and one of the oldest known statistical problems. Instrumental variable (IV) method is one of the popular solutions adopted to deal with the mismeasured variables in statistical and econometric analyses. This paper proposes an efficient IV estimator to the parameters of the simple regression model where both variables are subject to measurement errors. The proposed IV is defined using simple mathematical transformation of the manifest independent variable (mismeasured variable). The proposed method is straightforward, and easy to implement. The theoretical superiority of the proposed estimator over the existing IV based estimators due to Wald (1940), Bartlett (1949), and Durbin (1954) is established by analytical comparison and geometric expositions. Simulation based numerical comparisons of the proposed estimator with four different existing estimators are also included.

Abstract- Many methods have been applied in order to reduce nitrate concentration in aqueous solutions, among them

is the adsorption onto the surface of agricultural wastes. In this study, batch experiments were carried out to investigate

the adsorption of nitrate onto olive pomace (OP), a solid by-product of olive oil industry. To achieve this, six parameters

were studied by varying only one parameter at a time. These parameters were the effect of: pH, contact time,

temperature, adsorbent weight, agitation speed and nitrate concentration. The optimum pH was found to be 5, while the

optimum time was 75 minutes. Nitrate removal percentage was found to increase with increasing adsorbent weight or

temperature, with 92.5% of nitrate removed by using 2 g of OP and 48% of nitrate was removed at 60ºC. Generally,

agitation speed increased the nitrate removal percentage, while high initial concentration of nitrate was found to decrease

its removal percentage. These findings, combined with the low cost of OP and its abundance, suggest that OP is a

potential adsorbent for nitrate removal provided that the optimum conditions are applied. Applying this method for

nitrate removal will make drinking water safer to drink and wastewater safer to discharge.