A novel methodology for vessel extraction from retinal fundus image and detection of neovascularization

Multimedia Tools and Applications - Vessel extraction from the retinal fundus images plays a significant role in ophthalmologic disease diagnosis. Proliferative Diabetic Retinopathy (PDR) is the...     

Developing a Dynamic Cluster Quantization based Lossless Audio Compression (DCQLAC)

In this paper, an approach has been made to produce a compressed audio without losing any information. The proposed scheme is fabricated with the help of dynamic cluster quantization followed by Burrows Wheeler Transform (BWT) and Huffman coding. The encoding algorithm has been designed in two phases, i.e., dynamic cluster selection (of sampled audio) followed by dynamic bit selection for determining quantization level of individual cluster. Quantization level of each cluster is selected dynamically based on mean square quantization error (MSQE). Bit stream is further compressed by applying Burrows Wheeler Transform (BWT) and Huffman code respectively. Experimental results are supported with current state-of-the-art in audio quality analysis (like statistical parameters (compression ratio, space savings, SNR, PSNR) along with other parameters (encoding time, decoding time, Mean Opinion Score (MOS) and entropy) and compared with other existing techniques.

     

Segmentation of breast lesion in DCE-MRI by multi-level thresholding using sine cosine algorithm with quasi opposition-based learning

Pattern Analysis and Applications - In recent times, the high prevalence of breast cancer in women has increased significantly. Breast cancer diagnosis and detection employing computerized...     

A dynamic model for short-term prediction of stream attributes

Multiple data streams coming out of a complex system form the observable state of the system. The streams may correspond to various sensors attached with the system or outcome of internal processes. Such stream data may consist of multiple attributes and may differ in terms of their frequency of generation and observation. The streams may have dependency among themselves. One will have to rely on such data streams for monitoring the health of the system or to take any corrective measure. Predicting the value of certain stream data is an important task that can help one to take decision and act accordingly. In this work, a simple but generic visualization of a complex system is presented and thereafter a linear regression-based dynamic model for short-term prediction is proposed. The model is based on the past history of the attributes of multiple streams as suggested by the domain experts. But, it automatically determines the meaningful attributes and reformulates the model. The model is also re-computed if the prediction error exceeds the allowable tolerance. All these make the model dynamic. Experiment is carried out with stock market data streams to predict the close value well in advance. It is observed that in terms of quality of prediction and performance metric, the proposed model is quite effective.     

A Theoretical Analysis of Query Selection for Collaborative Filtering

We consider the problem of determining which of a set of experts has tastes most similar to a given user by asking the user questions about his likes and dislikes. We describe a simple algorithm for generating queries for a theoretical model of this problem. We show that the algorithm requires at most opt(F)(ln(|F|/opt(F)) + 1) + 1 queries to find the correct expert, where opt(F) is the optimal worst-case bound on the number of queries for learning arbitrary elements of the set of experts F. The algorithm runs in time polynomial in |F| and |X| (where X is the domain) and we prove that no polynomial-time algorithm can have a significantly better bound on the number of queries unless all problems in NP have n ^{O(log log n)} time algorithms. We also study a more general case where the user ratings come from a finite set Y and there is an integer-valued loss function on Y that is used to measure the distance between the ratings. Assuming that the loss function is a metric and that there is an expert within a distance from the user, we give a polynomial-time algorithm that is guaranteed to find such an expert after at most 2opt(F, ) ln + 2( + 1)(1 + deg(F, )) queries, where deg(F, ) is the largest number of experts in F that are within a distance 2 of any f F.     

A solid transportation problem for an item with fixed charge, vechicle cost and price discounted varying charge using genetic algorithm

In this paper, discount in transportation cost on the basis of transportated amount is extended to a solid transportation problem. In a transportation model, the available discount is normally offered on items/criteria, etc., in the form AUD (all unit discount) or IQD (incremental quantity discount) or combination of these two. Here transportation model is considered with fixed charges and vechicle costs where AUD, IQD or combination of AUD and IQD on the price depending upon the amount is offered and varies on the choice of origin, destination and conveyance. To solve the problem, genetic algorithm (GA) based on Roulette wheel selection, arithmetic crossover and uniform mutation has been suitably developed and applied. To illustrate the models, numerical examples have been presented. Here, different types of constraints are introduced and the corresponding results are obtained. To have better customer service, the entropy function is considered and it is displayed by a numerical example. To exhibit the efficiency of GA, another method—weighted average method for multi-objective is presented, executed on a multi-objective problem and the results of these two methods are compared.     

An EPQ model with promotional demand in random planning horizon: population varying genetic algorithm approach

One of the economic production quantity problems that have been of interest to researchers is the production with reworking of the imperfect items including waste most disposal form and vending the units. The available models in the literature assumed that the decay rate of the items is satisfied from three different points of view: (i) minimum demands of the customer’s requirement, (ii) demands to be enhanced for lower selling price and (iii) demands of the customers who are motivated by the advertisement. The model is developed over a finite random planning horizon, which is assumed to follow the exponential distribution with known parameters. The model has been illustrated with a numerical example, whose parametric inputs are estimated from market survey. Here the model is optimized by using a population varying genetic algorithm.     

Dialogues from the land of love and death

Knowledge and action constitute two important and inter-related domains of human existence. The very pace of our modern life with all its material abundance hardly allows us space for the dawning of higher knowledge or scope for imparting deeper meaning into the endless series of our mechanical actions. The limitations of linear thinking, binary logic and specialized disciplines of knowledge prevent our access to a holistic perception of our life-world. The article draws insights from three classical traditions of learning to highlight the importance of conversations and dialogues as alternative and non-conventional sources of creating and disseminating actionable knowledge. The author delves into a depth exploration of three timeless masterpieces of world literature and philosophy for a comprehensive understanding of the drama of life and death and attempts to create a space for unconditional love in our quest of illumined knowledge and engagement in meaningful action.     

Is cloned code really stable?

Clone has emerged as a controversial term in software engineering research and practice. The impact of clones is of great importance from software maintenance perspectives. Stability is a well investigated term in assessing the impacts of clones on software maintenance. If code clones appear to exhibit a higher instability (i.e., higher change-proneness) than non-cloned code, then we can expect that code clones require higher maintenance effort and cost than non-cloned code. A number of studies have been done on the comparative stability of cloned and non-cloned code. However, these studies could not come to a consensus. While some studies show that code clones are more stable than non-cloned code, the other studies provide empirical evidence of higher instability of code clones. The possible reasons behind these contradictory findings are that different studies investigated different aspects of stability using different clone detection tools on different subject systems using different experimental setups. Also, the subject systems were not of wide varieties. Emphasizing these issues (with several others mentioned in the motivation) we have conducted a comprehensive empirical study where we have - (i) implemented and investigated seven existing methodologies that explored different aspects of stability, (ii) used two clone detection tools (NiCad and CCFinderX) to implement each of these seven methodologies, and (iii) investigated the stability of three types (Type-1, Type-2, Type-3) of clones. Our investigation on 12 diverse subject systems covering three programming languages (Java, C, C#) with a list of 8 stability assessment metrics suggest that (i) cloned code is often more unstable (change-prone) than non-cloned code in the maintenance phase, (ii) both Type 1 and Type 3 clones appear to exhibit higher instability than Type 2 clones, (iii) clones in Java and C programming languages are more change-prone than the clones in C#, and (iv) changes to the clones in procedural programming languages seem to be more dispersed than the changes to the clones in object oriented languages. We also systematically replicated the original studies with their original settings and found mostly equivalent results as of the original studies. We believe that our findings are important for prioritizing code clones from management perspectives.     

Heterogeneous consensus of higher‐order multi‐agent systems with mismatched uncertainties using sliding mode control

A robust consensus controller is proposed for heterogeneous higher‐order nonlinear multi‐agent systems, when the agent dynamics are involved with mismatched uncertainties. A distributed consensus protocol based on a time‐varying nonhomogeneous finite‐time disturbance observer and sliding mode control is designed to realize the network consensus of higher‐order multi‐agent systems. The time‐varying finite‐time disturbance observer overcomes the problem of peaking value near the initial time caused by the constant gain one and is designed to estimate the uncertainties and to mitigate the effect of mismatched uncertainties during the sliding mode. To eliminate the chattering phenomenon and ensure finite‐time convergence to the sliding surface, the control law is designed by using the super twisting algorithm. Finally numerical simulations are given to illustrate the validity of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.