Early diagnosis of Alzheimer's disease and its prodromal stage, also known as mild cognitive impairment (MCI), is critical since some patients with progressive MCI will develop the disease. We propose a multi-stream deep convolutional neural network fed patch-based imaging data to classify stable MCI. First, we compare MRI images cognitively normal subjects identify distinct anatomical landmarks using multivariate statistical test. These are then used extract patches that into proposed...

A new method is proposed for long-term reservoir operation planning with stochastic inflows. In particular, the problem formulated as a two-stage linear program simple recourse. The inflows are approximated by multiple inflow scenarios, leading to very large deterministic model which hard solve using conventional optimization methods. This paper presents an efficient interior-point algorithm solving resulting problem. It also shown how exploiting structure enhances performance of algorithm....

Resource leveling problem is an attractive field of research in project management. Traditionally, a basic assumption this that network activities could not be split. However, real-world projects, some can interrupted and resumed different time intervals but activity splitting involves cost. The main contribution paper lies developing practical algorithm for resource large-scale projects. A novel hybrid genetic proposed to tackle multiple resource-leveling problems allowing splitting....

Abstract This paper presents a new method for finding optimal solutions of systems with design parameters which are random variables distributed various general and possibly non‐symmetrical distributions. A double‐bounded density function is used to approximate the Specifications may require tracking constraints in time domain stability conditions frequency domain. Using sensitivity information, proposed first finds linearized feasible region. Afterwards it attempts place tolerance box such...

This paper presents a general method for statistical design centering of integrated circuits with correlated parameters. It unifies worst-case design, nominal and tolerance in single framework by selecting appropriate norms to measure the distances from values. The uses an advanced first-order second moment technique as alternative simplicial algorithm. Yield estimation is calculated original space no transformation uncorrelated variables required. solution algorithms are based on recently...

The significance of data analytics and machine learning has increased in managing vast quantities healthcare effectively. According to recent statistics, Alzheimer’s disease is the most prevalent cause dementia worldwide. Moreover, arises some people with increasing mild cognitive impairment (MCI). Early detection treatment its prodromal stage, also known as MCI, vital prevent progression. For selecting relevant features, four feature selection methods, including Mutual Information (MI),...

Abstract We develop a multistage portfolio optimization model that utilizes options for mitigating market risk in dynamic setting. Due to the key role of scenarios quality investment decisions, new scenario generation method is proposed characterizes behavior asset returns. This methodology takes dependence structure different returns into account, and also considers serial correlations each Moreover, it preserves marginal distributions Also, precludes arbitrage opportunities. To investigate...

Purpose This study aims to differential diagnosis of some diseases using classification methods support effective medical treatment. For this purpose, different based on data, experts’ knowledge and both are considered in cases. Besides, feature reduction clustering used improve their performance. Design/methodology/approach First, the performances evaluated for diseases. Then, experts' is utilized modify Bayesian networks' structures. Analyses results show that more than other algorithms...

Abstract Exploitation of mature oil reservoirs has forced researchers to find ways for enhancing production from such reservoirs. An effective way do so is drilling horizontal wells. There are many advantages these kinds wells but they require extra investment and completion. The objective this research choose location, direction, length a new well maximize accumulative over planning horizon. authors employ various metamodeling techniques in order build good approximate model estimation...