Expert Systems with Applications: An International Journal

Feature based learning of time series sequences contains a systematic step of preprocessing, representing and analyzing the properties of time series elements. Representational features include the mapping of time series properties ...

• Identifying a set of generalized global features for time series feature learning.

• Unsupervised framework for lung tumor segmentation in hybrid PET/MRI.
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Tumor segmentation is a crucial but difficult task in treatment planning and follow-up of cancerous patients. The challenge of automating the tumor segmentation has recently received a lot of attention, but the potential of utilizing ...

Numerous number of tourism attractions along with a huge amount of information about them on web and social platforms have made the decision-making process for selecting and visiting them complicated. In this regard, the tourism ...

• Users' reviews on tourism networks are processed to extract their preferences.
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Exploration, the process of visiting a new region in a search space, and exploitation, the process of searching in the neighborhood of previously visited regions, are two centerpieces of any metaheuristic algorithm. It is a common ...

• A novel direct measure of exploration and exploitation based on attraction basins.

Optimization algorithms are widely employed for finding optimal solutions in many applications. Stochastic optimization algorithms including nature-inspired optimization algorithms are simple and easy to implement, and this is the ...

• Nature-inspired optimization algorithms are used to solve optimization problems.

The multi-objective quality of service (QoS)-driven web service composition problem (MOQWSCP) aims to find the best combinations of atomic web services (i.e. composite service) to answer high quality of the optimized QoS criteria in a ...

• Formulating a Fuzzy Multi-Objective QoS-based Web Service Composition Problem (FMOQWSCP).

Network traffic classification plays an important role in network monitoring and network management. With the continuous development of network technology, traditional methods of traffic classification have more limitations in accuracy ...

• We divide a large classification into small classifications with the tree structure.

• An American Sign Language recognition model was developed using Leap Motion.
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Though American sign language (ASL) has gained recognition from the American society, few ASL applications have been developed with educational purposes. Those designed with real-time sign recognition systems are also lacking. Leap ...

• Fuzzy graphs capture value dependencies among software requirements.
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One of the critical activities in software development is Requirements Selection, which is to find an optimal subset of the software requirements (features) with the highest value for a given budget. The values of the requirements, ...

• Melanoma dermoscopy features should be based on pixel energies of wavelet filters.

Proper diagnosis of cutaneous melanoma is a life-saving factor. The most important limitation is the early and sensitive recognition of melanoma relative to dysplastic nevi. We have studied wavelet-based features extracted from ...

• A novel back traceable self paced learning algorithm for bug classification.
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One of the areas most in need of improvement in the field of automated bug fixing, localization and triaging systems is that of an effective categorization, as this would bugs to reduce the time, cost and effort required to locate, ...

• Fuzzy arithmetic (FA) is essential to tackling approximate reasoning problems.
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Advancement in fuzzy arithmetic is essential to advancing the applicability of fuzzy set theory (FST) to approximate reasoning problems arose in engineering, medicine, managerial science and many other domains. In the recent FST ...

• The proposed evaluation provides a better correlation than state-of-the-art methods.

The Evaluation of Text Summaries (ETS) has been a task of constant challenges to the development of Automatic Text Summarization (ATS). Within the ATS task, the ETS is crucial to determine the performance of text summaries. Over the ...

• A prediction model that combines two approaches for the purpose of forecasting traffic accidents.

Urban traffic forecasting models generally follow either a Gaussian Mixture Model (GMM) or a Support Vector Classifier (SVC) to estimate the features of potential road accidents. Although SVC can provide good performances with less ...

• Contributions of knowledge-intensive services in new product development are assessed.

Knowledge intensive service (KIS) is a key resource for new product development (NPD) of a firm. As a KIS provider, public research organization plays a critical role in supporting the success of firms’ NPD process, thereby promoting ...

• A layer-based registration applies the vehicle’s motion to the registration method.

An intelligent vehicle must identify the exact position and class of the surrounding object in various situations to consider the interaction with them. For this reason, the light detection and range sensor, called LiDAR, is widely ...

• Hierarchical DEMATEL method for complex systems is proposed.
• Analytic framework ...

The decision-making trial and evaluation laboratory (DEMATEL) method has been widely applied to identifying critical factors of simple systems in different fields. Although lots of efforts have been spent on improving the DEMATEL, they ...

• An AIC rule based variable selection approach for eco-efficiency evaluation is proposed.

Eco-efficiency evaluation has received increasing public attention and plays an important role in the business community. In many practical applications, the decision-makers are interested in which eco-variables take a significant ...

• Mark embedding through synonyms substitutions avoids to compromise data quality.

In relational database watermarking, the semantic consistency between the original database and the distorted one is a challenging issue which is disregarded by most watermarking proposals, due to the well-known assumption for which a ...

• Systematic analysis of overoptimistic results in machine learning fault diagnosis.

This paper presents a systematic procedure to fairly compare experimental performance scores for machine learning methods for fault diagnosis based on vibration signals. In the vast majority of related scientific publications, the ...

• We propose an ensemble-based personalized location recommendation algorithm.
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Recommender systems (RSs) have attracted considerable attention with the aim of optimizing location service efficiency since a large volume of information is generated by location-based social networks. Prediction accuracy is generally ...

• Unsupervised local face averaging beautifies non-frontal, non-neutral faces.
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Posting attractive facial photos is part of everyday life in the social media era. Motivated by the demand, we propose a lightweight method to automatically and efficiently beautify the shapes of both portrait and non-portrait faces in ...

• Kernelized Unified Domain Adaptation on Geometrical Manifolds for Domain Adaptation is proposed.

Primitive machine learning algorithms like the k-nearest Neighbor (k-NN) and Support Vector Machine (SVM) are a major challenge for expert and intelligent systems that recognize objects with large-scale variations in lighting ...

Boosting algorithms are frequently used in applied data science and in research. To date, the distinction between boosting with either gradient descent or second-order Newton updates is often not made in both applied and methodological ...

• Present gradient, Newton, and hybrid gradient-Newton boosting in a unified framework.

Intelligent systems driven by deep learning have become relevant in real-world applications with the increasing availability of technology and data. However, real-world settings require effective and robust deep learning models that ...

• A study of the effects of negative transfer is performed over D-UDA methods.
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• Capability of identifying minor faults overshadowed by more severe ones.
• CNN ...

In the case of a compound fault diagnosis of rotating machinery, when two failures with unequal severity occur in distinct parts of the system, the detection of a minor fault is a complicated and challenging task. In this case, the ...

• Extensive review over existing automated breast cancer detection techniques is done.

The intervention of medical imaging has significantly improved early diagnosis of breast cancer. Different radiological and microscopic imaging modalities are frequently utilized by medical practitioners for identification and ...

• This paper investigates the problem of named entity recognition from tweets.
• We ...

The current paper investigates the problem of multimodal named entity recognition from Twitter data. Named entity recognition (NER) is an important task in natural language processing and has been carefully studied in recent decades. ...

• A new global eXplainable Artificial Intelligence method is proposed.
• Our method ...

Explainability of artificial intelligence methods has become a crucial issue, especially in the most regulated fields, such as health and finance. In this paper, we provide a global explainable AI method which is based on Lorenz ...