Composing RESTful Services and Collaborative Workflows: A Lightweight Approach

The use of RESTful Web services has gained momentum in the development of distributed applications based on traditional Web standards such as HTTP. In particular, these services can integrate easily into various applications, such as mashups. Composing RESTful services into Web-scale workflows requires a lightweight composition language that's capable of describing both the control and data flow that constitute a workflow. The authors address these issues with Bite, a lightweight and extensible composition language that enables the creation of Web-scale workflows and uses RESTful services as its main composable entities.     

Visual tracking using convolutional features with sparse coding

Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial...     

Corrosion-resistant lightweight metallic bipolar plates for PEM fuel cells

Corrosion resistant treated metal bipolar plates with higher rigidity and electrical conductivity than graphite were developed and tested for PEM fuel cell applications. Six replicas of single cells were used three of which were made of graphite composites bipolar plates and the other three of the treated metallic plates. A Membrane Electrode Assembly (MEA) with 5.55 cm² active electrode areas, 0.3 mg cm^–2 Pt loading and Nafion membrane 115 was fitted to each cell and operated under identical conditions. The experimental testing was conducted at room temperature (20 °C). The average value of the data obtained for the three graphite cells was plotted. Similarly, the average value of the data obtained for the three treated metal cells was plotted on the same graph for comparison. Generally, the treated metal bipolar plate provided at least 12% saving in hydrogen consumption in comparison to graphite. This is attributed to the lower bulk and surface contact resistance of the metal used in this study in relation to graphite. The results of lifetime testing, conducted at room temperature under variable loading showed no indication of power degradation due to metal corrosion for at least 1500 hours.     

A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

This paper presents a new technique to design fixed‐structure controllers for linear unknown systems using a set of measurements. In model‐based approaches, the measured data are used to identify a model of the plant for which a suitable controller can be designed. Due to the fact that real processes cannot be described perfectly by mathematical models, designing controllers using such models to guarantee some desired closed‐loop performance is a challenging task. Hence, a possible alternative to model‐based methods is to directly utilize the measured data in the design process. We propose an approach to designing structured controllers using a set of closed‐loop frequency‐domain data. The principle of such an approach is based on computing the parameters of a fixed‐order controller for which the closed‐loop frequency response fits a desired frequency response that describes some desired performance indices. This problem is formulated as an error minimization problem, which can be solved to find suitable values of the controller parameters. The main feature of the proposed control methodology is that it can be applied to stable and unstable plants. Additionally, the design process depends on a pre‐selected controller structure, which allows for the selection of low‐order controllers. An application of the proposed method to a DC servomotor system is presented to experimentally validate and demonstrate its efficacy.     

Optimal Artificial Intelligence Based Automated Skin Lesion Detection and Classification Model

Skin lesions have become a critical illness worldwide, and the earlier identification of skin lesions using dermoscopic images can raise the survival rate. Classification of the skin lesion from those dermoscopic images will be a tedious task. The accuracy of the classification of skin lesions is improved by the use of deep learning models. Recently, convolutional neural networks (CNN) have been established in this domain, and their techniques are extremely established for feature extraction, leading to enhanced classification. With this motivation, this study focuses on the design of artificial intelligence (AI) based solutions, particularly deep learning (DL) algorithms, to distinguish malignant skin lesions from benign lesions in dermoscopic images. This study presents an automated skin lesion detection and classification technique utilizing optimized stacked sparse autoencoder (OSSAE) based feature extractor with backpropagation neural network (BPNN), named the OSSAE-BPNN technique. The proposed technique contains a multi-level thresholding based segmentation technique for detecting the affected lesion region. In addition, the OSSAE based feature extractor and BPNN based classifier are employed for skin lesion diagnosis. Moreover, the parameter tuning of the SSAE model is carried out by the use of sea gull optimization (SGO) algorithm. To showcase the enhanced outcomes of the OSSAE-BPNN model, a comprehensive experimental analysis is performed on the benchmark dataset. The experimental findings demonstrated that the OSSAE-BPNN approach outperformed other current strategies in terms of several assessment metrics.     

Detection of Abnormal Activities from Various Signals Based on Statistical Analysis

We perceive big data with massive datasets of complex and variegated structures in the modern era. Such attributes formulate hindrances while analyzing and storing the data to generate apt aftermaths. Privacy and security are the colossal perturb in the domain space of extensive data analysis. In this paper, our foremost priority is the computing technologies that focus on big data, IoT (Internet of Things), Cloud Computing, Blockchain, and fog computing. Among these, Cloud Computing follows the role of providing on-demand services to their customers by optimizing the cost factor. AWS, Azure, Google Cloud are the major cloud providers today. Fog computing offers new insights into the extension of cloud computing systems by procuring services to the edges of the network. In collaboration with multiple technologies, the Internet of Things takes this into effect, which solves the labyrinth of dealing with advanced services considering its significance in varied application domains. The Blockchain is a dataset that entertains many applications ranging from the fields of crypto-currency to smart contracts. The prospect of this research paper is to present the critical analysis and review it under the umbrella of existing extensive data systems. In this paper, we attend to critics' reviews and address the existing threats to the security of extensive data systems. Moreover, we scrutinize the security attacks on computing systems based upon Cloud, Blockchain, IoT, and fog. This paper lucidly illustrates the different threat behaviour and their impacts on complementary computational technologies. The authors have mooted a precise analysis of cloud-based technologies and discussed their defense mechanism and the security issues of mobile healthcare.

     

Reference Range Estimation: Accounting for Measurement System Errors

Reference range is a statistic that is used in health related fields to represent the range of the most likely values for a variable of interest. Based on this range, individuals are classified as being healthy or unhealthy. In biostatistics, the reference range is calculated as the (1 ? α)% prediction interval, where this prediction interval is based on the estimated population variance from the data. Such estimation of population variance is not precise, because obtained test results do usually have errors associated with them. These errors are due to the imprecise test procedure or gauge used. In this paper, the total variability in the data is decomposed into two categories. The first is the patient‐to‐patient variability and the other is the variability due to the measurement system used. Estimation of the two kinds is performed through a gauge repeatability and reproducibility study, then the reference range is calculated, taking into account only the patient‐to‐patient variability. The revised reference range procedure is illustrated through a case study of vitamin B12 test results. A closed form formula is given to calculate the probability of a given test result being within the revised reference range. Copyright © 2015 John Wiley & Sons, Ltd.     

CNLs for the semantic web: a state of the art

One of the core challenges for building the semantic web is the creation of ontologies, a process known as ontology authoring. Controlled natural languages (CNLs) propose different frameworks for interfacing and creating ontologies in semantic web systems using restricted natural language. However, in order to engage non-expert users with no background in knowledge engineering, these language interfacing must be reliable, easy to understand and accepted by users. This paper includes the state-of-the-art for CNLs in terms of ontology authoring and the semantic web. In addition, it includes a detailed analysis of user evaluations with respect to each CNL and offers analytic conclusions with respect to the field.     

A recursive algorithm for generating the equations of motion of spatial mechanical systems with application to the five-point suspension

In this paper, a recursive formulation for generating the equations of motion of spatial mechanical systems is presented. The rigid bodies are replaced by a dynamically equivalent constrained system of particles which avoids introducing any rotational coordinates. For the open-chain system, the equations of motion are generated recursively along the serial chains using the concepts of linear and angular momenta. Closed-chain systems are transformed to open-chain systems by cutting suitable kinematic joints and introducing cut-joint constraints. The formulation is used to carry out the dynamic analysis of multi-link five-point suspension. The results of the simulation demonstrate the generality and simplicity of the proposed dynamic formulation.