Molecular weight averages as criteria for quality assessment of heated oils and fats

A simple method for quality assessment of heated oils and fats is described. The proposed method involves precise determination of molecular weight averages (MWA)viz., the weight average molecular weight ( ), the number average molecular weight ( ) and the Z-average molecular weight ( ) by high performance size exclusion chromatography (HPSEC) and their quantitative correlation to percent polar material obtained by column chromatography (CC). Change in MWA on heat treatment of fourteen different edible oils and fats at 180° ± 2°C for eight 8-hr days is studied. Relative standard deviations and regression coefficients of correlation between MWA and their ratios ( , { }, { }, { }, { } and { )vs percent polar material have been reported. Probable discard time was predicted for all the oils based on the above-mentioned correlations and also from the percent of high molecular weight (H. Mwt) species formed. It was observed that the oils which are generally recommended for coronary patients deteriorated faster. A possibility of extending this methodology to the frying oils is suggested. Part of the work was presented at “40th Pittsburgh Conference on Analytical Chemistry and Applied Spectroscopy” at Georgia World Congress Centre, USA, 1989. IICT Communication No. 2630.     

Quantitative determination of castor oil in edible and heat-abused oils by13C nuclear magnetic resonance spectroscopy

Application of¹³C nuclear magnetic resonance (NMR) spectroscopy for detection of castor oil (CO) in various edible oils, such as coconut oil, palm oil, groundnut oil and mustard oil, is described. Characteristic signals observed at δ 132.4, δ 125.6, δ 71.3, δ 36.8 and δ 35.4 ppm, due to C10, C9, C12, C13 and C11 carbons of ricinoleic acid (RA) in CO, were selected for distinguishing it from edible oils. Quantitative¹³C NMR spectra of oils were recorded in CDCl₃ with a gated decoupling technique. The minimum detection limits for qualitative and quantitative analyses were 2.0 and 3.0%, respectively. The proposed method is simple, nondestructive and requires no sample pretreatment. Its application to heat-abused oils has also been demonstrated successfully without any of the interferences observed in most other methods.     

Deep learning approaches for speech emotion recognition: state of the art and research challenges

Speech emotion recognition (SER) systems identify emotions from the human voice in the areas of smart healthcare, driving a vehicle, call centers, automatic translation systems, and human-machine interaction. In the classical SER process, discriminative acoustic feature extraction is the most important and challenging step because discriminative features influence the classifier performance and decrease the computational time. Nonetheless, current handcrafted acoustic features suffer from limited capability and accuracy in constructing a SER system for real-time implementation. Therefore, to overcome the limitations of handcrafted features, in recent years, variety of deep learning techniques have been proposed and employed for automatic feature extraction in the field of emotion prediction from speech signals. However, to the best of our knowledge, there is no in-depth review study is available that critically appraises and summarizes the existing deep learning techniques with their strengths and weaknesses for SER. Hence, this study aims to present a comprehensive review of deep learning techniques, uniqueness, benefits and their limitations for SER. Moreover, this review study also presents speech processing techniques, performance measures and publicly available emotional speech databases. Furthermore, this review also discusses the significance of the findings of the primary studies. Finally, it also presents open research issues and challenges that need significant research efforts and enhancements in the field of SER systems.

     

Behavioral Attestation for Web Services using access policies

Service Oriented Architecture with underlying technologies like web services and web service orchestration opens new vistas for integration among business processes operating in heterogeneous environments. However, such dynamic collaborations require a highly secure environment at each respective business partner site. Existing web services standards address the issue of security only on the service provider platform. The partner platforms to which sensitive information is released have till now been neglected. Remote Attestation is a relatively new field of research which enables an authorized party to verify that a trusted environment actually exists on a partner platform. To incorporate this novel concept in to the web services realm, a new mechanism called WS-Attestation has been proposed. This mechanism provides a structural paradigm upon which more fine-grained solutions can be built. In this paper, we present a novel framework, Behavioral Attestation for Web Services, in which XACML is built on top of WS-Attestation in order to enable more flexible remote attestation at the web services level. We propose a new type of XACML policy called XACML behavior policy, which defines the expected behavior of a partner platform. Existing web service standards are used to incorporate remote attestation at the web services level and a prototype is presented, which implements XACML behavior policy using low-level attestation techniques.     

Human-centered design of a wearable kinesthetic haptic device for surgical teleoperation

Artificial Life and Robotics - This paper describes the design and performance evaluation of a flexible wearable haptic device that aims to realize full kinesthetic haptic feedback for application...     

An Overview of Control Charts for High‐quality Processes

Major difficulties in the study of high‐quality processes with traditional process monitoring techniques are a high false alarm rate and a negative lower control limit. The purpose of time‐between‐events control charts is to overcome existing problems in the high‐quality process monitoring setup. Time‐between‐events charts detect an out‐of‐control situation without great loss of sensitivity as compared with existing charts. High‐quality control charts gained much attention over the last decade because of the technological revolution. This article is dedicated to providing an overview of recent research and presenting it in a unifying framework. To summarize results and draw a precise conclusion from the statistical point of view, cross‐tabulations are also given in this article. Copyright © 2016 John Wiley & Sons, Ltd.