A Diagnostic Case Study of a Young Man with Russell-Silver Syndrome and Associated Comorbidities

This is a case study of a young man diagnosed with Russell-Silver Syndrome or RSS for short (Online Mendelian Inheritance in Man® Classification Number #180860) and associated comorbidities. The aim of this paper is to provide diagnostic information about the syndrome with its comorbidities so that educational therapists and other allied professionals working with such individuals will know what to look out for, especially the RSS-associated comorbidities, and in that way, they become better informed in order to know what offer in their Response to Intervention (RtI) for such individuals with RSS

Cryptanalytic Flaws in Oh et al.\u27s ID-Based Authenticated Key Agreement Protocol

A key agreement protocol is designed for two or more entities to agree upon a shared secret key, which is used to preserve confidentiality and data integrity over an open network. In 2007, Oh et al. proposed an efficient ID-based authenticated key agreement protocol on elliptic curve pairings, which is believed to be able to generate two session keys securely after a protocol execution. However, we discover that their protocol is in fact susceptible to the basic impersonation attack as well as the key compromise impersonation attack. In this paper, we present the imperfections of Oh et al.\u27s scheme and subsequently we suggest a slight modification to the scheme which would resolve the problems

Cryptanalysis on Improved Chou et al.\u27s ID-Based Deniable Authentication Protocol

A deniable authentication protocol enables the protocol participants to authenticate their respective peers, while able to deny their participation after the protocol execution. This protocol can be extremely useful in some practical applications such as online negotiation, online shopping and electronic voting. Recently, we have improved a deniable authentication scheme proposed by Chou et al. due to its vulnerability to the key compromise impersonation attack in our previous report. However, we have later discovered that our previous enhanced protocol is vulnerable to the insider key compromise impersonation attack and key replicating attack. In this paper, we will again secure this protocol against these attacks and demonstrate its heuristic security analysis

An Enhanced One-round Pairing-based Tripartite Authenticated Key Agreement Protocol

A tripartite authenticated key agreement protocol is generally designed to accommodate the need of three specific entities in communicating over an open network with a shared secret key, which is used to preserve data confidentiality and integrity. Since Joux proposed the first pairing-based one-round tripartite key agreement protocol in 2000, numerous authenticated protocols have been proposed after then. However, most of them have turned out to be flawed due to their inability in achieving some desirable security attributes. In 2005, Lin-Li had identified the weaknesses of Shim\u27s protocol and subsequently proposed their improved scheme by introducing an extra verification process. In this paper, we prove that Lin-Li\u27s improved scheme remains insecure due to its susceptibility to the insider impersonation attack. Based on this, we propose an enhanced scheme which will not only conquer their defects, but also preserves the desired security attributes of a key agreement protocol

Secure Deniable Authenticated Key Establishment for Internet Protocols

In 2003, Boyd et al. have proposed two deniable authenticated key establishment protocols for Internet Key Exchange (IKE). However, both schemes have been broken by Chou et al. in 2005 due to their susceptibility to key-compromise impersonation (KCI) attack. In this paper, we put forward the improved variants of both Boyd et al.\u27s schemes in order to defeat the KCI attack. On top of justifying our improvements, we further present a detailed security analysis to ensure that the desired security attributes: deniability and authenticity remain preserved

Chemical composition of essential oil of exudates of Dryobalanops aromatica

Purpose: To identify the chemical composition of essential oil from the exudates of Dryobalanops aromatica from Malaysia.Methods: Exudate was collected from D. aromatica and subjected to fractional  distillation to obtain essential oil. Gas chromatography-mass spectrometry  (GC-MS) was used to characterize the composition of the isolated essential oil.Results: The yield of essential oil was 7.58 %, with the highest yield (3.24 %) within the first 2 h of fractional distillation. Thirty compounds which accounted for 97.56 % of essential oil composition were identified. These include sesquiterpenes (46.87 %), monoterpenes (31.05 %), oxygenated monoterpenes (16.76 %) and oxygenated  sesquiterpenes (2.13 %). Borneol accounted for 0.74 % of the essential oil.Conclusion: Essential oil from the exudates of D. aromatica contains terpenoid  compounds and borneol.Keywords: Dryobalanops aromatica, exudate, fractional distillation, essential oil, GS-MS, borneo

Determination of borneol and other chemical compounds of essential oil of Dryobalanops aromatica exudate from Malaysia

Purpose: To determine borneol and other chemical compounds of essential oil derived from the exudate of Dryobalanops aromatica in Malaysia.Methods: Exudate was collected from D. aromatica and subjected to fractional distillation to obtain essential oil. Gas chromatography-mass spectrometry (GC-MS) was performed to characterize the composition of the isolated essential oil.Results: Essential oil (7.58 %) was obtained with the highest yield (3.24 %) in the first 2 h of fractional distillation. Thirty compounds which accounted for 97.56 % of total essential oil composition were identified by GC-MS, and they include sesquiterpenes (46.87 %), monoterpenes (31.05 %), oxygenated monoterpenes (16.76 %) and oxygenated sesquiterpenes (2.13 %). Borneol (0.74 %) was also detected in the essential oil.Conclusion: Borneol and other terpenoid compounds are present in the essential oil of the exudate of D. aromatica.Keywords: Exudate, Dryobalanops Aromatica, Fractional distillation, Essential oil, Gaschromatography-mass spectrometry, Borneo

An improved turbomachinery conditionmonitoring method using multivariate statistical analysis

Industrial practitioners require a well-structured, proactive and precise conditionmonitoring package in order to optimize turbomachinery operation. Typically, conventional condition monitoring uses built-in software to capture faults or degradation processes based on threshold limits recommended by the Original Equipment Manufacturer (OEM). However, because OEM manual concurrent monitoring involves abundant information parameters, it is dependent on human intervention, insensitive to the development of machinery faults and tends to generate error-prone outcomes. This study proposes a simplified and advanced healthmonitoring method for turbomachinery using a multivariate statistical analysis (MSA) technique. By exploiting mathematical relationships between OEM recommended variables, the significance of input parameter is identified based on weighting factor. With a highly-correlated input subset, the revised condition monitoring method delivershigher sensitivity and a more accurate performance in investigating machine assessment mode

An improved image processing approach for machinery fault diagnosis

Wavelet analysis has been proven to be effective in analysing non-stationary vibration signals. However, the interpretation of the wavelet analysis results, such as a wavelet scalogram, requires high levels of knowledge and experience, which remains a great challenge to practitioners in the field. Recently, the rapid development and advancement of image processing technologies have shed new light on this challenge. In this study, image features such as Harris Stephens(Harris);speeded-up robust features(SURFs);and binary, robust, invariant, scalable keypoints (BRISKs)were obtained from a red, green, and blue (RGB) colour-filtered wavelet scalogram. Each colour filter generates a set of image features from an RGB-filtered wavelet scalogram. Then, the features were utilised as inputs to the fault classifier, namely the support vector machine (SVM),for fault classification. However, there will be a situation where the classification results from the fault classifier, based on the image generated from the different colour filters, are contradictory to each other. No conclusion can thus be made in these situations. This paper employed the Dempster-Shafer (DS) theory to refine the contradicting results and provide an ultimate conclusion to the machine condition. Therefore, the proposed method has improved the fault classification accuracy from 69% to 78%

Loss minimization DTC electric motor drive system based on adaptive ANN strategy

Electric motor drive systems (EMDS) have been recognized as one of the most promising motor systems recently due to their low energy consumption and reduced emissions. With only some exceptions, EMDS are the main source for the provision of mechanical energy in industry and accounts for about 60% of global industrial electricity consumption. Large energy efficiency potentials have been identified in EMDS with very short payback time and high-cost effectiveness. Typical, during operation at rated mode, the motor drive able to hold its good efficiencies. However, a motor usually operates out from rated mode in many applications, especially while under light load, it reduced the motor’s efficiency severely. Hence, it is necessary that a conventional drive system to embed with loss minimization strategy to optimize the drive system efficiency over all operation range. Conventionally, the flux value is keeping constantly over the range of operation, where it should be highlighted that for any operating point, the losses could be minimize with the proper adjustment of the flux level to a suitable value at that point. Hence, with the intention to generate an adaptive flux level corresponding to any operating point, especially at light load condition, an online learning Artificial Neural Network (ANN) controller was proposed in this study, to minimize the system losses. The entire proposed strategic drive system would be verified under the MATLAB/Simulink software environment. It is expected that with the proposed online learning Artificial Neural Network controller efficiency optimization algorithm can achieve better energy saving compared with traditional blended strategies