The root cause of black pad failure of solder joints with electroless Ni/Immersion gold plating

This paper reports on a study of the reaction of solder with the electrolessnickel with immersion gold (ENIG) plating system, and the resulting interfacial structures. Aforcused-ion beam (FIB) was used to polish the cross sections to reveal details of the microstructure of the ENIG-plated pad with and without soldering. High-speed pull testing of solder joints was performed to expose the pad surface. Results of scanning-electron microscopy/energy-dispersive x-ray analysis of the cross sections and fractured pad surfaces support the suggestion that black pad is the result of galvanic hyper-corosion of the plated electroless nickel by the gold plating bath. Criteria are proposed for diagnosing black pad of ENIG plating.     

Study of flavonoids in aqueous spinach extract using positive electrospray ionisation tandem quadrupole mass spectrometry

The presence of three flavonols (quercetin, kaempferol, myricetin) and two flavones (apigenin, luteolin) were investigated in the extract of fresh spinach leaves. Aqueous spinach extracts were prepared with a leaf/water ratio of 1:2 at 80 °C for 30 min stirring. Ferric ammonium sulphate method was used for measuring total polyphenols in the extracts and expressed as catechins and tannic acid equivalents. The flavonoids glycosides in the extract were hydrolysed to their aglycons with 1.2 M HCl in boiling 50% water methanol solution. The resulting aglycons were identified and quantified by a C18 reverse phase high-performance liquid chromatography (RP-HPLC). Furthermore, the results were confirmed by HPLC coupled to an electrospray ionisation tandem triple-quadrupole mass spectrometer ESI-MS performing low-energy collision induced dissociation (CID-MS/MS) in the collision cell (HPLC-ESI-MS/MS). Analyses were made in the multiple reaction monitory (MRM) mode. Results showed that total polyphenols contents in fresh spinach leaves were 270 mg kg⁻¹ and 390 mg kg⁻¹ as tannic acid and catechin equivalents, respectively, in which, major flavonoids aglycons were apigenin (170 mg kg⁻¹), quercetin (50 mg kg⁻¹) and kaempferol (30 mg kg⁻¹).     

A Generic Part Orientation System Based on Volumetric Error in Rapid Prototyping

The paper presents the development of a generic part orientation system for rapid prototyping by considering the issue of volumetric error encountered in parts during the layer by layer building process in a rapid prototyping (RP) system. An algorithm is developed that slices the part with horizontal planes and computes the volumetric error in the part at different orientations by rotation about user-specified axes. The system recommends the best orientation based on the least amount of volumetric error in the part. The system has been tested using several examples of simple and complex parts. The generic part orientation system is believed to be first of its kind based on a volumetric error approach and will be useful for RP users in creating RP parts with a higher level of accuracy and surface finish, and also for intelligent process planning in rapid prototyping. RID=" ID=" <E5>Correspondence and offprint requests to</E5>: Assoc. Prof. S. H. Masood, CAD/CAM/CAE Group, Industrial Research Institute Swinburne, Swinburne University of Technology, Hawthorn, Melbourne, 3122 Australia. E-mail: smasood&commat;swin.edu.au     

Marker-Based and Marker-Less Motion Capturing Video Data: Person and Activity Identification Comparison Based on Machine Learning Approaches

Biomechanics is the study of physiological properties of data and the measurement of human behavior. In normal conditions, behavioural properties in stable form are created using various inputs of subconscious/conscious human activities such as speech style, body movements in walking patterns, writing style and voice tunes. One cannot perform any change in these inputs that make results reliable and increase the accuracy. The aim of our study is to perform a comparative analysis between the marker-based motion capturing system (MBMCS) and the marker-less motion capturing system (MLMCS) using the lower body joint angles of human gait patterns. In both the MLMCS and MBMCS, we collected trajectories of all the participants and performed joint angle computation to identify a person and recognize an activity (walk and running). Using five state of the art machine learning algorithms, we obtained 44.6% and 64.3% accuracy in person identification using MBMCS and MLMCS respectively with an ensemble algorithm (two angles as features). In the second set of experiments, we used six machine learning algorithms to obtain 65.9% accuracy with the k-nearest neighbor (KNN) algorithm (two angles as features) and 74.6% accuracy with an ensemble algorithm. Also, by increasing features (6 angles), we obtained higher accuracy of 99.3% in MBMCS for person recognition and 98.1% accuracy in MBMCS for activity recognition using the KNN algorithm. MBMCS is computationally expensive and if we re-design the model of OpenPose with more body joint points and employ more features, MLMCS (low-cost system) can be an effective approach for video data analysis in a person identification and activity recognition process.     

Enhance Intrusion Detection in Computer Networks Based on Deep Extreme Learning Machine

Networks provide a significant function in everyday life, and cybersecurity therefore developed a critical field of study. The Intrusion detection system (IDS) becoming an essential information protection strategy that tracks the situation of the software and hardware operating on the network. Notwithstanding advancements of growth, current intrusion detection systems also experience dif- ficulties in enhancing detection precision, growing false alarm levels and identifying suspicious activities. In order to address above mentioned issues, several researchers concentrated on designing intrusion detection systems that rely on machine learning approaches. Machine learning models will accurately identify the underlying variations among regular information and irregular information with incredible efficiency. Artificial intelligence, particularly machine learning methods can be used to develop an intelligent intrusion detection framework. There in this article in order to achieve this objective, we propose an intrusion detection system focused on a Deep extreme learning machine (DELM) which first establishes the assessment of safety features that lead to their prominence and then constructs an adaptive intrusion detection system focusing on the important features. In the moment, we researched the viability of our suggested DELMbased intrusion detection system by conducting dataset assessments and evaluating the performance factors to validate the system reliability. The experimental results illustrate that the suggested framework outclasses traditional algorithms. In fact, the suggested framework is not only of interest to scientific research but also of functional importance.     

Design of stochastic assembly lines considering line balancing and part feeding with supermarkets

This article aims to address the assembly line balancing problem (ALBP) and supermarket location problem (SLP) as two long-term interrelated decision problems considering the stochastic nature of the task times and demands. These problems arise in real-world assembly lines during the strategic decision-making phase of configuring new assembly lines from both line balancing and part-feeding (PF) aspects. A hierarchical mathematical programming model is developed, in which the first level resolves the stochastic ALBP by minimizing the workstation numbers and the second level deals with the stochastic SLP while optimizing the PF shipment, inventory and installation costs. The results of case data from an automotive parts manufacturer and a set of standard test problems verified that the proposed model can optimize the configuration of assembly lines considering both ALBP and SLP performance measures. This study also validates the effect of the stochastic ALBP on the resulting SLP solutions.     

Privacy management of patient physiological parameters

Patient Physiological Parameters (PPPs) seem to be the most extensively accessed and utilized Personal Health Information (PHI) in hospitals, and their utilization by the various medical entities for treatment and diagnosis creates a real threat to patient privacy. This study aims to investigate whether PPPs access in a hospital environment violates patient privacy. If so, to what extent can we manage patient privacy while accessing PPPs in this environment? We investigated this question by analyzing questionnaire-based data from two Asian countries: Group A (China) and Group B (Pakistan). For data collection, we targeted those medical entities which were directly dealing with PPPs in their routine tasks. Results suggest that patient type directly influences the collection of PPPs: Group A (one-time?=?1.9, follow-up?=?1.06) and Group B (one-time?=?2.0 and follow-up?=?1.9). Both groups agreed that patients have the right to control their own PPPs. In both, doctors are the most trusted entity: for Group A, the Pearson Chi-Square with one degree of freedom is 1.414, p?=?0.234, whereas for Group B, the Pearson Chi-Square with three degrees of freedom is 4.511, p?=?0.11. Most of the Group A entities (92%) are familiar with unauthorized access of PPPs, while in Group B the level was only 35%. In Group B, only 35% of entities stated the purpose, specification and use limitations of PPPs. Doctors in both groups showed a high utilization of PPPs read authorization rights. This empirical evidence about PPPs usage in both countries will benefit health technology and improve policy on patient privacy.     

An investigation into design and manufacturing of mechanical conveyors systems for food processing

This paper presents the results of a research investigation undertaken to develop methodologies and techniques that will reduce the cost and time of the design, manufacturing and assembly of mechanical conveyor systems used in the food and beverage industry. The improved methodology for design and production of conveyor components is based on the minimisation of materials, parts and costs, using the rules of design for manufacture and design for assembly. Results obtained on a test conveyor system verify the benefits of using the improved techniques. The overall material cost was reduced by 19% and the overall assembly cost was reduced by 20% compared to conventional methods.     

Phylogenetic Studies,Gene Cluster Analysis,and Enzymatic Reaction Support Anthrahydroquinone Reduction as the Physiological Function of Fungal 17β‐Hydroxysteroid Dehydrogenase

17β‐Hydroxysteroid dehydrogenase (17β‐HSDcl) from the filamentous fungus Curvularia lunata (teleomorph Cochliobolus lunatus) catalyzes NADP(H)‐dependent oxidoreductions of androgens and estrogens. Despite detailed biochemical and structural characterization of 17β‐HSDcl, its physiological function remains unknown. On the basis of amino acid sequence alignment, phylogenetic studies, and the recent identification of the physiological substrates of the homologous MdpC from Aspergillus nidulans and AflM from Aspergillus parasiticus, we propose an anthrahydroquinone as the physiological substrate of 17β‐HSDcl. This is also supported by our analysis of a secondary metabolite biosynthetic gene cluster in C. lunata m118, containing 17β‐HSDcl and ten other genes, including a polyketide synthase probably involved in emodin formation. Chemoenzymatic reduction of emodin by 17β‐HSDcl in the presence of sodium dithionite verified this hypothesis. On the basis of these results, the involvement of a 17β‐HSDcl in the biosynthesis of other anthrahydroquinone‐derived natural products is proposed; hence, 17β‐HSDcl should be more appropriately referred to as a polyhydroxyanthracene reductase (PHAR).     

A study of a water-reducing agent from cashew nutshell liquid

The water-reducing agent better known as superplasticizer is a recent development. A number of base materials have been used for the development of such water-reducing agents which can act better than ordinary plasticizers in concrete. The sulphonated salts of melamine, napthalene, lignin, hydroxycarboxylic acids and hydroxylated polymers are some typical compounds. Recently cashew nutshell liquid obtained from a natural product waste as a thick black phenolic compound has been converted into a water-reducing agent. This paper describes the results obtained on its effectiveness in influencing the rheological properties of flow, viscosity, particle size distribution, etc, of cement particles in hydrating cements and the water-reducing capabilities in cement mortars and concretes.