Effects of Pretreatment on Properties of Gelatin from Perch (Lates Niloticus) Skin

Fish gelatins obtained from perch fish skin pretreated with various solutions containing acetic acid, sodium hydroxide (NaOH) and sodium chloride (NaCl) were successfully characterized for their nanostructure pattern using field emission scanning electron microscopy. Each pretreatment transformed collagen to gelatin with fibril, zigzag cracks, straight rods, and cross-linked rods nanostructure patterns. Pretreatment solutions also affect the gel yield, gel strength, amino acid profile, and functional groups in perch gelatin as analyzed by Fourier transform infrared spectroscopy. Samples pretreated with NaCl, NaOH, and acetic acid solution showed the highest gel yield (22.84%) and gel strength (179.84 g). Fourier transform infrared spectra for perch gelatins also revealed weak C–N amide II and III bond stretches as well as weak C=O bond stretch.     

Influence of the microstructure on the machinability of heat-treated Al–10.8% Si cast alloys: Role of copper-rich intermetallics

This study was conducted with the intention of investigating a new experimental alloy, namely the 396 alloy which belongs to the Al–Si near-eutectic cast alloy group and contains about 10.8%Si. In the light of the above, the main purpose of the work is to report on the changes observed in the mechanical and machinability criteria resulting from the effects of the presence of two levels of Cu, namely 2.25% and 3.5%; and of the effects of two levels of Mg, namely 0.3% and 0.6%. In addition to the preceding, the effects of Mg-free alloys and Sr-modification on these same alloys were also investigated.The results demonstrate that the increase in the levels of Cu and/or Mg in the 396-T6 alloy has a detrimental effect on drill life. Such an effect may be attributed to the formation of large amounts of the coarse blocklike Al₂Cu phase, together with the formation of thick plates of the Al–Si–Cu–Mg phase. The Mg-free experimental alloy displays the lowest cutting force and moment in addition to producing the highest number of holes in the alloys studied. This observation may be explained by the cooperative precipitation of the Al₂Cu, Mg₂Si, Al₂CuMg, and Al₅Si₆Cu₂Mg₈ hardening phases in Mg-containing alloys which confer greater strength on the alloy than would be the case with the precipitation of only the Al₂Cu phase in the Mg-free alloy. A comparison of the non-modified alloy and the Sr-modified alloy (containing the same level of Mg and Cu additions) in terms of the number of holes drilled, reveals that the morphology of Si particles has a noticeable effect in governing the tool life of near-eutectic Al–Si alloys. The chip breakability of the alloys containing the Al₂Cu phase is superior to that of the alloys containing Mg₂Si. Thus, combined additions of Cu and Mg are expected to further refine the size of the chips produced.     

Exploring the Approaches to Data Flow Computing

Architectures based on the data flow computing model provide an alternative to the conventional Von-Neumann architecture that are widely used for general purpose computing. Processors based on the data flow architecture employ fine-grain data-driven parallelism. These architectures have the potential to exploit the inherent parallelism in compute intensive applications like signal processing, image and video processing and so on and can thus achieve faster throughputs and higher power efficiency. In this paper, several data flow computing architectures are explored, and their main architectural features are studied. Furthermore, a classification of the processors is presented based on whether they employ either the data flow execution model exclusively or in combination with the control flow model and are accordingly grouped as exclusive data flow or hybrid architectures. The hybrid category is further subdivided as conjoint or accelerator-style architectures depending on how they deploy and separate the data flow and control flow execution model within their execution blocks. Lastly, a brief comparison and discussion of their advantages and drawbacks is also considered. From this study we conclude that although the data flow architectures are seen to have matured significantly, issues like data-structure handling and lack of efficient placement and scheduling algorithms have prevented these from becoming commercially viable.     

Prioritised best effort routing with four quality of service metrics applying the concept of the analytic hierarchy process

In this paper, a new approach that applies the concept of the Analytic Hierarchy Process (AHP) in the area of routing in communication networks is proposed. AHP is a well-known model in the area of decision making with multiple objectives. In addition, a new algorithm called Enhanced Best Effort Quality of Service Routing (QoS) with Multiple Prioritised Metrics is proposed for connection-oriented point-to-point communications. Four QoS metrics have been considered: delay, bandwidth, security and loss probability. The results presented and discussed in this paper are focussed on demonstrating the effects of metric prioritisation on the routing decisions. It is found that changing priority of a metric from 0 (the lowest priority) to 1 (the highest priority) applying the proposed algorithm improves the value of that metric by an average of (20–60)% for 90% of utilisation range.     

A combined multitasking performance measure involving sequential and parallel task executions

Cognition, Technology & Work - Research on human multitasking suggests several measures to evaluate performance. However, the suggested measures evaluate performance either when tasks are...     

Human-Animal Affective Robot Touch Classification Using Deep Neural Network

Touch gesture recognition is an important aspect in human–robot interaction, as it makes such interaction effective and realistic. The novelty of this study is the development of a system that recognizes human–animal affective robot touch (HAART) using a deep learning algorithm. The proposed system was used for touch gesture recognition based on a dataset provided by the Recognition of the Touch Gestures Challenge 2015. The dataset was tested with numerous subjects performing different HAART gestures; each touch was performed on a robotic animal covered by a pressure sensor skin. A convolutional neural network algorithm is proposed to implement the touch recognition system from row inputs of the sensor devices. The leave-one-subject-out cross-validation method was used to validate and evaluate the proposed system. A comparative analysis between the results of the proposed system and the state-of-the-art performance is presented. Findings show that the proposed system could recognize the gestures in almost real time (after acquiring the minimum number of frames). According to the results of the leave-one-subject-out cross-validation method, the proposed algorithm could achieve a classification accuracy of 83.2%. It was also superior compared with existing systems in terms of classification ratio, touch recognition time, and data preprocessing on the same dataset. Therefore, the proposed system can be used in a wide range of real applications, such as image recognition, natural language recognition, and video clip classification.     

In situ Investigation of the Growth of a Tribofilm Consisting of NaYF4 Fluorescent Nanoparticles

Tribofilms play a vital role in protecting lubricated surfaces in mechanical systems in motion. To date, understanding tribofilms has been mostly based on ex situ analysis. This research investigates the kinetics of a tribofilm formed on a pair of bearing steels (E52100). Strategically selected illuminative nanoparticles of NaYF₄ were added to a base oil in order to enable their tracking. Electrical conductivity was monitored during sliding that was found to be linked to the state of the interface and the tribofilm. Further characterization identified tribochemical reaction products of Y₂O₃ that exhibited superior tribological performance. In comparison with mineral oil as the base lubricant, the addition of NaYF₄ resulted in a reduction in wear of 82%. This work discovered three stages in tribofilm formation: running in, reactive, and growth. Interestingly, the formation of a tribofilm was dominated more by frictional force than applied load. This is significant because we can now use alternative strategies to generate quality tribofilms.