DOE applied to multi-response optimisation study on performance,combustion and emission characteristics of a VCR diesel engine

There are various parameters which may influence the IC engine performance. The trial and error method is a technique used to identify the best parameters. However, this method demands extensive experimental work and results in a great waste of time and resources. Thus, the design of experiments (DOEs) developed by Taguchi is employed. The multi-responses which need to be maximised are brake thermal efficiency, mechanical efficiency, cylinder pressure and cumulative heat release rate, whereas the responses which are to be minimised are specific fuel consumption, oxides of nitrogen and carbon monoxide. In the present study, an optimised DOE(L9) orthogonal array based on the Taguchi statistical method was formulated and a series of experiments were conducted under controlled supervision by considering three different injection operating pressures (IOPs) (200, 220 and 240 bar) and three different compression ratios (CRs) (16.5, 17.5 and 18.5). The main objective of this paper is to find the best suited IOP and CR values which obtain higher performance, better combustion and lower emissions.     

Accuracy improving guidelines for network anomaly detection systems

An unprecedented growth in computer and communication systems in the last two decades has resulted in a proportional increase in the number and sophistication of network attacks. In particular, the number of previously-unseen attacks has increased exponentially in the last few years. Due to the rapidly evolving nature of network attacks, a considerable paradigm shift has taken place in the intrusion detection community. The main focus is now on Network Anomaly Detection Systems (NADSs) which model and flag deviations from normal/benign behavior of a network and can hence detect previously-unseen attacks. Contemporary NADS borrow concepts from a variety of theoretical fields (e.g., Information theory, stochastic and machine learning, signal processing, etc.) to model benign behavior. These NADSs, however, fall short of achieving acceptable performance levels as therefore widespread commercial deployments. Thus, in this paper, we firstly evaluate the performance of eight prominent network-based anomaly detectors under malicious portscan attacks to identify which NADSs perform better than others and why. These NADSs are evaluated on three criteria: accuracy (ROC curves), scalability (with respect to varying normal and attack traffic rates, and deployment points) and detection delay. These criteria are evaluated using two independently collected datasets with complementary strengths. We then propose novel methods and promising guidelines to improve the accuracy and scalability of existing and future anomaly detectors. Experimental analysis of the proposed guidelines is also presented for the proof of concept.     

Effect of Postweld Heat Treatment on Microstructure, Hardness, and Tensile Properties of Laser-Welded Ti-6Al-4V

The effects of postweld heat treatment (PWHT) on 3.2-mm- and 5.1-mm-thick Ti-6Al-4V butt joints welded using a continuous wave (CW) 4-kW Nd:YAG laser welding machine were investigated in terms of microstructural transformations, welding defects, and hardness, as well as global and local tensile properties. Two postweld heat treatments, i.e., stress-relief annealing (SRA) and solution heat treatment followed by aging (STA), were performed and the weld qualities were compared with the as-welded condition. A digital image correlation technique was used to determine the global tensile behavior for the transverse welding samples. The local tensile properties including yield strength and maximum strain were determined, for the first time, for the laser-welded Ti-6Al-4V. The mechanical properties, including hardness and the global and local tensile properties, were correlated to the microstructure and defects in the as-welded, SRA, and STA conditions.     

Prebiotic fibre‐incorporated whey protein crisps processed by supercritical fluid extrusion

Prebiotic soluble fibre (fructooligosaccharides)‐incorporated whey protein crisps were produced by low‐shear supercritical fluid extrusion (SCFX), which utilises supercritical CO₂ as an expansion agent instead of steam. Protein crisps with desirable qualities were obtained with a formulation containing 8% prebiotic fibre and 60% whey protein concentrate (WPC‐80), which gave the final product with a protein content of 49.6% (w/w). A maximum of 70% WPC‐80 and 8% prebiotic fibre could be incorporated to produce expanded protein crisps; however, increasing WPC‐80 from 50% to 70% decreased the end‐product expansion ratio from 3.1 to 1.2 and increased the product hardness and piece density from 1.3 to 2.8 kN and 0.63 to 0.75 g mL^?1, respectively. Addition of 8% prebiotic fibre did not affect the textural qualities of final products. The process produced an expanded protein matrix with unique internal microstructure of uniformly distributed closed cells. Amino acid analysis indicated that 90% of the total lysine and 92% of the total essential amino acids were retained after SCFX processing and oven‐drying, indicating the preservation of protein nutritional quality during the process.     

Artificial Neural Network modeling of a hydrogen dual fueled diesel engine characteristics: An experiment approach

The rapid growth of vehicular pollution; mostly running on the diesel engine, emissions emerging are the concerns of the day. Owing to clean burn characteristics features, Hydrogen (H₂) as a fuel is the paradigm of the researcher. Extensive research presented in the literature on H₂ dual fueled diesel engine reveals, the significant role of H₂ in reducing emissions and enhancing the performance of a dual fueled diesel engine. With meager qualitative experiment data, the feasibility to develop an efficient Artificial Neural Network (ANN) model is investigated, the developed model can be utilized as a tool to investigate the H₂ dual fueled diesel engine further. In the process of developing an ANN model, engine load and H₂ flow rate are varied to register performance and emission characteristics. The creditability of the experiment is ascertained with uncertainty analysis of measurable and computed parameters. Leave-out-one method is adopted with 16 data sets; seven training algorithms are explored with eight transfer function combinations to evolve a competent ANN model. The efficacy of the developed model is adjudged with standard benchmark statistic indices. ANN model trained with Broyden, Fletcher, Goldfarb, & Shanno (BFGS) quasi-Newton backpropagation (trainbfg) stand out the best among other algorithms with regression coefficient ranging between 0.9869 and 0.9996.     

Antioxidant Capacity and Phenolic Content of the Aqueous Extract of Commonly Consumed Cucurbits

The antioxidant capacity of commonly consumed cucurbits vegetable was determined by the DPPH, FRAP, Fe³⁺ reducing power, and hydrogen peroxide scavenging assay. The aqueous extract of Luffa cylindrica showed the highest value of phenolic content and antioxidant capacity based on FRAP, Fe³⁺ reducing power, and hydrogen peroxide scavenging assay. However, Laginaria siceraria extract showed the highest flavonoid and DPPH scavenging activities among all three cucurbits used in this study. Phenolic content in aqueous extracts of Luffa cylindrica and Laginaria siceraria was almost equal. Cucurbita maxima exhibited the lowest phenolic, flavonoid content, and exhibited the lowest power of antioxidant scavenging. The antioxidant capacity of cucurbits was significantly correlated (P < 0.05) with the phenolic content of their extracts. The antioxidant capacity of Luffa cylindrica and Laginaria siceraria have also shown a significant correlation (P < 0.05).     

A low-power RF integrated circuit for implantable sensors

A low-power low-voltage analog signal processing circuit has been designed, fabricated, and tested. The circuit is capable of processing an analog sensor current and producing an ASK modulated digital signal with modulating signal frequency proportional to the sensor current level. An on-chip regulator has been included to stabilize the supply voltage received from an external RF power source. The circuit can operate with a power supply as low as 1 V and consumes only about 20 μW of power, which is therefore very suitable for implantable biomedical applications. The whole chip was laid out and fabricated in a 0.35 μm bulk CMOS technology. Experimental results show good agreement with the simulation results.     

A Functional Programming Framework for Latency Insensitive Protocol Validation

Latency insensitive protocols (LIPs) have been proposed as a viable means to connect synchronous IP blocks via long interconnects in a system-on-chip. The reason why one needs to implement LIPs on long interconnects stems from the fact that with increasing clock frequencies, the signal delay on some interconnects exceeds the clock period. Correctness of a system composed of synchronous blocks communicating via LIPs is established by showing latency equivalence between a completely synchronous composition of the blocks, and the LIP based composition. A design flow based on a synchronous composition specification, and stepwise refinement to LIP composition can be easily conceived, and a proof obligation to show latency equivalence between the synchronous specification and the refinement needs to be discharged. In this work, we propose a functional programming based framework for modeling and simulating LIP, and implement the semantics of various refinement steps in the programming model, so we can validate the LIP model against the original system within this functional programming framework. Such validation becomes easier due to the inherent denotational model of functional languages. We specifically use Standard ML to model the original system implementation as well as its latency insensitive version and compare the two by creating a model that contains both, giving them the same inputs and checking their outputs to be latency equivalent.