High-performance Processing Research Articles

On the improvement in process performance of ceramic inserts during hard turning in MQL environment

ABSTRACT Hard turning process, frequently used to finish the rotational surfaces of hard steel components, has some major issues like a high tool wear rate coupled with the degradation of surface finish and generation of brittle white layer. Due to this, the process productivity also remains low. In an attempt to improve the cutting tool productivity while machining hardened EN31 steel, uncoated ceramic inserts were used with the Minimum Quantity Lubrication (MQL) environment, which resulted in significant wear reduction on the ceramic inserts along with a better surface finish than that produced with a dry cutting. The most suitable process parameters, to produce an efficient cut, i.e., high process performance on both wear and surface finish fronts, were proposed. The surface integrity produced within the process parameter window identified was compared for both dry and MQL environments. It was confirmed that application of MQL brought about a significant reduction in formation of subsurface white layer both at lower and higher feeds (around 40% and 16.5% respectively) when compared to dry mode cutting. MQL condition enhanced the overall productivity of ceramic inserts with lower flank wear and better surface characteristics even at higher feeds, while at the same time, producing a thinner white layer.

Theophylline Determination in Pharmaceuticals Using a Novel High-performance Liquid Chromatographic Process

Objective: The current study aims to find a suitable, accurate, and faster RP-HPLC technique for the determination of theophylline, which could then be validated in accordance with the International Conference on Harmonization (ICH) guidelines. The Aim of this Study: The aim of this study was to develop an efficient, accurate, and faster RP-HPLC method for determining theophylline, which was then validated using the International Conference on Harmonization (ICH) guidelines. Methods: In the HPLC analysis, the Waters 2695 was used. The drug was isolated better using an Ion Pac zorbax 300-SCX Agilent Column, 5 m, 4.6 250 mm, with a liquid phase of Orthophosphoric acid (0.1 percent Orthophosphoric acid in HPLC acetonitrile and Methanol in the ratio of 50:50 v/v at a flow rate of 1ml/min, with discovery at 280 nm using a PDA detector. Results: Theophylline's preservation time was discovered to be 3.747 0.127 min. In the 5-25 mg/l range, the procedure was found to be linear, with a parallel coefficient (R2) of 0.9998. The LOD and LOQ of the system were determined to be (0.99 and 3) g/ml, respectively. The technique and system precisions were predicted using, and the outcomes were determined as percent RSD principles, which were noticed to be within the strict limitations. Theophylline recovery was detected to be in the 99-100 percent range, confirming the method's precision. Conclusion: Using basic ICH guidelines, the suggested RP-HPLC process was validated. The following methodology can be used successfully and easily for routine diagnostic analysis.

Evaluation of PAO adaptability to oxygen concentration change: Development of stable EBPR under stepwise low-aeration adaptation

Recent research has shown the adaptability of Biological Nutrient Removal (BNR) systems to very low level dissolved oxygen (DO) concentration, mainly focusing in the nitrification ability that maintains the nitrogen oxidation process even at very low DO levels. Although step-wise aeration decrease on Enhanced Biological Phosphorus Removal (EBPR) is not fully comprehended. This study investigated the effect of reaching micro-aeration with adaptation strategies on EBPR performance. A step-wise oxygen concentration decrease, arriving at an average aeration level of 0.4 mgO2/L was evaluated, with an outcome of approximately 90 % phosphorus removal efficiency. Compared with different aeration modes, the highest phosphorus (P)-removal efficiency, P-release and lowest effluent phosphorus was achieved in gradual DO decrease strategy. On the other hand, an instant decrease in aeration from stable EBPR process from 2 mgO2/L to 0.4 mgO2/L adversely impacted P-removal by decreasing the efficiency to average 60 % and deteriorating the phosphorus removing microbial consortium. Comparison of results between instant and gradual DO-decrease, indicated the sensitivity of microorganisms to aeration. Microbial adaptation to decreased oxygen availability is crucial to reach high process performance. This study proposes, a potential aeration mode, which contributes in reduction of energy consumption in BNR systems through wastewater treatment.

Management of medical and health big data based on integrated learning-based health care system: A review and comparative analysis

PurposeWe present a Health Care System (HCS) based on integrated learning to achieve high-efficiency and high-precision integration of medical and health big data, and compared it with an internet-based integrated system. MethodThe method proposed in this paper adopts the Bagging integrated learning method and the Extreme Learning Machine (ELM) prediction model to obtain a high-precision strong learning model. In order to verify the integration efficiency of the system, we compare it with the Internet-based health big data integration system in terms of integration volume, integration efficiency, and storage space capacity. ResultsThe HCS based on integrated learning relies on the Internet in terms of integration volume, integration efficiency, and storage space capacity. The amount of integration is proportional to the time and the integration time is between 170-450 ms, which is only half of the comparison system; whereby the storage space capacity reaches 8.3×28TB. ConclusionThe experimental results show that the integrated learning-based HCS integrates medical and health big data with high integration volume and integration efficiency, and has high space storage capacity and concurrent data processing performance.

Development of Optimal Design and Circular Broach Modular Design of Disc Cutters with the Development of a Parametric Model

Cutting tool is one of the most important instruments in production. It is used for machining of different components on machine tools. A material is cut into a chip to incur the desired work piece surface currently used in engineering various cutting tools. The directions of development of structures of metal cutting tools are: higher precision of dimensional and geometrical parameters, the use of new tool materials, cost, and quick. The cutting tools are not only affected by the design of machine, technology of manufacturing of products, but also impact the constructive forms of machine parts. The emergence of mechanical spine, thanks to the pull method. Spine broach can provide high-performance processing spine bore with the required accuracy. The development of heavy machine tools required the creation of new designs of large instruments. The use of mechanical automatic lines also required design tools with high dimensional stability capable of handling the items within the specified tolerance for a certain time. Instruments were developed in the process of renewing the cutting edge of the cutting tools with automatic adjustment; setting up tools on the size of the machine is a device for automatic replacement of worn tool in the process line of the Computer-Aided Manufacturing CAM of the cutting tool special requirements. Equipment must operate with high level efficiency, so to reduce the loss of time resetting of the need to minimal. A cutting tool requires knowledge of the theoretical foundations of design and calculation tools using CAD.

Preparation of poly(butylene succinate) vitrimer with thermal shape stability via transesterification reaction

AbstractPoly(butylene succinate) (PBS) refers to a high‐performance biodegradable polymer employed to substitute petroleum polymers that cause environmental issues. However, PBS exhibits the defect of flowing above the melting point and rapid dripping for its poor melt strength. Accordingly, this study proposed a novel method to fabricate PBS vitrimer by exploiting reactive extrusion technology to mix diepoxide with PBS and then by employing zinc acetate as a catalyst to crosslink the PBS. Therefore, after the reaction extrusion blending, the blend still has a lower viscosity and high processing performance; in the subsequent curing process, the polymer undergoes a transesterification reaction and the viscosity increases. Via transesterification to form a cross‐linked network, the storage modulus, and loss modulus of PBS vitrimer at 140°C reach 55,800% and 3500% of pure PBS, respectively. At this time, the crystallinity of PBS vitrimer is still as high as 56.9% (The crystallinity of pure PBS is 47.4%). And the shape stability of PBS at high temperatures was significantly improved. Moreover, PBS vitrimer could still be reshaped after the cross‐linking process. This study proposed a facile method to produce PBS materials exhibiting high thermal shape stability.

Temperature measurement of turbulent flame using CT-TDLAS (computed tomography-tunable diode laser absorption spectroscopy)

In order to satisfy the requirements of high-quality and high-performance optimal material manufacturing process, it is essential to control the gas system of the manufacturing process. In the actual industry, the quality of products is improved by controlling various gases in the manufacturing process. The tunable laser absorption spectroscopy (TDLAS) technique can be measured by the temperature and concentration of target gas simultaneously. Among the more advanced technologies, CT-TDLAS is the most crucial technique for measuring temperature and concentration distributions across two-dimensional planes. This study suggests a three-dimensional useful measurement of irregular flow or exhaust gases. Furthermore, an optical measurement method has been adopted to measure temperature distribution at a cross-section of the Methane Air premixed turbulent flame. The equivalence ratio of fuel can control this system. The burner system consists of two sections (main flame, sub-flame) for a turbulent flame. In the CT-TDLAS technique, it is essential to set the wavelength for target gases. There is a limit to high-temperature measurement in temperature estimation using a single laser-specific wavelength. Therefore, compared measurement performance was made using a mixed type laser (1388 nm, 1343 nm) and a single type laser (1388 nm). The temperatures obtained by using the optical measurement results were relatively evaluated with those obtained by the thermocouples. It was confirmed that the relative error of the temperature occurred at the central position of the burner. It was about 13.33% by the mixed laser system and 38.33% by the single laser system in most close to point from the burner.

Complexity Analysis of a Versatile Video Coding Decoder over Embedded Systems and General Purpose Processors.

The increase in high-quality video consumption requires increasingly efficient video coding algorithms. Versatile video coding (VVC) is the current state-of-the-art video coding standard. Compared to the previous video standard, high efficiency video coding (HEVC), VVC demands approximately 50% higher video compression while maintaining the same quality and significantly increasing the computational complexity. In this study, coarse-grain profiling of a VVC decoder over two different platforms was performed: One platform was based on a high-performance general purpose processor (HGPP), and the other platform was based on an embedded general purpose processor (EGPP). For the most intensive computational modules, fine-grain profiling was also performed. The results allowed the identification of the most intensive computational modules necessary to carry out subsequent acceleration processes. Additionally, the correlation between the performance of each module on both platforms was determined to identify the influence of the hardware architecture.

SeqFu: A Suite of Utilities for the Robust and Reproducible Manipulation of Sequence Files.

Sequence files formats (FASTA and FASTQ) are commonly used in bioinformatics, molecular biology and biochemistry. With the advent of next-generation sequencing (NGS) technologies, the number of FASTQ datasets produced and analyzed has grown exponentially, urging the development of dedicated software to handle, parse, and manipulate such files efficiently. Several bioinformatics packages are available to filter and manipulate FASTA and FASTQ files, yet some essential tasks remain poorly supported, leaving gaps that any workflow analysis of NGS datasets must fill with custom scripts. This can introduce harmful variability and performance bottlenecks in pivotal steps. Here we present a suite of tools, called SeqFu (Sequence Fastx utilities), that provides a broad range of commands to perform both common and specialist operations with ease and is designed to be easily implemented in high-performance analytical pipelines. SeqFu includes high-performance implementation of algorithms to interleave and deinterleave FASTQ files, merge Illumina lanes, and perform various quality controls (identification of degenerate primers, analysis of length statistics, extraction of portions of the datasets). SeqFu dereplicates sequences from multiple files keeping track of their provenance. SeqFu is developed in Nim for high-performance processing, is freely available, and can be installed with the popular package manager Miniconda.

PCJ Java library as a solution to integrate HPC, Big Data and Artificial Intelligence workloads

With the development of peta- and exascale size computational systems there is growing interest in running Big Data and Artificial Intelligence (AI) applications on them. Big Data and AI applications are implemented in Java, Scala, Python and other languages that are not widely used in High-Performance Computing (HPC) which is still dominated by C and Fortran. Moreover, they are based on dedicated environments such as Hadoop or Spark which are difficult to integrate with the traditional HPC management systems. We have developed the Parallel Computing in Java (PCJ) library, a tool for scalable high-performance computing and Big Data processing in Java. In this paper, we present the basic functionality of the PCJ library with examples of highly scalable applications running on the large resources. The performance results are presented for different classes of applications including traditional computational intensive (HPC) workloads (e.g. stencil), as well as communication-intensive algorithms such as Fast Fourier Transform (FFT). We present implementation details and performance results for Big Data type processing running on petascale size systems. The examples of large scale AI workloads parallelized using PCJ are presented.

Task Scheduling Strategy for Heterogeneous Multicore Systems

For heterogeneous computing systems, various types of processor cores cause system performance degradation due to uneven load. In addition, the inability of multitasking to match the appropriate processor core is also an urgent problem. This article proposes a swarm intelligence task scheduling strategy based on the genetic algorithm (GA) for high-performance heterogeneous multicore processors. In order to avoid the falling into local optimal solutions, we employ an adaptive mutation and injection strategy in the algorithm design. This swarm intelligence solution detects the computing capacities of different cores by processing specified tasks beforehand, and then an appropriate solution will be explored by introducing an adaptive mutation GA. Our technique aims to execute various types of tasks on heterogeneous processing cores for optimal performance. Experimental results show that this scheduling strategy can reduce the additional overhead and improve parallel computing efficiency and system performance.

High Performance Process Development for Iron Ore Concentration

References on microwave energy use were reviewed and it demonstrated wide use of this kind of energy in various sectors of national economy. However in ferrous metallurgy this type of energy practically is not used despite the fact that it holds much promise and offers a number of advantages over other kinds of energy. In this work an attempt was made to use microwave energy in ferrous metallurgy and it was implemented in terms of concentration process development for limonite ores of the Lisakskoye deposit with hydro-goethite being a base iron-bearing mineral. Qualitative and quantitative characteristics of the subsequent magnetic separation process were determined. The developed concentration process of the Lisakovskoye deposit ores with the microwave energy used for baking and magnetizing of intermediate concentration products was compared with the current deep concentration process of the Lisakovskiy Mining and Processing Works and its advantages were demonstrated. Technical and economic calculation showed that the concentration process with microwave energy used is more efficient than deep concentration process without the product baking; it allows a significant increase of iron recovery into the concentrate and provides additional profit to the Company.

Performance improvement for a 2D convolutional neural network by using SSC encoding on protein\u2013protein interaction tasks

BackgroundThe interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabolism, which is of extraordinary significance to modern proteomics research. Despite advances in experimental technology, it is still expensive, laborious, and time-consuming to determine protein–protein interactions (PPIs), and there is a strong demand for effective bioinformatics approaches to identify potential PPIs. Considering the large amount of PPI data, a high-performance processor can be utilized to enhance the capability of the deep learning method and directly predict protein sequences.ResultsWe propose the Sequence-Statistics-Content protein sequence encoding format (SSC) based on information extraction from the original sequence for further performance improvement of the convolutional neural network. The original protein sequences are encoded in the three-channel format by introducing statistical information (the second channel) and bigram encoding information (the third channel), which can increase the unique sequence features to enhance the performance of the deep learning model. On predicting protein–protein interaction tasks, the results using the 2D convolutional neural network (2D CNN) with the SSC encoding method are better than those of the 1D CNN with one hot encoding. The independent validation of new interactions from the HIPPIE database (version 2.1 published on July 18, 2017) and the validation of directly predicted results by applying a molecular docking tool indicate the effectiveness of the proposed protein encoding improvement in the CNN model.ConclusionThe proposed protein sequence encoding method is efficient at improving the capability of the CNN model on protein sequence-related tasks and may also be effective at enhancing the capability of other machine learning or deep learning methods. Prediction accuracy and molecular docking validation showed considerable improvement compared to the existing hot encoding method, indicating that the SSC encoding method may be useful for analyzing protein sequence-related tasks. The source code of the proposed methods is freely available for academic research at https://github.com/wangy496/SSC-format/.

Performance Analysis of Adiabatic Vedic Multipliers

Energy dissipation and reliability are the two important design constraints in the high performance processor design. With the advancements in the IC manufacturing and reduced feature sizes the energy dissipation increases in exponential manner at the lower technology nodes. So, there is a need to design energy-efficient and reliable circuits and systems. The reliability with temperature is also one of the major challenges in today’s smart systems as they are operated in harsh environments. Most of the works till date analyzed the reliability with respect to DC constraints. The basic operation in the high performance Digital Signal Processing (DSP) is the multiplication is used to simplify various operations like convolution, filtering and correlation. In this work, a Vedic multiplier with 4x4 size is implemented with FinFET based energy recovery Modified PFAL (MPFAL) logic at 45 nm technology node. The designed multiplier performance is analyzed and compared with our earlier work in terms of energy dissipation and delay. The results indicate a reduction of 55% in energy dissipation over ECRL based Vedic multiplier. Linear variation of power dissipation with temperature in the order of pW shows that design MPFAL Vedic muliplier is more reliable compared to CMOS multiplier.

Implementation and Comparison of Radix-8 Booth Multiplier by using 32-bit Parallel prefix adders for High Speed Arithmetic Applications

This paper presents the implementation and design of Radix-8 booth Multiplier using 32-bit parallel prefix adders. High performance processors have a high demand in the industrial market. For achieving high performance and to enhance the computational speed multiplier plays a key role in performance of digital system. But the major drawback is it consumes more power , area and delay. To enhance the performance and decrease the area consumption and delay there are many algorithms and techniques. In this paper we designed a radix-8 Booth Multiplier using two parallel prefix adders and compared them for best optimized multiplier. The number of parital products generation can be reduced by n/3 by using radix-8 in the multiplier encoding. To further reduce the additions we have used booth recoding mechanism .We have implemented the design using Kogge stone adder and Brent kung adder. We observed that by using parallel prefix adders reduces the delay further more which results in significant increase in speed of the digital systems. The simulation results are carried out on XILINX VIVADO software.

Advanced high-performance processing tools for diagnostics and control in fusion devices

The ITER project demanding operating conditions, as well as other enabling experiments in relevant fusion projects, present new challenges to the diagnostics, control and instrumentation. The most critical requirements relate to the high acquisition rates (up to some gigasample per second), high physical event rate (up to several megaevents per second), need to handle enormous quantities of data in long experimental pulses (up to 30 minutes) and highly complex control and diagnostic algorithms. Radiation hardness of all equipment involved must also be taken into account for high magnetic fields as well as neutron irradiation in the fusion devices port cells.The implementation of state-of-the-art designs were tested both with in-house built prototypes and complete systems installed in the major international fusion experiments. The main technologies used include Advanced Telecommunications Computing Architecture (ATCA), high speed electronic devices for signal digitization, complex real-time algorithms for physics analysis, control and data compression implemented in high-performance computing using field-programmable gate arrays and multicore processor architectures.The control and data acquisition group at Instituto de Plasmas e Fusão Nuclear (Instituto Superior Técnico - Lisboa) has conducted several projects and studies for the development of reliable high-performance processing tools and instrumentation for the diagnostics and control of fusion devices capable of complying with the most demanding requirements.

Atmospheric diffuse plasma jet formation from positive-pseudo-streamer and negative pulseless glow discharges

Atmospheric gas discharge is very likely to constrict into filaments and diffuse plasma formation is inefficient in most cases. Developing cost-efficient atmospheric diffuse plasma devices represents a significant challenge for high performance in biomedical decontamination and material processing. Here, we propose an alternative roadmap to produce a diffuse argon plasma jet by expanding and quenching the existing filamentary discharge at the initial or middle stage of streamer development. Possible mechanisms are summarized. With the gas flow velocity comparable to the ion drift one, enhancing ambipolar diffusion near the edge of the positive-streamer channel promotes the radial diffusion of newly-produced electrons, realizing the radial expansion of channel. Weakening electric field in front of the streamer head through head expansion and field offset, prevents the further development of streamer, leading to a positive-pseudo-streamer discharge. Reducing electric field in front of the negative-streamer head through ion compensation, impedes the initial growth of streamer, resulting in a negative pulseless glow discharge. The positive-pseudo-streamer and negative pulseless glow discharges function together to form the diffuse plasma jet.

Design of MAC unit for digital filters in signal processing and communication

Digital signal processors (DSP) the endless requirement is the development of ability in processors to hold the difficulties resulted in the assimilation of CPU cores in a particular IC. Certain functions like convolution, transform, correlation and filtering are performed using digital signal processor. All these functions requires multiplication and repetitive addition. So multiply and accumulate unit (MAC) has significance in digital signal processor. High performance processes are of high importance in the MAC unit. Finally DSP algorithms depend considerably on speed performance of MAC. In this paper, a high speed MAC unit based on Vedic multiplier(VM) technique is presented for Arithmetic Applications. The VM and the adder blocks in the MAC unit are designed using a high-speed Pipelined Brent Kung (BK) Adder architecture. The proposed design is compared with 32 bit MAC unit constructed using regular Brent Kung adder. It is observed from the synthesis results that proposed MAC unit is operating nearly five times quicker than MAC unit constructed using regular Brent Kung adder. All the designs were implemented on Xilinx Virtex 7 using Verilog HDL.

Simpson’s 3/8–based method stability analysis for milling processes

Chatter stability prediction based on linear time-periodic delay differential equations (DDEs) of the milling dynamic process is an important issue in achieving high-performance processing operations. To obtain efficient and precise regenerative chatter prediction, a novel method for milling stability analysis based on Simpson’s 3/8 rule is proposed. First, the dynamics model of milling processes, considering the regenerative effect, is modeled by an n-dimensional delay differential equation. Second, a set of algebraic equations is obtained to determine the transition matrix by converting and discretizing periodic DDE into a system of integral equations at the neighboring sampling grid points. Then, the eigenvalues of the transition matrix are utilized to determine stability based on Floquet theory. Finally, the comparisons of lobe diagrams calculated by different methods and discretization interval number for one and two degrees of freedom milling models are discussed, and the consistency of the predicted and experimental stability boundaries is analyzed. Results show that the proposed method achieves high computation accuracy with high efficiency.

An Adaptive Throughput-First Packet Scheduling Algorithm for DPDK-Based Packet Processing Systems

The continuous increase in network traffic has sharply increased the demand for high-performance packet processing systems. For a high-performance packet processing system based on multi-core processors, the packet scheduling algorithm is critical because of the significant role it plays in load distribution, which is related to system throughput, attracting intensive research attention. However, it is not an easy task since the canonical flow-level packet scheduling algorithm is vulnerable to traffic locality, while the packet-level packet scheduling algorithm fails to maintain cache affinity. In this paper, we propose an adaptive throughput-first packet scheduling algorithm for DPDK-based packet processing systems. Combined with the feature of DPDK burst-oriented packet receiving and transmitting, we propose using Subflow as the scheduling unit and the adjustment unit making the proposed algorithm not only maintain the advantages of flow-level packet scheduling algorithms when the adjustment does not happen but also avoid packet loss as much as possible when the target core may be overloaded Experimental results show that the proposed method outperforms Round-Robin, HRW (High Random Weight), and CRC32 on system throughput and packet loss rate.