Throughput Rate Research Articles

Digital twin implementation for performance improvement in process industries- A case study of food processing company

In recent years, the emerging Digital Twin (DT) paradigm under Industry 4.0 has been attracting more attention from both practitioners and academia due to its dynamic capabilities. Most DT studies are theoretical and deal with hypothetical analysis, whereas fewer studies are available on real-life empirical cases. Due to dynamic problem-solving capabilities, DT technologies are widely used in performance improvement analysis in food processing companies (FPC) despite limited implication’s for business strategies. Our study incorporates the DT technologies with an implementation case study on FPC and accomplishes the real-life problem of the food processing company (FPC). Moreover, the proposed DT research framework demonstrates the various DT implementation stages, such as strategic mapping and physical-virtual space replica, with rigorous analysis. The results show that DT enhances the existing system’s machine availability, allocation efficiency, technical efficiency, worker efficiency, utilization rate, effectiveness, step ratio, and throughput rate. The proposed physical-virtual interface model is executed using AnyLogic software with JAVA-enabled programming.

How innovations in methodology offer new prospects for volume electron microscopy

Detailed knowledge of biological structure has been key in understanding biology at several levels of organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, the throughput rate of conventional electron microscopes has limited the volume size and number of samples that can be imaged. Recent improvements in methodology are currently driving a revolution in volume EM, making possible the structural imaging of whole organs and small organisms. In turn, these recent developments in image acquisition have created or stressed bottlenecks in other parts of the pipeline, like sample preparation, image analysis and data management. While the progress in image analysis is stunning due to the advent of automatic segmentation and server‐based annotation tools, several challenges remain. Here we discuss recent trends in volume EM, emerging methods for increasing throughput and implications for sample preparation, image analysis and data management.

Reconfigurable Turbo and Low-Density Parity-Check (LDPC) Decoding Accelerators for Powerline Communications

This study presents two reconfigurable turbo/low-density parity-check (LDPC) decoding kernels for the two powerline communication standards, HomePlug and G.hn. Two architectures are presented, both of which use the radix-4 double-binary enhanced max-log maximum a posteriori probability algorithm with next-iteration initialization in turbo decoding. In LDPC decoding, the two architectures employ the normalized min-sum and the layered radix-4 forward and backward algorithms. The two algorithms cause differences in the architecture and throughput rate. Consequently, the proposed decoding kernels have different architectures when combined with the turbo decoding algorithm, and the two proposed decoding kernels each have their own advantages and disadvantages in terms of throughput and area cost. To make the features of two kernels more evident, we have implemented the proposed decoding kernels that lead to significant throughput gains and better area efficiency compared with other studies. The proposed decoding kernels can be operated in all modes specified in the HomePlug and G.hn standards using a 40-nm complementary metal-oxide-semiconductor (CMOS) process. Moreover, the proposed decoding kernels provide different solutions to achieve the expected throughput rates of the G.hn and HomePlug standards.

LAP-BFT: Lightweight Asynchronous Provable Byzantine Fault-Tolerant Consensus Mechanism for UAV Network

Mission-oriented UAV networks operate in nonsecure, complex environments with time-varying network partitioning and node trustworthiness. UAV networks are thus essentially asynchronous distributed systems with the Byzantine General problem, whose availability depends on the tolerance of progressively more erroneous nodes in the course of a mission. To address the resource-limited nature of UAV networks, this paper proposes a lightweight asynchronous provable Byzantine fault-tolerant consensus method. The consensus method reduces the communication overhead by splitting the set of local trusted state transactions and then dispersing the reliable broadcast control transmission (DRBC), introduces vector commitments to achieve multivalue Byzantine consensus (PMVBA) for identity and data in a provable manner and reduces the computational complexity, and the data stored on the chain is only the consensus result (global trustworthiness information of the drone nodes), avoiding the blockchain’s “storage inflation” problem. This makes the consensus process lighter in terms of bandwidth, computation and storage, ensuring the longevity and overall performance of the UAV network during the mission. Through QualNet simulation platform, existing practical asynchronous consensus algorithms are compared, and the proposed method performs better in terms of throughput, consensus latency and energy consumption rate.

A blockchain-based framework to support pharmacogenetic data sharing

The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue. The design requirements for PGxChain were identified through a systematic literature review, identifying technical challenges and barriers impeding the clinical implementation of pharmacogenomics. These requirements included security and privacy, accessibility, interoperability, traceability and legal compliance. A proof-of-concept implementation based on Ethereum was then developed that met the design requirements. PGxChain’s performance was examined using Hyperledger Caliper for latency, throughput, and transaction success rate. The findings clearly indicate that blockchain technology offers considerable potential to advance pharmacogenetic data sharing, particularly with regard to PGx data security and privacy, large-scale accessibility of PGx data, PGx data interoperability between multiple health care providers and compliance with data-sharing laws and regulations.

Modeling and Performance Analysis of a Fault-Tolerant 3D Photonic Network-on-Chip Based on Hybrid Photonics-Plasmonics.

The performance of electro-optic modulators and optical routers and their routing algorithms are the key factors affecting the performance of networks on optical chips. This paper improves the mesh 3-dimensional photonic network-on-chip (3D-PNoC) topology. An SPP hybrid silicon-based electro-optic modulator and an improved fault-tolerant SPP router are used to improve the performance of the network on an optical chip. SPP switching and SPP MRR are combined to form a fault-tolerant SPP router. On this basis, an improved genetic optimization routing algorithm is implemented on the improved mesh 3D PNoC topology, which completes the data exchange of the IP core of the network on the optical chip. Compared with the case of traditional optoelectronic devices, the performance of on-chip optical networks can be improved effectively. The simulation results show that upon the application of the improved genetic optimization routing algorithm to the improved mesh 3D PNoC topology, the average end-to-end delay is reduced by 32.9%, the throughput rate is increased by 28.5%, and the system power consumption is reduced by 27.6%. On the other hand, the average insertion loss and noise of optical routers are increased by 2.94 dB and 2.95 dB, respectively.

Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress.

Internet of Medical Thing (IoMT) is the most emerging era of the Internet of Thing (IoT), which is exponentially gaining researchers' attention with every passing day because of its wide applicability in Smart Healthcare systems (SHS). Because of the current pandemic situation, it is highly risky for an individual to visit the doctor for every small problem. Hence, using IoMT devices, we can easily monitor our day-to-day health records, and thereby initial precautions can be taken on our own. IoMT is playing a crucial role within the healthcare industry to increase the accuracy, reliability, and productivity of electronic devices. This research work provides an overview of IoMT with emphasis on various enabling techniques used in smart healthcare systems (SHS), such as radio frequency identification (RFID), artificial intelligence (AI), and blockchain. We are providing a comparative analysis of various IoMT architectures proposed by several researchers. Also, we have defined various health domains of IoMT, including the analysis of different sensors with their application environment, merits, and demerits. In addition, we have figured out key protocol design challenges, which are to be considered during the implementation of an IoMT network-based smart healthcare system. Considering these challenges, we prepared a comparative study for different data collection techniques that can be used to maintain the accuracy of collected data. In addition, this research work also provides a comprehensive study for maintaining the energy efficiency of an AI-based IoMT framework based on various parameters, such as the amount of energy consumed, packet delivery ratio, battery lifetime, quality of service, power drain, network throughput, delay, and transmission rate. Finally, we have provided different correlation equations for finding the accuracy and efficiency within the IoMT-based healthcare system using artificial intelligence. We have compared different data collection algorithms graphically based on their accuracy and error rate. Similarly, different energy efficiency algorithms are also graphically compared based on their energy consumption and packet loss percentage. We have analyzed our references used in this study, which are graphically represented based on their distribution of publication year and publication avenue.

Foam in Absorption Columns with Structured Packings – Part 2: Inhibition and Destruction

AbstractFoam in absorption and distillation processes is one of the main reasons for malfunctions in columns including higher pressure loss, lower throughput, and lower mass transfer rates leading to a reduction in the separation efficiency. This study evaluates different foam management solutions aiming at a foam‐reduced operation of columns with structured packings based on fundamental investigations. Firstly, the effect of spacers between structured packing layers is presented as a passive foam inhibition method. Secondly, the ability of acoustic waves at low frequencies around 50 s−1 (Hz) destructing existing foam in columns is analyzed and discussed. This method is able to reduce the pressure loss by –56 % and increase the corresponding F‐factor by +22 % in a DN300 column in continuous operation.

Foam in Absorption Columns with Structured Packings – Part 1: Characterization

AbstractFoam in absorption and distillation processes is one of the main reasons for malfunctions in columns including higher pressure loss, lower throughput, and lower mass transfer rates leading to a reduction in separation efficiency. Detailed investigations on the foam formation and its behavior in structured packings are conducted using two different scales: a transparent rectangular measurement cell and a DN300 column. The influence of maldistributions in structured packing is discussed along with a first‐time identified foam‐related hysteresis effect. Ad‐ and disadvantages of fully wetted film flow and partially wetted rivulet flow on foam formation are discussed in detail. Overall, structured packings without a microstructure show a reduced foam formation compared to structured packings with a microstructure.

G-tran

Graph transaction processing poses unique challenges such as random data access due to the irregularity of graph structures, low throughput and high abort rate due to the relatively large read/write sets in graph transactions. To address these challenges, we present G-Tran, a remote direct memory access (RDMA)-enabled distributed in-memory graph database with serializable and snapshot isolation support. First, we propose a graph-native data store to achieve good data locality and fast data access for transactional updates and queries. Second, G-Tran adopts a fully decentralized architecture that leverages RDMA to process distributed transactions with the massively parallel processing (MPP) model, which can achieve high performance by utilizing all computing resources. In addition, we propose a new multi-version optimistic concurrency control (MV-OCC) protocol with two optimizations to address the issue of large read/write sets in graph transactions. Extensive experiments show that G-Tran achieves competitive performance compared with other popular graph databases on benchmark workloads.

Dynamic Traffic Allocation in IEEE 802.11be Multi-Link WLANs

The multi-link operation (MLO) is a key feature of the next IEEE 802.11be Extremely High Throughput amendment. Through its adoption, it is expected to enhance users’ experience by improving throughput rates and latency. However, potential MLO gains are tied to how traffic is distributed across the multiple radio interfaces. In this letter, we introduce a traffic manager atop MLO, and evaluate different high-level traffic-to-link allocation policies to distribute incoming traffic over the set of enabled interfaces. Following a flow-level approach, we compare both non-dynamic and dynamic traffic balancing policy types. The results show that the use of a dynamic policy, along with MLO, allows to significantly reduce the congestion suffered by traffic flows, enhancing the traffic delivery in all the evaluated scenarios, and in particular improving the quality of service received by video flows. Moreover, we show that the adoption of MLO in future Wi-Fi networks improves also the coexistence with non-MLO networks, which results in performance gains for both MLO and non-MLO networks.

Современное обогащение железной руды – вызовы и решения от ALLMINERAL

This article describes current technologies and their application to various types of iron ores characterized with different material composition. The data presented demonstrate specific advantages of the Alljig jigging machine used in iron ore processing due to the precise separation with high density as well as the ease and low cost of operation. The Allflux hydroclassification technology ensures high output and yields three products. The Allgauss high intensity magnetic separators for slightly magnetic particles offer high throughput rates combined with unparalleled process flexibility and two-stage processing in a single plant. The Allflot pneumatic ejector flotation chambers can half the equipment footprint of the processing plant, while increasing the recovery of fine particles by reverse flotation. Technological performance indicators of the ArcelorMittal jigging machines are provided (CIS).

FPGA Implementation of High-Performance s-box Model and Bit-level Masking for AES Cryptosystem

The inadequacies inherent in the existing cryptosystem have driven the development of exploit the benefits of cipher key characteristics and associated key generation tasks in cryptosystems for high-performance security systems. In this paper, cipher key-related issues that exists in conventional symmetric AES crypto system is considered as predominant issues and also discussed other problems such as lack of throughput rate, reliability and unified key management problems are considered and solved using appropriate hierarchical transformation measures. The inner stage pipelining is introduced over composite field based s-box transformation models to reduce the path delay. In addition to that, this work also includes some bit level masking technique for AES. The improved diffusion and confusion metrics of bit masking transformation model mitigates key management related issues. An extensive analysis of data rate proved the performance metrics of proposed AES model. And finally, FPGA implementation is carried out to validate the performance metrics in real time.

Understanding the Key Features of Wi-Fi 6 and Exploring the Effect of Modulation Scheme on Throughput Rate

Today, the number of smart devices and applications are increasing day by day, whereas the older versions of Wi-Fi stander, i.e., n/a/g cannot meet the greed and need of these devices. Thus, the development of applications and devices has called to design of a new Wi-Fi version. Hence, a new Wi-Fi 6 vision has been promoted based on 802.11 IEEE stander. The scope of this paper has focused on the study and overview of Wi-Fi 6 features. As well as, exploring the simulation tools that can be used to implement 802.11ax. A simulation has been done by using NS-3 to measure the effect of modulation and coding schemes on the throughput rate. Where a scenario of the network model was taken on a single AP with a node and the MCS value range is (0 to 7), the channel width (20, 40, 80 or 160 MHz) and the guard interval (800ns, 1600ns or 3200ns). The time of simulation was set to 10 seconds. Hence, the output results explained that the change of modulation properties can increase/reduce the throughput rate.

Optimization Design and Performance Analysis of Improved IEEE802.11p MAC Mechanism Based on High Mobility of Vehicle

The high-speed movement of vehicles is the core factor affecting the rapid development of vehicular ad hoc network (VANET), especially the impact of vehicle mobility on data access and transmission performance. However, the classic IEEE802.11p data access and transmission protocol are still used in the multi-hop VANET under the highway system, which is adopted in the low-speed environment. Therefore, the impact of vehicle movement on the performance of the existing network is analyzed theoretically, and it is found that the network performance will be greatly reduced with the increase of vehicle speed. In order to improve the network performance in high-speed environment, an improved network access transmission protocol is proposed. Through Markov modeling, the analytic expressions of system delay, throughput, and packet loss rate are obtained. Finally, the effectiveness of the improved mechanism is verified by comparing the simulation results of two mechanisms.

Velocity‐based stowage policy for a semiautomated fulfillment system

AbstractOnline retail fulfillment is increasingly performed by semiautomated fulfillment systems in which inventory is stored in mobile pods that are moved by robotic drives. In this paper, we develop a model that explores the benefits of velocity‐based stowage policies for semiautomated fulfillment systems, also known as robotic mobile fulfillment systems. The stowage policies decide which pods to replenish with the received inventory. Specifically, we model policies that account for the velocity of the units being stowed. By stowing higher (lower) velocity units on higher (lower) velocity pods, we expect to increase the heterogeneity of the pod velocities. Greater heterogeneity in pod velocities can yield a greater reduction in pod travel distance from velocity‐based storage policies for the pod. Reducing pod travel distance decreases the number of robotic drives that are needed for the system to maintain a certain throughput rate. We analyze an M‐class velocity‐based stowage policy. We stow units from each velocity class onto pods dedicated to that velocity class; each class of pods then has its own storage zone, where the zones are ordered based on the distance to the stationary pick and stow stations. We characterize the pod travel distance as a function of the skewness of the demand distribution and the number and size of the classes. We find that with two or three classes we can achieve most of the benefits possible from a velocity‐based stowage and storage policy. For representative demand distributions, we find that a two‐class policy achieves 75% of the maximum possible travel‐time reduction and that a three‐class policy improves this to 90%.

A Code Rate-Compatible High-Throughput Hardware Implementation Scheme for QKD Information Reconciliation

For high-speed quantum key distribution (QKD) post processing, information reconciliation is the most computational step, which usually acts as the system speed bottleneck. Reconciliation efficiency and operation throughput are the two most important performance parameters, but they are often compromised to each other in actual realization due to the available hardware resources. Another characteristic of the information reconciliation is that its channel is time-varying, and in order to guarantee high efficiency, some rate-compatible error correction scheme should be adopted. To cope with the above problems, this paper proposes a rate-compatible high-efficiency reconciliation algorithm based on quasi-cyclic (QC) low-density parity-check (LDPC) codes and puncturing algorithms. On the other hand, in order to obtain high throughput while maintaining low implementation complexity, the normalized min-sum algorithm (NMSA) is realized and optimized by using the fast prototyping tool of high-level synthesis (HLS). The proposed information reconciliation module was implemented on the Xilinx Zynq Ultrascale+ ZCU102 development board. Experimental results show that the maximum throughput rate of the implemented reconciliation module in this paper can reach 136 Mbps, while the efficiency factor is kept lower than 1.32 across the error rate range of 1.7%∼10.6% under the remaining frame error rate level of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> . The comprehensive good performance obtained by our design can strongly support the development of modern high-speed QKD systems.

A Raman immunosensor based on SERS and microfluidic chip for all-fiber detection of brain natriuretic peptide

Early diagnosis of chronic heart failure (CHF) relies on the ultra-sensitive detection assay of its main biomarker, Brain natriuretic peptide (BNP). To meet such demand, we designed a near-infrared immunoassay biosensor, utilizing a fiber-embedded microfluidic chip for surface-enhanced Raman scattering (SERS) detection. A SERS probe, consisting of metal–organic framework and Au-HEPES coupling nanoparticles (AuHPs), was used to enhance the Raman signal of the toluidine blue (TB) dye. The probe anchored with TB is used as a SERS tag, which is linked to BNP through sandwich method. To enhance the Raman signal further, we embedded a SERS substrate at the bottom of the microfluidic channel, which serves an enhancer when the SERS tagged BNP passes through the microfluidic chip. The amplified Raman signal was collected by an optical fiber probe of a simple and portable Raman detection system with an all-fiber connected configuration. Such design resulted in the lowest detection limit of pg/mL, indicating that the proposed platform can be used for rapid and highly sensitive detection of BNP. In addition, our platform also has the advantages of low sample consumption and high throughput rate, providing an effective scheme for the early diagnosis of CHF.

Improved Multi-Channel Multi-Interface Routing Protocol for Wireless Mesh Networks

In recent years, Wireless Mesh Networks (WMN) are emerging as a potential technology to enhance the ability and availability of wireless networks. WMN consists of wireless mesh routers and terminals connected by wireless multi-hop communication. Besides, in WMN, each wireless node owns many interfaces, and each interface operates on many channels. However, effectively using multiple orthogonal channels and multiple interfaces to increase the performance of WMN and decrease the radio link transmission interference is of significant challenge. In this paper, we consider routing issues in WMN. Then, we proposed an on-demand routing protocol, adaptive multi-channel multi-interface operation, improved from the AODV protocol. This protocol is capable of effectively managing communication in the WMN and limited effects of co-channel interference. The simulation results on NS2 show that our proposed protocol improves throughput, delay and packet delivery rate compared to existing traditional protocols.

FOC-MOP: Fuzzy Optimal Clustering Based Multi-Objective Parameter Route Selection for Energy Efficiency

Wireless sensor networks are emerging and involved in a wide range of applications. Improving energy efficiency is a significant task in WSNs. Energy consumption is a crucial problem that affects the network lifetime due to energy limitations in sensor nodes. So, it's required to introduce more energy-efficient protocols for WSNs. Different types of energy-efficient solutions exist for WSNs. The energy consumption is optimized and controlled if clustering is an efficient data collection method. The cluster heads aggregate the data from the member nodes and transmit the aggregated data to BS (base station) either in an uncompressed or compressed manner after collecting all data by the cluster-heads (CHs). Due to the heavy inter-cluster relay and aggregation Overhead, earlier death happens to the CHs located very close to the sink. There is a need for an efficient and reliable CH selection algorithms to select reliable CHs to prevent the earlier death of CHs and frequent reselection of CHs. Therefore, in this work, a fuzzy optimal CH selection algorithm is proposed to select the optimal CHs to improve the network's lifetime. The proposed algorithm uses the following multi-objective parameters: cluster load, communication cost, neighbour density, inter and intra-cluster distance, and node energy for CH selection. The modified Emperor Penguin Optimization (EPO) is used in the proposed work to determine an optimal route for transmitting the data from CH to sink. The modified EPO algorithm helps to improve the multi-hop routing efficiency, reduces the cost of long-distance transmission, and decreases energy utilization during data transmission. The modified EPO considers the parameters like link quality factor, relative distance factor, and residual energy factor for relay selection. The proposed technique was compared against earlier methods like Z-DSS, CCR, RETOPSIS, and LEACH-FC. The various parameters like packet delivery ratio, lifetime, energy consumption, end-to-end delay, and Throughput are studied. The evaluation results prove that the proposed mechanism achieves 40% energy efficiency with 60% lesser Overhead and improves the Throughput rate by 50% than the compared methods.