Suitable Configuration Research Articles

Mathematical modelling and comparative analysis of treatment technologies for upgrading wastewater treatment plants: A case study of biofilm reactors in El-Gouna, Egypt

In recent years, Moving Bed Biofilm Reactors (MBBRs) have been preferred to conventional processes with suspended biomass. The main reason for this preference is that it can achieve better removal efficiencies than conventional systems with smaller footprints. However, unlocking the full potential of MBBRs in large-scale WWTPs remains challenging in real life. In this study, the performance of three different treatment technologies, Extended Aeration Activated Sludge (EAAS), Hybrid Fixed Bed Biofilm Reactor (HFBBR), and Hybrid Moving Bed Biofilm Reactor (HMBBR), was investigated over a year in a WWTP located in El-Gouna, Egypt. The COD removal efficiencies of the three systems were comparable, with the EAAS achieving 93.5%, HFBBR 94%, and HMBRR 95%. Nevertheless, the NH4 removal efficiency of the EAAS was slightly lower (97.5%) than that of the HFBBR and the HMBBR, that achieved a removal efficiency of 98%. BioWin Software was able to mimic the real case of the WWTP of El-Gouna and critically defined all plant limitations and operational data. Different simulations were modeled to test the hydraulic and organic loading capacities of the three systems under different scenarios and operating conditions. The HMBBR system failed to withstand the increase in organic load because of the biomass sloughing effect and subsequently high TSS loads in the settlers. Biomass sloughing overloaded the settlers and lead to biomass loss in the effluent. As the settleability of the HMBBR sludge was significantly lower than for the HFBBR the TSS loss in the effluent happened that much earlier that the moving carrier application had an adverse effect contradicting with the primary purpose of adding media carriers. Model simulations and data analysis findings were used to recommend the most suitable configuration for upgrading an existing system using the attached growth technique with all kinetic parameters and operational conditions. The recommended configuration focuses mainly on the separation of plastic media in a compartment with a very low hydraulic retention time to absorb the incoming shock load.

Learning Human-to-Robot Dexterous Handovers for Anthropomorphic Hand

Human-robot interaction plays an important role in robots serving human production and life. Object handover between humans and robotics is one of the fundamental problems of human-robot interaction. The majority of current work uses parallel-jaw grippers as the end-effector device, which limits the ability of the robot to grab miscellaneous objects from human and manipulate them subsequently. In this paper, we present a framework for human-to-robot dexterous handover using an anthropomorphic hand. The framework takes images captured by two cameras to complete handover scene understanding, grasp configurations prediction, and handover execution. To enable the robot to generalize to diverse delivered objects with miscellaneous shapes and sizes, we propose an anthropomorphic hand grasp network (AHG-Net), an end-to-end network that takes the single-view point clouds of the object as input and predicts the suitable anthropomorphic hand configurations with 5 different grasp taxonomies. To train our model, we build a large-scale dataset with 1M hand grasp annotations from 5K single-view point clouds of 200 objects. We implement a handover system using a UR5 robot arm and HIT-DLR II anthropomorphic robot hand based on our presented framework, which can not only adapt to different human givers but generalize to diverse novel objects with various shapes and sizes. The generalizability, reliability, and robustness of our method are demonstrated on 15 different novel objects with arbitrary handover poses from frontal and lateral positions, a system ablation study, a grasp planner comparison, and a user study on 6 participants delivering 15 objects from two benchmark sets.

Noah: Reinforcement-Learning-Based Rate Limiter for Microservices in Large-Scale E-Commerce Services.

Modern large-scale online service providers typically deploy microservices into containers to achieve flexible service management. One critical problem in such containerbased microservice architectures is to control the arrival rate of requests in the containers to avoid containers from being overloaded. In this article, we present our experience of rate limit for the containers in Alibaba, one of the largest e-commerce services in the world. Given the highly diverse characteristics of containers in Alibaba, we point out that the existing rate limit mechanisms cannot meet our demand. Thus, we design Noah, a dynamic rate limiter that can automatically adapt to the specific characteristic of each container without human efforts. The key idea of Noah is to use deep reinforcement learning (DRL) that automatically infers the most suitable configuration for each container. To fully embrace the advantages of DRL in our context, Noah addresses two technical challenges. First, Noah uses a lightweight system monitoring mechanism to collect container status. In this way, it minimizes the monitoring overhead while ensuring a timely reaction to system load changes. Second, Noah injects synthetic extreme data when training its models. Thus, its model gains knowledge on unseen special events and hence remains highly available in extreme scenarios. To guarantee model convergence with the injected training data, Noah adopts task-specific curriculum learning to train the model from normal data to extreme data gradually. Noah has been deployed in the production of Alibaba for two years, serving more than 50 000 containers and around 300 types of microservice applications. Experimental results show that Noah can well adapt to three common scenarios in the production environment. It effectively achieves better system availability and shorter request response time compared with four state-of-the-art rate limiters.

Experimental Study on Fire Performance of Polymer Foam Cavity Insulated Light Steel Framed Walls

AbstractLight steel frame (LSF) building systems are a fast, reliable and economical construction system for residential and non‐residential buildings. Since the thermal conductivity of steel significantly limits the effectiveness of such wall systems for use in modern energy‐efficient buildings, adequate thermal insulation is essential. For this reason, numerous research studies have been conducted on LSF structures with different types and positions of thermal insulation. Due to the combustible nature of polymer foam, LSF systems insulated with this type of insulation have not been the focus of this research. On the other hand, polymer foam is ideal for automated industrial production of prefabricated load‐bearing LSF walls, and research on such walls is mandatory. In this paper, the fire test results of two innovative LSF walls with polymer foam insulation and different gypsum fibreboards are presented. In the proposed configuration, spacers are also used to prevent direct contact between the wall panels and the steel studs. The study conducted shows that a suitable configuration of gypsum fibreboards can lead to satisfactory fire resistance of energy‐efficient LSF wall systems with polymer foam.

Rapidly Determine the Maximum Power Point in the Parallel Configuration of the Photovoltaic System.

The maximum power point tracking (MPPT) solutions improve power generation efficiency, quickly stabilizing the output waveform of photovoltaic (PV) systems under variable operating conditions. Along with new algorithms, improved and adjusted methods to exploit energy from PV systems are increasingly being researched and proposed. However, the proposed solutions based on the traditional algorithms and their improvements have poor performance, while the advanced algorithms or hybrid methods bring high performance but need to be simplified, and the response speed is higher. Moreover, a suitable PV configuration makes choosing a simple but highly efficient algorithm, especially in low-power PV system applications such as rooftop solar power, traffic lights, and moving vehicles…where the number of PV panels is insufficient to implement flexible configurations. This paper proposes a modified version of the Perturb and Observe (MPO) algorithm to improve MPPT performance and increase convergence speed in the parallel structure of PV panels. The Short-Circuit Current (Isc) and Open-Circuit Voltage (Voc) are calculated directly at specific operating conditions to quickly determine the potential maximum power point (MPP) that will reduce power interruptions and increase power generation efficiency compared to periodic updates. Therefore, the proposed solution converges faster, with higher efficiency, and the output signal in static and dynamic MPPT situations is more stable. The results show that the highest efficiency in simulation and experiment is 99.99% and 99.93%, respectively, while the convergence speed is 0.01 s and 0.03 s, respectively. They are better than the traditional Perturb and Observe (P&O) algorithm, the Variable Step Size Perturb and Observe (VSSP&O) method, and the Particle Swarm Optimization (PSO) technique under the same operating conditions. In addition, its performance and convergence speed are also compared with the latest introduced algorithms. The results show that it is valuable and reliable for parallel PV configuration.

Simulation as a Tool for Electropolishing Industrialization

Although the production of parts by additive manufacturing allows a great degree of freedom in design, a recurring problem lies in surface finish compared to the one produced by conventional machining, with important roughness and the risk of detachable particles presence. To overcome these issues, finishing processes are required, such as electropolishing for example. This electrochemical process relies on specific know-how, particularly in the choice of process parameters (agitation, electrical conditions, etc.). However, the high-complexity level of the geometries encountered requires a dedicated cathodes, which necessitates several iterations before reaching suitable configurations. Numerical simulation of electropolishing processes, for different conditions or different materials, allows predicting the thickness and roughness reduction. Indeed, it is possible to run simulations for complex geometries while taking into account agitation. Therefore, numerical studies of different cathode configurations allow a drastic reduction of the number of experimental tests, and therefore an acceleration of the industrialization. Figure 1

EvolveNet: Evolving Networks by Learning Scale of Depth and Width

Convolutional neural networks (CNNs) have shown decent performance in a variety of computer vision tasks. However, these network configurations are largely hand-crafted, which leads to inefficiency in the constructed network. Various other algorithms have been proposed to address this issue, but the inefficiencies resulting from human intervention have not been addressed. Our proposed EvolveNet algorithm is a task-agnostic evolutionary search algorithm that can find optimal depth and width scales automatically in an efficient way. The optimal configurations are not found using grid search, and are instead evolved from an existing network. This eliminates inefficiencies that emanate from hand-crafting, thus reducing the drop in accuracy. The proposed algorithm is a framework to search through a large search space of subnetworks until a suitable configuration is found. Extensive experiments on the ImageNet dataset demonstrate the superiority of the proposed method by outperforming the state-of-the-art methods.

Automated Configuration of Gripper Fingers from a Construction Kit for Robotic Applications

Gripper finger design is a complex process that requires a lot of experience, time, and effort. For this reason, automating this design process is an important area of research that has the potential to improve the efficiency and effectiveness of robotic systems. The current approaches are aimed at the automated design of monolithic gripper fingers, which have to be manufactured additively or by machining. This paper describes a novel approach for the automated design of gripper fingers. The motivation for this work stems from the increasing demand for flexible, adaptable handling systems in various industries in response to the increasing individualization of products as well as the increasing volatility in the markets. Based on the CAD data of the handling objects, the most suitable configuration of gripper fingers can be determined from the existing modules of a construction kit for the respective handling object, which can significantly reduce the provisioning time for new gripper fingers. It can be shown that gripper fingers can be effectively configured for a variety of objects and two different grippers, increasing flexibility in industrial handling processes.

Segmenting white matter hyperintensities in brain magnetic resonance images using convolution neural networks

White matter hyperintensities (WMHs) are found on magnetic resonance (MR) images of older individuals and are associated with many neurodegenerative disorders, although the exactrole of WMHs in Alzheimer’s disease and other dementias remains an open area of research. Fluid-attenuated inversion recovery (FLAIR) MR imaging sequences show WMHs with good image contrast. Manual segmentation of WMHs on FLAIR images is the widely accepted “gold standard”, however, this step is often time-consuming and has a high inter-rater variability. The absence of an automated, robust and accurate approach to segment WMHs remains a processing bottleneck. We explored convolutional neural networks (CNNs) for performing semantic segmentation of WMHs in FLAIR images. Two sets of experiments were conducted: (1) Variations of U-shaped CNNs (U-Nets) were evaluated in 186 individuals, specifically, four architectures (VGG16, VGG19, ResNet152 and EfficientNetB0) having three dimensionalities (2D, 2.5D and 3D). (2) New data from 60 individuals were added to test the generalizability of U-Net, LinkNet and Feature-Pyramid Network (FPN) variants. The first experiment showed that the 2.5D implementation with VGG16 or VGG19 was the most suitable configuration when segmenting WMH (F-measure > 95% and intersection-over-union > 90%). The second experiment confirmed generalizability of these variants when using unprocessed FLAIR images.

A New Reconfigurable Agricultural Vehicle Controlled by a User Graphical Interface: Mechanical and Electronic Aspects

The use of innovative mobile vehicles with increasingly advanced mechatronic aspects in the agricultural sector is becoming, in recent years, a stimulating field of research and comparison. In particular, the problem addressed in the present work refers to improving the locomotion of mobile vehicles on agricultural terrain by reducing the soil damage and improve the overall performance. Agricultural vehicles generally use tracks and wheels for locomotion; the main difference between the two systems is the contact area with the ground and, consequently, the pressure distribution. The present work presents a new reconfigurable agricultural vehicle that can switch from one locomotion system to another, choosing the suitable configuration according to the terrain conditions. All the mechanical and electronic aspects of the prototype developed are analyzed together with an in-depth analysis of the management of the innovative functions through a user-friendly graphical interface able to control the vehicle.

Effects of variable porosity net on flow field inside deep-sea aquaculture cage

This paper focuses on the effect of the porosity of nets on the flow field inside the deep-sea aquaculture cage. Based on CFD method, the 2D flow fields inside and surrounding the deep-sea aquaculture cage from different views are simulated. The effects of certain porosity net and variable porosity net with different configurations on the fishability area, aquaculture efficiency and benefit of the cage are investigated. The results showed that the variable porosity net with suitable configurations in vertical direction can increase the fishability area and change the flow field inside the cage. This can be conducive to improving the efficiency of fish aquaculture. In horizontal direction, increasing the porosity of the nets parallel to the incoming flow direction can increase the fishability area and improve the water exchange capacity. This can be beneficial to improve fish aquaculture benefit. The results of this paper can guide for the selection of nets for deep-sea aquaculture cages.

Estimating SpO2 with Deep Oxygen Desaturations from Facial Video Under Various Lighting Conditions: A Feasibility Study.

This paper presents a feasibility study to collect data, process signals, and validate accuracy of peripheral oxygen saturation (SpO2) estimation from facial video in various lighting conditions. We collected facial videos using RGB camera, without auto-tuning, from subjects when they were breathing through a mouth tube with their nose clipped. The videos were record under four lighting conditions: warm color temperature and normal brightness, neutral color temperature and normal brightness, cool color temperature and normal brightness, neutral color temperature and dim brightness. The air inhaled by the subjects was manually controlled to gradually induce hypoxemia and lower subjects' SpO2 to as low as 81%. We first extracted the remote photoplethysmogram (rPPG) signals from the videos. We applied the principle of pulse oximetry and extracted the ratio of ratios (RoR) for two color combinations: Red/Blue and Red/Green. Next, we assessed SpO2 estimation accuracy against the ground truth, a Transfer Standard Pulse Oximeter. We have achieved an RMSE of 1.93% and a PCC of 0.97 under the warm color temperature and normal brightness lighting condition using leave-one-subject-out cross validation between two subjects. The results have demonstrated the feasibility to estimate SpO2 remotely and accurately using consumer level RGB camera with suitable camera configuration and lighting condition.Clinical Relevance- This work demonstrates that SpO2 can be estimated accurately using an RGB camera without auto-tuning and under warm color temperature, enabling continuous SpO2 monitoring applications that require noncontact sensing.

Evaluation of Heat Transfer Coefficient for Plane and Perforated with Circular Perforations

This study focuses on the analysis of extended surfaces, which are commonly employed in various engineering applications to enhance convection heat transfer. The objective is to effectively increase the heat transfer rate by introducing perforations into the lateral surface of the fins. By determining the optimal perforation design and shape for these fins, this research aids in selecting the most suitable configuration. In preparation for the examination, aluminum and copper fins are specifically selected because of their elevated thermal conductivities and extensive use in heat transfer applications. The choice is based on their respective thermal conductivities: aluminum has a thermal conductivity of 210W/mK, while copper boasts a higher thermal conductivity of 410W/mK. KEY WORDS: Heat Transfer (HT), Heat Transfer Coefficient (HTC), Fins, Temperature and Perforations.

A Systematic Review of Energy Management Systems for Battery/Supercapacitor Electric Vehicle Applications

The purpose of this research is to present a thorough evaluation of energy management systems that consist of hybrid energy storage systems and their control algorithms, which may be used in electric vehicles. This paper outlines the characteristics of electric vehicles, research methods, an analysis of the hybrid energy storage system architecture, the converter topology, and energy management techniques. The strength and co-occurrence of keywords over the past ten years are shown in this study using a systematic research framework for performing a literature review and using keyword analysis techniques. This study reveals a pattern of recently and frequently used terms in works of literature. Consequently, their suitability, benefits, and drawbacks are assessed. In this study, the hybrid energy storage system and converter circuit architecture are evaluated and rated. A non-isolated DC-DC converter connected to an SC is a suitable configuration for the hybrid converter because it is simple to build, is reliable, and has minimal loss/weight/cost, which all improve vehicle performance. In terms of the application of control strategies, it is shown that deterministic and fuzzy-rule-based control techniques are successfully assessed using real-scale vehicle experiments and can be selected for manufacturing. On the other hand, real-time optimization-based energy management techniques have been effectively shown in lab-scale tests and may be used in a future real-scale vehicle.

A novel monocrystalline PV array configuration for enhancing the maximum power under partial shading conditions

Abstract Solar photovoltaic (PV) systems have gained importance as a promising renewable energy source in recent years. PV arrays are prone to variable irradiance levels under partial shading conditions due to non-uniform shading. As a result, there will be a decrease in the amount of power produced and hotspots will occur. To overcome these issues, it is essential to select an appropriate PV material and a suitable array configuration. To obtain the maximum output power from a PV array under partial shading conditions, this paper suggests a novel triple-series–parallel ladder topology with monocrystalline PV material. Considering short and wide, long and wide, short and narrow, long and narrow, middle and diagonal shading situations, a 6 × 6-sized array has been considered and compared with other existing configurations such as total cross-tied, bridge-link, honeycomb, series–parallel and series–parallel cross-tied. The proposed configuration has an optimal number of cross ties to produce maximum power. It has 4 cross ties fewer than a honeycomb, 3 cross ties fewer than a bridge link, 16 cross ties fewer than a total cross-tied and 7 cross ties fewer than series–parallel cross-tied configurations. The proposed configuration has an improvement in power of 0.1% to 20% compared with other configurations under the considered shading scenarios.

Development of a Sham Protocol to Investigate Transcutaneous Tibial Nerve Stimulation in Randomised, Sham-Controlled, Double-Blind Clinical Trials.

Transcutaneous tibial nerve stimulation (TTNS) is a promising treatment for neurogenic lower urinary tract symptoms. However, the evidence is limited due to a general lack of randomised controlled trials (RCTs) and, also, inconsistency in the sham and blinding conditions. In the context of much-needed RCTs, we aimed to develop a suitable sham-control protocol for a clinical setting to maintain blinding but avoid meaningful stimulation of the tibial nerve. Three potential electrode positions (lateral malleolus/5th metatarsal/plantar calcaneus) and two electrode sizes (diameter: 2.5 cm/3.2 cm) were tested to determine which combination provided the optimal sham configuration for a TTNS approach, based on a visible motor response. Sixteen healthy volunteers underwent sensory and motor assessments for each sham configuration. Eight out of them came back for an extra TTNS visit. Sensory thresholds were present for all sham configurations, with linear regression models revealing a significant effect regarding electrode position (highest at plantar calcaneus) but not size. In addition, motor thresholds varied with the position-lowest for the 5th metatarsal. Only using this position and 3.2 cm electrodes attained a 100% response rate. Compared to TTNS, sensory and motor thresholds were generally higher for the sham configurations; meanwhile, perceived pain was only higher at the lateral malleolus. In conclusion, using the 5th metatarsal position and 3.2 cm electrodes proved to be the most suitable sham configuration. Implemented as a four-electrode setup with standardized procedures, this appears to be a suitable RCT protocol for maintaining blinding and controlling for nonspecific TTNS effects in a clinical setting.

Chaotic coexistence of librational and rotational dynamics in the averaged planar three-body problem

Through an appropriate change of reference frame and rescalings of the variables and the parameters introduced, the Hamiltonian of the three-body problem is written as a perturbed Kepler problem. In this system, new Delaunay variables are defined and a suitable configuration of the phase space and the mass parameters is chosen. In such a system, wide regions of librational and rotational motions where orbits are regular and stable are found. Close to the separatrix of these regions, the existence of chaotic motions presenting a double rotational and librational dynamics is proved, numerically, through Poincaré sections and the use of FLI.

Random Vibration and Noise Analysis of Vehicle Seat Using Numerical Method

The development of vehicle seat used is a challenging task for the automotive industry. In this research the safeness of automotive seats by structural analysis and a random vibration analysis were studied. Hence, the main objective of this study is to determine the suitable vehicle seat configuration based on Noise, Vibration, and Harshness (NVH) performance. In order to achieve this objective, CFD software which is ANSYS was used to analyse frequency and deformation using different force distributed and different material on seat vehicle structure which the force applied from 250 N until 1000 N. The material used is aluminium alloy, magnesium alloy and structural steel to analyse the strength of seat structure. At the end of the study, the effect of different types of material vehicle seat structure was studied. The results confirm that by changing the seat structure material, the rattle noise and in general BSR noise can be improved or controlled accordingly. Consequently, for the seat system which has an identifiable structural dynamic, the BSR noise can be managed and controlled in early design phase by using the seat CAE model.

PERSPECTIVES ON ROBUST DESIGN – AN OVERVIEW OF CHALLENGES AND RESEARCH AREAS ACROSS INDUSTRY FIELDS

AbstractRobust Design offers a coherent and widely appreciated approach for the parametric exploration of the design space by means of simulation or experimentation, which is well-established in the quality-by design domain. From the perspective of design research, however, this only addresses a relatively narrow part of the design process and is not fully integrated with other design decisions such as concept exploration, the suitable configuration of system elements, or the design of interfaces. Particularly in light of the growing importance of developing technologically advanced and “smart” systems, it seems that a new methodical perspective on Robust Design is needed. Against this background, this paper consolidates knowledge and insights from different research fields and industry sectors. On this basis, new angles to the discussion on product robustness in different domains are explored in order to suggests directions for action and new research areas, both with respect to a methodical RD approach as well as the question of systematic research procedures.

On Searching All Solutions of Microwave Filter Synthesis Based on Interval Arithmetic

In this letter, the numerical interval Newton algorithm (NINA) is introduced into coupling matrix (CM) synthesis (reconfiguration) for the first time. In particular, all existing real solutions to microwave filter CM can be found with mathematical certainty, which provides designers with the flexibility to select the most suitable configuration. Also, CM limits can be directly imposed in the synthesis process to only compute solutions in the specified range. This synthesis process is independent of initial variable values, and the global convergence is theoretically guaranteed. Moreover, NINA is a deterministic method that can verify the existence or nonexistence, uniqueness or non-uniqueness of a given CM topology with the desired filtering performance. Furthermore, the processes dealing with both well-determined and over-determined systems are discussed to cover the synthesis of CMs with diverse configurations. One practical sixth-order dielectric filter with parasitic couplings is exemplified to validate the effectiveness of the presented synthesis approach.