Collective Operations Research Articles

Genetic algorithm hybridised by local search to optimise containers cleaning tours of municipal wastes

Collection of municipal wastes is an important logistic activity within any city. After the collection operations a systematic cleaning of the waste containers is important for the public health be...

Managing multiple satellite architectures by spatial grasp technology

The paper reviews some advanced space projects oriented on many satellites moving around the globe in low Earth orbits, and investigates how to organize their collective operation for solving important world problems, especially those related to global security and defense. It analyzes the application of the developed Spatial Grasp model and Technology (SGT), successfully tested on numerous applications, for simulation and management of multiple satellite architectures. Of particular interest is the latest Space Development Agency Next-Generation Space Architecture that uses a great number of cooperating satellites organized on different layers, which appears to be much more advanced than the known Strategic Defense Initiative project of the eighties. SGT is based on mobile recursive scenarios in a special high-level Spatial Grasp Language (SGL) which can self-navigate and self-match distributed environments while leaving throughout them powerful spatial infrastructures capable of solving any distributed problems. Providing basics of the latest SGT version, the paper describes examples of solutions in it of such problems as distributed tracing and elimination of complexly moving cruise missiles and hypersonic gliders, organization of effective custody layer which will be able to observe not only localized dangerous objects on the Earth but also any distributed terrestrial infrastructures as a whole. It also shows how to introduce a higher virtual layer for satellite constellation which may simplify formulation and solution of many problems in both terrestrial and celestial environments, including advanced command and control of complex national and international operations and campaigns from space.

Scalable Unsupervised ML: Latency Hiding in Distributed Sparse Tensor Decomposition

Latency overhead in distributed-memory parallel CPD-ALS scales with the number of processors, limiting the scalability of computing CPD of large irregularly sparse tensors. This overhead comes in the form of sparse reduce and expand operations performed on factor-matrix rows via point-to-point messages. We propose to hide the latency overhead through embedding all of the point-to-point messages incurred by the sparse reduce and expand into dense collective operations which already exist in the CPD-ALS. The conventional parallel CPD-ALS algorithm is not amenable for embedding so we propose a computation/communication rearrangement to enable the embedding. We embed the sparse expand and reduce into a hypercube-based ALL-REDUCE operation to limit the latency overhead to O(log K) for a K-processor system. The embedding comes with the cost of increased bandwidth overhead due to the multi-hop routing of factor-matrix rows during the embedded-ALL-REDUCE. We propose an embedding scheme that takes advantage of the expand/reduce properties to reduce this overhead. Furthermore, we propose a novel recursive bipartitioning framework that enables simultaneous hypergraph partitioning and subhypergraph-to-subhypercube mapping to achieve subtensor-to-processor assignment with the objective of reducing the bandwidth overhead during the embedded-ALL-REDUCE. We also propose a bin-packing-based algorithm for factor-matrix row to processor assignment aiming at reducing processors maximum send and receive volumes during the embedded-ALL-REDUCE. Experiments on up to 4096 processors show that the proposed framework scales significantly better than the state-of-the-art point-to-point method.

Feeding and growth coupling during different development larvae phases of the Mediterranean mussel Mytilus galloprovincialis L. from Amsa Bay

Spat supply for mussel farming in Morocco is essentially based on seed capture and collection from natural beds. However, natural irregularity recruitment in exploited areas and encountered difficulties during spat collection operations have led to develop and improve reproduction techniques under controlled conditions in hatcheries. The present study focused on the larvae phase aiming at assessing growth rate varies between different development stages. Trocophore larva stage had a size of 63.25 μm and reached the pedivilegere stage with a size of 272.56 μm in 18 culture days. Length growth was more significant than width growth for both H-batch and T-batch. For instance, larvae grew in terms of length quickly in H-batch than T-batch (11.10± 1.30 and 9.67 ± 1.17 μm day-1), and the same pattern was observed for T-batch larvae. Inversely, the total biomass consumed was higher during T-batch larvae rearing than H-batch ones. In contrast, the effect of feeding on growth was observed more significantly for H-batch larvae (t=7.55, df=23, p<0.001) than T-batch ones (t=4.13, df=23, p<0.001). However, the specific feeding effect was revealed higher for I. galbana for both batches rather than C. calcitrans and T. suecica. However, the larvae growth reduction is linked to the beginning of tissue synthesis.

Adaptive MPI collective operations based on evaluations in LogP model

Message passing model, represented by MPI (Message Passing Interface), is the principal parallel programming tool for distributed computer systems. The most of MPI-programs contain collective communications, which involve all the processes of a parallel program. Effectiveness of collective communications substantially effects on total time of program execution. In this work, we consider the problem of design of adaptive algorithms of collective communications on the example of barrier synchronization, which refers to one of the most common types of collective communications. We developed adaptive algorithm of barrier synchronization, which suboptimally selects barrier synchronization scheme in parallel MPI-programs among such algorithms as Central Counter, Combining Tree and Dissemination Barrier. The adaptive algorithm chooses the barrier algorithm with the minimal evaluation of execution time in the model LogP. Model LogP considers performance of computational resources and interconnect for point-to-point communications. Proposed algorithm has been implemented for MPI. We present the results of experiments on cluster systems, analyse dependency of algorithm selection on LogP parameters values. In particular, for the number of processes less than 20 adaptive algorithm selects Combining Tree, while for a larger number of processes adaptive algorithm selects Dissemination Barrier. Developed algorithm minimizes average time of barrier synchronization by 4%, in comparison with the most common determined barrier algorithms.

Forecast Future Production and Estimation of Future Costs of Municipal Solid Waste Collection and Transportation System in Yazd Using WAGS Software

Introduction: About 50 to 70 percent of the waste management total cost is spent on collection operations, so any little progress in reducing collection costs could significantly reduce total costs. This study aimed to analyze the collection and transportation of municipal solid waste cost in Yazd in the next 15 years. Materials and Methods: The study location (five areas) was different urban areas of Yazd city. To analyze the collection and transportation of normal waste cost in Yazd, WAGS software was used. To obtain demographic information, the Statistical Center of Iran data, information about the location of the area, equipment, costs, and taxes related to waste were obtained in cooperation with Yazd Municipality, Recycling Organization, Labor, and Social Affairs Office and field surveys. Apart from WAGS, the ARIMA time series method (1, 1, 0) was also used with SPSS 24. Results: The highest costs of waste collection belonged to the human resources sector, and personnel costs were 75.24%, machinery supply capital was 13.85%, repair costs were 6.15%, fuel costs were 4.59%, and the costs of the other parts of the total cost of the waste collection were 0.14%. Conclusion: The total collection and transfer of waste costs were estimated at 10414000 USD to collect and transfer municipal solid waste in Yazd in the next 15 years. Waste generation projection by time series method with the ARIMA model (1, 1, 0) showed more accurate results than waste generation projection with WAGS.

Robust Design of a Closed-Loop Supply Chain Considering Multiple Recovery Options and Carbon Policies Under Uncertainty

Increasing global warming, climate change and stringent governmental legislations are driving industry practitioners and decision makers to implement various strategies to reduce carbon emissions. One of the effective approaches to mitigate carbon emissions is the implementation of closed-loop supply chain (CLSC). The key motivation for considering multiple recovery options in the CLSC is to capture the remaining economic value and to reduce carbon emissions in the collection and recovery operations. Customer's willingness to return used product depends on the acquisition price and nearness to the collection center. This research proposes a deterministic mixed-integer linear programming (MILP) model for a multi-period and multi-product CLSC network under carbon pricing and carbon trading policies consideration. The model includes different acquisition price for returned products and multiple recovery options. Further, the study takes into consideration uncertainty in procurement cost, demand, and quantity of returned products. A robust optimization approach is adopted to address uncertainty in network parameters. Numerical results show that the proposed model captures trade-offs between total cost and carbon emission. Overall, the study reveals that the carbon trading policy incurs relatively lower total cost compared to the carbon pricing policy. Repair and recycling activities in the reverse supply chain contribute significantly to the total cost and carbon emission. This study provide evidence that it is possible to achieve an optimal CLSC network with reduced carbon emission at a moderate total supply chain cost. The proposed model could be used to guide firms to choose an appropriate budget of uncertainty toward achieving a robust supply chain network.

A sensory cell diversifies its output by varying Ca2+ influx‐release coupling among active zones

The cochlea encodes sound pressures varying over six orders of magnitude by collective operation of functionally diverse spiral ganglion neurons (SGNs). The mechanisms enabling this functional diversity remain elusive. Here, we asked whether the sound intensity information, contained in the receptor potential of the presynaptic inner hair cell (IHC), is fractionated via heterogeneous synapses. We studied the transfer function of individual IHC synapses by combining patch‐clamp recordings with dual‐color Rhod‐FF and iGluSnFR imaging of presynaptic Ca2+ signals and glutamate release. Synapses differed in the voltage dependence of release: Those residing at the IHC' pillar side activated at more hyperpolarized potentials and typically showed tight control of release by few Ca2+ channels. We conclude that heterogeneity of voltage dependence and release site coupling of Ca2+ channels among the synapses varies synaptic transfer within individual IHCs and, thereby, likely contributes to the functional diversity of SGNs. The mechanism reported here might serve sensory cells and neurons more generally to diversify signaling even in close‐by synapses.

Noisy Quantum Metrology Enhanced by Continuous Nondemolition Measurement.

We show that continuous quantum nondemolition (QND) measurement of an atomic ensemble is able to improve the precision of frequency estimation even in the presence of independent dephasing acting on each atom. We numerically simulate the dynamics of an ensemble with up to N=150 atoms initially prepared in a (classical) spin coherent state, and we show that, thanks to the spin squeezing dynamically generated by the measurement, the information obtainable from the continuous photocurrent scales superclassically with respect to the number of atoms N. We provide evidence that such superclassical scaling holds for different values of dephasing and monitoring efficiency. We moreover calculate the extra information obtainable via a final strong measurement on the conditional states generated during the dynamics and show that the corresponding ultimate limit is nearly achieved via a projective measurement of the spin-squeezed collective spin operator. We also briefly discuss the difference between our protocol and standard estimation schemes, where the state preparation time is neglected.

Patch-based classification of gallbladder wall vascularity from laparoscopic images using deep learning.

In this study, we propose a deep learning approach for assessment of gallbladder (GB) wall vascularity from images of laparoscopic cholecystectomy (LC). Difficulty in the visualization of GB wall vessels may be the result of fatty infiltration or increased thickening of the GB wall, potentially as a result of cholecystitis or other diseases. The dataset included 800 patches and 181 region outlines of the GB wall extracted from 53 operations of the Cholec80 video collection. The GB regions and patches were annotated by two expert surgeons using two labeling schemes: 3 classes (low, medium and high vascularity) and 2 classes (low vs. high). Two convolutional neural network (CNN) architectures were investigated. Preprocessing (vessel enhancement) and post-processing (late fusion of CNN output) techniques were applied. The best model yielded accuracy 94.48% and 83.77% for patch classification into 2 and 3 classes, respectively. For the GB wall regions, the best model yielded accuracy 91.16% (2 classes) and 80.66% (3 classes). The inter-observer agreement was 91.71% (2 classes) and 78.45% (3 classes). Late fusion analysis allowed the computation of spatial probability maps, which provided a visual representation of the probability for each vascularity class across the GB wall region. This study is the first significant step forward to assess the vascularity of the GB wall from intraoperative images based on computer vision and deep learning techniques. The classification performance of the CNNs was comparable to the agreement of two expert surgeons. The approach may be used for various applications such as for classification of LC operations and context-aware assistance in surgical education and practice.

INVESTIGATION OF THE PROCESS OF CHIPPING OF THE WALNUT SHELL AS A RESULT OF THE FORCE ACTION OF HEMISPHERICAL SURFACES

Knowledge of the technical properties of walnuts is essential to facilitate and improve the design of processing equipment and procedures and equipment for collection, packaging and storage. In the process of obtaining the fruit of a walnut and its derivatives, the kernels are subjected to a number of single operations. At each stage, based on the mechanical properties of walnuts, various types of equipment operate, including vibration equipment for cleaning, sorting, separating and peeling. Thus, the detailed results presented in this study provide useful data that can be used by engineers to design appropriate walnut processing machines, thereby improving process and quality control. To reduce mechanical damage and improve the Knowledge of the technical properties of walnuts is necessary to facilitate and improve the design of process equipment, as well as to mechanize the operations of collection, packaging and storage. In the process of obtaining walnuts, namely the kernels are subjected to a number of single operations. At each stage, based on the mechanical properties of walnuts, different types of equipment work, including vibrating for cleaning, sorting, separation and peeling. Thus, the detailed results presented in this study provide useful data that can be used by engineers in the design of appropriate machines for processing walnuts, thereby improving the process and quality control. The article provides a detailed review of the process of splitting the walnut kernel. Examples of many ways to split the shell, all their disadvantages and advantages are given. The mechanical method of peeling is theoretically investigated and substantiated. To reduce mechanical damage and improve the quality of extraction of walnut kernels during peeling, the object of study was selected 1 variety of walnut. The results of compression tests showed that the relationship between the breaking force and the deformation of the walnut was nonlinear, and the process of peeling (chipping) of the shell mainly consisted of three stages. The best method of splitting a walnut was «spherical compression» (between two spherical inserts), and the maximum value of the destructive force was also determined. The results showed that «spherical compression» was an appropriate way to destroy the walnut, which led to obvious trends in the spread of cracks in the shell and, moreover, to better integrity of the removed core. The article considers a number of small and large equipment designed for splitting nuts, both at home and in industrial conditions, of different design and performance.

Potential of medium chain fatty acids production from municipal solid waste leachate: Effect of age and external electron donors

A large quantity of leachate is generated during municipal solid waste collection operation and in landfills due to the large amount of organic waste and high humidity. The content of medium chain fatty acids (MCFAs) in the leachate is a low cost feedstock for bio-based chemical and fuel production processes. The aim of this study is to investigate the MCFA production potential of three leachate ages through chain elongation process under uncontrolled pH batch test. Moreover, the effect of using different external electron donors (ethanol, methanol and a mixture of both) is studied. The experiment consists of characterizing the samples then adding external electron donors with a specific ratio to leachate samples under mesophilic temperature. For this investigation, also a statistical analysis is done, which shows the production of MCFAs is highly influenced by leachate age. The results indicate that the production of even-numbered acids increase from 600 to 1,000 mg/L by the end of the ethanol chain elongation experiment for young leachate. However, a higher MCFA production of more than 1,000 mg/L is achieved by using the mixture of methanol and ethanol as electron donor. Furthermore, all methanol chain elongation experiments lead to an odd-numbered production of MCFAs, such as pentanoic and heptanoic acids. These results confirm the potential improvement of MCFA production from leachate through choosing the optimal leachate age and electron donor. Overall, producing MCFAs from leachate is a good example of circular bio-economy because waste is used to produce biochemicals, which closes the material cycle.

Disruptive Technologies for Improving Water Security in Large River Basins

Large river basins present significant challenges for water resource planning and management. They typically traverse a wide range of hydroclimatic regimes, are characterized by complex and variable hydrology, and span multiple jurisdictions with diverse water demands and values. They are often data-poor and in many developing economies are characterized by weak water governance. Rapid global change is seeing significant changes to the pressures on the water resources of large basins, exacerbating the challenge of sustainable water management. Diverse technologies have long supported water resource planning and development, from data collection, analytics, simulation, to decision-making, and real-time operations. In the last two decades however, a rapid increase in the range, capability, and accessibility of new technologies, coupled with large reductions in cost, mean there are increasing opportunities for emerging technologies to significantly “disrupt” traditional approaches to water resources management. In this paper, we consider the application of ‘disruptive technologies’ in water resources management in large river basins, through a lens of improving water security. We discuss the role of different actors and institutions for water management considering a range of emerging disruptive technologies. We consider the risks and benefits associated with the use of these technologies and discuss the barriers to their widespread adoption. We obverse a positive trend away from the reliance solely on centralized government institutions and traditional modeling for the collection and analysis of data, towards a more open and dynamic ‘data and knowledge ecosystem’ that draws upon data services at different levels (global to local) to support water planning and operations. We expect that technological advances and cost reductions will accelerate, fueling increased incremental adoption of new technologies in water resources planning and management. Large-basin analytics could become virtually free for users with global, regional, and national development agencies absorbing the costs of development and any subscription services for end users (e.g., irrigators) to help improve water management at user level and improve economic productivity. Collectively, these changes can help to ‘democratize’ water management through improved access to data and information. However, disruptive technologies can also be deployed in top-down or centralized processes, and so their use is sometimes contested or misunderstood. Increased attention therefore needs to be given to ensuring equity in technology access, and to strengthening the governance context for technology deployment. Widespread adoption of disruptive technologies will require adjustments to how water professionals are trained, increased adaptiveness in water resources planning and operations, and careful consideration of privacy and cybersecurity issues.

A Computer Vision System Applied to The Recognition of Different Capacitors

In this paper, we establish an automation system based on computer vision for the identification of capacitors with different capacitances. The images of capacitors on the industrial assembly line are obtained in real time by using a CCD industrial camera. Then, the obtained images based on RGB model are transformed into HSI color format to avoid the effect of environmental brightness. According to the calculated characteristic hue and saturation values, the established automation system could accurately and effectively identify the capacitances of the capacitors by colors. The identification results would provide accurate information for subsequent robot arm recognition, location, collection, and other operations. By applying to the industrial assembly line, this computer vision system could greatly improve the automation level and product quality of industrial production.

Assessment of Municipal Solid Waste Management Practices in Bahawalpur City, Pakistan

Solid waste management is a global issue persisting in most of the developing countries like Pakistan. Current study briefly appraises the management and practices of municipal solid waste (MSW) in Bahawalpur city. Data were collected from different sources by using an in-depth interview and questionnaire tool. The findings reveal that domestic organic waste accounts for about 35.32% followed by debris, dirt and construction material waste (30.89%). About 273.69 tons solid waste is generated on daily basis whereas only 218.95 tons per day is collected and disposed. The collection rate of MSW varies from 61% to 80% in the city. The service coverage area was about 70%. The total sanitary staff was also very limited (735) as compared to the increasing population and served only 75% population of the Bahawalpur. The equipment and machinery used for MSW collection and disposal operation were also limited and out of fashion which were needed to be replaced. There is no proper landfill for disposal of solid waste which is openly thrown at five dumping sites and burned. This situation further creates many environmental and health issues. Recycling is almost absent in the city and behavior of the inhabitants also adds to an ineffective solid waste management in the city. It is necessary to create awareness among the people about bad effects of improper dumping of solid waste and the need to tackle this problem.

MPI Parallel Implementation for Pseudo-Spectral Simulations for Turbulent Channel Flow

ABSTRACT The present study performs direct numerical simulations of turbulent channel flows using a spectral method in a large computational domain. Because of applying Fourier discretisation in the spectral method, parallelisation of the method may incur heavy communication overhead, thereby resulting in poor scalability. We design and improve the spectral code by exploring parallel techniques, including domain decomposition and data transposition algorithms. We focus particularly on the 2D domain decomposition and data transpose algorithm with the non-blocking collective operations improves parallel performance, thereby enabling latency mitigation by overlapping the computation and communication. Finally, we evaluate the code on the Nurion supercomputer at KISTI supercomputing centre. The transpose algorithm based on the non-blocking collective operations shows the best performance, which enables 3.55 times faster computing on 256 nodes using 16,384 MPI ranks for the L550 case of grid points than the non-optimised 2D decomposition case.

Online/at‐line measurement, analysis and control of product titer and critical product quality attributes (CQAs) during process development

Process analytical technology (PAT) has been defined by the Food and Drug Administration as a system for designing, analyzing, and controlling manufacturing through timely measurements to ensure final product quality. Based on quality-by-design (QbD) principles, real-time or near-real-time data monitoring is essential for timely control of critical quality attributes (CQAs) to keep the process in a state of control. To facilitate next-generation continuous bioprocessing, deployment of PAT tools for real-time monitoring is integral for process understanding and control. Real-time monitoring and control of CQAs are essential to keep the process within the design space and align with the guiding principles of QbD. The contents of this manuscript are pertinent to the online/at-line monitoring of upstream titer and downstream product quality with timely process control. We demonstrated that an ultra-performance liquid chromatography (UPLC) system interfaced with a UPLC-process sample manager (UPLC-PSM) can be utilized to measure titer and CQAs directly from bioreactors and downstream unit operations, respectively. We established online titer measurements from fed-batch and perfusion-based alternating tangential flow bioreactors as well as product quality assessments of downstream operations for real-time peak collection. This integrated, fully automated system for online data monitoring with feedback control is designed to achieve desired product quality.

Data-driven cyber-physical system framework for connected resistance spot welding weldability certification

• Realized data-driven cyber-physical system for RSW certification with integrated analytics and optimization capabilities. • Integrating data from analytics lifecycle phases - data collection operation to predictive analytics to design visualization. • The framework is based on conceptualization of layers of cyber-physical system and incorporates design and machine changes. • Closed-loop machine parameter optimization implemented considering the target product design. • Case study based on a real industrial weldability certification to illustrate the application of the envisioned framework. A cyber-physical system is one of the integral parts of the development endeavor of the smart manufacturing domain and the Industry 4.0 wave. With the advances in data analytics, smart manufacturing is gradually transforming the global manufacturing landscape. In the Resistance Spot Welding (RSW) domain, the focus has been more on the physical systems, compared to the virtual systems. The cyber-physical system facilitates the integrated analysis of the design and manufacturing processes by converging the physical and virtual stages to improve product quality in real-time. However, a cyber-physical system integrated RSW weldability certification is still an unmet need. This research is to realize a real-time data-driven cyber-physical system framework with integrated analytics and parameter optimization capabilities for connected RSW weldability certification. The framework is based on the conceptualization of the layers of the cyber-physical system and can incorporate the design and machine changes. It integrates data from the analytics lifecycle phases, starting from the data collection operation, to the predictive analytics operation, and to the visualization of the design. This integrated framework aims to support decision-makers to understand product design and its manufacturing implications. In addition to data analytics, the proposed framework implements a closed-loop machine parameter optimization considering the target product design. The framework visualizes the target product assembly with predicted response parameters along with displaying the process parameters and material design parameters simultaneously. This layer should help the designers in their decision-making process and the engineers to gain knowledge about the manufacturing processes. A case study on the basis of a real industrial case and data is presented in detail to illustrate the application of the envisioned cyber-physical systems framework.

Collectives in hybrid MPI+MPI code: Design, practice and performance

The use of hybrid scheme combining the message passing programming models for inter-node parallelism and the shared memory programming models for node-level parallelism is widely spread. Existing extensive practices on hybrid Message Passing Interface (MPI) plus Open Multi-Processing (OpenMP) programming account for its popularity. Nevertheless, strong programming efforts are required to gain performance benefits from the MPI+OpenMP code. An emerging hybrid method that combines MPI and the MPI shared memory model (MPI+MPI) is promising. However, writing an efficient hybrid MPI+MPI program – especially when the collective communication operations are involved – is not to be taken for granted.In this paper, we propose a new design method to implement hybrid MPI+MPI context-based collective communication operations. Our method avoids on-node memory replications (on-node communication overheads) that are required by semantics in pure MPI. We also offer wrapper primitives hiding all the design details from users, which comes with practices on how to structure hybrid MPI+MPI code with these primitives. Further, the on-node synchronization scheme required by our method/collectives gets optimized. The micro-benchmarks show that our collectives are comparable or superior to those in pure MPI context. We have further validated the effectiveness of the hybrid MPI+MPI model (which uses our wrapper primitives) in three computational kernels, by comparison to the pure MPI and hybrid MPI+OpenMP models.

Performance simulation and policy optimization of waste polyethylene terephthalate bottle recycling system in China

Owing to the convenience and price advantages, polyethylene terephthalate (PET) bottles have been widely used in daily life. This leads to a substantial number of waste PET bottles. Because of the lack of corresponding management policies in developing countries, PET bottles have entered the informal collection and recycling sectors in large quantities, causing serious environmental pollution. In China, how to regulate the formal collection and achieve optimal performance of a PET bottle recycling system with policy implementation methods are still being explored. This study constructs a dynamic recycling system of waste PET bottles for the production-consumption, consumption-collection, and collection-recycling subsystems that regulate the formal recycling of PET bottles through policies. The deposit-refund system, mandatory policy and tax refund system were used as the standard recycling policy in a simulation, and comprehensive performance changes were compared before and after the policy simulation. The results indicate that the comprehensive performance (basic scenario) of the PET bottle recycling system is an average of 5.42 billion CNY. With the policy mix scenario, it reached to 6.51 billion CNY, and the formal collection rate increased to 55.8%. Compared with the basic scenario, the comprehensive performance of the policy mix scheme increased by 20%, which is beneficial to the operations of the formal collection and recycling sectors and increases the production vitality of the formal PET recycling industry.