Selecting between Sequential Zoning and Simultaneous Zoning for Picker-to-parts Order Picking System Based on Order Cluster and Genetic Algorithm

The existing research of sequential zoning system and simultaneous zoning system mainly focuses on some optimization problems such as workload balance,product assignment and simulation for each system separately.But there is little research on comparative study between sequential zoning and simultaneous zoning.In order to help the designers to choose the suitable zoning policy for picker-to-parts system reasonably and quickly,a systemic selection method is presented.Essentially,both zoning and batching are order clustering,so the customer order sheet can be divided into many unit grids.After the time formulation in one-dimensional unit was defined,the time models for each zoning policy in two-dimensional space were established using filling curves and sequence models to link the one-dimensional unit grids.In consideration of ＂U＂ shaped dual tour into consideration,the subtraction value of order picking time between sequential zoning and simultaneous zoning was defined as the objective function to select the suitable zoning policy based on time models.As it is convergent enough,genetic algorithm is adopted to find the optimal value of order picking time.In the experimental study,5 different kinds of order/stock keeping unit（SKU） matrices with different densities d and quantities q following uniform distribution were created in order to test the suitability of sequential zoning and simultaneous zoning to different kinds of orders.After parameters setting,experimental orders inputting and iterative computations,the optimal order picking time for each zoning policy was gotten.By observing whether the delta time between them is greater than 0 or not,the suitability of zoning policies for picker-to-parts system were obtained.The significant effect of batch size b,zone number z and density d on suitability was also found by experimental study.The proposed research provides a new method for selection between sequential zoning and simultaneous zoning for picker-to-parts system,and improves the rationality and efficiency of selection process in practical design.

Peer selecting model based on FCM for wireless distributed P2P files sharing systems

IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.

Exploring the interplay of T cell receptor-V gene copy numbers and major histocompatibility complex selection pressure in avian species:Insights into immune system evolution and reproductive investment

Birds,a fascinating and diverse group occupying various habitats worldwide,exhibit a wide range of life-history traits,reproductive methods,and migratory behaviors,all of which influence their immune systems.The association between major histocompatibility complex(MHC)genes and certain ecological factors in response to pathogen selection has been extensively studied;however,the role of the co-working molecule T cell receptor(TCR)remains poorly understood.This study aimed to analyze the copy numbers of TCR-V genes,the selection pressure(ωvalue)on MHC genes using available genomic data,and their potential ecological correlates across 93 species from 13 orders.The study was conducted using the publicly available genome data of birds.Our findings suggested that phylogeny influences the variability in TCR-V gene copy numbers and MHC selection pressure.The phylogenetic generalized least squares regression model revealed that TCR-Vαδcopy number and MHC-I selection pressure were positively associated with body mass.Clutch size was correlated with MHC selection pressure,and Migration was correlated with TCR-Vβcopy number.Further analyses revealed that the TCR-Vβcopy number was positively correlated with MHC-IIB selection pressure,while the TCR-Vγcopy number was negatively correlated with MHC-I peptide-binding region selection pressure.Our findings suggest that TCR-V diversity is significant in adaptive evolution and is related to species’life-history strategies and immunological defenses and provide valuable insights into the mechanisms underlying TCR-V gene duplication and MHC selection in avian species.

Strategies of selective electroreduction of aqueous nitrate to N_(2) in chloride-free system:A critical review

Electroreduction of nitrate has been gaining wide attention in recent years owing to it's beneficial for converting nitrate into benign N_(2) from the perspective of electrocatalytic denitrification or into value-added ammonia from the perspective of electrocatalytic NH_(3) synthesis.By reason of the undesired formation of ammonia is dominant during electroreduction of nitrate-containing wastewater,chloride has been widely used to improve N_(2) selectivity.Nevertheless,selective electroreduction of nitrate to N2 gas in chloride-containing system poses several drawbacks.In this review,we focus on the key strategies for efficiently enhancing N_(2) selectivity of electroreduction of nitrate in chloride-free system,including optimal selection of elements,combining an active metal catalyst with another metal,manipulating the crystalline morphology and facet orientation,constructing core–shell structure catalysts,etc.Before summarizing the strategies,four possible reaction pathways of electro-reduction of nitrate to N_(2) are discussed.Overall,this review attempts to provide practical strategies for enhancing N2 selectivity without the aid of electrochlorination and highlight directions for future research for designing appropriate electrocatalyst for final electrocatalytic denitrifi-cation.

Optimum Selecting Method of CNC System′s Accessories

The object of this dissertation is to select the best-quality product in CNC system′s accessories.It applies the relative theories of Fuzzy Mathematics to solve the issue,and it sets up the effective optimum selecting theory model.Moreover,it presents a kind of applicable way,which selects the best-quality product,and proves its availability by the living case.

Flotation separation of brucite and calcite in dodecylamine system enhanced by regulator potassium dihydrogen phosphate

To achieve efficient flotation separation of brucite and calcite,flotation separation experiments were conducted on two minerals using dodecylamine(DDA)as the collector and potassium dihydrogen phosphate(PDP)as the regulator.The action mechanism of DDA and PDP was explored through contact angle measurement,zeta potential detection,solution chemistry calculation,FTIR analysis,and XPS detection.The flotation results showed that when DDA dosage was 35 mg/L and PDP dosage was 40 mg/L,the maximum floating difference between brucite and calcite was 79.81%,and the selectivity separation index was 6.46.The detection analysis showed that the main dissolved component HPO_(4)^(2−)of PDP is selectively strongly adsorbed on the Ca site on the surface of calcite,promoting the adsorption of the main dissolved component RNH_(3)^(+)of DDA on calcite surface,while brucite is basically not affected by PDP.Therefore,PDP is an effective regulator for the reverse flotation separation of brucite and calcite in DDA system.

A lightweight symmetric image encryption cryptosystem in wavelet domain based on an improved sine map

In the era of big data,the number of images transmitted over the public channel increases exponentially.As a result,it is crucial to devise the efficient and highly secure encryption method to safeguard the sensitive image.In this paper,an improved sine map(ISM)possessing a larger chaotic region,more complex chaotic behavior and greater unpredictability is proposed and extensively tested.Drawing upon the strengths of ISM,we introduce a lightweight symmetric image encryption cryptosystem in wavelet domain(WDLIC).The WDLIC employs selective encryption to strike a satisfactory balance between security and speed.Initially,only the low-frequency-low-frequency component is chosen to encrypt utilizing classic permutation and diffusion.Then leveraging the statistical properties in wavelet domain,Gaussianization operation which opens the minds of encrypting image information in wavelet domain is first proposed and employed to all sub-bands.Simulations and theoretical analysis demonstrate the high speed and the remarkable effectiveness of WDLIC.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

Sufficient variable selection of high dimensional nonparametric nonlinear systems based on Fourier spectrum of density-weighted derivative

The variable selection of high dimensional nonparametric nonlinear systems aims to select the contributing variables or to eliminate the redundant variables.For a high dimensional nonparametric nonlinear system,however,identifying whether a variable contributes or not is not easy.Therefore,based on the Fourier spectrum of densityweighted derivative,one novel variable selection approach is developed,which does not suffer from the dimensionality curse and improves the identification accuracy.Furthermore,a necessary and sufficient condition for testing a variable whether it contributes or not is provided.The proposed approach does not require strong assumptions on the distribution,such as elliptical distribution.The simulation study verifies the effectiveness of the novel variable selection algorithm.

Optimization-based mode selection scheme for OAM millimeter wave system in the off-axis misalignment case

Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system capacity.However,to fulfill this advantage,the antennas at the transmitter and receiver must be parallel and coaxial;otherwise,the accuracy of mode detection at the receiver can be seriously influenced.In this paper,we design an OAM millimeter-wave communication system for overcoming the above limitation.Specifically,the first contribution is that the power distribution between different OAM modes and the capacity of the system with different mode sets are analytically derived for performance analysis.The second contribution lies in that a novel mode selection scheme is proposed to reduce the total interference between different modes.Numerical results show that system performance is less affected by the offset when the mode set with smaller modes or larger intervals is selected.

Possible effects of selecting different station distributions in the optimal sequence estimation method

Since the inception of the optimal sequence estimation (OSE) method,various research teams have substantiated its efficacy as the optimal stacking technique for handling array data,leading to its successful application in numerous geoscience studies.Nevertheless,concerns persist regarding the potential impact of aliasing resulting from the choice of distinct station distributions on the outcomes derived from OSE.In this investigation,I employ theoretical deduction and experimental analysis to elucidate the reasons behind the immunity of the Y_(l'm')-related common signal obtained through OSE to variations in station distribution selection.The primary objective of OSE is also underscored,i.e.,to restore/strip a Y_(l'm')-related common periodic signal from various stations.Furthermore,I provide additional clarification that the‘Y_(l'm')-related common signal’and the‘Y_(l'm')-related equivalent excitation sequence’are distinct concepts.These analyses will facilitate the utilization of the OSE technique by other researchers in investigating intriguing geophysical phenomena and attaining sound explanations.

Mechanism of selective laser trabeculoplasty:a systemic review

Although selective laser trabeculoplasty(SLT)is a recognized method for the treatment of glaucoma,the exact changes in the target tissue and mechanism for its intraocular pressure lowing effect are still unclear.The purpose of this review is to summarize the potential mechanisms of SLT on trabecular meshwork both in vivo and in vitro,so as to reveal the potential mechanism of SLT.SLT may induce immune or inflammatory response in trabecular meshwork(TM)induced by possible oxidative damage etc,and remodel extracellular matrix.It may also induce monocytes to aggregate in TM tissue,increase Schlemm’s canal(SC)cell conductivity,disintegrate cell junction and promote permeability through autocrine and paracrine forms.This provides a theoretical basis for SLT treatment in glaucoma.

Practical Privacy-Preserving ROI Encryption System for Surveillance Videos Supporting Selective Decryption

With the advancement of video recording devices and network infrastructure,we use surveillance cameras to protect our valuable assets.This paper proposes a novel system for encrypting personal information within recorded surveillance videos to enhance efficiency and security.The proposed method leverages Dlib’s CNN-based facial recognition technology to identify Regions of Interest(ROIs)within the video,linking these ROIs to generate unique IDs.These IDs are then combined with a master key to create entity-specific keys,which are used to encrypt the ROIs within the video.This system supports selective decryption,effectively protecting personal information using surveillance footage.Additionally,the system overcomes the limitations of existing ROI recognition technologies by predicting unrecognized frames through post-processing.This research validates the proposed technology through experimental evaluations of execution time and post-processing techniques,ensuring comprehensive personal information protection.Guidelines for setting the thresholds used in this process are also provided.Implementing the proposed method could serve as an effective solution to security vulnerabilities that traditional approaches fail to address.

Multi-Binary Classifiers Using Optimal Feature Selection for Memory-Saving Intrusion Detection Systems

With the rise of remote work and the digital industry,advanced cyberattacks have become more diverse and complex in terms of attack types and characteristics,rendering them difficult to detect with conventional intrusion detection methods.Signature-based intrusion detection methods can be used to detect attacks;however,they cannot detect new malware.Endpoint detection and response(EDR)tools are attracting attention as a means of detecting attacks on endpoints in real-time to overcome the limitations of signature-based intrusion detection techniques.However,EDR tools are restricted by the continuous generation of unnecessary logs,resulting in poor detection performance and memory efficiency.Machine learning-based intrusion detection techniques for responding to advanced cyberattacks are memory intensive,using numerous features;they lack optimal feature selection for each attack type.To overcome these limitations,this study proposes a memory-efficient intrusion detection approach incorporating multi-binary classifiers using optimal feature selection.The proposed model detects multiple types of malicious attacks using parallel binary classifiers with optimal features for each attack type.The experimental results showed a 2.95%accuracy improvement and an 88.05%memory reduction using only six features compared to a model with 18 features.Furthermore,compared to a conventional multi-classification model with simple feature selection based on permutation importance,the accuracy improved by 11.67%and the memory usage decreased by 44.87%.The proposed scheme demonstrates that effective intrusion detection is achievable with minimal features,making it suitable for memory-limited mobile and Internet of Things devices.

Continuous Lithium-Ion Extraction From Seawater and Mine Water With a Fuel Cell System and Ceramic Membranes

The demand for electronic devices that utilize lithium is steadily increasing in this rapidly advancing technological world.Obtaining high-purity lithium in an environmentally friendly way is challenging by using commercialized methods.Herein,we propose the first fuel cell system for continuous lithium-ion extraction using a lithium superionic conductor membrane and advanced electrode.The fuel cell system for extracting lithium-ion has demonstrated a twofold increase in the selectivity of Li^(+)/Na^(+)while producing electricity.Our data show that the fuel cell with a titania-coated electrode achieves 95%lithium-ion purity while generating 10.23 Wh of energy per gram of lithium.Our investigation revealed that using atomic layer deposition improved the electrode's uniformity,stability,and electrocatalytic activity.After 2000 cycles determined by cyclic voltammetry,the electrode preserved its stability.

CL2ES-KDBC:A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless networks.Specifically,IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks.In this framework,a Covariance Linear Learning Embedding Selection(CL2ES)methodology is used at first to extract the features highly associated with the IoT intrusions.Then,the Kernel Distributed Bayes Classifier(KDBC)is created to forecast attacks based on the probability distribution value precisely.In addition,a unique Mongolian Gazellas Optimization(MGO)algorithm is used to optimize the weight value for the learning of the classifier.The effectiveness of the proposed CL2ES-KDBC framework has been assessed using several IoT cyber-attack datasets,The obtained results are then compared with current classification methods regarding accuracy(97%),precision(96.5%),and other factors.Computational analysis of the CL2ES-KDBC system on IoT intrusion datasets is performed,which provides valuable insight into its performance,efficiency,and suitability for securing IoT networks.

An Integrated Bipolar Picture Fuzzy Decision Driven System to Scrutinize Food Waste Treatment Technology through Assorted Factor Analysis

Food Waste(FW)is a pressing environmental concern that affects every country globally.About one-third of the food that is produced ends up as waste,contributing to the carbon footprint.Hence,the FW must be properly treated to reduce environmental pollution.This study evaluates a few available Food Waste Treatment(FWT)technologies,such as anaerobic digestion,composting,landfill,and incineration,which are widely used.A Bipolar Picture Fuzzy Set(BPFS)is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model.A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution(CRITIC-SPOTIS)approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry’s technical,environmental,and entrepreneurial aspects.The CRITIC method is used for the objective analysis of the importance of each criterion in FWT selection.The SPOTIS method is adopted to rank the alternative hassle-free,following the criteria.The proposed model offers a rank reversal-free model,i.e.,the rank of the alternatives remains unaffected even after the addition or removal of an alternative.In addition,comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.

A Hybrid Small-Cell and Clustered Cell-Free Massive MIMO System under Mobility Scenarios

Recently,cell-free(CF)massive multipleinput multiple-output(MIMO)becomes a promising architecture for the next generation wireless communication system,where a large number of distributed access points(APs)are deployed to simultaneously serve multiple user equipments(UEs)for improved performance.Meanwhile,a clustered CF system is considered to tackle the backhaul overhead issue in the huge connection network.In this paper,taking into account the more realistic mobility scenarios,we propose a hybrid small-cell(SC)and clustered CF massive MIMO system through classifications of the UEs and APs,and constructing the corresponding pairs to run in SC or CF mode.A joint initial AP selection of this paradigm for all the UEs is firstly proposed,which is based on the statistics of estimated channel.Then,closed-form expressions of the downlink achievable rates for both the static and moving UEs are provided under Ricean fading channel and Doppler shift effect.We also develop a semi-heuristic search algorithm to deal with the AP selection for the moving UEs by maximizing the weight average achievable rate.Numerical results demonstrate the performance gains and effective rates balancing of the proposed system.

Effects of atrial septal defects on the cardiac conduction system

The case report presented in this edition by Mu et al.The report presents a case of atrial septal defect(ASD)associated with electrocardiographic changes,noting that the crochetage sign resolved after Selective His Bundle Pacing(S-HBP)without requiring surgical closure.The mechanisms behind the appearance and resolution of the crochetage sign remain unclear.The authors observed the dis-appearance of the crochetage sign post-S-HBP,suggesting a possible correlation between these specific R waves and the cardiac conduction system.This editorial aims to explore various types of ASD and their relationship with the cardiac con-duction system,highlighting the diagnostic significance of the crochetage sign in ASD.

A preliminary site selection system for underground hydrogen storage in salt caverns and its application in Pingdingshan,China

Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns are recognized as ideal sites for pure hydrogen storage.Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues.In this article,the software CiteSpace is used to analyze and filter hot topics in published research.Based on a detailed classification and analysis,a“four‐factor”model for the site selection of salt cavern hydrogen storage is proposed,encompassing the dynamic demands of hydrogen energy,geological,hydrological,and ground factors of salt mines.Subsequently,20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted,which provided a preliminary site selection system for salt cavern hydrogen storage.Ultimately,the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City,Henan Province,thereby confirming its rationality and effectiveness.This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.