Finite Capacity Research Articles

A Study of a Two Storage Single Product Inventory System with Ramp Type Demand, N-Phase Prepayment and Purchase for Exigency

This model considers a two-warehouse inventory system of deteriorated items with ramp-type demand and a constant rate of deterioration. It is maintained a rental warehouse (RW) of infinite capacity to load the excess items of replenished goods after filling the items of finite capacity in the own warehouse (OW). Retailers are encouraged to opt for the prepayment option of paying their purchase cost in equal installments prior to the delivery of the ordered items with a considerable discount, which will ensure the purchase guarantee of their orders. The slotted backlog interval of the stock out period is handled in two different ways to retain the customers and ease their impatience. Customers in the first slot of the stock out period are satisfied by the emergency purchases from local suppliers with high purchasing costs to avoid losing customers. Customers in the next slot are satisfied immediately after the next replenishment point. Essential measures of the system are derived: optimal ordering quantities from both regular and local suppliers; replenishment cycle length; and a partitioned backlog interval. A numerical example is given along with the optimal solutions for a particular environment with sensitive analysis in order to validate the model’s efficacy.

Ultrahigh edge‑nitrogen-doped porous carbon anode materials for high-capacity and fast-charging lithium-ion batteries

Most reported nitrogen-doped carbon anode materials of lithium-ion batteries (LIBs) own finite capacities and inferior initial coulombic efficiency (ICE). One effective method to enhance capacities and capacities of the nitrogen-doped carbon anode materials is edge‑nitrogen doping. It still endures obstacles to realize a high edge‑nitrogen doping level owing to the difficulty to control of the nitrogen doping types. In this work, a series of edge‑nitrogen-doped porous carbon (ENPC) with different edge‑nitrogen doping levels are synthesized by annealing sucrose and g-C3N4 in a sealed graphite crucible. The edge‑nitrogen doping level from 8.88 at.% to 12.93 at.% for the ENPC-T can be regulated by changing the annealing temperature. Serving as LIBs anodes, the ENPC-800 exhibits an excellent capacity (1251.1 mAh g−1 at 0.1 A g−1), high ICE (82.9 %) and remarkable cycle life (650.5 mAh g−1 at 1 A g−1 after 1000 cycles with an exceptional capacity retention of 99.3 %). More significantly, by correlating the capacity and conductivity with the nitrogen doping configuration of the ENPC-T materials, the results highlight the effect of edge‑nitrogen on the capacity and conductivity. Meanwhile, the electrochemical characterizations of CV, GITT and EIS illustrate that a higher edge‑nitrogen doping level improves the capacity, electronic conductivity and fast-charging performance of ENPC-T. This new strategy can pave a new approach for the investigation and application of nitrogen-doped carbon anodes.

Dealing With Security Issues In IoT

IoT (Internet of Things) is related to design of a lot of iinter-related “contrived" gadgets having finite capacities with regard to memory and processing power and design is like an Internet. These are frequently battery-driven, raises requirement for adopting environment-friendly techniques. Between the noteworthy ultimatum that establishing interrelated smart objects accompanies are uniformity and coordination. Many smart objects are presumed to develop and addresses of IPv4 are normally utilized. IPv6 is recognized as a possibility for smartobject transmission. Internet of Things (IoT) is a global network of physical and virtual ‘things’ connected to the internet. All objects have unique IDs that are utilized for identification. IoT is the emerging technology which can change the way we communicate with devices. Hereafter almost every electronic device will be a smart device that will be able to compute and communicate with handheld and other infrastructure gadgets. The Internet of Things utilization builds a lot of security problems, which arises from • Smart objects essence: utilization of cryptographic algorithms which are delicate, with regard to requirements of processing and memory. • Quality protocols utilization and the requirement to reduce the data quantity swapped among nodes. An IoT usage which accumulates or handles consumer distinctive data like bank particulars require a foremost rank of security, while a sensor linked to a station area will have a low rank. It need not be costly to carry out fundamental security steps; but it is significant to determine a security strategy and incorporate recuperation measures in the security problems incidents. The main aim of this topic is to describe mechanisms which can help to deal with IoT security issues.

Cell-Free Massive MIMO With Finite Fronthaul Capacity: A Stochastic Geometry Perspective

In this work, we analyze the downlink performance of a cell-free massive multiple-input-multiple-output system with finite capacity fronthaul links between the centralized baseband unit and the access point (APs). Conditioned on the user and AP locations, we first derive an achievable rate for a randomly selected user in the network that captures the effect of finite fronthaul capacity as a compression error. From this expression, we establish that for the traditional cell-free architecture where each AP serves all the users in the network, the achievable rate becomes zero as the network size grows. Hence, to have a meaningful analysis, for the traditional architecture, we model the user and AP locations as two independent binomial point processes over a finite region and provide an accurate theoretical result to determine the user rate coverage. In contrast, for an asymptotically large network, we consider a user-centric architecture where each user in the network is served by a specified number of nearest APs that limits the fronthaul load. For this architecture, we model the AP and user locations as two independent Poisson point processes (PPPs). Since the rate expression is a function of the number of users served by an AP, we statistically characterize the load in terms of the number of users per AP. As the exact derivation of the probability mass function of the load is intractable, we first present the exact expressions for the first two moments of the load. Next, we approximate the load as a negative binomial random variable through the moment matching method. Using the load results along with appropriate distance distributions of a PPP, we present an accurate theoretical expression for the rate coverage of the typical user. From the analyses, we conclude that for the traditional architecture when the AP transmit power is relatively high, a more collocated antenna deployment is preferred. Further, for the user-centric architecture, the energy efficiency of the system is a concave function of the number of antennas per AP.

Optimal Strategies in a Production Inventory Control Model

We consider a production-inventory control model with finite capacity and two different production rates, assuming that the cumulative process of customer demand is given by a compound Poisson process. It is possible at any time to switch over from the different production rates but it is mandatory to switch-off when the inventory process reaches the storage maximum capacity. We consider holding, production, shortage penalty and switching costs. This model was introduced by Doshi, Van Der Duyn Schouten and Talman in 1978. In their paper they found a formula for the long-run average expected cost per unit time as a function of two critical levels, in this paper we consider expected discounted cumulative costs instead. We seek to minimize this discounted cost over all admissible switching strategies. We show that the optimal cost functions for the different production rates satisfy the corresponding Hamilton-Jacobi-Bellman system of equations in a viscosity sense and prove a verification theorem. The way in which the optimal cost functions solve the different variational inequalities gives the switching regions of the optimal strategy, hence it is stationary in the sense that depends only on the current production rate and inventory level. We define the notion of finite band strategies and derive, using scale functions, the formulas for the different costs of the band strategies with one or two bands. We also show that there are examples where the switching strategy with two critical levels is not optimal.

Strategic Resource Pricing and Allocation in a 5G Network Slicing Stackelberg Game

We consider a marketplace in the context of 5G network slicing, where Application Service Providers (ASP), <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.,</i> slice tenants, providing heterogeneous services, are in competition for the access to the virtualized network resource owned by a Network Slice Provider (NSP), who relies on network slicing. We model the interactions between the end users (followers) and the ASPs (leaders) as a Stackelberg game. We prove that the competition between the ASPs results in a multi-resource Tullock rent-seeking game. To determine resource pricing and allocation, we devise two innovative market mechanisms. First, we assume that the ASPs are pre-assigned with fixed shares (budgets) of infrastructure, and rely on a trading post mechanism to allocate the resource. Under this mechanism, the ASPs can redistribute their budgets in bids and customise their allocations to maximize their profits. In case a single resource is considered, we prove that the ASPs’ coupled decision problems give rise to a unique Nash equilibrium. Second, when ASPs have no bound on their budget, we formulate the problem as a pricing game with coupling constraints capturing the shared resource finite capacities, and derive the market prices as the duals of the coupling constraints. In addition, we prove that the pricing game admits a unique variational equilibrium. We implement two online learning algorithms to compute solutions of the market mechanisms. A third fully distributed algorithm based on a proximal method is proposed to compute the Variational equilibrium solution of the pricing game. Finally, we run numerical simulations to analyse the market mechanism’s economic properties and the convergence rates of the algorithms.

QoS maximization scheduling of multiple UAV base stations in 3D environment

Using Unmanned aerial vehicle (UAV) as base stations for providing communication services to urban residents has emerged as a novel trend in the era of the Internet of Things (IoT). However, UAV base stations (UAV-BSs) applications have faced some challenges, such as the finite energy capacity, the limited coverage range, and the complex flying environment. Consequently, addressing these challenges and maximizing communication service quality remains a significant problem. In order to achieve higher service quality, it is necessary for UAV-BSs to collaborate with each other, optimize their serving positions, and conserve energy. Although existing works have investigated some of these challenges, there has been a lack of work that considered all of them jointly. In this work, we propose a Local-based scheduling algorithm which aims to maximize the service quality by achieving a good balance between flying status and serving status of UAV-BSs. The proposed method has been evaluated by theoretical analysis and simulation experiments. The results demonstrate its effectiveness in significantly improving the communication service quality.

Thermo-economic optimization of irreversible Novikov power plant models including a proposal of dissipation cost

The main component of the cost–benefit ratio of the electricity generation market relates to the finite energy capacity of macroscopic systems to perform conversion processes. Within the context of Finite-Time Thermodynamics (FTT), we aim to introduce an economic feature analysis of a non-endoreversible power plant model, the so-called Chambadal–Novikov model. We emulate the irreversible energy conversion processes of real-world power plants via the non-endoreversibility parameter (R) and heat transfer laws such as the Newtonian, Dulong–Petit and Stefan–Boltzmann. We find a connection between two maximum economic-energetic optimization criteria: The power output and the generalized ecological one with the economic Π function. Furthermore, we show that the maximum power output regime can be considered as a short-term recovery regime; however, it produces considerably more dissipated energy towards the atmosphere. With the help of these economic regimes, we introduce a proposal of “dissipation cost” through the total running cost function, and it can lead us to propose an ecological tariff expressed as the difference between the ratio of the capitalization of fuel consumption cost and incomes.

Variability in exercise tolerance and physiological responses to exercise prescribed relative to physiological thresholds and to maximum oxygen uptake.

What is the central question of this study? Does prescribing exercise intensity using physiological thresholds create a more homogeneous exercise stimulusthanusing traditional intensity anchors? What is the main finding and its importance? Prescribing exercise using physiological thresholds, notably critical power, reduced the variability in exercise tolerance and acute metabolic responses. At higher intensities, approaching or exceeding the transition from heavy to severe intensity exercise, the imprecision of using fixed % as an intensity anchor becomes amplified. The objective of this study was to determine whether the variability in exercise tolerance and physiological responses is lower when exercise is prescribed relative to physiological thresholds (THR) compared to traditional intensity anchors (TRAD). Ten individuals completed a series of maximal exercise tests and a series of moderate (MOD), heavy (HVY) and severe intensity (HIIT) exercise bouts prescribed using THR intensity anchors (critical power and gas exchange threshold) and TRAD intensity anchors (maximum oxygen uptake; ). There were no differences in exercise tolerance or acute response variability between MODTHR and MODTRAD . All individuals completed HVYTHR but only 30% completed HVYTRAD . Compared to HVYTHR , where work rates were all below critical power, work rates in HVYTRAD exceeded critical power in 70% of individuals. There was, however, no difference in acute response variability between HVYTHR and HVYTRAD . All individuals completed HIITTHR but only 20% completed HIITTRAD . The variability in peak (F=0.274) and average (F=0.318) blood lactate responses was lower in HIITTHR compared to HIITTRAD . The variability in W' depletion (the finite work capacity above critical power) after the final interval bout was lower in HIITTHR compared to HIITTRAD (F=0.305). Using physiological thresholds to prescribe exercise intensity reduced the heterogeneity in exercise tolerance and physiological responses to exercise spanning the boundary between the heavy and severe intensity domains. To increase the precision of exercise intensity prescription, it is recommended that, where possible, physiological thresholds are used in place of .

Rational inattention, misallocation, and the aggregate economy

I study the effect of firm managers’ information-processing constraints on production decisions, resource misallocation, and the aggregate economy. Managers have a finite information-processing capacity to reduce uncertainty about firm-specific and economy-wide shocks. The model implies that an increase in aggregate uncertainty leads to reallocation of capacity from learning about firm-specific shocks to learning about aggregate state, leading to higher misallocation of resources and lower output. In contrast, an increase in idiosyncratic uncertainty (through an opposite mechanism) has a non-monotonic effect on aggregate productivity. The model produces new implications regarding the co-movement of inputs and Labor-TFP sensitivity which I confirm empirically.

Recursive decomposition/aggregation algorithms for performance metrics calculation in multi-level assembly/disassembly production systems with exponential reliability machines

Developing accurate and computationally efficient algorithms for system performance metrics calculation is critical to implementing effective control and optimization in manufacturing system operations. In this paper, we propose a recursive decomposition/aggregation-based method for calculating the performance metrics of assembly/disassembly systems with multiple merge/split operations and sub-assemblies. It is assumed that the machines follow the exponential reliability model and the buffers are of finite capacity. To achieve this, we first consider assembly systems with multiple component lines merging at a single assembly operation. By decomposing the system into a set of virtual serial lines, we derive an analytical procedure to approximate the starvation and blockage probabilities of the merge operation, which are used to recursively update the parameters of the virtual serial lines. Then, the performance metrics of the original assembly system are approximated based on the corresponding machines and buffers in these virtual serial lines. Next, we extend the algorithm to assembly/disassembly systems with multiple merge/split operations and sub-assemblies. This is accomplished by identifying the so-called assembly/disassembly units formed based on the virtual serial lines and applying the calculations derived earlier recursively. Simulation experiments are carried out to justify the convergence, computational efficiency, and approximation accuracy of the proposed algorithms. An industrial case study is presented to demonstrate the theoretical methods in practical applications.

A meta-heuristic optimization for a novel mathematical model for minimizing costs and maximizing donor satisfaction in blood supply chains with finite capacity queueing systems

Blood and blood banks play an essential role in patient care. This study proposes a novel mathematical model for Blood Supply Chains (BSCs), which minimizes the total costs and maximizes donor satisfaction by reducing the system’s waiting time. The model addresses several aspects of the BSC, such as locating collection centers, allocating blood donors to collection centers, inventory control in the main blood center, blood shortage and deterioration considerations, and queueing systems in collection centers over a planning horizon. Queueing systems lead to a better understanding of the BSC and provide an opportunity to investigate donors’ attendance and waiting times. A real-world case study is presented and solved using a new meta-heuristic algorithm to illustrate the model’s applicability. Finally, sensitivity analyses are performed, and several beneficial managerial insights are provided.

Improvement of a temperature response function for divertor heat flux monitoring in fusion devices

Temperature response functions have been developed to investigate sensor design and divertor heat flux estimation in magnetically confined plasmas. The time-dependent heat flux can be derived by fitting the response function to experimental thermocouple (TC) data. Because the TC signals have a time delay to transit events such as discharge start or confinement transition, the time delay is taken into account in a temperature response function. Such a function accurately describes the signal from each TC channel with time delay in a sensor test using a neutral beam injection. Measurement for commercial TCs shows that the time delay is caused by the finite heat capacity of TC wire and contact heat resistance between TC and target surface.

Finite temperature properties of uranium mononitride

Uranium mononitride (UN) is a promising nuclear fuel that combines the advantageous properties of readily used UO2 and uranium alloys, such as high melting temperature and high uranium density, and thermal conductivity, respectively. A better understanding of UN behavior at operating temperatures can be obtained from finite temperature data, such as elastic properties. To get this information, ab initio molecular dynamics (AIMD) simulations were performed at five different temperatures using constant volume (NVT) and constant pressure (NPT) ensembles. Initially, the performance of PBE functional in reproducing experimental crystallographic properties and magnetic ordering is assessed. The finite temperature phonon dispersions are calculated using NVT simulation results, which show a softening of the phonon modes with increasing temperature. The NPT results are used to obtain the thermal expansion of UN and finite temperature electronic properties. The calculated thermal expansion is compared with our measurements using neutron diffraction. Additionally, the temperature dependent elastic properties of UN are evaluated using the strain-stress method in AIMD simulations, indicating that UN becomes softer and more compressible with increasing temperature. Also, the calculated Young’s modulus slope is in very good agreement with the experiment. The finite temperature heat capacity and electronic thermal conductivity are calculated from AIMD simulations, which are in better agreement with the experiment than the heat capacity and thermal conductivity calculated using the structures relaxed at 0 K. Lastly, the thermal diffusivity from AIMD has opposite temperature dependence compared to experimental results, which we argued comes from the underestimated electronic thermal conductivity.

Zeolite Adsorbents for Selective Removal of Co(II) and Li(I) from Aqueous Solutions

Cobalt and lithium are critical metals because of its shortage, difficulty of extraction and huge economic impact due to their market value. The purpose of this work is to study their selective removal from aqueous solutions in different conditions using two commercial FAU zeolites as adsorbent materials. These solids were characterized by XRD, XRF and BET analysis, to follow up of their FAU structure integrity, their Si/Al ratio, and their specific surface area evolutions through their preparation process. The kinetic study indicates that using both zeolites with a dosage of 5 g/L a 100% cobalt removal from aqueous solutions is achievable, while lithium removal is kept around 30% (separation factor of 3.33). This selectivity is important as these two metals frequently appear together in leaching solutions form, for example, ion-Li batteries. In relation to the adsorption equilibrium, cobalt adsorption presents a finite adsorption capacity while this behavior is not observed in lithium adsorption. For this reason, Langmuir model is the most adequate to represent cobalt adsorption, while lithium adsorption is better represented by Freundlich model.

Ensemble-NQG-T5: Ensemble Neural Question Generation Model Based on Text-to-Text Transfer Transformer

Deep learning chatbot research and development is exploding recently to offer customers in numerous industries personalized services. However, human resources are used to create a learning dataset for a deep learning chatbot. In order to augment this, the idea of neural question generation (NQG) has evolved, although it has restrictions on how questions can be expressed in different ways and has a finite capacity for question generation. In this paper, we propose an ensemble-type NQG model based on the text-to-text transfer transformer (T5). Through the proposed model, the number of generated questions for each single NQG model can be greatly increased by considering the mutual similarity and the quality of the questions using the soft-voting method. For the training of the soft-voting algorithm, the evaluation score and mutual similarity score weights based on the context and the question–answer (QA) dataset are used as the threshold weight. Performance comparison results with existing T5-based NQG models using the SQuAD 2.0 dataset demonstrate the effectiveness of the proposed method for QG. The implementation of the proposed ensemble model is anticipated to span diverse industrial fields, including interactive chatbots, robotic process automation (RPA), and Internet of Things (IoT) services in the future.

Queueing Inventory System in Transport Problem

In this paper, we consider the batch arrival of customers to a transport station. Customers belonging to each category is considered as a single entity according to a BMMAP. An Erlang clock of order m starts ticking when the transport vessel reaches the station. When the Lth stage of the clock is reached, an order for the next vessel is placed. The lead time for arrival of the vessel follows exponential distribution. There are two types of rooms in this system: the waiting rooms and the service rooms for customers in the transport station and in the vessel, respectively. The waiting room capacity for customers of type 1 is infinite whereas those for customer of type 2,…,k are of finite capacities. The service room capacity Cj for customer type j,j=1,2,…,k is finite. Upon arrival, customers of category j occupy seats designated for that category in the vessel, provided there is at least one vacancy belonging to that category. The total number of vessels with the operator is h*. The service time of each vessel follows exponential distribution with parameter μ. Each group of customers belong to category j searches independently for customers of this category to mobilize passengers when the Erlang clock reaches L1 where L1&lt;L. The search time for customers of category j follows exponential distribution with parameter λj. The stability condition is derived. Some performance measures are estimated.

Effect of ground-motion sequences on a unreinforced masonry wall restrained by an elasto-plastic tie-rod

This work investigates the effect of international ground-motion sequences on the out-of-plane response of an ordinary-building façade. The following assumptions are made on the wall boundary conditions: the wall is resting on a foundation, it is adjacent to transverse walls and restrained by elasto-plastic tie rods with finite elongation capacity. Four walls are considered of different aspect ratio and size; two types of masonry are assumed, and the tie is designed following a force-based procedure according to the Commentary to the Italian Building Code. The walls are modelled as rigid blocks of finite thickness and free to rotate on one side only. The rocking response of the walls, excited in the out-of-plane direction under 56 sequences of records, is evaluated. The effect of sequences is estimated by the comparison of the response experienced during the sequence and under a single record, strongest in terms of either peak ground acceleration or velocity. Finally, in order to reduce the vulnerability originated by a seismic sequence, a proposal of a reduced behaviour factor to be adopted in the design of tie rods is formulated.

Equilibria in Network Constrained Energy Markets

We study an energy market composed of producers who compete to supply energy to different markets and want to maximize their profits. The energy market is modeled by a graph representing a constrained power network where nodes represent the markets and links are the physical lines with a finite capacity connecting them. Producers play a networked Cournot game on such a network together with a centralized authority, called market maker, that facilitates the trade between geographically separate markets via the constrained power network and aims to maximize a certain welfare function. We first study the existence and uniqueness of Nash equilibria. Then, we prove an important result that links capacity bottlenecks in the power network and the emergence of price differences between different markets that are separated by saturated lines, a phenomenon that is often observed in real power networks.

Analysis of Variance and Standard Deviation of FM/M/1/k Interdependent Stochastic Feedback Arrival Model with Finite Capacity and Single Server

In this paper, analysis of variance and standard deviation of interdependent stochastic feedback arrival rate and single server with service rate are considered. The steady-state solution and system characteristics are derived for this model. The effect of the nodal parameters on the system characteristics is established and using Maple software the analytical results are numerically illustrated and relevant conclusions are presented.