Designing a new mathematical model based on ABC analysis for inventory control problem: A real case study

In modern business today, organizations that hold large numbers of inventory items, do not find it economical to make policies for the management of individual inventory items. Managers, thus, need to classify these items according to their importance and fit each item to a certain asset class. The method of grouping and inventory control available in traditional ABC has several disadvantages. These shortcomings have led to the development of an optimization model in the present study to improve the grouping and inventory control decisions in ABC. Moreover, it simultaneously optimizes the existing business relationships among revenue, investment in inventory and customer satisfaction (through service levels) as well as a company's budget for inventory costs. In this paper, a mathematical model is presented to classify inventory items, taking into account significant profit and cost reduction indices. The model has an objective function to maximize the net profit of items in stock. Limitations such as budget even inventory shortages are taken into account too. The mathematical model is solved by the Benders decomposition and the Lagrange relaxation algorithms. Then, the results of the two solutions are compared. The TOPSIS technique and statistical tests are used to evaluate and compare the proposed solutions with one another and to choose the best one. Subsequently, several sensitivity analyses are performed on the model, which helps inventory control managers determine the effect of inventory management costs on optimal decision making and item grouping. Finally, according to the results of evaluating the efficiency of the proposed model and the solution method, a real-world case study is conducted on the ceramic tile industry. Based on the proposed approach, several managerial perspectives are gained on optimal inventory grouping and item control strategies

Complications 15 years after breast augmentation with polyacrylamide

AbstractPolyacrylamide hydrogel (PAAG) has been used as an injectable, permanent filler for soft-tissue augmentation for more than two decades. Several complications have been reported worldwide. In this case report, we present a woman with long-term complications 15 years after bilateral breast augmentation with PAAG injections

Impact of microplastics on organic fouling of hollow fiber membranes

Given the potential hazards of microplastics (MPs), it is desirable to efficiently remove them during wastewater treatment processes. To this end, ultrafiltration (UF) membranes can significantly increase the removal of MPs, however the fouling of such membrane modules can also be impacted by the presence of MPs. Magnetic Resonance Imaging (MRI) was used here to non-invasively quantify the effect of polyethylene (PE) MPs accumulation in a 3D UF hollow fiber (HF) membrane module containing 400 fibers, via direct non-invasive velocity imaging of the flow distribution between individual fibers during module operation. The co-effect of MPs and alginate (a common organic model foulant mimicking extracellular polymeric substances (EPS)) on fouling of the HF module was then explored. Flow was initially equally distributed with fouling causing flow in particular fibers to be significantly reduced. Fouling with MPs resulted in minimal flow distribution disruption and was easily remediated hydraulically, in contrast alginate fouling required chemical cleaning in order to fully restore homogeneous flow distribution between the fibers. The presence of both MPs and alginate resulted in a more heterogeneous disruption of the fibre flow distribution due to fouling and resulted in much more effective hydraulic cleaning of the module

Numerical and analytical investigation on meltpool temperature of laser-based powder bed fusion of IN718

Prediction of meltpool features in Laser-Based Powder Bed Fusion (LB-PBF) is a complex non-linear multiple phase dynamic problem. In this investigation, numerical simulations and analytical models are offered to predict meltpool temperature and to provide a methodology to estimate melt track quality. By determining the meltpool temperature, different rheological phenomena including recoil pressure can be controlled. Recoil pressure is known to drive the keyhole and conduction modes in LB-PBF which is an important factor to qualify the melt track. A numerical simulation was carried out using Discrete Element Method (DEM) with a range of process parameters and absorptivity ratios; allowing observation of the variation of meltpool temperature and free surface morphology, as calculated by the volume-of-fluid (VOF) method. A spatially thermophysical-based analytical model is developed to estimate meltpool temperature, based on LB-PBF process parameters and thermophysical properties of the material. These results are compared with experimentally observed meltpool depth for IN718 specimens and found to have a good accuracy. The numerical and analytic results show good agreement in the conduction mode to estimate the meltpool temperature and related phenomena such as recoil pressure to control the melt track and layering quality. The analytical model does not accurately predict the keyhole mode which may be explained by evaporation of chemical elements in the examined material

Multi-Stage Fuzzy Load Frequency Control Based on Multi-objective Harmony Search Algorithm in Deregulated Environment

A new Multi-Stage Fuzzy (MSF) controller based on Multi-objective Harmony Search Algorithm (MOHSA) is proposed in this paper to solve the Load Frequency Control (LFC) problem of power systems in deregulated environment. LFC problem are caused by load perturbations, which continuously disturb the normal operation of power system. The objectives of LFC are to mini small size the transient deviations in these variables (area frequency and tie-line power interchange) and to ensure their steady state errors to be zero. In the proposed controller, the signal is tuned online using the knowledge base and fuzzy inference. Also, to reduce the design effort and optimize the fuzzy control system, membership functions are designed automatically by the proposed MOHSA method. Obtained results from the proposed controller are compared with the results of several other LFC controllers. These comparisons demonstrate the superiority and robustness of the proposed strategy

Formal Methods for Autonomous Systems

Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems. The main building blocks of formal methods are models and specifications, which are analogous to behaviors and requirements in system design and give us the means to verify and synthesize system behaviors with formal guarantees. This monograph provides a survey of the current state of the art on applications of formal methods in the autonomous systems domain. We consider correct-by-construction synthesis under various formulations, including closed systems, reactive, and probabilistic settings. Beyond synthesizing systems in known environments, we address the concept of uncertainty and bound the behavior of systems that employ learning using formal methods. Further, we examine the synthesis of systems with monitoring, a mitigation technique for ensuring that once a system deviates from expected behavior, it knows a way of returning to normalcy. We also show how to overcome some limitations of formal methods themselves with learning. We conclude with future directions for formal methods in reinforcement learning, uncertainty, privacy, explainability of formal methods, and regulation and certification

Long range correlation in cosmic microwave background radiation

We investigate the statistical anisotropy and Gaussianity of temperature fluctuations of Cosmic Microwave Background radiation (CMB) data from {\it Wilkinson Microwave Anisotropy Probe} survey, using the multifractal detrended fluctuation analysis, rescaled range and scaled windowed variance methods. The multifractal detrended fluctuation analysis shows that CMB fluctuations has a long range correlation function with a multifractal behavior. By comparing the shuffled and surrogate series of CMB data, we conclude that the multifractality nature of temperature fluctuation of CMB is mainly due to the long-range correlations and the map is consistent with a Gaussian distribution.Comment: 10 pages, 7 figures, V2: Added comments, references and major correction

Persistent molecular disease in adult patients with AML evaluated with whole-exome and targeted error-corrected DNA sequencing

PURPOSE: Persistent molecular disease (PMD) after induction chemotherapy predicts relapse in AML. In this study, we used whole-exome sequencing (WES) and targeted error-corrected sequencing to assess the frequency and mutational patterns of PMD in 30 patients with AML. MATERIALS AND METHODS: The study cohort included 30 patients with adult AML younger than 65 years who were uniformly treated with standard induction chemotherapy. Tumor/normal WES was performed for all patients at presentation. PMD analysis was evaluated in bone marrow samples obtained during clinicopathologic remission using repeat WES and analysis of patient-specific mutations and error-corrected sequencing of 40 recurrently mutated AML genes (MyeloSeq). RESULTS: WES for patient-specific mutations detected PMD in 63% of patients (19/30) using a minimum variant allele fraction (VAF) of 2.5%. In comparison, MyeloSeq identified persistent mutations above 0.1% VAF in 77% of patients (23/30). PMD was usually present at relatively high levels (\u3e2.5% VAFs), such that WES and MyeloSeq agreed for 73% of patients despite differences in detection limits. Mutations in CONCLUSION: PMD and clonal hematopoiesis are both common in patients with AML in first remission. These findings demonstrate the importance of baseline testing for accurate interpretation of mutation-based tumor monitoring assays for patients with AML and highlight the need for clinical trials to determine whether these complex mutation patterns correlate with clinical outcomes in AML

Comparison of response of canola (Brassica napus L. CV. Hyola 401) to biofertilizer inoculation in optimal and delayed cropping dates

In order to compare the effects of phosphate solubilizing bacteria as biofertilizer and mineral phosphorous application in optimal date of sowing with delayed cropping date on canola (Brassica napus L.) growth and productivity, a splitplot experiment, using randomized complete block design with three replications, was conducted at Dashate-Naz Agronomy Research Station, in 2014. Four levels of bacterial inoculation (Pseudomonas putida, Pseudomonas fluorescens, singly or in combination) were applied as main plots and five levels of mineral phosphorus (P) application (0, 25, 50, 75, and 100 kg·ha-1 of mineral phosphorous) were applied as sub plots. Canola plant were sown at two dates of sowing, one at optimal date of sowing (30 Sept., 2014) and the other one month later as delayed cropping (30 Oct., 2014). The results obtained showed that effects of bacterial inoculation on number of seeds per pod, number of pods on plant, and seed yield were significant at one percent probability level at both sowing dates. Moreover, rates of phosphate application had significant effects on all traits at one percent level. Comparing the means showed that application of mineral P resulted in substantial increase in seed yield. At optimal date of sowing, it was shown that while minimum seed yield obtained at control treatment (1600 kg·ha-1), the maximum (2980 kg·ha-1) obtained with interaction effects of application of both bacterial strains along with 75 kg·ha-1 mineral P, having no statistically difference with that of P. fluorescens, along with 75 kg·ha-1 mineral P (2940 kg·ha-1). It was shown that delayed cropping resulted in decreasing canola growth which is reflected in seed yield and yield components. Minimum seed yield at control plot at first date of sowing (1600 kg·ha-1) decreased to 740 kg·ha-1, in the second date of sowing, showing 54 % decrease. The maximum seed yield also decreased in delayed cropping, from 2980 kg·ha-1 at 30 Sept., 2014, as compared to 1074 kg·ha-1 at 30 Oct., 2014, showing a 64% decrease. The results obtained showed that an increase in P level, eventually enhanced the seed yield. This increasing trend continued until a threshold level (75 kg·ha-1 of P), after which seed yield showed a declining fashion