Minimum Cost Research Articles

Implementation of companding scheme for performance enhancement of optical OFDM structure

Abstract Due to its great spectral efficiency and resistance to multi-path fading, OFDM, or orthogonal frequency division multiplexing, is commonly utilized in optical communication systems. However, because of nonlinear distortions in optical components, OFDM signals are prone to a high peak-to-average power ratio (PAPR), which can severely impair bit error rate (BER) performance. This paper introduces a companding scheme to address high PAPR in optical OFDM systems and improve BER performance. The proposed scheme uses a nonlinear transformation to compress signal peaks and expand valleys, effectively reducing PAPR. Specifically, we investigate the µ-law companding technique, known for its simplicity and effectiveness in handling the active range of OFDM signals in optical communication. The companded signals are transmitted through an optical link and demodulated at the receiver. Simulation results show that the µ-law companding technique substantially reduces PAPR, leading to a significant improvement in BER performance. The companding process maintains signal integrity and spectral efficiency with minimal computational complexity and implementation cost. By mitigating nonlinearities introduced by optical components, this companding scheme enhances the overall reliability and efficiency of the optical OFDM system. An SNR gain of 2 dB–3 dB was achieved at a BER of 10−3.

Towards Energy Efficient Cloud: A Green and Intelligent Migration of Traditional Energy Sources

Geographically distributed cloud data centers (DCs) consume enormous amounts of energy to meet the ever-increasing processing and storage demands of users. The brown energy generated using fossil fuels is expensive and significantly contributes to global warming. Considering the environmental impact caused by the high carbon emissions and relatively high energy cost of brown energy, we propose the integration of renewable energy sources (RES), especially solar and wind energy, with brown energy to power cloud data centers. In our earlier study, we addressed the intermittency of renewable energy sources, where we replaced the random initialization of artificial neural network (ANN) edge weights with the harmony search algorithm (HSA)-optimized assignment of weights. This study incorporated reliably forecast solar and wind energy into the input parameters of our proposed green energy manager (GEM), for cost minimization, carbon emission minimization, and better energy management of cloud DCs, to make our current study more reliable and trustworthy. Four power sources, on-site solar energy and wind energy, off-site solar energy and wind energy, energy stored in energy storage devices, and brown energy, were considered in this study and simulations were carried out for three different cases. The simulation results showed that case 1 (all brown) was 58% more expensive and caused 71% higher carbon emissions than case 2.1 (cost minimization). Case 1 (all brown) was 39% more expensive and had 80% higher carbon emissions than case 2.2 (carbon emission minimization). The simulation results justify the necessity and importance of the GEM, and finally the results proved that our proposed GEM is less expensive and more environmentally friendly.

Economic efficiency of small-scale wheat production in Jigawa state, Nigeria

Africa’s most populous country has failed to grow more food for its fast-rising population. With 420,000 metric tons of wheat produced in Nigeria in 2020, the country is still far from bridging its 4.6 million metric tons annual wheat gap. Increasing wheat production is a challenge for the nation to fulfill the food requirements of its growing population. So far literature has shown a rise in research on wheat in different parts of Nigeria, with a paucity of information on the economic efficiency of wheat production in the study area, and the country in general. To bridge these knowledge and empirical gaps, this research investigates the economic efficiency of wheat production in Jigawa State of Nigeria using information gathered from a survey elicited by a well-structured questionnaire coupled with an interview schedule from 341 active wheat farmers selected through a multi-stage sampling technique. Both descriptive and inferential statistics were used to analyze the data collected. Empirically, despite the wheat enterprise being profitable in the study area, farmers didn’t achieve the targeted goals of output maximization, cost minimization, and profit maximization as evident respectively by the technical, cost, and economic efficiency indexes. However, these goals were challenged by induced human risks viz. gender discrimination that affects women’s access to productive resources, poor labor productivity due to diminishing marginal returns associated with old age, capital consumption triggered by increased income, poor prioritization of wheat enterprise as a business, and vulnerable household size. Furthermore, the identified constraints mediating the links that affected the economic efficiency of wheat farmers were price/marketing, technological, managerial, and infrastructural risks. Therefore, for long-run sustainable wheat production, the responsibility lies on policymakers to concentrate more on marketing and technological risks challenging wheat production in the study area as empirically established by this research.

Considering sustainability and resilience in a location-routing problem

Purpose: Sustainability and resilience have emerged as two important topics. Consumers and governmental entities are becoming increasingly aware of the existing environmental and social issues, motivating companies to adopt more sustainable practices. In addition, the uncertainty and unpredictability that characterize today's competitive environment force companies to be able to handle disruptions efficiently. Despite this, when looking at some classes of problems in literature, cost is still the most, or even the only, objective addressed. This work analyses the integration of sustainability and resilience concerns in a class of problems that is often found in logistics, the Location-Routing Problem (LRP).Design/methodology/approach: A multi-objective LRP is addressed with the following objectives: minimization of the total cost of the logistics network, minimization of the environmental impact of CO2 emissions, and maximization of the resilience of the distribution network. Aiming to explore the effect that designing a more sustainable and resilient distribution network can have on its operating costs, the ?-constraint method is applied.Findings: Results show that resilience and environmental impacts, from a practical point of view, should not be considered in isolation, as they can have significant impacts on costs. Nevertheless, it is conceivable to design logistics networks that ensure a good compromise between operating costs, environmental impacts, and resilience to disruptions.Originality/value: This paper is an exploratory study addressing a new type of location-routing problem which, besides the usual cost objective, considers sustainability and resilience as objectives. The paper evaluates the sensitivity of the costs of logistics networks to the improvement of their resilience and sustainability. A new multi-objective formulation is proposed for this class of problems, tested in instances based on real-world data. The paper may provide important managerial insights for designing sustainable and resilient logistics networks.

First Report of Bacterial Leaf Spot Disease on Sesame (Sesamum indicum L.) Caused by Pseudomonas syringae pv. sesami in North Carolina.

In July 2022, dark brown to black, angular, water-soaked lesions were observed on sesame leaves (Sesamum indicum L.) in a research plot established to assess yield potential for eight varieties at the North Carolina (NC) Sandhills Research Station (Chavez 2023). Symptoms were indicative of a bacterial leaf spot (BLS). At early flowering stage, leaf spots were present on scattered plants; varieties ES108, SS3301, and ES201 exhibited up to 75% disease prevalence, with lower frequency in ES103, S39, S4302, S3251, and S3276. Symptomatic leaves from 3-4 plants were collected on four different dates from July through September. A section of symptomatic tissue was excised and macerated in sterile deionized water (SDW). A 10 µL aliquot was streaked onto SPA medium (15 g sucrose, 5.0 g proteose peptone, 0.50 g MgSO4 7H2O, 0.25 g K2HPO4, 15 g agar per liter of SDW) and incubated at 28ºC. After 72 h, numerous, smooth, white-cream colored, convex-shaped, colonies were individually isolated. Five randomly selected isolates from the different collection dates, designated as AHP108-AHP111 and AHP116, were genotyped. The 16S rRNA, gyrB, rpoD, and gapA genes were sequenced (Heuer et al. 1997; Hwang et al. 2005) and deposited to NCBI (GenBank Accessions: P213467- PP213470; OQ628040-OQ628042; PP214983-PP214994; and PP255798). These five isolates shared 100% sequence identity for gyrB and rpoD. AHP108-AHP111 shared 100% sequence identity for 16S rRNA and gapA, with 99.7% and 90.8% identity, respectively, for AHP116. A phylogenetic tree was inferred from a maximum-likelihood analysis of concatenated gyrB, rpoD, and gapA sequences of the five isolates and the top 11 hts from a blastn search of the NCBI nucleotide database. Those hits included closely related sequences from Pseudomonas syringae pv. sesami type strains ICMP 763T and ICMP 7459T. Based on this phylogenetic analysis AHP108-AHP111 and AHP116 are P. syringae pv. sesami. Recent genomic analysis suggests this pathovar is part of P. amygdali (Gomila et al. 2017), but an official name change has not been proposed. Each of the five isolates were infiltrated into leaves of sesame varieties ES108, ES103, and S327, consistently resulting in similar symptoms. Thus, strain AHP116, as a representative, was used to fulfill Koch's postulates using five, 30-day-old potted sesame plants (var. S3301). Plants were spray-inoculated with a bacterial suspension of ~108 CFU/ml until runoff; plants were incubated in moist chambers 24 h pre and post inoculation at 28ºC with 80% relative humidity and a 12 h photoperiod. At 13 days post inoculation, symptoms resembling those on plants at the Sandhills Research Stations in 2022 were evident. Reisolated bacteria were confirmed to be AHP116 through 16S rRNA and gyrB amplification and sequencing. No symptoms were observed on the five water-inoculated plants. BLS of sesame has been reported in Asia and is thought to be seedborne (Firdous et al. 2009; Prathuangwong and Yowabutra 1997). To our knowledge, this is the first report of P. syringae pv. sesami causing BLS on sesame in North Carolina. Sesame cultivation in the state increased from approximately 2,000 acres in 2022 to 13,000 acres in 2023 and there is interest in cultivating sesame as a rotational and alternative crop because it requires minimal input costs. Potential outbreaks of BLS in this warm, humid region could negatively affect sesame production, where little is known about the economic impact of the disease.

GABA-gated chloride channel mutation (Rdl) induces cholinergic physiological compensation resulting in cross resistance in Drosophila melanogaster

The Drosophila melanogaster MD-RR strain contains an Rdl mutation (A301S) resulting in resistance to several insecticide classes viz. phenyl pyrazoles (e.g., fipronil), cyclodienes (e.g., dieldrin), and chlorinated aliphatic hydrocarbons (e.g., lindane). Fitness costs are commonly observed with resistant insect populations as side effects of the genetic change conferring the resistant phenotype. Because of fitness costs, reversion from the resistant to susceptible genotype and phenotype is common. However, the Rdl genotype in D. melanogaster appears to allow the flies to maintain the resistant genotype/phenotype without selective pressure and with minimal fitness costs. We provide evidence that compensation for the Rdl mutation influences the cholinergic system, where an increase in acetylcholinesterase gene expression and enzyme activity results in neurophysiological changes and cross resistance to a carbamate insecticide (propoxur oral resistance ratio (RR) of 63) and an organophosphate insecticide (dichlorvos oral RR of 7). Such cross resistance was not previously reported with the initial collection and testing of this strain. In addition to acetylcholinesterase, the Rdl mutation influences the expression of the muscarinic acetylcholine receptor subtype-B, resulting in resistance to non-selective muscarinic compounds (pilocarpine and atropine). Collectively, these results indicate that the Rdl mutation (A301S) at GABA-gated ionophore complex influences the physiology of the cholinergic system, leading to resistance to established insecticide classes. Additionally, this mutation may impact the effectiveness of insecticides targeting novel sites, like muscarinic receptors.

Design cost minimization of a reinforced concrete column section using overnew swarm-based optimization algorithms

It is very tiresome for a practiser to detect the best feasible sizing design of structural members including reinforced concrete columns that is a highly nonlinear and complicated structural engineering optimization problem. This is due to such a design is practically conducted via conventional trial-and-error computing methods in which resistance to external loads, cost efficiency, and aesthetic factors, etc. have to be considered. This study focuses on minimizing the design cost of primarily proposed reinforced concrete column design problem via three overnew swarm-based optimizers such as Coati Optimization Algorithm, Fox Optimizer and Pelican Optimization Algorithm (POA) that are firstly utilized for this purpose. In this regard, the type of steel rebar distribution, the characteristic strength of the concrete, the height and width of the column section, and the number and diameter of the rebars are treated as discrete design variables of the newly proposed complex reinforced concrete column design cost optimization problem. In solution, the design requirements specified in practice code provisions should also be met. Here, Turkish Building Earthquake Code 2018 specifications are considered as practice structural design constraints. Consequently, the algorithmic performances of three overnew swarm-based metaheuristic optimization algorithms are compared and evaluated in detail. Amongst them, the POA shows most fruitful algorithmic design solution performance.

DivideMerge: A multi-vessel optimization approach for cooperative operation and maintenance scheduling in offshore wind farm

The optimization of maintenance scheduling and routing in offshore wind farms is crucial for the intelligent operation and maintenance of offshore wind energy. It involves determining the optimal timing, assigning vessels, planning routes, and efficiently completing maintenance tasks with maximum efficiency and minimal cost. Traditional branch-and-bound search methods, often used in multi-vessel cooperative maintenance scheduling models, face limitations in finding optimal solutions efficiently, while classic heuristic methods may compromise on global optimality. This paper introduces DivideMerge, a high-performance hybrid algorithm that synergizes heuristic and exact algorithms to address large-scale multi-vessel cooperative maintenance scheduling challenges in offshore wind farms. Initially, a maintenance task constraint decomposition heuristic method is utilized to break down the collaborative optimization scheduling problem into individual vessel scheduling sub-problems, ensuring adherence to the constraints of the original problem. Subsequently, the CP-SAT solver is employed to sequentially solve these sub-problems rapidly. The solutions for individual vessel scheduling are then merged to form a comprehensive solution for the multi-vessel cooperative maintenance scheduling problem. Computational results validate the effectiveness and robustness of DivideMerge, demonstrating a solution speed nearly 1000 times faster than the commercial Gurobi solver, thus offering a significant advancement in the field of offshore wind farm maintenance optimization.

Eliminating Negative Word Similarities for Measuring Document Distances: A Thoroughly Empirical Study on Word Mover's Distance.

Document distance is a fundamental yet significant research topic in the information retrieval community, and its accuracy dominates the performance of many text retrieval applications. Beyond the Bag-of-Words (BoW) model, the Word Mover's Distance (WMD) semantically defines the distance between documents as the minimum cost (i.e., measured by word similarities of embeddings) required to transport the words from one document to another, and it has been proven to be superior by k -nearest neighbor classification. In this article, we thoroughly study the characteristics of WMD and its relaxed versions, e.g., Relaxed WMD (RWMD) and Iterative Constrained Transfers (ICT), in various scenarios. Specifically, we concentrate on the problem of negative word similarity: the WMD family leverages all word similarities, however, most of them are meaningless, resulting in negative effects for measuring document distances. To remedy this problem, we propose Informative Similarity Filter (ISF), which retains a very small percentage of top word similarities and fixes the others as the same lower similarity. Built on it, we propose a greedy optimization (GOM) for WMD, an accurate approximation to WMD. We theoretically analyze that ISF-GOM is more applicable for relatively longer documents. Extensive experiments have been conducted to validate: 1) the problem of RWMD; 2) the effectiveness of ISF-GOM; and 3) the consistence of our analysis of ISF-GOM. Our codes and datasets are available at https://github.com/BoCheng-96/ISF-GOM.

State-of-Art Review of Renewable Energy-Based Systems for Electrical Machine Applications: Prospects and Challenges

Abstract Renewable energy sources (RES) are a game-changer since they produce no greenhouse gases (GHG). There is an increasing amount of interest in it across the world. The intermittent nature of RES makes it difficult to incorporate them into the existing power grid infrastructure and for use in electrical machines for industrial and domestic applications. As the number of RES grows along with different machine variants, innovative methods of interconnecting them are being explored. This study gives a thorough analysis of net zero RES (wind, solar and hydro) for electric machine applications considering their efficiency, feasibility, and reliability coupled with the trend of connection topologies. The Paradigm shift in material technology for RES application is also examined from the 1950s till the present paving the way for innovative design of novel electrical machines with optimal output performances and cost minimization. Modelling and optimization approaches were captured with the benefits and drawbacks highlighted. For electric machines to function at peak efficiency over time, energy harvesting from these sources becomes significant and must be controlled and maintained risk-free. In addition, the challenges, and prospects, associated with the operation of an Electric Machine technology in a clean environment have all been highlighted.

Tropical Shrimp Biofloc Aquaculture within Greenhouses in the Mediterranean: Preconditions, Perspectives, and a Prototype Description

Biofloc technology (BFT) offers an innovative eco-friendly approach that is particularly applicable in shrimp farming. Penaeus vannamei is the most important seafood species in terms of global economic value. Nevertheless, its increasing global demand highlights the necessity for sustainable production of P. vannamei shrimps outside their native range, assuring the avoidance of genetic pollution risk. Towards this direction, the present study focuses on the feasibility of tropical shrimp species aquaculture in indoor systems evaluating BFT application in temperate zones. The achievability of P. vannamei cultivation inside greenhouses in temperate latitudes is thoroughly examined and a representative experimental biofloc setup for P. vannamei within a greenhouse in Northern Greece is demonstrated. Nevertheless, there are two major limitations, related to economy and ecology, namely the energy demand for high seawater temperature and the fact that most reared shrimps are non-indigenous species setting risk for genetic pollution, respectively. To overcome the former, energy-saving measures such as tank and greenhouse insulation in combination with a microclimate chamber construction were implemented to optimize water temperature at minimal cost. Concerning the latter, there is clear evidence that P. vannamei populations cannot be established in the Mediterranean, setting aside any environmental risk. Overall, based on the developed and tested pilot prototype, employment of optimal management practices, innovative manufacturing and clean energy alternatives, and the utilization of ecosystem services could reduce the environmental impact and maximize the profitability of biofloc operations. These actions could probably permit sustainable and economically viable farming of P. vannamei employing BFT within greenhouses in the Mediterranean.

Comprehensive Method for Estimating the Time and Expenditures Required for Mine Liquidation Processes of Business Processes

Abstract The European Green Deal (EU Green Deal) has set the direction for the EU’s energy transition towards climate neutrality by 2050. In Poland, this means moving away from the extraction and use of coal. The Social Contract for the Mining Industry signed in 2021 states the necessity of last mine closure by 2049. Mine closure is a complex, lengthy and costly process. A complex scientific solution may concern the use of rational operations and minimization of mine closure costs. This article presents a system for the elementary assessment of the potential time and cost of coal mine liquidation. Estimating coal mine closure costs in the early design phase is an key aspect of supporting the company dealing with mine closure. The aim of the research was to improve the tool for assessing mine liquidation price. The extended assessment solution proposed in the article is formed on base of statistics of past mining institution liquidation processes. This method can, with minor modifications, be used for each restructuring and revitalizing task for mining industries in the process of liquidation. At the core of the developed method is a preliminary data analysis, which should be confirmed by a complex and multi-criteria estimation of the costs of the planned mine liquidation.

A Novel Localized Fast Multipole Method for Computations With Spatially Correlated Observation Error Statistics in Data Assimilation

AbstractSeveral observation types (e.g., geostationary satellite and Doppler radar observations) have recently been found to exhibit strong spatial error correlations. Including these error statistics in data assimilation for numerical weather prediction can improve analysis quality and forecast skill. Moreover, it allows for increases in the spatial density of observations assimilated, which is needed for the provision of information on appropriate scales for high‐resolution forecasting. However, introducing correlated error statistics may increase the computational complexity and parallel communication costs of matrix‐vector products involving observation precision matrices (inverse observation error covariance matrices). Without new approaches, we cannot take full advantage of new observation uncertainty estimates. We develop a new numerical approximation method based on a particular type of fast multipole method and a domain localization approach. The basic idea is to divide the observation domain into boxes and then separate calculations of matrix‐vector products according to the partition. These calculations can be done in parallel with very low communication overheads. The new method is easy to implement and parallelize, and it is applicable to a wide variety of observation precision matrices. We applied the new method to a simple variational data assimilation problem and found that the computational cost of the variational minimization was dramatically reduced while preserving analysis accuracy across a range of scales. The new method has the potential to be used as an efficient technique for practical applications where a large number of observations with mutual error correlations need to be assimilated quickly.

Prompt-guided DETR with RoI-pruned masked attention for open-vocabulary object detection

Prompt-OVD is an efficient and effective DETR-based framework for open-vocabulary object detection that utilizes class embeddings from CLIP as prompts, guiding the Transformer decoder to detect objects in base and novel classes. Additionally, our RoI-pruned masked attention helps leverage the zero-shot classification ability of the Vision Transformer-based CLIP, resulting in improved detection performance at a minimal computational cost. Our experiments on the OV-COCO and OV-LVIS datasets demonstrate that Prompt-OVD achieves an impressive 21.2 times faster inference speed than the first end-to-end open-vocabulary detection method (OV-DETR), while also achieving higher APs than four two-stage methods operating within similar inference time ranges. We release the code at https://github.com/DISL-Lab/Prompt-OVD.

Digital learning, face-to-face learning and climate change

Debates about digital learning, face-to-face learning and blended learning often focus on their effectiveness in achieving a few core educational outcomes. The cost or convenience of using different methods to achieve certain outcomes have increasingly come into the educational framework over the past two decades. However, only rarely do educators or learners consider the climate footprint of their various activities. This is an important shortcoming, as all learning activities can contribute to our overall climate footprint. Providers of education should do their best to minimise the carbon footprint associated with their learning. But learners also have responsibility to ensure that how they access learning is also associated with minimal environmental cost. Both providers and learners should focus on activities that are likely to have the greatest impact. This is relevant both to face-to-face education and digital learning.

Cost-effectiveness study of atezolizumab (ATZ) vs. durvalumab (DUR): Real-world data (RWD) on first-line chemotherapy combined with immune-checkpoint inhibitors (Chemo-ICIs) for extensive disease small-cell lung cancer (ED-SCLC).

8097 Background: Chemo-ICI is the standard of care in first-line therapy for ED-SCLC. Although there is no comparative data on ATZ vs. DUR, their efficacies appear to be equivalent based on results from IMpower133 and CASPIAN trials. On the other hand, the drug price of DUR is higher than that of ATZ, suggesting a different cost-effectiveness. Methods: This is a multicenter retrospective study of RWD. Clinical outcomes and safety information of ED-SCLC patients (pts) who had received Chemo-ICIs were collected from electronic medical records, and the total cost incurred during ICIs was obtained from the receipts of each hospital. Propensity score matching (PSM) was performed to adjust difference of pts' backgrounds of two groups (ATZ-G vs. DUR-G). The total monthly medical costs incurred during ICI administration for both groups were compared by cost minimization analysis to evaluate cost-effectiveness. Results: From August 2018 to December 2022, 274 pts (ATZ/DUR: 176/98) were extracted from 8 hospitals in Japan. After PSM and exclusion of cisplatin-treated pts, total 128 pts: 64 pts in each group were evaluated. The mean total medical costs per month during ICIs were 1,003,922 (±310,192) JPY (6,783 USD) in the ATZ-G and 1,596,511 (±371,405) JPY (10,787 USD) in the DUR-G (Wilcoxon rank sum test: p < 0.001). Mean ICI drug costs per month during ICIs were 799,079 (±89,555) JPY (5,399 USD) in the ATZ-G and 1,570,744 (±371,405) JPY (10,163 USD) in the DUR-G (p < 0.001). Response rate was 73.4% for ATZ-G and 75.0% for DUR-G. Median overall survivals (OSs) of ATZ-G vs. DUR-G were 13.9 (95% confidence interval [CI]: 11.7-17.5) vs. 13.6 (95% CI: 11.0-20.0) months, respectively (p = 0.919). Median progression-free survivals of ATZ-G vs. DUR-G were 4.9 (95% CI: 4.4-5.6) vs. 5.6 (95% CI: 5.0-6.7) months, respectively (p = 0.060). Cox-proportional hazard model identified poor performance status (hazard ratio [HR]: 5.5, p < 0.001) and bone metastases (HR: 1.8, p = 0.029) as significant factors for shorter OS, while ATZ vs. DUR was not significant. ATZ-G revealed lower incidences of immune-related adverse events (irAEs) ≥grade 2 (10.9 vs. 31.3%, p = 0.009) and any grade interstitial lung disease (ILD) (3.1 vs. 20.3%, p = 0.004) than DUR-G. Number of hospitalizations in ATZ-G (median 1, range 0-6) was lower than that in DUR-G (median 2, range 0-7) (p = 0.005). Conclusions: Our RWD demonstrated a superior cost-effectiveness of ATZ to that of DUR. Total efficacies were similar, whereas the safety profiles, including irAE and ILD were more favorable in ATZ-G. Further discussion is required regarding not only cost-effectiveness but also clinical practicality such as: dose schedule of 3 weeks vs. 4 weeks; regimen flexibility of carboplatin vs. cisplatin; and etoposide dose adjustment of 100 mg/m2 vs. 80 mg/m2. Clinical trial information: 000053483.

Deep Learning based Efficient Edge Slicing for System Cost Minimization in Wireless Networks

Deep Learning based Efficient Edge Slicing for System Cost Minimization in Wireless Networks

Optimization of multi-integrated energy microgrid scheduling under carbon trading mechanism

Abstract Realizing the power transaction and benefit distribution among multi-integrated energy microgrids with different interests in the system, a multi-microgrid cooperative operation optimization scheduling method under a carbon-trading mechanism is proposed. Considering the microgrid’s electric energy interaction, a model of multi-microgrid cooperation is established. The multi-microgrid cooperative game model is equivalently transformed into two sub-problems, multi-microgrid cooperative operation cost minimization and internal power transaction bargaining, and to solve the two sub-problems successively. The simulation results show that the method is valid.

Machine Learning Enabled Inventory Prediction

Effective inventory management is a critical aspect of business operations, ensuring optimal stock levels, minimizing costs, and meeting customer demand. Accurate inventory prediction plays a pivotal role in achieving these objectives. This project explores the application of the XGBoost algorithm, a powerful machine learning technique, for inventory prediction. XGBoost's ability to handle complex nonlinear relationships and its robust performance make it a promising approach for this task. The project aims to develop an inventory prediction system using the XGBoost algorithm, leveraging historical sales data and other relevant factors to forecast future inventory levels. This project demonstrates the potential of machine learning, specifically the XGBoost algorithm, to revolutionize inventory management practices, enabling businesses to achieve greater efficiency and profitability. Keyword : Machine Learning, Non-linear Relations, Cost Minimization, Stock levels, Profitability, Inventory Prediction.

Factors Associated with Defecation Satisfaction among Japanese Adults with Chronic Constipation.

Background: Constipation causes substantial morbidity worldwide. Methods: This survey assessed constipation-related factors in Japan using the Japanese version of the Irritable Bowel Syndrome Quality of Life (IBS-QOL-J) instrument. We also examined the relationship among laxative type, Bristol Stool Form Scale (BSFS) scores, and treatment cost. Finally, we examined differences in satisfaction scores according to laxative type, treatment type, treatment cost, and BSFS score. Results: IBS-QOL-J was higher among those taking salt and/or irritation laxatives. Those paying >JPY 5000 (USD 50.00) had the lowest IBS-QOL-J. IBS-QOL-J was significantly lower among those with a BSFS score of 1 or 2 (severe constipation). Conclusions: This study's findings suggest that a variety of factors, including treatment type and cost, are associated with defecation satisfaction. Those who had hard stools, used multiple laxatives, or spent more on treatment were less satisfied. Future strategies should target therapies that do not require multiple laxatives with lower treatment costs. Adequate defecation with a small number of appropriate laxatives at minimal cost appears to improve defecation satisfaction. It is desirable to identify appropriate laxatives and improve dietary habits and exercise routines. It is also necessary to stop blindly increasing laxative usage and properly diagnose constipation disorders such as anatomical abnormalities other than functional constipation.