Innovative Sales Forecasting: Utilizing Fuzzy Neural Networks for Enhanced Sales Prediction

This study aims to improve retail sales forecasting using fuzzy neural networks (FNNs). Traditional methods often miss complex sales patterns. We use accuracy and loss metrics to apply FNNs to the Walmart sales dataset, comparing them to conventional time series models and advanced techniques like LightGBM and LSTM. Comprehensive data preprocessing ensures data quality. FNNs handle uncertainties and complex relationships better, outperforming traditional methods. The findings suggest that FNNs enhance forecasting accuracy, supporting informed decision-making in retail

Biological Denitrification of High Nitrate Processing Wastewaters from Explosives Production Plant

Wastewater samples originating from an explosives production plant (3,000 mg N l−1 nitrate, 4.8 mg l−1 nitroglycerin, 1.9 mg l−1 nitroglycol and 1,200 mg l−1 chemical oxygen demand) were subjected to biological purification. An attempt to completely remove nitrate and to decrease the chemical oxygen demand was carried out under anaerobic conditions. A soil isolated microbial consortium capable of biodegrading various organic compounds and reduce nitrate to atmospheric nitrogen under anaerobic conditions was used. Complete removal of nitrates with simultaneous elimination of nitroglycerin and ethylene glycol dinitrate (nitroglycol) was achieved as a result of the conducted research. Specific nitrate reduction rate was estimated at 12.3 mg N g−1 VSS h−1. Toxicity of wastewater samples during the denitrification process was studied by measuring the activity of dehydrogenases in the activated sludge. Mutagenicity was determined by employing the Ames test. The maximum mutagenic activity did not exceed 0.5. The obtained results suggest that the studied wastewater samples did not exhibit mutagenic properties

Digital technology for digital supply chain : the clusters identification

PURPOSE: On the basis of the conducted research global trends that relate to technological support (digital technologies, DT) for the Digital Supply Chain were identified. It resulted in the creation of a set of eight key non-one-directional technological support trends. The goal is of cognitive and conceptual character.DESIGN/METHODOLOGY/APPROACH: The research implemented benefits from the text mining method and cluster analysis using genetic algorithms. Made it possible to identify conceptual clusters by singling out a group of similar objects which coexist intensively.FINDINGS: The use of digital technologies in supply chains will be essential to ensure even and faster global recovery. Over the next three years, we are expected to experience various types of economic turbulence, supply chain disruptions, and unforeseen events. It is clear that neither resilience nor governance will be possible without reliable and advanced digital technologies.PRACTICAL IMPLICATIONS: In the near future, digitization will play an even greater role in the operation of supply chains. It will increase the information transparency of supply chains and increase the resilience of supply chains.ORIGINALITY/VALUE: The article indicates the directions of research and works on digital technologies and digitization in the coming years in Digital Supply Chains.This research was funded by the Poznan University of Technology, grant number 0812/SBAD/4204.peer-reviewe

Sources of information about suppliers used in purchasing processes on the B2B market

PURPOSE: The purpose of this article was to identify the sources of information regarding suppliers most often used by manufacturing companies and to define their importance.DESIGN/METHODOLOGY/APPROACH: The considerations based on the analysis of the literature and the results of empirical research indicate that enterprises use both direct forms (such as sales representatives, recommendations of other clients, fairs and exhibitions) and on-line forms (such as suppliers' websites). Specialized industry as sources of information about suppliers. portals as a source of information about suppliers. The thesis is confirmed by the results of empirical research conducted with the computer-assisted telephone interviewing (CATI) technique in medium and large manufacturing companies operating in Poland.FINDINGS: The results of the conducted research indicate that the sources of information concerning new suppliers most frequently indicated by the surveyed companies are visits of sales representatives of suppliers sending the offer by suppliers, suppliers' websites, direct contacts of the management/specialists employed in the enterprise with suppliers, recommendations of other companies and fairs and exhibitions. The results of the conducted research also indicate that for manufacturers the most important sources of information about suppliers were: suppliers' websites, sending the offer by suppliers, direct contacts of the management / specialists employed in the enterprise with suppliers and the visits of sales representatives of suppliers.PRACTICAL IMPLICATIONS: The considerations based on the analysis of the literature and the results of empirical research indicate that both direct forms (such as sales representatives, recommendations of other clients, fairs and exhibitions) and electronic on-line forms of contact (such as suppliers' websites, specialized industry portals) play an important role in the B2B market as sources of information about suppliers.ORIGINALITY/VALUE: Research on sources of information about suppliers used in purchasing processes on the B2B market is undertaken very rarely. Therefore, the results of studies presented in this article fill the research gap.peer-reviewe

The relationship between the level of choosing competences of operational employees and the acceptance of work in an automated warehouse

PURPOSE: The aim of the paper is to determine the relationship between the level of employees' competences in the field of ability to use interfaces, adaptability and flexibility, creativity / initiative, critical thinking, laying out logical structures, quick response to change in the process, spatial imagination / orientation in space and their level of acceptance of work in an automated environment interpreted on the basis of the degree of their interest in work and cooperation with technology.DESIGN/METHODOLOGY/APPROACH: The research model and research constructs were developed on the basis of the survey results. Employees completing the questionnaire made a self-assessment in terms of the level of their competence and interest in technology. To test the research model and proposed hypothesis, this study applies Partial Least Squares Path Modelling (PLS), a variance-based structural equation modelling technique (SEM) that aims to maximise the explained variance of the dependent latent constructs. SmartPLS version 3 was used to analyze the data in this study following a two-step analysis approach.FINDINGS: The level of acceptance of work in an automated environment depends on the level of competence, the ability to use interfaces and Quick of response to change in the process. People with a higher level of these competencies also show a higher interest in technology and its use both in private and professional life. These people are also characterized by a higher level of acceptance of work in an automated environment.PRACTICAL IMPLICATIONS: The conducted research made it possible to identify the relationship between employees' competencies and the degree of their acceptance of work in an automated environment. Thanks to the results, it is possible to identify whether the employee will feel comfortable working in an automated environment or not.ORIGINALITY/VALUE: Thanks to the identification of the relationship between competencies, there is no need to test all, but only selected ones, which will greatly facilitate the diagnosis.peer-reviewe

Screening and Identification of Trichoderma Strains Isolated from Natural Habitats with Potential to Cellulose and Xylan Degrading Enzymes Production

A total of 123 Trichoderma strains were isolated from different habitats and tested for their ability to degrade cellulose and xylan by simple plate screening method. Among strains, more than 34 and 45% respectively, exhibited higher cellulolytic and xylanolytic activity, compared to the reference strain T. reesei QM 9414. For strains efficiently degrading cellulose, a highest enzyme activity was confirmed using filter paper test, and it resulted in a range from 1.01 to 7.15 FPU/ml. Based on morphological and molecular analysis, the isolates were identified as Trichoderma. The most frequently identified strains belonged to Trichoderma harzianum species. Among all strains, the most effective in degradation of cellulose and xylose was T. harzianum and T. virens, especially those isolated from forest wood, forest soil or garden and mushroom compost. The results of this work confirmed that numerous strains from the Trichoderma species have high cellulose and xylan degradation potential and could be useful for lignocellulose biomass conversion e.g. for biofuel production

Not Just a Pot: Visual Episodic Memory in Cannabis Users and Polydrug Cannabis Users: ROC and ERP Preliminary Investigation

Background While research has consistently identified an association between long-term cannabis use and memory impairments, few studies have examined this relationship in a polydrug context (i.e., when combining cannabis with other substances).Aims: In this preliminary study, we used event-related potentials to examine the recognition process in a visual episodic memory task in cannabis users (CU) and cannabis polydrug users (PU). We hypothesized that CU and PU will have both–behavioral and psychophysiological–indicators of memory processes affected, compared to matched non-using controls with the PU expressing more severe changes.Methods 29 non-using controls (CG), 24 CU and 27 PU were enrolled into the study. All participants completed a visual learning recognition task while brain electrical activity was recorded. Event-related potentials were calculated for familiar (old) and new images from a signal recorded during a subsequent recognition test. We used receiver operating characteristic curves for behavioral data analysis.Results The groups did not differ in memory performance based on receiver operating characteristic method in accuracy and discriminability indicators nor mean reaction times for old/new images. The frontal old/new effect expected from prior research was observed for all participants, while a parietal old/new effect was not observed. While, the significant differences in the late parietal component (LPC) amplitude was observed between CG and PU but not between CG and CU nor CU and PU. Linear regression analysis was used to examine the mean amplitude of the LPC component as a predictor of memory performance accuracy indicator. LPC amplitude predicts recognition accuracy only in the CG.Conclusion The results showed alterations in recognition memory processing in CU and PU groups compared to CG, which were not manifested on the behavioral level, and were the most prominent in cannabis polydrug users. We interpret it as a manifestation of the cumulative effect of multiple drug usage in the PU group