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Ready-mix concrete delivery problem (RMCDP), a specific version of the vehicle routing problem (VRP), is a relevant supply-chain engineering task for construction management with various formulations and solving methods. This problem can range from a simple scenario involving one source, one material and one destination to a more challenging and complex case involving multiple sources, multiple materials and multiple destinations. This paper presents an Internet of Things (IoT)-supported active building information modeling (BIM) system for optimized multi-project ready-mix concrete (RMC) delivery.

The presented system is BIM-based, IoT supported, dynamic and automatic input/output exchange to provide an optimal delivery program for multi-project ready-mix-concrete problem. The input parameters are extracted as real-time map-supported IoT data and transferred to the system via an application programming interface (API) into a mixed-integer linear programming (MILP) optimization model developed to perform the optimization. The obtained optimization results are further integrated into BIM by conventional project management tools. To demonstrate the features of the suggested system, an RMCDP example was applied to solve that included four building sites, seven eligible concrete plants and three necessary RMC mixtures.

The system provides the optimum delivery schedule for multiple RMCs to multiple construction sites, as well as the optimum RMC quantities to be delivered, the quantities from each concrete plant that must be supplied, the best delivery routes, the optimum execution times for each construction site, and the total minimal costs, while also assuring the dynamic transfer of the optimized results back into the portfolio of multiple BIM projects. The system can generate as many solutions as needed by updating the real-time input parameters in terms of change of the routes, unit prices and availability of concrete plants.

The suggested system allows dynamic adjustments during the optimization process, andis adaptable to changes in input data also considering the real-time input data. The system is based on spreadsheets, which are widely used and common tool that most stakeholders already utilize daily, while also providing the possibility to apply a more specialized tool. Based on this, the RMCDP can be solved using both conventional and advanced optimization software, enabling the system to handle even large-scale tasks as necessary.

Introduction: With many new technologies requiring real-time data processing, cloud computing has become challenging to implement due to high bandwidth and high latency requirements.

Purpose: To overcome this issue, edge computing is used to process data at the network’s edge. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed. It is used to process time-sensitive data.

Methodology: The authors implemented the model using Linux Foundation’s open-source platform EdgeX Foundry to create an edge-computing device. The model involved getting data from an on-board sensor (on-board diagnostics (OBD-II)) and the GPS sensor of a car. The data are then observed and computed to the EdgeX server. The single server will send data to serve three real-life internet of things (IoT) use cases: auto insurance, supporting a smart city, and building a personal driving record.

Findings: The main aim of this model is to illustrate how edge computing can improve both latency and bandwidth usage needed for real-world IoT applications.

The production of biohydrogen from rice mill wastes, including rice bran and rice mill effluent by Clostridium acetobutylicum NCIM 2877 was investigated in a batch culture system and optimized the temperature and pH conditions. At 35 °C with initial pH of 5.2 a yield of 55.7±0.8 ml with 88.6 ± 0.3% substrate utilization and at pH 6 the production was 68.7 ± 0.9 ml with 85 ± 1.0 % substrate utilization. Addition of metal ions resulted in better yield and substrate utilization efficiency of the bacteria. FeSO₄.7H₂O at a concentration of 50 mg/l gave 79.7 ± 1.5 ml with 96% of substrate utilization. Cobalt effected the production greatly by giving 96.3 ± 0.9 ml with 95.3 ± 0.7% of substrate utilization whereas Nickel didn’t showed much effective results by giving only a maximum of 74.7 ± 1.5 ml production at 25 mg/l concentration. Conclusively, it can be stated that rice mill wastes can be used as a substrate and use of metal ions will play a key role in the enhancement of biohydrogen production.

A new approach in the field of renewable energy is- the microbial fuel cells (MFCs). It is a technique to produce bioelectricity from available organic waste. It is helpful to fulfill the lighting requirements of rural areas. The aim of our research work is to construct twocompartment system and to study various parameters like performance of the different combination of electrodes, optimization of pH and temperature. In this study, using bacteria as biocatalyst, the naturally found cow dung was used to generate an open circuit voltage of 0.84 ± 0.010 V and a current of 3.51 ± 0.620 mA. Optimization of various parameters shows that among different temperature range, 37°C temperature gives the highest voltage production of 0.84 ± 0.091 V and current of 3.08 ± 0.512 mA. In case of pH there are not any significant changes were found when pH range is changed. Although, pH 4.0 is found to be more efficient as it produces voltage of 0.90 ± 0.045 V and current of 4.85 ± 0.587 mA. Furthermore, three electrogenic bacterial strains were isolated and studied for their electrogenic properties individually and among them CDB-3 was found best in their performance.

The purpose of this paper is to visualize the prioritization among essential factors of cellular manufacturing system (CMS) implementation using the analytic hierarchy process (AHP) and analytic network process (ANP) methods.

Based on literature review, 4 enabler dimensions and 17 CM factors were identified which were validated by experts from academia and industry. Then, AHP and ANP models are proposed in evaluating CMS implementation dimensions and factors. The results are validated using sensitivity analysis.

These models give firms a straightforward and simple to utilize way to deal with CMS efficiently. The two strategies were appeared to be powerful in choosing a strategy for CMS implementation. The two strategies brought about nearly similar outcomes. Both methods consider the particular necessities of the organization through its own accessible ability.

The techniques exhibited in this paper can be utilized by a wide range of organizations for adopting CMS that have a higher impact on performance and thus overall productivity. The two techniques are explained in a step-by-step approach for easier adoption by practitioners.

The strength of the present study is that it is one of the first few to be conducted in perspective for CM implementation factors analysis.

Federation analytics approaches are a present area of study that has already progressed beyond the analysis of metrics and counts. It is possible to acquire aggregated information about on-device data by training machine learning models using federated learning techniques without any of the raw data ever having to leave the devices in the issue. Web browser forensics research has been focused on individual Web browsers or architectural analysis of specific log files rather than on broad topics. This paper aims to propose major tools used for Web browser analysis.

Each kind of Web browser has its own unique set of features. This allows the user to choose their preferred browsers or to check out many browsers at once. If a forensic examiner has access to just one Web browser's log files, he/she makes it difficult to determine which sites a person has visited. The agent must thus be capable of analyzing all currently available Web browsers on a single workstation and doing an integrated study of various Web browsers.

Federated learning has emerged as a training paradigm in such settings. Web browser forensics research in general has focused on certain browsers or the computational modeling of specific log files. Internet users engage in a wide range of activities using an internet browser, such as searching for information and sending e-mails.

It is also essential that the investigator have access to user activity when conducting an inquiry. This data, which may be used to assess information retrieval activities, is very critical. In this paper, the authors purposed a major tool used for Web browser analysis. This study's proposed algorithm is capable of protecting data privacy effectively in real-world experiments.

Digital technologies emerged as innovative avenues for launching new products, advertising brands, increasing customer awareness and thus leaving a remarkable impact on the online marketplace. The present study analyzed the effects of crucial antecedents of AR interactive technology on customers' behavior toward AR-based e-commerce websites.

Convenience sampling was used to collect primary data from 357 iGen respondents aged 16–22 years; residing in New Delhi and the NCR region of India and examined using the structural equation modeling technique.

Results revealed that technology anxiety and virtuality significantly influence customers' attitudes and behavioral intentions toward AR-based e-commerce websites. However, interactivity and innovativeness remain non-significant. Additionally, non-significant moderating effects were identified for the moderators, i.e. trust and need for touch. At the same time, gender has a significant moderating effect only for the association between technology anxiety and attitude toward AR-based e-commerce websites.

The study summarizes numerous theoretical and managerial implications for AR-based website designers and policymakers, followed by the crucial limitations and directions for future research.

The present research provides a significant understanding of the e-commerce industry by providing valuable insights about young iGen consumers' perceptions of AR-based e-commerce websites.

The purpose of this study is to offer a better and more effective hexacopter design for a 3 kg payload using finite element analysis (FEA), facilitating the use of different materials for different components that too without compromising strength.

A 3D computer-aided design (CAD) model of a hexacopter with a regular hexagonal frame is presented. Furthermore, a finite element model is developed to perform a structural analysis and determine Von Mises stress and strain values along with deformations of different components of the proposed hexacopter design.

The results establish that carbon fibre outperforms acrylonitrile butadiene (ABS) with respect to deformations. Within the permissible limits of the stress and strain values, both carbon fiber and ABS are suggested for different components. Thus, a proposed hexacopter offers lighter weight, high strength and low cost.

The use of different materials for different components is suggested by making use of static structural analysis. This encourages new research work and helps in developing new applications of hexacopter, and it has never been reported in literature. The suggested materials for the components of the hexacopter will prove to be suitable considering weight, strength and cost.

The purpose of this paper to standardize the technique for the development of potato flour and to incorporate it in development of the products along with defatted soy flour and maize flour. Also, effect of processing techniques like frying and fermentation on anti‐nutritional content of the products was studied.

The ingredients as well as developed products were analyzed for the macronutrients, viz protein, ash and fat. Also anti‐nutrients like phytic acid, saponin, polyphenols and trypsin inhibitors were estimated by employing standard techniques. Data thus obtained were subjected to analysis of variance according to standard method of statistical analysis.

Potato flour being a versatile ingredient can be easily incorporated in development of various products. Frying and fermentation resulted in decrease of anti‐nutritional factors.

These developed products could be instrumental in alleviating malnutrition as they have high nutritional value and are low in anti‐nutrients.