Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

Optimization of the Water Distribution Networks with Differential Evolution (DE) and Mixed Integer Linear Programming (MILP)

Nowadays, due to increasing population and water shortage and competition for its consumption, especially in the agriculture, which is the largest consumer of water, proper and suitable utilization and optimal use of water resources is essential. One of the important parameters in agriculture field is water distribution network. In this research, differential evolution algorithm (DE) was used to optimize Ismail Abad water supply network. This network is pressurized network and includes 19 pipes and 18 nodes. Optimization of the network has been evaluated by developing an optimization model based on DE algorithm in MATLAB and the dynamic connection with EPANET software for network hydraulic calculation. The developing model was run for the scale factor (F), the crossover constant (Cr), initial population (N) and the number of generations (G) and was identified best adeptness for DE algorithm is 0.6, 0.5, 100 and 200 for F and Cr, N and G, respectively. The optimal solution was compared with the classical empirical method and results showed that implementation cost of the network by DE algorithm was 10.66% lower than the classical empirical method.

Hydrogen production from methane and carbon dioxide mixture using all-solid-state electrochemical cell based on a proton-conducting membrane and redox-robust composite electrodes

In recent years, interest in hydrogen as a fuel has sharply increased in the field of alternative and green energy due to its high energy capability and zero-emission behaviour. As a result, research in the development of new highly efficient methods for producing high-purity hydrogen is relevant. This paper presents, for the first time, the test results of an electrochemical cell with a proton-conducting La_(0.9)Sr_(0.1)ScO_(3-δ) electrolyte and symmetrical Sr_(1.95)Fe_(1.4)Ni_(0.1)Mo_(0.5)O_(6-δ)+ La_(0.9)Sr_(0.1)Sc_(0.9)Co_(0.1)O_(3-δ) electrodes as a hybrid setup for electricity generation in proton ceramic fuel cell mode, for hydrogen separation from H_(2)+ Ar mixture and the production of high-purity hydrogen from methane with simultaneous CO_(2) utilization.It was found that this electrochemical cell generates high flow rates of hydrogen during its separation through a proton-conducting membrane from H_(2)+ Ar mixture, about 500 cm^(3)h^(-1)cm^(-2)at a current density of 0.6 A cm^(-2)as well as about 370 cm^(3) h^(-1)cm^(-2)at a current density of 0.5 A cm^(-2) from CH_(4)+ CO_(2) mixture at 800 ℃ which shows that these cells are promising for hydrogen production.

Factors Explaining the Dynamics of Agricultural Technological Innovations Adoption: Evidence from Senegal’s Rain Maize Farmer

This paper analyzes the adoption dynamics of improved rainfed maize seeds disseminated in Senegal in 2013 by the West African Agricultural Productivity Program (WAAPP). We group maize producers into five groups (non-adopters, laggards/abandoners, late adopters, followers and pioneers/innovators) and take into account the heterogeneity of unobservable characteristics of the producers. In the pioneers/innovators group, the availability of labour, household size, shocks, and frequency of access to advice positively influence adoption, whereas financial constraints and high numbers of plots reduce the probability of adoption. Producers in the followers’ category tend to be older and more educated than those in the other categories. However, food insecurity and shocks such as diseases hamper adoption. For the group of late adopters, household size and available storage infrastructures explain adoption. However, the number of plots and shocks reduces their probability of adoption. Laggards tend to face shocks and food insecurity. The authors recommend to consider the dynamics of the adoption of technological innovations and heterogeneity of the characteristics of adopters groups in future research. They also recommend farmers to increase their adoption rate of the “Early Thai” and “Suwan 1” seed varieties thanks to their higher yields compared to traditional varieties. Also, a higher adoption rate would positively impact the food security of maize farmers in Eastern Senegal and High Casamance, especially in terms of availability. Other studies measuring the number of years needed for large-scale adoption of improved seed varieties should be conducted.

Which Aspects of Big Data Usage is Creating Information Security Concern?

The present research study proposed some of the big data usage perspectives for testing either they have a role in creating information security concern or not.The researchers first dig out some of the theoretical support for filling the gap regarding big data and information security bridge that was previously noted in literature.The present researches approached big data analytics manager in the Pakistani banking industries for validating the proposed model.The data were analyzed using SPSS Andrews approach due to the nature of the research study.The findings revealed that the proposed perspective including perceived benefits,cloud storage,and online behavior monitoring should be tested in the future studies by proposing their indirect affect in the creation of information security issue.The study brings a new aspect in literature of management regarding big data usage practices.

Strategic Analysis and Choice for Forestry Enterprises Developing E-business

Forestry industry is an important commonweal and fundamental industry. Forestry enterprises take the burden of ecological construction and supply of forest products, and economical benefits, ecological benefits, and social benefits as well. However, electronic-business (e-business), as a completely new business operation model, will bring great opportunities and challenges to forestry enterprises. On the basis of simple analysis of e-business conception model, the internal and external environment for forestry enterprises to develop e-business was thoroughly analysed and researched , and finally effective strategic options were proposed.

Research on Comprehensive Evaluation of Financial Innovation Ability of the National-Level New Areas Based on Grey Correlation

On the basis of setting up an evaluation index system of financial innovation ability and using the grey systems theory and the coefficient variation method, the article has proposed a synthetic evaluation method with grey correlation. Through evaluating the ability of financial innovation of the national-level new areas comprehensively, the article has offered reliable suggestions to adjust regional economic structure and make financial policy.