Predicting Purchasing Behavior on E-Commerce Platforms: A Regression Model Approach for Understanding User Features that Lead to Purchasing

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.

An updated inventory of marine opisthobranch(Mollusca,Gastropoda)from the territorial waters of the Republic of Mauritius

Island ecosystems support diverse aquatic invertebrate communities comprising endemic taxa.Documentation of existing species is important for conservation.In this study,a checklist of marine opisthobranch from the Republic of Mauritius is presented.A combination of benthic surveys(50 m×5 m in triplicates),rover diving techniques and photo documentation were used over two years(2018–2020)within 35 sheltered and unsheltered lagoons.Morphological and molecular analysis were used for identification.Species composition within sheltered and unsheltered areas in Mauritius was estimated using the Bray-Curtis similarity.The checklist featured 117 species belonging to 61 genera and 28families,of which 13 are new records.The findings increased the knowledge of opisthobranch diversity from the Mauritius by 15.4%.Among the listed species,the distribution range of Cyerce nigra,Actinocyclus papillatus,and Phyllidia picta extended from the Western Pacific to the South Western Indian Ocean.Molecular analysis of the undescribed Gymnodoris sp.showed it resembled Gymnodoris sp.from Hawaii and were different by a genetic distance value of 10.6%.The species richness and evenness were higher within the sheltered regions of Mauritius which harboured the food resource of opisthobranch.These areas as compared to unsheltered regions were heavily populated,suggesting the probable influence of wave actions on opisthobranch diversity and abundance.The order Nudibranchia was reported as most speciose,with 86 species.The Sacoglossa and Nudibranchia were observed only on macroalgae and sponges respectively.High abundance was also recorded on shipwrecks which are the most common form of artificial reefs.With the inclusion of observations from previous studies,201species belonging to 94 genera and 36 families are now known from the Mauritius.

Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology

This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.

A Note on an Order Level Inventory Model with Varying Two-Phased Demand and Time-Proportional Deterioration

The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.

An open-accessed inventory of landslides triggered by the M_(S)6.8 Luding earthquake,China on September 5,2022

This study constructs a preliminary inventory of landslides triggered by the M_(S) 6.8 Luding earthquake based on field investigation and human-computer interaction visual interpretation on optical satellite images.The results show that this earthquake triggered at least 5007 landslides,with a total landslide area of 17.36 km^(2),of which the smallest landslide area is 65 m^(2)and the largest landslide area reaches 120747 m^(2),with an average landslide area of about 3500 m^(2).The obtained landslides are concentrated in the IX intensity zone and the northeast side of the seismogenic fault,and the area density and point density of landslides are 13.8%,and 35.73 km^(-2) peaks with 2 km as the search radius.It should be noted that the number of landslides obtained in this paper will be lower than the actual situation because some areas are covered by clouds and there are no available post-earthquake remote sensing images.Based on the available post-earthquake remote sensing images,the number of landslides triggered by this earthquake is roughly estimated to be up to 10000.This study can be used to support further research on the distribution pattern and risk evaluation of the coseismic landslides in the region,and the prevention and control of landslide hazards in the seismic area.

Spatial distribution and inventory of natural gas hydrate in the Qiongdongnan Basin,northern South China Sea

Natural gas hydrate is a potential clean energy source and is related to submarine geohazard,climate change,and global carbon cycle.Multidisciplinary investigations have revealed the occurrence of hydrate in the Qiongdongnan Basin,northern South China Sea.However,the spatial distribution,controlling factors,and favorable areas are not well defined.Here we use the available high-resolution seismic lines,well logging,and heat flow data to explore the issues by calculating the thickness of gas hydrate stability zone(GHSZ)and estimating the inventory.Results show that the GHSZ thickness ranges between mostly~200 and 400 m at water depths>500 m.The gas hydrate inventory is~6.5×109-t carbon over an area of~6×104 km2.Three areas including the lower uplift to the south of the Lingshui sub-basin,the Songnan and Baodao sub-basins,and the Changchang sub-basin have a thick GHSZ of~250-310 m,250-330 m,and 350-400 m,respectively,where water depths are~1000-1600 m,1000-2000 m,and2400-3000 m,respectively.In these deep waters,bottom water temperatures vary slightly from~4 to 2℃.However,heat flow increases significantly with water depth and reaches the highest value of~80-100 mW/m2 in the deepest water area of Changchang sub-basin.High heat flow tends to reduce GHSZ thickness,but the thickest GHSZ still occurs in the Changchang sub-basin,highlighting the role of water depth in controlling GHSZ.The lower uplift to the south of the Lingshui sub-basin has high deposition rate(~270-830 m/Ma in 1.8-0 Ma);the thick Cenozoic sediment,rich biogenic and thermogenic gas supplies,and excellent transport systems(faults,diapirs,and gas chimneys)enables it a promising area of hydrate accumulation,from which hydrate-related bottom simulating reflectors,gas chimneys,and active cold seeps were widely revealed.

Screening Tree Species for Carbon Storage Potential through Urban Tree Inventory in Planted Vegetation

Urban tree inventory is a great tool for gathering data that can be used by different end users. This study attempted to chart the species diversity in planted areas and measure their tree diameter at breast height to screen them for the carbon storage potential. A total of 2860 trees belonging to 36 species were recorded in the planted vegetation in parks and avenue plantation. The dominant species were Azadirachta indicia (25.5%), Conocarpus erectus (19.2%), Ficus spp. (15.5%), Tabebuia rosea (9.2%), Peitophorum pterocarpum (9.0%) and the remaining represents (21.6%) of the tree identified in this study. It was found that the highest contribution of carbon sequestration (CO2 equivalent) is dominated by the Ficus spp. (30.3%) with a total of 3399.3 tCO2eq, followed by Azadirachta indicia (25.4%) with a total of 2845.2 tCO2eq and Conocarpus erectus (20.4%) with a total of 2286 tCO2eq. The entire area has the capability to sequester around 11,213.3 tCO2eq and on average of 3.9 ± 0.1 tCO2eq. In accordance with the findings, it is imperative for the preservation of a sustainable environment to have vegetation that has the capacity to store carbon. The study suggests, there is potential to increase carbon sequestration in urban cities through plantation programs on existing and new land uses and along roads.

YKK achieves 100% renewable energy purchasing at 31 sites worldwide

YKK Corporation announces that the number of YKK locations that have switched 100%of their electricity consumption to renewable energy in fiscal year 2022 has increased by 20 locations from FY2021 to FY2022,reaching 31 locations globally.

The national forest inventory in China:history-results-international context

Background： National forest resource assessments Inventories （NFI＇s）, constitute an important nationa and monitoring, commonly known as National Forest information infrastructure in many countries. Methods： This study presents details about developments of the NFI in China, including sampling and plot design and the uses of alternative data sources, and specifically · reviews the evolution of the national forest inventory in China through the 20th and 21st centuries, with some reference to Europe and the US; · highlights the emergence of some common international themes： consistency of measurement; sampling designs; implementation of improved technology; expansion of the variables monitored more efficient scientific transparency;· presents an example of how China＇s expanding NFI exemplifies these global trends. Results： Main results and important changes in China＇s NFI are documented, both to support continued trend analysis and to provide data users with historical perspective. Conclusions： New technologies and data needs ensure that the Chinese NFI, like the national inventories in other countries, will continue to evolve. Within the context of historical change and current conditions, likely directions for this evolution are suggested.

Optimization purchase price and the profit policy undervendor managed inventory

The optimization policy of the purchase price and the profit under vendor managed inventory(VMI) is studied. For a salable product, supply chain mode of VMI is established, which is based on deterministic demand, having initial stock and having stock-out cost. With the further analysis of the mode, VMI is found to increase profits of the buyer in the short-term motivation. But VMI will reduce profits of the supplier under the matching condition. And in the short-term motivation, VMI will increase the purchase price to compensate the transfer cost of the supplier. As a result, the foundation of theory is provided to implement VMI in the supply chain, and have some definituded project significance.

A biogenic volatile organic compounds emission inventory for Yunnan Province

The first detailed inventory for volatile organic compounds(VOC) emissions from vegetation over Yunnan Province, China was presented. The spatially and temporally resolved inventory was developed based on a geographic information system(GIS), remote sensing(RS) data and field measurement data, such as digitized land-use data, normalized difference vegetation index(NDVI) and temperature data from direct real-time measurement. The inventory has a spatial resolution of 5 km×5 km and a time resolution of 1 h. Urban, agriculture, and natural land-use distributions in Yunnan Province were combined with biomass factors for each land-use category to produce a spatially resolved biomass inventory. A biogenic emission inventory was developed by combining the biomass inventory with hourly emission rates for tree, shrub and ground cover species of the study area. Correcting for environmental factors, including light intensity and temperature, a value of 1.1×10 12 gC for total annual biogenic VOC emissions from Yunnan Province, including 6.1×10 11 gC for isoprene, 2.1×10 11 gC for monoterpenes, and 2.6×10 11 gC for OVOC was obtained. The highest VOC emissions occurred in the northwestern, southwestern and north region of Yunnan Province. Some uncertainties were also discussed in this study.

The inventory of the carbon stocks in sub tropical forests of Pakistanfor reporting under Kyoto Protocol

The United Nations Framework Convention on Climate Change （UNFCCC） requires reporting net carbon stock changes and anthropogenic greenhouse gas emissions, including those related to forests. This paper describes the status of carbon stocks in sub tropical forests of Pakistan. There are two major sub types in subtropical forests of Pakistan viz a viz Subtropical Chir Pine and Subtropical broadleaved forests. A network of sample plots was laid out in four selected site. Two sites were selected from sub tropical Chir Pine （Pinus roxburghii） forests and two from Subtropical broadleaved forests. Measurement and data acquisition protocols were developed specifically for the inventory car- ried out from 2005 to 2010. In total 261 plots （each of lha.） were established. Estimation of diameter, basal area, height, volume and biomass was carried out to estimate carbon stocks in each of the four carbon pools of above- and below-ground live biomass. Soil carbon stocks were also determined by doing soil sampling. In mature （-100 years old） pine forest stand at Ghoragali and Lehterar sites, a mean basal area of 30.38 and 26.11 m2.ha-1 represented mean volume of 243 and 197 m3·ha-1, respectively. The average biomass （t.ha-1） was 237 in Ghoragali site and 186 tha-1 in Lehterar site, which is equal to 128 and 100 t·ha-1 including soil C. However, on average basis both the forests have 114.5± 2.26 t.ha-1 of carbon stock which comprises of 92% in tree biomass and only 8% in the top soils. In mixed broadleaved evergreen forests a mean basal area （m2.ha-1）was 3.06 at Kherimurat with stem volume of 12.86 and 2.65 at Sohawa with stem volume of 11.40 m3.ha-1. The average upper and under storey biomass （t·ha-1） was 50.93 in Kherimurat site and 40.43 t.ha-1 in Sohawa site, which is equal to 31.18 and 24.36 t ·ha-1 including soil C stocks. This study provides a protocol monitoring biomass and carbon stocks and valuable baseline data for in Pakistan＇s managed and unmanaged sub-tropical forests.

Preparation of earthquake-triggered landslide inventory maps using remote sensing and GIS technologies:Principles and case studies

Inventory maps of earthquake-triggered landslides can be constructed using several methods,which are often subject to obvious differences due to lack of commonly accepted criteria or principles,To solve this problem,the author describes the principles for preparing inventory maps of earthquake-triggered landslides,focusing on varied methods and their criteria,The principles include the following key points：all landslides should be mapped as long as they can be recognized from images;both the boundary and source area position of landslides should be mapped;spatial distribution pattern of earthquake-triggered landslides should be continuous;complex landslides should be divided into distinct groups;three types of errors such as precision of the location and boundary of landslides,false positive errors,and false negative errors of earthquake-triggered landslide inventories should be controlled and reduced;and inventories of co-seismic landslides should be constructed by the visual interpretation method rather than automatic extraction of satellite images or/and aerial photographs,In addition,selection of remote sensing images and creation of landslides attribute database are also discussed in this paper,Then the author applies these principles to produce inventory maps of four events：the 12 May 2008 Wenchuan,China M_w 7.9,14 April 2010 Yushu,China M_w 6,9,12 January 2010 Haiti M_w7.0,and 2007 Aysen Fjord,Chile M_w 6.2,The results show obvious differences in comparison with previous studies by other researchers,which again attest to the necessity of establishment of unified principles for preparation of inventory maps of earthquake-triggered landslides.

Purchasing Behaviour of University Students towards Cyber Shopping in Hong Kong

The developments of Internet and e-commerce provide a new market place to businessman to sell their products and allow people to buy products via Internet as well as to create a new shopping media to consumers. The study aims to investigate the factors affecting consumers' purchase decision via Internet and how product characteristics affect cyber shopping in Hong Kong. The study has revealed that the security of personal data,delivery time, product brand and price were the major concerns for developing cyber market. For marketing apparel products, brand loyalty becomes very important since consumers' judging confidence on the products can be increased in terms of fitting standards and quality aspects.

Quantifying forest structural diversity based on large-scale inventory data:a new approach to support biodiversity monitoring

Background: The importance of structurally diverse forests for the conservation of biodiversity and provision of a wide range of ecosystem services has been widely recognised. However, tools to quantify structural diversity of forests in an objective and quantitative way across many forest types and sites are still needed, for example to support biodiversity monitoring. The existing approaches to quantify forest structural diversity are based on small geographical regions or single forest types, typically using only small data sets.Results: Here we developed an index of structural diversity based on National Forest Inventory(NFI) data of BadenWurttemberg, Germany, a state with 1.3 million ha of diverse forest types in different ownerships. Based on a literature review, 11 aspects of structural diversity were identified a priori as crucially important to describe structural diversity. An initial comprehensive list of 52 variables derived from National Forest Inventory(NFI) data related to structural diversity was reduced by applying five selection criteria to arrive at one variable for each aspect of structural diversity. These variables comprise 1) quadratic mean diameter at breast height(DBH), 2) standard deviation of DBH, 3) standard deviation of stand height, 4) number of decay classes, 5) bark-diversity index, 6) trees with DBH ≥ 40 cm, 7) diversity of flowering and fructification, 8) average mean diameter of downed deadwood, 9) mean DBH of standing deadwood, 10) tree species richness and 11) tree species richness in the regeneration layer. These variables were combined into a simple,additive index to quantify the level of structural diversity, which assumes values between 0 and 1. We applied this index in an exemplary way to broad forest categories and ownerships to assess its feasibility to analyse structural diversity in large-scale forest inventories.Conclusions: The forest structure index presented here can be derived in a similar way from standard inventory variables for most other large-scale forest inventories to provide important information about biodiversity relevant forest conditions and thus provide an evidence-base for forest management and planning as well as reporting.

Optimal plot design in a multipurpose forest inventory

Background： We explore the factors affecting the optimal plot design （size and type as well as the subsample tree selection strategies within a plot） and their relative importance in defining the optimal plot design in amultipurpose forest inventory. The factors include time used to lay out the plot and to make the tree measurements within the plot, the between-plot variation of each of the variables of interest in the area, and the measurement and model errors for the different variables. Methods： We simulate different plot types and sizes and subsample tree selection strategies on measuredtest areas from North Lapland. The plot types used are fixed-radius, concentric and relascope plots. Weselect the optimal type and size first at plot level using a cost-plus-loss approach and then at cluster level byminimizing the weighted standard error with fixed budget. Results： As relascope plots are ve~/efficient at the plot level for volume and basal area, and fixed-radius plots for stems per ha, the optimal plot type strongly depends on the relative importance of these variables. The concentric plot seems to be a good compromise between these two in many cases. The subsample tree selection strategy was more important in selecting optimal plot than many other factors. In cluster level, the most important factor is the transfer time between plots. Conclusions： While the optimal radius of plots and other parameters were sensitive to the measurement times and other cost factors, the concentric plot type was optimal in almost all studied cases. Subsample tree measurement strategies need further studies, as they were an important cost factor. However, their importance to the precision was not as clear.

Mapping aboveground biomass by integrating geospatial and forest inventory data through a k-nearest neighbor strategy in North Central Mexico

As climate change negotiations progress,monitoring biomass and carbon stocks is becoming an important part of the current forest research.Therefore,national governments are interested in developing forest-monitoring strategies using geospatial technology.Among statistical methods for mapping biomass,there is a nonparametric approach called k-nearest neighbor(kNN).We compared four variations of distance metrics of the kNN for the spatially-explicit estimation of aboveground biomass in a portion of the Mexican north border of the intertropical zone.Satellite derived,climatic,and topographic predictor variables were combined with the Mexican National Forest Inventory(NFI)data to accomplish the purpose.Performance of distance metrics applied into the kNN algorithm was evaluated using a cross validation leave-one-out technique.The results indicate that the Most Similar Neighbor(MSN)approach maximizes the correlation between predictor and response variables(r=0.9).Our results are in agreement with those reported in the literature.These findings confirm the predictive potential of the MSN approach for mapping forest variables at pixel level under the policy of Reducing Emission from Deforestation and Forest Degradation(REDD+).

Mapping forest age using National Forest Inventory,airborne laser scanning,and Sentinel-2 data

Background:The age of forest stands is critical information for forest management and conservation,for example for growth modelling,timing of management activities and harvesting,or decisions about protection areas.However,area-wide information about forest stand age often does not exist.In this study,we developed regression models for large-scale area-wide prediction of age in Norwegian forests.For model development we used more than 4800 plots of the Norwegian National Forest Inventory(NFI)distributed over Norway between latitudes 58°and 65°N in an 18.2 Mha study area.Predictor variables were based on airborne laser scanning(ALS),Sentinel-2,and existing public map data.We performed model validation on an independent data set consisting of 63 spruce stands with known age.Results:The best modelling strategy was to fit independent linear regression models to each observed site index(SI)level and using a SI prediction map in the application of the models.The most important predictor variable was an upper percentile of the ALS heights,and root mean squared errors(RMSEs)ranged between 3 and 31 years(6%to 26%)for SI-specific models,and 21 years(25%)on average.Mean deviance(MD)ranged between^(−1) and 3 years.The models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 years.Using a mapped SI,which is required for practical applications,RMSE and MD on plot level ranged from 19 to 56 years(29%to 53%),and 5 to 37 years(5%to 31%),respectively.For the validation stands,the RMSE and MD were 12(22%)and 2 years(3%),respectively.Conclusions:Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing age.Overall,we obtained good results,especially for stands with high SI.The models could be considered for practical applications,although we see considerable potential for improvements if better SI maps were available.

Supply Chain for Regional Centralized Purchasing: An Application Model

In Europe Health Organizations are progressively modifying their management models to rationalize expenditure in order to assure better levels of effectiveness and efficiency: many countries are going to centralize the management of goods and services supply. In this paper a specific model of centralized purchasing is proposed;it is particularly suitable in cases of severe economy suffering at regional level (e.g. Campania, Lazio, Calabria in Italy) or at national level (e.g. Greece, Ireland, Italy), that means in all those cases where the scale economies, obtainable by supply centralization, would be partly or totally compromised by the extra charges induced by the missing of contractual commitments. This work aims either to analyse such specific approach for centralized purchasing or to propose a simulation model based on Petri net, which could be useful for designing and managing similar case studies.

Study on Low-carbon City Planning Strategies Based on Urban Greenhouse Gas Inventory

From the perspective of urban greenhouse gas inventory, this paper analyzed the composition and tendency of urban greenhouse gas inventory of Guangzhou, and compared greenhouse gas inventory of representative international cities. Taking Guangzhou Haizhu Eco-city for example, this paper from the perspective of urban-rural planning put forward the low-carbon development paths and strategies such as increasing carbon sink, industrial transformation, spatial restructuring, traffic organization, green civil engineering and resource utilization, and green building for the main carbon-emitting fields such as industry, energy supply, transport, building and waste disposal.