Assessment of Factors Influencing the Number and Consequences of Electric Scooter Accidents

Problem: E-scooters are a new form of mobility used more frequently in urban environments worldwide. As there is evidence of an increased risk of head injuries, helmets are recommended and (less frequently) legislated. Denmark has enacted mandatory e-scooter helmet use legislation from January 1, 2022. So far, it is unclear how this newly implemented law influenced helmet use of e-scooter riders in Denmark immediately after its implementation. Method: In this observational study, we register and compare e-scooter helmet use before the mandatory helmet use legislation (December 2021) and after (February 2022). As observational survey data collection in the field can be highly time-consuming, we conducted a video-based observation survey. We trained and applied a computer vision algorithm to automatically register e-scooter helmet use in the video data. Results: The trained algorithm produces accurate helmet use data, which does not differ significantly from human-registered helmet use. In applying the algorithm to video data collected in December 2021 and February 2022, we register an overall e-scooter helmet use of 4.4% in n = 1054 riders. Splitting the observation between the time before and after the implementation of the helmet use law reveals a significant increase in helmet use from 1.80% to 5.56%. Discussion: In this study, we successfully train and apply an object detection algorithm to register accurate helmet use data in videos collected in Copenhagen, Denmark. Using this algorithm, we find a significant impact of a new mandatory e-scooter helmet use law on e-scooter riders’ helmet use behavior. Limitations of the study as well as future research needs, are discussed. Practical Applications: Computer vision algorithms can be used for accurate e-scooter helmet assessments. Implementing a mandatory helmet use law can increase helmet use of e-scooters at specific observation sites.

Groundwater resources are essential for drinking water, irrigation, and the economy mainly in semiarid environments where rainfall is limited. Currently, unpredictable rainfall due to climate change and pollution on the Earth’s surface directly affects groundwater resources. In this area, most people depend on groundwater resources for irrigation and drinking purposes, and every summer, most of the area depends on groundwater in a semiarid environment. Hence, we selected two popular methods, the analytical hierarchy process (AHP) and multiple influence factor (MIF) methods, which can be applied to map groundwater potential zones. Nine thematic layers, such as land use and land cover (LULC), geomorphology, soil, drainage density, slope, lineament density, elevation, groundwater level, and geology maps, were selected for this study using remote sensing and geographic information system (GIS) techniques. These layers are integrated in ArcGIS 10.5 software with the help of the AHP and MIF methods. The map of the groundwater potential zones in the study area revealed four classes, i.e., poor, moderate, good, and very good, based on the AHP and MF methods. The groundwater potential zone area is 241.50 (ha) Poor, 285.64 (ha) moderate, 408.31 (ha) good, and 92.75 (ha) very good using the AHP method. Similarly, the MIF method revealed that the groundwater potential classes were divided into four classes: 351.29 (ha) poor, 511.18 (ha), moderate, 123.95 (ha) good, and 41.78 (ha) very good. The results were compared to determine which methods are best for planning water and land resource development in specific areas that have basaltic rock and drought conditions. Both groundwater potential zone maps were validated with water yield data. The receiver operating characteristic (ROC) curve and area under the curve (AUC) model results are found to be 0.80 (good) and 0.93 (excellent) using the MIF and AHP methods, respectively; hence, the AHP method is best for delineation of groundwater potential zone maps and groundwater resource planning. The present study’s framework and the results will be valuable for improving the efficiency of irrigation, conserving rainwater and maintaining the ecosystem in India.

Purpose Drilling of carbon fiber reinforced plastic (CFRP) composite plates with high surface quality are of great importance for assembly operations. The article aims to optimize the drill geometry and cutting parameters to improve the surface quality of CFRP composite material. In this study, CFRP plates were drilled with uncoated carbide drill bits with standard and step geometry. Thus, the effects of standard and step drill bits on surface quality have been examined comparatively. In addition, optimum output parameters were determined by Taguchi, ANOVA and multiple decision-making methods. Design/methodology/approach Drill bit point angles were selected as 90°, 110° and 130°. In cutting parameters, three different cutting speeds (25, 50 and 75 m/min) and three different feeds (0.1, 0.15 and 0.2 mm/rev) were determined. L18 orthogonal sequence was used with Taguchi experimental design. Three important output parameters affecting the surface quality are determined as thrust force, surface roughness and delamination factor. For each output parameter, the effects of drill geometry and cutting parameters were evaluated. Input parameters affecting output parameters were analyzed using the ANOVA method. Output parameters were estimated by creating regression equations. Weights were determined using the analytic hierarchy process (AHP) method, and multiple output parameters were optimized using technique for order preference by Similarity to An ideal solution (TOPSIS). Findings It has been determined from the experimental results that step drills generate smaller thrust forces than standard drills. However, it has been determined that it creates greater surface roughness and delamination factor. From the Taguchi analysis, the optimum input parameters for Fz step tool geometry, 90° point angle, 75 m/min cutting speed and 0.1 mm/rev feed. For Fd, are standard tool geometry, 90° point angle, 25 m/min cutting speed and 0.1 mm/rev feed and for Ra, are standard tool geometry, 130° point angle, 25 m/min cutting speed and 0.1 mm/rev feed. ANOVA analysis determined that the most important parameter on Fd is the tip angle, with 56.33%. The most important parameter on Ra and Fz was found to be 40.53% and 77.06% tool geometry, respectively. As a result of the optimization with multiple criteria decision-making methods, the test order that gave the best surface quality was found as 4–1-9–5-8–17-2–13-6–16-18–15-11–10-3–12-14. The results of the test number 4, which gives the best surface quality, namely, the thrust force is 91.86 N, the surface roughness is 0.75 µm and the delamination factor is 1.043. As a result of experiment number 14, which gave the worst surface quality, the thrust force was 149.88 N, the surface roughness was 3.03 µm and the delamination factor was 1.163. Practical implications Surface quality is an essential parameter in the drilling of CFRP plates. Cutting tool geometry comes first among the parameters affecting this. Therefore, different cutting tool geometries are preferred. A comparison of these cutting tools is discussed in detail. On the other hand, thrust force, delamination factor and surface roughness, which are the output parameters that determine the surface quality, have been optimized using the TOPSIS and AHP method. In this way, this situation, which seems complicated, is presented in a plain and understandable form. Originality/value In the experiments, cutting tools with different geometries are included. Comparatively, its effects on surface quality were examined. The hole damage mechanism affecting the surface quality is discussed in detail. The results were optimized by evaluating Taguchi, ANOVA, TOPSIS and AHP methods together.

PT Vizta Pratama Bengkulu is a branch of a franchise company engaged in family karaoke entertainment services, founded by a well-known dangdut singer, Inul Daratista and starting its first operation in 2005 in Kelapa Gading area. PT. Vizta Pratama Bengkulu has not used the Decision Support System Application. The decision to determine the recipient of the annual bonus is only to calculate the total value based on 3 criteria, namely responsibility, discipline, honesty without using a decision support method, therefore sometimes it is felt that the giving of employee annual bonuses is not right on target. Decision support system for giving annual bonus at PT. Vizta pratama using the analytical hierarchy process (AHP) method is a desktop-based application that has implemented the AHP (Analytical Hierarchy Process) method, this application runs on a Windows operating system created using the Visual Basic .NET programming language and SQL Server 2008r2. This application can be used to assist in the assessment process in determining the annual bonus at PT. Vizta Pratama Bengkulu where this application uses 4 predetermined criteria and then processed using the AHP (Analytical Hierarchy Process) method so as to produce values that will be ranked. Based on the results of the Blackbox testing that has been carried out, it can be concluded that the decision support system for providing annual bonuses at PT. Viztapratama by using the analytical hierarchy process (AHP) method is able to run well and can overcome data input errors by users and the SPK application with the Analytical Hierarchy Process method has provided effective results in accordance with the results of calculations using paired comparisons of 4 criteria where the comparison of pairs of criteria must produce consistent weighting criteria.

Assessment and prioritization of soil erosion triggering factors using analytical hierarchy process and Taguchi method

Supplier selection is one of the most important things in the company's purchasing activities. The selection of suppliers must be done carefully; if done wrong, it can cause disruption to the company's operations. Supplier selection becomes a multi-criteria problem, which includes qualitative and quantitative factors. One method that can be used for supplier selection is the AHP (Analytical Hierarchy Process) method. This research was conducted at a footwear industrial company, PT. Adis Dimension Footwear. The problems found in this research are: Which chemical supplier will be chosen by PT Adis Dimension Footwear based on the AHP method? Then what is the order of priority criteria and sub-criteria in the selection of chemical suppliers at PT. Adis Dimension Footwear? The sample for this research is the decision-makers and the parties who are in the purchasing and warehouse departments and know the performance of suppliers. This study uses the AHP (Analytical Hierarchy Process) method. From the results of the research, the importance of the criteria in supplier selection produces the following weights: The first order is quality criteria with a weighted value of 0.6333. Furthermore, the second rank is the criteria for delivery time with a weight of 0.2605, and the third is the price criteria with a weight of 0.1062. The chemical supplier selected based on research using the AHP method is Grand Chemical, which has a total weight of 0.4285. Asia Chemical Supplier comes in second with a total weight of 0.4093. Binzhou Longfeng Chemical Supplier comes in third place with an overall score. Keywords: Supplier selection, Analytical Hierarchy Process (AHP), footwear industrial, chemical supplier.

In this study, it is aimed to examine the studies based on the AHP (Analytic Hierarchy Process) method in the field of education and to present the researcher's perspective on how to use the AHP method in the field of education. Within the scope of this aim, firstly the AHP method was introduced with a sample application and then the results were interpreted. The other aim of the research; studies which based on the AHP methods in the field of education in the last five years have been examined through content analysis. AHP; is one of the “Multiple Criteria Decision Making (MCDC)” methods that can determine the priority or weights among the criteria and alternatives based on comparative judgments. The content analysis conducted within the scope of the research was carried out in the context of eight criteria determined by the researchers. According to the results of the analysis; the AHP method has shown an increasing tendency compared to the years, and usually is used for determining and prioritizing teaching priorities. Especially in Asia Pacific countries, the AHP method is used much more intensive. Another result is that the AHP method is used to make group decisions rather than individual decisions. It has been seen that the research has been done especially with undergraduate students. In addition to these, there are lots of studies with academicians and experts.

Land transportation infrastructure, such as roads and bridges, plays a crucial role as a link between regions that supports the economic, social, and cultural growth of a region. With limited budget in road management in Pacitan Regency, priority determination is needed to ensure that road management is carried out more efficiently and on target. This study aims to calculate the weight of the criteria using the Analytical Hierarchy Process (AHP) method based on expert opinions and to determine the priority order of road management in Pacitan Regency by utilizing the Provincial/Regency Road Management System (PKRMS) application, the AHP method, and a combination of the two methods. The method used in this study involves AHP with six criteria, namely road conditions, traffic volume, road connectivity, regional development, connecting economic and agricultural areas, and connecting public service facilities. This study focuses on five road sections in Pacitan Regency. The results of the study show that based on the AHP method, the road connectivity criterion gets the highest weight of (35%), followed by connecting public service facilities (22%), road conditions (14%), connecting economic and agricultural areas (13%), regional development (12%), and traffic volume (4%).

With the rapid development of science and technology, new technology is starting to be used in various fields including education. Education has a very important progress in a nation, because it can optimize individual potential. The educational process in higher education has a big influence on a student's future. However, there are many students who experience difficulties in choosing a college major after graduating from vocational high school (SMK) or senior high school (SMA), because of the complexity in identifying the suitability between interests and study programs. Decision making is a problem that everyone faces, especially in choosing an appropriate college major. There are many factors to consider, and with many options available, the decision-making process can be difficult. To overcome this problem, this research aims to create a decision support system (DSS) using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique For Order By Similarity To Ideal Solution) methods. The AHP method is used to solve complex problems by structuring a hierarchy of criteria and developing weights or priorities. However, when the AHP method is used with many criteria and alternatives, other methods are needed for more effective results. Therefore, a combined method of AHP and TOPSIS was chosen, where AHP focuses on pairwise comparison matrices and consistency analysis, while TOPSIS can measure relative performance and alternative decision making simply and efficiently. The results of research on decision support systems for selecting majors using the AHP and TOPSIS methods show that the application of the combined AHP-TOPSIS method can be used to determine the best alternative in selecting majors by comparing alternatives based on predetermined criteria. In addition, system testing results show that the system functions as expected and meets user needs. With a decision support system for selecting college majors implemented on the website, it can simplify the decision-making process for students and BK teachers in choosing college majors. The results of the calculation of the percentage of system feasibility in blackbox testing show a value of 95.71%, which indicates that this major selection decision support system website can be used.

Application and validation of AHP and FR methods for landslide susceptibility mapping around choke mountain, northwestern ethiopia

Scenario‐based test methods are employed to assess the safety and performance of autonomous vehicles. The analytic hierarchy process (AHP) method is a common assessment method for determining the criticality of test scenarios. However, the AHP method is subjective and less reproducible when performed by different persons, as the elements of pairwise comparison values that are directly linked to the outcome must be assigned by the person involved. This paper proposes a novel AHP method that automatically generates pairwise comparison values by optimizing the correlation between performance metrics and risk of test scenarios by simulation. Performance metrics are defined as the minimum relative distances and corresponding relative velocities between vehicles, and the risk of the test scenario is determined by the pairwise comparison values of AHP. The novel AHP method was evaluated using a cut‐in scenario. The results showed that the minimum relative distance and the risk determined by the novel AHP method achieved a better correlation coefficient of −0.96, which is better than the conventional AHP of −0.828 and Fuzzy AHP of −0.824. These results suggest that the criticality of the test scenarios determined by the novel AHP method can more accurately reflect real‐world driving environments.

SD Negeri 12 Central Bengkulu is one of the public elementary schools in Central Bengkulu Regency, Bengkulu Province. At SD Negeri 12 Bengkulu, every academic year an assessment of students is carried out through several criteria to select outstanding students who have the ability to master lessons and good self-ethics. The implementation of Analytical Hierarchy Process (AHP) method in the selection of outstanding students at SD Negeri 12 Central Bengkulu can help provide information in the form of recommendations for selecting outstanding students at school based on the final results of AHP method, and can help homeroom teachers in determining outstanding students by looking at the assessment aspects of report cards, attitude scores, percentage of student attendance, and academic and non-academic achievements obtained by students. From the sample data of student assessments at SD Negeri 12 Central Bengkulu, used for calculations through the Analytical Hierarchy Process (AHP) Method for the 2023/2024 academic year as many as 10 students, the recommended ranking results for outstanding students who are in the top 3 are Daffa Hidayatullah, Aura Despianty, and Ciko Pandu Wiryo. Based on the black box testing that has been carried out, the results show that the functionality of the implementation of Analytical Hierarchy Process (AHP) method in selecting outstanding students at SD Negeri 12 Central Bengkulu runs as expected and the application is able to display the results of recommendations for selecting outstanding students through AHP method stages. Based on the alpha testing, the results obtained that the application is quite interesting and quite helpful in selecting outstanding students in each class at SD Negeri 12 Central Bengkulu.

Although the traumatic injury death rate in the United States decreased during the last 20 years, the percent of all injury deaths attributable to brain injuries has remained steady. Head injuries are a leading cause of injury among motorcycle riders in crashes, and the helmet is an effective measure to reduce these injuries. To reduce the burden and cost of motorcycle injuries, many states have increased helmet use by introducing mandatory helmet legislation. This report presents evidence on the effects of the motorcycle helmet and helmet use legislation--two interrelated prevention strategies which decrease traumatic brain injury among motorcycle riders. Nonfatally injured motorcyclists were included if they crashed between January 1, 1991 and December 31, 1993 and were treated in one of 18 hospitals in 10 California counties. Medical records for all injured motorcyclists admitted to these 18 hospitals and those treated in the emergency department and released in eight of these hospitals were individually reviewed. Complete lists of injury diagnoses for each rider were coded according to the 1990 Abbreviated Injury Severity Scale by trained clinical staff. Before the universal helmet law was introduced (when only a third of injured riders wore helmets) 38.2% of riders sustained head injuries. When helmet use increased to over 85% of injured riders following the law, less than 25% of riders sustained head injuries. Both the severity and the number of head injuries per individual rider decreased after the mandatory helmet use law led to increased helmet use. Riders wearing helmets suffered fewer skull fractures, fewer intracranial injuries, had less frequent and shorter periods of loss of consciousness, more favorable GCS scores, and shorter hospital stays. Mandatory motorcycle helmet use laws are an effective mechanism to increase helmet use among riders and thus prevent head and brain injuries resulting from motorcycle crashes.

Bureau of Student Advisory Center (BSAC) Universitas Pembangunan Panca Budi is a center for career development and character building for students. In this case, a soft skill seminar is conducted to find the best candidate employees in the field of recruitment offered based on the criteria of student soft skill training. Determining the level of soft skill competences of students using the Analytical Hierarchy Process (AHP) method and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). For decision support systems using the AHP and PROMETHEE methods in determining the level of soft skill competencies, in order to obtain prospective employees who have the required soft skill competency level. Data collection was carried out by conducting research. The data is taken from the seminar results with 100 participants. The data that has been collected, processed and analyzed before being used as input and output as a basis for learning or training using the AHP and Promethee methods. Based on the calculations of the two methods, namely the AHP and Promethee methods, there are differences in calculations. In other words, because Promethee does not support the determination of weights and the hierarchy of criteria and does not have the assurance of consistency when determining weights like AHP. So that the program execution has a different time in the results, in the AHP method, program execution until the final result is obtained is better than the Promethee method. AHP has advantages in determining weights and criteria hierarchy, while Promethee has advantages in the alternative ranking process using different preference and weight functions.

BackgroundThe Dharamshala region of Kangra valley, India is one of the fastest developing Himalayan city which is prone to landslide events almost around the year. The development is going on a fast pace which calls for the need of landslide susceptibility zonation studies in order to generate maps that can be used by planners and engineers to implement the projects at safer locations. A landslide inventory was developed for Dharamshala with help of the field observations. Based on field investigations and satellite image studies eight casual factors viz. lithology, soil, slope, aspect, fault buffer, drainage buffer, road buffer and land cover were selected to represent the landslide problems of the study area. The research presents the comparative assessment of geographic information system based landslide susceptibility maps using analytical hierarchy process and frequency ratio method. The maps generated have been validated and evaluated for checking the consistency in spatial classification of susceptibility zones using prediction rate curve, landslide density and error matrix methods.ResultsThe results of analytical hierarchy process (AHP) shows that maximum factor weightage results from lithology and soil i.e. 0.35 and 0.25. The frequency ratios of the factor classes indicate a strong correlation of Dharamsala Group of rock (value is 1.28) with the landslides which also agrees with the results from the AHP method where in the same lithology has the maximum weightage i.e. 0.71. The landslide susceptibility zonation maps from the statistical frequency ratio and heuristic analytical hierarchy process method were classified in to five classes: very low susceptibility, low susceptibility, medium susceptibility, high susceptibility and very high susceptibility. The landslide density distribution in each susceptibility class shows agreement with the field conditions. The prediction rate curve was used for assessing the future landslide prediction efficiency of the susceptibility maps generated. The prediction curves resulted the area under curve values which are 76.77% for analytical hierarchy process and 73.38% for frequency ratio method. The final evaluation of the susceptibility maps was based on the error matrix approach to calculate the area distributed among the susceptibility zones of each map. This technique resulted in assessing the spatial differences and agreement between both the susceptibility maps. The evaluation results show 70% overall spatial similarity between the resultant landslide susceptibility maps.ConclusionsHence it can be concluded that, the landslide susceptibility map (LSM) generated from the AHP and frequency ratio method have yielded good results as the 100% landslide data falls in the high susceptibility and very high susceptibility classes of both the maps. Also, the spatial agreement of almost 70% between the resultant maps increases the reliability on the results in the present study. Therefore, the LSM generated from AHP method with 76.77% landslide prediction efficiency can be used for planning future developmental sites by the area administration.