基于Vue开发的大学生防诈骗交互式课件系统源码+sql数据库+项目使用说明.zip

package com.mossflower.antifraud.admin.service.impl; import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper; import com.mossflower.antifraud.admin.service.AdminPortraitService; import com.mossflower.antifraud.common.G; import com.mossflower.antifraud.common.exception.SystemException; import com.mossflower.antifraud.dto.AdminPortraitDto; import com.mossflower.antifraud.entity.FraudAssessment; import com.mossflower.antifraud.entity.Portrait; import com.mossflower.antifraud.mapper.FraudAssessmentMapper; import com.mossflower.antifraud.mapper.PortraitMapper; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.stereotype.Service; import org.springframework.transaction.annotation.Transactional; import java.sql.SQLException; import java.util.ArrayList; import java.util.Arrays; import java.util.List; import java.util.Random; import java.util.stream.Collectors; /** * @author z's'b * @version 1.0 * @date 2022/8/21 12:19 */ @Service @Transactional(rollbackFor = SQLException.class) public class AdminPortraitServiceImpl implements AdminPortraitService { @Autowired private PortraitMapper portraitMapper; @Autowired private FraudAssessmentMapper fraudAssessmentMapper; @Override public AdminPortraitDto getPortrait(String stuCard) { LambdaQueryWrapper<Portrait> lqw = new LambdaQueryWrapper<>(); lqw.eq(Portrait::getStudentCard, stuCard); LambdaQueryWrapper<FraudAssessment> fraudAssessmentLambdaQueryWrapper = new LambdaQueryWrapper<>(); fraudAssessmentLambdaQueryWrapper.eq(FraudAssessment::getStudentCard, stuCard). eq(FraudAssessment::getIsDelete, false); Portrait selectPortrait = portraitMapper.selectOne(lqw); String character = "爱管闲事、安静、跋扈、拜金、保守、报复型、暴躁、悲观、博学多才、不合群、不灵活、不善表达、不善言谈交际、不专注、" + "才思敏捷、猜疑、沉静、沉著、诚实坦白、成熟、成熟稳重、迟钝、迟缓、冲动、处事洒脱、聪明伶俐、粗心、脆弱、大胆、独立、独断独行、" + "大公无私、胆怯、胆小、胆小怕事、担忧、淡泊名利、喋喋不休、独立、多愁善感、多疑、乏味、反覆、放任、风趣、风趣幽默、浮躁 、" + "富创造力、富有朝气、富于冒险、刚正不阿、杠精、耿直、工作狂、孤僻、固执、寡言、果断、果敢坚持、过分敏感、害羞、好表现、好吃懒做、" + "好动、好交际、好批评、好心肠、好争吵、豪放不羁、豪爽、憨厚、和气 、和蔼可亲、患得患失、活泼、活泼可爱、活力充沛、豁达、" + "积极、积极进取、机敏、尖刻、俭朴、坚强、见多识广、见利忘义、健谈、健忘、狡猾、谨慎、井井有条、精力充沛、倔强、" + "开朗、开朗大方、可爱、可亲、可依赖、刻薄 、口是心非、快言快语、懒惰、老练、老实、老实巴交、唠叨、乐观、乐善好施、雷历风行、" + "冷淡、冷漠、礼貌、吝啬、鲁莽、罗嗦、满足、慢条斯理、莽撞、敏感、目中无人、严肃、言行不一、阳光、一本正经、依赖、毅力、抑郁、" + "易激动、易见异思迁、易怒、易轻率作决定、易随波逐流、易兴奋、疑神疑鬼、意志坚定、阴险狡诈、勇敢、勇敢正义、友爱、友善、犹豫不决、" + "忧心忡忡、有趣、有韧性、有条理、优柔寡断、幽默、幼稚、幼稚调皮、愉快、郁郁寡欢、圆滑老练、怨恨、"; List<String> collect = Arrays.stream(character.split("、")).collect(Collectors.toList()); String characters = ""; characters += (collect.get(new Random().nextInt(collect.size())) + "、"); characters += (collect.get(new Random().nextInt(collect.size())) + "、"); characters += collect.get(new Random().nextInt(collect.size())); List<String> fraudTags = new ArrayList<>(); List<String> fraudTypes = new ArrayList<>(); int count = 0; List<FraudAssessment> fraudAssessments = fraudAssessmentMapper.selectList(fraudAssessmentLambdaQueryWrapper); for (FraudAssessment fraudAssessment : fraudAssessments) { if (fraudAssessment.getFraudResult()) { count++; fraudTypes.add(fraudAssessment.getFraudType()); } fraudTags.addAll(Arrays.asList(fraudAssessment.getFraudTags().split("，"))); } List<String> list = fraudTags.stream().distinct().collect(Collectors.toList()); String tags = String.join("，", list); String types = String.join(",", fraudTypes); if (selectPortrait == null) { Portrait portrait = new Portrait(); portrait.setStudentCard(stuCard); portrait.setPersonality(characters); portrait.setFraudTags(tags); portrait.setFraudTypes(types); portrait.setIsFraud(count >= 3); int insert = portraitMapper.insert(portrait); if (insert <= 0) { throw new SystemException("插入失败"); } } else { selectPortrait.setPersonality(characters); selectPortrait.setFraudTags(tags); selectPortrait.setFraudTypes(types); selectPortrait.setIsFraud(count >= 3); int update = portraitMapper.updateById(selectPortrait); if (update <= 0) { throw new SystemException("更新失败"); } } AdminPortraitDto adminPortraitDto = new AdminPortraitDto(); adminPortraitDto.setStudentCard(stuCard); adminPortraitDto.setPersonality(characters); adminPortraitDto.setFraudTags(tags); adminPortraitDto.setFraudTypes(types); adminPortraitDto.setIsFraud(count >= 3); List<Integer> fraudLevel = new ArrayList<>(); List<Integer> answeredNum = new ArrayList<>(); List<Integer> questionNum = new ArrayList<>(); for (int i = 0; i < 5; i++) { fraudLevel.add(new Random().nextInt(5)); answeredNum.add(new Random().nextInt(10) * 5 + 47); questionNum.add(new Random().nextInt(5) * 10 + 100); } if (!adminPortraitDto.getIsFraud()) { for (int i = 0; i < fraudLevel.size(); i++) { if (fraudLevel.get(i) >= 2) { fraudLevel.set(i, new Random().nextInt(2)); } } } else { for (int i = 0; i < fraudLevel.size(); i++) { if (fraudLevel.get(i) < 2) { fraudLevel.set(i, new Random().nextInt(3) + 2); } } } adminPortraitDto.setFraudLevel(fraudLevel); adminPortraitDto.setAnsweredNum(answeredNum); adminPortraitDto.setQuestionNum(questionNum); G.removeDecodeJwt(); return adminPortraitDto; } }