modify number

Author: oyb98

src/i18n/en-US/index.js

@@ -69,9 +69,9 @@ export default {
   l14_tag: "",
   l14_desc: "",
 
-  ls1_1: "1.1 Time Series Forecasting",
-  ls1_2: "1.2 Time Series Anomaly Detection",
-  ls1_3: "1.3 Time Series Classification",
+  ls1_1: "Time Series Forecasting",
+  ls1_2: "Time Series Anomaly Detection",
+  ls1_3: "Time Series Classification",
   lst1_1_1: "Time-frequency domain based forecasting:",
   lst1_1_2: "Model-agnostic plugin:",
   lst1_1_3: "Automated correlated time series forecasting:",
@@ -90,10 +90,10 @@ export default {
   lst1_2_5: "Explainable outlier detection: ",
   lst1_2_6: "Ensemble learning based outlier detection：",
 
-  ls4_1: "2.1 Traffic State Estimation",
-  ls4_2: "2.2 Preference Identification",
-  ls4_3: "2.3 Data-Driven Navigation Decision-Making",
-  ls4_4: "2.4 Others",
+  ls4_1: "Traffic State Estimation",
+  ls4_2: "Preference Identification",
+  ls4_3: "Data-Driven Navigation Decision-Making",
+  ls4_4: "Others",
   lst4_1_1: "Route Traffic State:",
   lst4_1_2: "Road Network Traffic State:",
   lst4_3_1: "Decision-Making Under Uncertainty:",
@@ -102,10 +102,10 @@ export default {
   lst4_3_4: "Top-K Decision-Making:",
   lst4_3_5: "Eco-routing:",
 
-  ls7_1: "3.1 Path Representation Learning",
-  ls7_2: "3.2 Graph Attribute Prediction",
-  ls7_3: "3.3 Spatiotemporal Sequence Correlation Learning",
-  ls7_4: "3.4 Shortest Path Algorithm for Uncertain Graphs",
+  ls7_1: "Path Representation Learning",
+  ls7_2: "Graph Attribute Prediction",
+  ls7_3: "Spatiotemporal Sequence Correlation Learning",
+  ls7_4: "Shortest Path Algorithm for Uncertain Graphs",
 
   lst6_4_1: "Time Series Forecasting：",
   lst6_4_2: "Graph-Based Prediction：",

src/i18n/zh-CN/index.js

@@ -66,9 +66,9 @@ export default {
   l10_tag: "",
   l10_desc: "迁移学习与模型泛化性",
 
-  ls1_1: "1.1 时间序列预测",
-  ls1_2: "1.2 时序异常检测",
-  ls1_3: "1.3 时序分类",
+  ls1_1: "时间序列预测",
+  ls1_2: "时序异常检测",
+  ls1_3: "时序分类",
   lst1_1_1: "Time-frequency domain based forecasting:",
   lst1_1_2: "Model-agnostic plugin:",
   lst1_1_3: "Automated correlated time series forecasting:",
@@ -87,10 +87,10 @@ export default {
   lst1_2_5: "Explainable outlier detection: ",
   lst1_2_6: "Ensemble learning based outlier detection：",
 
-  ls4_1: "2.1 交通状态预估",
-  ls4_2: "2.2 偏好识别",
-  ls4_3: "2.3 数据驱动的导航决策",
-  ls4_4: "2.4 其他",
+  ls4_1: "交通状态预估",
+  ls4_2: "偏好识别",
+  ls4_3: "数据驱动的导航决策",
+  ls4_4: "其他",
   lst4_1_1: "路径交通状态:",
   lst4_1_2: "路网交通状态:",
   lst4_3_1: "不确定性下的决策:",
@@ -99,10 +99,10 @@ export default {
   lst4_3_4: "Top-K 决策:",
   lst4_3_5: "Eco-routing:",
 
-  ls7_1: "3.1 路径表征学习",
-  ls7_2: "3.2 图属性预测",
-  ls7_3: "3.3 时空序列关联性学习",
-  ls7_4: "3.4 不确定性图的最短路径算法",
+  ls7_1: "路径表征学习",
+  ls7_2: "图属性预测",
+  ls7_3: "时空序列关联性学习",
+  ls7_4: "不确定性图的最短路径算法",
 
   lst6_4_1: "时间序列预测：",
   lst6_4_2: "基于图预测：",

src/pages/PageDetail.vue

@@ -4,7 +4,8 @@
     <div v-if="data" class="md:tw-w-2/3 md:tw-m-auto">
       <div>
         <div class="tw-text-2xl tw-mt-10 tw-leading-10 tw-p-4 tw-my-4 tw-bg-gray-50 tw-border-l-4 tw-border-gray-300">
-          <span>{{ data.id }}. </span> {{ $t(data.section) }}
+          <!-- <span>{{ data.id }}. </span>  -->
+          {{ $t(data.section) }}
         </div>
 
         <p class="tw-m-5">