Update app.py

app.py

@@ -9,7 +9,7 @@ import matplotlib.pyplot as plt
 def generate_random_pile(num_points=50, max_height=10.0, noise=0.5):
     """
     Generates a random 'pile shape' with a certain maximum height.
-    We'll shape it as a bell-curve-like mound plus random noise.
+    shape it as a bell-curve-like mound plus random noise.
     
     Args:
         num_points (int): Number of discrete x-points to model the silo cross-section.
@@ -32,7 +32,7 @@ def generate_random_pile(num_points=50, max_height=10.0, noise=0.5):
 def simulate_sensor_readings(x_array, height_array, sensor_type="LiDAR", num_sensors=5):
     """
     Simulates sensor readings from the height array.
-    We randomly pick a few positions along x_array,
+    randomly pick a few positions along x_array,
     then record the height + some noise depending on sensor_type.
     
     Args:
@@ -133,10 +133,9 @@ st.set_page_config(page_title="ITC PSPD - Wood Chip Silo Demo", layout="centered
 st.title("Wood Chip Silo Monitoring - ITC PSPD Demo")
 
 st.markdown("""
-**Welcome to a simple demonstration of ** *Wood-chip silo* height profile Detection and Volume Estimation*.  
-This is an **Industry 4.0** inspired solution to **digitally** track the *height* and *volume*  
-of wood chips in a silo, supporting **paperboard and specialty paper** operations at **ITC PSPD**.
-
+Welcome to a simple demonstration of Wood-chip silo height profile Detection and Volume Estimation*.  
+This is an Industry 4.0 inspired solution to digitally track the height and volume 
+of wood chips in a silo, supporting paperboard and specialty paper operations at ITC PSPD.
 ---
 """)