About the Album:

• Wikipedia/Discogs Page Link)
• YouTube Link
• Group Members: One Be Lo, Senim Silla
• Release Date: October 31, 2000
• Region: Pontiac, Michigan
• Number of Tracks: 24

Track Listing:

1. Reality Check
2. Conquistadors
3. Solar Powered (Intro)
4. Solar Powered
5. Slang Blade (Intro)
6. Slang Blade
7. The Binary Shuffle (Intro)
8. The Binary Shuffle
9. Fellowship (feat. Athletic Mic League, Decompoze)
10. New Hip Hop
11. Masters Of The Universe
12. Indy 500
13. The Evolution Of Man (feat. Brenda J)
14. I Know Why The Caged Bird Sings Part 1
15. I Know Why The Caged Bird Sings Part 2
16. Honest Expression
17. Honest Expression (Outro)
18. Glen Close
19. Wolf Man Jack (Intro)
20. Wolf Man Jack
21. One Man Army
22. K.G.B. (Intro)
23. K.G.B. (feat. Elzhi, J.U.I.C.E., Lacks, Maliki, O Type Star, Texture)
24. Outro

Question Section:

• Level 101: Basic/Main Questions
• Level 201: Intermediate
• Level 301: Advanced
• Level 401: Expert

101 Level Review Questions & Prompts (Basic):

1. Share your thoughts on the album. What did you like or dislike about it?
2. What are your favorite tracks from the album, and why? Feel free to score each track on a scale from 1 to 10. You could also give a more detailed review of each one.
3. Do you think this album brings something original or unique to hip hop? Describe what it is.

201 Level Discussion Questions (Intermediate):

1. What emotions or feelings does the album evoke for you?
   
2. What do you think about the production? How does it compare to other producers?
   
3. What are some lyrics or wordplay from the album that you have never heard before?
   
4. Any criticisms or aspects you think could have been improved?
   

301 Level Discussion Questions (Advanced):

1. What other albums from that era are comparable to this one? Are there other albums/songs that sound completely or almost completely similar?
   
2. How has your perception of the album evolved with repeated listens?
   
3. How does the album sound as a cohesive project? Does each track flow nicely from one to the next? Would you rearrange the track list? How so?
   
4. What societal, political, or other issues does this album address, if any?
   

401 Level Discussion Questions (Expert):

1. How would you describe the sub-genre of the album? What themes or vibes does it have?
   
2. How does the album's artwork and other packaging contribute to the overall experience?
   
3. Has this album influenced later artists or hip hop's history at large, if at all?
   
4. What is the local legacy of this album where it was released? How did it influence the culture there?
   

• Season 3, Episode 5

• Duke voiced by Clifford Chapin
• Alice voiced by Kristen McGuire
• Rob voiced by Kent Williams
• Viola voiced by Kayli Mills
• Cuff voiced by Sarah Wiedenheft
• Zain voiced by Ricco Fajardo
• Walter voiced by Alan Lee
• Daleth voiced by Katelyn Barr
• Sharon voiced by Felecia Angelle
• Keto voiced by Jad Saxton
• Teto voiced by Morgan Lauré
• Nico voiced by Hayden Daviau
• Ichi voiced by Monica Rial
• Flea voiced by Ben Phillips
• Millie voiced by Lisette Monique Diaz
• Pheifer voiced by Molly Zhang
• Evelyn voiced by Kelsey Poppen
• Sade voiced by Dawn M. Bennett
• Narrator voiced by Meli Grant

• Voice Director: Jad Saxton
• Producer: Susie Nixon
• Adaptation: Ben Phillips
• Mixer: Matt Grounds *

• What my project does: This transformation is applied to signal processing, analyzing transient changes of a signal during very short-time. Some special use case can be in power system signal, or Geophysical signal analysis, or MRI ...
• Target audience: anyone who is interested in signal processing or power system analysis or geographical analysis.
• Comparison: The comparison with Wavelet Transform has been shown. (which shows more potential in detecting transient changes)

Quick Usage

import numpy as np from hstransform import HSTransform # Create input signal (for example: Voltage signal) t = np.linspace(0, 10, 100) # timeseries V_m = 220*np.sqrt(2) # peak voltage f_V = 50 # frequency phi_V = 0 # phase V_clean = V_m * np.sin(2 * np.pi * f_V * t + phi_V) # Create voltage sag/dip (80% of the nominal voltage for 0.15 second) V_sag = np.where((t >= 2) & (t <= 3.5), 0.5 * V_clean, V_clean) # Create an instance of HSTransform hs = HSTransform() # Perform the transform signal = V_sag S_transformed = hs.fit_transform(t, signal) 

• What my project does: This transformation is applied to signal processing, analyzing transient changes of a signal during very short-time. Some special use case can be in power system signal, or Geophysical signal analysis, or MRI ...
• Target audience: anyone who is interested in signal processing or power system analysis or geographical analysis.
• Comparison: The comparison with Wavelet Transform has been shown. (which shows more potential in detecting transient changes)

Quick Usage

import numpy as np from hstransform import HSTransform # Create input signal (for example: Voltage signal) t = np.linspace(0, 10, 100) # timeseries V_m = 220*np.sqrt(2) # peak voltage f_V = 50 # frequency phi_V = 0 # phase V_clean = V_m * np.sin(2 * np.pi * f_V * t + phi_V) # Create voltage sag/dip (80% of the nominal voltage for 0.15 second) V_sag = np.where((t >= 2) & (t <= 3.5), 0.5 * V_clean, V_clean) # Create an instance of HSTransform hs = HSTransform() # Perform the transform signal = V_sag S_transformed = hs.fit_transform(t, signal) 

• What my project does: This transformation is applied to signal processing, analyzing transient changes of a signal during very short-time. Some special use case can be in power system signal, or Geophysical signal analysis, or MRI ...
• Target audience: anyone who is interested in signal processing or power system analysis or geographical analysis.
• Comparison: The comparison with Wavelet Transform has been shown. (which shows more potential in detecting transient changes)

Quick Usage

import numpy as np from hstransform import HSTransform # Create input signal (for example: Voltage signal) t = np.linspace(0, 10, 100) # timeseries V_m = 220*np.sqrt(2) # peak voltage f_V = 50 # frequency phi_V = 0 # phase V_clean = V_m * np.sin(2 * np.pi * f_V * t + phi_V) # Create voltage sag/dip (80% of the nominal voltage for 0.15 second) V_sag = np.where((t >= 2) & (t <= 3.5), 0.5 * V_clean, V_clean) # Create an instance of HSTransform hs = HSTransform() # Perform the transform signal = V_sag S_transformed = hs.fit_transform(t, signal)