Delaram Yazdansepas

Schedule

Fri, 02 Jan 2026 00:00:00 +0000

Readings Key

TP = Think Python by Allen B. Downey (Required Texts)
AB = Automate the Boring Stuff with Python (Optional Text)

Schedule

Note, the schedule of lectures is subject to change to accommodate guest speakers, catch up on materials, etc. Revisions will be posted on the course Website.

CMSI 1010 – Spring 2026 Course Schedule

Note: Schedule subject to change. Updates will be posted on the course site.

Readings Key:
TP = Think Python by Allen B. Downey (Required)
AB = Automate the Boring Stuff with Python (Optional)

Class #	Date	Topic	Reading	Labs	Due Dates
0	Tue 01/13	Introductions & Welcome		Lab 0
1	Thu 01/15	A Bit of History	TP: Ch 1		Lab 0
2	Tue 01/20	Python Variables and Syntax	TP: Ch 2
3	Thu 01/22	Conditional Statements	TP: Ch 5.4–5.7, 5.11
4	Tue 01/27	Functions	TP: Ch 3, 6.1–6.3	Lab 1	Labs 1&2, ps0
5	Thu 01/29	Boolean Logic, Operators & Types	TP: Ch 5.1–5.3, 6.4	Lab 2
6	Tue 02/03	Loops	TP: Ch 7	Lab 3	Labs 3&4, ps1
7	Thu 02/05	Strings	TP: Ch 8	Lab 4
8	Tue 02/10	Lists	TP: Ch 10	Lab 5	Labs 5&6
9	Thu 02/12	Dictionaries	TP: Ch 11	Lab 6	ps2
10	Tue 02/17	Exam 1 Review	TP: Ch 12	Lab 7	Labs 7&8
11	Thu 02/19	Exam 1 Review		Lab 8
12	Tue 02/24	Exam 1
13	Thu 02/26	Git and Terminal Commands			Lab 9, ps3
–	Tue 03/03	No Class – Spring Break
–	Thu 03/05	No Class – Spring Break
14	Tue 03/10	Recursion	TP: Ch 5.8–5.10, 6.5–6.9	Lab 9
15	Thu 03/12	Turtles and Fractals	TP: Ch 4	Lab 10	ps4
16	Tue 03/17	Objects & Classes	TP: Ch 15	Lab 11	Labs 10&11
17	Thu 03/19	Inheritance	TP: Ch 16	Lab 12	ps5
18	Tue 03/24	Exam 2 Review	TP: Ch 18	Lab 13	Labs 12&13
19	Thu 03/26	Exam 2
–	Tue 03/31	No Class – Cesar Chavez Day
–	Thu 04/02	No Class – Easter Holidays
20	Tue 04/07	Introduce Projects		Lab 14
21	Thu 04/09	Pygame	( https://bit.ly/3OtOE5x)	Lab 15	Lab 14, ps6
22	Tue 04/14	Data Science Intro	( https://bit.ly/34sVEdw)	Lab 16
23	Thu 04/16	GitHub with Teams			proposal
24	Tue 04/21	Unit Tests & Debugging
25	Thu 04/23	Project Work Session			milestone
26	Tue 04/28	Project Work Session			Labs 15&16
27	Thu 04/30	Labs Check-in & Final Wrap-up
28	Tue 05/05	Project Presentations			presentation
–	Tue 05/12	Final Project Due			📥 Due at 11:59

Papers

Wed, 03 Jan 2024 00:00:00 +0000

Paper Presentation Guidelines

Overview

Each student will present one academic paper to the class. This presentation will serve as an opportunity to deeply engage with current research in ubiquitous computing and develop critical analysis skills.

Presentation Format

Presentation Length: 20 minutes
Discussion Period: 10 minutes
Total Time: 30 minutes per presentation

Paper Selection

Students can choose from two options:

Select a paper from the provided reading list below
Choose their own paper from top-tier venues such as:
- UbiComp
- UIST
- CCS
- PerCom
- SIGCHI
- IEEE Pervasive Computing (Magazine)
- Personal and Ubiquitous Computing (Journal)

If selecting your own paper, ensure it aligns with the course themes and comes from a reputable academic venue. All paper selections should be approved by the instructor.

Presentation Requirements

As the “paper expert,” you are expected to:

Read the paper thoroughly
Prepare clear and engaging slides
Lead the class discussion
Answer questions about the paper’s content
Facilitate meaningful dialogue about the paper’s implications

Presentation and Discussion Facilitation Guidelines

Your presentation should address key aspects of the paper and generate thoughtful discussion. Consider these questions while preparing your presentation and facilittation of the class discussion:

Critical Analysis Points

How well is the work motivated?
What real-world impact could this research have?
Are the methods and approaches sound?
How does this work relate to and build upon prior research?
Are the experiments well-designed and executed?
What are the main research questions being addressed?
How well-supported are the paper’s claims?
What assumptions underlie the work?
How generalizable are the findings?
What questions remain unanswered?

Important Dates

Presentations will begin Mid Feb
Sign up Sheet on Brightspace

Questions?

If you have any questions about paper selection or presentation requirements, please ask.

Project

Wed, 03 Jan 2024 00:00:00 +0000

🚀 Project Structure

The semester-long project is your opportunity to design and implement a significant ubiquitous computing system. Working in teams of 3 students, you’ll develop a solution that demonstrates practical application of course concepts.

Project Categories

Teams may choose one of the following approaches:

Functional Prototype: Develop a working ubiquitous computing system that implements context-awareness, seamless interaction, and real-world sensing.
Design Innovation: Create a comprehensive technical exploration of a novel ubiquitous computing concept, including detailed specifications and interaction models.
Critical Analysis System: Develop a system that examines existing ubiquitous computing paradigms, proposing innovative solutions while considering ethical implications.

Project Milestones

Proposal and Requirements (Week 4)
- Problem statement and motivation
- User requirements and scenarios
- Technical feasibility analysis
- Initial architecture proposal
Design and Architecture (Week 8)
- System architecture
- Interface design
- Technical specifications
- Initial prototype
Implementation and Testing (Week 12)
- Working prototype
- Test results
- User feedback
- Implementation challenges and solutions
Final Delivery (Week 16)
- Complete working system
- Comprehensive documentation
- Final presentation
- Project reflection

Milestone Deliverables

Each milestone includes:

Written documentation
In-class demonstration
Peer feedback session

Evaluation Criteria

Projects will be assessed on:

Technical innovation (25%)
Design thinking (25%)
Integration of course concepts (25%)
Documentation quality (25%)

Schedule

Wed, 03 Jan 2024 00:00:00 +0000

📅 Weekly Schedule

Week 1-2: Foundations and Vision

Introduction to ubiquitous computing principles, Weiser’s vision, calm technology, and invisible interfaces. Course overview and team formation.

Project: Team formation and ideation begins

Week 3-4: Context-Aware Computing

Core principles of context, sensing strategies, and designing context-aware applications.

Assignment 1: Context Analysis
Project Milestone 1: Initial Concept Presentations

Week 5-6: Distributed and Mobile Systems

System architectures, mobile computing paradigms, and implementation strategies.

Paper Presentations Begin
Assignment 2: Distributed System Design

Week 7-8: Sensing and Human Activity

Environmental sensing, data analytics, and human behavior recognition.

Project Milestone 2: Design Documentation
Assignment 2 Due

Week 9-10: Location and Natural Interfaces

Spatial computing, location services, and ambient interaction design.

Assignment 3: Sensor Data Processing

Week 11-12: Wearables and Smart Spaces

Wearable computing design, smart environments, and infrastructure sensing.

Project Milestone 3: Implementation Progress
Assignment 3 Due

Week 13-14: Critical Considerations

Privacy, security, ethics, and sustainability in ubiquitous systems.

Assignment 4: Privacy and Security Analysis
Project Implementation Completion

Week 15-16: Integration and Future

System evaluation, emerging trends, and final presentations.

Final Project Documentation Workshop
Final Project Presentations

Important Notes

Paper presentations run from Week 5 through Week 14
Assignment deadlines may be adjusted based on class progress
Project milestones include documentation and demonstrations
Guest speakers will be scheduled throughout the semester
Weekly readings will be posted on the course website

Schedule

Sun, 08 Jan 2023 00:00:00 +0000

Topics and Schedule

Note, the schedule of lectures is subject to change to accommodate guest speakers. Revisions will be posted on the course Website.

#	Date	Topic	Presenter
1	08/29	Welcome and overview of LMU Computer Science (LMUCS). Slack signup. Pointer to Student Guide. Key people. Curriculum overview.	–
2	09/05	First Year Advising Committee (FYAC). Academic Honesty. Generative AI Use. In-depth Slack activity themed around ACM Tech News. Students will learn Slack threads and tagging	Dr. Forney
3	09/12	Highlights of the book “So Good They Can’t Ignore You” by Cal Newport	Dr. Jordan Freitas
4	09/19	Grace Hopper and her contributions to languages and compilers. The GHC. Slack activity: share bio, fun facts, and pictures of Grace Murray Hopper.	–
5	09/26	3-D UFO code-a-long	Dr. Toal
6	10/03	Combination of networking with example and MSCS/4 + 1 grad program	Dr. Johnson
7	10/10	Muddy City (Minimum Spanning Tree Problem). Slack activity: post your solutions as pictures, also with a text description of the algorithm you discovered.	Dr. Dionisio
8	10/17	Tourist Town (NP Completeness)	Dr. Dionisio
9	10/24	Computing and Computer Science landscape. Fixed and Growth Mindsets. Related disciplines and careers. Slack activity: non-traditional careers in CS
10	10/31	The department-wide Faculty Lightning Talks will take place at the regular class time. Attendance is required (Checkin on slack). Keck-O-Ween party follows the talk.	–
11	11/07	Introduction and research (AI, NLP, Spoken Dialog Systems)	Dr. Korpusik
12	11/14	Introduction and research, with a presentation on PsycholgAI and opportunities for research in our Applied Cognitive Technologies Lab.	Dr. Forney
13	11/21	TBA
14	11/28	Grad School Opportunities. Industry Careers	–
15	12/05	Great Names in CS presentations	–

Schedule

Sat, 23 Jul 2022 00:00:00 +0000

🗓 Schedule

Note, the schedule of lectures is subject to change to accommodate catching up on materials and etc. Revisions will be posted on the course Website.

Date	Topic	Assignments
Week of Aug 29 to Sep 2	Propositional Logic
Week of Sep 5 to 9	Propositional Logic	A1 out
Week of Sep 12 to 16	Predicate Logic	A1 due, A2 out
Week of Sep 19 to 23	Rules of Inference, Proofs, and Proof Strategies.	A2 due
Week of Sep 26 to 30	Sets, Relations, Exam 1	A3 out
Week of Oct 3 to 7	Relations and Functions	A3 due, A4 out
Week of Oct 10 to 14	Sequences, and Summations, Cardinality of Sets	A4 due
Week of Oct 17 to 21	Number Theory	A5 out
Week of Oct 24 to 28	Mathematical Induction	A5 due
Week of Oct 31 to Nov 4	Mathematical Induction, Exam 2	A6 out
Week of Nov 7 to 11	Mathematical Induction	A6 due
Week of Nov 14 to 18	Counting and Pigeonhole Principle	A7 out
Week of Nov 21 to 25	Permutations and Combinations - Thanksgiving Holidays	A7 due
Week of Nov 28 to Dec 2	Graph Theory	A8 out
Week of Dec 5 to 9	Graph Theory	A8 due
Dec 15th @ 8 am	Final Examination

Schedule

Sat, 28 Aug 2021 00:00:00 +0100

Readings Key

100 = 100 Things Every Designer Should Know (Required Text) ED = Emotional Design (Required Texts)
DM = Designing with the Mind in Mind (Optional Text)

Schedule

Note, the schedule of lectures is subject to change to accommodate guest speakers, catch up on materials, etc. Revisions will be posted on the course Website.

#	Date	Topic	Reading	Due	Additional Notes
1	8/31	Introductions & Welcome
2	9/2	Stakeholder Analysis/Ice breaker	Effective Self-Managed Teams
3	9/7	Requirements Gathering	Personas – A Simple Introduction
4	9/9	Requirements Gathering	Conducting Task Analysis	P0
5	9/14	Human Abilities (S & P)	100: Chapters 1-18
6	9/16	Human Abilities (S & P)	100: Chapters 19-36	HW1
7	9/21	Human Abilities (A & M)	100: Chapters 37-49
8	9/23	Human Abilities (A & M)
9	9/28	Guest Lecture: Cognitive Neuroscience
10	9/30	Studio Session 1		P1
11	10/5	Information Processing	Card et. al paper
12	10/7	Information Processing
13	10/12	Information Visualization	Tufte papers
14	10/14	Prototyping		HW2
15	10/19	Visual Design Strategies
16	10/21	Visual Design Strategies	IKEA	P2
17	10/26	Studio Session 2
18	10/28	Gestalt Principles
19	11/2	DOET I	DOET
20	11/4	DOET II	DOET
21	11/9	User Experience (Emotional Design)	ED
22	11/11	Prototyping Software		HW3
23	11/16	Evaluation I (Usability Evals)	Barnum I
24	11/18	Studio Session 3		P3
25	11/23	Evaluation II (Heuristic Evals)	Barnum II
	11/25	Thanksgiving Break - No Class
26	11/30	Mobile & International UIs	Nielsen
27	12/2	No UIs & Natural UIs		HW4
28	12/7	TBA
29	12/9	Wrap-up		P4
	12/16	Final Presentations		Video	Thurs, Dec. 16

Schedule

Fri, 01 Jan 2021 00:00:00 +0000

Readings Key

CP = Composing Programs by John DeNero (Required Text)
TP = Think Python by Allen B. Downey (Required Texts)
AB = Automate the Boring Stuff with Python (Optional Text)

Schedule

Note, the schedule of lectures is subject to change to accommodate guest speakers, catch up on materials, etc. Revisions will be posted on the course Website.

#	Date	Topic	Reading	Assignments
0	1/12	Introductions & Welcome
1	1/14	Introducing Python	CP 1.1, 1.2	A1 Released
2	1/19	Python Variables and Syntax	TP 2
3	1/21	Data Structures I	AB 4, TP 10	A2 Released
4	1/26	Data Structures II	TP 7,	A1 Due
5	1/28	Loops and Lists Exercises
6	2/02	Conditional Statements	CP 1.5.4, TP 5.1-5.7	A3 Released
7	2/04	Exceptions and types of errors	CAB 2	A2 Due
8	2/09	Functions I	CP 1.3, TP 3.1-3.8
9	2/11	Functions II	AB 3	A4 Released
10	2/16	Recursions	CP 1.7	A3 Due
11	2/18	Funtions and Recursions Exercises
12	2/23	Review Day		A4 Due
13	2/25	Test 1		A5 Released
	3/02	Spring Break - No Class
	3/04	Spring Break - No Class
14	3/09	Reading and Writing Files	TP 14.1-14.5 , AB 9	A6 Released
15	3/11	String Manipulation	TP 8 , AB 6	A5 Due
16	3/16	Vectorized Programming
17	3/18	Array Indexing, Slicing, and Broadcasting		A7 Released
18	3/23	Object-Oriented Programming (OOP)	TP 15, CP 2.5	A6 Due
19	3/25	Implementing Classes & Objects
20	3/30	Inheritance	TP 18	A7 Due
	4/01	Easter Holidays - No Class
21	4/06	Review Day
22	4/08	Test 2		A8 Released
23	4/13	Python and Data Science
24	4/15	Data Exploration and Visualization		A9 Released
25	4/20	Natural Language Processing		A8 Due
26	4/22	TBA
27	4/27	TBA		A9 Due
28	4/29	Final Review

Assignment 1

Tue, 25 Aug 2020 00:00:00 +0100

PURPOSE

This homework assignment is designed to give you experience in gathering and developing design requirements. You will apply concepts and techniques discussed during lecture.

TASK

CRITERIA

SUBMISSION INSTRUCTIONS

Create one PDF file including the reports, graphs and sketches and upload to the assignment dropbox on Brightspace. Make sure your name is in the top-right part of the first page. Narrative text must be typed, but sketches can be hand-drawn.

LATE POLICY

Your assignment is due on Friday, Aug 18th, 2020 at 11:59 pm. There is a 15% point reduction (off of the original assignment’s value) for each 24-hour period the assignment is late for up to four days.

Schedule

Sun, 05 May 2019 00:00:00 +0100

Readings Key

100 = 100 Things Every Designer Should Know (Required Text) ED = Emotional Design (Required Texts)
DM = Designing with the Mind in Mind (Optional Text)

Schedule

Note, the schedule of lectures is subject to change to accommodate guest speakers, catch up on materials, etc. Revisions will be posted on the course Website.

#	Date	Topic	Reading	Due	Additional Notes
1	9/1	Introductions & Welcome
2	9/3	Stakeholder Analysis/Ice breaker	Effective Self-Managed Teams
3	9/8	Requirements Gathering	Personas – A Simple Introduction
4	9/10	Requirements Gathering	Conducting Task Analysis	P0
5	9/15	Human Abilities (S & P)	100: Chapters 1-18
6	9/17	Human Abilities (S & P)	100: Chapters 19-36	HW1
7	9/22	Human Abilities (A & M)	100: Chapters 37-49
8	9/24	Human Abilities (A & M)
9	9/29	Studio Session 1		P1
10	10/1	Guest Lecture: Cognitive Neuroscience
11	10/6	Information Processing	Card et. al paper
12	10/8	Information Processing
13	10/13	Information Visualization	Tufte papers
14	10/15	Prototyping		HW2
15	10/20	Visual Design Strategies
16	10/22	Visual Design Strategies	IKEA
17	10/27	Studio Session 2		P2
18	10/29	Gestalt Principles
19	11/3	DOET I	DOET
20	11/5	DOET II	DOET
21	11/10	User Experience (Emotional Design)	ED
22	11/12	Prototyping Software		HW3
23	11/17	Evaluation I (Usability Evals)	Barnum I (eLC)
24	11/19	Evaluation II (Heuristic Evals)	Barnum II (eLC)
25	11/24	Studio Session 3		P3
26	11/26	International UIs	Nielsen
	11/28	Thanksgiving Break - No Class
27	12/1	Mobile UIs	Nielsen	HW4
28	12/3	No UIs & Natural UIs
30	12/8	TBA		P4
31	12/10	Wrap-up
	12/17	Final Presentations		Video	Thurs, Dec. 17

Assignment 2

Tue, 25 Aug 2020 00:00:00 +0100

PURPOSE

TASK

CRITERIA

SUBMISSION INSTRUCTIONS

LATE POLICY

Your assignment is due on Friday, Oct 16th, 2020 at 11:59 pm. There is a 15% point reduction (off of the original assignment’s value) for each 24-hour period the assignment is late for up to four days.

Assignment 3

Tue, 25 Aug 2020 00:00:00 +0100

PURPOSE

TASK

CRITERIA

SUBMISSION INSTRUCTIONS

LATE POLICY

Your assignment is due on Friday, November 13th, 2020 at 11:59 pm. There is a 15% point reduction (off of the original assignment’s value) for each 24-hour period the assignment is late for up to four days.

Assignment 4

Tue, 25 Aug 2020 00:00:00 +0100

PURPOSE

TASK

CRITERIA

SUBMISSION INSTRUCTIONS

LATE POLICY

Your assignment is due on Tuesday, December 1st, 2020 at 11:59 pm. There is a 15% point reduction (off of the original assignment’s value) for each 24-hour period the assignment is late for up to four days.

Milestone 1- Understanding the Problem

Tue, 25 Aug 2020 00:00:00 +0100

Milestone 2- Design Alternatives

Tue, 25 Aug 2020 00:00:00 +0100

OBJECTIVE:

TASK:

CRITERIA:

Milestone 3- Prototype & Evaluation Plan

Tue, 25 Aug 2020 00:00:00 +0100

OBJECTIVE

TASK

CRITERIA

Milestone 4- Evaluation

Tue, 25 Aug 2020 00:00:00 +0100

OBJECTIVE:

TASK:

CRITERIA:

Example Talk

Sat, 01 Jun 2030 13:00:00 +0000

Click on the Slides button above to view the built-in slides feature.

Slides can be added in a few ways:

Create slides using Academic’s Slides feature and link using slides parameter in the front matter of the talk file
Upload an existing slide deck to static/ and link using url_slides parameter in the front matter of the talk file
Embed your slides (e.g. Google Slides) or presentation video on this page using shortcodes.

Further talk details can easily be added to this page using Markdown and $\rm \LaTeX$ math code.

Soft-Label MET Estimation: Uncertainty-Aware Energy Expenditure from Wrist-worn Accelerometers

Fri, 10 Jul 2026 00:00:00 +0000

A Smart Phone App to Improve Intuitive Eating and Diet Quality: Design and Usability Study

Tue, 16 Jun 2026 00:00:00 +0000

Accelerometer-Based Activity Recognition to Support Calorie-Free Feedback in an Intuitive Eating Mobile Platform

Sun, 01 Feb 2026 00:00:00 +0000

Accelerometer-Based MET Estimation for Wearable Energy Expenditure Monitoring

Sun, 01 Feb 2026 00:00:00 +0000

Real-Time Human Activity Classification Using Gait Cycle Averaging and Biometric Heuristics

Wed, 20 Dec 2023 00:00:00 +0000

Geometric Gait Clustering for Unobtrusive Analysis

Sun, 08 Oct 2023 00:00:00 +0000

Improving Student Sentiment of Active Learning in CS

Sat, 01 Aug 2020 00:00:00 +0000

Active Learning in CS2 and Discrete Mathematics

Wed, 01 Jan 2020 00:00:00 +0000

Designing an Interactive Eco-Feedback Environment

Wed, 01 Jan 2020 00:00:00 +0000

How Personalized Feedback Emails Can Enhance Participation Rate in Online Courses

Wed, 01 Jan 2020 00:00:00 +0000

Personalized Feedback Emails: A Case Study on Online Introductory Computer Science Courses

Wed, 01 Jan 2020 00:00:00 +0000

Writing technical content in Academic

Fri, 12 Jul 2019 00:00:00 +0000

Academic is designed to give technical content creators a seamless experience. You can focus on the content and Academic handles the rest.

Highlight your code snippets, take notes on math classes, and draw diagrams from textual representation.

On this page, you’ll find some examples of the types of technical content that can be rendered with Academic.

Examples

Code

Academic supports a Markdown extension for highlighting code syntax. You can enable this feature by toggling the highlight option in your config/_default/params.toml file.

```python
import pandas as pd
data = pd.read_csv("data.csv")
data.head()
```

renders as

import pandas as pd
data = pd.read_csv("data.csv")
data.head()

Math

Academic supports a Markdown extension for $\LaTeX$ math. You can enable this feature by toggling the math option in your config/_default/params.toml file.

To render inline or block math, wrap your LaTeX math with $...$ or $$...$$, respectively.

Example math block:

$$\gamma_{n} = \frac{ 
\left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T 
\left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}
{\left \|\nabla F(\mathbf{x}_{n}) - \nabla F(\mathbf{x}_{n-1}) \right \|^2}$$

renders as

$$\gamma_{n} = \frac{ \left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T \left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}{\left |\nabla F(\mathbf{x}{n}) - \nabla F(\mathbf{x}{n-1}) \right |^2}$$

Example inline math $\nabla F(\mathbf{x}_{n})$ renders as $\nabla F(\mathbf{x}_{n})$.

Example multi-line math using the \\\\ math linebreak:

$$f(k;p_0^*) = \begin{cases} p_0^* & \text{if }k=1, \\\\
1-p_0^* & \text {if }k=0.\end{cases}$$

renders as

$$f(k;p_0^) = \begin{cases} p_0^ & \text{if }k=1, \\ 1-p_0^* & \text {if }k=0.\end{cases}$$

Diagrams

Academic supports a Markdown extension for diagrams. You can enable this feature by toggling the diagram option in your config/_default/params.toml file or by adding diagram: true to your page front matter.

An example flowchart:

```mermaid
graph TD
A[Hard] -->|Text| B(Round)
B --> C{Decision}
C -->|One| D[Result 1]
C -->|Two| E[Result 2]
```

renders as

graph TD
A[Hard] -->|Text| B(Round)
B --> C{Decision}
C -->|One| D[Result 1]
C -->|Two| E[Result 2]

An example sequence diagram:

```mermaid
sequenceDiagram
Alice->>John: Hello John, how are you?
loop Healthcheck
    John->>John: Fight against hypochondria
end
Note right of John: Rational thoughts!
John-->>Alice: Great!
John->>Bob: How about you?
Bob-->>John: Jolly good!
```

renders as

sequenceDiagram
Alice->>John: Hello John, how are you?
loop Healthcheck
    John->>John: Fight against hypochondria
end
Note right of John: Rational thoughts!
John-->>Alice: Great!
John->>Bob: How about you?
Bob-->>John: Jolly good!

An example Gantt diagram:

```mermaid
gantt
section Section
Completed :done,    des1, 2014-01-06,2014-01-08
Active        :active,  des2, 2014-01-07, 3d
Parallel 1   :         des3, after des1, 1d
Parallel 2   :         des4, after des1, 1d
Parallel 3   :         des5, after des3, 1d
Parallel 4   :         des6, after des4, 1d
```

renders as

gantt
section Section
Completed :done,    des1, 2014-01-06,2014-01-08
Active        :active,  des2, 2014-01-07, 3d
Parallel 1   :         des3, after des1, 1d
Parallel 2   :         des4, after des1, 1d
Parallel 3   :         des5, after des3, 1d
Parallel 4   :         des6, after des4, 1d

An example class diagram:

```mermaid
classDiagram
Class01 <|-- AveryLongClass : Cool
<<interface>> Class01
Class09 --> C2 : Where am i?
Class09 --* C3
Class09 --|> Class07
Class07 : equals()
Class07 : Object[] elementData
Class01 : size()
Class01 : int chimp
Class01 : int gorilla
class Class10 {
  <<service>>
  int id
  size()
}
```

renders as

classDiagram
Class01 <|-- AveryLongClass : Cool
<<interface>> Class01
Class09 --> C2 : Where am i?
Class09 --* C3
Class09 --|> Class07
Class07 : equals()
Class07 : Object[] elementData
Class01 : size()
Class01 : int chimp
Class01 : int gorilla
class Class10 {
  <<service>>
  int id
  size()
}

An example state diagram:

```mermaid
stateDiagram
[*] --> Still
Still --> [*]
Still --> Moving
Moving --> Still
Moving --> Crash
Crash --> [*]
```

renders as

stateDiagram
[*] --> Still
Still --> [*]
Still --> Moving
Moving --> Still
Moving --> Crash
Crash --> [*]

Todo lists

You can even write your todo lists in Academic too:

- [x] Write math example
- [x] Write diagram example
- [ ] Do something else

renders as

Write math example
Write diagram example
Do something else

Tables

Represent your data in tables:

| First Header  | Second Header |
| ------------- | ------------- |
| Content Cell  | Content Cell  |
| Content Cell  | Content Cell  |

renders as

First Header	Second Header
Content Cell	Content Cell
Content Cell	Content Cell

Asides

Academic supports a shortcode for asides, also referred to as notices, hints, or alerts. By wrapping a paragraph in {{% alert note %}} ... {{% /alert %}}, it will render as an aside.

{{% alert note %}}
A Markdown aside is useful for displaying notices, hints, or definitions to your readers.
{{% /alert %}}

renders as

A Markdown aside is useful for displaying notices, hints, or definitions to your readers.

Spoilers

Add a spoiler to a page to reveal text, such as an answer to a question, after a button is clicked.

{{< spoiler text="Click to view the spoiler" >}}
You found me!
{{< /spoiler >}}

renders as

Click to view the spoiler

You found me!

Icons

Academic enables you to use a wide range of icons from Font Awesome and Academicons in addition to emojis.

Here are some examples using the icon shortcode to render icons:

{{< icon name="terminal" pack="fas" >}} Terminal  
{{< icon name="python" pack="fab" >}} Python  
{{< icon name="r-project" pack="fab" >}} R

renders as

Terminal
Python
R

Display Jupyter Notebooks with Academic

Tue, 05 Feb 2019 00:00:00 +0000

from IPython.core.display import Image
Image('https://www.python.org/static/community_logos/python-logo-master-v3-TM-flattened.png')

print("Welcome to Academic!")

Welcome to Academic!

Install Python and JupyterLab

Install Anaconda which includes Python 3 and JupyterLab.

Alternatively, install JupyterLab with pip3 install jupyterlab.

Create or upload a Jupyter notebook

Run the following commands in your Terminal, substituting <MY-WEBSITE-FOLDER> and <SHORT-POST-TITLE> with the file path to your Academic website folder and a short title for your blog post (use hyphens instead of spaces), respectively:

mkdir -p <MY-WEBSITE-FOLDER>/content/post/<SHORT-POST-TITLE>/
cd <MY-WEBSITE-FOLDER>/content/post/<SHORT-POST-TITLE>/
jupyter lab index.ipynb

The jupyter command above will launch the JupyterLab editor, allowing us to add Academic metadata and write the content.

Edit your post metadata

The first cell of your Jupter notebook will contain your post metadata ( front matter).

In Jupter, choose Markdown as the type of the first cell and wrap your Academic metadata in three dashes, indicating that it is YAML front matter:

---
title: My post's title
date: 2019-09-01

# Put any other Academic metadata here...
---

Edit the metadata of your post, using the documentation as a guide to the available options.

To set a featured image, place an image named featured into your post’s folder.

For other tips, such as using math, see the guide on writing content with Academic.

Convert notebook to Markdown

jupyter nbconvert index.ipynb --to markdown --NbConvertApp.output_files_dir=.

Example

This post was created with Jupyter. The orginal files can be found at https://github.com/gcushen/hugo-academic/tree/master/exampleSite/content/post/jupyter

Slides

Tue, 05 Feb 2019 00:00:00 +0000

Create slides in Markdown with Academic

Academic | Documentation

Features

Efficiently write slides in Markdown
3-in-1: Create, Present, and Publish your slides
Supports speaker notes
Mobile friendly slides

Controls

Next: Right Arrow or Space
Previous: Left Arrow
Start: Home
Finish: End
Overview: Esc
Speaker notes: S
Fullscreen: F
Zoom: Alt + Click
PDF Export: E

Code Highlighting

Inline code: variable

Code block:

porridge = "blueberry"
if porridge == "blueberry":
    print("Eating...")

Math

In-line math: $x + y = z$

Block math:

$$ f\left( x \right) = ;\frac{{2\left( {x + 4} \right)\left( {x - 4} \right)}}{{\left( {x + 4} \right)\left( {x + 1} \right)}} $$

Fragments

Make content appear incrementally

{{% fragment %}} One {{% /fragment %}}
{{% fragment %}} **Two** {{% /fragment %}}
{{% fragment %}} Three {{% /fragment %}}

Press Space to play!

One **Two** Three

A fragment can accept two optional parameters:

class: use a custom style (requires definition in custom CSS)
weight: sets the order in which a fragment appears

Speaker Notes

Add speaker notes to your presentation

{{% speaker_note %}}
- Only the speaker can read these notes
- Press `S` key to view
{{% /speaker_note %}}

Press the S key to view the speaker notes!

Themes

black: Black background, white text, blue links (default)
white: White background, black text, blue links
league: Gray background, white text, blue links
beige: Beige background, dark text, brown links
sky: Blue background, thin dark text, blue links

night: Black background, thick white text, orange links
serif: Cappuccino background, gray text, brown links
simple: White background, black text, blue links
solarized: Cream-colored background, dark green text, blue links

Custom Slide

Customize the slide style and background

{{< slide background-image="/media/boards.jpg" >}}
{{< slide background-color="#0000FF" >}}
{{< slide class="my-style" >}}

Custom CSS Example

Let’s make headers navy colored.

Create assets/css/reveal_custom.css with:

.reveal section h1,
.reveal section h2,
.reveal section h3 {
  color: navy;
}

Questions?

Ask

Documentation

University Online Courses: Correlation between Students’ Participation Rate and Academic Performance

Tue, 01 Jan 2019 00:00:00 +0000

Towards Efficient & Real-time Human Activity Recognition using Wearable Sensors: A Shapelet-based Pattern Matching Approach

Mon, 01 Jan 2018 00:00:00 +0000

Statistical Analysis of Window Sizes and Sampling Rates in Human Activity Recognition.

Sun, 01 Jan 2017 00:00:00 +0000

Academic: the website builder for Hugo

Wed, 20 Apr 2016 00:00:00 +0000

Create a free website with Academic using Markdown, Jupyter, or RStudio. Choose a beautiful color theme and build anything with the Page Builder - over 40 widgets, themes, and language packs included!

Check out the latest demo of what you’ll get in less than 10 minutes, or view the showcase of personal, project, and business sites.

👉 Get Started
📚 View the documentation
💬 Ask a question on the forum
👥 Chat with the community
🐦 Twitter: @source_themes @GeorgeCushen #MadeWithAcademic
💡 Request a feature or report a bug
⬆️ Updating? View the Update Guide and Release Notes
❤️ Support development of Academic:
- ☕️ Donate a coffee
- 💵 Become a backer on Patreon
- 🖼️ Decorate your laptop or journal with an Academic sticker
- 👕 Wear the T-shirt
- 👩‍💻 Contribute

Academic is mobile first with a responsive design to ensure that your site looks stunning on every device.

Key features:

Page builder - Create anything with widgets and elements
Edit any type of content - Blog posts, publications, talks, slides, projects, and more!
Create content in Markdown, Jupyter, or RStudio
Plugin System - Fully customizable color and font themes
Display Code and Math - Code highlighting and LaTeX math supported
Integrations - Google Analytics, Disqus commenting, Maps, Contact Forms, and more!
Beautiful Site - Simple and refreshing one page design
Industry-Leading SEO - Help get your website found on search engines and social media
Media Galleries - Display your images and videos with captions in a customizable gallery
Mobile Friendly - Look amazing on every screen with a mobile friendly version of your site
Multi-language - 15+ language packs including English, 中文, and Português
Multi-user - Each author gets their own profile page
Privacy Pack - Assists with GDPR
Stand Out - Bring your site to life with animation, parallax backgrounds, and scroll effects
One-Click Deployment - No servers. No databases. Only files.

Themes

Academic comes with automatic day (light) and night (dark) mode built-in. Alternatively, visitors can choose their preferred mode - click the sun/moon icon in the top right of the Demo to see it in action! Day/night mode can also be disabled by the site admin in params.toml.

Choose a stunning theme and font for your site. Themes are fully customizable.

Ecosystem

Academic Admin: An admin tool to import publications from BibTeX or import assets for an offline site
Academic Scripts: Scripts to help migrate content to new versions of Academic

Install

You can choose from one of the following four methods to install:

Then personalize and deploy your new site.

Updating

View the Update Guide.

Feel free to star the project on Github to help keep track of updates.

License

Released under the MIT license.

A Hierarchical Meta-Classifier for Human Activity Recognition

Fri, 01 Jan 2016 00:00:00 +0000

A Multi-featured Approach for Wearable Sensor-Based Human Activity Recognition

Fri, 01 Jan 2016 00:00:00 +0000

Comparative Study of Verse Similarity for Multi-lingual Representations of the Qur'an

Thu, 01 Jan 2015 00:00:00 +0000

CMSI 1010 Computer Programming and Lab

Mon, 01 Jan 0001 00:00:00 +0000

Course Description

This course presents a variety of topics in computational thinking, problem-solving, small-scale programming, and applications. This includes basic programming constructs such as data, variables, functions, conditionals, loops, lists, files, sets, and dictionaries. It also includes, especially in the latter part of the semester, object-oriented programming and problem-solving. Previous programming experience is neither required nor expected. Students are expected to spend, on average, six to eight hours per week outside of lectures and labs studying course concepts, practicing programming, and working on the programming projects. The course focuses on Python, an interpreted, high-level, and general-purpose programming language. Many class assignments and programming assignments will be assigned throughout the semester. Students will work on the assignments and if needed, class assignments outside of the normal class periods. Course grades will be based on tests, programming assignments, quizzes/in-class work, and attendance.

Required text

Think Python 2nd Edition by Allen B. Downey. http://greenteapress.com/thinkpython2/html/index.html

Recommended text

How to Think Like a Computer Scientist. by Brad Miller et al. Luther College Runestone Interactive Project. https://runestone.academy/runestone/static/thinkcspy/index.html
Automate the Boring Stuff with Python - Practical Programming for Total Beginners by Al Sweigart. https://automatetheboringstuff.com/

Learning Outcomes

By the end of this course you will be able to:

Explain what Computer Science is and why it is important.
Craft well-structured, working programs in the Python 3 programming language.
Correctly use variables, conditionals, loops, lists, objects, and functions.
Develop recursive solutions to problems and draw the stack diagrams.
Design objects and classes for a final project.
Have fun programming!!

CMSI 185 Computer Programming

Mon, 01 Jan 0001 00:00:00 +0000

Course Description

Required text

Composing Programs by John DeNero. http://composingprograms.com/
Think Python 2nd Edition by Allen B. Downey. http://greenteapress.com/thinkpython2/html/index.html

Recommended text

Automate the Boring Stuff with Python - Practical Programming for Total Beginners by Al Sweigart. https://automatetheboringstuff.com/

Learning Outcomes

At the end of this course You will be able to:

Demonstrate proficiency in the purpose and behavior of basic programming constructs.
Organize code into more manageable chunks by developing programs that define and use functions; and develop programs that handle potential errors.
Develop and implement maintainable programs that organize and manipulate data using Python data types like lists and dictionaries.
Write, test, and debug small-scale programs.
Demonstrate an understanding of the wide-spread application of computational thinking to real-world problems.

CMSI 1900 Exploring Computer Science

Mon, 01 Jan 0001 00:00:00 +0000

📜 Course Description

The purpose of this course is to help you develop the skills you need to excel in the Computer Science major and to give you a view of modern Computer Science and possible career paths. One of the main goals of this course is that you develop close relationships with the other students in the class since these are the people with whom you will be completing homework, studying, working on projects, and attending conferences. In addition, you will meet each of the faculty. Most importantly, our goal is for you to feel a sense of belonging as we welcome you into our community. 🤗

🗝 Learning Outcomes

By the end of this course you will be able to:

Get along with with many of the LMU Computer Science community members
Have developed strategies for success in the Computer Science major
Describe various fields of Computer Science and career opportunities
Name several famous computer scientists

🎒 Prerequisites

You should be a computer science major in your first semester of college.

📚 Workload

In accordance with the LMU Credit Hour Policy, this 0-unit course has no specific hourly outside-of-class work or study requirements, though attendance at community and social events may be part of the expectations for the satisfaction of the learning outcomes.

📝 Assignments and Grading

This course is pass/fail based on (1) attendance and participation and (2) completion of a presentation on a famous computer scientist on the last day of class.

In addition, students will be (3) responsible for attending a number of department and college events as a part of your orientation to all things LMU and LMU CS. These events include student organization meetings, college events, and socials. These events will announced on Slack well ahead of time. Also, if you know of an LMU-affiliated meeting taking place, please add the name, date, time and an RSVP to the Slack Channel. You will be rewarded with much respect and appreciation from the teaching staff and your fellow students for your sharing!

💬 Communication

Please check your LMU email at least once a day. All emails to the instructor must come from your LMU email address and must include “CMSI 1900" in the subject line. Please allow 1 business day for the instructor to respond to your email.

🦁 A note on belonging

The field of Computer Science is plagued with stereotypes. If you hear a voice in your head saying, “Ugh, if I’m wrong or if I’m not impressive enough, it will reflect badly on [groups I identify with, especially, but not limited to, race, gender, English as a second language, etc.]!’’ then you might be experiencing a Stereotype Threat. Just know, it’s not just you—many of us have experienced this too. Everyone can do well in this course with a willingness to learn, grow, incorporate feedback, and enjoy.

CMSI 2820 Discrete Mathematics

Mon, 01 Jan 0001 00:00:00 +0000

Course Description

This course presents a survey of the fundamental mathematical tools used in computer science: sets, relations, and functions; propositional and predicate logic; proof writing strategies such as direct, contradiction and induction; number theory, counting; and graph theory with applications in computer science

Students will become familiar with a broad range of mathematical objects like sets, functions, relations, graphs, that are omnipresent in computer science. Perhaps more importantly, they will reach a certain level of mathematical maturity - being able to understand formal statements and their proofs; coming up with rigorous proofs themselves; and coming up with interesting results. This course attempts to be rigorous without being overly formal. This means, for every concept we introduce we will show at least one interesting and non-trivial example and give a full proof. However, we will do so without too much formal notation, employing examples and figures whenever possible. The main topics of this course are

Fundamental concepts of mathematics: Definitions, proofs, sets, functions, relations.
Discrete structures: graphs, modular arithmetic, counting.

The course will focus on a combination of lectures, class discussions and activities. Your course grade will be on written tests, class participation/quizzes and homework assignments.

Learning Outcomes

At the end of this course You will be able to:

Construct basic mathematical arguments using propositional logic, including structures such as quantified statements, normal form constructions, and Boolean algebra constructions.
Carry out set theoretic operations to describe and compare unordered collections.
Be able to select and use an appropriate proof strategy for a potential or known theorem.
Carry out operations on different integer representations, and construct valid arguments for statements related to modular arithmetic.
Construct valid arguments for statements related to counting and combinatorics
Understand the principles of graphs and graph theory and apply them to solve problems

CMSI 370 Interaction Design

Mon, 01 Jan 0001 00:00:00 +0000

Course Description

This course is introduction to human-computer interaction and focuses primarily on user-centered design techniques. It does not presuppose any earlier knowledge of human-computer interaction or psychology; however, students are expected to be proficient in programming. The class covers three broad categories of topics within human-computer interaction:

(a) concepts in human factors, usability, and interface design, and the effects of human capabilities and limitations on interaction with computer systems;
(b) design, development, and evaluation of user interfaces for computer systems; and
(c) current areas of cutting-edge research and development in human-computer interaction.

Required Textbook

Weinschenk, S. 100 Things Every Designer Should Know About People. ISBN-13: 978-0321-7675350
Norman, D. Emotional Design: Why We Love (or hate) Everyday Things. ISBN-13: 978-0465-51366

Learning Outcomes

At the end of this course You Will Be Able To:

Apply the principles of user-centered design, via group projects, in formulating user interface prototypes in novel domains
Gather user design requirements, conduct analysis and communicate findings through written reports and common HCI summations including personas and scenarios.
Analyze and specify tasks to be supported in a UI and generate several UI design alternatives to satisfy user requirements.
Create prototypes using programming or software packages
Develop and implement a testing plan to evaluate the tradeoffs of usability considerations of interface designs

CMSI 3700 Interaction Design

Mon, 01 Jan 0001 00:00:00 +0000

Course Description

(a) concepts in human factors, usability, and interface design, and the effects of human capabilities and limitations on interaction with computer systems;
(b) design, development, and evaluation of user interfaces for computer systems; and
(c) current areas of cutting-edge research and development in human-computer interaction.

Required Textbook

Weinschenk, S. 100 Things Every Designer Should Know About People. ISBN-13: 978-0321-7675350
Norman, D. Emotional Design: Why We Love (or hate) Everyday Things. ISBN-13: 978-0465-51366

Learning Outcomes

At the end of this course You Will Be Able To:

Apply the principles of user-centered design, via group projects, in formulating user interface prototypes in novel domains
Gather user design requirements, conduct analysis and communicate findings through written reports and common HCI summations including personas and scenarios.
Analyze and specify tasks to be supported in a UI and generate several UI design alternatives to satisfy user requirements.
Create prototypes using programming or software packages
Develop and implement a testing plan to evaluate the tradeoffs of usability considerations of interface designs

CMSI 5998 Pervasive Computing Systems

Mon, 01 Jan 0001 00:00:00 +0000

📜 Course Description

Imagine a world where computers are invisible yet everywhere—seamlessly blending into the environment and transforming the way we live, work, and interact. This is the essence of ubiquitous computing, a paradigm that envisions technology so integrated into our surroundings that it “disappears” into the fabric of daily life. Students will learn about the technical foundations of sensing, computing, and system integration, which enable smooth and seamless interactions in a continuous manner. Using these foundations, students will work on practical projects addressing cutting-edge real-world problems, developing innovative solutions through mobile and ubiquitous computing. Along the way, we’ll also explore the history of ubiquitous computing and its evolution, engaging in collaborative research to understand the central challenges and questions driving contemporary theory and practice in this field. Be ready to engage deeply—reading, critical thinking, research, and writing will be integral parts of this course. Your performance will be assessed not only on these elements but also on your capacity to design, develop, and implement systems that embody the core principles of this transformative field.

📚 Recommended text

Krumm, J. (2009). Ubiquitous Computing Fundamentals (1st ed.). Chapman & Hall/CRC. http://www.amazon.com/Ubiquitous-Computing-Fundamentals-John-Krumm/dp/1420093606
While this course does not rely heavily on a single textbook, this book serves as a helpful resource for foundational concepts. Emphasis will be placed on scientific articles, which will be provided through the course website. Additionally, students are encouraged to conduct independent literature research to support their assignments and project work.

🗝 Learning Outcomes

By the end of this course you will be able to:

Apply foundational principles of mobile, ubiquitous, and pervasive computing to design and develop practical, real-world applications.
Evaluate the capabilities and limitations of various components of mobile and ubiquitous systems, enabling informed decisions about system usability, functionality, and potential technical challenges.
Synthesize innovative solutions by integrating sensing technologies, system architecture, and software tools for seamless and context-aware user interactions.
Analyze the history, evolution, and contemporary challenges of ubiquitous computing to understand the theoretical and practical implications for modern applications.
Create functional prototypes that demonstrate the effective use of mobile, pervasive, and wearable computing techniques to address real-world problems.
Critique existing ubiquitous computing systems and applications to identify areas for improvement and opportunities for innovation.
Communicate findings and ideas effectively through research, design documentation, and presentations, demonstrating clear articulation of technical and conceptual insights.

CSCI 1360 Foundations of Informatics

Mon, 01 Jan 0001 00:00:00 +0000

Course Description

Informatics, or “data science,” are rapidly becoming essential skills for scientists across fields; in addition to field-specific specializations, researchers require knowledge of and experience with quantitative analytical techniques for extracting knowledge from raw data. This course aims to provide an introduction to concepts in scientific programming and data science using the Python language. Students are given hands-on opportunities to learn techniques applicable to quantitative analyses across a broad range of fields. These core techniques involve formulating solutions in terms of their inputs and outputs (functional programming), repeated operations (loops), branching operations (conditionals), different methods of organizing data (data structures), how to implement an optimal problem-solving strategy (algorithm design), and methods for visualizing and interpreting results. Course evaluations will be on written tests, class participation and programming assignments.

Learning Outcomes

At the end of this course You Will Be Able To:

Frame scientific experiments in terms of their inputs and outputs.
Formulate algorithms in terms of conditionals, loops, functions, return values, data structures, and existing Python APIs.
Write a program or package to implement automated analysis of data.
Process data of varying types, such as text or images.
Render appropriate visualizations of analysis results, and interpret these visualizations

CSCI 2610 Discrete Mathematics

Mon, 01 Jan 0001 00:00:00 +0000

Course Description

This course presents a survey of the fundamental mathematical tools used in Computer Science: sets, relations, and functions; propositional and predicate logic; proof writing strategies such as direct, contradiction and induction; summations and recurrences; elementary asymptotics and timing analysis; counting and discrete probability with applications in computer science.

Required Textbook

Kenneth H. Rosen Discrete Mathematics and its Applications 7th Edition ISBN-13: 978-0073229720

Learning Outcomes

This course presents a survey of topics in discrete mathematics most relevant to students studying computer engineering. At the end of the semester, all students will be able to do the following:

Construct basic mathematical arguments using propositional logic, including structures such as quantified statements, normal form constructions, and Boolean algebra constructions.
Carry out set theoretic operations to describe and compare unordered collections.
Relate sets to functions; Use functions to describe complexity as well as basic and recursive sequences and progressions.
Be able to select and use an appropriate proof strategy for a potential or known theorem.
Carry out operations on different integer representations, and construct valid arguments for statements related to modular arithmetic.
Construct valid arguments for statements related to counting and discrete probability

Delaram Yazdansepas

Schedule

Readings Key

Schedule

CMSI 1010 – Spring 2026 Course Schedule

Papers

Paper Presentation Guidelines

Overview

Presentation Format

Paper Selection

Presentation Requirements

Presentation and Discussion Facilitation Guidelines

Critical Analysis Points

Suggested Topics and Papers

1. Human-Computer Interaction in Ubiquitous Computing

2. Ubiquitous Data Access

3. Sensing & Actuation

4. Security & Privacy

5. Location & Context Awareness

6. Design Methodologies & Infrastructure

7. Wearable Computing

8. Mobile Health and Wellness Applications

9. Social Computing in Ubiquitous Environments

10. Smart Spaces and Environmental Intelligence

Additional Topics

Important Dates

Questions?

Project

🚀 Project Structure

Project Categories

Project Milestones

Milestone Deliverables

Evaluation Criteria

Schedule

📅 Weekly Schedule

Week 1-2: Foundations and Vision

Week 3-4: Context-Aware Computing

Week 5-6: Distributed and Mobile Systems

Week 7-8: Sensing and Human Activity

Week 9-10: Location and Natural Interfaces

Week 11-12: Wearables and Smart Spaces

Week 13-14: Critical Considerations

Week 15-16: Integration and Future

Important Notes

Schedule

Topics and Schedule

Schedule

🗓 Schedule

Schedule

Readings Key

Schedule

Schedule

Readings Key

Schedule

Assignment 1

PURPOSE

TASK

CRITERIA

SUBMISSION INSTRUCTIONS

LATE POLICY

Schedule

Readings Key

Schedule

Assignment 2

PURPOSE

TASK

CRITERIA

SUBMISSION INSTRUCTIONS

LATE POLICY

Assignment 3

PURPOSE

TASK

CRITERIA

SUBMISSION INSTRUCTIONS

LATE POLICY

Assignment 4

PURPOSE

TASK

CRITERIA

SUBMISSION INSTRUCTIONS